Search is not available for this dataset
article
stringlengths 4.36k
149k
| summary
stringlengths 32
3.35k
| section_headings
listlengths 1
91
| keywords
listlengths 0
141
| year
stringclasses 13
values | title
stringlengths 20
281
|
|---|---|---|---|---|---|
During a primary influenza infection , cytotoxic CD8+ T cells need to infiltrate the infected airways and engage virus-infected epithelial cells . The factors that regulate T cell motility in the infected airway tissue are not well known . To more precisely study T cell infiltration of the airways , we developed an experimental model system using the trachea as a site where live imaging can be performed . CD8+ T cell motility was dynamic with marked changes in motility on different days of the infection . In particular , significant changes in average cell velocity and confinement were evident on days 8–10 during which the T cells abruptly but transiently increase velocity on day 9 . Experiments to distinguish whether infection itself or antigen affect motility revealed that it is antigen , not active infection per se that likely affects these changes as blockade of peptide/MHC resulted in increased velocity . These observations demonstrate that influenza tracheitis provides a robust experimental foundation to study molecular regulation of T cell motility during acute virus infection .
Influenza virus productively infects the epithelial cells that line the upper and lower respiratory tract and is restricted to this site by a requirement for a locally-expressed trypsin-like enzyme that activates the viral hemagglutinin ( HA ) protein . The specific epithelial cell types and location along the respiratory tree are further influenced by the specificity of the viral HA for sialic acid moieties on the surface of the cells [1] . Most seasonal human influenza viruses , for example , recognize alpha-2 , 6 linked sialic acids expressed on cells higher in the respiratory tract [1] . Avian H5 influenza viruses favor alpha-2 , 3 linked sialic acids expressed in birds and on cells lower in the human respiratory tract [2 , 3] . This partially explains the poor transmission of the H5 avian influenzas in humans [2] . Viral replication deep in the lung and alveolar spaces is associated with severe disease and is uncommon in most human infections with seasonal strains of the virus , which are restricted to the trachea , upper airways , and nasopharynx [4–7] . In general , transmission of influenza occurs through the generation of aerosol droplets in the nasopharynx followed by airborne transfer [8] or contact with contaminated surfaces [9 , 10] . It follows that viral replication and immune control in the nasopharynx and proximal trachea are important for influenza epidemics and pandemics . Early characterizations of influenza pathology in humans and in animal models describe an acute tracheitis [5 , 7 , 11] , which is how many clinicians characterize the disease caused by seasonal flu . Yet many contemporary animal models of influenza immunity have focused on events in the lung , blood , or lymphoid organs , with few recent studies of the infection and immune response in the trachea , upper airways , and nasopharynx . During a primary influenza infection , cytotoxic CD8+ T cells ( CTL ) are the main effectors mediating elimination of infected cells [12–14] . The CTL directly engage infected targets through class I MHC-viral peptide complexes expressed on the surface of infected cells [13 , 15 , 16] . Therefore , the CTL must have mechanisms that allow them to enter the epithelium and mediate effector function . However , in spite of the importance of migration into the airways , the spatial locomotive , chemotactic , and adhesion mechanisms that regulate this process are only partially understood . Most studies that have identified molecular cues have inferred the function of these molecules by measuring relative accumulation of cells in the airways ( sampled by lavage ) , or lung tissue ( disrupting the tissue to harvest lymphocytes ) , or by performing conventional microscopic examination of tissue sections after immunostaining to localize T cells . In order to more fully understand cellular immunity to influenza infection , studies of immune cell behavior and regulation in the tissue at the site of infection are needed . For example , using live imaging , we showed that neutrophil-derived CXCL12 is an important molecular cue that guides CD8+ T cells to the infected airways [17] . Many studies of experimental influenza infection and immunity rely on the mouse model , with investigations of cellular immune responses focused on those cells that can be easily obtained by bronchoalveolar lavage ( BAL ) sampling of cells in the airways , and/or mechanical disruption of the lung after dissection . For this reason , much of the literature about immune responses at the site of infection discusses events in the lung . However , with the exception of highly pathogenic influenza viruses , or in cases of immune suppression , influenza infection in humans is clinically characterized as an infectious tracheitis , with involvement of the large conducting airways . Influenza viruses that replicate high in the respiratory tree , including the trachea and nasopharyngeal epithelium , transmit more efficiently [18] , so immune control of infection in the trachea may be more important to limit transmission . Therefore , we developed a mouse model of influenza infection of the trachea using the broncho-tropic H3N2 influenza virus A/Hong Kong/X31 for the study of immune responses [19] . Infection of the trachea is not a new observation , and early ( >40 yrs ago ) descriptions of animal models of influenza mention of the prominence of this site [4 , 7 , 20 , 21] . Furthermore , the trachea offers a relatively easy site to access for the purposes of live imaging , and as we show below , is more uniformly involved than the lung during infection with high specific output of virus . An acute virus infection is dynamic in terms of the kinetics of viral replication , the cellular immune response , and virus clearance [22] . Unlike some models of live imaging of T cell responses that focus on a single time point for reproducibility , the present study interrogates the cells across the entire acute phase of the infection . Experiments were performed to distinguish the presence of infected cells versus persisting antigen in regulating T cell dynamics and motility . The significance of this study is derived from the focus on the key effector cell responsible for controlling influenza infection , a disease that kills hundreds of thousands of people each year worldwide . Understanding the molecular basis of T cell motility and migration into the infected airways has the potential to lead to novel ways to improve control of influenza infection and pathogenesis . This new knowledge will translate into many other infections that occur in different mucosal sites and epithelial surfaces .
C57BL/6J ( B6 ) mice were purchased from Jackson Labs ( Bar Harbor , ME ) and used from 8–12 weeks of age . A colony of the OT-I transgenic mouse strain that expresses a TCR specific for the OVA SIINFEKL ( OVA257–264 ) peptide presented in the context of H-2Kb ( 14 ) was crossed with a transgenic mouse expressing GFP under a chicken beta-actin promoter [23] . Both lines of mice were maintained at the University of Rochester Vivarium . All animals were housed in the University of Rochester Vivarium facilities under specific pathogen-free conditions using microisolator technology . All experimental protocols were performed in accordance with the standards established by the United States Animal Welfare Act , as set forth by the National Institutes of Health guidelines . The experimental protocols were reviewed and approved by the University Committee for Animal Resources , number 101431-UCAR-2006-029R , and conducted in Association for Assessment and Accreditation of Laboratory Animal Care International accredited facilities . The influenza H3N2 A/Hong Kong/X31 ( X31 ) virus , and A/X31-OVA-I influenza virus that expresses the ovalbumin ( OVA ) 257–264 ( siinfekl ) peptide in the hemagglutinin viral protein [24] were grown and titered in embryonated chicken eggs and harvested as allantoic fluid preparations ( Allan et al . , 1990 ) . Mice were sedated with avertin ( 2 , 2 , 2-tribromoethanol ) prior to intranasal ( i . n . ) challenge with 105 EID50 of X31 or 3 x 103 EID50 X31-OVA-I in 30 μl of PBS . Following cardiac perfusion of the mice with PBS , the trachea was canulated to just above the tracheal carina ( first bifurcation of the airways ) and bronchoalveolar lavage cells were collected by lavage with 1 ml HBSS three times . These were then resuspended in complete ( +10% fetal bovine serum ) minimal essential medium ( cMEM ) ( Gibco , Grand Island , NY ) . Single-cell suspensions were prepared from spleen and lymph nodes by disruption in cMEM by Dounce homogenization , washed , and resuspended in cMEM . Trachea and lung were collected and disrupted using a tissue chopper , then digested using Collagenase Type II ( Worthington ) . Lymphocytes were isolated on a Percoll ( Sigma , St . Louis , MO ) gradient . Viable cell counts were obtained by trypan blue exclusion . Cells collected from trachea were pooled in like groups ( 3–5 trachea per group ) and stained with various combinations of mAbs to CD8a ( 53–6 . 7 ) , CD4 ( RM4-5 ) , CD49a ( Ha31/8 ) , CD3 ( 145-2C11 ) , Live/Dead Aqua ( Invitrogen ) , and CD19 ( 1D3 ) . The conjugated mAbs were purchased from BD Pharmingen , eBioscience or BioLegend and are referenced in their current catalogs . Tetrameric complexes of H-2Db/influenza polymerase ( PA ) 224–233 ( DbPA ) , and H-2Db/influenza nucleoprotein ( NP ) 366–374 ( DbNP ) , were prepared by the NIH Tetramer Facility ( Atlanta , GA ) . Data was collected using an 18-color LSR-II , and analyzed using FlowJo software ( Tree Star ) . To obtain tissue for immunohistology , mice were infected intranasally with HK/X31 . At time of harvest , mice were injected with Avertin and placed in a surgical plane . The renal artery was severed and the mouse was euthanized via exsanguination . The chest cavity was opened and the lungs were perfused with PBS . The trachea was exposed and a canula was inserted and fixed in place with a suture . Using a 1ml syringe , 0 . 8ml of warmed OCT was instilled to inflate the lungs , and a suture was placed at the base of the trachea to maintain the inflation . The lungs were excised and placed in OCT , then immediately frozen by floating on top of liquid Nitrogen . The trachea was also excised , inserted into OCT and frozen as for the lungs . Tissues were wrapped in aluminum foil and stored in a -80°C freezer . Sections from 5–10 μm were cut transversally using a Shandon LSE Cryotome Cryostat . They were mounted on pre-cleaned superfrost plus slides from VWR . Slides were immediately placed in ice-cold acetone for 10 minutes for fixation , removed and allowed to dry for 10 minutes . They were then placed in a slide box , wrapped in aluminum foil , and stored at -80°C until ready for staining . For immunofluorescent staining , sections were removed from -80°C and thawed on ice for 10 minutes . They were then placed at room temperature and allowed to dry for 10 minutes . Residual OCT was removed and rehydration of tissues was accomplished by incubating slides for 10 minutes with 1ml of PBS . The Fc receptor was blocked with PBS-Tween20 ( 0 . 05% ) containing anti-CD16/32 ( BD Pharmingen 1:200 ) , normal rat serum and normal goat serum ( Jackson , 1:100 ) . Sections were incubated for 15 minutes at room temperature in a humidified chamber . From this point , all washing and staining was done using PBS-Tween20 . Sections were washed for 5 minutes and stained with the following antibodies: Alexa Fluor 647 labeled rat anti-mouse CD8a ( BioLegend; 1:200 ) , FITC labeled Monotope–Influenza A Virus ( Virostat 1:100 ) and unlabeled goat anti-type IV collagen ( Southern Biotechnology Associates; 1:400 ) for 60 min . Sections were then washed and incubated with a secondary donkey anti-goat Cy-3 for 30 min . The sections were then washed and mounted using a cover slip and DAPI Fluoromount-G ( Southern Biotech ) . Fluorescence microscopy was performed at 20X using a Nikon Eclipse TE2000E fluorescence microscope equipped with an X-Cite Series 120 fluorescence Illuminator and a Cool-SNAP HQ charge-coupled device camera ( Roper Scientific ) with NIS-Elements software . All imaging filters were from Chroma Technology Corp . ( Bellows Falls , VT ) . For whole mount , intact tracheas were excised from infected mice . The tracheas were cut in half longitudinally and placed in PBS/BSA 1% ( PBA ) . Fc receptors were blocked with CD16/32 ( BD Pharmingen , 1:100 ) . Primary antibodies were added in various combinations in excess ( 1:50 ) : CD31 , CD8 , CD19 , CD4 PE , Class II , ICAM , LYVE-1 , and CD45 conjugated to FITC , PE , Alexa Fluor 647 , Cy3 , PerCP and APC . The conjugated mAbs were purchased from BD Pharmingen , eBioscience or BioLegend and are referenced in their catalogs . Tissue sections were incubated in a cold room at 4°C , on a rocker , for 4 hours . They were washed with 4 ml of PBA for 5 minutes and then mounted on a clean glass slide in 100 μl of PBA under a cover slip . Imaging was performed with an Olympus BX40 with fluorescent attachment , a Retiga 1300 Monochrome cooled 12 bit camera from Q-Imaging systems , and Image Pro Plus Version 5 . 0 from Media Cybernetics . Imaging was performed using an Olympus FV1000AOM-Multiphoton imaging system in combination with a Spectra-Physics MaiTai-HP Deep See fs Ti:Sa laser system . Fluorescence was collected with a water immersion objective Olympus XLMUMPlanFI 25x NA1 . 05 for high-resolution imaging or a Zeiss C-Apochromat 10x NA0 . 45 water immersion objective for imaging large fields of view ( ~1200x1200um2 ) . Fluorescence was separated from the excitation light using a dichroic mirror / blocking filter combination ( Dichroic Olympus 650LP; Blocking Filters FF01-680/SP , Semrock , Rochester , NY ) . The fluorescence was divided into two channels using an appropriate dichroic mirror ( 505DCXRU , Chroma ) . The laser-power and the laser-pulse-width were continuously monitored using a Pulse-Scout-Autocorrelator ( Spectra-Physics ) and a wavelength-calibrated laser-power power meter ( 1918-C . Spectra-Physics ) . All imaging data was taken at 12bit-depth and analyzed and visualized using Volocity ( Perkin Elmer ) and Imaris ( Bitplane ) software , respectively . A line of GFP+/OT-1+ animals was maintained and used as donors for adoptive transfer of C57BL/6 naïve animals prior to infection . Whole splenocytes were isolated , and 1x106 cells contained in 200ul of DPBS were transferred via tail vein . 24–48 hours post transfer , the animals were sedated with 120 mg/kg of Avertin . Once animals were sedated and exhibited no pedal reflex , 30 μl of X31-OVA-1 ( 2 . 7x103 EID50/ml ) was administered intra-nasally . Animals were monitored until fully recovered from anesthesia , and then daily for weight-loss . Prior to surgery , the animal was anesthetized with pentobarbital ( 65 mg/kg ) . During imaging the level of anesthesia was maintained with isofluorane , administered at 0 . 5–2% as necessary based on heart rate . Pancuronium bromide ( 0 . 4mg/kg ) was administered prior to imaging , to prevent movement of the imaging area . The hair was removed with a shaver from one hind leg , thigh to groin , exposing the skin for the MouseOX Plus sensor ( Starr Life Sciences ) . The hair was removed from the thoracic area with scissors and/or a shaver . The animal was placed in a supine position , on a warming blanket , once surgical plane of anesthesia was determined by lack of both pedal and palpebral reflex . The coat was opened from below the chin to the top of the ribcage . The salivary glands were separated to reveal the muscles covering the trachea . Using round forceps , the muscles were separated to expose the trachea . The forceps were then inserted beneath the trachea to lift and separate it from the muscle and mouse body . A small flexible plastic support was placed in the space created by the forceps to permanently hold the trachea above and separated from the muscle , surrounding tissue and coat . The animal was moved to the previously warmed stage . A small incision was made between the cartilage rings below the larynx . The steel cannula was inserted into the opening in the trachea until it reached just below the sternum . The cannula provided physical immobilization of the trachea . The cannula was secured on the stage with a support that holds it in position so it is correctly aligned with the trachea . It was held in place with 2 screws that prevent it from moving in transport , or during the attachment of the respirator . The forepaws were secured to the stage with surgical tape to maintain position of the mouse body on the stage . A few drops of saline were placed on the exposed tracheal tissue to prevent drying . The cannula was quickly attached to the Harvard Inspira ASV ventilator , and both 100% O2 and 0 . 5% isofluorane flow was started , according to mouse weight . The MouseOX Plus thigh sensor was attached to the exposed thigh and monitoring was started immediately . Oxygenation levels were maintained at >95% and heart rate ranged between 250 and 600 beats per minute . The rectal body-temperature was continuously monitored and maintained using a small animal temperature controller that is connected to a rectal probe and a feedback-regulated rodent heating pad . After achieving stable physiology , and verification of lack of both pedal and palpebral reflex , the pancuronium bromide ( 0 . 4 mg/kg ) was administered , based on body weight . The saline covering the exposed trachea was blotted away and replaced with 0 . 05% agarose to seal the exposed area . Once the agarose was solidified , a support ring was placed over the imaging area and covered with a piece of plastic wrap . Approximately 5 ml of water was pooled over the imaging area to submerse the objective . Prior to the start of surgery , 100μg of anti-H2 Kb/ siinfekl ( 25-D1 . 16 ) antibody [25] was injected via tail vein . Animals were then prepared for imaging , which took place either one or two hours after administering the antibody . For the imaging , the animals were maintained either at 37°C or 35°C as described in the results .
The well-established mouse model of non-lethal influenza infection has defined kinetics of viral replication in the lung , with clearance of the virus by 9 to 10 days after infection [26 , 27] , while T cell infiltration of the airways sampled by broncho-alveolar lavage ( BAL ) becomes easily detectable by day 6 [26 , 28] . For the trachea , our initial goal was to determine if the kinetics of the virus and cellular immune responses were comparable to the BAL or lung tissue . To establish a baseline , mice were infected with a standard laboratory strain of H3N2 influenza A virus ( HKx31 ) using an intranasal route of administration to sedated animals . Each mouse received 105 EID50 of virus diluted in 30μl PBS [27 , 29] . To determine the localization of infected cells and lymphocyte infiltrates , frozen sections were prepared for immunohistology and stained for CD4 and CD8 T cells , collagen IV , and influenza nucleoprotein ( NP ) . On day 2 in mice infected with HKx31 , the cells of the epithelium were uniformly positive for NP , with few T cells visible ( Fig 1A ) . At day 8 , the epithelium now demonstrated substantial T cell infiltrates in and below the epithelial surface ( Fig 1B ) . This data suggests that HKx31 virus replicates efficiently in the tracheal epithelium . To determine the kinetics of virus replication and production of infectious virus , the whole lung and a section of trachea ( ~3mm ) were individually dissected from the animals , weighed , and snap frozen . When homogenized in an equal volume of media , the concentration of recovered virus in the trachea was lower than the lung at all time points , but followed a similar time course ( Fig 1C ) . However , the amount of virus being produced per gram of tissue was equivalent to the lung ( Fig 1D ) , despite the larger epithelial surface area . In the experiment shown , infectious virus was cleared from the trachea by day 9 , and only one of three mice cleared virus from the lung by day 10 , though the residual amount ( ~100 EID50 ) was low . Overall the kinetics of HKx31 are similar in trachea and lung tissue . Since the virus replication and clearance kinetics were similar in lung and trachea , we wanted to also compare T cell responses in the trachea to the airways sampled by BAL , and to lung tissue . Although the total cell numbers were small given the size of the tissue section ( ~10mg ) and relative surface areas being sampled , CD4+ and CD8+ , CD3+ T cells were easily detectable by flow cytometry on day 8 ( Fig 2A , 2C and 2D ) , including Db/NP ( 8–11% of CD8+ ) and Db/PA ( 7–17% of CD8+ ) tetramer positive cells ( Fig 2B and 2E ) . The trachea also contained higher proportions of CD19+ cells ( 5–10% ) than the BAL ( >1% ) , but less than the lung ( ~25% ) . Total CD3+ cells peaked 8 days after infection , and then declined . The peak of the response was less sharp than in the BAL or lung tissue ( Fig 2 ) , though it should be noted that the difference in cell numbers in the trachea from days 6 , 8 or 10 are statistically insignificant , reflecting variability in cell recovery and a smaller denominator in terms of total cell counts . Collectively , these data show that the adaptive cellular immune response to influenza infection in the trachea is robust , with a rise and fall that corresponds with clearance of the virus as it does in the BAL and lung tissue . Having established that the trachea is a suitable site of infection with HKx31 and X31-OVA , we proceeded to develop it as a site for imaging . To give some perspective on where in the tissue the imaging is performed , the trachea was surgically exposed in a live animal , showing it has a translucent appearance between the cartilage rings ( Fig 3A ) . Imaging was performed on the tissue between the rings . For further perspective , explanted trachea was split longitudinally , opened and placed between a cover slip and glass slide for whole mount imaging . The tissue was stained for CD4 ( blue ) and CD8 ( red ) to image the T cells , and collagen IV ( green ) to visualize the lamina densa of the basement membrane , just underlying the epithelial surface ( Fig 3B ) . Next , because of its ability to optically penetrate intact tissues to a greater depth , we used multiphoton imaging of the infected trachea to further reveal structural features and T cell localization . Dextran ( red ) was injected intravenously to highlight the blood vessels . Peering through the tissue , the blood vessels , T cells ( green ) and outer collagen fibers ( white ) can be visualized ( Fig 3C–3E and S1 Movie ) . CD8+ cells are close to the blood vessels , in the parenchymal space below the epithelial surface . Unfortunately , the collagen bundles directly underlying the epithelium do not produce a detectable second harmonic signal . Using explanted trachea stained with antibodies to collagen IV , the T cells can be seen above and below the Col-IV layer corresponding to the lamina densa at the base of the epithelial surface , suggesting some of the T cells are in the epithelium itself ( S1 Fig ) . This is consistent with conventional immunohistology using frozen sections [30] . The ability to optically penetrate the trachea from the outside in opens the possibility of imaging the infected trachea in situ in an intact live animal . Migration into the infected epithelium is critical for CTL mediated control of infected cells . Mechanisms that regulate effector CD8+ T cell motility in the infected tissue are largely undefined , and studies need to be done in the intact tissue to begin interrogating the mechanisms . Live imaging of the lung in live animals is limited by the need for the lung to continue functioning in breathing , with movement of the tissue and the challenge of maintaining intrathoracic pressure during respiration as significant technical hurdles [31] . Mice infected with influenza have lower body temperatures and low blood oxygen saturation [32] . Anesthetization can further lower body temperature [33 , 34] and suppress breathing , affecting blood oxygen levels [34] . In our experiments , rectal temperatures of infected mice after sedation for imaging were variable , and lowest at days 5–6 ( Fig 4A ) , a time when virus titers are still relatively high and the T cell infiltrates are just becoming measurable . As the animals recover and virus titers were reduced , pre-imaging body temperatures rise , though were still lower than reported for unsedated animals ( Fig 4A ) [32] . Mice being imaged also exhibited low blood oxygen saturation and erratic heart rates ( Fig 4B ) . Because of concerns about the effects of physiological variability on cell motility , we elected to provide respiratory and temperature support to maintain normal physiology since cell movement is affected by both temperature and oxygenation [35] . Body temperature was controlled via a heat block on the stage , a warming blanket with feedback from the animal using a rectal probe , as well as a warmed objective lens . A respirator maintained breathing rate and oxygenation , with pulse oximetry . This setup allows longer-term ( 2h ) imaging . Tracheostomy and cannulation of the trachea both stabilized the tissue from respiratory movement and facilitated mechanical ventilation . First , we wanted to know how variable T cell motility was over the course of an acute infection . The number of studies measuring CD8+ T cell motility during respiratory infection is limited . CD8+ T cell velocity during a model of influenza infection has been reported to be similar on days 6 and 8 , with significantly higher velocities on day 10 [36] . These experiments were performed using an excised lung slice and combined imaging of lung tissue and airway versus airway alone . To get a more comprehensive set of T cell motility parameters , and compare motility in primarily an airway to a more heterogeneous tissue , we adoptively transferred OT-I TCR transgenic CD8+ T cells crossed to a mouse that expresses GFP under an actin promoter , and then infected mice with X31-OVA-I at a sublethal dose . Note that this dose was lower than for wild-type X31 because mice infected with higher doses were too fragile for long-term imaging . Animals were imaged between days 5 and 14 . Events in the lymph node and spleen related to T cell activation and differentiation initially occur between one and 3 days after infection [22 , 28 , 29 , 37 , 38] , well before virus-specific T cells become detectable in the respiratory tract . Few cells were visible prior to day 5 , so imaging was done on days 5 , 6 , 7 , 8 , 9 , 10 , and 14 ( S1–S7 Movies show an extended focus , while S8–S12 Movies are animated to visualize the cells and tissue from different angles in 3D ) . Visible cells were still variable on day 5 in some experiments , so we include only motility parameters from day 5 experiments that had substantial T cell infiltrates . Each imaging time point was repeated 3–5 times in replicate experiments using separate mice conducted over a period of more than a year . CD8+ T cell motility was not uniform throughout the infection . Cell velocity began relatively high at days 5 and 6 and decreased steadily , reaching a nadir ( p < 0 . 001 ) at day 7–8 , presumably as effector CD8+ T cells accumulate in the respiratory epithelium where the infected cells are located ( Fig 4C , S4b and S5b Movies ) . Remarkably , at day 9 there was a significant ( p < 0 . 001 ) increase in velocity that then returned to slower speeds by day 10 and beyond ( p < 0 . 001 ) ( Fig 4C , S4a & S4b , S5a & S5b , S6a & S6b Movies ) . The meandering index , a measure of the straightness or confinement of cell tracks that is the ratio of the displacement of a cell to the total length of the path that the cell has travelled [39] , also changed dramatically ( p < 0 . 001 ) from day 8 to 9 and 9 to 10 , being lowest at day 9 , suggesting the cells were more restricted in their movement ( Fig 4D and S12–S16 Movies ) . Displacement was highest at days 5 and 6 ( the only time points significantly different than the others ) , suggesting rapid infiltration of the infected tissue ( Fig 4E ) . Differences in displacement and cell tracks are depicted in spider plots for days 7 and 9 ( Fig 4G and 4H ) . To reinforce our interpretation of the motility data , we used an approach that provides a better visual representation of the changes in cell behavior . Since the cell motility parameters for each cell are linked , average cell velocities can be plotted against the meandering index to give an assessment of migratory properties over the course of the infection . Mrass et al . used this approach to describe four quadrants in the plot into which the cell populations fall ( see inset Fig 5 ) [39 , 40] . Quadrant 1 contains cells with high velocity and high apparent confinement ( low meandering index ) ; these are the cells exhibiting active directional migration , but that do not cover much distance from the origin . Quadrant 2 contains the cells with high velocity and low confinement , which are the cells showing sustained motility , with limited stopping . Quadrant 3 contains the cells of low velocity and high confinement , the so-called low motility or stopped cells . The fourth quadrant contains the cells with low velocity and low confinement , indicating cells that actively move only during certain periods , consistent with non-sustained motility . Histograms along the top and right side of each plot show the cell distribution . Similar to a flow cytometry plot , the locations of the crosshairs are based on the cell densities most easily seen in Fig 5D , but are otherwise arbitrary . The plots of velocity versus meandering index change rather dramatically over days 6–10 and day 14 ( Fig 5 ) . On day 6 , cells are found distributed in all four quadrants , with many in quadrants 1 and 2 , suggesting active directional and sustained motility ( Fig 5A and S2 Movie ) . Fewer cells are in quadrant 3 , exhibiting low motility . This is consistent with rapidly infiltrating cells that need to cover a lot of ground as they seek infected and antigen-bearing cells . On days 7–8 ( Fig 5B and 5C ) , the majority of the cells move out of quadrants 1 and 2 ( reduced velocity ) , and by day 8 most are in quadrant 4 , exhibiting the non-sustained motility of cells that are not confined and actively moving during short periods ( Fig 5C , S3 and S4 Movies ) . This behavior is consistent with cells that have reached their destination and are perhaps sequentially encountering antigen bearing and infected cells . On day 9 ( Fig 5D ) , there is a major shift towards quadrant 1 and 3 as the velocities rise and the cells are moderately confined , consistent with low motility and displacement , showing that the cells are very active but not going very far . Closer examination of the d9 images shows many cells arrested and rounded in appearance compared to d8 , while others exhibit rapid local migration ( S13–S16 Movies ) . The high apparent velocities and increased confinement are consistent with rapid surveillance , perhaps sampling their immediate cellular environment for infection . On day 10 ( Fig 5E ) the cells shift again down to quadrants 3 and 4 , which remains consistent on day 14 , though with fewer cells ( Fig 5F , S6 and S7 Movies ) . These are cells with low motility and high apparent confinement , possibly because they are entering a more sessile state . Calculation of the arrest coefficients supports these conclusions . On day 6 , few T cells are arrested ( Fig 6A ) . On days 7 & 8 , the values are broadly distributed , with an increase in cells exhibiting arrest ( Fig 6B and 6C ) , again perhaps as they accumulate at the epithelium . On day 9 few cells are arrested though their displacement values are low ( Fig 6D ) , indicating that they are very actively moving , but not traveling far . On day 10 , the majority of cells are close to arrest , while by day 14 the majority of cells are fully arrested ( Fig 6E and 6F ) , which is not surprising given the absence of active infection at these time points . A substantial infiltrate of OT-I T cells in mice infected with influenza encoding the cognate siinfekl OVA H2Kb restricted peptide is present by day 5 post infection [24 , 27] . To determine whether there were differences in virus clearance compared to non-OVA HKx31 , we performed virus titers of lung and trachea at several time points after infection using an indirect immunofluorescence assay . Possibly due to the more rapid T cell response and lower dose of virus , virus titers were lower in the lung and below detection in the tracheas of two out of three mice at days 6 , 7 , and 8 . However , one mouse was positive on all three of those days . The incomplete control may relate to a requirement for neutralizing antibodies , which are not typically detectable until day 7 [41] . We conclude that while virus was below the limit of detection in some mice , the data suggest that it may persist as far as day 8 , which is similar to the wild-type kinetics . ( Fig 7A ) Collectively , the data show that , early in the response , the cells travel at higher speed over more distance . As the cells accumulate along the epithelium , the displacement decreases and confinement increases , presumably due to physical restrictions to movement at the epithelial surface . The data also indicate an abrupt shift in motility that occurs between days 8 , 9 , and 10 . The increase in velocity , decrease in angle and meandering index would be consistent with the cells becoming established in the epithelium , and exhibiting behavior associated with surveillance for residual antigen [42 , 43] . To test whether this could be the case , mice were treated on day 7 with a monoclonal antibody that specifically blocks Kb/siinfekl peptide-MHC complex , while leaving other Kb class I complexes intact [44] . CD8+ T cell motility was measured 1 and 2 hours later . On day 7 in control mice , average CD8+ T cell velocities hover close to 2 μm/min ( Fig 7B ) . In the antibody treated mice however , initial cell velocities at the start of the imaging session were between 3 and 4 μm/min , suggesting the antibody was having an effect ( Fig 7C ) . However , over the 25-minute imaging session , the velocities returned to the lower values more closely resembling day 7–8 in untreated mice . We wondered whether the imaging conditions that include warming both the mouse body and the imaging site to 37°C with a warming objective was having an effect on the peptide MHC blockade . To test , we performed the imaging at 35°C , and turned off the objective lens warmer . Under the lower temperatures , cell velocities remained higher at between 3–4μm/min ( Fig 7D ) . Both the slow decline at 37°C , and the stable cell behaviors at 35°C were reproduced in multiple mice on multiple imaging sessions . The data suggests that the low velocities and increased confinement on day 7 , similar to day 8 , is a result of cells arresting through interaction with antigen-bearing cells . The increased velocity on day 9 is most likely due to the elimination of the majority of the antigen-bearing cells ( and virus ) . After day 10 , the cells return to slower velocities , are less confined , with many cells arrested ( velocities < 2μm/min ) . Given that the virus is absent at this and later time points , it is most likely a reflection of a less activated phenotype .
Utilization of the mouse trachea to study influenza infections is not a new idea , as infection of the trachea was described as long ago as the 1960’s and perhaps earlier [5 , 7 , 20] . Natural infection of humans with circulating seasonal influenza virus strains is similarly clinically presented as tracheitis [45] , except in extreme cases of highly pathogenic strains or immunosuppression leading to more widespread infection of the lung [45] . The study described here , using a mouse-adapted strain of influenza ( H3N2 influenza A/Hong Kong/X31 ) [46] , shows that tracheal epithelium is uniformly infected as demonstrated by influenza nucleoprotein positive cell staining within 2 days of inoculation . Specific production of virus by the tracheal tissue is high and on par with the lung as a whole . The data show that the trachea is a very relevant site in which to study the antiviral immune response . The majority of studies in the field of mouse models of influenza infection over the last 20 or so years have largely focused on events in the lung as a whole . Typical study designs , including many from our lab , involved collecting bronchoalveolar lavage to sample the airways , and explanting the entire lung followed by tissue disruption to make single cell suspensions of infiltrating lymphocytes for in vitro assays . Because the preponderance of recent quantitative cellular immunity literature is derived from the lung , not the trachea , we felt that it was important to provide a complete characterization of the cellular response to influenza infection of the trachea . The data was useful in designing the imaging studies that follow . Not surprisingly , the initial immune response to primary infection stimulates a cellular response limited by the time it takes to prime T cells in the draining lymph nodes and spleen , cellular proliferation , and eventual circulation via the blood to sites of infection . As observed in the lung , this takes up to 4–5 days before substantial numbers of virus-specific CD8+ T cells can be detected either by tissue disruption or direct imaging methods . The imaging of an immune response in a respiratory tissue is not without its challenges . The principal technical hurdle is overcoming the physiological requirement of the lung to expand and contract for breathing and gas exchange . While there are algorithms that can correct for small tissue movement , the degree to which the lung moves in a single breath cycle exceeds the capability to correct for motion [31] . Strategies that have been used by others to overcome this issue include using lung explants of mostly intact tissue [36] , and thoracic “windows” in which the lung is suctioned against a clear viewing portal placed by cutting through the chest wall [32] . To our knowledge , only the former approach has been used in a model of influenza infection . We succeeded in targeting the trachea with a combination of minor surgery , optimization of paralytic and sedative agents , and partial physical immobilization by cannulation . Combined with transgenic reporter cells ( OT-I-GFP ) and recombinant virus that encodes the cognate OVA peptide [24 , 27] , we have demonstrated that the trachea is an optically penetrable tissue suitable for cell migration studies . A finding that was both unexpected at the time and , in retrospect , unsurprising , was that the influenza-infected mice prepared for imaging were physiologically compromised and fragile . This was caused by the combination of the consequences of the infection and the use of anesthetics on the mice , both of which can reduce respiration and blood oxygen saturation [33] . In a study reported in 2009 , Verhoeven and Farber [32] demonstrated that pulse oximetry to measure blood oxygen was a more sensitive measure of lung pathology than the more widely used weight loss measure . Blood oxygen levels declined with increased virus dose ( and titers ) as well as with the presence or absence of an adaptive immune response , which when absent caused reduced weight loss , but much lower oxygen saturation and increased lung pathology [32] . These authors went on to investigate the effects of warming on blood oxygen , and concluded there was no effect . Although we did not directly investigate this ourselves , temperature can affect cell migration independent of its effects on blood oxygen [47] . T cells move optimally at a normal physiological temperature [47] . Given the reduced body temperatures induced by both the infection and sedation , we felt compelled to maintain the body temperature at close to normal healthy levels . One could argue that we should have maintained a temperature closer to that of a “normal” flu infected animal , which is reported to be an average of 3 . 8°C below normal [32] . However , we reasoned that it was best to maintain a common baseline temperature in all the experiments to reduce the chance of introducing additional mouse-to-mouse and day-to-day variability to the motility data . Therefore mechanical respiration and feedback controlled temperature maintenance became part of our standard protocol for imaging . Studies of CD8 T cell motility in the airways or lung tissue are limited compared to those on neutrophils [31] , dendritic cell ( DC ) behavior and migration [36 , 48] , or CD4+ T cell migration in models of allergic airway disease [48] . In our studies , we found that CD8+ T cells migrated at the highest apparent velocities on days 6 and 9 , the two time points that frame initial T cell infiltration of the tissue and the time when virus is cleared . However , analysis of confinement at those two time points revealed markedly different values that demonstrate the T cells are far more confined on day 9 and do not migrate far from their origins . During the acute phase when virus was still present , the CD8+ T cells moved at the slowest average velocities and moderate confinement at day 8 , consistent with sequential engagement of antigen bearing cells and/or localization in the epithelial layer , which would be expected to limit lateral migration . Indeed turning angles clustered around the 90° point at day 8 which would be consistent with movement in the relatively two-dimensional space of the epithelium . After the virus was cleared , cell velocities returned to lower values , suggesting a less activated state . Interestingly , day 10 is a time point that we have observed that the CD8+ T cells in the airways become dependent on the integrin alpha-1 for retention [30 , 49 , 50] . A similar phenomenon of slowed migration was noted recently in explanted lung tissue from infected mice , where the authors also suggested this is a time when the cells begin rapid migration on collagen [36] , consistent with our hypothesis that this is when the T cells switch to an integrin-dependent mode . Notably , they also observed higher velocities on day 10 , which is the day virus ( and possibly antigen ) is cleared in the lung , and potentially similar to the phenomenon we saw on day 9 in the trachea . It is also possible that the T cell populations in the tissue from days 8 , 9 , 10 , and 14 are not the same , as the airway is not a closed system . Our data on the role of alpha-1 integrin suggest that , at least after virus clearance , there is a selective process for the cells that can be retained [49 , 50] , possibly leading to the establishment of tissue-resident memory , which if true may account for the differences in cell motility behaviors . Compared to the aforementioned study using explanted lung sections [36] , our data from the trachea of influenza-infected mice differs in that we see lower ( vs . higher ) cell velocities on day 8 than day 6 . The day 6 CD8+ T cells were equally moderately confined and average velocities were similar ( not lower ) on day 14 compared to day 10 . It is possible that there is a difference in overall cell and viral clearance kinetics that can account for these variations . For example , if you use day 9 in our studies to compare to days 8 and 10 , you get a set of observations more similar to the differences noted in the lung comparing day 8 to days 6 and 10 . Interestingly , both studies note the brief switch to a rapid scanning mode on the day after virus clearance has been demonstrated . Other mechanisms could also account for the differences in CD8+ T cell motility behavior on different days of the acute response . We recently demonstrated that neutrophil-derived chemokine CXCL12 deposited in membrane vesicles onto the extracellular matrix stimulates CD8+ T cell chemotaxis sensed through CCR4 on the CD8+ T cells in the flu-infected trachea [17] . Inhibition of this mechanism through various interventions reduced the rate of CD8+ T cell infiltration into the tissue ( measured at day 8 or earlier ) , by affecting cell velocities and localization within the tissue relatively distal to the airway surface [17] . It is likely that this is an effect manifested at the early time points when the T cells are first infiltrating the tissue , and diminishes towards the end of the acute response as the neutrophil vesicles become less frequent . The higher apparent velocities in neutrophil-depleted mice is consistent with the interpretation of the data in the current paper that progressive localization into the epithelial layer and engagement of antigen-bearing cells from days 6 to 8 slows the T cells . There is a major contraction of the CD8+ T cell response between days 8 and 9 , with massive apoptosis of the T cells [49] . However , we do not think the remaining cells measured on day 9 are apoptotic given their apparent high velocity readings that indicate the cells must be viable , as well as our earlier data that shows no measurable increase in the proportion of apoptotic cells [49] . The blip in cell velocities and increased confinement we observed between days 8 and 9 is remarkable . We wondered whether it was the infection itself or the presence of antigen-bearing cells that changed . Experiments were performed to distinguish antigen from infection . While some mice in the OT-I/X31-OVA-I system may have cleared virus as early as day 6 , it was treatment with OVA-peptide MHC blocking antibodies that altered cell motility , increasing their velocities . The resemblance of these increased velocities to that observed on day 9 suggests that the event driving the transient increase on day 9 reflects clearance of most antigen-bearing cells . It is entirely conceivable that the CTL do not distinguish infected versus antigen-bearing cells and kill them , as antigen-bearing dendritic cells are eliminated by cellular cytotoxicity [12 , 51] . Sensitive techniques to detect antigen-bearing cells have not been developed , making it difficult to measure the presence or absence of these cells directly . We also did not identify the phenotype of the antigen bearing cells . Obvious follow-up studies that need to be performed include the study of dendritic cells and monocyte/macrophage , and role of these cells in regulating cell motility and localization . It will be critical to investigate the role of extracellular matrix interactions through integrins and other matrix receptors that are known to affect the CD8+ T cell responses to flu [40] . The fact that the peptide-MHC antibodies seemed to get into the tissue when administered intravenously appears to rule out the possibility that the integrin antibodies would not get to the site , making blocking studies , such as those done in the inflamed dermis [52] , feasible . Similarly , studies looking at dependence on chemokine receptor signals at all stages of the response need to be performed . It will also be important to look at the memory phase of the immune response to influenza in the trachea , as well as secondary infection , which is the scenario closest to most human infections . In closing , we have presented a comprehensive analysis of using the mouse trachea as a site to study the migration behavior and mechanisms regulating cell motility . We have demonstrated its relevance to the overall cellular immune response to primary infection , and as an important site of virus replication . The behavior of the CD8+ T cells we measured differed in several aspects from that reported in other sites of influenza infection . Interference with OVA peptide/MHC complexes suggests the T cells in the influenza infected tissue are affected by antigen-bearing cells , providing an explanation for slowed velocities and high confinement observed just prior to virus clearance . The ability of the cell to increase velocities on day 9 , or under the influence of peptide-MHC blocking , tells us that the cells are not necessarily physically confined by their environment . We believe this work contributes to a better understanding of influenza immunity and will lead to novel interventions that could improve the control of virus infection , establishment of protective memory , and reduction of the tissue damage caused by the infection and immune pathology .
|
Influenza virus infects the cells that line the trachea and lung airways . Virus-specific cytotoxic ( cell killing ) T cells are the first line of adaptive immunity responsible for elimination of infected cells . We studied the cell movement , or motility , of these T cells responding to infection in the mouse trachea . Multiphoton live imaging was used to observe the cells in real time in intact tissue and measure their movement both quantitatively and qualitatively . The behavior of the CD8+ T cells responding to influenza infection was highly variable depending on the day after infection the imaging was performed . The most dramatic changes occurred after infectious virus was eliminated from the tissue , triggering a substantial shift in cell motility between days 8 and 9 . Blocking peptide/MHC complexes with antibodies reversed cell arrest , increased velocities , and reduced confinement , similar to the changes observed from days 8 to 9 . This suggested antigen-presentation persists after virus clearance with continued T cell engagement , and that T cell motility in the infected tissue is dynamically regulated by the infection and the presence of antigen-bearing cells in particular . In addition , these studies establish the trachea as a suitable site for live imaging of immune responses to virus infection .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"blood",
"cells",
"cell",
"motility",
"medicine",
"and",
"health",
"sciences",
"immune",
"cells",
"respiratory",
"infections",
"pathology",
"and",
"laboratory",
"medicine",
"influenza",
"pathogens",
"immunology",
"microbiology",
"orthomyxoviruses",
"pulmonology",
"viruses",
"respiratory",
"system",
"rna",
"viruses",
"cytotoxic",
"t",
"cells",
"trachea",
"infectious",
"diseases",
"white",
"blood",
"cells",
"animal",
"cells",
"medical",
"microbiology",
"t",
"cells",
"microbial",
"pathogens",
"pathogen",
"motility",
"cell",
"biology",
"anatomy",
"virulence",
"factors",
"influenza",
"viruses",
"viral",
"pathogens",
"biology",
"and",
"life",
"sciences",
"cellular",
"types",
"viral",
"diseases",
"organisms"
] |
2016
|
Live Imaging of Influenza Infection of the Trachea Reveals Dynamic Regulation of CD8+ T Cell Motility by Antigen
|
The identification of a new generation of potent broadly neutralizing HIV-1 antibodies ( bnAbs ) has generated substantial interest in their potential use for the prevention and/or treatment of HIV-1 infection . While combinations of bnAbs targeting distinct epitopes on the viral envelope ( Env ) will likely be required to overcome the extraordinary diversity of HIV-1 , a key outstanding question is which bnAbs , and how many , will be needed to achieve optimal clinical benefit . We assessed the neutralizing activity of 15 bnAbs targeting four distinct epitopes of Env , including the CD4-binding site ( CD4bs ) , the V1/V2-glycan region , the V3-glycan region , and the gp41 membrane proximal external region ( MPER ) , against a panel of 200 acute/early clade C HIV-1 Env pseudoviruses . A mathematical model was developed that predicted neutralization by a subset of experimentally evaluated bnAb combinations with high accuracy . Using this model , we performed a comprehensive and systematic comparison of the predicted neutralizing activity of over 1 , 600 possible double , triple , and quadruple bnAb combinations . The most promising bnAb combinations were identified based not only on breadth and potency of neutralization , but also other relevant measures , such as the extent of complete neutralization and instantaneous inhibitory potential ( IIP ) . By this set of criteria , triple and quadruple combinations of bnAbs were identified that were significantly more effective than the best double combinations , and further improved the probability of having multiple bnAbs simultaneously active against a given virus , a requirement that may be critical for countering escape in vivo . These results provide a rationale for advancing bnAb combinations with the best in vitro predictors of success into clinical trials for both the prevention and treatment of HIV-1 infection .
The ability to elicit potent broadly neutralizing antibodies through immunization remains an elusive goal in the development of an effective HIV-1 vaccine [1] . This has motivated major efforts over the past 6 years to isolate and characterize Env-specific antibodies from HIV-1-infected individuals who exhibit broad and potent serum neutralizing activity [2–4] . Through technological advances in single cell sorting of antigen-specific memory B cells [5–11] , high-throughput antibody cloning and screening methods , numerous novel monoclonal antibodies have since been isolated , some of which exhibit exceptional neutralization breadth and potency when tested in vitro against large panels of diverse HIV-1 isolates [7 , 9–20] . Identification of the epitope targets of these bnAbs has dramatically expanded our knowledge regarding sites of common vulnerability on the Env spike [21] . Major epitope targets include the CD4bs [5 , 11 , 16 , 19 , 22–27] , a glycan-dependent site in variable region 3 ( V3 ) of gp120 [9 , 17 , 28–31] , a V1/V2 glycan-dependent quaternary site on the apex of the Env trimer [9 , 10 , 12 , 32–37] , the MPER [15 , 38–41] , and epitopes bridging both gp120 and gp41 [13 , 14 , 18 , 42] . The hope remains that characterization of these epitope targets and efforts to elucidate the pathways of bnAb development in vivo will eventually result in the rational design of novel immunogens and immunization strategies for eliciting such antibodies through vaccination [12 , 16 , 24 , 43–46] . However , a more immediate potential exists for using bnAbs in clinical settings of passive transfer for the prevention and/or treatment of HIV-1 infection . In support of preventative modalities , pre-clinical studies in non-human primates ( NHP ) have demonstrated that passive transfer of bnAbs can confer sterilizing protection against high dose mucosal challenges with chimeric simian-human immunodeficiency viruses ( SHIVs ) [23 , 47–53] . Studies in NHP and humanized mice have further investigated the therapeutic potential of bnAb infusion in the setting of established viral infection , and demonstrated that transfer of single bnAbs can result in a transient decline in plasma viremia , reduction of proviral DNA , and in some cases extended control of viral replication [53–56] . However , viral rebound generally occurs once the concentration of transferred antibody decays below the therapeutic range , and the emergence of neutralization resistant escape variants is often observed . Similar observations were recently described in a phase I clinical study evaluating passive infusion of the CD4bs bnAb 3BNC117 in HIV-1 infected individuals [57] . While escape from antibody monotherapy remains a concern , additional data from animal model studies have shown that therapeutic strategies employing combinations of bnAbs to simultaneously target different epitopes on the Env spike can impede viral rebound and escape , and exert sustained control of viral replication [53–55] . Thus , for bnAbs to be effectively employed for treatment of HIV-1 infection , combinations of multiple antibodies will likely be required to confront the extraordinary diversity of the virus and its ability to escape from selective immune pressure . Recent studies of in vitro neutralization have established that combinations of bnAbs targeting distinct epitopes can act in a complementary and additive manner , and exhibit improved neutralization breadth and potency compared to single bnAbs [58–60] . In the study by Kong et al . , it was shown that the breadth and potency of bnAb combinations could be reliably predicted using an additive model , with consistent patterns of minor non-additive interactions for particular bnAb combinations , either antagonistic or synergistic [60] . Certain double , triple and quadruple bnAb combinations were found to achieve 89 to 100% coverage when tested against a large diverse multiclade virus panel . However , due to the complementary nature of the bnAb combinations , in many cases increased breadth was due to only a single bnAb in the mixture exhibiting neutralizing activity against a given virus . In a clinical setting , such a bnAb combination would in essence be the equivalent of single antibody monotherapy against a substantial fraction of viruses , which would have a greater opportunity for escape . Thus , for treatment of HIV-1 infection , it may be advantageous to use bnAb combinations that offer the best potential for active coverage of most viruses by two or more antibodies . For bnAb immunotherapy in the setting of chronic infection , viral clearance is the most desirable outcome , albeit challenging to achieve . Thus , more complex options are being considered , such as including combinations of the most potent bnAbs together with latency reversing agents ( LRAs ) and standard antiretroviral drug treatment [61–63] . For such strategies to be beneficial , bnAbs will need to be effective at three levels . First , they will need to neutralize the diversity of viruses circulating in the population targeted for treatment . Second , they will need to effectively neutralize the complex within-host quasispecies that develop during chronic HIV-1 infection . And finally , they should be effective against the full spectrum of expressed forms of Env on any given virion . It has been observed that some bnAbs exhibit neutralization curves that plateau well below 100% when tested against particular Env pseudoviruses in vitro [10 , 13 , 64 , 65] . This well-established behavior is surprising given the genetically clonal nature of viruses used in these assays , and could possibly stem from post-translational variation in the glycosylation patterns or alternate variable loop and structural configurations of expressed Env [13 , 65–68] . It is a concern that such incomplete neutralization may pose a severe limitation for achieving the desired therapeutic efficacy in vivo . Thus , an ideal immunotherapy candidate antibody combination should maximize the genetic and antigenic spectrum of viruses that are potently neutralized , while minimizing the impact of incomplete neutralization . A key question that remains is how many bnAbs will be required for long term beneficial effects in a preventative or therapeutic setting , and which combinations of bnAbs will provide the most potent and active coverage for testing in human clinical trials . Over the past several years , multiple bnAbs for each major epitope have emerged as viable candidates based on extensive in vitro and pre-clinical animal model testing . Given the tremendous resources required to move even a single candidate bnAb forward into human clinical trials , rational decisions must be made to select single antibodies , bivalent antibodies , or components of bnAb combinations that will theoretically provide the highest potency and coverage against the diversity of circulating HIV-1 . As bnAb clinical efficacy studies are currently being planned for conduct in southern Africa , coverage and potency of bnAbs against the HIV-1 clade C viruses that dominate the epidemic in that region is of considerable interest . Here we utilized a newly described panel of 200 acute/early clade C HIV-1 Env pseudoviruses to assess the breadth and potency of 15 of the most promising bnAb candidates targeting four major epitopes of HIV-1 Env . A mathematical modeling approach was developed that increased the accuracy in predicting neutralization titers of bnAb combinations . We experimentally validated the improved accuracy of this model , and then used it to predict the behavior of all possible 2 , 3 , and 4 bnAb combinations using data derived from single bnAb testing . Using these predictions , we compared the performance of a comprehensive spectrum of potential bnAb combinations , and identified those that provide the most optimal potency , breadth , complete neutralization , and active coverage .
A panel of bnAbs targeting HIV-1 Env was used to assess and compare the breadth and potency of neutralization against acute/early clade C Envs . Fifteen bnAbs were selected that target four distinct epitope regions: the CD4 binding site ( CD4bs: 3BNC117 , VRC01 , VRC07 , VRC07-523 , VRC13 ) [11 , 19 , 23 , 69 , 70] , the V3-glycan supersite ( V3g: 10–1074 , 10-1074V , PGT121 , PGT128 ) [9 , 17] , the V1/V2-glycan site ( V2g: PG9 , PGT145 , PGDM1400 , CAP256-VRC26 . 08 , CAP256-VRC26 . 25 ) [9 , 10 , 12 , 20 , 32] , and the gp41 MPER epitope ( 10E8 ) [15] . BnAbs were tested against a panel of 200 clade C HIV-1 Env pseudoviruses using the validated luciferase-based TZM-bl assay . This virus panel consists of viruses isolated from individuals in the acute/early stages of infection from five southern African countries , including South Africa , Tanzania , Malawi , Zambia , and Botswana . Serial dilutions of individual bnAbs were tested against each virus using a starting concentration that ranged from 10–50 μg/ml , depending on sample availability at the time of testing . Neutralizing activities were evaluated using potency-breadth curves ( the percentage of viruses neutralized versus an IC50 or IC80 cutoff , Fig 1A and 1B ) , scatter plots ( Fig 1C and 1D ) and heatmaps ( Fig 1E and 1F ) . The 5 bnAbs targeting the V1/V2-glycan region neutralized between 67–75% of viruses with positive IC50 titers , and the 4 bnAbs targeting V3-glycan neutralized 54–68% . When positive , these glycan-dependent bnAbs were strikingly potent . Using the more stringent IC80 measure , median IC80 titers ranged from 0 . 003–1 . 274 μg/ml for V1/V2-glycan and 0 . 073–0 . 203 μg/ml for V3-glycan bnAbs ( Table A in S1 Text ) . CD4bs bnAbs tended to exhibit greater breadth ( 71–96% at IC50 ) , but were generally less potent than V1/V2-glycan or V3-glycan antibodies ( median IC80 titers 0 . 30–1 . 58 μg/ml ) . The MPER directed bnAb 10E8 exhibited lower overall potency ( median IC80 3 . 399 μg/ml ) , yet had exceptional IC50 breadth , neutralizing 98% of viruses . Even the most resistant isolates were sensitive to at least 3 bnAbs , which most often targeted the CD4bs or MPER . Overall , clear differences in potency and/or breadth were observed among bnAbs of the same class ( defined here as bnAbs that target the same epitope region ) . Based on IC50 and IC80 titers , best-in-class bnAbs were CAP256-VRC26 . 25 ( V2-glycan ) , 10-1074V ( V3-glycan ) , VRC07-523 ( CD4bs ) , and 10E8 ( MPER ) . As visualized in heat maps ( Fig 1E and 1F ) , and by hierarchical clustering ( Fig A in S1 Text ) , bnAbs targeting the same epitope region exhibit similar patterns of neutralizing activity , with clear patterns of complementarity between epitope classes . For example , distinct clusters of viruses were resistant to V1/V2-glycan antibodies but sensitive to V3-glycan antibodies , whereas other virus clusters exhibit the opposite phenotype . These data illustrate how different combinations of bnAbs targeting distinct epitopes can complement one another for enhanced coverage against clade C viruses . Because it is not practical to assay all combinations of bnAbs against a large panel of viruses , a new method to accurately predict combination bnAb neutralization efficacy using the available large-scale single bnAb neutralization data was developed to facilitate rational decisions for selection of the best bnAb combinations for clinical testing . In a previous study by Kong et al . , the additive model worked well in predicting potency of bnAb combinations using experimental data from single bnAbs [60] . They also found that the experimental bnAb combination data deviated slightly from model predictions . Most combinations performed slightly better than predicted , while a few combinations that included a V3-glycan bnAb performed slightly worse than predicted . The additive model derives from an application of equilibrium mass action kinetics to simplified in vitro antibody-virus interactions ( S1 Text ) . This theoretical treatment assumes that single bnAb neutralization curves follow Hill curves with Hill exponents equal to one , and that antibodies act independently with little possibility of multiple antibodies inhibiting the same virion . The first assumption of a unit Hill exponent is largely valid for CD4bs and V3-glycan bnAbs , however , bnAbs targeting the V2-glycan and MPER epitopes frequently exhibit Hill exponents of less than 1 [65 , 71 , 72] . To overcome these limitations of the additive model , we developed a new model , the “Bliss-Hill model” ( BH model ) . This model combines single bnAb Hill curves ( with arbitrary slopes ) within the framework of the Bliss independence model for the binding of multiple species of ligands to a substrate [72 , 73] , and incorporates a correction for multiple ligands independently attaching to the substrate ( S1 Text ) . We tested the BH model by using experimental data from combination bnAb neutralization assays . The assays comprised 10 combinations of 2 , 3 and 4 bnAbs ( including 2-bnAb combinations with both antibodies targeting similar epitopes , Fig B in S1 Text ) assayed against a smaller panel of 20 viruses . The 20 viruses were chosen because they are sensitive to almost all bnAbs tested and comprise a maximized range of IC80 titers for the bnAb combinations . The BH model proved highly accurate in explaining the clade C panel bnAb combination data ( Fig 2A , R2 = 0 . 9154 , Pearson r = 0 . 9584 ) . Moreover , the BH predictions were closer to the observed data than the additive model for 9 of the 10 combinations tested ( Fig 2B , p = 0 . 021 using Binomial Test ) , with the only exception being the combination VRC07-523 + 10-1074V . Thus the BH model offered a significant , though modest in magnitude , improvement in prediction accuracy over the additive model . We confirmed this by reanalyzing a larger dataset from Kong et al . , and again found the BH model predictions to be highly accurate ( R2 = 0 . 9655 , Pearson r = 0 . 9862 , Fig C in S1 Text ) . The BH model performed slightly better than the additive model in all cases , and the difference reached high levels of statistical significance for most of the 2 , 3 , and 4 bnAb combinations tested . This improvement was due to the systematic trend of BH predictions being more potent than the additive model predictions ( Figs D and E in S1 Text ) , and thus closer to the observed titers since additive model predictions were found to be less potent than the observed titers for most combinations [60] . Nonetheless , for some antibody combinations , experimentally measured IC80 titers still showed minor deviations from the BH model predictions ( Fig 2 , Figs C-G in S1 Text ) . For a few viruses , the combination IC80 titers were 3-fold higher than the most potent bnAb in the combination ( Fig D in S1 Text ) , which is counter-intuitive since both the additive and BH models predict greater potency for combinations relative to the component bnAbs . In such cases we find that the very potent neutralization of a virus by an antibody ( particularly CAP256-VRC26 . 25 , Fig D in S1 Text ) is somewhat inhibited by the presence of additional antibodies , albeit still resulting in potent neutralization by the combination . Models that incorporated additional parameters based on observed deviations could further improve predictions in some cases ( S1 Text , Figs F and G in S1 Text ) , but the magnitude of deviations were small for most viruses . Furthermore , using deviation modeling with BH model ( Fig H in S1 Text ) or using additive model ( Fig I in S1 Text ) did not affect the conclusions below , as the best combinations selected were robust using either model . Passive and active immunization strategies that aim to protect against the acquisition of HIV-1 infection would benefit from information regarding how many and which bnAb combinations provide optimal coverage and potency . An antibody that may have the best characteristics when considered alone may not have the optimal complementarity when considered for combination bnAb regimens . We predicted the combination scores for all potential 2 , 3 and 4 bnAb combinations using the BH model on single bnAb neutralization data for 15 bnAbs against 200 clade C viruses , thus enabling direct comparisons of bnAb combinations . For 2 bnAb combinations , only combinations consisting of bnAbs targeting different epitopes were considered , while for 3 and 4 bnAb combinations , multiple bnAbs targeting the same epitope region were also considered . Predicted potency-breadth curves for all of the 2 , 3 and 4 bnAb combinations ( 1 , 622 combinations total ) are shown in Fig 3 . The combinations were stratified by the number of bnAbs targeting different epitopes ( referred to as “categories” , e . g . , CD4bs+V2g is a combination of a CD4bs and a V2-glycan bnAb , and V2g ( 2x ) +V3g has two V2-glycan and one V3-glycan bnAbs ) . Within each category , multiple combinations were possible due to multiple bnAbs targeting the same epitope . Best-in-category bnAb combinations were identified as those with the lowest geometric mean IC80 values for the 200 viruses ( highlighted in Fig 3 by dark , bold lines ) . Of note , the area under the IC80 potency-breadth curve is negatively , but linearly , and almost perfectly correlated to the Log10 geometric mean IC80 . Thus using either measure gives identical results . The best-in-category combinations were not always clear , as second best combinations were very comparable ( e . g . CAP256-VRC26 . 25 + 10-1074V + PGT128 or PGT121 with geometric mean IC80 of 0 . 007 and 0 . 0071μg/ml , respectively ) . Comparisons of best-in-category combinations having the same number of bnAbs are shown in Fig 4 . Best-in-category 2 bnAb combinations had significantly better predicted potency ( geometric mean IC80 range = 0 . 02–0 . 29 μg/ml ) and breadth ( 88 . 5–97 . 5% of viruses with IC80 < 10 μg/ml ) , than single bnAbs ( geometric mean IC80 = 0 . 17–5 . 91 μg/ml and breadth = 44–92 . 5% ) . The two best-in-category 2 bnAb combinations , CAP256-VRC26 . 25 ( V2-g ) with either 10-1074V ( V3-g ) ( geometric mean IC80 = 0 . 020 μg/ml ) or VRC07-523 ( CD4bs ) ( geometric mean IC80 = 0 . 021 μg/ml ) were significantly better than the other best-in-category 2 bnAb combinations ( p < 0 . 01 and q-value < 0 . 02 ) ( Fig 4A , 4B and 4C ) . However , it was unclear which of these two combinations was better , because each pairing had different advantages . While CAP256-VRC26 . 25 and 10-1074V alone are more potent than VRC07-523 when active ( Table A in S1 Text ) , they have more limited breadth , each neutralizing ~60% viruses at IC80 < 10 μg/ml as compared to 92 . 5% for VRC07-523 . Consistent with this , we found that the combination of CAP256-VRC26 . 25 + 10-1074V missed ~13% of viruses at IC80 < 10 μg/ml , while CAP256-VRC26 . 25 + VRC07-523 missed only ~3% . Thus , while CAP256-VRC26 . 25 + VRC07-523 was slightly less potent than CAP256-VRC26 . 25 + 10-1074V , it provides ~10% better coverage . For 3 bnAb combinations , the best breadth and potency was seen with CAP256-VRC26 . 25 + 10-1074V + VRC07-523 ( Fig 4D , 4E and 4F ) . This combination , which targets 3 separate epitopes , neutralized 99 . 5% viruses ( all but one in the panel ) at IC80 < 10 μg/ml , with a geometric mean IC80 of 0 . 0083 μg/ml . The superior performance of this combination draws from the complementary neutralization profiles of the most potent panel bnAbs , CAP256-VRC26 . 25 and 10-1074V , combined with the broad and potent profile of VRC07-523 ( Fig 1 ) . This combination was significantly more potent than most other best-in-category 3bnAb combinations ( p < 0 . 02 , q < 0 . 03 ) . Replacing VRC07-523 with either PGDM1400 or 10E8 in combinations containing CAP256-VRC26 . 25 + 10-1074V resulted in a small loss of potency and breadth that was not statistically significant . Overall , 3 bnAb combinations showed improved breadth ( 89 to 99 . 5% at IC80 < 10 μg/ml ) and markedly improved potency ( geometric mean IC80 of 0 . 008–0 . 060 μg/ml ) than 2 bnAb combinations , with 6 out of 7 best-in-category 3 bnAb combinations predicted to have better geometric mean IC80 than the best 2 bnAb combinations . The two best-in-category 4 bnAb combinations , one targeting 3 epitopes and another targeting 4 epitopes , had comparable potency ( geometric mean IC80 ~ 0 . 007 μg/ml ) and breadth ( 99 . 5% at IC80 < 10 μg/ml ) ( Fig 4G , 4H and 4I ) , and were more potent and broadly active than 4 bnAb combinations targeting only 2 epitopes ( geometric mean IC80 of 0 . 01 to 0 . 05 μg/ml and breadth 92–98 . 5% at IC80 < 10 μg/ml ) . Thus bnAb combinations targeting three epitopes showed a significant gain in breadth and potency compared to those targeting two , but the further gain in targeting all four major epitopes , for this panel is negligible . This information is useful to efforts that aim to achieve optimal coverage and potency to protect against the acquisition of infection in passive or active vaccination settings , but does not take into account ease of escape in the setting of passive immunotherapy for active infection . Combinations of bnAbs are likely to be advantageous in a therapeutic setting not only to maximize potency and breadth but also to minimize the potential for viral escape by targeting multiple epitopes simultaneously [55] . Thus , we investigated the extent of simultaneous neutralization by two or more bnAbs in the best-in-category bnAb combinations at different activity thresholds . First we quantified the percent of panel viruses actively neutralized by at least 2 , 3 or 4 bnAbs in all best-in-category 2 , 3 and 4 bnAb combinations at physiologically relevant concentrations . We used IC80 thresholds of 1 , 5 and 10 μg/ml , which fall in the range of bnAb serum concentrations in HIV-1 infected patients administered a single dose of 1–30 mg/kg of 3BNC117 [57] . For combinations with multiple bnAbs targeting the same epitope class , a modified counting procedure was employed that accounted for overlap in escape-associated mutations ( S1 Text ) . The percent of viruses neutralized by the best bnAb combinations at different thresholds of activity are shown in Table B in S1 Text . We modified the potency-breadth curves for best-in-category bnAb combinations to highlight cases where multiple bnAbs in a combination were simultaneously active ( Fig 5 ) . These curves show cumulative coverage of the 200 panel viruses at a given predicted combination IC80 value limited by counting only those viruses that were simultaneously sensitive to 2 , 3 or 4 bnAbs at single bnAb IC80 < 1 , 5 , or 10 μg/ml . When the percentage of viruses neutralized by at least 2 bnAbs was considered , the best coverage at our least restrictive threshold within the experimental assay range of IC50 <10 μg/ml was 92 . 5% , 97 . 5% and 100% for 2 , 3 and 4 bnAb combinations , respectively ( Table B in S1 Text , Fig 5 ) . This coverage decreased , as expected , to 80% , 91% and 95 . 5% , respectively , when a more stringent IC80 <10 μg/ml threshold was used , and continued to decrease until only 44% , 67 . 5% and 73 . 5% coverage was seen , respectively , at our most stringent threshold of IC80 <1 μg/ml . The percentage of viruses neutralized when requiring at least three bnAbs in the best-in-category 3 and 4 bnAb combinations to be active was of course even lower at each of these thresholds . Here , the best coverage at the less restrictive threshold of IC50 <10 μg/ml was 66 . 5% and 89% for 3 and 4 bnAb combinations , respectively , and progressively decreased to only 19 . 5% and 26 . 5% coverage at the most stringent IC80 <1 μg/ml threshold . Poor coverage was seen at all thresholds when all 4 bnAbs in the best-in-category 4 bnAb combinations were required to be active . Using extrapolated single bnAb neutralization curves ( see “BnAb combinations reduce levels of incomplete neutralization” below ) , we also investigated coverage with multiple active bnAbs using single bnAb IC80 < 50 μg/ml and < 100 μg/ml ( Fig J in S1 Text ) . These concentrations roughly approximate the 28 day trough plasma concentrations of passively-administered VRC01 and 3BNC117 in human trials [57 , 74] and more closely approximate the range of plasma concentrations that resulted in transient reductions in plasma viremia in patients who received 3BNC117 [57] . We found that the best coverage with 2 bnAbs active at IC80 <50–100 μg/ml was 93–100% for 2 , 3 and 4 bnAb combinations , and with 3 bnAbs active was 68–92 . 5% ( Fig J and Table B in S1 Text ) . The overall most potent and broad 2 , 3 , and 4 bnAb combinations ( Fig 4 ) , also had best or close to best coverage with multiple bnAbs active ( Fig 5 ) . However , best-in-category combinations that included the exceptionally broad but less potent 10E8 showed superior coverage with multiple bnAbs active at less restrictive thresholds . Neutralization curves for some bnAb/virus pairings can show incomplete neutralization of the genetically clonal virus population [65] . This suggests that a sub-population of virus is resistant to neutralization by the bnAb even at the highest concentrations tested . Given the importance of carbohydrates for many bnAb epitopes , post-translational glycan heterogeneity resulting from incomplete carbohydrate addition or modification may be an important contributing factor to such resistant sub-populations [68] . The inability to neutralize all variants would compromise the use of bnAbs for immunotherapy and may also impede the ability of bnAbs to protect against HIV acquisition . Hence , we investigated the extent of incomplete neutralization of clonal viruses by various bnAb combinations . We first analyzed neutralization curves for single bnAbs and bnAb combinations that were experimentally measured in the study by Kong et al . [60] . We could accurately predict the combination maximum percent inhibition ( MPI ) using the Bliss independence model on single bnAb MPI values ( Methods , Fig K in S1 Text , Pearson r = 0 . 9904 , difference between observed and predicted MPI: median = 0 . 1% , 95% CI = 0–4 . 5% ) . Using this model , we then predicted the MPI values for the 2 , 3 and 4 bnAb combinations composed of the best single bnAbs against the clade C panel . Experimental MPI values for single bnAbs are shown in Fig 6A ( see S1 Text for discussion on different assay starting concentrations for panel bnAbs ) , and the predicted MPI values for 2 , 3 and 4 bnAb combinations are shown in Fig 6B , 6C and 6D , respectively . Incomplete neutralization was observed against several viruses for all single bnAbs and was frequent for the V2- and V3-glycan bnAbs CAP256-VRC26 . 25 and 10-1074V , ( 56% and 44% viruses with MPI < 95% , respectively ) . A lower frequency of incomplete neutralization was observed with VRC07-523 ( 11% viruses with MPI < 95% ) and 10E8 ( 16 . 5% ) . Encouragingly , the fraction of resistant variants within a single virus preparation was predicted to decrease with increasing number of bnAbs in a combination , indicating that bnAbs tend to be complementary not only in terms of viral sensitivity at the population level , but in terms of the resistant subpopulations of post-translational Env variants . The 2 bnAb combination with the least fraction of viruses incompletely neutralized was VRC07-523 + 10E8 ( 2% ) , while VRC07-523 + CAP256-VRC26 . 25 , which had one of the best potency and breadth profiles , had 4% viruses with MPI < 95% . Consistent with the high levels of incomplete neutralization seen with the V2- and V3-glycan bnAbs , a higher extent of incomplete neutralization was predicted for CAP256-VRC26 . 25 + 10-1074V , where MPI <95% was seen for 18% of viruses . Strikingly , the 3 bnAb combinations had MPI < 95% for only 0 . 5–1% viruses ( n = 1–2 out of 200 ) , and the 4 bnAb combination never had MPI < 95% for any virus . The analysis of experimentally measured MPI from the Kong et al . study also showed similar patterns ( Fig L in S1 Text ) . Studies of passive bnAbs in humans aim to achieve plasma concentrations that for periods of time exceed 25 μg/ml , a dose commonly tested in our neutralization assays [60] . We therefore experimentally tested the extent of incomplete neutralization at concentrations of up to 100–200 μg/ml against a subset of 24 viruses that were selected based on incomplete neutralization at the lower doses tested ( Fig M in S1 Text ) . Most of these viruses were still incompletely neutralized at the highest concentrations tested ( only 1 out of 24 showed 95% or higher neutralization ) . We then estimated the best-fit Hill curves using data points below 25 μg/ml ( Methods , S1 Text ) and used these to predict neutralization at the highest concentrations tested for each of these high-concentration assays . The predictions were quite accurate ( average root mean square error = 6% , Kendall Tau p = 3 . 7 x 10−5 , Fig N in S1 Text ) . Thus , using this approach , we predicted the MPI at 100 μg/ml for all best-in-class bnAbs ( Fig N in S1 Text ) and their combinations ( Fig O in S1 Text ) for all 200 clade C panel viruses . As expected , the fraction of viruses with predicted neutralization less than 95% at 100 μg/ml was reduced compared to the values at 25 μg/ml . Still , we found substantial levels of incomplete neutralization at 100 μg/ml and these results qualitatively recapitulated the above patterns of MPI at 25 μg/ml for single bnAbs and for bnAb combinations . The metric instantaneous inhibitory potential ( IIP ) measures the log10 reduction in a single round of infection events in the presence of a drug . This metric correlates with clinical success of antiretroviral drug combinations , and can be used to characterize their efficacy [75] . Jilek et al . found that IIPave values ( average IIP during the dosing interval , given drug pharmacokinetics ) of 5–8 logs were necessary for successful antiretroviral therapy . Drug combinations in this range showed a reduction of viral load to <50 RNA copies/ml at 48 weeks in 70% or more of infected individuals . Applying their approach , we calculated the IIP values for the best-in-class single bnAbs and best bnAb combinations for the clade C panel . IIP values for single bnAbs were calculated using either the best-fit Hill curves of experimental neutralization data for the best-in-class bnAbs ( Fig 7 , S1 Text ) , or estimated Hill curves using IC50 and IC80 values ( Fig P in S1 Text ) ( with the former expected to yield more accurate predictions since IIP values are critically sensitive to neutralization close to 100% ) . Using BH model , we calculated the IIP values ( Methods ) for 2 , 3 and 4 bnAb combinations of the best-in-class bnAbs ( Fig 7 ) . Since IIP values depend on bnAb concentration , and precise doses and pharmacokinetics of bnAbs are still being established , we analyzed IIP at bnAb concentrations of 1 , 10 and 100 μg/ml . The 1 and 10 μg/ml concentrations are within the experimental assay range , whereas results for the 100 μg/ml dose are estimates obtained by extrapolation . The best-in-class single bnAbs had median IIPs of 0 . 4–2 . 8 across viruses , depending on the bnAb and concentration , with CD4bs bnAb VRC07-523 giving the highest value , followed by V3-glycan bnAb 10-1074V ( Fig 7 , Fig P in S1 Text ) . The best-in-category bnAb combinations showed higher median IIP values of 1 . 2–5 . 0 , 2 . 3–6 . 6 , and 3 . 5–8 . 1 for 2 , 3 and 4 bnAb combinations , respectively . The 2 bnAb combinations with highest IIP values consisted of VRC07-523 with either CAP256-VRC26 . 25 or 10-1074V , depending on the concentration . The 3 bnAb combinations with the highest IIP values were VRC07-523 + 10-1074V with either CAP256-VRC26 . 25 or 10E8 , with the latter combination having a slightly better median IIP at 100 μg/ml ( median IIP of 6 . 2 and 6 . 6 , respectively ) . Single bnAbs rarely had IIP > 5 , the level found to be critical for clinical success of antiretroviral drug combinations [75] , while 2 , 3 and 4 bnAb combinations had IIP > 5 for 0–50% , 1 . 5–79% , and 15–92% of viruses , respectively , depending on concentration . The median IIP of the best 3 bnAb combinations exceeded 5 only at 100 μg/ml , while the best 4 bnAb combination had median IIP > 5 at a lower concentration threshold of 10 μg/ml . The range of median IIP values for the best 4 bnAb combination ( 3 . 5–8 . 1 ) is comparable to the average IIP for some of the currently prescribed antiretroviral triple-drug combinations ( IIP ~ 3 . 5–12 ) [75] . We next systematically compared the best-in-category 2 , 3 , and 4 bnAb combinations to evaluate the benefit of having combinations with more total antibodies on overall performance using the metrics described above; namely the overall potency-breadth curves ( Figs 3 and 4 ) , the number of active bnAbs in the combination ( Fig 5 ) , the extent of incomplete neutralization ( Fig 6 ) , and IIP values ( Fig 7 ) . The relative impact of these metrics on clinical success is unknown and the relevance of each metric might differ for prevention versus treatment of HIV-1 infection , e . g . neutralization by multiple active bnAbs and IIP may be more relevant for latter . Working under the a priori hypothesis that an ideal combination should maximize performance using all four metrics , we chose VRC07-523 + CAP256-VRC26 . 25 , VRC07-523 + CAP256-VRC26 . 25 + 10-1074V and VRC07-523 + CAP256-VRC26 . 25 + 10-1074V + 10E8 as the best 2 , 3 , and 4 bnAb combinations for comparison , respectively . These combinations showed best or near best performance using all four metrics when compared with other combinations with same number of bnAbs . Using overall potency and breadth profiles , the best 3 and 4 bnAb combinations were significantly more potent than the best 2 bnAb combination , with a 2 . 6–3 . 1-fold more potent geometric mean IC80 ( Fig 8A , p < 0 . 0014 ) , and showed higher breadth of 97–99% versus 87% viruses neutralized at IC80 < 10 μg/ml , respectively . The best 3 and 4 bnAb combinations also demonstrated superior performance over the best 2 bnAb combination in limiting the extent of incomplete neutralization ( Fig 8B ) . The fraction of viruses predicted to have < 95% neutralization at 10 μg/ml for 3 ( 1 . 5% viruses ) and 4 bnAbs ( 0 . 5% viruses ) was significantly lower than that for 2 bnAbs ( 8% viruses , p < 0 . 0036 ) . Similarly , IIP for 3 and 4 bnAb combinations were significantly higher than the 2 bnAb combination ( Fig 8C , p < 2 . 5 x 10−16 ) , and showed significantly higher fraction of viruses above the clinically relevant threshold of 5 ( p < 1 . 2 x 10−10 , Fisher’s exact test ) . The best 3 and 4 bnAb combinations also showed significant improvement of coverage with at least 2 bnAbs active ( Fig 8D and 8G , 28–42% improvement in coverage , p < 7 . 7 x 10−10 ) . The main reason behind the poor coverage of viruses neutralized by 2 bnAbs in the best 2-bnAb combination was the limited breadth of CAP256-VRC26 . 25 , which was included for its potency when positive ( Fig 8E–8G ) . Four bnAbs were predicted to be similar to 3 bnAbs by some metrics , and significantly better by others . The best 3 and 4 bnAb combinations showed nearly identical distributions of IC80 values ( Fig 8A ) , and levels of incomplete neutralization ( Fig 8B ) . In contrast , the best 4 bnAb combination showed significantly higher coverage than the best 3 bnAb combination for both neutralization by at least 2 active bnAbs ( improvement in coverage 9 . 5% using activity threshold of IC80 < 10 μg/ml , p = 0 . 0001 ) , and by at least 3 active bnAbs ( improvement in coverage 47% , p = 1 . 9 x 10−21 , Fisher’s exact test ) ( Fig 8D and 8G ) . Also potentially relevant for success in therapeutic settings , the best 4 bnAb combination showed significantly higher IIP scores ( Fig 8C , p = 8 . 9 x 10−9 ) and significantly higher number of viruses with IIP > 5 than the best 3 bnAb combination ( 25% more viruses , p = 8 . 5 x 10−7 ) . These results indicate that 4 bnAb combinations may be more effective in preventing viral escape compared to 3 bnAb combinations .
The exceptional breadth and potency of a new generation of bnAbs offers new clinical opportunities for the prevention and/or treatment of HIV-1 infection . Two CD4bs bnAbs , VRC01 and 3BNC117 , have already initiated phase I clinical testing in infected subjects , and efficacy studies for the prevention of HIV-1 infection are planned [57 , 74] . The most effective approaches will likely employ combinations of bnAbs targeting multiple epitopes on HIV-1 Env to maximize potency and coverage and to impede escape , which may be particularly important in the case of immunotherapy . Prevention of sexual transmission of HIV-1 may represent a relatively easier target for success , as bnAbs at mucosal surfaces at the time of exposure need only to block the infecting virus , while therapeutic approaches need to contend with high levels of replicating virus , complex within-host viral diversity , and established latent viral reservoirs . Given the large number of bnAbs now available against multiple epitope regions of HIV-1 Env , it is of great interest to have experimental measures and predictive models that can be used for evaluating and selecting optimal combinations of bnAbs for clinical development for the prevention and/or treatment of HIV-1 infection . Among the bnAbs tested here , the best-in-class single bnAbs for potency and breadth against our panel of 200 clade C viruses were CAP256-VRC26 . 25 ( V2-glycan ) , 10-1074V ( V3-glycan ) and VRC07-523 ( CD4bs ) ( Fig 1 ) . While 10E8 was the only MPER-directed bnAb tested , it was previously shown to be the most broadly reactive and potent of the known MPER bnAbs against other virus panels [15] . To evaluate various combinations of bnAbs we developed a new model , the Bliss Hill ( BH ) model , and found it to more accurately predict the breadth and potency of antibody combinations than the additive model ( Fig 2 , Fig C in S1 Text ) . We applied the BH model to predict neutralization profiles of over 1 , 600 possible 2 , 3 , and 4 bnAb combinations against the 200 clade C viruses using experimental data from the testing of single bnAbs alone ( Figs 3 and 4 ) . These predictions allowed us to identify and compare best-in-category bnAb combinations . The overall potency and breadth of neutralizing activity significantly improved as the total number of bnAbs in the combination was increased from 2 to 3 , but not from 3 to 4 ( Figs 4 and 8 ) . Two best 2 bnAb combinations were identified that demonstrate superior performance in overall potency and breadth . While CAP256-VRC26 . 25 + 10-1074V was slightly more potent than CAP256-VRC26 . 25 + VRC07-523 , the latter combination exhibited better breadth , and thus may be preferred . The best 3 bnAb combination ( CAP256-VRC26 . 25 + VRC07-523 + 10-1074V ) benefitted from combining the complementary potent profiles of CAP256-VRC26 . 25 and 10-1074V , with the added potency and breadth of VRC07-523 . The best 4 bnAb combinations were significantly better than the best 2 but not 3 bnAb combinations . Together , these results demonstrate the substantial benefit bnAb combinations afford when selected to complement and optimize target epitopes , potency , and breadth of coverage . These parameters will be important to consider when selecting bnAb combinations for both prevention and immunotherapy of HIV-1 clade C infection . We note that 8 of the 15 bnAbs tested here did not show up as a component of best combinations . In most cases these bnAbs exhibited weaker potency and breadth of neutralization than bnAbs in the corresponding epitope class that did show up ( Fig 1A ) . An exception is VRC07 , which had a better profile than 3BNC117 , yet 3BNC117 and not VRC07 showed up as a component of best combinations . Another exception is PGT121 , which was marginally better than PGT128 , yet PGT128 and not PGT121 showed up in best combinations . In both of these cases the bnAb in best combinations ( 3BNC117 and PGT128 ) had slightly greater potency against sensitive viruses ( Table A in S1 Text ) . Our analyses further highlight that bnAb combinations , especially those to be used for treating established HIV-1 infection , can be selected to increase the probability of having at least two antibodies in the mixture active against a patient’s virus . While having an increased number of active bnAbs in a combination is desirable , our results illustrate the sobering limitations with even the best bnAbs currently available ( Figs 5 and 8 ) . For IC80 thresholds of 1–10 μg/ml , the percentage of clade C viruses neutralized was reduced to 44–95 . 5% when requiring a minimum of 2 bnAbs in the combination to be active . This coverage substantially increased when IC80 thresholds of 50 μg/ml or higher were considered ( Fig J in S1 Text ) . Therefore maintaining high in vivo antibody concentrations , in plasma and especially in infected tissues , may be key in therapeutic settings , and thus the tissue distribution and in vivo pharmacokinetics of individual bnAbs will be critical factors . The coverage of viruses by active antibodies naturally increased with the total number of bnAbs included in a combination , yet even for the best 4 bnAb combination , only 73 . 5% , 26 . 5% , and 2 . 5% of viruses would have either 2 , 3 , or all 4 antibodies active at a threshold IC80 titer of < 1 . 0 μg/ml , respectively . From these analyses , it becomes apparent that inclusion of a bnAb with better overall breadth ( such as 10E8 , Figs 1 and 5 , Fig J in S1 Text ) in a combination may be more advantageous than choosing the most complementary bnAbs with the highest potency . By further analogy to antiretroviral therapy , it is possible that at least 3 agents simultaneously active against the virus will be critical to avoid escape . For the prevention of HIV-1 infection , it may not be quite as critical to have multiple antibodies simultaneously active , as bnAbs at mucosal surfaces need only to block the transmitting virus at the time of exposure . Nonetheless , combinations of at least 2 or 3 bnAbs may provide an advantage for breadth and potency in preventing infection , and should enhance coverage against viral quasispecies from a chronically infected donor . We also considered the impact of bnAb combinations on limiting the extent of incomplete neutralization of HIV-1 Env pseudoviruses . Combinations with a higher number of bnAbs , in addition to improving breadth and potency across different viruses , also improved the capacity to completely neutralize the expressed forms of an Env within a genetically clonal virus population ( Fig 6 , Figs L and O in S1 Text ) . The experimental data suggests that the resistant sub-populations of virions for different bnAbs do not overlap substantially . This complementarity reduces the extent of incomplete neutralization shown by combinations with higher number of bnAbs , an important consideration when selecting optimal bnAb combinations for both prevention and treatment of HIV-1 infection . It should be noted that the pseudoviruses utilized in our study were produced in 293T cell lines , and thus may differ in glycan heterogeneity and susceptibility to incomplete neutralization compared to viruses derived from primary PBMC . However , a recent study comparing clonal viruses grown in either 293T or human PBMC found overall similar trends in levels of incomplete neutralization for individual bnAbs [65] . These data suggest that the complementarity of bnAbs to limit incomplete neutralization will likely prove to be effective for primary PBMC grown viruses as well . The slopes of in vitro neutralization curves for individual bnAbs have been shown to exhibit inherent variability , with bnAbs exhibiting slopes >1 . 0 predicted to have greater in vivo efficacy than classes of bnAbs having slopes ≤1 . 0 [71] . The metric instantaneous inhibitory potential ( IIP ) , which measures the Log10 reduction in infectious events in the presence of drugs/antibodies , is positively correlated with neutralization curve slopes , in that bnAbs with higher slopes are predicted to have IIP values that increase faster with concentration [76] . Here we calculated IIP values for best-in-category bnAb combinations as an opportunity to quantitatively compare their efficacy based on what is seen with antiretroviral drug combinations [75] . Such a comparison between bnAbs and standard antiretroviral drugs comes with several caveats . First , Env is much more variable than the targets of most antiretroviral drugs , making it essential to measure bnAb activity against a large panel of virus variants , whereas IIP values in the Jilek et al . study were calculated for a single virus . Second , because bnAbs can engage in Fc receptor-mediated effector functions [77 , 78] , the overall in vivo efficacy of bnAb combinations might be greater than the neutralization measured in vitro . Third , since IIP values depend on the concentration of drug , tissue-wide heterogeneity and pharmacokinetic profiles of bnAbs will be needed for accurate prediction . With these caveats in mind , we found that IIP values for the best 3 and 4 bnAb combinations compare favorably with those of several available antiretroviral drug combinations , for which an IIP threshold of 5–8 was found to correlate with clinical success [75] . While single bnAbs and 2 bnAb combinations had IIP < 5 for most viruses , we found that the best 3 and 4 bnAb combinations had median IIP values > 5 at concentration thresholds of 100 μg/ml and 10 μg/ml , respectively ( Fig 7 ) . Thus , using the Jilek et al . criterion , the 3 and 4 bnAb combinations could lead to favorable clinical outcomes , while single and 2 bnAb combinations are less likely to succeed . It must be emphasized that the results from our analyses do not imply that other bnAb candidates should not be further considered for inclusion in combinations for clinical testing . In fact V3-glycan bnAbs 10–1074 and PGT121 have either started or will soon initiate phase I clinical testing , respectively . Our results do , however , suggest favorable bnAb combinations for future studies , and provide a reasoned way to narrow the otherwise vast array of possible bnAb combinations . We provide modeling strategies that enable quantitative assessment of the neutralization patterns of combinations of bnAbs using several metrics , to better inform selection for clinical use . Yet these in vitro measures and modeling results are just a few of the parameters that must be considered when selecting optimal bnAb candidates . The stability , manufacturability , and in vivo pharmacokinetics , tissue distribution , and safety profiles are just a few additional key parameters that must also be evaluated when moving bnAb candidates forward in the clinical pipeline . Our study focused on HIV-1 clade C viruses as the predominant subtype in sub-Saharan Africa where bnAb clinical efficacy studies will likely be conducted , and is a dominant subtype globally . Some bnAb combinations may be more effective against other genetic subtypes , as bnAbs can exhibit variable levels of neutralization breadth among different clades of virus ( e . g . many V3-glycan antibodies exhibit more limited breadth against CRF01_AE viruses , and CAP256-VRC26 . 25 has limited breadth against clade B viruses ) [17 , 32] . Extensive data sets are available from the testing of individual bnAbs against large standardized panels of viruses from multiple subtypes , and the BH-model presented here may be utilized to thoroughly investigate the question of how viral clade impacts optimal bnAb combinations . We are developing a web-tool , CombiNaber , which will available on the Los Alamos HIV Immunology Database ( http://www . hiv . lanl . gov/content/sequence/COMBINABER/combinaber . html ) . This tool will predict bnAb combination neutralization results from single bnAb neutralization data using either BH or additive models and perform systematic analysis to provide the user with the best candidate combinations for their panel ( S1 Text ) . In summary , we have assessed optimal bnAb combinations predicted to have greatest success in the prevention and treatment of infection by HIV-1 clade C , taking into account multiple metrics . In addition to evaluating overall potency and breadth , we have also taken into account the number of active bnAbs within a given combination , the impact of combinations in limiting the extent of incomplete neutralization , and to calculate the IIP of bnAb combinations . These latter metrics may be of critical importance when considering the use of bnAbs for the treatment of HIV-1 infection , as they directly relate to confronting the ability of virus to escape from selective immune pressure . Our results indicate that for both the prevention and treatment of HIV-1 infection , combinations with higher numbers of bnAbs are advantageous in providing increased potency , breadth , complete neutralization , and active coverage . Given the tremendous resources required to take each single bnAb forward into clinical testing , our results outline important parameters that can inform the selection of bnAbs with the best indicators of success for clinical development , and stresses the importance of considering the behavior of bnAb combinations early in planning stages .
This was a non-randomized laboratory study designed to investigate the breadth and potency of HIV-1 bnAbs against a panel of 200 clade C HIV-1 Env pseudoviruses , and to develop mathematical models to predict combinations of 2 , 3 , or 4 bnAbs that would exhibit enhanced breadth , potency , extent of complete neutralization , and IIP relative to single bnAbs . Fifteen recently described bnAbs targeting four distinct epitopes on HIV-1 Env were each tested against the panel pseudoviruses in vitro to determine IC50 and IC80 titers and MPI . All neutralization assays were performed in duplicate and without blinding . Neutralizing antibody titers of bnAbs were determined using a luciferase-based assay in TZM . bl cells ( NIH AIDS Research and Reference Reagent Program ) as previously described [79 , 80] . Unless stated otherwise , starting concentrations of individual bnAbs ranged from 10–50 μg/ml depending on the available supply at the time of testing . BnAbs were serially diluted seven times using 5-fold titration series . The concentration range tested for each bnAb is indicated in Table A in S1 Text . All assays were performed in a laboratory meeting GCLP standards . A panel of 200 clade C HIV-1 Env pseudoviruses was utilized to assess the potency and breadth of bnAb neutralization activity . Functional Env clones were derived from individuals in acute/early stages of infection from South Africa ( 65% ) , Tanzania ( 14% ) , Malawi ( 11 . 5% ) , Zambia ( 6 . 5% ) , and Botswana ( 3% ) collected over 12 years ( 1998–2010 ) . All Envs were from heterosexual transmissions except for a single case of breastfeeding transmission . The majority of Envs exhibit a Tier 2 neutralization phenotype ( 75% , n = 150 ) , with 1% classified as Tier 1A , 8 . 5% classified as Tier 1B , and 15 . 5% classified as Tier 3 [81] . Pseudovirus stocks were generated via transfection in 293T/17 cells ( ATCC , Manassas , VA ) and titrated using TZM . bl cells as previously described [82] . A panel of 15 particularly broad and potent human monoclonal antibodies was selected based on prior data from testing against large multiclade panels of HIV-1 pseudoviruses . In some cases we included somatic variants or newly engineered variants that exhibited enhanced activity over parental wildtype bnAbs ( i . e . 10-1074V , VRC07-523 , CAP256-VRC26 . 25 ) . Importantly , we included bnAbs that are currently in human clinical trials ( VRC01 , 3BNC117 , 10–1074 ) or are advanced candidates for clinical testing ( PGT121 , 10E8 , PGDM1400 , CAP256-VRC26 . 25 ) . Antibodies were generated in the laboratories of D . Burton at The Scripps Research Institute ( PGT145 , PGMD1400 , PG9 , PGT121 , PGT128 ) , M . Nussenzweig at The Rockefeller University ( 10–1074 , 10-1074V , 3BNC117 ) , or the NIH Vaccine Research Center ( CAP256-VRC26 . 08 , CAP256-VRC26 . 25 , VRC01 , VRC07 , VRC07-523 , VRC13 , 10E8 ) . VRC01 and VRC07 are CD4bs bnAbs of the same lineage [69] . VRC07-523 is an engineered clonal variant of VRC07 with increased potency and breadth [23] . Of note , VRC07-523 was made with a two amino acid mutation in the Fc domain ( M428L/N424S ) to increase affinity for the FcRn and therefore increase circulating in vivo half-life [83]; these mutations do not affect antibody-mediated neutralization . VRC13 is a CD4bs antibody that is distinct from the VRC01-class of antibodies in that it contacts gp120 primarily via CDR binding loops [70] . 10–1074 and PGT121 are clonal variants from the same donor [17] . 10-1074V is a variant of parental 10–1074 in which six complex-type glycan-contacting residues in IgH have been substituted with those from bnAb PGT121 . For theoretical derivations of models , see S1 Text . The additive model [60] predicts combination IC80 as IC80comb=1/ ( 1/IC80A+1/IC80B+… ) , where IC80A , IC80B , … are the single bnAb scores . The equation for combination IC50 is similar using single bnAb IC50 . The Bliss-Hill model involves estimating single bnAb neutralization curves using Hill functions , f ( c ) = cm/ ( km + cm ) , where c = bnAb concentration , k = IC50 , and m = log ( 4 ) /[log ( IC80 ) –log ( IC50 ) ] . The combination neutralization , using the Bliss Independence model , is f = 1 − ( 1 − fA ) ( 1 − fB ) ( 1 − fC ) … where fA ( c ) , fB ( c ) , fC ( c ) , … are the single bnAb neutralization functions and c is the bnAb concentration . This equation is solved for the combination IC50/IC80 ( we use Brent algorithm[84 , 85] implemented in Scipy [86] ) . Treatment of single bnAb IC50/IC80 values above or below experimental thresholds is detailed in the S1 Text . For combinations with multiple bnAbs targeting the same epitope , the combined neutralization function of such bnAbs is calculated using fA ( c ) = ( gA1 ( c ) +gA2 ( c ) +… ) / ( 1+gA1 ( c ) +gA2 ( c ) +… ) , where gAi ( c ) =fAi ( c ) / ( 1−fAi ( c ) ) and fAi ( c ) are Hill curves for each of the bnAbs A1 , A2 , … The Bliss independence model equation is used with the neutralization functions fA ( c ) , fB ( c ) , fC ( c ) , … for each epitope to get neutralization by the combination . Given the experimental or predicted MPI values for single bnAbs at a given concentration , fA , fB , fC , … , the combination MPI value was predicted as f = 1 − ( 1 − fA ) ( 1 − fB ) ( 1 − fC ) … IIP is defined as IIP = −Log10 ( 1 − f ( c ) ) , where f ( c ) is the neutralization by a single bnAb or bnAb combination at concentration c . The Hill functions for neutralization by single bnAbs were calculated from IC50 and IC80 values , or by fitting experimental neutralization curves ( S1 Text ) . For IIP of combinations , best-fit single bnAb neutralization functions together with BH model were used . All statistical analyses were performed using the Stats module in Scipy [86] . Non-parametric tests were preferred and two sided p-values are reported . False discovery rates ( q-values ) were calculated by using qvalue package for Python ( https://github . com/nfusi/qvalue ) , based on the calculations outlined in reference [87] .
|
In recent years , a new generation of monoclonal antibodies has been isolated from HIV-1 infected individuals that exhibit broad and potent neutralizing activity when tested against diverse strains of virus . There is a high level of interest in the field in determining if these antibodies can be used to prevent or treat HIV-1 infection . Because HIV-1 is adept at escaping from immune recognition , it is generally thought that combinations of multiple antibodies targeting different sites will be required for efficacy , much the same as seen for conventional antiretroviral drugs . How many and which antibodies to include in such combinations is not known . In this study , a new mathematical model was developed and used to accurately predict various measures of neutralizing activity for all possible combinations having a total of 2 , 3 , or 4 of the most promising antibodies . Through a systematic and comprehensive comparison , we identified optimal combinations of antibodies that best complement one another for enhanced anti-viral activity , and therefore may be most effective for the prevention or treatment of HIV-1 infection . These results provide important parameters that inform the selection of antibodies to develop for clinical use .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"antimicrobials",
"antiretrovirals",
"complement",
"system",
"medicine",
"and",
"health",
"sciences",
"immune",
"physiology",
"body",
"fluids",
"pathology",
"and",
"laboratory",
"medicine",
"pathogens",
"drugs",
"immunology",
"microbiology",
"retroviruses",
"viruses",
"immunodeficiency",
"viruses",
"clinical",
"medicine",
"rna",
"viruses",
"pharmacology",
"antibodies",
"microbial",
"genetics",
"immunotherapy",
"immune",
"system",
"proteins",
"proteins",
"medical",
"microbiology",
"hiv",
"microbial",
"pathogens",
"hiv-1",
"blood",
"plasma",
"hematology",
"pharmacokinetics",
"immune",
"system",
"biochemistry",
"blood",
"anatomy",
"clinical",
"immunology",
"virology",
"viral",
"pathogens",
"physiology",
"genetics",
"microbial",
"control",
"biology",
"and",
"life",
"sciences",
"antivirals",
"lentivirus",
"organisms"
] |
2016
|
Optimal Combinations of Broadly Neutralizing Antibodies for Prevention and Treatment of HIV-1 Clade C Infection
|
Bacterial Toxin-Antitoxin systems ( TAS ) are involved in key biological functions including plasmid maintenance , defense against phages , persistence and virulence . They are found in nearly all phyla and classified into 6 different types based on the mode of inactivation of the toxin , with the type II TAS being the best characterized so far . We have herein developed a new in silico discovery pipeline named TASmania , which mines the >41K assemblies of the EnsemblBacteria database for known and uncharacterized protein components of type I to IV TAS loci . Our pipeline annotates the proteins based on a list of curated HMMs , which leads to >2 . 106 loci candidates , including orphan toxins and antitoxins , and organises the candidates in pseudo-operon structures in order to identify new TAS candidates based on a guilt-by-association strategy . In addition , we classify the two-component TAS with an unsupervised method on top of the pseudo-operon ( pop ) gene structures , leading to 1567 “popTA” models offering a more robust classification of the TAs families . These results give valuable clues in understanding the toxin/antitoxin modular structures and the TAS phylum specificities . Preliminary in vivo work confirmed six putative new hits in Mycobacterium tuberculosis as promising candidates . The TASmania database is available on the following server https://shiny . bioinformatics . unibe . ch/apps/tasmania/ .
Toxin-antitoxin systems ( TAS ) were originally known for their involvement in a process known as post-segregational killing ( PSK ) , a plasmid maintenance mechanism based on the differential decay of the products of two plasmid-encoded genes: a toxin gene and its antagonistic antitoxin [1–3] . The current model for TA activation is that under normal growth conditions , the antitoxin efficiently counteracts the toxin negative effects . Yet , under certain stress situations the toxin is released , thus leading to a transient metabolic shutdown and growth arrest . TAS can be acquired from mobile genetic elements such as plasmids or phages , and are also present in core genomes [4] . The ability to be transferred both vertically and horizontally renders any phylogenetic analysis difficult and little is known about the distribution of the TAS among phylum . The work by Wood and his group with artificial toxin derived from endogenous antitoxins ( and vice-et-versa ) highlights the plasticity of ubiquitous TAS and the complexity of their origins [5] . Since the discovery of the PSK , the growing list of TAS related studies has led to a list of more complex ( and sometimes controversial ) roles for TAS . To name a few , TAS are involved in cell suicide following a phage abortive infection [6] or nutritional stress [7] , in regulating biofilm dynamics [8] and in bacterial persistence [9–11] . Some studies even show that chromosomal TAS can counteract PSK [12] . All TAS toxins are proteins that target a variety of essential biological processes ( e . g . , membrane integrity , translation , replication ) and they are divided in groups based on the nature and mechanism of action of the cognate antitoxin [13] . Currently there are six types of TAS described in the literature . In the type I family , an ncRNA antitoxin ( generally in antisense of the toxin gene ) inhibits the translation of the toxin mRNA . Typical examples of type I TAS are the hok/sok systems [3] . Type II TAS , which constitute the most commonly studied family , are composed of an antitoxin protein that binds directly to the toxin protein and inhibits its activity . Some toxins target DNA replication [14] , or affect the cell membrane integrity by phosphorylating peptidoglycan precursors [15] , while others have acetyltransferase activity [16 , 17] , or are kinases that target the translation elongation factor EF-Tu [18 , 19] . Yet , many type II toxins are ribonucleases that i ) cleave target mRNAs in a ribosome-dependent manner [20] or ii ) cleave free mRNA [21] , and they can also target non coding RNA [22 , 23] . Type III is a more recent addition , with ToxN/ToxI as a reference member [6] and more families added later by the pioneering work from Salmond’s group [24] . The type III toxin is a nuclease that cleaves a broad range of mRNA and RNA , while the antitoxin is a small non-coding RNA that binds directly to the toxin protein , thus inhibiting its action . In type IV there is no direct interaction between the toxin and antitoxin components . Here the antitoxin counteracts the toxin by competing with its targets , like cytoskeleton proteins [25] . Type V currently has so far only a single member , the GhoT/GhoS system [26] , in which the antitoxin itself is an endoribonuclease protein that targets the toxin mRNA [27] . Type VI TAS are grouped TA systems that involve a third partner . This partner promotes the toxin decay in trans [28] or the antitoxin stability in cis [29] . The ubiquity of the TAS and the diversity of their functions open question about their potential interactions in trans . Numerous publications suggest that it may be between noncognates from same families [12 , 30–32] or between noncognates from different TAS types [33 , 34] . On the other hand , other data suggest isolated TA units [35] . The Laub group used co-evolution study of protein-protein interactions to show that paralogous ParD/ParE pairs are highly specific in their operon cognates [36] . Nevertheless , their model of promiscuous intermediates still leaves room for interactions in trans . Finally , most of the TAS studies focus on the canonical TAS that are usually found in a configuration with the antitoxin gene being upstream of the toxin gene , with few TAS families presenting a reversed order [4 , 37] . Alternative structures have been mentioned by van Melderen and her group , which highlights the existence of orphan TA loci [38] . So far , TAS screening approaches usually skip the multigene TA systems , despite known tripartite TAS [29 , 39–41] and TAS modules inserted within operons [7 , 42] . Validated and predicted TAS are collected in the TADB2 database [43] . TADB2 focuses mainly on type II TAS that were mined from the literature ( N = 105 TA loci ) and from previous published screens ( N = 6088 TA loci ) extracted from 870 bacteria and archaea genomes . The 6088 TA loci were predicted using Blastp on 126 genomes [37] or PSI-Blast searches with validated literature datasets [44] . A few of them were additionally combined with known operon structure obtained from STRING [45] . TADB2 also includes a search tool called TAFinder ( http://202 . 120 . 12 . 133/TAfinder/index . php ) combining homologous search and operon structure module filters [43] . TAFinder uses Blastp searches with the TADB2 dataset and HMM searches with 108 Toxin HMMs and 201 Antitoxin HMMs to select the TA loci . These loci are then filtered using protein size ( by default >30aa and <300aa ) and intergenic distance ( by default from -20nt to +150nt ) . TADB2 and TAFinder are very stringent in their criteria to minimize false positives . Our primary goal is to provide the microbiology community with a largely extended database of the type I to type IV ( and potentially type V to VI as side hits ) toxin and antitoxin loci . We also propose an objective annotation of the TA independently of the cognate components . With the current nomenclature based on the identification of the toxin cognate , the antitoxin would “inherit” the toxin family name . This can be misleading and ignores the modularity of TA cognates . Instead , our method allows the discovery of unexpected combinations of toxin and antitoxin families . We include a “guilt-by-association” approach in our pipeline , similarly to methods developed by others [38 , 44] . The large dataset of genomes enables us to apply phylogenetic comparisons .
The EnsemblBacteria database ( Rel . 33 Nov . 2016 ) contains N = 41'610 genomic assemblies that correspond to N = 23'921 unique taxonomic identifiers ( taxonomy ids ) , indicating a high degree of redundancy in the assemblies . At least one hit was found for N = 40'993 assemblies present at least one hit with the TASmania HMM scan , of which N = 22'950 correspond to unique taxonomy ids . A closer look at the taxonomy ids shows that 40% of the genomic assemblies belong to the Proteobacteria phylum and 34% to the Firmicutes phylum , these two groups making up three quarters of the database ( S1 Fig ) . The Actinobacteria and Bacteroidetes phyla represent 12% and 3% of the assemblies , respectively . The remaining 11% of the assemblies correspond to N = 72 other phyla and/or unclassified bacteria . TASmania is based on the pipeline summarized in Fig 1 . Briefly , the strategy relies on TA HMM profiles built from an initial set of proteins annotated with TA InterPro ( IPR ) ( S1 Table ) . This critical initial set is a known limitation affecting other methods like TADB2 or TAFinder and might lead to missing families . From the protein clustering we obtain N = 369 toxin HMM profiles ( with at least 10 unique protein sequences ) and N = 305 antitoxin HMM profiles ( with at least 10 unique protein sequences ) . From the theoretical N = 369*305 = 112’545 possible combinations in canonical AT/TA operons , we only observe N = 2’600 HMM profile combinations . We combine the HMM profiles into larger HMM clusters by similarity . This allows to decrease the number of toxin HMM profiles ( N = 369 ) and antitoxin HMM profiles ( N = 305 ) combinations to plot . When using clustered HMM profiles ( N = 152 clusters for toxin HMM profiles and N = 130 clusters for antitoxin HMM profiles ) , we go from theoretical N = 152*130 = 19’760 combinations to only N = 1’567 observed pairs . Thus , grouping the HMM profiles into clusters allows a decrease of ∼40% in the number of combinations and reduces potential redundancy of certain HMM profiles . We always keep the link between HMM profiles and their clusters . We call each of these clusters TASMANIA . T1 to TASMANIA . T152 ( T1 to T152 ) for the toxins , and TASMANIA . A1 to TASMANIA . A130 ( A1 to A130 ) for the antitoxins . We enhance the value of the putative TA hits by structuring the loci into pseudo-operons and including phylogenetics information . A given combination of two clusters within pseudo-operon is dubbed “popTA” . Finally , for reverse-compatibility with the current TA nomenclature , we also include a nearest Pfam annotation for a given HMM profile and cluster ( S2 Table ) . More details are given in Materials and Methods section . After scanning EnsemblBacteria with the HMM profiles , we obtain N = 1'155'070 putative toxin gene hits , corresponding to N = 228'074 unique toxin protein sequences; and N = 1'283'761 putative antitoxin genes hits , corresponding to N = 270'733 unique antitoxin protein sequences . In total , the putative toxin or antitoxin hits correspond to N = 2'298'903 unique pseudo-operons containing TA modules ( including redundant ones ) . A phylogenetic analysis of the TA hits distribution shows that Cyanobacteria are very TA-rich and are the most common phylum in the top 200 most TA-enriched genomes ( S2 Fig ) . Our method does not use a protein length filtering , thus allowing for discovery . The protein length distribution of the putative toxin and antitoxin hits confirms previous results [46] , as shown in Fig 2 . We can see that the absence of length thresholding allows the discovery of more putative TAs ( right tail of the distributions ) . When focusing on the canonical—i . e . , the two-gene T->A or A->T modules—the protein length distribution mimicks the previously published data by narrowing the proteins length into the 30–210 residues window used by [46] . This effect is most probably due to the bias of annotation favouring AT/TA modules . However , as can be seen in green on Fig 2 , some toxin and antitoxins of the canonical AT/TA modules exceed the 210 aa limit from [46] and 300 aa from [43] . The distribution of the pseudo-operon structures of the HMM scan hits in Fig 3A i ) indicates that TAS can be multi-cistronic organisation , not uniquely bi-cistronic . ; ii ) confirms that the A->T module type is more common than the T->A type and iii ) shows the existence of many “orphan” hits , i . e . , a toxin or antitoxin gene as single-gene pseudo-operon . These hits could be either true orphaned T’s or A’s , and/or false positives and/or could be due to the mis-annotation of the operons and/or potentially type I or type III toxins as we cannot detect the ncRNA with our current method . The prevalence of the A->T type is highlighted when comparing only canonical two-genes structures ( Fig 3B ) . We compared TASmania putative TAS hits with the ones proposed by TAfinder . Since we cannot download the entire datasets from this webtool , we used a few reference model strains as a proof of principle: Mycobacterium tuberculosis H37Rv ( M . tuberculosis ) , Mycobacterium smegmatis MC2155 ( M . smegmatis ) , Caulobacter crescentus CB15 ( C . crescentus ) and Staphylococcus aureus NCTC8325 ( S . aureus ) . The putative hits were manually downloaded from these websites and compared against TASmania hits ( Fig 4 ) . These data show that TASmania covers most of TAfinder hits and gives many other putative candidates ( Fig 4 and S3 Table ) . Looking closely at the TAfinder hits missed by TASmania , the module Rv2653c/Rv2654c in M . tuberculosis H37Rv seems to encode prophage proteins , with no IPR annotation , hence their absence from TASmania ( S4 Table ) . This module could be a real TAS and if this hypothesis happens to be confirmed experimentally , they will be added to TASmania profiles . The remaining TAfinder hits missed by TASmania fall into the transcriptional regulators ( e . g . , ArsR , LysR , TetR , MarR ) , transposases and uncharacterized proteins categories . It is difficult to evaluate if these loci are true TA missed by TASmania or false positives from TAfinder . Although it is technically not possible to assess the overall rate of false positives in the TASmania-specific hits , the in vivo analysis performed on some TASmania candidates shows promising results . We investigated whether some of the putative TA systems of M . tuberculosis identified by TASmania were indeed bona fide new TA systems . We selected 11 putative TA systems that are not found by TAfinder or TADB2 and asked whether expression of their putative toxins could affect growth of the closely related M . smegmatis strain MC2155 . Putative toxin encoding genes were cloned into the pLAM12 vector under the control of an acetamide inducible promoter , transformed into MC2155 and incubated for 3 days at 37°C on kanamycin agar plates without or with 0 . 2% acetamide inducer . Under these conditions we found that six out of eleven putative toxins affected M . smegmatis growth , with four of them exhibiting a robust toxicity , namely Rv0078A , Rv0366c , Rv2016 and Rv2514c , and two only inducing a slow growth phenotype , namely Rv0207c and Rv0269c ( Fig 5 ) . These results suggest that these six genes could encode toxins of new or uncharacterized TA systems in M . tuberculosis , thus further extending the long list of TA in this bacterium [47] . In order to investigate whether these toxic genes are part of bona fide TA systems , the six corresponding TA operons composed of the putative toxin encoding genes and of the putative cognate antitoxin genes were cloned in pLAM12 vector , transformed in MC2155 and their effect on bacterial growth was monitored as in Fig 6 . Note that 4 out of these 6 putative TA systems are in antitoxin first , toxin second ( AT orientation ) , and the last two in toxin first , antitoxin second gene organization ( TA orientation ) ( Fig 6 ) . We found that in all cases bacterial growth could be rescued by the presence of the putative antitoxin genes in all cases , although to various levels ( Fig 6 ) . Rv0078B/Rv0078A ( A->T ) and Rv2515c/Rv2514c ( A->T ) operons both support the in silico prediction of putative TAS: the high toxicity of the putative toxin expressed alone is inhibited by the co-expression of the putative cognate antitoxin . Rv0078B/Rv0078A ( A->T ) is a very interesting case . Remarkably , although Rv0078B acts as an antitoxin and rescues the toxicity of Rv0078A , TASmania HMM scan flags Rv0078B as a putative toxin from the cluster T52 ( nearest Pfam SymE_toxin type I ) . Rv0078A is also flagged as a toxin via its IPR annotation ( IPR014942 AbiEii toxin type IV ) . This unexpected predicted “TT” pair could be the signature of a new family of TAS , with Rv0078B being a potential example of a TAS cognate that “switched” function [4] . T52 hits like Rv0078B are found in diverse pseudo-operons structures , although T52 should in theory be a toxin of type I and therefore rather appears in pseudo-operons looking like orphans ( “T” ) . M . tuberculosis presents only a single pseudo-operon with T52 hit , while it is absent from M . smegmatis and appears in N = 34 different loci in Thalassomonas actiniarum . In the latter , T52 hits are all orphan toxins , suggesting that , in this species at least , T52 looks more like a classical SymE-like toxin type I ( the antitoxin cognate being a ncRNA , it cannot be annotated currently by TASmania ) . On the other hand , Rv0208c/Rv0207c and Rv0269c/Rv0268c are both putative TAS operons with the toxin exhibiting a weak toxicity when expressed in M . smegmatis . This could be due to various reasons , including missing/divergent M . tuberculosis toxin targets in M . smegmatis , potential cross-interactions in trans with the cognate antitoxins of other similar TAS , a poorly expressed toxin in M . smegmatis , a non-essential toxin target or a target not required under the growth conditions tested . Rv0269c/Rv0268c is a TAS in T->A conformation , with the antitoxin Rv0268c annotated as a A24 ( nearest Pfam family PhdYeFM_antitox ) , while Rv0269c is proposed as a guilt-by-association toxin . In M . tuberculosis , only Rv0268c is found as a A24 hit , but many other loci ( N = 12 ) belong to PhdYeFM_antitox clusters ( A24 , A9 , A27 , A81 , A94 , A100 ) . Rv0269c/Rv0268c is interesting since it is in a T->A configuration , which is unusual for the PhdYeFM antitoxin . Homologies suggest that Rv0269c is related to proteins with a DNA polymerase/primase/ligase domain . Therefore Rv0269c/Rv0268c is a puzzling pair worth deeper investigation . Whether these two systems are bona fide TA pairs remains to be investigated . Rv0367c/Rv0366c ( A->T ) is a putative TA couple where both loci are hit by TASmania HMM profiles belonging to the A123 ( nearest Pfam ParD_like ) and T70 ( nearest Pfam Zeta_toxin ) clusters , respectively . The combination A123 . T70 ( nearest Pfam ParD_like . Zeta_toxin ) could represent a new TAS family , since the canonical zeta toxin is described in the literature as the cognate of epsilon antitoxin . In the TASmania database , most of T70 clusters hits appear as paired with A49 and A123 clusters ( both with nearest Pfam ParD_like ) . Finally , in the case of Rv2016 ( T144 nearest Pfam HicA_toxin ) , which is highly toxic when expressed in M . smegmatis , we could also detect an effective but very limited suppression of toxicity in the presence of the putative antitoxin gene Rv2017 ( A32 nearest Pfam HTH_3 ) . Whether this is due to the genetic organization with the toxin and/or to the lack of a chaperone partner is unknown [48] . All together , these experimental validations of TASmania in silico predictions show how our database can be a very powerful tool in discovering unexpected TAS families . For clarity and reproducibility , we focus on the two-genes modules to study the toxin and antitoxin clusters co-occurrence within the pseudo-operons , i . e . , popTAs . In order to minimize bias introduced by the overrepresentation of certain phylogenetic groups over others ( see S1 Fig ) , we apply a correction to cluster counts with the weight of each phylum in the database . Out of the theoretical N = 152*130 = 19'760 possible combinations , we find N = 1'522 popTAs , independently of their T->A or A->T orientation; and N = 1'567 popTAs if the orientation is taken into account . The popTA features highlight the potential issues that the TA annotations can produce . In the current way toxins and antitoxins are annotated , namely by giving priority to the toxin for naming the antitoxin , many inconsistencies are created . For example in M . tuberculosis , several antitoxins are annotated as a “VapB” while the TASmania HMM profiles hitting these antitoxins belong to diverse Pfam families like PhdYeFM , ribbon-helix-helix ( RHH ) , CopG or MazE ( Table 3 ) . Therefore , we here propose a more objective and systematic annotation of the toxins and antitoxins based on cluster identifiers , rather than misleading functional names inferred from cis-occurrence . The guilt-by-association approach [38 , 44] allows the discovery of previously undescribed protein families . This strategy relies on the non-targeted cognate loci of TASmania hits in two-genes operons—“xT” , “Tx” , “Ax” and “xA” . For convenience we focus on xT/Tx starting by collecting and pooling the protein sequences corresponding to the “x” cognates of toxins HMM hits in TASmania . These x cognates are loci that do not have any previous IPR annotation corresponding to known TAS families , nor are they picked up by any of HMM profiles . But they have a toxin as direct neighbour gene , identified by TASmania HMM profile ( s ) and/or direct IPR annotation . As a proof of principle , we screen all the “x” genes having as neighbour a toxin T cognate , in two-genes pseudo-operons “xT” and “Tx” ( we dub these two types of pairs as “popTx” , independently of the orientation ) . We obtain N = 24’377 unique protein sequences that could potentially belong to new uncharacterized antitoxins . We build and cluster the HMM profiles using the same procedure as for TASmania ( see Methods below ) . These putative new antitoxin families are summarized in Table 4 . Many x antitoxins are annotated as nearest to Pfam HTH_3 ( A*1 and A*8 ) and RHH_1 ( A*27 ) features , for instance in the following pairing types: HigB_toxin . HTH3 , HipA_C . HTH_3 , HTH_3 . HipA_C , ParE_toxin . HTH_3 , RelE . HTH_3 and RHH_1 . ParE_toxin . These HTH_3 and RHH_1 Pfam annotations are too general to directly infer functional clues for these putative new antitoxin families but they are good candidates to discover new antitoxin families . Each of the different popTx groups derived from these HTH_3 and RHH_1 combinations would require further characterization based on cognates alignments and structural analyses for example . Some other interesting x antitoxins are the ones with nearest Pfam annotations of Colicin_Pyocin ( A*190 , as in Colicin_Pyocin . YafQ_toxin— . A*190 . T4 ) , VraX ( A*371 , as in VraX . PemK_toxin—A*371_T143 , specific to Staphylococcus ) , Glyoxalase ( A*77 , as in YafQ_toxin . Glyoxalase—T32 . A*77 ) , Antirestrict ( A*237 , as in Antirestrict . CbtA_toxin—A*237 . T3 ) and Response_reg ( T5 , as in Cpta_toxin . Response_reg—T5 . A*2 ) . VraX ( IPR035374 ) and Glyoxalase ( IPR004360 ) are both involved in antibiotics resistance pathways . The VraX-like putative antitoxins seem to originally be derived from a phage protein . Intriguingly , the VraX . PemK pair is not found in the reference Staphylococcus aureus subsp . aureus NCTC 8325 while it is present in other S . aureus strains ( S4 Fig ) . Colicin_Pyocin and Response_reg families could potentially give some clues in the evolution of the TAS . The Colicin_Pyocin ( IPR000290 ) family contains the immunity proteins and/namely members of the effector-immunity system , which is a two-component genetic system ( TCS ) similar to the TAS but where both cognates are secreted in order to protect the bacteria itself and its clonemates [50] . Response_reg ( IPR001789 ) belongs to another two-component genetic system called “two-component signal transduction system” , which also presents similarities with the TAS . Previous publications have already suggested potential interplay and/or homology between different TCS [51 , 52] . Finally , annotations from other x antitoxins indicate that many more popTx could be promising candidates: Ap_endonuc_2 ( as in AP_endonuc_2 . ParE_toxin ) and Phage_integrase ( as in CcdB . Phage_integrase , Phage_integrase . PemK_toxin or Phage_integrase . Zeta_toxin ) . These two candidates highlight the link between the TAS and the phages . More investigation will be needed to confirm these candidates as functional new antitoxin families .
TASmania is a new resource for the discovery of toxin-antitoxin in known bacterial genomes . Even though it is based on existing protein domain descriptions , its flexibility allows for the uncovering of potential new combination of pairs and totally new families of toxins and/or antitoxins using a guilt-by-association strategy . The experimental validation in vivo of several predicted TAS confirms the potential of this resource for the identification of TAS .
The global strategy is to build an updated list of toxin and antitoxin HMM profiles and scan a local version of the EnsemblBacteria database ( N>41K assemblies ) with thoses HMM profiles . To achieve this , we have downloaded EnsemblBacteria ( release 33 , November 2016 ) [55] , updated its InterPro ( IPR ) ( version Nov 2016 ) [56] annotation and applied a pseudo-operon annotation with arbitrary definition where a maximal intergenic distance of 100 bp is applied , as shown in Fig 1 . In parallel , we perform HMM profiles comparison in order to reduce the number of profiles , using the Profile Comparer program PRC ( v1 . 5 . 6 ) [59] . Combining the PRC results with the NetworkAnalyzer [60] in CytoScape ( 3 . 5 ) [61] network analysis , we select the first PRC E-value of 10−12 where the number of connected components ( CC ) ( i . e clusters of HMM profiles ) is reaching the plateau . For clarity and continuity with previous TAS annotations found in the literature , each TASMANIA cluster identifier is given the nearest corresponding Pfam family names ( release 31 . 0 ) to which the TAS scientific community is used to . The “nearest” Pfam annotation is performed as follows: using the PRC program for profile-profile comparison ( default settings ) , each TASmania HMM profile is scanned against Pfam database . The best Pfam profile match for each TASmania HMM profile ( i . e . , the lowest E-value ) is selected and the identifier of this Pfam annotation is used as the Pfam equivalent of the given TASmania HMM profile . On top of the HMM profile annotation , the TASmania clusters are also attributed a Pfam annotation . For each TASmania cluster we attribute the common profile Pfam annotation when there is no ambiguity . In cases of heterogeneity ( more than one Pfam annotation per cluster ) , the Pfam match with the smallest E-value is selected . But in all cases , the individual Pfam annotation of each TASmania HMM profile is kept and shown in S2 Table for methodology coherence . We used the word”nearest” to emphasize the potential issues of such equivalences . The final TASmania database contains: i ) the putative hits from the HMM scan; ii ) the genes annotated with a reference TAS IPR and that were filtered out due to the small size of their proteins clusters ( less than 10 unique sequences ) when building the HMM profiles; iii ) the guilt-by-association “x” cognates ( see S5 Fig ) . We also add an extra annotation of the putative TAS hits by analysing the cis-occurrence—within a same pseudo-operon—of toxins and antitoxins clusters: we call these T<->A clusters associations “popTA” groups . To construct these popTAs we first define the pseudo-operon structures using a relaxed model containing one , two or more genes . Our pseudo-operon model is simply based on an arbitrary intergenic distance -100nt < = D < = +100nt between adjacent genes oriented in the same direction ( strand ) , keeping in mind that there is no "one-size-fits-all" D value . We selected the arbitrary value of 100nt based on some previous studies of intergenic distances distributions [62] . The pipeline is summarized in the Fig 1 . The popTA sequences comparisons in Fig 9 are done with ClustalO , the MSA plots with Jalview ( 2 . 9 . 0b2 ) [63] and the HMM profiles of the MSA are plotted with Skylign [64] . Plasmid constructs . Plasmid pLAM12 [65] has been described elsewhere . The eleven putative new toxins identified by TASmania were PCR amplified using primers from S7 Table and cloned in pLAM12 under the control of an acetamide inducible promoter . Cloning was performed using appropriate restriction enzymes or by In-Fusion methodology ( Clontech ) , as indicated in S7 Table . Constructs were sequence verified using primers pLAM-For 5’- ACCCTCCACCGGCCGCGCTC and pLAM-Rev 5’- TGGCAGTCGATCGTACGCTA . For toxins that affected M . smegmatis growth , their respective toxin-antitoxin operons ( six in total ) were then PCR amplified and cloned into pLAM12 , using appropriate primers from S7 Table . In vivo growth assay . The pLAM12-based constructs were first electroporated in Strain M . smegmatis MC2155 ( strain ATCC 700084 ) . Following 3 h incubation at 37°C in LB medium + tween 80 ( 0 , 05% ) , 1/100 of the transformants were directly plated on LB agar supplemented with kanamycin ( 20 μg/ml ) and acetamide ( 0 , 2% ) . Plates were incubated 3 days at 37°C . Note that Rv0229c only showed a tiny but reproducible effect on M . smegmatis growth when expressed alone ( Fig 5 ) . Therefore , we decided to test it within the context of its operon as well . The effect of the putative antitoxin Rv0230c was hardly detectable ( S6 Fig ) , indicating that Rv0229c/Rv0230c may not be a functional TA system when expressed in M . smegmatis . Similar to the popTAs analysis performed on the canonical TA/AT hits previously , we pool all the “x” protein sequences , cluster them with MMseqs2 , make an MSA of each cluster , build an HMM profile for each protein cluster , and compare and cluster the HMM profiles ( N = 805 ) with PRC and Cytoscape . We dub these putative antitoxin HMM clusters as TASMANIA . A*n ( A*n ) ( N = 536 at E-value = 10−5 ) . After Pfam annotation of these putative antitoxin clusters , we perform a semi-automated curation to discover new antitoxin families . One criterion of selection we applied is that the nearest Pfam annotation of the “x” antitoxin should not belong to known antitoxin families ( e . g . , ParD_antitox , CcdA , CbeA_antitoxin , MazE_antitoxin , PhdYeFM_antitox , CopG_antitoxin , AbiEi , VAPB_antitox ) . We then go further in stringency by selecting only pairs whose T toxin cognate had an HMM E-value below 10−20 and we thus obtain N = 222 xT/Tx combinations . We find that 27 popTx contain putative new antitoxin protein families worth investigating , since they are conserved up to high stringency .
|
TASmania offers an extensive annotation of TA loci in a very large database of bacterial genomes , which represents a resource of crucial importance for the microbiology community . TASmania supports i ) the discovery of new TA families; ii ) the design of a robust experimental strategy by taking into account potential interferences in trans; iii ) the comparative analysis between TA loci content , phylogeny and/or phenotypes ( pathogenicity , persistence , stress resistance , associated host types ) by providing a vast repertoire of annotated assemblies . Our database contains TA annotations of a given strain not only mapped to its core genome but also to its plasmids , whenever applicable .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"bacteriology",
"medicine",
"and",
"health",
"sciences",
"toxins",
"pathology",
"and",
"laboratory",
"medicine",
"markov",
"models",
"microbiology",
"operons",
"toxicology",
"toxic",
"agents",
"mathematics",
"genome",
"analysis",
"bacterial",
"genetics",
"dna",
"microbial",
"genetics",
"bacteria",
"research",
"and",
"analysis",
"methods",
"bacterial",
"toxins",
"genomics",
"antitoxins",
"toxin-antitoxin",
"modules",
"microbial",
"physiology",
"proteins",
"hidden",
"markov",
"models",
"biological",
"databases",
"actinobacteria",
"probability",
"theory",
"biochemistry",
"bacterial",
"physiology",
"nucleic",
"acids",
"database",
"and",
"informatics",
"methods",
"protein",
"domains",
"genetics",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"computational",
"biology",
"genomic",
"databases",
"organisms"
] |
2019
|
TASmania: A bacterial Toxin-Antitoxin Systems database
|
The four-subunit Negative Elongation Factor ( NELF ) is a major regulator of RNA Polymerase II ( Pol II ) pausing . The subunit NELF-E contains a conserved RNA Recognition Motif ( RRM ) and is proposed to facilitate Poll II pausing through its association with nascent transcribed RNA . However , conflicting ideas have emerged for the function of its RNA binding activity . Here , we use in vitro selection strategies and quantitative biochemistry to identify and characterize the consensus NELF-E binding element ( NBE ) that is required for sequence specific RNA recognition ( NBE: CUGAGGA ( U ) for Drosophila ) . An NBE-like element is present within the loop region of the transactivation-response element ( TAR ) of HIV-1 RNA , a known regulatory target of human NELF-E . The NBE is required for high affinity binding , as opposed to the lower stem of TAR , as previously claimed . We also identify a non-conserved region within the RRM that contributes to the RNA recognition of Drosophila NELF-E . To understand the broader functional relevance of NBEs , we analyzed promoter-proximal regions genome-wide in Drosophila and show that the NBE is enriched +20 to +30 nucleotides downstream of the transcription start site . Consistent with the role of NELF in pausing , we observe a significant increase in NBEs among paused genes compared to non-paused genes . In addition to these observations , SELEX with nuclear run-on RNA enrich for NBE-like sequences . Together , these results describe the RNA binding behavior of NELF-E and supports a biological role for NELF-E in promoter-proximal pausing of both HIV-1 and cellular genes .
RNA polymerase II ( Pol II ) is a molecular machine responsible for transcribing all protein coding genes in the eukaryotic genome in a highly regulated multistep process . With the help of specific and general transcription factors , it binds to promoters , rapidly initiates transcription , transcribes approximately 20–60 nucleotides of nascent RNA , and then can pause before entering productive elongation [1] , [2] . Recent genome-wide studies have demonstrated that promoter-proximal pausing is a frequently observed feature of metazoan genes and a major point of regulation [3]–[5] . Three protein complexes have a major role in Pol II pausing . Two of these , NELF ( Negative elongation factor ) and DSIF [DRB ( 5 , 6-dichloro-1-b-D-ribofuranosylbenzimidazole ) sensitivity inducing factor] , form a stable complex with Pol II and inhibit its elongation shortly after initiation . In contrast , P-TEFb ( Positive transcription elongation factor b ) , a complex of CDK9 kinase and CyclinT , overcomes the influence of these factors and promotes the release of Pol II into productive elongation [6]–[9] . Experimental evidence indicates that P-TEFb phosphorylates NELF , DSIF , and the C-terminal domain ( CTD ) of Pol II and that one or more of these modifications alleviate the pause [10]–[12] . Several ChIP-chip and ChIP-seq experiments have revealed that these pausing factors co-occupy promoter-proximal regions of active genes where Pol II also accumulates [3] , [13]–[15] . Composite profiles of Pol II demonstrate an overall decrease in promoter occupancy after depleting cells of NELF or DSIF subunits . In contrast , a marked increase in promoter-proximal Pol II occupancy is seen after treating cells with a P-TEFb inhibitor [3] , [14] , [16]–[18] . In agreement with these observations , knockdown of NELF in Drosophila S2 cells leads to a decrease in Pol II density in promoter regions relative to Pol II occupancy in gene bodies [16] , [17] . NELF consists of four protein subunits ( NELF-A , NELF-B , NELF-C/D , and NELF-E ) [7] . NELF-E contains a canonical βαββαβ RNA recognition motif ( RRM ) that is essential for its ability to bind RNA and inhibit elongation in vitro [19] . In human cells , the absence of NELF-E abolishes the ability of NELF to repress elongation . This suggests that NELF-E plays a role in the pausing mechanism [20] . One prevailing hypothesis is that NELF-E RNA binding enables NELF to stabilize paused Poll II as the nascent RNA exits the polymerase [19] , [20] . However , a recent in vitro cross-linking study by Gilmour and coworkers suggested that RNA binding by Drosophila NELF-E may not be involved in promoter-proximal pausing , but instead may interact with longer nascent transcripts at a location further downstream [21] . While they show that NELF and DSIF are required to inhibit elongation , they did not identify a NELF/RNA contact among short nascent RNAs that are associated with promoter-proximal paused Pol II . It is possible , however , that the template used in this study lacks a specificity determinant required for an interaction . Therefore , the function for the RNA binding activity of NELF-E remains unresolved . Studies investigating the regulation of HIV-1 transcription implicate how NELF-E functions [22] . HIV-1 proviral expression is regulated at the level of early elongation , and the leading model suggests that NELF-E binds to the double stranded portion of the RNA transactivation response ( TAR ) element found between +1 and +59 nucleotides downstream from the transcription start site where Pol II is paused . P-TEFb and the transactivator protein Tat then bind to the TAR element , NELF dissociates , and paused Pol II is then released into productive elongation [23] . Qualitative binding experiments suggest that NELF-E binds to the lower stem region of TAR RNA [12] , [19] . In addition , NMR studies have solved the structure of the RRM domain of NELF-E [24] , [25] . This work also used fluorescence equilibrium titrations to test its interaction to single and double stranded RNA fragments of the lower stem of TAR . These experiments measured binding affinities in the µM range; however , the precise binding region in TAR RNA was unable to be determined . Here , we characterize the RNA binding specificity of NELF-E and attempt to clarify its role in promoter-proximal pausing . We demonstrate that NELF-E is capable of binding to RNA with high affinity and specificity . Moreover , we define the NELF-E binding element ( NBE ) for both Drosophila and human NELF-E ( dNELF-E and hNELF-E , respectively ) and identify the presence of an NBE within TAR RNA , which is located in a different region than previously thought to be bound by NELF-E . Finally , we found that NBEs are enriched at promoter-proximal pause regions in the Drosophila genome . This implies a functional role for NELF-E RNA binding in Pol II pausing .
No published studies have investigated the nucleotide specificity of Drosophila NELF-E . To identify the sequence specificity of dNELF-E , a microcolumn-based SELEX ( Systematic Evolution of Ligands by Exponential Enrichment ) experiment was performed with full-length dNELF-E or its RRM domain [26] . The RNA library ( >5×1015 unique molecules ) used contained a 70-nucleotide randomized region flanked by two constant regions that allowed for amplification of selected RNAs and in vitro transcription to generate subsequent aptamer pools . This affinity-based approach utilized modular , custom-made microcolumns that permit high-efficiency selection of aptamers by exploiting optimal fluidic parameters [26] . Microcolumns containing protein-bound resin were subjected to six cycles of SELEX , and the resulting pools were sequenced by the high-throughput Illumina Hi-Seq platform to identify putative target-binding aptamer sequences . Approximately 2–4 million sequence reads were obtained for each pool from cycles 4 and 6 . After clustering to identify unique sequences , the top 3 , 000 sequences with the highest multiplicity in pool 6 were analyzed using MEME ( Multiple EM for Motif Elicitation ) , a computational tool that searches for repeated , ungapped sequence patterns from a list of DNA sequences [27] , [28] . A highly conserved motif was present within 1 , 049 out of 3 , 000 sequences selected for binding to full-length NELF-E and 1 , 362 of 3 , 000 sequences for binding to its RRM domain ( Figure 1a ) . These motifs are nearly identical for both proteins and define the NELF-E binding element ( NBE ) for dNELF-E and its RRM domain as CUGAGGA ( U ) . Examination of the pool 6 sequencing results suggests that the more conserved 3′ position in the NBE from the RRM domain selection is due to faster convergence of NBE containing sequences during earlier SELEX cycles ( unpublished data ) . Analysis of the most enriched RNA aptamers containing an NBE revealed a common secondary structure consisting of a putative non-canonical kink-turn ( K-turn ) ( Figure S1 ) [29] . K-turn structures have an asymmetric internal loop that causes a sharp bend between two helical regions . The 3′ end of this loop is typically flanked by a GA/AG Hoogsteen-Sugar edge platform [30] . The NBE is located in the internal loop of the K-turn among candidate aptamers ( Figure S1 , Figure 1b ) . A truncated version of the most abundant candidate aptamer , Napt1min , is shown in Figure 1b . Two approaches were used to quantitatively measure the equilibrium dissociation constant ( Kd ) of dNELF-E binding to Napt1min: a fluorescence electrophoretic mobility shift assay ( F-EMSA ) and a fluorescence polarization ( FP ) assay , each relying on different physical properties of the protein/RNA complex [31] . Each assay revealed that dNELF-E binds with high affinity to Napt1min ( Kd; F-EMSA = 44±22 nM and FP = 21±7 nM ) ( Fig . 1c–e; Table 1 ) . Moreover , two other NBE-containing aptamers tested bound with similar high affinity ( Figure S2 , Table 1 , unpublished data ) . The binding constants measured by F-EMSA and FP were ( unless otherwise noted ) typically within two-fold of each other , supporting confidence in the measured values . As discussed above , the majority of aptamers selected have the conserved NBE motif and putative K-turn . To assess the contribution that these features have on dNELF-E RNA binding , we generated a variety of Napt1min mutants and tested them for dNELF-E binding . To test the significance of the NBE within Napt1min , a mutant was generated in which four nucleotides within the NBE were changed , but the predicted secondary structure was kept intact ( Napt1NBEmut ) . The binding affinity of dNELF-E to Napt1NBEmut is much weaker ( Kd; F-EMSA = 880±170 nM and FP>2000 nM ) , demonstrating the importance of the NBE ( Figure 2 , Table 1 ) . To determine if binding requires that the NBE is accessible in a single-stranded region , dNELF-E was tested for binding to a Napt1min variant that forms a perfect hairpin by complementary base pairing with the NBE sequence ( Napt1+hairpin; Figure 2a ) . The binding affinity between dNELF-E and this variant is substantially weaker ( Kd; F-EMSA = 810±50 nM and FP = 470±170 nM ) compared to that of Napt1min ( Figure 2 , Table 1 ) . This suggests that an NBE located in dsRNA cannot effectively bind dNELF-E . Next , to test if dNELF-E requires the putative K-turn structure for high affinity binding , Napt1min was mutated to generate an RNA sequence that has no predicted secondary structure , but still contained the NBE ( Napt1-Δstem; Figure 2a ) . Interestingly , this putatively unstructured sequence is still able to bind dNELF-E with moderate affinity ( Kd; F-EMSA = 205±20 nM and FP = 270±130 nM ) compared to the parent minimal aptamer Napt1min ( Figure 2 , Table 1 ) . This indicates that the putative K-turn present in selected aptamers contributes to dNELF-E binding but is not essential for the interaction . From this group of Napt1min mutants , we conclude that the NBE is necessary and sufficient for RNA binding to dNELF-E so long as it is accessible as single-stranded RNA . The NELF-E RRM is conserved between Drosophila and humans , but we were surprised that the reported hNELF-E target , HIV-1 TAR RNA , bore no structural resemblance to our aptamers . HIV-1 TAR RNA forms a highly stable hairpin structure ( Figure 3a ) that includes a three nucleotide bulge ( UCU ) that is bound by HIV-1 TAT , and a stem-loop that is bound specifically by Cyclin T1 , a subunit of P-TEFb [32] . Previous reports suggested that the hNELF-E RRM binds to the lower stem region of TAR with low specificity and affinity ( Kd>2 µM ) [12] , [25] . We find that the Drosophila homolog , dNELF-E , binds specifically and with high affinity to its RNA targets . Interestingly , a closer examination of the TAR sequence reveals the sequence CUGGGA within the loop region , which is very similar to the NBE sequence CUGAGGA found in Napt1min . To assess whether dNELF-E is able to bind to TAR RNA , we performed quantitative binding experiments . We found that dNELF-E does indeed bind to TAR , although somewhat weaker than it binds Napt1min ( Kd; F-EMSA = 350±40 nM and FP = 130±10 nM ) ( Figure 3b , d ) . Since dNELF-E binds tighter to Napt1min , we examined if it would bind tighter to the TAR element containing the same NBE that was identified by SELEX . To do this , a single adenosine was inserted into the loop region to make an NBE site within the stem loop ( TAR+A ) and this RNA was tested for binding . Remarkably , this single nucleotide insertion increases the binding affinity to dNELF-E about 6-fold ( Kd; F-EMSA = 59±2 nM and FP = 82±1 nM ) ( Figure 3b , d and Table 1 ) . Based on these experiments , we conclude that dNELF-E binds to TAR RNA , and that it targets an NBE-like motif within the loop region of TAR . In light of this result , we wanted to clarify the specificity of the human form of NELF-E so we reexamined its interaction with HIV-1 TAR RNA . Because an NBE-like motif is present in TAR RNA ( hereafter referred to as hNBE; human NELF-E binding element ) and dNELF-E specifically targets the hNBE , it is plausible that hNELF-E actually binds this region of TAR , instead of the lower stem as previously reported . The wild-type TAR RNA sequence was first tested for binding with hNELF-E and found to bind with a higher affinity than previously reported ( Kd; F-EMSA = 300±20 nM and FP = 200±10 nM ) ( Figure 3c , d and Table 1 ) [25] . This may be due to amino acids outside of the RRM domain that contribute to the NELF-E RNA binding affinity . To test if hNELF-E requires the hNBE in the loop region for its interaction , binding to the isolated dsRNA stem of TAR was examined . We generated a stem that lacks the hNBE ( TAR-ΔhNBE ) by annealing together two ssRNA sequences of TAR . No significant binding was detected with concentrations up to 2 µM hNELF-E protein ( Figure 3c and Table 1 ) . This was also observed for dNELF-E ( Table 1 ) . From this analysis , we conclude that hNELF-E , like dNELF-E , binds to the loop region of HIV-1 TAR , rather than the lower stem . To compare the binding specificity of hNELF-E with dNELF-E , the affinity of hNELF-E was measured against TAR+A , which contains the NBE identified by SELEX in the loop region . This sequence does not bind significantly tighter , contrary to that observed with dNELF-E , but has a similar binding constant ( Kd; F-EMSA = 250±20 nM and FP = 250±20 nM ) as unmodified TAR ( Figure 3c , d and Table 1 ) . This suggests that hNELF-E has a more flexible NBE specificity , CUGA0–1GGA , than dNELF-E . To identify the region within the RRM that influences the differential specificity observed in dNELF-E , we aligned RRM domains from different species ( Figure 4a ) and noted a region that is not conserved between human and Drosophila , amino acids 269–275 in hNELF-E , as one of interest . hNELF-E has a glutamate residue in this region that has previously been defined as part of the RNA binding interface [24] . This residue and a proceeding aspartate are shifted four amino acids towards the C-terminus in Drosophila as well as in many other species examined and have a low alignment quality score relative to other positions in the RRM ( Figure 4a ) . To determine whether the amino acid shift observed in dNELF-E relative to hNELF-E accounts for the differences in RNA binding , we generated a humanized version of dNELF-E , dNELF-E ( mut ) , that substitutes the seven amino acid region of dNELF-E with the human counterpart ( Figure 4b ) . We then measured its binding to Napt1min , TAR , and TAR+A RNAs ( Table 1 ) . To assess the contribution that this region has on specificity , we used the observed binding constants ( and those of dNELF-E and hNELF-E reported above ) to calculate ΔΔG° , the difference between the standard binding free energies of the NELF-E variants to Napt1min and TAR ( Figure 4c ) . A ΔΔG° measurement greater than 0 . 5 kcal mol−1 represents more than a two-fold change in binding affinity . Because dNELF-E binds much more tightly to Napt1min than to TAR RNA , the ΔΔG° is large ( >1 kcal mol−1 ) , while hNELF-E binds the two targets with similar affinities and has a small difference in binding free-energy ( ΔΔG° = −0 . 25 kcal mol−1 ) . The results for dNELF-E ( mut ) show that , like hNELF-E , it does not discriminate between the two targets ( ΔΔG° = −0 . 15 kcal mol−1 ) . This analysis was repeated comparing the binding of each NELF-E variant to TAR+A and TAR RNA ( Figure 4c ) . A similar behavior was observed with these sequences as well . Based on these experiments , we conclude that the seven amino acid stretch tested in these experiments consists of residues that contribute to the binding specificity of Drosophila NELF-E . The reciprocal mutation made to hNELF-E does not , however , narrow the specificity of the hNELF-E ( Figure S3 ) . This implies that there are likely additional specificity determinants outside of the region tested that influence dNELF-E RNA recognition . The NELF complex is highly enriched in promoter-proximal pause regions , and binding of the paused RNA transcript by co-localized NELF-E might support the ability of NELF to stabilize promoter-proximal paused Pol II [3] , [14] . We hypothesized that the localization of NELF to these pause regions results , at least in part , from the enrichment of NBEs there . To test this , we searched for the NBE in Drosophila genomic regions near annotated transcription start sites ( TSSs ) . The conserved seven-nucleotide NBE ( CUGAGGA ) that was characterized in this study ( Figure 1a ) was searched among all annotated Drosophila genes between −50 and +150 base pairs of TSSs ( Figure 5a ) . Interestingly , we detect an enriched signal +20 to +30 base pairs downstream of the TSS , just upstream of the major Pol II pause site at +50 base pairs ( Figure 5b , Figure S4 ) [2] . A sequence logo was generated using the identified motif in each sequence ( Figure 5c ) . Interestingly , the observed motif is a more degenerate NBE than that identified by SELEX . We propose that weaker NELF-E binding sites might be tolerated or even preferred for some genes , allowing Pol II to release from the paused state more readily . If NELF-E's interaction with NBE-related sequences contributes to Pol II pausing , then these sequence elements should be more abundant in paused genes than in non-paused genes . Our group has previously mapped the genome-wide distribution of all transcriptionally engaged Pol II in Drosophila using GRO-seq , and more recently , at base-pair resolution using PRO-seq [2] , [17] . Using these results , we found that there was a significant ( two-sample unequal variance t-test p-value<1 . 3×10−5 ) increase of the NBE similarity index among paused genes compared to non-paused genes ( Figure 5a and 5d ) . This result is consistent with the idea that NELF-E binding to nascent RNA transcripts contributes to pause formation and stabilization . In addition , enrichment of NBE-like sequences downstream of Pol II pause regions suggests that NELF-E might have a functional role downstream of the more prominent proximal-promoter pausing . Transcription of HIV-1 provides a well-established model to assess the functionality of NBEs in Pol II promoter-proximal transcription regulation . As we have shown , hNELF-E binds specifically to the hNBE present within the stem loop of TAR ( Figure 3 ) , which clarifies the precise binding region for this known regulator of HIV-1 transcription . In agreement with this analysis , Feng and Holland previously reported that the loop region of TAR is essential for TAT trans-activation of an HIV-1 reporter [33] . They systematically mutagenized an HIV-1 reporter and demonstrated that the five-nucleotide element , CUGGG , in the stem-loop structure is a bona fide cis-regulatory element required for the activation of HIV-1 transcription . This pentanucleotide represents 5 of the 6 hNBE nucleotides . Moreover , this element is found in all three loops of a predicted HIV-2 TAR secondary structure [33] . The requirement of the NBE for HIV-1 transcription , as well as the presence of NBE-related sequences at the start of genes provoked us to analyze the binding of NELF-E to naturally transcribed RNAs . We combined the advantages of highly sensitive GRO-seq and our microcolumn based SELEX method to perform a SELEX experiment on nascent transcribed RNA . GRO-seq methodology was used to prepare a library of nascent RNAs ( GRO-RNA ) from transcriptionally engaged Pol II in Drosophila S2 cells . This allowed us to survey a pool of RNA sequences that are contextually relevant to NELF during transcription . One round of RAPID-SELEX ( 2 cycles with no amplification ) [34] was performed using either dNELF-E as a target or a negative control with resin only . After high-throughput sequencing with the Illumina Hi-Seq platform , we searched for enrichment of NBE-like sequences ( permitting 1 mutation ) in the NELF-E selected pool and the resin only control pool using the pattern searching tool PatScan [35] . Since there are no amplification steps within the selection , enrichments were limited by the multiplicity of sequences within the initial GRO-RNA pool . Despite these limitations , there was still a significant enrichment of NBE-like sequences from NELF-E compared to the resin only control , as expected ( p-value<2 . 2×10−16 , Fisher's Exact Test ) ( Figure S5 ) . This supports the hypothesis that NELF-E preferentially targets NBE sites in nascent RNA transcripts . Together , these data reveal that the NBE is enriched in contextually relevant regions and supports a biological role for NELF-E in promoter-proximal pausing .
RRM-domain proteins are known to have diverse modes of target recognition that can include a variety of specific RNA , DNA , and protein interactions [36] . Recent work has highlighted the role of these proteins in promoter-proximal pausing [37] . Our study here demonstrates that RRM-containing NELF-E is capable of binding to RNA with high affinity and sequence specificity ( NBE: CUGAGGA ( U ) for Drosophila ) . NELF-E requires that the consensus be accessible in single-stranded RNA , and the binding can be enhanced with more complex secondary structures , such as the K-turn of Napt1min or the loop region of HIV-1 TAR RNA . This work reveals that hNELF-E binds specifically to the HIV-1 TAR RNA stem loop that is closely related to the dNBE . These results have important implications for transcriptional regulation of HIV-1 by NELF and the P-TEFb-Tat complex . The hNBE overlaps the binding site for the P-TEFb subunit CycT1 and is adjacent to the TAR bulge region where Tat binds [32] , [38] , [39] . Instead of NELF-E binding to the lower stem as suggested previously [12] , [19] , our results indicate that NELF-E binds to the hNBE present in the loop to assist in establishment of a Pol II that is poised for transcription activation . After P-TEFb phosphorylation of NELF-E , we propose that the P-TEFb-Tat complex competes off NELF and releases Pol II into productive elongation . Further studies will unfold the complex interchange that occurs between these protein complexes to promote HIV-1 transcription , as well as a possible role for NELF in the establishment and maintenance of HIV-1 latency . The lower stem region of TAR does have a sequence that somewhat resembles the NBE ( nucleotides 48 to 54 in Figure 3a ) ; however , as we have shown , NELF-E does not bind to this double-stranded site with high affinity . For NELF to bind this site , the TAR stem would have to be melted to make the element accessible . It is fitting that the NBE would be enriched in pause regions ( +20 to +60 base pairs from the TSS ) seeing that NELF plays a critical role in promoter-proximal pausing for many genes . Binding of NELF-E to this element might stabilize paused Poll II , working together with other pausing factors including DSIF [8] , [21] , the core promoter complex [1] , [40] , and GAGA factor [13] . It is possible that NELF-E binds RNA cooperatively with these factors , which could explain why the genomic NBE generated is more degenerate ( Figure 5c ) than the selected consensus sequence ( Figure 1a ) . Additionally , the local proximity of the NELF complex with nascent RNA might be sufficient for an interaction and permit a weaker binding site . An intriguing observation is the increased probability of NBE-like sequences >100 base pairs downstream of the TSS into the gene body ( Figure 5b ) . This agrees with the Gilmour study , which detected a NELF interaction with longer transcripts ( 70 nucleotides ) [21] . As described earlier , NELF is enriched in promoter-proximal regions and the observed binding location is , for many genes , broadly dispersed , even beyond the initial pause peak ( maximal at +200 base pairs from the TSS ) [3] . Perhaps there are multiple NELF-E interactions with the nascent RNA that assist in Pol II pausing as well as downstream RNA processes; and many genes might have “backup” NBE loci located downstream of the initial pause site . A possible role for these sites would be to provide a slow transition from the paused state into productive elongation before NELF dissociates from Pol II . Beyond the scope of this initial study , a detailed kinetic investigation of early elongation rates will help test this hypothesis . Alternatively , high affinity NBEs downstream might act as “deposit sites” to expel the NELF complex from paused Pol II and promote elongation . In addition to its role in promoter-proximal pausing , evidence suggests that NELF may coordinate a number of mRNA processing steps during transcription [41] . Handa and coworkers have demonstrated that NELF interacts with the nuclear cap binding complex ( CBC ) to regulate the 3′ end processing of replication-dependent histone mRNAs . They also identify intranuclear focal accumulations of NELF , “NELF bodies , ” that associate with RNA processing Cajal bodies and Cleavage bodies . Future studies will unveil the possible roles that NELF-E RNA binding has in other transcriptional and post-transcriptional regulatory mechanisms .
Full length Drosophila and human NELF-E , and the RRM domain of dNELF-E ( amino acid residues 147–247 ) were subcloned into pHIS-parallel1 to generate N-terminal hexahistindine-tagged recombinant proteins [42] . Mutated proteins were engineered using site-directed mutagenesis with primers that changed the corresponding codons for the 7 amino acids described in the text . Protein was expressed in BL21 ( DE3 ) -RIPL E . coli cells ( Agilent Technologies ) . Liquid cultures were grown at 37°C and induced in mid-log phase with IPTG . Cultures were induced with either 1 mM IPTG at 37°C for 3 hours or 0 . 2 mM IPTG at 18°C overnight before collecting cells by centrifugation . Harvested cells were purified in batch according to the manufacturer's instructions for Ni-NTA Superflow ( Qiagen ) resins . Buffers used for the purification included lysis buffer ( 40 mM Tris-Cl , 300 mM NaCl , pH 8 . 0 , 20 mM Imidazole , 10% glycerol , 5 mM 2-mercaptoethanol , EDTA-free protease inhibitor tablet ( Roche Applied Science , 0 . 2 mg/ml lysozyme ) , wash buffer ( lysis buffer with 200 mM NaCl ) , and elution buffer ( wash buffer with 20% glycerol and 250 mM Imidazole ) . When necessary , eluted protein samples were subject to a mono Q column ( GE Healthcare ) for further purification as described elsewhere [43] . The quality of final protein products was analyzed by SDS-polyacrylamide gel electrophoresis . Purified samples were kept in elution buffer and small aliquots were flash frozen in liquid nitrogen and stored at −80°C . A 120 nucleotide RNA library was generated as described [26] . The library was derived from a DNA template that consists of a 70 nucleotide randomized region flanked by two constant regions: 5′-AAGCTTCGTCAAGTCTGCAGTGAA-N70-GAATTCGTAGATGTGGATCCATTCCC-3′ . This template allows for amplification and transcription using primers that are complementary to the constant regions and one primer encoding a T7 promoter . The starting RNA pool used in this selection had a complexity of >5×1015 unique molecules . Microcolumn SELEX was performed on dNELF-E and its RRM domain using a 20 µl column for each protein . A detailed method was previously described by Latulippe and Szeto et al . with some modifications [26] . The binding buffer used in this experiment consists of 10 mM HEPES-NaOH pH 7 . 5 , 100 mM NaCl , 25 mM KCl , ( 5 mM MgCl2 for round 1 and 1 mM MgCl2 for each subsequent round ) , and 0 . 02% Tween-20 . Wash buffer includes 20 mM Imidazole in the binding buffer . A purified PCR product from cycles 4 and 6 were re-amplified with barcoded primers and sequenced on the HiSeq 2000 ( Illumina ) sequencing platform using a standard single-end , 100 nucleotide sequencing protocol at the Cornell University Life Sciences Core Laboratory Center ( http://cores . lifesciences . cornell . edu/brcinfo ) . Analysis of the sequencing data , which includes filtering and clustering analysis are described in detail by Latulippe and Szeto et al . [26] . The top 3000 unique DNA sequences in pool 6 obtained from the clustering analysis ( see below ) were subject to MEME [27] to derive a sequence logo for dNELF-E and its RRM domain . RNA secondary structure predictions were generated from the mfold web server [44] . Fluorescence electrophoretic mobility shift ( F-EMSA ) and fluorescence polarization ( FP ) assays were performed as described previously [45] . The RNA sequences tested in this study were in vitro transcribed from synthetic DNA templates ( Integrated DNA Technologies ) , PAGE purified , and eluted into DEPC treated 10 mM Tris-Cl pH 7 . 5 . Napt1min includes an additional GC base pair on end to accommodate for the additional guanosine designed in the Napt1min template containing a T7 promoter . Purified RNA were then 3′-end labeled with fluorescein 5-thiosemicarbazide ( Invitrogen ) as described [31] , [46] . ( HIV-1 TAR-ΔhNBE RNA was prepared by annealing two synthesized RNA oligos ( Integrated DNA Technologies ) in annealing buffer ( 50 mM NaCl , 20 mM Tris pH 7 . 5 , 1 mM EDTA ) . HIV-1 TAR-ΔhNBE was heat denatured ( >60°C ) at 1 µM concentration and cooled down to anneal before diluting samples for F-EMSA . All other RNAs were heated denatured in the F-EMSA binding buffer before adding protein . Binding reactions were prepared with 2 nM labeled RNA and varying concentrations of purified protein ( from 0 to 2000 nM ) in binding buffer ( 10 mM HEPES-NaOH pH 7 . 5 , 100 mM NaCl , 25 mM KCl , 1 mM MgCl2 , and 0 . 02% Tween-20 , 0 . 01% IGEPAL CA-630 , and 10 µg/ml yeast tRNA ) to a final volume of 50 µl in black flat-bottom 96-well half-area microplates ( Corning ) . It is recommended to use DEPC-treated water and SUPERase-In RNase inhibitor ( Invitrogen ) according to the manufacturers directions to prevent RNA degradation . Reactions were equilibrated for 1–2 hours before taking FP measurements on a Synergy H1 Microplate Reader ( BioTek ) with the appropriate filter cube for fluorescein ( Ex: 485/20 Em: 528/20 ) . After taking FP measurements , the same experiment was loaded on a pre-chilled 5% slab acrylamide gel ( 0 . 5X TBE ) and electrophoresed at 4°C for approximately 1 hour and 10 minutes . Gels were imaged immediately on a Typhoon 9400 imager ( GE Healthcare Life Sciences ) . The fluorescence intensity of bound and free RNA was measured with ImageQuant and the data was fit to a Hill equation in Igorpro software ( Wavemetrics ) , which includes the Levenberg-Marquadt algorithm and statistical analysis tools [47] . Nuclei were isolated from non-heat-shocked Drosophila S2 cells as described previously [48] . Nuclear run-ons were performed using 2×107 nuclei and GRO-seq libraries were prepared as in Core et al . [5] , with the following specifications . Base hydrolysis of the nascent RNA was performed on ice for 20 min . 5′ and 3′ RNA adaptor sequences ligated to the run-on RNA were synthesized to match the constant regions of the N70 library [26] . cDNA synthesis was performed using a reverse oligo that anneals to the 3′ constant region ( 5′- AAGCTTCGTCAAGTCTGCAGTGAA-3′ ) and the library was amplified using this oligo and a forward oligo that recognizes the 5′ constant region and contains the T7 promoter ( 5′-GATAATACGACTCACTATAGGGAATGGATCCACAT CTACGA-3′ ) , allowing the final library to utilize the same reagents that are used for preparation of SELEX pools between cycles . The final GRO-RNA library had an average size of ∼150–200 nucleotides including the constant regions . Due to the relatively low complexity of the GRO-RNA library , a total of two selection cycles were completed using a method we call RAPID ( RNA aptamer isolation via dual-cycles ) which has been shown to significantly reduce the time and cost of isolating RNA aptamers and to improve enrichment rates , by systematically omitting amplification steps [34] . These RAPID selections were performed using 20 µl microcolumns loaded with 10 µM of full length dNELF-E , or with resin alone . The two selection cycles were completed in one round of RAPID , where the reverse transcription and amplification steps were omitted between cycles 1 and 2 to increase the specificity of the amplified and transcribed material that was used for downstream analysis . Purified PCR products from Pool 0 ( initial GRO-RNA library ) and Pools 2 were barcoded and sequenced as described below . Control and experimental libraries were multiplexed and sequenced on an Illumina HiSeq 2000 instrument using a standard single-end , 100 nucleotide sequencing protocol at the Cornell University Life Sciences Core Laboratory Center ( http://cores . lifesciences . cornell . edu/brcinfo ) . Following sequencing , reads were partitioned according to 5′-end barcode using the fastx_barcode_splitter . pl script from the FASTX-Toolkit v0 . 0 . 13 . 1 ( http://hannonlab . cshl . edu/fastx_toolkit/ ) . Barcodes were then trimmed using the fastx_trimmer utility from the FASTX-Toolkit . After trimming , the 5′ library preparation adapter was removed using the semi-global alignment and adapter removal utility cutadapt v1 . 1 ( parameters: -g -e 0 . 20 -m 26 -O 18 –match-read-wildcards ) [49] . Likewise , cutadapt was then used to remove the 3′ library preparation and sequencing adapters ( parameters: -a -e 0 . 20 -O 2 -m 26 ) . Given that the RNA library used for the SELEX experiments originated from NaOH-fragmented , nascently transcribed RNAs , we expected a heterogeneous distribution of sequencing read lengths . Therefore , we combined reads with and without a 3′ adapter into a single pool for all downstream analyses . Trimmed sequences were then mapped to the D . melanogaster genome ( assembly dm3 ) using 64-bit bowtie v0 . 12 . 7 allowing 2 possible mismatches and requiring unique alignment [50]–[52] . To account for fragmentation during the GRO library preparation , alignments were processed to obtain the genomic sequence beginning at the 5′ end of each mapping , and extended 100 bases downstream ( the average length of the run-on RNA ) . These sequences were then analyzed using PatScan [35] . DNA sequence motifs were analyzed as described previously [2] . Briefly , DNA sequences were obtained from −50 to +150 base pair positions relative to the annotated TSS based on short capped nuclear RNA analysis in Drosophila [53] . For each position relative to the TSS , sequence similarity of the 7-mer to NBE was calculated from position weight matrix scores . The position weight matrix was built from the log-likelihood of an NBE consensus motif . p-values for the scores were calculated by comparing to 100 , 000 random permutated DNA sequence scores . The best matched 7-mer to the NBE consensus from +0 to +50 nucleotide positions relative to TSS were selected for every gene , and the base frequencies for each position were calculated . The base frequencies were used to generate the sequence logo as described previously [54] . For the comparison of paused and non-paused genes , gene lists were obtained from a previous study [2] , and analyzed as described above . To test the statistical significance of the difference between paused and non-paused genes , the maximum of the NBE similarity score ( –log10 p-value ) within +10 to +30 base pair region for each gene was used as the test value , and the two groups were compared using a Kolmogorov-Smirnov test or two-sample unequal variance t-test . Sequence logos were generated as described previously [54] using an in-house script .
|
RNA polymerase II ( Pol II ) is a molecular machine that is responsible for transcribing all protein coding genes in the eukaryotic genome . Transcription by Pol II is a highly regulated process consisting of several rate-limiting steps . During transcription elongation , a number of transcription factors are essential to modulate Pol II activity . One of these factors is the Negative Elongation Factor ( NELF ) , and it plays a major role in promoter-proximal pausing , a widespread phenomenon during early transcription elongation . NELF-E , a protein subunit of the NELF complex contains a conserved RNA binding domain that is thought to regulate transcription through its interaction with newly transcribed RNA made by Pol II . However , the function of the RNA binding activity of NELF-E remains unresolved due to prior conflicting studies . Here , we clarify the RNA binding properties of NELF-E and provide insight into how this protein might facilitate promoter-proximal pausing of Pol II in transcription . Moreover , we identify the precise region of NELF-E binding in one of its known regulatory targets , HIV-1 . Taken together , the results presented indicate a dynamic interplay between NELF and specific RNA sequences around the promoter pause region to modulate early transcription elongation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology",
"biomacromolecule-ligand",
"interactions",
"biochemistry",
"rna",
"genome",
"analysis",
"tools",
"genomics",
"protein",
"interactions",
"nucleic",
"acids",
"proteins",
"gene",
"expression",
"genetics",
"regulatory",
"proteins",
"biology",
"recombinant",
"proteins",
"molecular",
"cell",
"biology",
"dna",
"transcription"
] |
2014
|
Defining NELF-E RNA Binding in HIV-1 and Promoter-Proximal Pause Regions
|
Gene duplication was prevalent during hominoid evolution , yet little is known about the functional fate of new ape gene copies . We characterized the CDC14B cell cycle gene and the functional evolution of its hominoid-specific daughter gene , CDC14Bretro . We found that CDC14B encodes four different splice isoforms that show different subcellular localizations ( nucleus or microtubule-associated ) and functional properties . A microtubular CDC14B variant spawned CDC14Bretro through retroposition in the hominoid ancestor 18–25 million years ago ( Mya ) . CDC14Bretro evolved brain-/testis-specific expression after the duplication event and experienced a short period of intense positive selection in the African ape ancestor 7–12 Mya . Using resurrected ancestral protein variants , we demonstrate that by virtue of amino acid substitutions in distinct protein regions during this time , the subcellular localization of CDC14Bretro progressively shifted from the association with microtubules ( stabilizing them ) to an association with the endoplasmic reticulum . CDC14Bretro evolution represents a paradigm example of rapid , selectively driven subcellular relocalization , thus revealing a novel mode for the emergence of new gene function .
Gene duplication has been important for the evolution of phenotypes specific to species and evolutionary lineages by providing the genetic raw material for the emergence of genes with new or altered functions [1] . Duplicate gene copies are commonly generated through duplication of gene-containing chromosomal segments ( segmental duplication; [2] ) , or by reverse-transcription of mRNAs from parental source genes ( termed retroduplication or retroposition ) , generating intronless gene copies ( retrocopies ) of the parent [3 , 4] . However , although both of these mechanisms were shown to have generated a significant number of gene copies during recent primate evolution on the lineage leading to humans [5–7] , little is known with respect to their functional evolution and impact on phenotypes typical to humans and their close evolutionary primate relatives . Indeed , only a relatively small number of functionally preserved segmentally duplicated genes or functional retrocopies ( retrogenes ) that emerged in hominoids ( humans and apes ) have been pinpointed [6 , 8–12] . Although some of these genes revealed striking signatures of positive selection [10] , selectively driven substitutions could only rarely be tied to functional protein change and adaptation [8] . Even in primates in general , few cases of new duplicate genes exist where amino acid substitutions resulting from positive selection were experimentally demonstrated to lead to functional adaptation of the encoded protein [13 , 14] . In a previous survey [6] , we identified an interesting retrogene , termed CDC14Bretro ( denoted CDC14B2 in [6] ) , which originated by retroduplication ( from Chromosome 9 to 7 ) from its parent , CDC14B , in the hominoid ancestor around 18–25 million years ago ( Mya ) [15] ( Figure 1A ) . CDC14B and its paralog CDC14A were recently shown to represent the mammalian counterparts of the single , dual-specificity phosphatase gene CDC14 from yeast , a key regulator of late mitotic events , which is particularly important for mitotic exit [16] . Although both paralogs can rescue CDC14 deletion mutants of Schizosaccharomyces pombe ( fission yeast ) , CDC14B was shown to be the functional ortholog of CDC14 from budding yeast [17] . Prompted by the potential functional implications of an additional CDC14 family member for the phenotypic evolution of hominoids , we set out to characterize the functional evolution of the CDC14B daughter gene , CDC14Bretro .
To understand the origin of CDC14Bretro , we first characterized the transcript that gave rise to CDC14Bretro , because two CDC14B splice variants have been analyzed in previous studies [17–19] ( we have termed them CDC14B1 and CDC14B2 , Figure 1A ) . To this end , we aligned the CDC14Bretro sequence to the genomic locus of its parental gene on Chromosome 9 . This procedure revealed a previously undescribed exon structure , indicating a transcript ( the “parent”—termed CDC14Bpar—that gave rise to CDC14Bretro ) with a previously unknown 3′ splicing pattern ( Figure 1A ) . A fourth 3′-end splice variant ( CDC14B3 ) is annotated ( Ensembl database [20] ) and supported by expressed sequence tags ( Figure 1A ) . Thus , the human CDC14B gene encodes at least four different alternative splice variants . Spatial expression analyses revealed that these variants are widely expressed , as reverse-transcriptase ( RT ) -PCR products specific to CDC14Bpar , B1 , B2 , and B3 were found in all of the 12 tissues tested ( Figure 2 ) . In contrast , CDC14Bretro is specifically expressed in the adult brain ( in all eight regions tested ) and testes ( Figure 2 ) . In addition , CDC14Bretro transcripts were also detected specifically in the human embryonic forebrain , including the dorsal telencephalon , which contains the primordium of the cerebral cortex ( Figure 2 ) . Thus , CDC14Bretro likely evolved a specific function in the embryonic/adult brain and/or testis since the duplication event in the hominoid ancestor . To date the origin of its brain-/testis-specific expression , we performed RT-PCR experiments using brain , testis , and liver RNA preparations from chimpanzees and gibbons . Like in humans , we detected CDC14Bretro expression in brain and testis from these two apes but not in liver ( Figure 2 ) . This suggests that brain- and testis-specific expression was acquired soon after the duplication event in the common hominoid ancestor , although additional ape tissues need be analyzed in the future to confirm this hypothesis . To trace the functional evolution of CDC14Bretro , we first analyzed its coding sequence evolution in a phylogenetic framework . The evolution of CDC14Bretro appears to have been shaped mainly by purifying selection , as indicated by the generally low nonsynonymous ( dN ) to synonymous ( dS ) substitution rate ( dN/dS; Figure 3A ) . In sharp contrast , the internal branch leading to the last common ancestor of African apes ( human , chimpanzee , and gorilla ) reveals a strikingly different pattern , with 12 nonsynonymous and 0 synonymous substitutions , which is indicative of accelerated protein evolution driven by positive Darwinian selection [21] . A conservative maximum likelihood analysis ( [22]; see Materials and Methods for details ) confirms that the excess of nonsynonymous relative to synonymous substitutions is statistically significant ( p < 0 . 05 ) . Furthermore , we found that the nonsynonymous substitutions are nonrandomly distributed in the sequence . Nine of the 12 amino acid changes occurred in the N- or C- terminal part of the protein , whereas the remaining three substitutions occurred in the phosphatase core domain ( Figure 4 ) —a statistically significant difference ( Fisher's exact test , two-tailed p < 0 . 01 , see Materials and Methods for details ) . Interestingly , the nonsynonymous substitutions that occurred in the 5′ end of CDC14Bretro during the period of positive selection in the African ape ancestor entailed the origin of a new methionine start codon that allowed the original start codon to be lost in humans and chimpanzees ( Figure 4 ) . Analysis of the full-length transcript revealed no other possible in-frame ATG start codon , suggesting that the new downstream start codon is indeed used for initiation of translation . This new methionine start codon disrupts the KKIR motif ( replacing the isoleucine residue by a methionine ) , which was reported to be crucial for the nuclear localization of CDC14B1 [17] . Thus , we hypothesized that the N-terminal substitutions that occurred during the phase of positive selection were associated with a change in subcellular localization of CDC14Bretro in the African ape ancestor . To obtain the necessary background information for testing this hypothesis , we first sought to assess the subcellular localization of CDC14Bpar relative to the other 3' splice variants of the CDC14B parental gene , because it represents a novel protein variant with a previously uncharacterized subcellular localization . Protein localization experiments of the CDC14B splice isoforms with fluorescent reporters fused to their C termini ( Figure 1A ) show that whereas CDC14B1 ( nucleoli ) and CDC14B2 ( nuclear speckles ) localize to the nucleus in interphase cells as previously described [17] ( Figure 1B and 1C and Figure S1 ) , CDC14Bpar and the other previously uncharacterized variant CDC14B3 show highly structured filaments throughout the cell , reminiscent of microtubules ( MT ) ( Figures 1E , 1D , and S1 ) . Microtubular staining of transfected cells revealed that these two CDC14B isoforms indeed co-localize with MTs ( Figure 1D and 1E and Figure S1 ) . We note that CDC14B1 shows microtubular association in a small proportion of cells , consistent with a previous report that found microtubular co-localization of this variant in 14% of transfected cells [17] . This study also showed that a CDC14B1 mutant protein with an altered KKIR motif shows increased microtubular association . Together , these results suggest that all CDC14B splice variants have the inherent capacity to co-localize with microtubules , and that in addition to the N terminus , the C-terminal part of CDC14B is crucial for the subcellular localization of the different splice isoforms . In the case of CDC14Bpar and CDC14B3 , their specific C-terminal sequences apparently override the nuclear localization signal . This notion is supported by a CDC14Bpar recombinant protein that lacks the C-terminal domain; this truncation mutant localizes to the nucleus ( Figure S2 ) . Thus , we reasoned that the seven amino acid substitutions that occurred during the phase of positive selection in the C terminus of CDC14Bretro ( Figure 4 ) might—in addition to the substitutions in the N terminus ( see above ) —also have contributed to a potential subcellular localization shift in African apes . Prompted by these observations , we proceeded to directly test the hypothesis of a subcellular localization shift of CDC14Bretro in the African ape ancestor . To this end , we reconstructed the ancestral sequences of the last common ancestor of great apes and African apes , representing the CDC14Bretro variants before ( node B ) and after ( node A ) the period of positive selection ( Figures 3A and 4; see Materials and Methods for details ) . Subcellular localization experiments of the proteins expressed from these resurrected genes showed that CDC14Bretro from node B co-localizes with MTs during interphase , similar to the parental protein CDC14Bpar ( Figure 3F and Figures S3 and S4 ) . In sharp contrast , CDC14Bretro from node A did not localize to microtubules , but rather displayed a new localization pattern with nonfilamentous fluorescent signals around the nucleus ( Figure 3B and Figures S3 and S4 ) . CDC14Bretro from human , chimpanzee , and gorilla shows localization patterns similar to that of the node A sequence ( Figure 3B and 3C and Figures S3 , S5A , and S5B ) , whereas CDC14Bretro from orangutans and gibbons shows microtubular association ( Figure S5C and S5D ) , like CDC14Bretro from node B . Thus , except for some small differences between individual extant CDC14Bretro variants , the localization patterns before and after the phase of positive selection have been largely preserved in the Asian and African apes , respectively . This is consistent with the evidence for purifying selection in these lineages ( dN/dS < 1 , p < 10−2 for both African and Asian apes; Figure 3A ) . The evidence of functional preservation by purifying selection further supports functionality of CDC14Bretro , in addition to our original evidence of the conservation of its open reading frame by purifying selection ( the paucity of non-neutral insertion/deletions; [6] ) . We note , however , that the evolution of CDC14Bretro in the descendant ape lineages has generally been less constrained than that of its parent ( Figure S6 , p < 10−2 ) , which may be indicative of ( further ) functional adaptation and/or some relaxation of selection at certain sites of the CDC14Bretro protein in apes . Although CDC14Bretro appears to have accumulated particularly many amino acid substitutions on the gibbon lineage ( Figures 3A and 4 ) , the synonymous substitution rate was high on this lineage as well ( as also reflected by the low dN/dS ratio ) . This suggests that CDC14Bretro function was generally selectively preserved by purifying selection , consistent with the preservation of the ancestral MT localization ( see above , Figure S5 ) . Using human CDC14Bretro and CDC14Bpar as representatives of the new and ancestral protein variants , respectively , we show that the subcellular shift is present throughout the cell cycle; whereas CDC14Bpar ( as well as CDC14Bretro of the Asian apes; unpublished data ) strikingly reorganizes from the microtubules in interphase to the spindle pole during mitosis ( Figure 3H and Figure S3 ) and intercellular bridge during cytokinesis ( Figure 3I and Figure S3 ) , human CDC14Bretro lacks association with microtubules also during these phases of the cell cycle ( Figure 3D and 3E and Figure S3 ) . To characterize the new cellular localization of CDC14Bretro from African apes , we co-stained cells transfected with the human CDC14Bretro construct using 13 different cellular markers ( Materials and Methods and Figure S7 ) . Human CDC14Bretro co-localizes with a marker of the endoplasmic reticulum ( ER ) in interphase cells ( Figure 5A and Figure S8 ) . CDC14Bretro from node A shows a similar ER co-localization pattern ( Figure 5B and Figure S8 ) . Furthermore , human CDC14Bretro retains its ER localization during mitosis ( Figure 5C ) , which suggests that CDC14Bretro from humans/African apes does not associate with microtubules at any phase of the cell cycle but remains associated with the ER . Proteins that are targeted to enter the lumen of the ER have well-described signal peptides with characteristic properties . These include a stretch of 5–15 hydrophobic amino acids that is preceded by a positively charged ( basic ) amino acid , which allow the protein to pass through the hydrophobic ER membrane . Visual inspection and in silico prediction programs of the N-terminal sequences of CDC14Bretro from African apes reveal no evidence of such signal peptides that could target the protein to the ER or secretory pathway ( see Materials and Methods for details ) . This suggests that CDC14Bretro from African apes localizes to the cytosolic face of the ER , thus probably binding to substrates and/or protein interaction partners on the ER membrane . We conclude that CDC14Bretro evolved a dramatically altered subcellular localization during the cell cycle in the African ape ancestor ∼7–12 Mya [15] , shifting from the ancestral microtubular association to a new localization on the cytosolic face of the ER—a process likely driven by positive selection . To elucidate which substitutions that occurred during the period of positive selection were responsible for the subcellular shift in the African ape ancestor , we generated hybrid constructs of the ancestral CDC14Bretro gene variants . Hybrid proteins , where the N and C termini correspond to the node B sequence but the phosphatase core domain corresponds to that of node A ( hybrid BAB ) , show microtubular localization very similar to that seen for the node B protein in ∼53% of cells ( Figure 6 ) . A hybrid protein where the N and C termini correspond to the node A sequence and the core domain to that of node B ( ABA ) loses the filamentous microtubular association in the majority ( ∼80% ) of cells , although some association with MTs is retained ( Figure 6 ) . Thus , positively selected substitutions in the N- and C-terminal parts of CDC14Bretro have contributed to the shift in subcellular localization in the African ape ancestor , consistent with our original hypothesis ( which was based on the excess of amino acid replacements in the termini ) . In addition , substitutions in the core domain also affected the capacity for microtubular localization . Consequently , these results confirm that CDC14Bretro did not “simply” gain an N-terminal signal peptide that could target it to the ER lumen ( see above ) , but was rather shaped by substitutions throughout the protein that lead to a localization on the cytosolic face of the ER . The finding that substitutions in the phosphatase domain of CDC14Bretro from African apes have contributed to the subcellular shift may suggest that the change in subcellular localization was associated with the acquisition of a new function . We note that the subcellular localization of many enzymes depends on their catalytic activity/substrate binding ( e . g . , [23 , 24] ) . Thus , we hypothesize that the subcellular relocalization of CDC14Bretro in the African ape ancestor was due to a change in substrate and/or protein interaction partners . A recent report revealed evidence for some microtubular bundling and stabilizing activity of CDC14B1 in a fraction of cells [17] . Thus , to gain further insights into the functional shift associated with the change of subcellular localization in African apes , we tested the ability of the parental and retrogene variants of CDC14B to stabilize MTs by treating transfected cells with the MT depolymerization agent nocodazole . These analyses show that while CDC14Bpar and CDC14B3 effectively stabilize MTs , the other two , predominantly nuclear parental isoforms ( CDC14B1 and 2 ) show little or no stabilization capacity ( Figure 7 ) . The resurrected node B protein as well as CDC14Bretro from orangutan and gibbon show high stabilization capacity; as high ( node B protein ) , or almost as high ( orangutan , gibbon ) , as that of CDC14Bpar . The somewhat lower capacity of the orangutan and gibbon variants may be due to small , lineage-specific affinity changes . In contrast , CDC14Bretro from node A and its extant descendants have completely lost the ability to stabilize MTs , consistent with the absence of detectable microtubular localization and their likely new functional role on the ER . As predicted from the localization experiments ( loss of MT association ) , the hybrid construct ABA shows complete loss of MT stabilization activity . In spite of its microtubular association in ∼53% of cells ( see above ) , hybrid construct BAB loses MT stabilization capacity in most ( ∼85% ) of the cells ( Figure 7 ) . These results suggest that the localization and MT stabilization capacities are , to some extent , decoupled . The termini seem to be crucial for MT localization , while the core domain is necessary for MT stabilization . Thus , there seems to be a complex interplay of the different parts of the protein; both the protein termini and the core domain are needed for effective MT association and stabilization of the ancestral CDC14B variants . Together , the MT localization and stabilization analyses substantiate the view that most or all of the substitutions that occurred throughout the protein during the period of positive selection in the African ape ancestor were likely adaptive and required for the subcellular/functional shift of CDC14Bretro . In this study , we set out to characterize the CDC14B cell cycle gene and , in particular , the functional evolution of its daughter gene CDC14Bretro . We found that CDC14B , which has , as yet , not been characterized in detail , encodes four different splice isoforms that differ with respect to their subcellular localization ( nucleus or microtubule-associated ) and functional properties ( microtubular stabilization capacities ) as a consequence of their 3′ splicing patterns ( Figures 1 and 7 ) . This result has important consequences , as future studies of CDC14B need to take the presence of different isoforms into account and assess their functional roles separately . We have begun here to functionally characterize one of the novel splice variants , CDC14Bpar , and we find that it encodes a protein that is associated with MTs throughout the cell cycle . CDC14Bpar reorganizes from MTs in interphase to the spindle pole during mitosis and possesses a strong microtubular stabilization capacity ( Figures 1E , 3G–3I , 7 , and Figure S3 ) . Thus , the CDC14Bpar isoform may be involved in mitotic microtubule dynamics and organization . CDC14Bpar spawned a new retroduplicate gene copy , CDC14Bretro , which was fixed in the common hominoid ancestor ( Figure 1A ) . It adopted or evolved brain and testis expression soon after the duplication event . A shift toward an enlarged neocortex and enhanced cognitive capacities relative to other primates occurred in the hominoid ancestor , presumably driven by selection for increased social complexity [25] . Conceivably , the fixation of CDC14Bretro—like that of another hominoid-specific retrogene [8]—might have been associated with the evolution of the more complex ape brain . In this context , it is interesting that we detected CDC14Bretro expression in the early human embryonic brain , which might point to a role of this gene in neural development . But what functional role might it have obtained in the hominoid brain and/or testis ? Our functional analyses—demonstrating conservation of ancestral MT localization and stabilization patterns of CDC14Bretro from the great ape ancestor and the extant Asian apes—suggest that until the evolutionary separation of African and Asian apes ∼12 Mya [15] , CDC14Bretro may have been functionally preserved ( and advantageous ) to provide increased dosage of the CDC14Bpar parental isoform during the cell cycle of these tissues . In the African ape ancestor , a radical shift toward a new localization on the ER then occurred . The subcellular/functional shift of CDC14Bretro was perhaps facilitated by the evolution of increased brain ( testis ) expression of CDC14Bpar , which might have released selective pressure to retain a second CDC14B gene copy with similar functional properties in the African ape ancestor . Although CDC14Bretro apparently retained its phosphatase function ( all sites required for its phosphatase activity have remained unchanged ) , it very likely changed its substrate and/or protein interaction partners after relocalizing to the ER . The new function of CDC14Bretro from African apes on the ER may be unrelated to the cell cycle , although we note that a cell cycle–related function of CDC14Bretro might not be so unlikely , in view of a growing body of work revealing important ties of the ER and the cell cycle ( e . g . , [26] ) . However , the precise new role of CDC14Bretro on the ER of the African ape brain and testis warrants further experimental scrutiny . In any event , the signature of positive selection driving this subcellular/functional adaptation suggests that it is a function that has been beneficial to African apes . More generally , our study reveals a new mode with respect to how new gene copies may obtain new functional roles . A recent study indicated that new genes that emerge through a complex combination of segmental duplications and genomic rearrangements ( including exon gain/loss ) may evolve new localization patterns [27] . Our work here reveals that subcellular shifts of new duplicate proteins may occur through rapid and adaptive protein evolution , driven by intense positive selection . But how frequently has the process of subcellular adaptation occurred during evolution ? It has been shown in various individual molecular studies that proteins from the same family may show different subcellular localization patterns in mammals ( e . g . , [28] ) . Indeed , a recent global survey ( using yeast as a model system ) suggests that protein subcellular adaptation represents a rather common mechanism through which duplicate genes may functionally diversify [29] . Thus , we believe that in addition to changes in gene expression and/or biochemical function [30] , rapid and selectively driven adaptation to new subcellular compartments—as exemplified by the new hominoid CDC14Bretro protein—may represent a widespread mechanism underlying the evolution of new gene function .
Total RNA preparations from normal adult human brain , colon , heart , kidney , liver , lung , ovary , spleen , stomach , testis , thymus , and thyroid were purchased from AMSBio , and human amygdala , cerebellar hemisphere , cerebellum , hippocampus , hypothalamus , frontal cortex , motor cortex , and prefrontal cortex from Ambion . Total adult brain- , liver- , and testis-RNA from chimpanzee and gibbon , were extracted from post-mortem tissues , kindly provided by S . Pääbo and colleagues , using the Maxwell 16 Total RNA purification kit ( Promega ) . Total RNA from gorilla ( EB ( JC ) ) and orangutan ( EB185 ( JC ) ) cell lines ( ECACC repository , Wiltshire , UK ) was extracted using a Maxwell 16 Total RNA purification kit ( Promega ) . RNA from human fetal forebrain , dorsal telencephalon ( from day 63–67 stages ) , and liver ( from 19 gestational weeks ) was extracted using Trizol and a mirVana RNA extraction kit ( Ambion ) , followed by DNAse treatment with the DNA-free kit ( Ambion ) , according to manufacturer's instructions . Reverse transcription of total RNA was done using SuperScript III first-strand system for RT-PCR ( Invitrogen ) following the instructions of the supplier . Final RNA concentration per reverse-transcription reaction was 1 . 25 ng/μl . The expression patterns of human CDC14Bretro and the four CDC14B splice variants were determined by PCR using the cDNA libraries described above . Actin expression was monitored as a positive control . PCR reactions were done using JumpStart DNA Polymerase ( Sigma-Aldrich ) and primer pairs specific for the different CDC14Bretro and CDC14B parental gene variants ( primer sequences available upon request ) . cDNA concentration per PCR reaction was 8% ( v/v ) . Amplifications were performed in a Mastercycler gradient ( Eppendorf ) using a standard cycling protocol . PCR reactions were repeated using independent cDNA preparations from different panels ( derived from different individuals ) . To map the 5′ end of human CDC14Bretro , we used the FirstChoice RACE-Ready cDNA system ( Ambion ) following the manufacturer's protocol . An aliquot of 0 . 5 ng of cDNA was used as template for the PCR . We used a primer specific to the CDC14Bretro untranslated region ( sequence available upon request ) and 5′-RACE outer primer ( provided in the kit ) . The PCR reaction product was further amplified using a nested CDC14Bretro UTR-specific primer and 5′-RACE inner primer ( kit ) . The resulting PCR product was purified using the GenElute PCR-cleanup system from Sigma , cloned into the pGEM-T easy vector ( Promega ) , and then sequenced . The phylogenetic tree of the CDC14B coding sequences was reconstructed using a maximum likelihood procedure ( DNAML ) as implemented in the Phylip package [31] ) . The topology of the CDC14B sequences in the tree reflects the accepted species phylogeny [15] . Other reconstruction methods , such as Bayesian phylogeny reconstruction using the Markov Chain Monte Carlo method ( as implemented in the MrBayes program , [32] ) , yield identical topologies . dN/dS ratios in the phylogenetic tree were estimated using the codeml free-ratio model as implemented in the PAML4 package ( http://abacus . gene . ucl . ac . uk/software/paml . html ) [33] . To test if the observed excess of nonsynonymous substitutions in the lineage leading to African apes was a consequence of positive selection , we first compared a one-ratio model ( that assumes an equal dN/dS ratio for all the branches in the phylogeny ) to a two-ratio model , where an additional dN/dS value is allowed on the African ape lineage . The two models were compared using the likelihood-ratio test [34] , and the two-ratio model was found to fit the data significantly better ( p < 10−4 ) than the one-ratio model . To test whether the dN/dS value of the branch of the common African ape ancestor was significantly different from 1 , we compared its likelihood to that of a model where dN/dS on this lineage was fixed to 1 . In addition , we tested statistical significance of the excess of amino acid substitutions in the N- and C-terminal sequences compared to the core domain of CDC14Bretro from the African ape ancestor using Fisher's exact test ( nine amino acid substitutions at 139 sites of the termini , 3/338 sites in the core domain ) . To test for purifying selection ( dN/dS < 1 ) on the descendant African ape ( since their last common ancestor ) and Asian ape lineages , respectively , we compared the likelihood of models where dN/dS was fixed to 1 to models where dN/dS was estimated from the data . To test for dN/dS rate differences between CDC14Bretro from African apes ( since their last common ancestor ) /Asian apes and CDC14Bpar , we compared models where the rate was the same for the two groups to models where the rates were allowed to be different ( see also Figure S6 ) . The ancestral sequences for nodes A and B were reconstructed using a maximum likelihood procedure ( one-ratio model , M0 ) as implemented in codeml ( the same sequences are obtained using other standard codeml models such as the free-ratio model ) . Posterior probabilities for all reconstructed codons of these sequences are high ( p ≥ 0 . 99 ) . The same sequences are also obtained using other procedures such as maximum parsimony ( unpublished data ) . We note that posterior probabilities for all reconstructed sites throughout the tree are high ( p ≥ 0 . 95 ) . To screen for potential signal peptides in CDC14Bretro from African apes and predict its subcellular localization in silico , we used several different program packages , including: SignalP ( version 3 . 0; http://www . cbs . dtu . dk/services/SignalP/ ) , TargetP ( v1 . 1 , http://www . cbs . dtu . dk/services/TargetP/ ) , pTARGET ( http://bioapps . rit . albany . edu/pTARGET/ ) , and PREDATOR ( http://bioweb . pasteur . fr/seqanal/interfaces/predator . html ) . Neither of the programs provides any evidence that CDC14Bretro from African apes has an N-terminal signal peptide targeting it to the ER or secretory pathway . Complete coding sequences for the four alternatively spliced CDC14B isoforms were obtained by PCR using human testis cDNA . CDC14Bretro coding sequences were obtained by PCR ( primers sequences available upon request ) using the following primate genomic DNA samples from the ECACC repository ( Wiltshire , UK ) : Human “Caucasian , ” chimpanzee ( Pan troglodytes ) , gorilla ( Gorilla gorilla ) , and orangutan ( Pongo pygmaeus ) . The gibbon/siamang ( Symphalangus syndactylus ) sample was kindly provided by C . Roos . The sequences reconstructed for nodes A and B were synthesized and cloned by GenScript . Hybrids ABA and BAB were obtained through directed mutagenesis by introducing substitutions A149E , P161S , and R298G in the node A and E149A , S161P , and G298R in the node B sequence ( all primers and restriction enzymes used are available upon request ) . All inserts were cloned into pEGFP-N1 or pDsRed-N1 ( Clontech ) vectors using standard procedures ( recombinant proteins expressed from these vectors carry the fluorescent reporters at their C termini ) . COS7 , HeLa , and LN229 cells were cultivated under standard conditions . 24 h before transfection , cells were plated on 18-mm coverslips in 12-well cluster culture vessels . Transient transfection was carried out using the Lipofectamine Plus method ( Invitrogen ) . For immunofluorescence analyses , cells were fixed in 3% formaldehyde for 10 min at room temperature 24 h after transfection . Monoclonal anti-beta tubulin ( Invitrogen ) , polyclonal anti-GRP94 ( Abcam ) , monoclonal anti-calreticulin ( BD transduction laboratory ) , monoclonal anti-GM130 , monoclonal anti-caveolin ( Abcam ) , monoclonal anti-vimentine ( Sigma ) , monoclonal anti-vinculine ( Sigma ) , and monoclonal anti-TGN46 ( Abcam ) were used as primary antibodies for the subcellular localization analyses . Alexa Fluor 594 goat anti-mouse IgG ( H+L ) ( Invitrogen ) , Anti-Mouse Polyvalent Immunoglobulins-FITC from goat ( Sigma ) , and Alexa Fluor 594 chicken anti-rabbit IgG ( H+L ) ( Invitrogen ) were used as secondary antibodies . Organelles were stained as follow: Golgi and membrane with WGA-Alexa Fluor 568 ( Invitrogen ) , mitochondria with MitoTracker Red CMXRos ( Invitrogen ) , lysosomes with LysoTracker Red DND-99 , peroxisomes with the SelectFX Alexa Fluor 488 Peroxisome Labeling Kit ( Invitrogen ) , and nuclear DNA with DAPI ( Sigma ) . Cells were analyzed using a Confocal Microscope Zeiss LSM 510 Meta INVERTED by using a 63-fold oil objective . We used LSM for image analysis . For the nocodazole washout experiments , COS7 cells were treated with nocodazole ( Sigma ) at a final concentration of 10 μg/ml for 2 h , 22 h after transfection . The drug was removed by warm phosphate-buffered saline ( PBS ) treatment . Cells were fixed at 2 min after washout in 3% formaldehyde and then stained with an anti-beta tubulin antibody . To perform blind counting of cells with different phenotypes , a coded name was assigned to each lamelle with respect to the plasmid used for the transfection . For each condition , the proportion of cells with intact microtubules was assessed by counting 50–100 cells at 63-fold magnification over ten arbitrarily chosen areas . Each experiment was repeated five times . Differences between treatment groups were evaluated using ANOVA followed by a Post Hoc ( Tukey HSD Test ) , with significance set at p < 0 . 05 . The human fetal material was used according to the guidelines of the three relevant local Ethics Committees ( Erasme Academic Hospital , University of Brussels , and Belgian National Fund for Scientific Research ) on Research Involving Human Subjects . Written informed consent was given by the parents in each case .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank/ ) accession numbers for genes discussed in this paper are: CDC14B1 cDNA ( AF023158 ) ; CDC14B2 ( AF064104 ) ; CDC14Bpar ( EF611343 ) ; CDC14Bretro ( termed CDC14B2 in GenBank ) human ( DQ120635 ) , chimpanzee ( DQ120636 ) , gorilla ( DQ120637 ) , orangutan ( DQ120638 ) , and siamang ( EF606887 ) . The Ensembl ( http://www . ensembl . org ) accession code for CDC14B3 is ENST00000265659 .
|
Many new gene copies emerged by gene duplication in human and ape ( hominoid ) ancestors . However , little is known with respect to their functional evolution . We used a combination of evolutionary analyses and cell biology experiments to unveil the adaptive evolution of the hominoid-specific CDC14Bretro gene , which arose as a reverse-transcribed copy of a messenger RNA of its “parent , ” the CDC14B cell cycle gene . We first show that the CDC14B parental gene encodes different splice isoforms that differ with respect to their subcellular localization and functional properties . One of these isoforms , which is associated with microtubules throughout the cell cycle ( stabilizing them and potentially contributing to their organization ) , spawned CDC14Bretro in the common ape ancestor 18–25 million years ago . In the African ape ( human/chimp/gorilla ) ancestor , around 7–12 million years ago , intense positive selection then led to rapid relocalization of the CDC14Bretro protein from microtubules to a new cellular location—the endoplasmic reticulum . This radical subcellular shift likely reflects the evolution of a new function of CDC14Bretro in the African ape lineage . In contrast , CDC14Bretro retained the ancestral ( parental ) localization and function in Asian apes ( orangutans and gibbons ) . Our study not only adds to the rare known cases of ape-specific genes for which selectively driven substitutions could be tied to functional protein change and adaptation , but , more generally , reveals a novel mode that may underlie the emergence of new gene function: rapid , selectively driven subcellular adaptation .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"cell",
"biology",
"evolutionary",
"biology"
] |
2008
|
Birth and Rapid Subcellular Adaptation of a Hominoid-Specific CDC14 Protein
|
The organization of cells , emerging from cell–cell interactions , can give rise to collective properties . These properties are adaptive when together cells can face environmental challenges that they separately cannot . One particular challenge that is important for microorganisms is migration . In this study , we show how flagellum-independent migration is driven by the division of labor of two cell types that appear during Bacillus subtilis sliding motility . Cell collectives organize themselves into bundles ( called “van Gogh bundles” ) of tightly aligned cell chains that form filamentous loops at the colony edge . We show , by time-course microscopy , that these loops migrate by pushing themselves away from the colony . The formation of van Gogh bundles depends critically on the synergistic interaction of surfactin-producing and matrix-producing cells . We propose that surfactin-producing cells reduce the friction between cells and their substrate , thereby facilitating matrix-producing cells to form bundles . The folding properties of these bundles determine the rate of colony expansion . Our study illustrates how the simple organization of cells within a community can yield a strong ecological advantage . This is a key factor underlying the diverse origins of multicellularity .
Many properties of biological systems come about through the interactions of the parts that compose such systems . These so-called collective properties are said to “emerge” from these interactions , because they cannot be produced by the parts separately [1–3] . The most remarkable collective properties are found in multicellular organisms , where cell–cell interactions result in a bewildering diversity of forms and functions that cannot be generated by the cells in isolation [4–7] . Cell differentiation is an important factor underlying this diversity [8 , 9] . Cell types that differ in their adhesive properties , motility , or shape interact with each other and thereby guide developmental change [5 , 10] . When a collective property is adaptive , cell types that give rise to this property can be favored by selection [11–13] . The evolution of cell differentiation and collective properties can therefore go hand in hand [5] . Collective properties are often studied in species where cells can live independently , but often choose not to . These species are ideal for studying why and when cells form collectives and how these collectives come about . One of the most remarkable examples of such voluntary cell collectives comes from the soil-dwelling bacterium Myxoccocus xanthus [3 , 14] . During predation of other bacteria , thousands of M . xanthus cells coordinate their behavior to lyse and degrade prey [15] . When nutrient levels decrease , M . xanthus cells aggregate and assemble into a fruiting body filled with many thousands of spores [16 , 17] . The aerial projections of the fruiting body are thought to aid in spore dispersal [18] . Whereas it is a major challenge for individual cells to disperse , the cell collectives solve this problem by sticking out from the soil [1 , 2 , 8 , 9 , 19] . Dispersal is a major challenge for many soil-dwelling microorganisms . As a result , aerial spore-containing structures evolved independently in a number of bacterial and eukaryotic species , through the process of convergent evolution [20–22] . Another major challenge for soil-dwelling organisms is migration: how to get from one soil particle to the next . Without the possibility of swimming through liquid , cells have to find alternative ways to migrate [9] . These are often studied by examining colony growth patterns [19 , 23–27] . For example , Paenibacillus vortex migrates by making vortices that consist of millions of cells that swirl around over agar surfaces , producing beautiful fractal growth patterns [19 , 28 , 29] . A closely related species , Bacillus mycoides , forms chiral branching patterns that orient clockwise or counterclockwise while expanding over the agar surface [30] . A number of other species from the same bacterial families , Bacillaceae and Paenibacillaceae , have been studied as well with respect to colony growth patterns [26 , 31–35] . In all cases , cells solve the challenge of migration by migrating together . Yet how cells coordinate migration is often unknown: which cell types drive migration and how do they interact ? This lack of knowledge is partly because little is known about the cell types that are expressed during colony growth . Interestingly , one species from the Bacillaceae family , B . subtilis , produces a number of different cell types and has been intensely studied with respect to cell differentiation [36] . The phenotypes of these cell types are well characterized [37] . B . subtilis therefore is the ideal species to examine if and how different cell types guide the migration of cell collectives . Furthermore , it gives a unique opportunity to examine how adaptations at the cell level relate to the collective properties that emerge from them . B . subtilis can express at least five distinct cell types , which are often studied in the context of biofilm formation . Each of these cell types is associated with a unique set of phenotypes: motility , surfactin production , matrix production , protease production , and sporulation [36–39] . Motile cells synthesize flagella that can be used for swimming . Surfactin-producing cells secrete surfactin , a surfactant that reduces water surface tension [21 , 40] , functions as a communication signal [41 , 42] , and acts as an antimicrobial [43] . Matrix-producing cells secrete an extracellular polysaccharide ( EPS ) and the structural protein TasA [44 , 45] . EPS acts as a “glue” that surrounds cells inhabiting the biofilm . In addition , colony wrinkling requires EPS , and under some conditions , colony expansion also depends on EPS [46–48] . TasA assembles into amyloid-like fibers that attach to the cell wall and , like EPS , is required for colony wrinkling [45 , 49 , 50] . Since tasA and eps mutants complement each other when cocultured , TasA and EPS are considered common goods that are shared between cells [45 , 51] . In addition to EPS and TasA , matrix-producing cells secrete antimicrobial compounds that can kill sibling cells and other soil-dwelling organisms [52] . Protease-producing cells secrete proteases that facilitate nutrient acquisition [53 , 54] . Finally , cells can differentiate into spores: stress-resistant cells that can survive long periods of desiccation and nutrient limitation [55] . The regulatory mechanisms underlying cell differentiation in B . subtilis are well-characterized [37] . In addition , most cell types have been associated with some colony-level properties , although a detailed causal relation is often lacking [56] . Here we study how cell differentiation affects the migration of cell collectives during B . subtilis colony expansion via sliding motility . We grow bacteria on a specific medium that prevents cells from swimming and swarming ( which both rely on flagella ) , but still allows for colony expansion . In this way , we can examine whether colony expansion depends on cell differentiation , and if so , how the interactions between cell types drive migration . We show that migration depends critically on two cell types: surfactin-producing and matrix-producing cells . Together they drive migration through a mechanism in which cell collectives form highly organized bundles at the colony edge , which we have termed “van Gogh bundles . ” Van Gogh bundles are formed from many tightly aligned filaments consisting of chains of cells . They appear elastic and fold into filamentous loops that push themselves away from the colony . Surfactin-producing and matrix-producing cells divide labor during the formation of van Gogh bundles . We propose that surfactin-producing cells reduce the friction between cells and their substrate , which facilitates formation of the van Gogh bundles by the matrix-producing cells . Whereas EPS production is necessary for the formation of these bundles , TasA seems to fine-tune their biophysical properties . Finally , as a complement to the experiments , a mathematical model illustrates how simple cellular properties can affect a bundle’s folding properties and hence the migration rate .
We studied migration by examining colony growth on MSggN [57] . MSggN is a growth medium that induces colony expansion and resembles the biofilm-inducing medium , MSgg , that is typically used to study cell differentiation in the context of B . subtilis biofilms [21 , 38 , 57] . Colony expansion is more apparent on MSggN than on MSgg , which makes the former more suitable for studying migration ( see Materials and Methods ) . Colony growth on MSggN consists of two main phases that are morphologically distinct ( Fig 1; see also [57] ) . First , the colony forms dendrites that spread radially from the inoculum . Second , phenotypically distinct outgrowths , which we call “petals , ” appear at the end of the dendrites . In some instances the petals change into another morphological structure at the colony edge , which we call “rays . ” The distinct growth phases do not result from genetic change , because cells from the morphologically distinct regions of the colony behave the same as wild type ( WT ) when re-inoculated onto a fresh growth medium ( S1 Fig ) . To determine which cell types are involved in colony expansion we tested mutants deficient in the production of surfactin ( srfA mutant ) , extracellular matrix ( eps and tasA mutants ) , spores ( sigF mutant ) , and flagella ( hag mutant ) . Both surfactin-producing and matrix-producing cells were necessary for colony expansion , whereas motility and sporulation mutants showed a nearly WT colony expansion ( Fig 1 ) . We examined two matrix-related mutants: eps and tasA . While the eps mutant did not show any degree of colony expansion , tasA mutants did expand beyond the colony boundaries present at inoculation , although the expansion was much less than that of WT ( Fig 1 ) . These results are in agreement with previous studies that showed that B . subtilis colony expansion on MSggN is independent of flagellum formation , but requires surfactin production [57–59] . In addition , our experiment showed that matrix-producing cells are also required for colony expansion . To examine whether colony expansion could be recovered by extracellular complementation , different pairs of expansion-deficient mutants were cocultured as chimeric colonies [60] . Such two-mutant cocultures can reveal something about the interactions between different cell types during colony growth [45 , 61] . All examined chimeric colonies in which mutant cells were mixed at a 1:1 ratio showed a partial to full recovery of colony expansion when compared to the WT ( Fig 2A ) . Interestingly , two of the chimeric colonies appeared to outperform WT in the extent of colony expansion: srfA + eps and eps tasA + srfA . Thus , the task differentiation of matrix and surfactin production by mutant strains enhanced the degree of colony expansion . To further examine these fast-expanding chimeric colonies , we varied the initial ratio of strains deficient in surfactin ( srfA ) and matrix ( double mutant eps tasA ) production . Colonies were compared 24 h after inoculation . In chimeric colonies that contained many eps tasA mutant cells , there was little colony expansion ( Fig 2B , 9:1 eps tasA:srfA ) , and in chimeric colonies with many srfA mutant cells , colonies expanded far ( Fig 2B , 1:9 eps tasA:srfA ) . In the eps tasA + srfA chimera , eps tasA mutant cells are responsible for surfactin production and srfA mutant cells are responsible for matrix production . Therefore , we conclude that the extent of colony expansion is mostly constrained by the number of cells that produce matrix: a small number of surfactin-producing cells is sufficient to fully restore colony expansion ( see Fig 2B , 1:9 eps tasA:srfA ) , while a small number of matrix-producing cells is not ( see Fig 2B , 9:1 eps tasA:srfA ) . Finally , we examined chimeric colonies of strains that were marked with different fluorescent reporters . This allowed us to determine how strains mixed in space when grown together . Interestingly , not all strain combinations mixed homogeneously . When strains differed in terms of matrix production , for example , in a chimera of a matrix-deficient mutant ( eps tasA ) and the WT strain , spatial segregation was observed ( Fig 2C ) . This directly affected colony expansion . Even though the WT strain has the potential to fully expand over the agar plate , it could not expand when strongly outnumbered by the matrix-deficient strain in the initial inoculum ( Fig 2C , 19:1 eps tasA:WT ) . This suggests that matrix-deficient cells prevent WT cells from migrating . Mutant cells might simply block WT cells by surrounding them at the colony edge ( Fig 2C ) . Alternatively , in the presence of mutant cells , the appropriate environmental signals to trigger colony expansion might be lacking . When the fraction of WT cells in the inoculum increased ( from left to right in Fig 2C ) , the WT could expand over the agar plate . In that case , both strains were found in the expanded section of the colony . Thus , in addition to matrix-producing cells facilitating colony expansion , matrix-deficient cells can inhibit colony expansion . The chimeric colonies showed that colony expansion depends on the presence of both surfactin-producing and matrix-producing cells . In the next sections we examine how these cell types interact in the WT and consequently drive migration . To study surfactin-producing and matrix-producing cells in a WT strain , we used a double-labeled strain in which the expression of two fluorescent reporters , genes coding for yellow ( YFP ) and cyan ( CFP ) fluorescent proteins , is under the control of the promoter for surfactin biosynthesis genes ( PsrfA ) and the tasA operon promoter ( PtapA ) , respectively [42] . Thus , in the double-labeled strain , surfactin-producing cells express YFP , and matrix-producing cells express CFP . First , we examined the temporal gene expression dynamics by performing a time-course experiment . Colonies were examined every 2 h for 12 h after inoculation , as well as at 24 h and 31 h after inoculation ( Materials and Methods ) . Since the srfA promoter is very weakly expressed , it was impossible to detect using flow cytometry . Instead , direct microscopy was performed on the colony samples , which were first dispersed in phosphate buffered saline ( PBS ) buffer to get a representative fraction of cells . At every time point , microscopy pictures were taken from a labeled WT strain ( n = 20–50 microscopy images ) and , as a control , an unlabeled WT strain ( n = 10–30 microscopy images ) . Since it was impossible to accurately analyze all of the images manually ( n = 439 ) , a MatLab program was used to quickly select , process , and statistically analyze the images ( see Materials and Methods for details; [62] ) . Fig 3A shows the expression of srfA and tapA over time . The expression pattern is characterized by two phases: in the first phase there is a peak in the average expression of srfA , while in the second phase there is sharp increase in the average expression of tapA ( Fig 3A ) . Fig 3B shows a representative image from each of these two phases . At the onset of colony growth there is also a slight peak in tapA expression , which is due to background expression in the inoculation conditions ( for details see Materials and Methods ) . When taking the time frame of gene expression into consideration , the up-regulation of srfA corresponds to dendrite formation , and the up-regulation of tapA corresponds to petal formation ( Figs 1 and 3 ) . The distinct growth phases that are apparent at the macroscopic level therefore relate to gene expression dynamics at the cell level ( microscopic ) . The same microscopy images were used to examine the co-expression of srfA and tapA . As expected from previous studies [42] , the expression of srfA and the expression of tapA were mutually exclusive ( S1 Text; S2 Fig ) . This confirmed that also for our growth conditions , surfactin-producing and matrix-producing cells are mutually exclusive and distinct cell types ( S2 Fig ) . Next we studied the spatial arrangement of surfactin-producing and matrix-producing cells . Colonies were examined by cutting a piece of the agar at the colony edge . This agar piece was subsequently flipped onto a glass-bottom well , sandwiching the cells between the coverslip and an agar pad , and the cut piece of colony edge was subjected to a detailed microscopic examination ( for details see Materials and Methods ) . The advantage of this technique is that intact cell collectives could be observed , as they would occur in growing colonies . Examining these cell collectives is particularly important because it might help in understanding how cells migrate during colony expansion . However , a disadvantage of the technique is that colonies can be examined only at the edge , where a monolayer of cells exists , which is necessary for accurate quantification of fluorescent images . The colony edge was dissected at different time points ranging over two colony growth phases: dendrite formation ( <11–13 h ) and petal formation ( >11–13 h ) ( summarized at the top of Fig 4 ) . During dendrite formation , cells aggregate into clumps . These clumps consist of matrix-producing cells ( false-colored green ) and are surrounded by surfactin-producing cells ( false-colored red , Fig 4A ) . The clumps appear within a few hours after inoculation . Even when we made certain that there were no surfactin-producing or matrix-producing cells present in the inoculum ( by performing a passaging experiment , see Materials and Methods ) clumps formed rapidly . The clumps were relatively unorganized: the shape , size , and location varied strongly ( Fig 4A shows one example ) . Although both surfactin producers and matrix producers are necessary for dendrite formation , as is evident from the mutant phenotypes ( Fig 1 ) , it is unclear if and how these clumps contribute to dendrite formation . During the transition between the first growth phase ( dendrite growth ) and the second growth phase ( formation of petal-shaped colony outgrowths at the tip of the dendrites ) ( Fig 1 ) , a new type of aggregate appeared ( Fig 4B ) . As was observed for clumps , there was strong spatial segregation between surfactin-producing and matrix-producing cells: matrix-producing cells occurred inside the bundle , whereas surfactin was expressed by cells surrounding the bundle . Interestingly , in contrast to aggregates in the first growth phase , the bundles appear organized . The bundles consist of many cellular filaments that are arranged side by side and are only a single cell layer thick . During the transition , the bundles seem to push themselves out of the colony edge ( i . e . , away from the single cells ) . The coordinated appearance of the bundles is even more striking at later time points . Fig 5A and 5B show the colony edge after 34 h of colony growth . At this point , the colony edge consists of only the well-organized bundles . Henceforth , we refer to these bundles as “van Gogh bundles , ” because of the resemblance of these cell collectives to the brushstrokes in van Gogh’s The Starry Night . The organized appearance of van Gogh bundles results from a remarkably strong alignment of cells inside the bundles ( S2 Text ) . This is especially apparent when comparing the alignment of cells inside van Gogh bundles to the alignment of cells at the colony edge earlier in colony growth ( S3–S5 and S7 Figs ) . In fact , when considering only the alignment of cells , one can discriminate regions in a microscopy image that contain van Gogh bundles from regions that do not ( S6 Fig ) . Furthermore , van Gogh bundles appear flexible . When flipping the colony onto the glass-bottom well , the bundles sometimes folded ( Fig 5B ) , yet they hardly ever broke . Thus , adhesive forces between the cells must keep them aligned and attached such that shear forces or friction do not break them . In the chimeric colonies of strains with expansion-deficient mutations , described above , colony expansion was partly or fully recovered ( Fig 2 ) . From the previous section , one expects that the recovery of colony expansion results from the formation of van Gogh bundles . To test this , we examined the chimeric colonies using microscopy . Colonies were examined at the start of the second growth phase ( i . e . , the start of petal outgrowths ) , when both single cells and van Gogh bundles were expected to be present ( see S8 Fig ) . The strains in the chimeric colonies were marked with fluorescent reporters , so that their spatial arrangement could be examined as well . Fig 6 shows that all chimeric colonies produced van Gogh bundles , although the bundles were not always as apparent as those in WT colonies ( e . g . , the eps + tasA chimera showed less apparent bundle formation ) . Thus , the recovery of colony expansion coincided with the emergence of van Gogh bundles during colony growth . In contrast , most mutants could not produce van Gogh bundles by themselves ( see below ) . Interestingly , although both mutant strains were necessary for recovering the van Gogh bundles , not all cells became part of the van Gogh bundles . The fluorescent overlays show that the van Gogh bundles were made up of cells from the EPS-producing strains only . This is particularly apparent for the first and last mutant chimeras ( e . g . , srfA + eps and eps tasA + srfA ) , in which EPS-deficient cells never formed cell chains that were part of the van Gogh bundle ( Fig 6 ) . In cases where both strains produced EPS , such as in the srfA + tasA chimera , van Gogh bundles did consist of cells from both strains , with the cell chains inside the van Gogh bundles belonging to either one of them . All in all , these results indicate that EPS is strictly required for the formation of van Gogh bundles , presumably for the adhesion between neighboring cell chains . After evaluating the mutant chimeras , it is still unclear what the role of TasA is in the formation of van Gogh bundles . TasA was not strictly required for the formation of van Gogh bundles ( see the eps + tasA chimera in Fig 6 ) . Yet , the tasA mutant was partly impaired in colony expansion ( Fig 1 ) . In order to evaluate the role of TasA , we examined the distribution of TasA protein directly by using a fusion of TasA and a red fluorescent protein ( the fusion protein is designated TasA-mCherry ) . TasA-mCherry was examined by microscopy during the transition from the first to the second growth period . Previous studies suggested that TasA is freely shared between cells in the colony , since tasA mutants could be complemented when grown together with TasA-producing cells [45 , 50] . Interestingly , Fig 7A shows that TasA was predominantly localized to the van Gogh bundles—where TasA is also produced—and only a limited fraction of TasA diffused to the surrounding single cells ( see S3 Text and S9 Fig ) . In fact , TasA particularly localized to the “pole to pole” interactions between cells ( see arrowheads in Figs 7A and S10 ) . Thus , in contrast to previous studies , our results suggest that there is only limited diffusion of TasA . To examine whether TasA is shared between neighboring cells inside the van Gogh bundle , we examined a chimeric colony of TasA-mCherry + tasA mutant . Since the strain producing the fusion TasA-mCherry and the tasA mutant strain can form van Gogh bundles together ( i . e . , they both produce EPS ) , this chimera allows us to examine whether TasA produced by the TasA-mCherry strain is shared with the tasA mutant cells inside the van Gogh bundle ( Fig 7B ) . Indeed , a small fraction of TasA diffused from the TasA-producing cells to the tasA mutant cells ( S11 Fig ) . However , interestingly , there was no accumulation of TasA at the pole-to-pole interactions between tasA mutant cells ( Figs 7B and S11 ) . Thus , TasA accumulated only at the cell poles of TasA-producing cells inside the van Gogh bundle . It is plausible that a large fraction of the TasA produced by a WT cell localizes to its own poles . In summary , van Gogh bundles are cell collectives that consist solely of matrix-producing cells but that require the presence of surfactin producers for their development . This is further confirmed by the fact that colony expansion in srfA mutants can be recovered by adding surfactin exogenously ( S12 Fig; [58] ) . The matrix-producing cells secrete EPS and TasA . While EPS is absolutely necessary for the formation of a van Gogh bundle , TasA seems to fine-tune the cell-to-cell interactions . In the previous sections we showed that colony expansion coincides with the formation of van Gogh bundles , which are formed when both surfactin-producing and matrix-producing cells are present . Surfactin functions as a surfactant and facilitates colony expansion by reducing the friction between cells and their substrate [57–59] . The question , however , remains as to how the cell collectives that organize themselves in van Gogh bundles migrate in space . To address this question , we examined van Gogh bundles in more detail . In order to analyze the structures that emerge at a larger spatial scale , we next imaged the van Gogh bundles at a lower magnification using a stereomicroscope . By using the stereomicroscope , no further manipulation of the colony was required , and growing colonies could be examined multiple times as growth progressed ( the air objective does not disrupt the colony ) . Surprisingly , at lower magnification it became apparent that van Gogh bundles form large filamentous loops at the edge of the colony ( Fig 8 ) . These loops extend up to a few millimeters in length . We hypothesized that the van Gogh bundles migrate by simply pushing themselves away from the colony center as the filamentous loops grow . A time-lapse movie indeed confirmed our expectation ( S1 Movie ) . Thus , colony expansion indeed emerges from the interaction of cells that organize themselves into van Gogh bundles . The lack of colony expansion in sliding-deficient mutants , with the exception of tasA , can be explained by the lack of van Gogh bundles and the associated loops at the colony edge ( Fig 9 ) . Interestingly , eps and eps tasA mutants do show chains of cells , similar to the chains of cells in van Gogh bundles , but they are not aligned with each other ( Fig 9 ) . The tasA mutant strain is mainly deficient in colony expansion during the second growth phase , as it can form dendrites ( Fig 9 ) . Furthermore , the filamentous loops at the edge of the tasA colony are typically smaller and show more folds than those of the WT ( S13 Fig ) . We hypothesize that TasA , although not strictly required for the formation of van Gogh bundles , may fine-tune the folding properties of the bundles . This hypothesis is supported by the fact that TasA localizes to the pole-to-pole contact points between cells in the van Gogh bundles , where it potentially affects biophysical properties such as the bending rigidity ( Fig 7 ) . Interestingly , while the lack of TasA reduces colony expansion , the artificial overproduction of TasA does not enhance colony expansion ( S14 Fig ) . Inspired by the folding differences between filamentous loops produced by the WT and those produced by tasA ( S13 Fig ) , we wondered if and how cell-level properties ( e . g . , phenotype of a cell or cell–cell interactions ) could affect the collective properties that we observed at the colony level . For this purpose , we constructed a simple phenomenological model . This model was not designed with the aim of quantitatively reproducing our experimental results , which at present is impossible given our limited knowledge of the biophysical properties of the van Gogh bundles . Rather , we aimed to illustrate how local cell interactions could shape colony-level properties . Previous models on multicellular development have shown that—through self-organization—simple cell-to-cell interactions can underlie complex properties that emerge at the organismal level [6 , 7 , 63] . Mathematical models are therefore a valuable tool to shape our intuition on the cell-level properties that are important for the qualitative patterns we observe at the colony level [4 , 7] . Inspired by models on epithelium folding [64–66] , we modeled filaments of pole-to-pole-attached cells that grow in time ( we ignored side-to-side attachment for simplicity ) . The model does not include the origin of filament formation , but instead examines filament growth . At every time step , cells can undergo one of three events: cell elongation , division , or turning ( see Materials and Methods for modeling details ) . Cell elongation occurs with a certain growth rate , taken from a uniform distribution , and can result in cell division when the cell length exceeds a certain threshold ( i . e . , the maximum cell length ) ; in that case the mother cell divides into two equally long daughter cells . Cells can also turn and change their spatial orientation with respect to their neighbors . Cells turn only when the new orientation—determined by a random change in a cell’s angle with respect to its neighbors—is energetically favored compared to the cell’s original orientation . In the energetically preferred position , a cell is perfectly aligned with its neighbors ( i . e . , there is no angle between two neighboring cells ) . The chance that a cell turns depends on the bending rigidity ( see Materials and Methods ) . Cell elongation , division , and turning are local events that do not alter the spatial configuration of cells in other parts of the filament . Thus , the properties of the filament as a whole come about through the accumulation of local events . As shown in Fig 10 , these three simple cell-level behaviors are sufficient to produce expanding filamentous loops at the colony edge that look surprisingly similar to those observed in our experiments . Cell elongation and division result in undulations of the filaments ( i . e . , regions where the filaments bend slightly inwards or outwards ) . These undulations get smoothened as long as neighboring cells resist bending by strongly aligning with respect to each other ( i . e . , bending rigidity ) . However , when growth continues , the filament gets compressed and undulations increase . As a consequence , the filament starts folding . The folds turn into loops , which expand in space . As observed in the experimental results ( Figs 8–10 ) , the model gives rise to bigger loops at the edge of the colony ( Fig 10 ) . To examine how small changes at the cell level affect the expansion of filamentous loops , two modeling parameters were varied: the maximal cell length and the bending rigidity . These parameters correspond to properties that probably can be influenced by a cell . For example , we showed that cells inside van Gogh bundles are longer than their single-cell siblings ( Figs 4 , 5 , and S7; two-sample t-test: p < 10−16 , df = 184 ) , which suggests that cells can alter the length at which they divide . In addition , we showed that van Gogh bundles show a particularly strong alignment ( S2 Text ) , which seems to partly depend on TasA that accumulates at the pole-to-pole interactions ( Figs 7 , 9 , S10 , and S13 ) . This indicates that cells can alter their bending rigidity with respect to neighboring cells . Interestingly , in the model , both longer cells and higher bending rigidities result in filaments that fold less ( Fig 10 , conditions B and C ) . Longer cells reduce folding because there are fewer pole-to-pole interactions at which the filament could accumulate undulations . Likewise , when the bending rigidity is high , cells align more strongly , which results in less folding as well . The reduced tendency to fold increases the migration rate ( Fig 10 , compare conditions A , B , and C ) . Our phenomenological model thus illustrates how small changes at the cell level can shape the collective properties that emerge at the colony level . The collective properties we examined are the expanding filamentous loops that appear at the colony edge . One can imagine that evolution favors adaptations at the cell level , like a strong cell-to-cell alignment , that result in a higher migration rate of the filamentous loops .
In this study we analyzed sliding motility in B . subtilis to determine the factors that allow for the collective migration of cells . We found that cells organize themselves into bundles that spread by forming expanding filamentous loops at the colony edge . These cell collectives , which we call van Gogh bundles , are distinct from previously described filaments in B . subtilis due to their strong alignment and functionality [21 , 67] . The folding properties of the filamentous loops determine the migration rate and , in part , depend on the products secreted by matrix-producing cells . The development and expansion of van Gogh bundles depend critically on the synergic interaction of surfactin-producing and matrix-producing cells . To our knowledge , this is the first example of bacterial cells dividing labor in order to overcome one of the major ecological challenges: migration ( Fig 11 ) . We show that colony expansion is characterized by up-regulation of srfA expression ( i . e . , the surfactin-producing cell type ) followed by an increase in tapA expression ( i . e . , the matrix-producing cell type ) . The two expression phases correspond to the two growth periods that are apparent at the macroscopic level: dendrite formation and petal-shaped colony outgrowth [57] . The temporal dynamics in gene expression correspond to the regulatory pathways controlling cell differentiation in B . subtilis . For example , srfA expression is regulated by quorum sensing [41 , 68]; at high cell density , the expression of srfA increases , which explains the gradual up-regulation of srfA at the onset of colony growth . In addition , surfactin can function as a signal that triggers matrix production [41 , 42] . It is therefore not surprising that the peak in srfA expression is followed by a peak in tapA expression . This regulatory link between cell differentiation of surfactin-producing cells and matrix-producing cells corresponds closely to the functional link we describe in this study: van Gogh bundles , consisting of matrix-producing cells , can develop only in the presence of surfactin ( Fig 11 ) . Thus , surfactin-producing and matrix-producing cells divide labor in order to facilitate colony expansion ( see also [69] ) . The division of labor typically evolves in response to strong phenotypic trade-offs [70 , 71] . For example , cyanobacteria divide labor between photosynthetic cells and heterocysts , because photosynthesis and nitrogen fixation are incompatible [72 , 73] . Likewise , there might be a trade-off between the formation of van Gogh bundles by matrix-producing cells and the production of surfactin . Unfortunately , it is unclear what this trade-off might be; perhaps the cell-to-cell attachment of matrix-producing cells would be harmed if cells simultaneously produced surfactin . The fact that eps tasA + srfA chimeras—colonies in which different strains perform different tasks—can expand further than WT colonies suggests there may indeed be a trade-off at play . Besides surfactin , matrix production can also be triggered by environmental stressors like starvation , hypoxia , and osmotic stress [36 , 74 , 75] . Environmental changes during colony growth might therefore also be responsible for the temporal up-regulation of matrix production and the transition from the dendrite to the petal growth phase . We showed that cells isolated from the petal growth phase readily switch back to dendrite formation , when re-inoculated on a fresh growth medium . This indicates that the environment is indeed an important determinant for the different growth phases . When van Gogh bundles first appear , the matrix-producing cells are surrounded by surfactin-producing cells . Given their proximity , the co-occurring cell types probably sense nearly identical environmental conditions , yet they behave differently [69 , 76 , 77] . This indicates that—besides depending on the environment—cell differentiation also depends on inherent stochasticity . A recent study showed that under constant environmental conditions , cells can spontaneously differentiate into matrix-producing cell chains [78] that are preserved for a number of generations due to a regulatory feedback loop that creates a bi-stable switch [79–81] . A similar switch might also be important for the first cell chains that appear in the formation of van Gogh bundles . While previous studies have shown that surfactin production and EPS production can affect colony expansion [47 , 48 , 58 , 59] , these studies did not show a synergistic interaction between cell types . In addition , the colony expansion in our study is of a different nature than the ones described in previous studies . For example , EPS production has been shown to have a relatively small effect on biofilm colony expansion , and that effect was hypothesized to depend on osmotic pressures [47 , 48] . Here we show that EPS has an all-or-none effect on colony expansion during sliding motility . The migration of van Gogh bundles does not directly rely on osmotic gradients , but instead results from mechanic force ( although osmotic gradients can affect cell differentiation [74] ) . Hence , EPS stimulates migration by allowing for the organization of van Gogh bundles . How EPS exactly guides bundle formation requires further examination . Our results suggest that EPS is required for side-to-side attachment of cell chains . However , EPS might also affect the pole-to-pole interactions . Besides being essential in the formation of van Gogh bundles , EPS production was also essential for dendrite formation . At this early growth phase , matrix-producing cells do form multicellular clumps , but these clumps lack the tight alignment of cells that characterizes the van Gogh bundles . Thus , the mere presence of surfactin-producing and matrix-producing cells does not guarantee the formation of van Gogh bundles . It would be interesting to examine why matrix-producing cells are essential for dendrite formation , while forming van Gogh bundles only in the petal growth phase . The functions of EPS and TasA inside the van Gogh bundle are different . Whereas EPS is absolutely necessary for the formation of van Gogh bundles , TasA seems to fine-tune the folding properties of the van Gogh bundles . TasA specifically localizes to the pole-to-pole interaction zones of TasA-producing cells inside the van Gogh bundle . Our mathematical model shows that the folding properties of van Gogh bundles determine the efficiency of migration: when the filament is less likely to fold , it can expand farther in space . We suggest that TasA might affect folding , by manipulating the bending rigidity at the pole-to-pole interactions between cells . Although this claim awaits further biophysical quantification , our study suggests that both EPS and TasA have specialized functions that guide the development of van Gogh bundles [64–66] . In this way , matrix-producing cells can organize themselves into multicellular structures that facilitate migration . B . subtilis is not the only species that switches to a multicellular lifestyle to accomplish migration . Filamentous structures also occur during the colony growth of P . vortex and B . mycoides , whose growth patterns are described in the Introduction [28–30] . Furthermore , an impressive study by Vilain and colleagues [34] showed that the closely related species B . cereus switches to a multicellular lifestyle when grown on filter-sterilized soil-extracted soluble organic matter ( SESOM ) or artificial soil microcosm ( ASM ) —media that mimic the environmental conditions cells encounter in the soil . They showed that the lifestyle switch to multicellularity allows for migration . Interestingly , B . mycoides and B . subtilis show the same lifestyle switch when exposed to SESOM or ASM . This strongly supports our hypothesis that the collective properties that emerge from the interaction between surfactin-producing and matrix-producing cells—van Gogh bundles—evolved to facilitate migration . This hypothesis is further supported by the fact that the domesticated lab strain , B . subtilis 168 , which is known to be defective in surfactin production , cannot make the switch to a multicellular lifestyle when grown on SESOM or ASM [34 , 82] . It would be interesting to examine whether SESOM and ASM indeed induce surfactin and matrix production and hence the development of van Gogh bundles in the wild isolate of B . subtilis . Like other forms of bacterial multicellularity [9] , van Gogh bundles illustrate how the organization of cells can help to overcome important ecological challenges . Ultimately , we hope that the study of such simple forms of organization can improve our understanding on how evolution constructs [10 , 83–88]: how cells can evolve to become integrated collectives that , together , form a new organizational unit .
We constructed a model to study how cellular properties could influence features of multicellular organization such as the folding properties of the van Gogh bundles , which are important for the rate of colony expansion . We did not aim to accurately model the biophysical details of the growth of van Gogh bundles ( parameterization of such a model would be impossible ) , but rather to make a simple phenomenological model to shape our intuition based on previous models of epithelium folding [65 , 66] . In the model we examine the growth of a cellular filament . Unlike the van Gogh bundles , the filament is simplified to a single chain of pole-to-pole-attached cells . The cells in the filament can elongate , divide , and turn and thereby affect the macroscopic shape of the filament . The filament is placed in a two-dimensional space with fixed boundaries ( the space is 1 × 1 spatial units big; this size is relevant for the cell size and growth rate mentioned below ) . The cells inside the filament are not allowed to overlap , and the ends of the filament are fixed in space , as being attached to the colony . At the start of each simulation , the filament consists of N cells that are placed as a horizontal line at the bottom of the two dimensional space ( y-coordinate is 0 ) . The filament is updated every time step by selecting a random cell from the population and performing one out of three possible update events: ( 1 ) cell elongation , ( 2 ) cell division , or ( 3 ) cell turning . After T time steps the simulation is stopped . The final shape of the filament results from the accumulation of local update events . The degree of colony expansion is measured in the y-direction . Here we give a short description for each of the three update events ( see S16 Fig ) .
|
Some problems can be solved only when individuals act together . This applies to bacteria in the same way that it applies to humans . Here we study how bacteria overcome the environmental challenge of migration over a solid surface by bundling their forces . Migration can be a significant environmental challenge for bacteria , especially when food sources are distributed far apart and have to be reached by movement along a solid surface , where swimming motility does not work . We show that Bacillus subtilis—a common inhabitant of the soil—migrates over a solid surface by forming multicellular structures . Migration depends on the synergistic interaction of two cell types: surfactin-producing and matrix-producing cells . Surfactin-producing cells facilitate migration by reducing the friction between cells and their substrate , thereby allowing matrix-producing cells to organize themselves into bundles that form filamentous loops at the colony edge . Using time-course microscopy , we observe that the filamentous loops drive migration by pushing themselves away from the colony . A mathematical model further shows that the folding properties of these loops are critical for the rate of colony expansion . Thus , not only do cells act together to overcome the challenge of migration , they also divide labor , in that different cell types specialize on distinct tasks .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
From Cell Differentiation to Cell Collectives: Bacillus subtilis Uses Division of Labor to Migrate
|
A research priority for Plasmodium vivax malaria is to improve our understanding of the spatial distribution of risk and its relationship with the burden of P . vivax disease in human populations . The aim of the research outlined in this article is to provide a contemporary evidence-based map of the global spatial extent of P . vivax malaria , together with estimates of the human population at risk ( PAR ) of any level of transmission in 2009 . The most recent P . vivax case-reporting data that could be obtained for all malaria endemic countries were used to classify risk into three classes: malaria free , unstable ( <0 . 1 case per 1 , 000 people per annum ( p . a . ) ) and stable ( ≥0 . 1 case per 1 , 000 p . a . ) P . vivax malaria transmission . Risk areas were further constrained using temperature and aridity data based upon their relationship with parasite and vector bionomics . Medical intelligence was used to refine the spatial extent of risk in specific areas where transmission was reported to be absent ( e . g . , large urban areas and malaria-free islands ) . The PAR under each level of transmission was then derived by combining the categorical risk map with a high resolution population surface adjusted to 2009 . The exclusion of large Duffy negative populations in Africa from the PAR totals was achieved using independent modelling of the gene frequency of this genetic trait . It was estimated that 2 . 85 billion people were exposed to some risk of P . vivax transmission in 2009 , with 57 . 1% of them living in areas of unstable transmission . The vast majority ( 2 . 59 billion , 91 . 0% ) were located in Central and South East ( CSE ) Asia , whilst the remainder were located in America ( 0 . 16 billion , 5 . 5% ) and in the Africa+ region ( 0 . 10 billion , 3 . 5% ) . Despite evidence of ubiquitous risk of P . vivax infection in Africa , the very high prevalence of Duffy negativity throughout Central and West Africa reduced the PAR estimates substantially . After more than a century of development and control , P . vivax remains more widely distributed than P . falciparum and is a potential cause of morbidity and mortality amongst the 2 . 85 billion people living at risk of infection , the majority of whom are in the tropical belt of CSE Asia . The probability of infection is reduced massively across Africa by the frequency of the Duffy negative trait , but transmission does occur on the continent and is a concern for Duffy positive locals and travellers . The final map provides the spatial limits on which the endemicity of P . vivax transmission can be mapped to support future cartographic-based burden estimations .
The bulk of the global burden of human malaria is caused by two parasites: Plasmodium falciparum and P . vivax . Existing research efforts have focussed largely on P . falciparum because of the mortality it causes in Africa [1] , [2] . This focus is increasingly regarded as untenable [3]–[6] because the following factors indicate that the public health importance of P . vivax may be more significant than traditionally thought: i ) P . vivax has a wider geographical range , potentially exposing more people to risk of infection [7] , [8]; ii ) it is less amenable to control [9] , [10]; and , most importantly , iii ) infections with P . vivax can cause severe clinical syndromes [5] , [11]–[16] . A key research priority for P . vivax malaria is to improve the basic understanding of the geographical distribution of risk , which is needed for adequate burden estimation [6] . Recent work by the Malaria Atlas Project ( MAP; www . map . ox . ac . uk ) [17] has shown P . falciparum malaria mapping to be a fundamental step in understanding the epidemiology of the disease at the global scale [18] , [19] , in appraising the equity of global financing for control [20] and in forming the basis for burden estimation [21] , [22] . The benefits of a detailed knowledge of the spatial distribution of P . vivax transmission , and its clinical burden within these limits , are identical to those articulated for P . falciparum: establishing a benchmark against which control targets may be set , budgeted and monitored . Such maps do not exist for P . vivax , making any strategic planning problematic . In addition , information about the global extent of P . vivax transmission and population at risk ( PAR ) is crucial for many nations that are re-evaluating their prospects for malaria elimination [23] , [24] . This paper documents the global spatial limits of P . vivax malaria using a combination of national case-reporting data from health management information systems ( HMIS ) , biological rules of transmission exclusion and medical intelligence combined in a geographical information system . The output is an evidence-based map from which estimates of PAR are derived . The resulting map also provides the global template in which contemporary P . vivax endemicity can be estimated and it contributes to a cartographic basis for P . vivax disease burden estimation .
A schematic overview of the analyses is presented in Figure 1 . Briefly , P . vivax malaria endemic countries ( PvMECs ) were first identified and the following layers were progressively applied within a geographical information system to constrain risk areas and derive the final P . vivax spatial limits map: i ) a P . vivax annual parasite incidence ( PvAPI ) data layer; biological exclusion layers comprising of ii ) temperature and iii ) aridity data layers; iv ) a medical intelligence exclusion layer; and v ) a predicted Duffy negativity layer . A detailed description of these steps follows . Those countries that currently support P . vivax transmission were first identified . The primary sources for defining national risk were international travel and health guidelines [25] , [26] augmented with national survey information , pertinent published sources and personal communication with malariologists . Nations were grouped into three regions , as described elsewhere [19]: i ) America; ii ) Africa , Saudi Arabia and Yemen ( Africa+ ) ; and iii ) Central and South East ( CSE ) Asia . To further resolve PAR estimates , the CSE Asia region was sub-divided into West Asia , Central Asia and East Asia ( Protocol S1 ) . Methods described previously for mapping the global spatial limits of P . falciparum malaria [18] were used to constrain the area defined at risk within the PvMECs using PvAPI data ( the number of confirmed P . vivax malaria cases reported per administrative unit per 1 , 000 people per annum ( p . a . ) ) . The PvAPI data were obtained mostly through personal communication with individuals and institutions linked to malaria control in each country ( Protocol S1 ) . The format in which these data were available varied considerably between countries . Ideally , the data would be available by administrative unit and by year , with each record presenting the estimated population for the administrative unit and the number of confirmed autochthonous malaria cases by the two main parasite species ( P . falciparum and P . vivax ) . This would allow an estimation of species-specific API . These requirements , however , were often not met . Population data by administrative unit were sometimes unavailable , in which cases these data were sourced separately or extrapolated from previous years . An additional problem was the lack of parasite species-specific case or API values . In such cases , a parasite species ratio was inferred from alternative sources and applied to provide an estimate of species-specific API . There was , thus , significant geographical variation in the ability to look at the relative frequency of these parasites between areas and this was not investigated further . Finally , although a differentiation between confirmed and suspected cases and between autochthonous and imported cases was often provided , whenever this was not available it was assumed that the cases in question referred to confirmed and autochthonous occurrences . The aim was to collate data for the last four years of reporting ( ideally up to 2009 ) at the highest spatial resolution available ( ideally at the second administrative level ( ADMIN2 ) or higher ) . A geo-database was constructed to archive this information and link it to digital administrative boundaries of the world available from the 2009 version of the Global Administrative Unit Layers ( GAUL ) data set , implemented by the Food and Agriculture Organization of the United Nations ( FAO ) within the EC FAO Food Security for Action Programme [27] . The PvAPI data were averaged over the period available and were used to classify areas as malaria free , unstable ( <0 . 1 case per 1 , 000 p . a . ) or stable ( ≥0 . 1 case per 1 , 000 p . a . ) transmission , based upon metrics advised during the Global Malaria Eradication Programme [28]–[30] . These data categories were then mapped using ArcMAP 9 . 2 ( ESRI 2006 ) . To further constrain risk within national territories , two “masks” of biological exclusion were implemented ( Protocol S2 ) . First , risk was constrained according to the relationship between temperature and the duration of sporogony , based upon parameters specific to P . vivax [31] . Synoptic mean , maximum and minimum monthly temperature records were obtained from 30-arcsec ( ∼1×1 km ) spatial resolution climate surfaces [32] . For each pixel , these values were converted , using spline interpolation , to a continuous time series representing a mean temperature profile across an average year . Diurnal variation was represented by adding a sinusoidal component to the time series with a wavelength of 24 hours and the amplitude varying smoothly across the year determined by the difference between the monthly minimum and maximum values . For P . vivax transmission to be biologically feasible , a cohort of anopheline vectors infected with P . vivax must survive long enough for sporogony to complete within their lifetime . Since the rate of parasite development within anophelines is strongly dependent on ambient temperature , the time required for sporogony varies continuously as temperatures fluctuate across a year [31] . For each pixel , the annual temperature profile was used to determine whether any periods existed in the year when vector lifespan would exceed the time required for sporogony , and hence when transmission was not precluded by temperature . This was achieved via numerical integration whereby , for cohorts of vectors born at each successive 2-hour interval across the year , sporogony rates varying continuously as a function of temperature were used to identify the earliest time at which sporogony could occur . If this time exceeded the maximum feasible vector lifespan , then the cohort was deemed unable to support transmission . If sporogony could not complete for any cohort across the year , then the pixel was classified as being at zero risk . Vector lifespan was defined as 31 days since estimates of the longevity of the main dominant vectors [33] indicate that 99% of anophelines die in less than a month and , therefore , would be unable to support parasite development in the required time . The exceptions were areas that support the longer-lived Anopheles sergentii and An . superpictus , where 62 days were considered more appropriate ( Protocol S2 ) [18] . The second mask was based on the effect of arid conditions on anopheline development and survival [34] . Limited surface water reduces the availability of sites suitable for oviposition and reduces the survival of vectors at all stages of their development through the process of desiccation [35] . The ability of adult vectors to survive long enough to contribute to parasite transmission and of pre-adult stages to ensure minimum population abundance is , therefore , dependent on the levels of aridity and species-specific resilience to arid conditions . Extremely arid areas were identified using the global GlobCover Land Cover product ( ESA/ESA GlobCover Project , led by MEDIAS-France/POSTEL ) [36] . GlobCover products are derived from data provided by the Medium Resolution Imaging Spectrometer ( MERIS ) , on board the European Space Agency's ( ESA ) ENVIronmental SATellite ( ENVISAT ) , for the period between December 2004 and June 2006 , and are available at a spatial resolution of 300 meters [36] . The layer was first resampled to a 1×1 km grid using a majority filter , and all pixels classified as “bare areas” by GlobCover were overlaid onto the PvAPI surface . The aridity mask was treated differently from the temperature mask to allow for the possibility of the adaptation of human and vector populations to arid environments [37]–[39] . A more conservative approach was taken , which down-regulated risk by one class . In other words , GlobCover's bare areas defined originally as at stable risk by PvAPI were stepped down to unstable risk and those classified initially as unstable to malaria free . Medical intelligence contained in international travel and health guidelines [25] , [26] was used to inform risk exclusion and down-regulation in specific urban areas and sub-national territories , which are cited as being free of malaria transmission ( Protocol S3 ) . Additional medical intelligence and personal communication with malaria experts helped identify further sub-national areas classified as malaria free in Cambodia , Vanuatu and Yemen . Specified urban areas were geo-positioned and their urban extents were identified using the Global Rural Urban Mapping Project ( GRUMP ) urban extents layer [40] . Rules of risk modulation within these urban extents were as follows: i ) risk within urban extents falling outside the range of the urban vector An . stephensi [41] ( Protocol S3 ) was excluded; ii ) risk within urban areas inhabited by An . stephensi was down-regulated by one level from stable to unstable and from unstable to free ( Protocol S3 ) . Specified sub-national territories were classified as malaria free if not already identified as such by the PvAPI layer and the biological masks . These territories were mapped using the GAUL data set [27] . Since Duffy negativity provides protection against infection with P . vivax [42] , a continuous map of the Duffy negativity phenotype was generated from a geostatistical model fully described elsewhere ( Howes et al . , manuscript in preparation ) . The model was informed by a database of Duffy blood group surveys assembled from thorough searches of the published literature and supplemented with unpublished data by personal communication with relevant authors . Sources retrieved were added to existing Duffy blood group survey databases [43] , [44] . The earliest inclusion date for surveys was 1950 , when the Duffy blood group was first described [45] . To model the Duffy system and derive a global prediction for the frequency of the homozygous Duffy negative phenotype ( [Fy ( a-b- ) ] , which is encoded by the homozygous FY*BES/*BES genotype ) , the spatially variable frequencies of the two polymorphic loci determining Duffy phenotypes were modelled: i ) nucleotide −33 in the gene's promoter region , which defines positive/negative expression ( T-33C ) ; ii ) the coding region locus ( G125A ) determining the antigen type expressed: Fya or Fyb [46] . Due to the wide range of diagnostic methods used to describe Duffy blood types in recent decades , data were recorded in a variety of forms , each providing differing information about the frequency of variants at both loci . For example , some molecular studies sequenced only the gene's promoter region , and thus could not inform the frequency of the coding region variant; serological diagnoses only testing for the Fya antigen could not distinguish Fyb from the Duffy negative phenotype . As part of the larger dataset , however , these incomplete data types can indirectly inform frequencies of negativity . Therefore , despite only requiring information about the promoter locus to model the negativity phenotype , variant frequencies at both polymorphic sites were modelled . This allowed the full range of information contained in the dataset to be used rather than just the subset specifically reporting Duffy negativity frequencies . The model's general architecture and Bayesian framework will be described elsewhere ( Howes et al . , manuscript in preparation ) . Briefly , the dataset of known values at fixed geographic locations was used to predict expression frequencies at each locus in all geographic sites where no data were available , thereby generating continuous global surfaces of the frequency of each variant . From the predicted frequency of the promoter region variant encoding null expression ( -33C ) , a continuous frequency map of the Duffy negative population was derived . The GRUMP beta version provides gridded population counts and population density estimates for the years 1990 , 1995 , and 2000 , both adjusted and unadjusted to the United Nations' national population estimates [40] . The adjusted population counts for the year 2000 were projected to 2009 by applying national , medium variant , urban and rural-specific growth rates by country [47] . These projections were undertaken using methods described previously [48] , but refined with urban growth rates being applied solely to populations residing within the GRUMP urban extents , while the rural growth rates were applied to the remaining population . This resulted in a 2009 population count surface of approximately 1×1 km spatial resolution , which was used to extract PAR figures . The PAR estimates in Africa were corrected for the presence of the Duffy negativity phenotype by multiplying the extracted population by [1 - frequency of Duffy negative individuals] .
A total of 109 potentially endemic countries and territories listed in international travel and health guidelines were identified [25] , [26] . Ten of these countries: Algeria , Armenia , Egypt , Jamaica ( P . falciparum only ) , Mauritius , Morocco , Oman , Russian Federation , Syrian Arab Republic and Turkmenistan have either interrupted transmission or are extremely effective at dealing with minor local outbreaks . These nations were not classified as PvMECs and are all considered to be in the elimination phase by the Global Malaria Action Plan [24] . Additionally , four malaria endemic territories report P . falciparum transmission only: Cape Verde [49] , the Dominican Republic [50] , Haiti [50] , [51] and Mayotte [52] . This resulted in a global total of 95 PvMECs . Figure 1 summarises the various layers applied on the 95 PvMECs in order to derive the limits of P . vivax transmission . The results of these different steps are described below . PvAPI data were available for 51 countries . Data for four countries were available up to 2009 . For 29 countries the last year of reporting was 2008 , whilst 2007 and 2006 were the last years available for 11 and six countries , respectively . For Colombia the last reporting year was 2005 . No HMIS data could be obtained for Kyrgyzstan and Uzbekistan , for which information contained in the most recent travel and health guidelines [25] , [26] was used to map risk . With the exception of Namibia , Saudi Arabia , South Africa and Swaziland , which were treated like all other nations , no HMIS data were solicited for countries in the Africa+ region , where stable risk of P . vivax transmission was assumed to be present throughout the country territories . In Botswana , stable risk was assumed in northern areas as specified by travel and health guidelines [25] , [26] . Amongst those countries for which HMIS data were available , 16 reported at ADMIN1 and 29 at ADMIN2 level . For Southern China , Myanmar , Nepal and Peru , data were available at ADMIN3 level . Data for Namibia and Venezuela were resolved at ADMIN1 and ADMIN2 levels . In total , 17 , 591 administrative units were populated with PvAPI data . Protocol S1 describes these data in detail . Figure 2 shows the spatial extent of P . vivax transmission as defined by the PvAPI data , with areas categorised as malaria free , unstable ( PvAPI<0 . 1 case per 1 , 000 p . a . ) or stable ( PvAPI≥0 . 1 case per 1 , 000 p . a . ) transmission [29] . Figure 3 shows the limits of P . vivax transmission after overlaying the temperature mask on the PvAPI surface . The P . vivax-specific temperature mask was less exclusive of areas of risk than that derived for P . falciparum [18] . Exclusion of risk was mainly evident in the Andes , the southern fringes of the Himalayas , the eastern fringe of the Tibetan plateaux , the central mountain ridge of New Guinea and the East African , Malagasy and Afghan highlands . There was a remarkable correspondence between PvAPI defined risk in the Andean and Himalayan regions and the temperature mask , which trimmed pixels of no risk at very high spatial resolution in these areas . The aridity mask used here [36] was more contemporary and derived from higher spatial resolution imagery than the one used to define the limits of P . falciparum [18] . Figure 4 shows that the effects of the aridity mask were more evident in the Sahel and southern Saharan regions , as well as the Arabian Peninsula . In the western coast of Saudi Arabia , unstable risk defined by the PvAPI layer was reduced to isolated foci of unstable risk by the aridity mask . In Yemen , stable risk was constrained to the west coast and to limited pockets along the southern coast . Similarly , endemic areas of stable risk defined by PvAPI data in southern Afghanistan , southern Iran and throughout Pakistan were largely reduced to unstable risk by the aridity mask . The two international travel and health guidelines consulted [25] , [26] cite 59 specific urban areas in 31 countries as being malaria free , in addition to urban areas in China , Indonesia ( those found in Sumatra , Kalimantan , Nusa Tenggara Barat and Sulawesi ) and the Philippines ( Protocol S3 ) . A total of 42 of these cities fell within areas classified as malarious and amongst these , eight were found within the range of An . stephensi , as were some urban areas in south-western Yunnan , China . Risk in the latter was down-regulated from stable to unstable and from unstable to free due to the presence of this urban vector . In the remaining 34 cities and other urban areas in China , Indonesia and the Philippines , risk was excluded . In addition , 36 administrative units , including islands , are cited as being malaria free ( Protocol S3 ) . These territories were excluded as areas of risk , if not already classified as such by the PvAPI surface and biological masks . In addition , the island of Aneityum , in Vanuatu [53] , the area around Angkor Watt , in Cambodia , and the island of Socotra , in Yemen [54] , were classified as malaria free following additional medical intelligence and personal communication with malaria experts from these countries . From the assembled library of references , 821 spatially unique Duffy blood type surveys were identified . Globally the data points were spatially representative , with 265 in America , 213 in Africa+ ( 167 sub-Saharan ) , 207 in CSE Asia and 136 in Europe . The total global sampled population was 131 , 187 individuals , with 24 , 816 ( 18 . 9% ) in Africa+ and 33 African countries represented in the final database . The modelled global map of Duffy negativity ( Figure 5 ) indicates that the P . vivax resistant phenotype is rarely seen outside of Africa , and , when this is the case , it is mainly in localised New World migrant communities . Within Africa , the predicted prevalence was strikingly high south of the Sahara . Across this region , the silent Duffy allele was close to fixation in 31 countries with 95% or more of the population being Duffy negative . Frequencies fell sharply into southern Africa and into the Horn of Africa . For instance , the frequency of Duffy negativity in the South African population was 62 . 7% , increasing to 65 . 0% in Namibia and 73 . 5% across Madagascar . The situation was predicted to be highly heterogeneous across Ethiopia , with an estimated 50 . 0% of the overall population being Duffy negative . The estimated P . vivax endemic areas and PAR for 2009 are presented in Table 1 , stratified by unstable ( PvAPI<0 . 1 per 1 , 000 p . a . ) and stable ( PvAPI≥0 . 1 per 1 , 000 p . a . ) risk of transmission , globally and by region and sub-region . It was estimated that there were 2 . 85 billion people at risk of P . vivax transmission worldwide in 2009 , the vast majority ( 91 . 0% ) inhabiting the CSE Asia region , 5 . 5% living in America and 3 . 4% living in Africa+ , after accounting for Duffy negativity . An estimated 57 . 1% of the P . vivax PAR in 2009 lived in areas of unstable transmission , with a population of 1 . 63 billion . Country level PAR estimates are provided in Protocol S4 . The ten countries with the highest estimated PAR , in descending order , were: India , China , Indonesia , Pakistan , Viet Nam , Philippines , Brazil , Myanmar , Thailand and Ethiopia . PAR estimates in India accounted for 41 . 9% of the global PAR estimates , with 60 . 3% of the more than one billion PAR ( 1 . 19 billion ) living in stable transmission areas . The situation in China was different as , according to the PvAPI input data , areas of stable transmission were only found in the southern provinces of Yunnan and Hainan , and in the north-eastern province of Anhui , which reported an unusually high number of cases up to 2007 . The latter is in accordance with a recent report documenting the resurgence of malaria in this province [55] . Transmission in the rest of China was largely negligible , with PvAPI values well below 0 . 1 case per 1 , 000 people p . a . Given the reported cases , however , these were classified as unstable transmission areas and the total PAR estimated within them , after urban exclusions , was 583 million people . All other countries reporting the highest PAR were in CSE Asia , with the exception of Brazil and Ethiopia .
We present a contemporary evidence-based map of the global distribution of P . vivax transmission developed from a combination of mapped sub-national HMIS data , biological rules of transmission exclusion and medical intelligence . The methods used were developed from those implemented for P . falciparum malaria [18] and can be reproduced following the sequence of data layer assemblies and exclusions illustrated in Figure 1 . Plasmodium vivax is transmitted within 95 countries in tropical , sub-tropical and temperate regions , reaching approximately 43 degrees north in China and approximately 30 degrees south in Southern Africa . The fact that P . vivax has a wider range than P . falciparum [18] is facilitated by two aspects of the parasite's biology [56]: i ) its development at lower temperatures during sporogony [31]; and ii ) its ability to produce hypnozoites during its life cycle in the human host [57] . The sporogonic cycle of P . vivax is shorter ( i . e . a lower number of degree days required for its completion ) and the parasite's sexual stage is active at lower temperatures than other human malaria parasites ( Protocol S2 ) [31] . Consequently , generation of sporozoites is possible at higher altitudes and more extreme latitudes . In the human host , hypnozoites of P . vivax temperate strains can relapse anywhere between months and years after the initial infection , often temporally coincident with optimal climatic conditions in a new transmission season [10] , [57] . The resulting maps produced an estimate of 2 . 85 billion people living at risk of P . vivax malaria transmission in 2009 . The distribution of P . vivax PAR is very different from that of P . falciparum [18] , due to the widespread distribution of P . vivax in Asia , up to northern China , and the high prevalence of the Duffy negativity phenotype in Africa . China accounts for 22 . 0% of the global estimated P . vivax PAR , although 93 . 1% of these people live in areas defined as unstable transmission ( Protocol S4 ) . An important caveat is that PvAPI data from central and northern China could only be accessed at the lowest administrative level ( ADMIN1 ) ( Protocol S1 ) . The very high population densities found in this country exacerbate the problem , inevitably biasing PAR estimates , despite urban areas in China being excluded from the calculations following information from the sources of medical intelligence that were consulted [25] , [26] . Malaria transmission in most of these unstable transmission areas in China is probably negligible given the very few cases reported between 2003 and 2007 . It is important to stress the necessity to access PvAPI data at a higher spatial resolution from China ( i . e . at the county level ) in order to refine these estimates and minimise biases . In Africa , the modelled prevalence of Duffy negativity shows that very high rates of this phenotype are present in large swaths of West and Central Africa ( Figure 5 ) . One of the functions of the Duffy antigen is being a receptor of P . vivax [46] and its absence has been shown to preclude infection with this parasite [58] , [59] , although the extent of this has been questioned [60]–[63] . There is no doubt that the African continent has a climate highly conducive to P . vivax transmission ( Protocol S2 ) . Moreover , dominant African Anopheles have been shown to be competent vectors of this parasite [62] , [64] , [65] . In addition , there is a plethora of evidence of P . vivax transmission in Africa , mostly arising from travel-acquired P . vivax infections during visits to malaria endemic African countries ( Table 2; Protocol S1 ) . This evidence supports the hypothesis that P . vivax may have been often misdiagnosed as P . ovale in the region due to a combination of morphological similarity and the prevailing bio-geographical dogma driven by the high prevalence of Duffy negativity [60] . Despite the fact that the risk of P . vivax is cosmopolitan , PAR estimates in Africa were modulated according to the high limitations placed on infection by the occurrence of the Duffy negative trait . Consequently , the PAR in the Africa+ region accounts for only 3 . 5% of the global estimated P . vivax PAR . Although recent work has shown 42 P . vivax infections amongst 476 individuals genotyped as Duffy negative across eight sites in Madagascar [63] , we have taken a conservative approach and consider it premature to relax the Duffy exclusion of PAR across continental Africa until this study has been replicated elsewhere . Mapping the distribution of P . vivax malaria has presented a number of unique challenges compared to P . falciparum , some of which have been addressed by the methods used here . The influence of climate on parasite development has been allowed for by implementing a temperature mask parameterised specifically for the P . vivax life cycle . The question of Duffy negativity and P . vivax transmission has also been addressed by modelling the distribution of this phenotype and by allowing the predicted prevalence to modulate PAR . It is also worth noting that the accuracy of HMIS for P . vivax clinical cases , particularly in areas of coincidental P . falciparum risk , is notoriously poor [66] , in part because microscopists are less likely to record the presence of a parasite assumed to be clinically less important . Here , HMIS data were averaged over a period of up to four years and used to differentiate malaria free areas from those that are malarious . Within the latter , a conservative threshold was applied to classify risk areas as being of unstable ( PvAPI<0 . 1 per 1 , 000 p . a . ) or stable ( PvAPI≥0 . 1 per 1 , 000 p . a . ) transmission [29] . We believe that this conservative use of HMIS data balances , to some extent , anomalies introduced by P . vivax underreporting and the correspondence of the biological masks and PvAPI data in many areas is reassuring . The intensity of transmission within the defined stable limits of P . vivax risk will vary across this range and this will be modelled using geostatistical techniques similar to those developed recently for P . falciparum [19] . This modelling work will be cognisant of the unique epidemiology of P . vivax . First , in areas where P . vivax infection is coincidental with P . falciparum , prevalence of the former may be suppressed by cross-species immunity [67] or underestimated by poor diagnostics [66] . Second , there is the ability of P . vivax to generate hypnozoites that lead to relapses . These characteristics render the interpretation of prevalence measures more problematic [5] . Third , the prevalence of Duffy negativity provides protection against infection in large sections of the population in Africa [58] , [59] . An appropriate modelling framework is under development and will be the subject of a subsequent paper mapping P . vivax malaria endemicity using parasite prevalence data . These data are being collated in the MAP database , with nearly 9 , 000 P . vivax parasite rate records archived by 01 March 2010 .
|
Growing evidence shows that Plasmodium vivax malaria is clinically less benign than has been commonly believed . In addition , it is the most widely distributed species of human malaria and is likely to cause more illness in certain regions than the more extensively studied P . falciparum malaria . Understanding where P . vivax transmission exists and measuring the number of people who live at risk of infection is a fundamental first step to estimating the global disease toll . The aim of this paper is to generate a reliable map of the worldwide distribution of this parasite and to provide an estimate of how many people are exposed to probable infection . A geographical information system was used to map data on the presence of P . vivax infection and spatial information on climatic conditions that impede transmission ( low ambient temperature and extremely arid environments ) in order to delineate areas where transmission was unlikely to take place . This map was combined with population distribution data to estimate how many people live in these areas and are , therefore , exposed to risk of infection by P . vivax malaria . The results show that 2 . 85 billion people were exposed to some level of risk of transmission in 2009 .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"public",
"health",
"and",
"epidemiology/global",
"health"
] |
2010
|
The International Limits and Population at Risk of Plasmodium vivax Transmission in 2009
|
This paper describes a general model that subsumes many parametric models for continuous data . The model comprises hidden layers of state-space or dynamic causal models , arranged so that the output of one provides input to another . The ensuing hierarchy furnishes a model for many types of data , of arbitrary complexity . Special cases range from the general linear model for static data to generalised convolution models , with system noise , for nonlinear time-series analysis . Crucially , all of these models can be inverted using exactly the same scheme , namely , dynamic expectation maximization . This means that a single model and optimisation scheme can be used to invert a wide range of models . We present the model and a brief review of its inversion to disclose the relationships among , apparently , diverse generative models of empirical data . We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain .
To simplify notation we will use fx: = fx ( x ) = ∂xf = ∂f/∂x to denote the partial derivative of the function , f , with respect to the variable x . We also use x ˙ = ∂tx for temporal derivatives . Furthermore , we will be dealing with variables in generalised coordinates of motion , which will be denoted by a tilde; x̃: = [x , x′ , x″ , …] T = [x[0] , x[1] , x[2] , …] T , where x[i] denotes ith order motion . A point in generalised coordinates can be regarded as encoding the instantaneous trajectory of a variable , in the sense it prescribes its location , velocity , acceleration etc .
In this section , we cover hierarchal models for dynamic systems . We start with the basic model and how generalised motion furnishes empirical priors on the dynamics of the model's hidden states . We then consider hierarchical forms and see how these induce empirical priors in a structural sense . We will try to relate these perspectives to established treatments of empirical priors in static and state-space models . This section considers variational inversion of models under mean-field and Laplace approximations , with a special focus on HDMs . This treatment provides a heuristic summary of the material in [2] . Variational Bayes is a generic approach to model inversion that approximates the conditional density p ( ϑ|y , m ) on some model parameters , ϑ , given a model m and data y . This is achieved by optimising the sufficient statistics ( e . g . , mean and variance ) of an approximate conditional density q ( ϑ ) with respect to a lower bound on the evidence ( marginal or integrated likelihood ) p ( y|m ) of the model itself . These two quantities are used for inference on the parameters of any given model and on the model per se . [11]–[15] . The log-evidence for any parametric model can be expressed in terms of a free-energy F ( ỹ , q ) and a divergence term , for any density q ( ϑ ) on the unknown quantities ( 15 ) The free-energy comprises the internal energy , U ( y , ϑ ) = ln p ( y , ϑ ) expected under q ( ϑ ) and an entropy term , which is a measure of its uncertainty . In this paper , energies are the negative of the corresponding quantities in physics; this ensures the free-energy increases with log-evidence . Equation 15 indicates that F ( ỹ , q ) is a lower-bound on the log-evidence because the cross-entropy or divergence term is always positive . The objective is to optimise q ( ϑ ) by maximising the free-energy and then use F≈ln p ( ỹ|m ) as a lower-bound approximation to the log-evidence for model comparison or averaging . Maximising the free-energy minimises the divergence , rendering q ( ϑ ) ≈p ( ϑ|y , m ) an approximate posterior , which is exact for simple ( e . g . , linear ) systems . This can then be used for inference on the parameters of the model selected . Invoking an arbitrary density , q ( ϑ ) converts a difficult integration problem ( inherent in computing the evidence; see discussion ) into an easier optimisation problem . This rests on inducing a bound that can be optimised with respect to q ( ϑ ) . To finesse optimisation , one usually assumes q ( ϑ ) factorises over a partition of the parameters ( 16 ) In statistical physics this is called a mean-field approximation . This factorisation means that one assumes the dependencies between different sorts of parameters can be ignored . It is a ubiquitous assumption in statistics and machine learning . Perhaps the most common example is a partition into parameters coupling causes to responses and hyperparameters controlling the amplitude or variance of random effects . This partition greatly simplifies the calculation of things like t-tests and implies that , having seen some data , knowing their variance does not tell you anything more about their mean . Under our hierarchical dynamic model we will appeal to separation of temporal scales and assume , q ( ϑ ) = q ( u ( t ) ) q ( θ ) q ( λ ) , where u = [ṽ , x̃ , ] T are generalised states . This means that , in addition to the partition into parameters and hyperparameters , we assume conditional independence between quantities that change ( states ) and quantities that do not ( parameters and hyperparameters ) . In this dynamic setting q ( u ( t ) ) and the free-energy become functionals of time . By analogy with Lagrangian mechanics , this calls on the notion of action . Action is the anti-derivative or path-integral of energy . We will denote the action associated with the free energy by F̅ , such that ∂tF̅ = F . We now seek q ( ϑi ) that maximise the action . It is fairly easy to show [2] that the solution for the states is a function of their instantaneous energy , U ( t ) : = U ( u|θ , λ ) = ln p ( ỹ , u|θ , λ ) ( 17 ) where V ( t ) = ∂tV̅ u is their variational energy . The variational energy of the states is simply their instantaneous energy averaged over their Markov blanket ( i . e . , averaged over the conditional density of the parameters and hyperparameters ) . Because the states are time-varying quantities , their conditional density is a function of time-dependent energy . In contrast , the conditional density of the parameters and hyperparameters are functions of their variational action , which are fixed for a given period of observation . ( 18 ) Where Uθ = ln p ( θ ) and Uλ = ln p ( λ ) are the prior energies of the parameters and hyperparameters respectively and play the role of integration constants in the corresponding variational actions; V̅ θ and V̅ λ . These equations provide closed-form expressions for the conditional or variational density in terms of the internal energy defined by our model; Equation 10 . They are intuitively sensible , because the conditional density of the states should reflect the instantaneous energy; Equation 17 . Whereas the conditional density of the parameters can only be determined after all the data have been observed; Equation 18 . In other words , the variational energy involves the prior energy and an integral of time-dependent energy . In the absence of data , when the integrals are zero , the conditional density reduces to the prior density . If the analytic forms of Equations 17 and 18 were tractable ( e . g . , through the use of conjugate priors ) , q ( ϑi ) could be optimised directly by iterating these self-consistent nonlinear equations . This is known as variational Bayes; see [16] for an excellent treatment of static conjugate-exponential models . However , we will take a simpler approach that does not require bespoke update equations . This is based on a fixed-form approximation to the variational density . As with conventional variational schemes , we can update the modes of our three parameter sets in three distinct steps . However , the step dealing with the state ( D-step ) must integrate its conditional mode over time to accumulate the quantities necessary for updating the parameters ( E-step ) and hyperparameters ( M-step ) . We now consider optimising the modes or conditional means in each of these steps .
In these models the causes are known and enter as priors η with infinite precision; Σ v = 0 . Furthermore , if the model is static or , more generally when gx = 0 , we can ignore hidden states and dispense with the D-step . In these models , the parameters are known and enter as priors ηθ with infinite precision , Σ θ = 0 . This renders the E-Step redundant . We will review estimation under static models and then consider Bayesian deconvolution and filtering with dynamic models . Static models imply the generalised motion of causal states is zero and therefore it is sufficient to represent conditional uncertainty on their amplitude; i . e . , n = 0⇒D = 0 . As noted above the D-step for static models is integrated until convergence to a fixed point , which entails setting Δt = ∞; see [15] . Note that making n = 0 renders the roughness parameter irrelevant because this only affects the precision of generalised motion . In all the examples below , both the parameters and states are unknown . This entails a dual or triple estimation problem , depending on whether the hyperparameters are known . We will start with simple static models and work towards more complicated dynamic variants . See [33] for a comprehensive review of unsupervised learning for many of the models in this section . This class of models is often discussed under the rhetoric of blind source separation ( BSS ) , because the inversion is blind to the parameters that control the mapping from sources or causes to observed signals . In this final section , we revisit DEM and show that it can be formulated as a relatively simple neuronal network that bears many similarities to real networks in the brain . We have made the analogy between the DEM and perception in previous communications; here we focus on the nature of recognition in generalised coordinates . In brief , deconvolution of hidden states and causes from sensory data ( D-step ) may correspond to perceptual inference; optimising the parameters of the model ( E-step ) may correspond to perceptual learning through changes in synaptic efficacy and optimising the precision hyperparameters ( M-step ) may correspond to encoding perceptual salience and uncertainty , through neuromodulatory mechanisms .
In summary , any generic inversion scheme needs to induce a lower-bound on the log-evidence by invoking an approximating conditional density q ( ϑ ) that , for dynamic systems , covers generalised motion . Physical constraints on the representation of q ( ϑ ) enforce a fixed parameterised form so that is can be encoded in terms of its parameters or sufficient statistics . The Laplace or Gaussian assumption about this fixed-form affords a substantial simplification of recognition dynamics at the price of restricting recognition to unimodal probabilistic representations; a price that evolution may well have paid to optimise neuronal schemes . The mean-field approximation is ubiquitous in the statistics but may not be necessary in an online or neuronal setting . In conclusion , we have seen how the inversion of a fairly generic hierarchical and dynamical model of sensory inputs can be transcribed onto neuronal quantities that optimise a variational bound on the evidence for that model This optimisation corresponds , under some simplifying assumptions , to suppression of prediction error at all levels in a cortical hierarchy . This suppression rests upon a balance between bottom-up ( prediction error ) influences and top-down ( empirical prior ) influences that are balanced by representations of their precision ( uncertainty ) . These representations may be mediated by classical neuromodulatory effects and slow postsynaptic cellular processes that are driven by overall levels of prediction error . The ideas presented in this paper have a long history , starting with the notion of neuronal energy [87]; covering ideas like efficient coding and analysis by synthesis [88] , [89] to more recent formulations in terms of Bayesian inversion and predictive coding ( e . g . , [90] , [91] ) . The specific contribution of this work is to establish the generality of models that may , at least in principle , be entertained by the brain .
|
Models are essential to make sense of scientific data , but they may also play a central role in how we assimilate sensory information . In this paper , we introduce a general model that generates or predicts diverse sorts of data . As such , it subsumes many common models used in data analysis and statistical testing . We show that this model can be fitted to data using a single and generic procedure , which means we can place a large array of data analysis procedures within the same unifying framework . Critically , we then show that the brain has , in principle , the machinery to implement this scheme . This suggests that the brain has the capacity to analyse sensory input using the most sophisticated algorithms currently employed by scientists and possibly models that are even more elaborate . The implications of this work are that we can understand the structure and function of the brain as an inference machine . Furthermore , we can ascribe various aspects of brain anatomy and physiology to specific computational quantities , which may help understand both normal brain function and how aberrant inferences result from pathological processes associated with psychiatric disorders .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"mathematics/statistics",
"neuroscience",
"neuroscience/theoretical",
"neuroscience"
] |
2008
|
Hierarchical Models in the Brain
|
Trachoma is thought to be common over large parts of Southern Sudan . However , many areas of the country , particularly west of the Nile , have not yet been surveyed . The aim of this study was to confirm whether trachoma extends into Western Equatoria State from neighboring Central Equatoria , where trachoma is highly prevalent , and whether intervention with the SAFE strategy is required . Population-based cross-sectional surveys were conducted using a two-stage cluster random sampling method to select the study population . Subjects were examined for trachoma by experienced graders using the World Health Organization ( WHO ) simplified grading scheme . Two counties thought to be most likely to have trachoma were surveyed , Maridi and Mundri . In Maridi , prevalence of one of the signs of active trachoma ( trachomatous inflammation-follicular ( TF ) ) in children aged 1–9 years was 0 . 4% ( 95% confidence interval ( CI ) , 0 . 0%–0 . 8% ) , while no children showing the other possible sign , trachomatous inflammation-intense ( TI ) , were identified . No trachomatous trichiasis ( TT ) was found in those aged under 15 , and prevalence was 0 . 1% ( 95% CI , 0 . 0%–0 . 4% ) in those aged 15 years and above . In Mundri , active trachoma was also limited to signs of TF , with a prevalence of 4 . 1% ( 95% CI , 1 . 4%–6 . 9% ) in children aged 1–9 years . Again , no TT was found in those aged under 15 , and prevalence in those aged 15 years and above was 0 . 3% ( 95% CI , 0 . 0%–0 . 8% ) . Trachoma prevalence in the east of Western Equatoria State is below the WHO recommended intervention threshold for mass drug administration of antibiotic treatment in all villages . However , the prevalence of TF and TT in some villages , particularly in Mundri County , is sufficiently high to warrant targeted interventions at the community level . These results demonstrate that trachoma is not a major public health problem throughout Southern Sudan . Further studies will be required to determine trachoma prevalence in other areas , particularly west of the Nile , but there are presently no resources to survey each county . Studies should thus be targeted to areas where collection of new data would be most informative .
Trachoma is caused by ocular infection with the obligate intracellular bacterium Chlamydia trachomatis . Ocular Chlamydia is spread through contact with eye discharge from the infected person and through transmission by eye-seeking flies [1] . The disease is associated with poor personal and environmental hygiene , in particular limited access to water and sanitation , overcrowding and poor socioeconomic conditions . Trachoma is the leading infectious cause of blindness , estimated to be responsible for 3 . 6% of blindness worldwide [2] . It is endemic in 56 countries , mainly in poor rural areas , including parts of Central and South America , many African countries and some countries in the Eastern Mediterranean [3] . However , there is a lack of information from some major populations , including large parts of Southern Sudan , which remains an important obstacle to estimating the disease burden and to the implementation of control efforts [4] . The World Health Organization ( WHO ) has identified a need for more trachoma data , and it is recognized that such data are necessary for implementation of the SAFE strategy: Surgery for trichiasis , Antibiotics to treat infection , and Facial cleanliness and Environmental improvement to reduce transmission [5] . Trachoma has long been known to be prevalent in parts of Sudan [6] , [7] , but comprehensive data on distribution and burden particularly in Southern Sudan continue to be limited . To generate baseline data , the Carter Center and the Ministry of Health , Government of Southern Sudan ( MoH-GoSS ) , have jointly conducted prevalence surveys in thirteen sites covering a large geographical area mostly to the east of the river Nile [8] , [9] , [10] , [11] . In all of these locations the average prevalence of active trachoma ( trachomatous inflammation-follicular ( TF ) and/or trachomatous inflammation-intense ( TI ) ) in children aged 1–9 years was found to be well above the 10% threshold recommended by WHO for large-scale SAFE intervention [5] , [11] , [12] . Ngondi and colleagues have used prevalence data from Upper Nile and Jonglei to estimate that in these two States alone 3 . 9 million people need antibiotic treatment and 206 , 000 people are in need of immediate trichiasis surgery [9] . These estimates are based on the assumption that trachoma prevalence is homogenous over large areas , which remains to be confirmed for Southern Sudan . In common with other neglected tropical diseases ( NTDs ) endemic to Southern Sudan , there is a need to conduct additional surveys to better understand the epidemiology of trachoma and identify areas requiring interventions [13] . In Southern Sudan , a National Program for Integrated Control of NTDs has recently been established , presenting a new opportunity to contribute towards trachoma control by integrating annual distribution of antibiotic treatment with mass drug administration ( MDA ) of preventive chemotherapy ( PCT ) for other common NTDs , namely onchocerciasis , lymphatic filariasis ( LF ) , soil-transmitted helminth ( STH ) infection and schistosomiasis [14] , [15] . The program has started to operate in geographic areas where community-directed treatment with ivermectin ( CDTI ) for onchocerciasis control has been conducted for a number of years , because it intends to use the CDTI approach for co-implementation of other interventions where feasible [16] , [17] . Western Equatoria State is one of the two States that has been selected for initial integrated NTD intervention , because it has a large onchocerciasis focus and a well-established CDTI network , and anecdotal and past survey data indicate that LF , STH infection and schistosomiasis are also prevalent [12] . To date there are , however , no information or data available for this State on the distribution or prevalence of trachoma . The present study was therefore conducted to generate baseline data on the prevalence of trachoma in parts of Western Equatoria State to provide evidence as to whether annual MDA of PCT should include antibiotic treatment , and to contribute data to revise mapping of the burden of trachoma in the region [4] .
During November 2008 , two population-based prevalence surveys were conducted in Western Equatoria State , which lies in the South-West of Southern Sudan ( Figure 1 ) . The majority of people are agriculturalist , growing maize , cassava , groundnut , and fruit . The state capital is Yambio , and the other major towns are Tambura , Nzara , Maridi and Mundri . The total population of Western Equatoria State was estimated to be 845 , 989 in 2008 , using data collected during National Immunization Day . This is approximately 8% of the total population of Southern Sudan , which is estimated to be around 10 million . One trachoma survey was conducted in Mundri county and the other in Maridi county ( Figure 1 ) . At the time of the surveys , 186 , 668 people were estimated to live in Mundri and 186 , 830 in Maridi; both counties consisted of six payams . The study followed the standard MoH-GoSS protocol for trachoma prevalence surveys [18] . The protocol recommends that population-based prevalence surveys are conducted at county ( rather than payam ) level , which is the second ( rather than the third ) administrative level; the State being the first administrative level in Southern Sudan . Estimation at county rather than payam level was thought to be consistent with WHO guidelines , which recommend trachoma prevalence be estimated at district level or an administrative area corresponding to an average population size of 100 , 000 [19] , [20] . It was estimated that in each county a total sample size of 2000 people ( of all ages and sexes ) was required . This allows for an estimated prevalence of 5% trachomatous trichiasis ( TT ) in adults aged 15 years and above ( chosen because TT was likely to be the least prevalent indicator measured ) within a precision of 2% , given a 95% confidence limit and a design effect of 2 , and based on the assumption that adults aged 15 years and above comprise 50% of the population . In each county 20 villages were sampled with probability proportional to the estimated population size of the payam , although not all of the payams in Maridi were accessible . Households were randomly selected using the sketch map and segmentation method [21] . All residents of the household were enumerated , and all those present who gave informed consent were examined . Ophthalmic Clinical Officers and General Clinical Officers from the local payams were trained by an experienced ophthalmologist ( K . Lewis ) to use the WHO simplified grading system [22] . This scheme categorizes trachoma infection according to five grades: TF , TI , trachomatous scarring ( TS ) , TT and corneal opacity ( CO ) . Two stages of assessment were used to select the best trainees . In the first stage , trainee examiners identified trachoma grades using the WHO set of trachoma slides [22] . Those examiners who achieved at least 80% agreement then proceeded to the second stage of field evaluation . During field evaluation , a reliability study comprising 50 persons of varying age and sex were selected by the ophthalmologist to represent all trachoma grades . Each trainee examiner evaluated all 50 participants independently and recorded their findings on a pre-printed form . Inter-observer agreement was then calculated for each trainee using the ophthalmologists' observation as the “gold standard . ” Only trainees achieving at least 80% inter-observer agreement after the field evaluation were included as graders . All inhabitants of selected households who provided verbal consent were examined using a torch and a 2× magnifying binocular loupe . Each eye was first examined for in-turned lashes ( TT ) , and the cornea was then inspected for CO . The upper conjunctiva was subsequently examined for inflammation ( TF and TI ) and scarring ( TS ) . Both eyes were examined . Signs had to be clearly visible in accordance with the simplified grading system in order to be considered present . Trachoma signs only had to be present in one eye for the person to be categorized as suffering from a particular grade of trachoma . Alcohol-soaked cotton swabs were used to clean the examiner's fingers between examinations . Individuals with signs of active trachoma or bacterial conjunctivitis were treated with 1% tetracycline eye ointment and provided with information on face washing and good hygiene practices . Patients with TT or other significant eye conditions were referred to the nearest facility where free surgery is available ( i . e . Juba Teaching Hospital ) . The data was initially entered using Personal Digital Assistants ( PDA , Palm Tungsten E2 ) in the field . A second data entry was conducted by the Trachoma Control Program , MoH-GoSS using Microsoft Office Excel . Consistency checks were performed in EpiInfo version 3 . 2 . 2 ( Centers for Disease Control and Prevention [http://www . cdc . gov/EpiInfo] ) . Range and consistency checks were conducted for all variables . Data were analyzed in STATA 9 . 0 software ( Stata Corporation , College Station , TX , U . S . A . ) . Individuals with missing data on sex and/or age were excluded from the analysis . For each county , prevalences of trachoma signs were summarized by age , in relation to WHO recommendations for implementation of trachoma control activities [5] . Unadjusted exact binomial 95% confidence intervals ( CIs ) are presented , along with adjusted 95% CIs that account for potential clustering obtained using generalized estimating equation ( GEE ) modeling . Chi-squared tests , or Fishers test where appropriate , were used to examine evidence for differences in proportions . The study protocol received ethical approval from the Directorate of Research , Planning and Health System Development , MoH-GoSS . Clearance to conduct the surveys was obtained from the State MoH , followed by County Health Departments and the local government . The study was explained to each member of the selected households . The household heads were asked to provide written consent for the entire household to participate in the study , and each inhabitant of the household who provided verbal consent was examined . Those individuals who did not provide verbal consent were not examined . Personal identifiers were removed from the dataset before analysis .
The overall prevalence of TF ( adjusted 95% CI ) in children aged 1–9 years in Maridi was 0 . 4% ( 0 . 0–0 . 8% ) with cases occurring only in male children ( Table 2 ) . In Mundri , the prevalence of TF ( adjusted 95% CI ) in children aged 1–9 years was 4% ( 1 . 4–6 . 9% ) , with similar prevalence in male and female children . No cases of TI were found in either county , so prevalence estimates for active trachoma are the same as for TF . For TT , the overall prevalence ( adjusted 95% CI ) in those aged 15 years and above in Maridi was estimated to be 0 . 1% ( 0 . 0–0 . 4% ) based on just one female individual with TT ( Table 2 ) . In Mundri , three male individuals were found to have TT leading to a prevalence estimate of 0 . 3% ( 0 . 0–0 . 8% ) . The small number of individuals with TT also had some degree of corneal opacity . No trichiasis was found in individuals under the age of 15 in either county . Little evidence of scarring was observed in either county , the highest prevalence ( adjusted 95% CI ) was in individuals aged 15 and over in Mundri; 0 . 9% ( 0 . 2–1 . 5% ) . No villages in Maridi had a prevalence of TF above 5% , but one village did have a prevalence of TT of more than 1% ( Table 3 , Figure 1 ) . In Mundri , two villages had a prevalence of TF between 5% and 9% and a further three villages had a prevalence of more than 10% ( Table 3 , Figure 1 ) , suggesting a requirement for F and E components of the SAFE strategy in these five villages along with annual MDA of antibiotics in the three villages with higher prevalence . Two additional villages in Mundri had a prevalence of TT of more than 1% ( Figure 1 ) .
The low prevalence of trachoma observed in the present study and the lack of reported cases from other counties in Western Equatoria State suggest that trachoma is also unlikely to be highly endemic in those counties not surveyed to date . Although this needs to be verified , we do not consider this a current priority . Instead , the limited resources available for surveys should be used to generate baseline data for counties where trachoma is known to be a problem , but where there is no data to monitor interventions . Among these , counties where intervention is feasible ( in terms of access and funding ) should be prioritized . In addition , it will be important to complete the picture of trachoma epidemiology in Southern Sudan , to get a better understanding of the scale of the burden and the resources required to eliminating blinding trachoma from Southern Sudan by 2020 . In the interest of conserving scarce resources , we propose that trachoma distribution is assessed in stages . In the first stage , the large amount of existing prevalence data should be used to develop a trachoma risk map for the whole of Southern Sudan , which will not only indicate where trachoma is certain to be highly endemic but also where prediction of endemicity is rather uncertain . Based on this information , rapid assessments should then be conducted in those areas with no data and high uncertainty of the level of endemicity . Based on the outcome of such assessments it can be decided whether one should move to the third stage - detailed prevalence surveys - to provide baseline data . In an iterative process , the data generated through rapid assessments and additional prevalence surveys should be used to verify the predictions of the risk map model , and fine tune and improve these , including estimates of the national trachoma burden .
|
Baseline data on trachoma prevalence is a prerequisite for intervention . Prior to the present study , all surveys in Southern Sudan reported trachoma prevalences that exceeded the threshold for large-scale intervention . This gave rise to the notion that the disease may be endemic throughout the country . The present study was conducted under the auspices of the National Program for Integrated Control of Neglected Tropical Diseases , to verify whether prevalences in two counties west of the Nile exceeded the WHO recommended intervention threshold for mass drug administration ( MDA ) of antibiotic treatment . The results show that trachoma prevalence at county level was below this threshold . However , prevalences in some communities within the county were above the threshold , meaning that they should be targeted with MDA of antibiotics , as well as with other interventions such as trichiasis surgery , health promotion and improved water and sanitation . This finding reminds us of the need for geographical targeting of resources , both for surveys and subsequent intervention . Current resources are insufficient to conduct population-based prevalence surveys for trachoma throughout Southern Sudan . Further surveys should thus be conducted in areas where collection of additional information will be most informative . We propose that a combination of risk-mapping and rapid assessments is used to identify such areas .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/bacterial",
"infections",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"public",
"health",
"and",
"epidemiology",
"infectious",
"diseases/epidemiology",
"and",
"control",
"of",
"infectious",
"diseases"
] |
2009
|
Trachoma in Western Equatoria State, Southern Sudan: Implications for National Control
|
In Lao People’s Democratic Republic pigs are kept in close contact with families . Human risk of infection with pig zoonoses arises from direct contact and consumption of unsafe pig products . This cross-sectional study was conducted in Luang Prabang ( north ) and Savannakhet ( central-south ) Provinces . A total of 59 villages , 895 humans and 647 pigs were sampled and serologically tested for zoonotic pathogens including: hepatitis E virus ( HEV ) , Japanese encephalitis virus ( JEV ) and Trichinella spiralis; In addition , human sera were tested for Taenia spp . and cysticercosis . Seroprevalence of zoonotic pathogens in humans was high for HEV ( Luang Prabang: 48 . 6% , Savannakhet: 77 . 7% ) and T . spiralis ( Luang Prabang: 59 . 0% , Savannakhet: 40 . 5% ) , and lower for JEV ( around 5% ) , Taenia spp . ( around 3% ) and cysticercosis ( Luang Prabang: 6 . 1 , Savannakhet 1 . 5% ) . Multiple correspondence analysis and hierarchical clustering of principal components was performed on descriptive data of human hygiene practices , contact with pigs and consumption of pork products . Three clusters were identified: Cluster 1 had low pig contact and good hygiene practices , but had higher risk of T . spiralis . Most people in cluster 2 were involved in pig slaughter ( 83 . 7% ) , handled raw meat or offal ( 99 . 4% ) and consumed raw pigs’ blood ( 76 . 4% ) . Compared to cluster 1 , cluster 2 had increased odds of testing seropositive for HEV and JEV . Cluster 3 had the lowest sanitation access and had the highest risk of HEV , cysticercosis and Taenia spp . Farmers which kept their pigs tethered ( as opposed to penned ) and disposed of manure in water sources had 0 . 85 ( 95% CI: 0 . 18 to 0 . 91 ) and 2 . 39 ( 95% CI: 1 . 07 to 5 . 34 ) times the odds of having pigs test seropositive for HEV , respectively . The results have been used to identify entry-points for intervention and management strategies to reduce disease exposure in humans and pigs , informing control activities in a cysticercosis hyper-endemic village .
Approximately two thirds ( 66 . 9% ) of the 6 . 4 million residents of Lao PDR reside in rural areas and most ( 83% ) of the 0 . 8 million households are considered agricultural holdings [1] . The majority of these employ mixed farming systems ( i . e . keeping both livestock and crops ) . In recent years , intensification of crop production has improved accessibility to remote villages which were previously isolated . Although this has many benefits for both crop and livestock production , e . g . improved access to markets , it also increases infectious disease transmission between villages . Historically , most pig-owning households employed traditional village practices ( low-input , extensive scavenger systems ) , however farmers are switching to confined systems in order to reduce disease risk and prevent cash-crop damage [2] . Integrated pig production also occurs whereby pig faeces is utilized as an input for another production system such as manure for crops or fish feed . Co-habitation with animals is common in Lao PDR; even in urban households and households where livestock rearing is not a major source of income [3] . Close proximity with livestock poses a risk of zoonotic infection via direct contact or environmental contamination . Additional potential transmission routes include consumption of unsafe products such as raw or undercooked pork , raw pig’s blood and fermented pork sausage . In Lao PDR , funding for human health care and veterinary services is lacking; resulting in poor access , low diagnostic capabilities and virtually non-existent surveillance and control of zoonotic diseases [4] . As a result , under-reporting of diseases is commonplace and public health and veterinary services’ capacity are readily overwhelmed by disease outbreaks [5] . The epidemiology of hepatitis E , cysticercosis/taeniasis , trichinellosis and Japanese encephalitis were investigated in this study . Stakeholders from the Ministry of Health , National Animal Health Laboratories and the National Centre for Laboratory and Epidemiology in Lao PDR , and previous research funded by the Australian Centre for International Agricultural Research ( ACIAR ) [6–9] identified these diseases as pig zoonoses of national importance . Hepatitis E virus ( HEV ) is primarily water-borne and can cause acute hepatitis; transmission is via faecal-oral route and contaminated water is responsible for most outbreaks [10] . Symptoms include jaundice , abdominal pains , nausea and fever with high case fatality rate reported in pregnant women [10] . Zoonotic transmission occurs through consumption of undercooked contaminated meat and shellfish [11] . In addition , slaughterhouse workers , pig farmers and veterinarians have a high risk of occupational exposure [12] . Transmission routes for pigs are direct contact or ingestion of feed or water contaminated with faeces of infectious pigs . The disease in pigs is generally asymptomatic . Hepatitis E is generally endemic in regions with poor sanitation and hygiene including large parts of Asia . Previous estimates of HEV seroprevalence in pigs in Lao PDR in the Luang Prabang Province were 15% ( dry season ) and 47 . 1% ( wet season ) [7] . Trichinella spiralis is thought to be endemic in the pig population in Lao PDR and infection in humans occurs via the ingestion of raw or undercooked meat containing the larvae of T . spiralis nematodes [8 , 13] . Suspected human cases occur regularly in Lao PDR , however , diagnostic facilities and outbreak investigation are lacking [5] . Large outbreaks of the disease usually occur at festivals or funerals and the largest reported outbreak in Lao PDR was in the north with 650 suspected human cases [5] . Transmission among pigs is through scavenging or feeding of undercooked meat containing the parasite . Faecal oral transmission and tail biting are believed to be minor routes of infection [14] . Japanese encephalitis , a vector-borne virus transmitted by Culex mosquitos is a major cause of morbidity and mortality in humans , and reduced productivity of pigs in Southeast Asia [15] . Epidemics occur after amplification of Japanese encephalitis virus ( JEV ) in immunologically naïve pigs housed close to human populations; most notably near rice paddies during the rainy season . A previous study in Oudomxay , Luangprabang , Xiengkhuang and Huaphan Provinces estimated the seroprevalence in pigs to be high ( 74 . 7% ) [9] . Taenia solium causes human and porcine cysticercosis and is considered one of the most important diseases in Southeast Asia , and a neglected zoonotic disease [4] . Human taeniasis describes infection by the adult tapeworm following consumption of raw or undercooked pork contaminated with the larval stage of T . solium ( or T saginata in beef ) [16] . Cysticercosis in pigs and humans is caused by ingestion of T . solium eggs expelled from infected humans via food , water , or environmental faecal contamination . In humans , this can lead to the development of mature cysts in various organs including muscles , eyes , subcutaneous tissues and the central nervous system . Cysticercosis causes significant morbidity and mortality in humans and can lead to neuro-cysticercosis; the leading cause of epilepsy in the region [4] . Although , asymptomatic in pigs , losses occur due to the development of metacestodes leading to carcass condemnation . Previous prevalence estimates in Lao PDR ( Vientiane ) in pigs range from 0 to 14% [6] . The aim of the study was to estimate the seroprevalence of HEV , JEV , T . spiralis in humans and pigs and Taenia spp . and cysticercosis in humans in Luang Prabang ( upland ) and Savannakhet ( lowland ) Provinces and identify risk factors for infection . Focussing on ‘unsafe practices’ facilitates identification of entry points for intervention; providing useful information for the control and surveillance of zoonotic diseases in Lao PDR . These data are intended for use by animal and human health authorities to inform targeting of scarce resources to high risk populations .
The study was conducted in 2011 in one upland and one lowland Province of Lao PDR which differed in terms of climate , topography , farming systems , range of ethnicities and socioeconomic status . In addition to discussion with local partners , a report by the Swiss National Centre of Competence in Research ( NCCR ) which detailed geographic differences of indicators of socioeconomic status ( e . g . sanitation , drinking water and education ) was consulted to ensure variation in risk factors for the pathogens investigated [17] . Luang Prabang Province ( 20 . 21°N , 102 . 62°E ) , situated in northern Lao PDR covers an area of 16 , 875km2 and shares a border with Vietnam . At an altitude of 700 to 1 , 800m above sea level , it was selected to represent a typical upland Province . In addition to Lao Loum ( the predominant ethnic group in Lao PDR ) this Province is inhabited by Hmong ( Lao Soung ) who tend to reside in mountainous regions and Khmu ( Lao Theung ) who have settled at medium altitudes [18] . Each of these groups are unique in terms of culture , language , and differ in land-use practices and socio-economic status [18] . Savannakhet Province ( 26 . 54°N 105 . 78°S ) , situated in the southern-central part of the country shares a border with both Thailand and Vietnam , covers an area of 21 , 774km2 and is 145m above sea level . Lao Loum is the main ethnic group ( >75% ) with the remainder of the population being predominantly of Lao Theung ethnicity . The Province contains floodplains of the Mekong Delta and is the largest rice-producer in the country . Annual rainfall averages around 1 , 450mm per year and the Province is prone to both droughts and flooding [19] . Pig production is common and there are an increasing number of commercial pig farms close to the Thai border . The sample size calculation used a seroprevalence of 50% as little prior information was available and was sufficient to estimate human seroprevalence with 5% precision . In total , 59 villages were randomly selected ( 29 in Luang Prabang and 30 in Savannakhet ) using probability proportional to human population . In each village , 15 households were randomly selected regardless of pig ownership during a village-wide meeting . Within these households , one household member over 5 years of age was randomly selected to be sampled and interviewed , resulting in a total of 895 human participants . A questionnaire for humans , developed in consultation with local health authorities , gathered information on socio-economic factors , pig-farming practices , cooking and eating behaviour , sanitation facilities and hygiene practices . Questionnaires were administered by district public health officials belonging to several ethnic groups and were conducted in native languages of the villagers . Approximately 15 pig-owning households were randomly selected from each village . In each household , one pig over 12 weeks of age was randomly selected for blood sampling and the owner was interviewed . A questionnaire for pig owners gathered information on pig health and management . As sampling was done probability proportional to human size selected villages were found to have a range of pig densities , therefore the target of 15 pig-owning households could not be satisfied in all villages resulting in a total 647 pigs sampled . In addition , seroprevalence estimates for pigs will have lower accuracy and may be subject to bias . Therefore we will only refer to the percentage of pigs testing seropositive when discussing the pig results . Although the results will give an indication of the magnitude of the problem in pigs . Knowledge dissemination to participating villages consisted of a summary of results and information regarding prevention of these diseases in pigs and humans . These sessions were carefully designed in an attempt to maximise the uptake of recommendations . Ethical approval was granted by the Institutional Research Ethics Committee ( IREC ) of the International Livestock Research Institute ( ILRI ) and the National Ethics Committee for Health Research in Lao PDR ( No . 772 NIOPH/NECHR ) . All selected participants were asked to give informed written consent before being blood sampled and interviewed , if they were under the age of 18 then their parent or guardian provided consent and could give information on their behalf when needed . Owners of selected pigs were asked to give informed consent to be interviewed and for their pigs to be sampled . All laboratory testing was performed in Lao PDR at the National Animal Health Laboratory , Ministry of Agriculture and Fisheries or the National Centre for Laboratory and Epidemiology , Ministry of Health . Blood samples were collected in plain vacutainers . Samples were refrigerated and then placed on ice until arrival at the laboratory , where they were stored at -20°C before testing . Human serum samples were tested for the presence of antibodies against HEV , T . spiralis , JEV and the ratio of JEV to dengue virus antibodies using the following commercial diagnostic kits: HEV ELISA 4 . 0 ( MP Diagnostics , Singapore , reported sensitivity of 98% and specificity of 96 . 7% ) , T . spiralis IgG ELISA ( IBL International , Germany , reported sensitivity of 95% and specificity of 94 . 8% ) and the JE-Dengue IgM Combo ELISA Test E-JED01C ( Panbio , France , sensitivity at 89 . 3% and specificity at 99 . 2% using samples from Thailand [20] ) . Manufacturers’ instructions were followed when conducting and interpreting these kits . Antibodies against cysticercosis and Taenia spp . were detected using an enzyme-linked immunoelectrotransfer blot ( EITB ) as per Salim et al . ( 2009 ) [21] . This strip contains two recombinant antigens for cysticercosis ( rT24H ) and Taenia spp . ( rES33 ) . The detection of the T24 antigen has a sensitivity of 94% with two or more cysts in the brain [22] , but drops to around 63% with only one cyst , specificity is around 98% . For Taenia spp . sensitivity of rES33 of 99 . 4% and specificity of 94 . 5% have been reported [23] . Pig serum samples were tested for the presence of antibodies against HEV using the HEV ELISA 4 . 0v kit ( MP Diagnostics , Singapore: reported sensitivity of 98% and specificity of 96 . 7% ) ; for T . spiralis antibodies using the Priocheck Trichinella Ab ELISA ( Prionics , Switzerland . Sensitivity: 97 . 1–97 . 8% and specificity: 99 . 5–99 . 8% ) [24]; and for JEV IgM specific antibodies and IgG specific antibodies using non-commercial ELISA kits developed by the Australian Animal Health Laboratory , Geelong Australia . Pigs were not tested for cysticercosis as part of this study as the antibodies lack diagnostic specificity and severe cross-reactivity can occur with pigs infected with other parasites ( which may be present in the region ) . Manufacturers’ instructions were followed when using these kits .
In total 895 people and 647 pigs were sampled . Problematic samples ( e . g . insufficient serum ) or inconclusive test results were classified as missing ( <10% for any pathogen ) . A high percentage of both pigs and people were seropositive for HEV ( Table 1 ) . However , humans were more likely to be seropositive in Savannakhet: 77 . 7% ( 95% Confidence interval ( CI ) : CI: 73 . 7 to 81 . 6 ) vs . 48 . 6% ( 95% CI: 43 . 9 to 53 . 3 ) , whilst pigs were more likely to be seropositive in Luang Prabang Province . There was a high seroprevalence of T . spiralis in humans; particularly in Luang Prabang Province ( 59 . 0% , 95% CI: 54 . 3 to 63 . 6 ) . Seroprevalence for JEV in pigs was high; particularly in Savannakhet ( 81 . 4% , 95% CI: 76 . 8 to 85 . 8 ) Fig 1 shows the coordinates of each variable on the two dimensions which explained the largest percentage of the variance in the data . Variables with coordinates close to zero are not well represented and the further away from the axis , the better represented the variable on that dimension . Variables which are closest to each other on the scatterplot are the most closely related . The variables in black are those which contributed to the creation of the dimensions; variables such as slaughtering pigs , pigs’ blood consumption and whether they boiled water before consumption are well represented on both dimensions . Type of water source and whether individuals handle pigs are better represented on dimension one ( horizontal axis on Fig 1 ) , whilst handling offal is well represented on the second dimension . Supplementary variables ( purple ) are also included on the scatterplot to visualise how these relate with the dimensions . The cluster analysis was performed using the first three dimensions which explained 49 . 8% of the total variation and not less than 12% individually . The profiles of each cluster identified through HCA are described in Table 2; most people were classified as cluster 1 ( 51 . 1% ) . In general , this cluster had more females ( 65 . 6% ) , people were mainly Lao Loum ( 84 . 4% ) and appeared to be better educated than the other clusters . They also appeared to have better hygiene practices with most people having toilet access ( 86 . 1% ) , washing their hands after the toilet ( 92 . 5% ) , using protected water sources ( 90 . 4% ) and boiling water before consumption ( 92 . 1% ) . In terms of pig contact , most had no pigs in the household ( 83 . 0% ) and did not handle or slaughter pigs ( >95% ) . This cluster was used as the baseline for risk factor analysis . People in cluster 2 were mostly male ( 83 . 1% ) , many were Khmu ( 42 . 7% ) and from Luang Prabang Province ( 70 . 2% ) . Sanitation and education levels were lower than the majority of cluster 1 , however , the main differences were due to contact with pigs and consumption habits . Most were involved with pig-slaughtering ( 83 . 7% ) , handled offal and/or raw meat ( 99 . 6% ) consumed raw pigs’ blood ( 76 . 4% ) , and more had pigs in the household compared to cluster 1 ( 36 . 0% ) . Around half had access to toilets ( 56 . 2% ) and used protected water sources ( 51 . 1% ) . However , most washed their hands after using the toilet ( 83 . 1% ) and boiled water before consumption ( 87 . 1% ) . Some cluster 3 participants also used unprotected water sources ( 34 . 7% ) and only a third boiled their water before consumption . Only 7 . 2% of this cluster had toilet access and most people did not always wash their hands after using the toilet ( 61 . 9% ) . This cluster appeared to have the lowest level of education with 42 . 4% having no schooling . For the analysis the odds of testing seropositive for the various pathogens for people in cluster 2 and 3 were compared to the odds of testing seropositive in in cluster 1 ( protected water sources , boiled water , good hygiene practices and relatively low pig contact ) . These results are summarised in Table 3 . Compared to cluster 1 , people in cluster 2 ( higher pig contact: particularly in terms of slaughtering , handling offal/raw meat and more likely to drink raw pigs’ blood with moderate hygiene practices , mostly Luang Prabang Province ) and people in cluster 3 ( unprotected water sources , poorer hygiene practices , pigs in household , mostly Savannakhet Province ) had 0 . 52 ( 95% CI: 0 . 33 to 0 . 82 ) and 0 . 42 ( 95% CI: 0 . 28 to 0 . 61 ) times the odds of testing seropositive for T . spiralis , respectively . Therefore cluster 1 had the highest risk of this parasite . Clusters 2 and 3 had 2 . 18 ( 95% CI: 1 . 37 to 3 . 45 ) and 2 . 30 ( 95% CI: 1 . 58 to 3 . 33 ) times the odds of testing seropositive for HEV , compared to cluster 1 , respectively . People in cluster 2 ( high pig contact ) were also more likely to test seropositive for JEV ( OR: 2 . 49 , 95% CI: 1 . 12 to 5 . 19 ) and cluster 3 ( poor sanitation ) were more likely to test seropositive for Taenia spp . ( OR: 3 . 38 , 95% CI: 1 . 12 to 10 . 2 ) and cysticercosis ( OR: 2 . 69 , 95% CI: 1 . 00 to 7 . 50 ) , compared to cluster 1 . Farmers that called an animal health worker ( or similar ) if their pig was sick had 0 . 38 ( 95% CI: 0 . 18 to 0 . 80 ) times the odds of having pigs test seropositive for T . spiralis , compared to farmers which reported self-treating their pigs ( Table 4 ) . Pigs kept in tethered systems had 0 . 85 ( 95% CI: 0 . 18 to 0 . 91 ) times the odds of testing seropositive for hepatitis E compared to those in penned systems . Further; households that disposed of pig manure in water sources had 2 . 39 ( 95% CI: 1 . 07 to 5 . 34 ) times the odds of testing seropositive for hepatitis E .
The seroprevalence of HEV in humans was very high , particularly in Savannakhet province . Seroprevalence does not necessarily indicate recent infection as humans may be exposed at a young age and develop immunity to subsequent exposures . However , it does suggest circulation of the virus in the area . Cluster 2 and 3 had increased odds of seropositivity for HEV compared to cluster 1 . Presumably , the main transmission route is consumption of contaminated water as these clusters were more likely to use unprotected water sources and practice open defaecation . People in cluster 3 were also much less likely to boil water before consumption and wash their hands after . The zoonotic nature of the disease was suggested as people in cluster 2 were more likely to have occupational contact ( slaughtering and handling pigs ) . This has previously been reported as a risk factor for infection [11] , although adult pigs are usually free of virus shedding . However , we cannot be sure that humans had a zoonotic strain of the virus as only two ( genotype 3 and 4 ) of the four virus genotypes affecting humans are commonly found in pigs . In a previous study in Luang Prabang district 15 . 7% ( 95% CI: 5 . 4 to 26 . 0 ) of pigs had detectable HEV RNA ( genotype 4 ) in their faeces [7] . In the current study , pigs from households where manure ended up in water sources were more likely to be seropositive for HEV . HEV strains of swine origin have previously been identified in surface water; which may also present an additional route of transmission to humans [26] . Hepatitis E is responsible for more than 50% of cases of acute hepatitis in endemic countries and the disease has a high case fatality rate in pregnant women [27] . People in cluster 1 appeared to have the highest risk of T . spiralis . More people in this cluster reported eating fermented sausage ( compared to cluster 2 ) and were from Luang Prabang Province ( compared to cluster 3 ) . Most previous outbreaks have been reported in the North [5] . Although cluster 1 had the best hygiene practices and higher education levels they appeared to have a higher risk of T . spiralis . However , due to its route of transmission ( consumption of contaminated meat ) it is generally associated with wealthier Lao residents who tend to consume meat more often [8] . Heavy parasite loads can lead to myocarditis , encephalitis or death . The International Commission on Trichinellosis recommends a range of measures including well-cooked pork and not feeding undercooked pork to pigs in swill . Cluster 3 had the highest risk of Taenia spp . /cysticercosis and people in this cluster were the most likely to practice open defaecation ( 92 . 5% ) , which is one of the biggest risk factors for cysticercosis [16] . Around 50% of the cluster consumed fermented sausage which may lead to ingestion of the tapeworm ( taeniasis ) ; however , this was a similar figure to cluster 1 which had a lower risk of testing seropositive for Taenia spp . It is possible that in areas where open defaecation is practiced , ingestion of contaminated vegetation and/or water by pigs and humans is more likely , maintaining the parasite lifecycle [6] . In addition , cluster 3 were mainly from Savannakhet where more than half the pigs sampled were tethered or free grazed , compared to Luang Prabang Province where 90 . 6% were penned , suggesting that pigs may have greater access to human faecal matter in this province . Although it is assumed humans were infected with T . solium , T . hydatigena may also have been responsible for seropositive results . Cysticercosis should be a priority disease for control as it is endemic throughout Southeast Asia , is the leading cause of epilepsy in the region , and is currently classified as a Neglected Tropical Disease [4] . Following this study an intervention was launched in a very high prevalence ( “hyper-endemic” ) village . This combined Mass Drug Administration in humans with vaccination and anthelmintic treatment in pigs . This was done in conjunction with education campaigns to increase community awareness and knowledge of the risks of the disease and preventive measures , in order to discourage open defaecation . This intervention has promising results to date [28] . The selection of the study areas aimed for a representative cross-section of villages in Lao PDR in terms of ethnicities and production systems . Therefore study findings may be generalised to some other areas . The results of this study could be used to inform entry points for intervention . For example targeting villages for risk-based surveillance and control activities such as reduction of open defaecation practices , particularly with high levels of pigs in free range scavenger systems . Japanese encephalitis is a major public health concern due to its’ high mortality and morbidity , particularly in younger children [27] . The percentage of seropositive pigs was 73 . 0% which is very similar to a previous study in Northern Lao PDR [9] . People in cluster 2 , with the highest seroprevalence were mainly from Luang Prabang and had the highest pig contact . Pigs are a reservoir for human infection and per capita pig density is reported to be high in the northern region of Lao PDR [1] . A higher proportion of pigs were seropositive to the JEV MAC test in the North; this detects IgM antibodies indicating recent infection . Use of mosquito nets in the sampled villages was ubiquitous and it appears close pig contact poses the biggest risk in the region . The study has several limitations; the main limitation is that pigs and humans were recruited separately therefore correlation of infection within households cannot be investigated as part of this study . Robust seroprevalence estimates were achieved for the human part of the survey , but not for pigs . Adjusting the estimates to predict pig seroprevalence might have been possible by applying weightings to the villages according to their proportion of the total provincial pig population . However , village-level pig population data was not available , even at the Provincial level . Prevalence estimates based on serology do not give an accurate estimate of recent infections and risk factor analysis may have excluded past exposures . However , it does mean that past infections are included in the study . In addition , cross-reactivity for Taenia spp . can occur with other parasitic infections e . g . echinococcosis , schistosomiasis , angiostrongyliasis and fasciolasis [23 , 29] . Recent high quality evidence on the presence of these parasites in the study areas is lacking , therefore the likelihood of false positive results cannot be assessed . As risk factor analysis was performed using the results of the cluster analysis the risk factors are aggregated and associations with specific exposures and the pathogens are not explicitly assessed . However , many of the exposures were highly correlated and the seroprevalence of cysticercosis , Taenia spp . and JEV was very low and HEV seroprevalence very high which made multivariate risk factor analysis using traditional methods difficult . Despite these drawbacks the results provide useful information on the burden and routes of transmission of important zoonotic pathogens of pigs for a country where surveillance data is lacking . Meat inspection is recommended for the control of certain zoonoses including trichinellosis and taeniasis/cysticercosis but informal slaughter practices , lack of secure funding , limited technical capacity and limited data on the supply chain make this very difficult to implement in Lao PDR . Many farmers rely on middlemen who buy and sell their pigs and the point of slaughter is often unknown . Therefore , farmers require practical and low cost options for control . Increasing awareness of the financial impact of zoonotic diseases in pigs may motivate farmers’ to participate in disease control . Over 80% of individuals in cluster 2 , which had higher risk of Taenia spp . , cysticercosis and HEV , did not wash hands after using the toilet or boil water before consumption . Furthermore , 42 . 3% of all individuals in the current study practiced open defaecation . Simple low-cost measures such as correct hand washing and reducing consumption of undercooked meat may reduce the zoonotic disease burden in Lao PDR . However , many of these factors are socio-cultural; encouraging behaviour change can be difficult and education campaigns are needed . Schools may provide a good starting point for education interventions , provided they are attended by the majority of children . School-led sanitation programs in other developing countries have shown some success in encouraging hand washing and reducing open defaecation near schools , and the community [30] . This study highlights the importance of zoonotic diseases originating from pigs in Lao PDR and has identified typologies of individuals who are at higher risk of infection . Funding for disease control in Lao PDR is lacking therefore recommendations for realistic and low-cost disease control measures in both pigs and humans are required . Increasing disease awareness may motivate farmers to participate in disease control and encourage Laotians to use simple preventive measures to reduce transmission of these pathogens to humans .
|
In Lao PDR , pigs are an important source of food and income and are kept by many rural residents . This study investigated five diseases that are transmitted between pigs and humans ( zoonoses ) , namely hepatitis E , Japanese encephalitis , trichinellosis , cysticercosis and taeniasis . Humans and pigs in Lao PDR were tested for antibodies against the agents ( pathogens ) responsible for these diseases . Human participants were classified into three groups or "clusters" based on hygiene and sanitation practices , pig contact and pork consumption . Cluster 1 had low pig contact and good hygiene practice . Cluster 2 had moderate hygiene practices: around half used toilets and protected water sources; most people washed their hands after using the toilet and boiled water prior to consumption . Most people in this cluster were involved in pig slaughtering , drank pigs’ blood and were more likely test positive for antibodies against hepatitis E and Japanese encephalitis viruses . Finally , people in cluster 3 had lowest access to sanitation facilities , were most likely to have pigs in the household and had the highest risk of hepatitis E , taeniasis and cysticercosis . The diseases in this study pose a significant threat to public health and impact pig production . This study identified characteristics of high-risk individuals and areas with high disease burden and could be used to target future disease control activities to those most vulnerable .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"livestock",
"medicine",
"and",
"health",
"sciences",
"enzyme-linked",
"immunoassays",
"lao",
"people",
"pathology",
"and",
"laboratory",
"medicine",
"pathogens",
"tropical",
"diseases",
"microbiology",
"vertebrates",
"parasitic",
"diseases",
"animals",
"mammals",
"health",
"care",
"ethnicities",
"viruses",
"sanitation",
"neglected",
"tropical",
"diseases",
"infectious",
"disease",
"control",
"immunologic",
"techniques",
"research",
"and",
"analysis",
"methods",
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"swine",
"zoonoses",
"medical",
"microbiology",
"microbial",
"pathogens",
"immunoassays",
"hepatitis",
"viruses",
"agriculture",
"people",
"and",
"places",
"helminth",
"infections",
"environmental",
"health",
"viral",
"pathogens",
"cysticercosis",
"biology",
"and",
"life",
"sciences",
"population",
"groupings",
"amniotes",
"organisms",
"hepatitis",
"e",
"virus"
] |
2016
|
Endemicity of Zoonotic Diseases in Pigs and Humans in Lowland and Upland Lao PDR: Identification of Socio-cultural Risk Factors
|
In the Gran Chaco region , control of Triatoma infestans has been limited by persistent domestic infestations despite the efforts of the Vector Control Services . In Paraguay , this region is the highest endemic area in the country , showing high levels of indoor and outdoor infestation . Although sylvatic T . infestans have been found in the Bolivian and Argentine Chaco , similar searches for sylvatic populations of this species in Paraguay had been unsuccessful over the last 20 years . Here we present a new approach to detecting sylvatic Triatominae , using a trained dog , which has successfully confirmed sylvatic populations of T . infestans and other triatomine species in Paraguay . A total of 22 specimens corresponding to dark morph forms of T . infestans were collected , and 14 were confirmed as T . infestans by the mitochondrial cytochrome B gene analysis . Through this analysis , one of which were previously reported and a second that was a new haplotype . Triatomines were captured from amongst vegetation such as dry branches and hollows trees of different species such Aspidosperma quebracho-blanco , Bulnesia sarmientoi and Stetsonia coryne . The colonies found have been small and without apparent infection with Trypanosoma cruzi . During the study , Triatoma sordida and Triatoma guasayana have also been found in ecotopes close to those of T . infestans .
Triatoma infestans ( Hemiptera , Reduviidae ) is the main vector of Chagas disease ( American trypanosomiasis ) in the Southern Cone of Latin America . Through the Southern Cone Initiative against Chagas disease , vectorial transmission to humans has been interrupted in Chile , Uruguay and Brazil , but Argentina and Paraguay have achieved this only in some regions [1] . In the Gran Chaco region , comprising parts of Argentina , Bolivia and Paraguay , control of the vectors has been limited due to the persistence of domestic infestations despite the efforts of the Vector Control Services in these countries [2] , [3] . Studies conducted since the 1970s have shown high levels of indoor infestation of T . infestans in the Paraguayan Chaco , characterizing this region as the highest endemic area in the country [4]–[8] . However , sylvatic populations of this vector have only occasionally been reported in Paraguay [9] although nymphs of T . infestans were recently reported amongst vegetation near indigenous dwellings [10] . By contrast , sylvatic T . infestans have been more frequently reported from the Andean valleys of Cochabamba and La Paz in Bolivia , and also in the Bolivian Chaco [11]–[13] and the Argentine Chaco [9] , [14] . The finding of dark morph ( DM ) T . infestans in parrot nests in Argentina [14] , and the finding of extensive new foci of sylvatic triatomine populations in Bolivia [15] encouraged the intense search in the Paraguayan Chaco region , but the search for this species using light traps and manual checking of fallen trees and burrows had been unsuccessful . We report here a novel approach using a trained dog , which has revealed several sylvatic populations of T . infestans in the Paraguayan Chaco . Domestic dogs ( Canis familiaris ) are used by humans to locate a range of substances because of their superior olfactory acuity . Their area of olfactory epithelium ( 18 to 150 cm2 ) [16] is much greater than that of humans ( 3 cm2 ) [17] . They are widely used to detect non-biological ( explosives , chemical contaminants , illegal drugs ) and biological scents ( human odours , animal scents ) and have an important role in conservation [18] . Dogs have been trained for search and rescue of missing people [19] , to search for brown tree snakes [20] , insects that damage plants [21] , birds [22] , egg masses of gypsy moths [23] , subterranean termites [24] , screwworm-infested wounds [25] , catfish off-flavour compounds [26] , animal scat detection [27] and microbial organisms such as rot fungi , building moulds , and bacteria [28] . However , as far as we know , there are no previous attempts to train dogs to detect triatomine bugs . Triatominae produce volatile compounds , which seem to play a role in their defense and alarm processes , as well as in sexual communication and mating . The Brindley's glands , present in adult Triatominae , seem mainly to secrete isobutyric acid – believed to be involved in defense against predators [29] , [30] . The metasternal glands , also present in adults , have been associated with sexual communication , and some highly volatile ketones ( 3-pentanone ) and alcohols that are emitted by adults during mating have been identified [29] , [30] . Moreover , the nymphs do not have Brindley's glands , metasternal glands , or dorsal abdominal glands [31] . The bug faeces are also a source of attractants [32] and both adults and nymphs respond to faeces from different species [33]–[37] . The compounds most commonly found in fresh faeces are ammonia and uric acid , and other compounds such as o-aminoacetophenone , 4-methylquinazoline , 2 , 4-dimethylquinazoline , and 2-pyrolidinone [37] , [38] . Based on the possibility of detecting bugs by means of their odours we have implemented a new method in which we use a trained dog to search for triatomines . This has enabled us to find sylvatic T . infestans in the region of the Paraguayan Chaco through a quick , easy and low-cost procedure .
The study in the indigenous communities was approved by the local Ethical Committee of the Fundación Moisés Bertoni ( IDRC Grant No . 103696-009- Revision 07/27/2007 ) and CEDIQUIFA ( Approved 02/18/2008 ) ( Argentina ) . Following local indigenous conventions for the approval of research in their communities , the local leaders of the villages of 12 de Junio and 10 Leguas were informed of the study objectives prior to commencing the study and they signed an informed consent form on behalf of the members of the community . This village-level consent process was approved by both ethics committees . The use and handling of animals in this study was approved by Fundación Moisés Bertoni ( Grant No . 103696-009-Addendum 05/03/2010 ) and the animal care and facilities supporting this activity was maintained according to the standards of the Council for International Organizations of Medical Sciences ( CIOMS , 1985 ) [39] . Within the framework of an entomological surveillance study of indigenous communities , sylvatic triatomines were sought within the peridomicile of the indigenous communities of 12 de Junio and 10 Leguas in the Department of Presidente Hayes ( Figure 1 ) . The surrounding area represents typical xeromorphic Chaco woodland , characterized by species such as Aspidosperma quebracho-blanco , Schinopsis quebrachocolorado , Bulnesia sarmientoi , Prosopis nigra , Schinopsis balansae , Calycophyllum multiflorum y Stetsonia coryne [40] , [41] . The climate in this part of the Chaco is characterized by extreme summer heat and mild winters . Temperature extremes range from 45° C in spring and summer to −7°C in winter . Windspeed averages 3 . 3 meters/second ( 11 . 9 km/h ) that increases up to 3 . 9 m/s ( 14 . 0 km/h ) in winter [42] . For this study geo-referenced points were identified using a GPS ( GARMIN Etrex Legend ) during field trips . Triatomines were manually captured in demarcated areas during daylight hours with the help of NERO , a 9 month-old gray German Shepherd male dog ( Figure 2D ) . NERO had basic obedience training and was further trained to locate triatomines by an experienced dog trainer . The trainer used live , laboratory-reared , uninfected male and female adult bugs throughout the training process . The specimens were placed individually in plastic containers closed with gauze , with paper as a substrate . Training was carried out in the trainer's home using the method outlined by the United States Customs Service [43] . First the living triatomines were presented to the dog to stimulate the dog's olfactory memory before being hidden somewhere in a house , and the dog was told to “search” . After daily training sessions for 3 weeks , the triatomines were no longer presented to the dog at the beginning of the session , and the dog was asked to “search” for hidden bug samples . In the third phase , several samples were hidden around the house simultaneously . The dog's ability to locate different intensities of odor was tested by hiding samples of several bugs at some sites and single bugs at other sites . Tasks with no positive samples were included as well . When the dog found the sample , he would sit at attention next to the sample and look at his trainer . Small pieces of sausage were used as rewards . The training took a total of 3 months . In the field , the dog was accompanied by his trainer and a field team made up of three or four biologists . Every time the dog made the appropriate signal the field team made a thorough revision of the area looking for triatomines . The collection of triatomines was carried out 5 times during the months of May to August 2010 . The place and characteristics where triatomines were found were geo-referenced and noted with the climatic characteristics of the days when captures were carried out . Specimens were placed together in plastic cups with paper as a substrate , coded according to capture sites , and transported live to the laboratory where they were classified by species , sex , and stage following standard taxonomic keys [31] . Faecal matter expressed from each specimen was also checked microscopically at 400× for possible trypanosome infection . Specimens were then preserved in 70% ethanol for subsequent DNA extraction from legs . For DNA extraction , four legs from each specimen were ground to a fine powder in the presence of liquid nitrogen , mixed with 1 mL of lysis buffer , and incubated overnight at 37°C [44] . DNA was extracted sequentially with phenol , phenol-chloroform-isoamyl alcohol , and chloroform-isoamyl alcohol , and precipitated with ethanol in 0 . 3 M sodium acetate [45] . The mitochondrial cytochrome B gene was targeted for amplification as described by Lyman et al [46] and a frangment of 415 bp ( primer regions not included ) with no insertions or deletions was considered in the analysis . PCR products were sequenced directly and in both directions . Sequences from sylvatic bugs were compared with GenBank Triatoma spp . sequences by Blast analysis with Genbank default parameters . To determine if the dog was able to differentiate between nymph and adult triatomines , laboratory-reared 3rd and 5th stage T . infestans were placed in plastic containers and hidden for the dog to search for them . Similarly , two trials were conducted to assess which triatomine odours the dog could detect . In the first , a plastic vial containing a filter paper impregnated with 50 uL of commercial isobutyric acid ( MERCK ) was hidden . The second trial used papers impregnated with fresh or dried faeces from adult and nymph stage T . infestans . Each of these trials was done on two occasions in the trainer's house .
A total of 70 triatomines was collected during 5 field trips with NERO . All specimens were captured alive from vegetation such as dry branches , hollow or standing trees of different species like quebracho blanco ( Aspidosperma quebracho-blanco ) , verawood [better known by its spanish name palo santo] ( Bulnesia sarmientoi ) and dried cactus ( Stetsonia coryne ) . In the case of quebrachos , the bugs were found inside hollow dry branches , while in palo santo they were captured from the cortex . Triatomines were also found in a Tabara major nest in a fallen quebracho blanco tree ( Figure 2A ) , in rodent burrows inside a fallen palo santo tree ( Figure 2B ) and in piles of quebracho blanco branches cut for firewood ( Figure 2C ) . The house nearest to capture sites was located 408 meters from the town of 10 Leguas , while the distances from capture sites to the nearest community averaged 2 . 8±1 km ( Figure 1 ) . Of the 70 bugs collected , 22 specimens ( 16 adults and 6 nymphs ) corresponded to dark morph ( DM ) forms of T . infestans ( Table 1 ) . Purified DNA from 14 of these successfully amplified the target cyt-b fragment , resulting in two haplotypes that differed in 4 synonymous substitutions . The Blast analysis with sequences available in GenBank confirmed them as T . infestans . One of the haplotypes presented 100% similarity to already published sequences ( accession numbers AY062165 . 1 and EF639038 . 1 ) . The other haplotype is now deposited in Genbank under accession number HQ848648 . The remaining bugs comprised 18 specimens of Triatoma guasayana , and 30 specimens of Triatoma sordida ( Table 2 ) . There was a predominance of T . sordida in relation to T . infestans , and although both species were found in the same period of time they were never found sharing the same habitat . None of the specimens of any species examined under the microscope appeared to be infected with trypanosomes . Following the discovery of triatomine colonies in the forested areas of the Chaco we attempted further trials to see if the dog was capable of identifying nymphs and adults independently , and what specific scent the dog was detecting . The dog was exposed to nymphs , fresh and dry bug faeces , and isobutyric acid , in independent experiments . The dog consistently marked the location of the nymphs , but did not find the fresh or dry faeces on any occassion . When the dog was exposed to a flask containing isobutyric acid the dog was able to locate the flask , but did not clearly indicate the location as when finding a live triatomine bug .
DNA sequence of 660 bp of the new haplotype including the cytochrome B gene was deposited in GenBank under accession number HQ848648 . This sequence was obtained using the primers described by Monteiro et al [58] .
|
Confirmation of sylvatic colonies of Triatoma infestans has a significant connotation for Paraguay . Prior to our findings , we believed this vector —unlike in other regions of the Gran Chaco—was living exclusively in domestic and peridomestic habitats . We never considered the possibility of sylvatic species re-infesting domiciliary dwellings . After this discovery , the frame of transmission dynamics of Trypanosoma cruzi in the Paraguayan Chaco proposes new research perspectives . This also opens the door to promote knowledge regarding potential genetic flows between different T . infestans populations , reservoirs associated with their colonies , as well as their impact over control actions . Fieldwork for wild species identification is difficult and often unsuccessful , we used several techniques and tools , proven by others such as light traps , and mouse-baited sticky traps however , the triatomine collection in our study area was scarce or null . Incorporating a trained dog – NERO – to our work team has been a highly successful and productive initiative . The surprising ability NERO has shown will enable us to provide specific data regarding the still unknown wild ecotopes of T . infestans , as well as the potential use of trained dogs as a community surveillance tool of triatomine species considered particularly important for public health .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"community",
"ecology",
"zoology",
"ecology",
"entomology",
"biology",
"species",
"interactions",
"biodiversity",
"parasitology"
] |
2011
|
First Report of Colonies of Sylvatic Triatoma infestans (Hemiptera: Reduviidae) in the Paraguayan Chaco, Using a Trained Dog
|
Clinical manifestations in onchocerciasis range from generalized onchocerciasis ( GEO ) to the rare but severe hyperreactive ( HO ) /sowda form . Since disease pathogenesis is associated with host inflammatory reactions , we investigated whether Th17 responses could be related to aggravated pathology in HO . Using flow cytometry , filarial-specific cytokine responses and PCR arrays , we compared the immune cell profiles , including Th subsets , in individuals presenting the two polar forms of infection and endemic normals ( EN ) . In addition to elevated frequencies of memory CD4+ T cells , individuals with HO showed accentuated Th17 and Th2 profiles but decreased CD4+CD25hiFoxp3+ regulatory T cells . These profiles included increased IL-17A+ , IL-4+ , RORC2+ and GATA3+CD4+ T cell populations . Flow cytometry data was further confirmed using a PCR array since Th17-related genes ( IL-17 family members , IL-6 , IL-1β and IL-22 ) and Th2-related ( IL-4 , IL-13 , STAT6 ) genes were all significantly up-regulated in HO individuals . In addition , stronger Onchocerca volvulus-specific Th2 responses , especially IL-13 , were observed in vitro in hyperreactive individuals when compared to GEO or EN groups . This study provides initial evidence that elevated frequencies of Th17 and Th2 cells form part of the immune network instigating the development of severe onchocerciasis .
Onchocerciasis is a neglected tropical disease causing both health and socioeconomic problems [1] . Elicited by the parasitic nematode Onchocerca volvulus ( Ov ) , it is transmitted through the bite of infected black flies ( genus Simulium ) . Characteristic disease symptoms include dermatological disorders and eye lesions that can lead to blindness [2] . Two polar forms of clinical manifestations can occur: generalized onchocerciasis ( GEO ) presenting mild skin disease or the hyperreactive form ( HO ) exhibiting severe skin inflammation ( also called sowda if inflammation is unilaterally predominant ) [3]–[5] . Although 99% of infected people live in Africa , small pockets of endemicity can be found in Yemen and Central and Southern America [2] . Over 37 million people are currently infected and within those , around 1% develop HO [6] . In endemic areas , putative immune individuals or endemic normals ( EN ) are persons , who despite permanent exposure to the parasite , remain without infection or clinical signs of disease [4] , [5] . Variations in host immune responsiveness include a spectrum of clinical manifestations ranging from i ) GEO individuals with high parasite loads , mild pathology but strong regulatory responses to ii ) HO individuals presenting few worms but varying degrees of dermal pathology ( acute and chronic papular onchodermatitis , leopard skin , and depigmentation ) ; the term “sowda” is reserved for unilateral , extreme hyperreactivity [3]–[6] . Onchocerca are long-living and are renowned for modulating host immune regulatory mechanisms [3] , [5] , [6] , [7] . Adult female worms encase themselves in so called onchocercomas in the skin that are composed of various cell types [5] , [6] , [8] , [9] . CD4+ T cells have been reported to be the predominant IL-10 secreting cells in onchocerciasis [10] . However , due to the infrequency of HO cases , few studies have addressed the types of cytokine secreting Th subsets or cellular immune profiles in these individuals . Since Th17 cells have been associated with helminth-induced overt pathology [11] , [12] we determined here whether they are active in HO individuals . When compared to GEO and EN groups , HO individuals presented elevated Th17 and Th2 profiles which were accompanied by reduced numbers of Foxp3+ regulatory T cells ( Treg ) . Upon PCR array analysis , Th17 and Th2-related genes were also up-regulated in HO patients . These data suggest that preventing the development of HO should focus on tipping the Treg/Th17 balance towards a more regulated response .
In 2011 , adult O . volvulus-infected male and female ( 21–55 years ) individuals from an endemic region in Ghana were recruited within the study: "Enhanced Protective Immunity Against Filariasis ( EPIAF ) " , ( http://www . filaria . eu/projects/projects/epiaf . html ) . Ethical clearance was given by the Committee on Human Research Publication and Ethics at the University of Science and Technology in Kumasi , and the Ethics Committee at the University Hospital Bonn . For comparison , samples were collected from 16 mixed gender infection-free volunteers ( 27–55 years ) that had resided in the same area for at least 10 years ( EN ) . These individuals were negative for MF , had no palpable onchocercomas , and had no pathology related to onchocerciasis . Written informed consent was obtained from all individuals . All infected individuals presented at least one nodule and/or skin lesions and were screened for the presence of dermal microfilariae ( MF/mg skin ) as previously described [13] , [14] , [15] . Infections with other intestinal helminths ( schistosomes , ascaris ) and protozoa ( Plasmodium ) were diagnosed using standard methods ( Kato-Katz , finger prick and urine analysis ) and all individuals donating samples for this study were free of such infections . A soluble antigen extract from O . volvulus adult worms ( OvAg ) was prepared as previously described [15] . In preceding experiments , thawed PBMCs from infected individuals were cultured with the antigen over 7 days to determine the optimal time-point for cytokine measurement ( S1A-D Fig . ) . PBMCs isolation was performed as previously described [15] and followed by cryo-preservation in liquid nitrogen until required [16] . PBMCs were thawed slowly ( 37°C ) and then washed with RPMI 1640 medium supplemented with 10% FCS , gentamycin , penicillin/streptomycin ( 50 µg/ml ) and L-glutamine ( 292 . 3 µg/ml ) , all from PAA ( Linz , Austria ) . In 96-well plates , 1×105 PBMCs/well were left unstimulated or stimulated with OvAg ( 20 µg/ml ) or αCD3/αCD28microbeads ( 40 , 000 beads/ml , Dynal/Invitrogen , Carlsbad , USA ) in duplicate for 7 days . Cytokine levels were measured from pooled supernatants using a human FlowCytomix Multiplex Th1/Th2/Th9/Th17/Th22 13-plex kit ( eBioscience , San Diego , CA , USA ) . Data were acquired on a FACS Canto flow cytometer ( BD Biosciences , Heidelberg , Germany ) and analyzed using FlowCytomix Pro3 . 0 software ( eBioscience ) . All reagents were obtained from eBioscience and staining was done as previously described [17] . 1×105 cells/100 µl staining buffer were incubated for 30 mins ( 4°C ) with either 1 ) anti-human CD3-PerCP-Cy5 . 5 , CD16-FITC ( clone CB16 ) and CD56-PE PE ( clone CMSSB ) ; 2 ) anti-human CD4-APC ( clone OKT4 ) , anti-CD45RO-FITC ( clone UCHL1 ) and CD45RA-PerCP-Cy5 . 5 ( clone HI100 ) ; 3 ) CD8-APC ( clone SK1 ) and CD14-FITC ( clone 61D3 ) or 4 ) CD19-APC ( clone HIB19 ) and CD27-FITC ( clone LG7F9 ) . For intracellular staining , cells were activated with a Cells Stimulation Cocktail ( phorbol 12-myristate 13-acetate {PMA} and Ionomycin ) plus Brefeldin A and monensin ( eBioscience ) for 6 hours . Thereafter , cells were stained with anti-CD4-APC and to assess Treg levels , anti-human CD25-PECy7 ( clone BC96 ) was added as well . After employing Fix-Perm reagent ( eBioscience ) , cells were blocked with normal rat serum and then incubated for 30 mins ( 4°C ) with either 1 ) anti-human T-bet-PE ( clone eBio4B10 ) and IFN-γ-FITC ( clone 4S . B3 ) ; 2 ) GATA3-PE ( clone TWAJ ) and IL-4-FITC ( clone B-S4 ) 3 ) RORC2-PE ( clone AFKJS-9 ) and IL-17A-FITC ( clone eBio64DEC17 ) or 4 ) Foxp3-FITC ( clone 236A/E7 ) and IL-10-PE ( clone JES3-9D7 ) . After further washing cells were re-suspended in fix-perm buffer ( eBioscience ) . To correct spectral overlap , fluorescence compensation was done using UltraComp ebeads ( eBioscience ) . Data were acquired and analyzed using a FACS Canto flow cytometer and software ( BD Biosciences ) . Gene expression profiles were quantified using the Human Th17 autoimmunity and inflammation PCR array and RT2SYBR Green Mastermix kit ( Qiagen , Hilden , Germany ) according to protocol . In short , PBMCs were stimulated with αCD3/αCD28 microbeads for 3 hours and RNA was extracted using Trizol ( Invitrogen ) . DNA was digested using the DNA-free kit ( Invitrogen ) and the concentration and the purity of RNA was determined using the NanoDrop 1000 ( Peqlab , Erlangen , Germany ) . Extracted RNA was reverse transcribed using Qiagen Master mix ( Qiagen , ) and incubated in the Primus Thermocycler ( MWG-Biotech , Ebersberg , Germany ) . Amplification was performed on the RotorGene 6000 ( Corbett Research , Sydney , Australia ) . Data were analyzed by RT2 profiler PCR Array data analysis 3 . 5 software ( Qiagen ) . Statistical analyses were performed using PRISM 5 programme ( GraphPad Software , Inc . , La Jolla , USA ) . Since most of the variables did not show a normal distribution , the following tests were chosen: to compare three groups a Kruskal-Wallis-test was performed and , if significant , followed by a Mann-Whitney–U test for a further comparison of the groups . P-values of 0 . 05 or less were considered significant .
To distinguish differences in the immune cell profiles of individuals with onchocerciasis , we analyzed PBMCs for the frequency of innate and adaptive cell populations . Individuals with GEO had significantly less CD8+ T cells when compared to EN ( Fig . 1A ) . When compared to levels in EN , both CD16brightCD56dim and CD16dimCD56brightNK populations were significantly lower in GEO and HO individuals but no differences could be observed between infected groups ( Fig . 1B and C ) . CD3+CD16+ but not CD3+CD56+NKT cells were also lower in GEO but not HO individuals ( Fig . 1D and 1E ) . Whereas no differences could be observed in the frequency of memory B cells ( Fig . 1F ) , significantly elevated numbers of monocytes ( CD14+ cells ) were identified in HO individuals ( Fig . 1G ) . When compared to GEO and EN groups , HO individuals displayed higher amounts of memory CD4+CD45RO+ ( Fig . 1H ) but significantly less naive T cells ( Fig . 1I ) . These data were also reflected when calculated on absolute cell numbers . Next , we determined the frequency of cytokine producing CD4+ T cells . CD4+IFN-γ+ T cells were significantly higher in EN when compared to either infected group ( Fig . 2A ) . However , CD4+ T cells from GEO individuals did produce more IFN-γ than cells from HO individuals ( Fig . 2A ) . In contrast , infected groups displayed significantly elevated frequencies of IL-4-secreting CD4+ T cells when compared to EN groups ( Fig . 2B ) . Moreover , T cells from HO individuals produced more IL-4 than cells from GEO persons ( Fig . 2B ) . Whereas IL-17A-producing CD4+ T cells appeared to be a unique characteristic in HO individuals ( Fig . 2C ) , those with GEO had a dominant IL-10 phenotype ( Fig . 2D ) . In association with their elevated numbers of IFN-γ-producing CD4+ T cells ( Fig . 2A ) , EN had significantly higher frequencies of CD4+T-bet+ T cells when compared to HO individuals ( Fig . 3A ) . Strikingly , the Treg associated transcription factor Foxp3 was strongly expressed by CD4+ T cells from hyperreactive individuals , even when compared to GEO individuals ( Fig . 3B ) . Therefore , we expanded our profile panel to include CD25hi expressing CD4+ T cells using a previously described protocol and gating strategy [17] , [18] . Interestingly , the inclusion of CD25hi cells dramatically changed the profile of CD4+ regulatory T cell profile in HO individuals since both CD4+CD25hi ( Fig . 3C ) and CD4+CD25hiFoxp3+ ( Fig . 3D ) subsets were higher in GEO individuals . This suggests the presence of Foxp3+ effector CD4+ T cells in persons with HO . Correlating with the elevated IL-4 and IL-17 cytokine expression , CD4+ T cells from HO individuals had significantly higher levels of both GATA3 ( Fig . 4A ) and RORC2 ( Fig . 4B ) transcription factors . In addition , the ratio of CD4+IL-17A+/CD4+IL-4+ T cells was higher in individuals with HO ( Fig . 4C ) when compared to the GEO group . This trend remained when comparing the ratio CD4+RORC2+/CD4+CD25hiFoxp3+ in HO individuals with both GEO and EN groups ( Fig . 4D ) . Using a Th17-based PCR array , we compared expression levels of Th17 , Th2 and Treg related genes in GEO and HO individuals . As shown in Fig . 4E , IL-17 associated genes , such as IL17A , IL17C , IL17D , IL17F , RORC and STAT3 , were all up-regulated in cells from HO individuals . The genes of cytokines known to be required for the induction of Th17 cells such as IL-6 , IL-1β , TGF-β1 , IL-21 and IL-23A [19] , [20] and the IL22 gene were also highly up-regulated in HO persons ( Fig . 4F ) . With regards to Th2-related genes and the Treg-associated foxp3 expression , the IL13 gene presented the strongest fold increase and correlated to the elevated gene expression of GATA3 and STAT6 ( Fig . 4G ) . In correlation with elevated amounts of CD4+Foxp3+ cells in HO individuals , foxp3 gene expression in these patients was also upregulated ( Fig . 4G ) . To measure filarial-specific responses from cyro-preserved PBMCs , cells were cultured with OvAg for 7 days: the optimal time-point for cytokine production ( S1A-D Fig . ) . When compared to EN or GEO groups , PBMCs from HO individuals secreted significantly more IL-5 and IL-13 when activated with either OvAg or αCD3/αCD28 ( Fig . 5A-D ) . Cultures from all groups produced little IL-10 in response to OvAg ( Fig . 5E ) , although infected individuals did produce more IL-10 than control cultures upon activation with αCD3/αCD28 ( Fig . 5F ) . Cultures from EN secreted significantly more IFN-γ upon activation with OvAg ( Fig . 5G ) which correlates with their CD4+ T cell cytokine profile shown in Fig . 2A . The dampened IFN-γ responses from cells of HO individuals was not reflected upon αCD3/αCD28 activation indicating that failure to produce IFN-γ was not a deficit of Th1 cells but dampened filarial-specific IFN-γ-producing cells ( Fig . 5H ) . The induction of Th17 cells requires IL-6 , IL-1β , TGF-β and IL-23 [19] . In contrast to the high amounts of IL-17A secreting CD4+ T cells observed by flow cytometry ( Fig . 2C ) , upon culturing with OvAg , only low levels of IL-17A were detected in the culture supernatants in the HO group . Nevertheless , the basal levels of IL-17A were significantly higher than the basal levels in culture supernatants from the GEO group ( Fig . 6A ) . Upon activation with αCD3/αCD28 however , cells from HO individuals presented significantly higher levels of IL-17A when compared to both EN and GEO group ( Fig . 6B ) , reflecting again the findings via flow cytometry ( Fig . 2C ) . IL-6 levels from cultures of PBMCs from HO individuals were significantly higher than the other groups ( Fig . 6C and D ) . As with IL-17A , no significant differences in the levels of IL-22 or IL-1β following stimulation with OvAg were observed ( Fig . 6E and G respectively ) . However , after activation with αCD3/αCD28 , PBMCs cultures from HO individuals secreted elevated amounts of IL-22 and IL-1β when compared to EN and GEO groups ( Fig . 6F and H respectively ) . Thus , although the overall filarial-specific Th17-related responses were not highly significant in hyperreactive individuals , these cytokines were enhanced upon αCD3/αCD28 activation indicating a biased Th17 inflammatory profile .
Cases of HO are infrequent ( probably 1% of the infected population ) and the underlying etiology has only partially been elucidated [4] , [5] , [6] . After comparing cellular immune profiles we have determined that an accentuated Th17/Th2 phenotype forms part of the immune network which drives the development of hyperreactive onchocerciasis . Th1 cells do not contribute to this stage of pathogenesis since T-bet+ and IFN-γ producing CD4+ T cells in HO individuals were significantly lower when compared to EN . Indeed , both CD4+IFN-γ+ T cells and IFN-γ levels released following OvAg stimulation by PBMCs were significantly higher in the EN group . The association of IFN-γ and putative immunity in endemic-residing individuals has been demonstrated in studies investigating reactions to L3 larvae [21] . Cooper et al . further demonstrated that early exposure to infection elicited elevated IFN-γ responses to OvAg but not L3 larvae [22] . Since recent reports have suggested that Wolbachia , the endosymbiotic bacteria in O . volvulus , are the principal activator of innate and Th1 inflammatory immunity [4] , these responses may stem from exposure to worms and/or bacteria . Previous studies have noted that HO individuals present elevated numbers of peripheral leucocytes including eosinophils but not neutrophils [23] , [24] . Brattig et al . [23] also found no differences in CD19+ B cells and expanding on those findings we observed no alterations in memory B cells either . Interestingly , GEO individuals presented reduced numbers of CD8+ T cells , NK and NKT cells . Since these individuals have higher worm burdens there is likely elevated amounts of helminth-derived glycolipids and glycoproteins , which may lead to migration of NK and NKT cells into the skin , resulting in decreased numbers in blood . In contrast to O . volvulus-infected individuals , EN presented elevated CD16brightCD56dim and CD16dimCD56bright NK cells . The role of NK cells during filariasis is not well defined although studies with the murine model , Litomosoides sigmodontis , showed that depletion of NK cells enhanced worm load and Th2 responses [25] . Previous in vitro investigations using PBMCs from healthy individuals demonstrated that NK activation and consequential apoptosis resulted from contact with IL-12-producing monocytes after stimulation with filarial antigens [26] . Therefore , the observed increase of monocytes in HO individuals could be initiated by a ) an elevated requirement of phagocytosis due to increased apoptotic material , b ) increased stimulation due to dying or dead filariae or c ) simply elevated APC requirement due to hyperreactivity . An increased requirement for antigen presentation in HO individuals would correlate with their elevated levels of memory CD4+ T cells , an immunological difference not previously reported between the two polar versions of O . volvulus infection . In association , CD45RO+ cells have been observed in nodules from sowda individuals via immunohistochemistry [27] . Alongside the immunohistochemical observations of Foxp3+ and TGF-β+ cells in nodules of GEO but not HO individuals [8] , [9] , our current data substantiates the known regulatory phenotype in GEO persons . Indeed , we show that GEO individuals have higher frequencies of CD4+IL-10-producing T cells which further correlates with studies demonstrating IL-10-secreting Tr1 cells cloned from tissue surrounding the onchocercomas [28] . Moreover , CD4+ T cells have been shown to be the largest producers of IL-10 in O . volvulus-infected individuals via flow cytometry and although nearly a fifth of those cells further secreted IL-4 hardly any produced IFN-γ [10] . It will be interesting to investigate multifunctional Th17 cells in onchocerciasis , especially HO individuals . Surprisingly , the number of CD4+Foxp3+ T cells were elevated in HO individuals and following PCR array analysis we also observed higher gene expression levels of foxp3 in this group without mitogen stimulation . However , upon analysis of the classical Treg phenotype ( CD4+CD25hiFoxp3+ ) , we confirmed that GEO patients have higher numbers of this regulatory T cell population . Although mitogen stimulation during the flow cytometry process could have boasted Foxp3 levels in T cells per se , future studies will be required to investigate whether these CD4+Foxp3+ T cells in the HO individuals have any functional relevance or simply reflects the hyperresponsive profile in these patients [5] , [29] . A major new finding in this present study is the dominant Th17/Th2 phenotype in HO individuals . Indeed , comparing the cytokine profiles of activated PBMCs from infected individuals revealed that HO patients secreted higher amounts of IL-5 and IL-13 but not IL-10 . Such observations were further confirmed via PCR arrays since Th2 genes , especially IL-13 , were up-regulated in HO individuals . This correlates to studies showing an increased likelihood for developing sowda in persons carrying the Arg110 variant of IL-13 which leads to higher IL-13 signalling [30] . Th2 responses in filarial infections are linked to infection resistance [31] , [32] and microfilariae can elicit pro-inflammatory responses when they are degenerated or moribund [33] . Thus , a potential scenario for developing hyperresponsiveness may be that deviated Th2 responses provoke microfilariae death , which in turn induces a Th17 phenotype . It will be interesting to investigate in the future whether such elevated Th17 responses are induced by microfilariae-derived antigen preparations or recombinant microfilarial proteins . In the study performed here , CD4+IL-17A-secreting T cells were 4 times higher in HO individuals and this dominant Th17 phenotype was further confirmed by the higher expression of RORC2 at both the protein and mRNA level . Interestingly , the pronounced IL-17A phenotype was further observed upon TCR activation and the basal level of this cytokine was significantly higher in culture supernatants from PBMCs of HO individuals when compared to the GEO group . Th17 cells are promoted by the inhibition of Foxp3 by IL-6 and elevated TGF-β and IL-1β responses . IL-1β , especially in synergy with IL-23 , plays an essential role in the induction and expansion of Th17 cells [34] . In the PCR array , all essential Th17-related genes were up-regulated in HO individuals including IL-22 , IL-23A , IL-21 , RORC2 and STAT3 genes . Although other genes such as IL-6 and IL-1β were also up-regulated in HO individuals , further investigations would be required to ascertain whether they have other functions than just the induction of Th17 responses . From the 84 analysed genes , 16 were down-regulated in the HO patients and included CCR4 , TLR4 , the IL-7R and members of the IL-12 family . Interestingly , since environments which enhance IL-7/IL-7R signalling favour alloreactive and autoreactive T cells expansion due to Treg inhibition [35] , this would fit to the diminished Treg ( CD4+CD25hiFoxp3+ ) numbers in the HO group . A protective role of Th2 cytokines elicited during helminth infection , especially in regards to mediating milder forms of pathology , is well established [36] . Recent studies have reported relevant associations between pathology and Th17 characteristics [37] . For example , IL-17A producing cells have been shown to play a significant role in allergic rhinitis [38] , allergic contact dermatitis [39] and other immunoinflammatory disorders including psoriatic arthritis , multiple sclerosis and asthma [37] , [40] , [41] . Indeed , with regards to the latter , strong Th17/Th2 immune responses during allergic asthma result in different clinical manifestations [41] . The relationship between pathology and Th17 cells has been extensively studied in murine schistosome models and revealed that Th17 cells instigated the development of aggravated egg-induced pathology in schistosomiasis [42] . Indeed , the more pronounced granulomatous inflammation in Schistosome japonicum infections , was ameliorated upon neutralization of IL-17 in vivo [43] . Interestingly , co-infection of S . mansoni with the nematode Heligmosomoides polygyrus in CBA mice , that develop severe immunopathology , reduced granuloma development and diverted the dominant IL-17 and IFN-γ granuloma-secreting phenotype into one producing Th2-related cytokines instead [44] . The mechanisms behind this modulatory capacity of H . polygyrus requires further investigation but it has been suggested that it might lie in changes to the gut microbiota [45] . In lymphatic filariasis ( LF ) , increased Th17 responses have been observed in individuals with chronic lymphoedema and are prominent in patients who have cleared bloodstream microfilariae [38] . This raises the question therefore whether microfilariae normally down-regulate Th17 responses to extend their survival . A recent study on Schistosoma haematobium-infected individuals has also revealed an association between Th17 responses and enhanced pathology [12] . Nevertheless , despite the association of pathology and Th17 cells our findings in O . volvulus-infected individuals differ from those studies in two regards: 1 ) Patients presenting filarial lymphoedema , had elevated Th1 and Th17 but not Th2 responses following filarial-specific re-stimulation and had no alterations in the amount of secreted IL-10 either [11] . 2 ) In the study using S . haematobium-infected children [12] , Treg frequencies were equal amongst the infected and control groups whereas in the HO cohort studied here , individuals had reduced numbers of IL-10+CD4+ and CD25hiFoxp3+CD4+ Treg when compared to the GEO group . Indeed when investigating the Th17/Treg balance , the ratio of CD4+IL-17A+/CD4+IL-10+ and CD4+RORC2/CD4+CD25hiFoxp3+ was higher in the HO group suggesting prominent Th17 responses in HO persons and dominant Treg in GEO individuals . Thus , although Th17 cells appear to be a common denominator in helminth-infected individuals displaying severe pathology , each type of infection appears to have created its own subtle collaboration of immune parameters such as Treg or IL-10 . Indeed , we show here that the Th17 milieu in individuals with HO is uniquely linked to elevated Th2 responses as well .
|
Onchocerciasis , also known as river blindness is a tropical disease causing health and socioeconomic problems in endemic communities especially sub-Saharan Africa . The disease is transmitted by a filarial nematode called Onchocerca volvulus , which is spread by the bite of infected Simulium black flies . Characteristic disease symptoms include dermatological disorders and eye lesions that can lead to blindness . Two polar forms of clinical manifestations can occur: generalized onchocerciasis ( GEO ) presenting mild skin disease or the hyperreactive form ( HO ) exhibiting severe skin disorders and inflammation . The immunological determinants behind such disease polarization are still not fully clarified . Here , we compared the immune profiles of individuals presenting these two polar forms with those of endemic normals ( EN ) : individuals who have no clinical or parasitological evidence of infection despite ongoing exposure to the infectious agent . We could show that HO individuals , in contrast to GEO and EN , simultaneously presented elevated Th17 and Th2 profiles which were accompanied by reduced numbers of Foxp3+ regulatory T cells . This study provides initial evidence that elevated frequencies of Th17 and Th2 cells form part of the immune network associated with severe onchocerciasis .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"biology",
"and",
"life",
"sciences",
"immunology",
"tropical",
"diseases",
"parasitic",
"diseases"
] |
2015
|
Hyperreactive Onchocerciasis is Characterized by a Combination of Th17-Th2 Immune Responses and Reduced Regulatory T Cells
|
The human gene encoding the cleavage/polyadenylation ( C/P ) factor CstF-77 contains 21 exons . However , intron 3 ( In3 ) accounts for nearly half of the gene region , and contains a C/P site ( pA ) with medium strength , leading to short mRNA isoforms with no apparent protein products . This intron contains a weak 5′ splice site ( 5′SS ) , opposite to the general trend for large introns in the human genome . Importantly , the intron size and strengths of 5′SS and pA are all highly conserved across vertebrates , and perturbation of these parameters drastically alters intronic C/P . We found that the usage of In3 pA is responsive to the expression level of CstF-77 as well as several other C/P factors , indicating it attenuates the expression of CstF-77 via a negative feedback mechanism . Significantly , intronic C/P of CstF-77 pre-mRNA correlates with global 3′UTR length across cells and tissues . In addition , inhibition of U1 snRNP also leads to regulation of the usage of In3 pA , suggesting that the C/P activity in the cell can be cross-regulated by splicing , leading to coordination between these two processes . Importantly , perturbation of CstF-77 expression leads to widespread alternative cleavage and polyadenylation ( APA ) and disturbance of cell proliferation and differentiation . Thus , the conserved intronic pA of the CstF-77 gene may function as a sensor for cellular C/P and splicing activities , controlling the homeostasis of CstF-77 and C/P activity and impacting cell proliferation and differentiation .
Pre-mRNA cleavage/polyadenylation ( C/P ) is a 3′ end processing mechanism employed by almost all protein-coding genes in eukaryotes [1] , [2] . The site for C/P , commonly known as the polyA site or pA , is typically defined by both upstream and downstream cis elements [3] , [4] . In metazoans , upstream elements include the polyadenylation signal ( PAS ) , such as AAUAAA , AUUAAA , or close variants , located within ∼40 nucleotides ( nt ) from the pA; the UGUA element [5] , typically located upstream of the PAS; and U-rich elements located around the PAS . Downstream elements include the U-rich and GU-rich elements , which are typically located within ∼100 nt downstream of the pA . Most mammalian genes express alternative cleavage and polyadenylation ( APA ) isoforms [6] , [7] . While the majority of alternative pAs are located in the 3′-most exon , leading to regulation of 3′ untranslated regions ( 3′UTRs ) , about half of the genes have pAs located in introns [8] , leading to changes in coding sequences ( CDSs ) and 3′UTRs . Intronic pAs can be classified into two groups depending upon the splicing structure of the resultant terminal exon: composite terminal exon pA or skipped terminal exon pA . A composite terminal exon pA is located in a terminal exon which contains both exon and intron sequences . In this case , a 5′ splice site ( 5′SS ) is located upstream of the pA . A skipped terminal exon pA is located in a terminal exon which can be entirely skipped in splicing . We previously found that composite terminal exon pAs in the human genome are typically located in large introns with weak 5′SS [9] . A classic model of composite terminal exon pA is the intronic pA of the immunoglobulin heavy chain M ( IgM ) gene [10] . IgM mRNAs switch from using a 3′-most exon pA to an intronic pA during activation of B cells , which results in a shift in protein production from a membrane-bound form to a secreted form . In mammalian cells , over 20 proteins are directly involved in C/P [1] , [11] . Some proteins form complexes , including the Cleavage and Polyadenylation Specificity Factor ( CPSF ) , containing CPSF-160 , CPSF-100 , CPSF-73 , CPSF-30 , hFip1 , and Wdr33; the Cleavage stimulation Factor ( CstF ) , containing CstF-77 , CstF-64 , and CstF-50; Cleavage Factor I ( CFI ) , containing CFI-68 or CFI-59 and CFI-25; and Cleavage Factor II ( CFII ) , containing Pcf11 and Clp1 . Single proteins involved in C/P include Symplekin , poly ( A ) polymerase ( PAP ) , nuclear poly ( A ) binding protein ( PABPN ) , and RNA Polymerase II ( RNAPII ) . In addition , RBBP6 , PP1α , PP1β are homologous to yeast C/P factors [12] , whose functions in 3′ end processing are yet to be established in mammalian cells . CstF-77 has been shown to interact with several proteins in the C/P complex , such as CstF-64 and CstF-50 in CstF [13] , [14] , [15] , [16] , CPSF-160 [17] , and the carboxyl ( C ) -terminal domain ( CTD ) of RNAPII [18] . CstF-77 can dimerize through the second half of its amino ( N ) -terminal 12 HAT domains [15] , [16] , which is also responsible for dimerization of the CstF complex . Therefore , the role of CstF-77 in 3′ end processing appears to be bridging and/or positioning various factors for C/P . While CstF-77 has not been extensively studied in mammalian cells , its homolog in Drosophila , suppressor of forked or su ( f ) , has been associated with a number of functions . First , su ( f ) regulates 3′ end processing of transposable elements , impacting their effects on cellular genes [14] , [19] , [20]; Second , su ( f ) regulates the usage of an intronic pA of its own pre-mRNA , creating an autoregulatory mechanism [21]; Third , su ( f ) is more expressed in mitotically active cells , which was suggested to be attributable to weak autoregulation in dividing cells compared to non-dividing ones [22] , and the su ( f ) mutant strain showed a defect in cell proliferation [23] . However , not all parts of su ( f ) can be replaced by human CstF-77 for functional complementation , indicating structural and functional differences between these two proteins [24] . We previously identified a conserved pA in intron 3 ( In3 ) of the human CstF-77 gene [25] . Here , we analyze the function of In3 pA and the significance of its flanking splicing and C/P features . We elucidate how In3 pA usage is related to global 3′UTR regulation across cells and tissues , and how In3 pA is regulated by C/P and splicing activities . We demonstrate that perturbation of CstF-77 expression leads to widespread APA and disturbance of cell proliferation and differentiation .
We previously found that vertebrate genes encoding the C/P factor CstF-77 contain a conserved intronic pA ( Figure S1 ) [25] . To elucidate the function of this pA , we first focused on the human CstF-77 gene ( CSTF3 ) , which has 21 exons ( Figure 1A ) with the conserved intronic pA located in intron 3 ( In3 ) . Remarkably , the 5′ portion of the gene before exon 4 accounts for 69% of the gene region . Both introns 1 and 3 are very large , with intron 3 ( 33 . 2 kb ) being larger than 96% of all introns in the human genome and accounting for 43% of the gene region , whereas intron 2 is small , below 8% of all introns in the genome ( Figure 1B , left panel ) . In addition , introns 1–3 are highly conserved in size across vertebrate CstF-77 genes , both in absolute and relative values ( Figure S2A ) , suggesting functional relevance . Using the maximum entropy ( MaxEnt ) method to examine splice site strength [26] , we found that the 5′ splice site ( 5′SS ) of intron 3 is very weak , at the 0 . 7th-percentile of all introns in the human genome ( Figure 1B , middle panel ) , whereas the 3′SS of intron 3 is very strong , at the 94 . 3th-percentile of all human introns ( Figure 1B , right panel ) . Notably , using PhastCons scores [27] , we found that the surrounding sequences of the 5′SS and intronic pA are much more conserved than those of other 5′SSs and pAs , respectively , in the human genome ( Figure S2B ) . By contrast , conservation of sequence around the 3′SS is modest ( Figure S2B ) . We next examined how unique is the combination of large intron , weak 5′SS and strong 3′SS in the human genome . Since splicing in higher species is typically governed by the exon-definition model [28] , we also included 3′SS of exon 3 and 5′SS of exon 4 in the analysis ( Figure 1C ) . Using the intron density map ( see Materials and Methods for detail ) to simultaneously interrogate intron size and 5′SS or 3′SS strength ( Figures 1D and 1E ) , we found that large introns in the human genome in general are flanked by strong 5′SS and 3′SS of both upstream and downstream exons , as indicated by enrichment of introns with these features relative to introns with randomized size and 5′SS or 3′SS strengths ( shown as observed ( Obs ) /expected ( Exp ) ) . This trend holds for intron 3 of CSTF3 except for its 5′SS . Indeed , the combination of large intron with weak 5′SS is significantly depleted in the human genome ( Figure 1D ) . Therefore , the combination of large size and weak 5′SS of intron 3 is rather unique for human introns . To examine the significance of various features surrounding In3 pA of CSTF3 , we constructed reporter plasmids ( called pRinG-77S ) containing an intron using the 5′SS and 3′SS of intron 3 ( Figure 2A ) . The 5′ region also contained the In3 pA , which can lead to a short , intronic pA isoform ( isoform P ) encoding the red fluorescence protein ( RFP ) . If the intronic pA is not used , a long , splicing isoform ( isoform S ) is expressed , which encodes both RFP and enhanced green fluorescence protein ( EGFP ) ( Figure 2A ) . To examine the importance of intron size , we cloned 3′ regions of intron 3 with various sizes . As the insert size increased , the amount of intronic pA product also increased ( Figure 2B ) . A linear correlation between the ratio of isoform P to isoform S ( log2 ) , representing the intronic pA usage , and the insert size can be discerned for inserts from 401–1 , 690 nt . However , the ratio did not change when the insert size was increased to 2 , 378 nt . This regulation of intronic pA usage is due to the change of intron size rather than the distance between the intronic pA and the SV40 pA at the 3′ end of reporter gene , because no significant difference could be discerned when we expanded the region after 3′SS by adding another EGFP sequence ( Figure S3A ) . In addition , a linear decrease of intronic pA usage was also observed when the distance between 5′SS and pA was expanded by random sequences ( Figure S3B ) . Taken together , these data indicate that there is a kinetic competition between C/P and splicing in the usage of In3 pA . Several cis elements around In3 pA are highly conserved across vertebrates , including the upstream UGUA and AUUAAA elements and downstream U-rich and GU-rich elements ( Figure S1 ) . To examine the contributions of these cis elements to the pA strength , we mutated AUUAAA to AAUAAA , a stronger C/P signal [29] , and/or deleted the downstream GU-rich elements . We found that mutation of AUUAAA to AAUAAA led to an ∼2-fold increase in pA usage , whereas deletion of the GU-rich elements led to an ∼10-fold decrease ( Figure 2C ) . Thus , this analysis indicates that the strength of In3 pA of CSTF3 is at a suboptimal level . Interestingly , the slope of the curve for log2 ( P/S ) vs . pA to 3′SS distance appeared different for constructs with GU-rich elements compared to those without ( Figure 2C ) . By contrast , mutation of AAUAAA to AUUAAA did not lead to a slope change , suggesting that the contribution of GU-rich elements to pA strength may be different than that of PAS . We next examined the importance of 5′SS and 3′SS strengths . We mutated the 5′SS sequence to two stronger sequences ( mutants 1 and 2 , Figure 2D ) based on their MaxEnt scores . Mutants 1 and 2 would be at the 51 . 9th- and 95 . 5th-percentile , respectively , in the human genome . The relative strengths of the 5′SSs were also confirmed by comparison with the consensus sequence of all human 5′SSs , represented by position-specific scoring matrix ( PSSM ) scores , and by free energy values for base-pairing with U1 snRNA ( Figure 2D ) . Strengthening 5′SS drastically inhibited intronic pA usage: ∼90% decrease for mutant 1 and no detectable intronic pA usage for mutant 2 even though AAUAAA was used as PAS ( Figure 2D ) . We also weakened 3′SS strength from the 94 . 3th-percentile to the 3 . 8th-percentile based on the MaxEnt score . However , only a minor increase of intronic pA usage was detected ( Figure 2E ) . Together , these data indicate 5′SS strength is a determining factor for the usage of In3 pA . In both human and mouse cells , the In3 pA can lead to 2 short isoforms ( isoforms 2 and 3 in Figure 1A ) , depending upon whether or not intron 2 is spliced . The isoform 2 , which does not have retention of intron 2 , is ∼2–3-fold more abundant than isoform 3 in HeLa and C2C12 cells based on the semi-quantitative reverse transcription ( RT ) -PCR analysis ( Figure S4 ) . According to the open reading frames , isoform 2 would encode a protein of 103 amino acids ( aa ) , containing the N-terminal region of CstF-77 and some aa from the intronic region of intron 3 ( Figure S5 ) , whereas isoform 3 would encode a protein of 44 aa . However , we could not detect these protein products using various antibodies against the N-terminal region of CstF-77 . In addition , several lines of evidence indicate that the coding region from intron 3 may cause rapid degradation of the protein encoded in isoform 2: 1 ) pRinG-77S constructs expressing different amounts of intronic pA isoforms showed the same red fluorescence to green fluorescence ratio when transfected into HeLa cells ( Figure S6A ) ; 2 ) immunoblot analysis using an antibody against RFP did not detect protein products of the intronic isoforms expressed from pRinG-77S constructs ( Figure S6B ) ; 3 ) a bicistronic mRNA containing RFP tagged with the intronic coding sequence between 5′SS and stop codon followed by IRES and EGFP resulted in green fluorescence only ( Figure S6C ) . Thus , it appears that the protein products from intronic pA isoforms are expressed at very low levels at most . Given that CstF-77 is a C/P factor , we next reasoned that it may regulate the usage of its own intronic pA , creating a feedback autoregulatory mechanism , similar to its fly homolog su ( f ) [21] . To this end , we used small interfering RNAs ( siRNAs ) to specifically knock down the expression of the CstF-77 transcripts encoding full length protein ( named CstF-77 . L mRNAs ) . The CstF-77 . L mRNA level significantly decreased after 8 hr of siRNA transfection and its protein level started to decrease after 16 hr ( Figure 3A ) . Interestingly , expression of isoforms 2 and 3 , collectively named CstF-77 . S mRNAs , also gradually decreased after 16 hr , indicating that the expression of CstF-77 . S mRNAs can be controlled by the CstF-77 protein level . By contrast , knockdown of CstF-77 . S mRNAs ( by ∼50% , Figure 3B , left ) did not affect CstF-77 . L mRNAs ( Figure 3B , right ) , suggesting that expression of CstF-77 . S mRNA is not important for CstF-77 . L expression . In accord with the autoregulatory mechanism , expression of exogenous CstF-77 led to increased expression of endogenous CstF-77 . S mRNAs and decreased expression of endogenous CstF-77 . L mRNAs ( Figure 3C ) . Consistently , knockdown of CstF-77 . L mRNAs inhibited intronic pA usage for the reporter construct pRinG-77S-831 ( structure shown in Figure 2A ) , whereas knockdown of CstF-77 . S mRNAs had no effect ( Figure 3D ) ; and overexpression of CstF-77 enhanced intronic pA usage for the reporter construct ( Figure 3E ) . We next reasoned that the negative feedback autoregulatory control may cause CstF-77 . S and CstF-77 . L isoforms to oscillate in their expression . To test this hypothesis , we examined expression of CstF-77 . S and CstF-77 . L mRNAs over time after plating cells . Indeed , as shown in Figure 4F , these two isoforms oscillated over time: when CstF77 . L level was high CstF77 . S level was low , and vice versa . Taken together , these data indicate that intronic pA usage is responsive to CstF-77 expression , creating a feedback autoregulatory mechanism . We previously found that the expression of C/P factors negatively correlates with the 3′UTR length in development and cell differentiation [30] . We asked whether the CstF-77 . S/CstF-77 . L ratio is related to APA of 3′UTRs . To this end , we analyzed an exon array dataset for 11 mouse tissues and a deep sequencing dataset for 10 human tissues and 7 human cell lines . The CstF-77 . S/CstF-77 . L ratio was calculated by comparing the intensity of microarray probes or density of RNA-seq reads for CstF-77 . S with those for CstF-77 . L ( Figure 4A ) . The global 3′UTR length changes were calculated by comparing the intensity of microarray probes or density of RNA-seq reads for the region upstream of first pA in 3′UTR ( called constitutive 3′UTR or cUTR ) with those for the downstream region ( called alternative 3′UTR or aUTR ) ( Figure 4A ) . This value was also called Relative expression of isoforms Using Distal pAs ( RUD , see Materials and Methods for detail ) . The median RUD of all genes reflects the relative global 3′UTR length . Interestingly , the CstF-77 . S/CstF-77 . L ratio generally correlated with the global 3′UTR length in both human ( R2 = 0 . 61 , Pearson Correlation ) ( Figure 4B ) and mouse cells/tissues ( R2 = 0 . 71 , Pearson Correlation ) ( Figure 4C ) . This result indicates that the CstF-77 . S/CstF-77 . L ratio is associated with APA of 3′UTRs . We next analyzed our previously published exon array data for differentiation of C2C12 myoblast cells [31] , with which we reported general lengthening of 3′UTR during cell differentiation . A linear correlation ( R2 = 0 . 61 ) between CstF-77 . S/CstF-77 . L and RUD was also detected ( Figure 4D ) . To validate this finding , we examined expression of CstF-77 . S and CstF-77 . L mRNAs by RT-qPCR in proliferating C2C12 cells and cells after 1 day or 4 days of differentiation . CstF-77 . S mRNAs showed increased expression by ∼20% after 1 day of differentiation but no significant change of expression after 4 days . By contrast , the expression of CstF-77 . L mRNAs gradually decreased ( Figure 4E ) . Consequently , the CstF-77 . S/CstF-77 . L ratio gradually increased in differentiation ( Figure 4E ) . Consistently , the CstF-77 protein level decreased by 27% after 1 day and by 46% after 4 days ( Figure 4F ) . Thus , the usage of In3 pA of CstF-77 gene inversely correlates with CstF-77 protein level in cell differentiation . Given CstF-77's role in C/P , this result suggests that CstF-77 protein level may be the underlying reason for the connection between the CstF-77 . S/CstF-77 . L ratio and global 3′UTR length . The increased CstF-77 . S/CstF-77 . L ratio in differentiation could be due to activation of C/P at In3 pA , which , however , seems in discord with our previous finding that the C/P activity in general is weakened in C2C12 differentiation [31] . Notably , intronic pA of CstF-77 without flanking 5′SS and 3′SS was less used in differentiated cells compared to proliferating cells by reporter assays ( Figure S7 ) , suggesting that the pA usage per se is decreased in differentiation . To explore this issue further , we knocked down several factors in the C/P machinery , including CstF-64 in the CstF complex ( Figure 5A ) , CFI-25 , CFI-68 , and CFI-59 in the CFI complex ( Figures 5B ) , and CPSF-160 and CPSF-73 in the CPSF complex ( Figure 5C ) . All the knockdowns led to significant decrease of the CstF-77 . S/CstF-77 . L ratio , indicating that the pA usage is responsive to perturbation of the C/P activity . Furthermore , changing the pA strength does not alter the trend of CstF-77 . S/CstF-77 . L ratio changes in differentiation ( Figure 5D ) . We next reasoned that since intron size and 5′SS strength can regulate the usage of intronic pA , change of splicing activity in differentiation may lead to change of CstF-77 . S/CstF-77 . L . Notably , mRNAs encoding several U1 snRNP and U2 snRNP factors are downregulated in differentiation based on microarray analysis ( Figure 6A ) , suggesting weakening of their activities . To examine the effect of splicing regulation on CstF-77 . S/CstF-77 . L , we knocked down U1-70K , one of the components of U1 snRNP [32] , SF3B1 , a key component of U2 snRNP [33] , and U2AF65 , a factor involved in recognition of 3′SS and recruitment of U2 snRNP [34] . Knockdown of U1-70K led to a significant increase ( ∼50% ) of the CstF-77 . S/CstF-77 . L ratio ( P<0 . 05 , Figure 6B ) , whereas knockdown of SF3B1 led to a marginal increase of the ratio ( P>0 . 1 , Figure 6C ) , and knockdown of U2AF65 led to a significant decrease of the ratio ( P<0 . 05 , Figure 6D ) . Thus , U1 snRNP may play a role in regulation of intronic pA usage in C2C12 differentiation . To further explore the role of U1 snRNP in intronic C/P of CstF-77 , we used an oligonucleotide which mimics the consensus sequence of 5′SS [35] , termed U1 domain ( U1D ) oligo ( Figure 6E ) . Presumably , U1D can sequester U1 snRNP in the cell , thereby inhibiting 5′SS recognition by U1 snRNP [35] . Upon treatment of U1D , the CstF-77 . S/CstF-77 . L ratio increased by 2-fold ( Figure 6F ) . An even greater increase ( ∼9-fold ) of intronic pA usage was observed from reporter assays using pRinG-77S-1690 ( Figure 6G ) . Taken together , these results indicate that the intronic pA CstF-77 gene is under the control of U1 snRNP . The effect of U1 snRNP regulation on intronic C/P is consistent with the critical role of 5′SS for pA usage ( see above ) . To directly examine whether the 5′SS strength is important for intronic pA usage , we used reporter constructs with different 5′SS strengths in proliferating and differentiating C2C12 cells ( Figure 6H ) . Interestingly , while the construct with wild type , weak 5′SS recapitulated the intronic pA usage of endogenous CstF-77 pre-mRNAs , the mutant 5′SS with medium strength showed the opposite trend , indicating that 5′SS strength is critical for the regulation of intronic pA usage . This result is in line with the general trend that intronic pAs activated in C2C12 differentiation tend to be in introns with weak 5′SS ( Figure S8 ) . In order to understand how critical it is to control CstF-77 expression in cell proliferation and differentiation , we knocked down CstF-77 in proliferating C2C12 cells and examined APA and gene expression genome-wide using our newly developed method , 3′ region extraction and deep sequencing ( 3′READS ) ( Figure 7A ) [8] . We found 1 , 068 genes that had significant APA changes in 3′UTRs ( P<0 . 05 , Fisher's Exact test , and >5% change in isoform abundance ) ( Figure 7A ) . However , there was no significant bias of expression to proximal or distal pA isoforms , indicating no global 3′UTR shortening or lengthening after CstF-77 knockdown . Gene Ontology analysis indicated that genes with different functions were affected differently ( Table 1 ) . For example , genes with functions in “protein localization” , “intracellular transport” , “RNA processing” were more likely to have 3′UTRs lengthened , whereas those with functions in “cell-cell adhesion” , “mitosis” , and “Ras protein signal transduction” were more likely to have 3′UTRs shortened . We next compared this data with our recently published data for APA regulation in C2C12 differentiation [8] . Whereas only a small set of genes were found to be commonly regulated between CstF-77 knockdown and C2C12 differentiation , the number of consistently regulated genes was significantly greater than that of oppositely regulated genes ( P = 4 . 1×10−9 , Chi-squared test ) , suggesting downregulation of CstF-77 is involved in regulation of a subset of APA events in C2C12 differentiation ( Figure 7B ) . We next examined cis elements surrounding pAs of regulated isoforms . Remarkably , U-rich elements were significantly enriched for pAs whose isoforms were downregulated after CstF-77 knockdown , particularly in the −40 nt to −1 nt region relative to the pA ( set to 0 ) ( Figure 7C ) . This result suggests that pAs with U-rich elements are highly dependent on CstF-77 for C/P . Since CstF-77 is in the same complex as CstF-64 , we next examined CstF-64 binding near regulated pAs using the CstF-64 CLIP-seq data we recently published [8] . Consistent with the interaction between CstF-77 and CstF-64 , pAs of downregulated isoforms had significantly more CstF-64 binding in nearby regions than those of upregulated ones ( P<0 . 05 , bootstrap analysis ) , suggesting that usage of these pAs are also dependent on CstF-64 ( Figure 7D ) . Our data also indicated that a large number of genes ( 1 , 776 in total ) had significant changes of expression ( fold change >1 . 5 and P<0 . 01 , Fisher's Exact test ) after CstF-77 knockdown . By GO analysis , we found , to our surprise , that genes related to cell cycle were most significantly downregulated ( Table 2 and Figure 8A ) . This result was validated by RT-qPCR for a set of cell cycle-related genes , such as Ccnb1 ( cyclin B1 ) , Cdca3 ( cell division cycle associated 3 ) , Cdk4 ( cyclin-dependent kinase 4 ) , Mcm6 ( minichromosome maintenance complex component 6 ) , and Tipin ( timeless interacting protein ) ( Figure 8B ) . This result indicates that the CstF-77 level is important for expression of cell cycle genes , and suggests that downregulation of CstF-77 may help cells halt proliferation and launch differentiation . To explore this further , we overexpressed CstF-77 in proliferating C2C12 cells , induced differentiation , and examined marker genes that are normally upregulated during differentiation . All three marker gene mRNAs , including Myh3 ( heavy polypeptide 3 , skeletal muscle , embryonic ) , MyoG ( myogenin ) , and Tpm2 ( tropomyosin 2 , beta ) , were significantly less upregulated in cells overexpressing CstF-77 ( Figure 8C ) , further indicating that the CstF-77 level is important for cell proliferation/differentiation .
In this study , we examined the evolution and regulation of intronic C/P of human and mouse CstF-77 genes . The conservation of various features involved in pA usage across vertebrates underscores its importance . Notably , the Drosophila gene encoding the homologue of CstF-77 , su ( f ) , also contains an intronic pA [19] . Unlike the intronic pA isoforms of vertebrate CstF-77 genes , which have open reading frames , the su ( f ) intronic pA isoform does not have an in-frame stop codon . However , both vertebrate and fly intronic pAs appear to function to attenuate expression of the gene via feedback autoregulation . Remarkably , there is no conservation in surrounding sequences or adjacent intron/exon structures between the intronic pAs in vertebrates and in fly , indicating convergent evolution of this mechanism . Intriguingly , we could not find a similar mechanism in C . elegans after exhaustive search of all available public pA data . It remains to be seen whether or not the CstF-77 homolog in C . elegans is subject to another type of autoregulation . In addition to autoregulation , we found that the intronic pA usage is regulated upon perturbation of several other C/P factors , including those in the CstF , CPSF and CFI complexes , suggesting it is responsive to the general C/P activity in the cell . Two key features of the intronic pA of the CstF-77 gene may make it particularly suitable for this function: first , its suboptimal strength can create a wide dynamic range of usage in response to change of C/P activity; second , its placement in an intron can allow rapid regulation because of competition of its usage with splicing . Juge et al . proposed two modes of autoregulation for fly su ( f ) , a strong mode in non-dividing cells and a weak mode in dividing cells [22] . Here , our study indicates that splicing plays a dominant role in the usage of intronic pA of CstF-77 gene . Consistently , inhibition of the U1 snRNP activity , not the C/P activity , recapitulates the intronic pA regulation in cell differentiation . Thus , we propose that the U1 snRNP activity sets the general level of intronic pA usage under different conditions , such as in cell proliferation and differentiation , and the C/P activity plays a fine tuning role to robustly control CstF-77 expression under a given condition ( Figure 9 ) . This model would readily explain the two modes of autoregulation proposed by Juge et al . , i . e . , the U1 snRNP activity is high in dividing cells and weak in non-dividing cells . Moreover , control of CstF-77 level by U1 snRNP suggests that the C/P activity in the cell is modulated by the splicing activity , leading to coordination between these two pre-mRNA processing steps . This coordination may ensure that the widespread cryptic pAs in introns are not activated when U1 snRNP is downregulated under conditions like cell differentiation [9] . Conversely , this result may explain , at least partially , that mild inhibition of U1 snRNP can lead to 3′UTR lengthening [36] . Regulation of intronic pA of CstF-77 is reminiscent of a similar mechanism for the IgM gene . Both intron size and 5′SS strength were found to be important for the usage of intronic pA in the IgM gene [37] , [38] . A number of factors have been implicated in the regulation , including the C/P factor CstF-64 [10] , the U1 snRNP component U1A [39] , and the RNAPII transcription elongation factor ELL2 [40] . Whereas we found U1 snRNP regulation correlates with the activation of intronic pA of CstF-77 gene , future studies are needed to examine whether additional mechanisms can contribute to this regulation . Of particular importance is whether other splicing factors also play a role in the regulation of intronic pA . Notably , splicing factors in general are downregulated in C2C12 differentiation ( Figure S9 ) . Here we observed only marginal activation of In3 pA after SF3B1 knockdown and , surprisingly , inhibition of the pA after U2AF65 knockdown . It remains to be seen how factors involved in different steps of splicing regulate the usage of In3 pA and intronic C/P in general . Perturbation of CstF-77 expression led to widespread APA and expression changes of a large number of genes . Remarkably , the genes with functions in cell cycle are most significantly affected , indicating that they are highly dependent upon CstF-77 for expression . pAs surrounded with U-rich elements appeared to be more affected by CstF-77 knockdown . Indeed , we found downregulated genes with a single pA also tend to have U-rich elements surrounding the pA ( Figure S10 ) , suggesting that inefficient 3′ end processing may lead to their downregulation of expression . Intriguingly , cell cycle genes tend to have shortened 3′UTRs after CstF-77 knockdown ( Table 1 ) . Since genes with shortened 3′UTRs tend to be downregulated ( Figure S11 ) , it is possible that distal pAs of cell cycle genes are more responsive to the CstF-77 level . Future work is needed to fully unravel the mechanism by which CstF-77 regulates cell cycle genes . We found pAs with more CstF-64 binding are more likely to be affected by CstF-77 knockdown indicating that some of the regulation is through the CstF complex . However , CstF-64 is also known to bind GU-rich elements [41] , and our cross-linking immunoprecipitation and high-throughput sequencing ( CLIP-seq ) data from C2C12 cells showed that the top two most significant pentamers for CstF-64 binding are UGUGU and UUUUU [8] . But GU-rich elements are only modestly enriched in the downstream region of regulated pAs after CstF-77 knockdown . Whether pAs with a different number or placement of U-rich and UG-rich elements are differentially regulated by CstF-77 and CstF-64 needs to be examined in the future . Moreover , a recent genome-wide study of CstF-64 knockdown in HeLa cells indicated that only a small set of APA events in these cells are regulated by the factor [42] . However , co-depletion of CstF-64 and its paralog τCstF-64 leads to more APA changes , largely leading to 3′UTR lengthening . That APA pattern appears different than that observed in this study with CstF-77 knockdown . Whether the difference is due to different levels of knockdown or different cell types used in the studies needs to be further explored .
Construction of the pRinG vector and all plasmids derived from pRinG are described in Table S1 . The pRiG vector and pRiG-77 . AE containing the intronic pA of CstF-77 were described previously [31] . For pCMV-CstF-77 , the open reading frame ( ORF ) of human CstF-77 was obtained from the IMAGE clone 5223351 ( Invitrogen ) by PCR using primers 5′-CGATGAATTCATGTC AGGAGACGGAGCC and 5′-GGCCCTCGAGCTACCGAATCCGCTTCTG . The fragment was digested by EcoR I and Xho I , and then inserted into the pcDNA3 . 1/His C vector ( Invitrogen ) digested with the same enzymes . HeLa cells and C2C12 cells were maintained in Dulbecco's Modified Eagles Medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) . Differentiation of C2C12 cells was induced by switching cell media to DMEM+ 2% horse serum ( Sigma ) when cells were ∼100% confluent . All media were also supplemented with 100 units/ml penicillin and 100 µg/ml streptomycin . Transfection with plasmids or siRNAs was carried out with Lipofectamine™ 2000 ( Invitrogen ) or jetPEI ( polyplus ) according to manufacturer's recommendations . Transfection was carried out for 48 hr unless described otherwise . siRNA sequences are shown in Table S2 . The U1D oligo ( 5′-gCcAgGuAaGuau ) and control oligo ( 5′-CAGAAATACACAATA ) , where locked nucleic acid ( LNA ) residues are in uppercase , 2′-OMe RNA residues are in lowercase , DNA nucleotides are in underlined uppercase , were previously described in Goraczniak et al . [35] ( called UA17-13B-U1D and UA17-13B-TD , respectively ) . These oligos were transfected into C2C12 cells at 15 µM using Lipofectamine 2000 when the confluency of cells was about 50% . Cells were harvested 48 hr after transfection . For fluorescent activated cell sorting ( FACS ) analysis , cells were released from culture dishes by Trypsin-EDTA 24 h after transfection and green and red fluorescence signals were read at 530 nm and 585 nm , respectively , in the BD FACScalibur system ( BD Biosciences ) . For immunoblot , the RIPA buffer ( 1% NP-40 , 0 . 1% SDS , 50 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 0 . 5% Sodium Deoxycholate , and 1 mM EDTA ) was used to extract proteins from the cell . Proteins were resolved by SDS-PAGE , followed by immunoblotting using antibodies . Antibodies used in this study and their sources are shown in Table S3 . Total cellular RNA was extracted using Trizol ( Invitrogen ) according to manufacturer's protocol . RNA was run in a 1 . 2% denaturing agarose gel , and was transferred to nylon membrane overnight . RNA was detected by hybridization with a radioactively labeled probe for the RFP sequence . The probe was made by PCR using pDsRED-Express-c1 as template and primers 5′-CGATGCTAGCATGGCCTCCTCCGAGGAC and 5′-GGCCCTCGAGCTACAGGAACAG GTGGTG with α-32P-dCTP . For RT-qPCR , mRNA was reverse-transcribed using the oligo-dT primer ( Promega ) , and qPCR was carried out with Syber-Green I as dye . Primers are shown in Table S4 . To calculate the global 3′UTR length ( RUD ) score , we used exon array data for C2C12 cell differentiation [31] , exon array data for mouse tissues ( http://www . affymetrix . com/support/technical/sample_data/exon_array_data . affx ) , and RNA-seq data for human tissues and cell lines [7] . Exon array data were first normalized by the Robust Multichip Average ( RMA ) method . Expressed genes were selected by the Detection Above Background ( DABG ) method . The RUD score was based on the ratio of average probeset intensity of aUTR to that of cUTR , as previously described [31] . For RNA-seq data , the RUD score was based on the ratio of read density of aUTR to that of cUTR , as described previously [43] . For both analyses , aUTRs and cUTRs were defined by PolyA_DB 2 [44] . The relative expression of CstF-77 . S vs . CstF-77 . L was calculated based on the probes or RNA-seq reads specific for each isoform . For analysis of splicing factor expression , we examined mRNAs encoding splicing factors defined by Jurica and Moore [45] . 5′SS and 3′SS were analyzed as previously described [9] . Briefly , we used all GT-AT type introns supported by human RefSeq sequences to build Position Specific Scoring Matrices ( PSSMs ) for 5′SS and 3′SS . For 5′SS , we used −3 to +6 nt surrounding the 5′SS , with 3 nt in the exon and 6 nt in the intron; for 3′SS , we used −22 to +2 nt surrounding the 3′SS , with 22 nt in the intron and 2 nt in the exon . The maximum entropy scores were calculated with MaxEnt [26] . 5′SS sequences were also scored by their ability to anneal with U1 snRNA . We used the sequence 5′-ACUUACCUG of U1 snRNA to form duplex structures with 5′SS sequences using the RNAduplex function of ViennaRNA [46] . For intron density map , we used all the RefSeq-supported introns as the observed set , and created an expected set using randomized pairs of intron size and splice site . The introns were divided into 20 fractions based on intron size and splice site strength , respectively , and distributed in a 20×20 grid . For each cell in the grid , the ratio of the number of introns in the observed set to that in the expected set was calculated and represented by color in a heatmap . The 3′ region extraction and deep sequencing ( 3′READS ) method used in this study is the same as previously described [8] , except that 10 µg of total RNA was used , and poly ( A ) + RNA was selected by the chimeric U5 and T45 ( CU5T45 ) oligo conjugated on streptavidin beads and fragmented by 1 U RNase III at 37°C for 30 min . Poly ( A ) + RNA fragments were subject to further processing as previously described [8] . pA identification was carried out as previously described [8] . Only poly ( A ) site supporting ( PASS ) reads , defined as having >2 non-genomic Ts at the beginning of read , were used for further analysis . The expression level of an APA isoform was calculated using the number of PASS reads assigned to the pA . To study APA in the 3′-most exon , we first selected the top two expressed isoforms and used the Fisher Exact test to examine their difference in abundance between CstF-77 knockdown and control . Significantly regulated isoforms were those with P<0 . 05 and change of abundance >5% . Gene expression was calculated using the total number of PASS reads assigned to a gene . Differentially regulated genes after CstF-77 knockdown were those with P<0 . 01 ( Fisher's Exact test ) and fold change >1 . 5 compared to control . The DAVID software was used to identify Gene Ontology terms enriched for genes with significant changes in gene expression or APA [47] . We examined four regions around the pA , i . e . , −100 to −41 nt , −40 to −1 nt , +1 nt to +40 nt and +41 nt to +100 nt . For each region , the Fisher's Exact test was used to check whether a sequence was enriched for a set of pAs vs . another set , for example , those of upregulated isoforms vs . downregulated isoforms . CLIP-seq reads of CstF-64 [8] were aligned to the mouse genome ( mm9 ) using Novoalign ( http://www . novocraft . com/ ) . Reads with deletions caused by skipping of reverse transcriptase at the UV cross-linked bases were used for analyses . A bootstrapping method [8] was used to compare CstF-64 binding in the −10 to +40 nt region around the pA for pAs of upregulated isoforms vs . those of downregulated isoforms after CstF-77 knockdown .
|
Autoregulation is commonly used in biological systems to control the homeostasis of certain activity , and cross-regulation coordinates multiple processes . We show that vertebrate genes encoding the cleavage/polyadenylation ( C/P ) factor CstF-77 contain a conserved intronic C/P site ( pA ) which regulates CstF-77 expression through a negative feedback loop . Since the usage of this intronic pA is also responsive to the expression of other C/P factors , the pA can function as a sensor for the cellular C/P activity . Because the CstF-77 level is important for the usage of a large number of pAs in the genome and is particularly critical for expression of genes involved in cell cycle , this autoregulatory mechanism has far-reaching implications for cell proliferation and differentiation . The human intron harboring the pA is large and has a weak 5′ splice site , both of which are also highly conserved in other vertebrates . Inhibition of U1 snRNP , which recognizes the 5′ splice site of intron , leads to upregulation of the intronic pA isoform of CstF-77 gene , suggesting that the C/P activity in the cell can be cross-regulated by splicing , leading to coordination between these two processes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"systems",
"biology",
"rna",
"rna",
"processing",
"nucleic",
"acids",
"gene",
"expression",
"biology",
"molecular",
"cell",
"biology"
] |
2013
|
The Conserved Intronic Cleavage and Polyadenylation Site of CstF-77 Gene Imparts Control of 3′ End Processing Activity through Feedback Autoregulation and by U1 snRNP
|
Leishmania donovani is the main cause of visceral leishmaniasis ( VL ) in East Africa . Differences between northern Ethiopia/Sudan ( NE ) and southern Ethiopia ( SE ) in ecology , vectors , and patient sensitivity to drug treatment have been described , however the relationship between differences in parasite genotype between these two foci and phenotype is unknown . Whole genomic sequencing ( WGS ) was carried out for 41 L . donovani strains and clones from VL and VL/HIV co-infected patients in NE ( n = 28 ) and SE ( n = 13 ) . Chromosome aneuploidy was observed in all parasites examined with each isolate exhibiting a unique karyotype . Differences in chromosome ploidy or karyotype were not correlated with the geographic origin of the parasites . However , correlation between single nucleotide polymorphism ( SNP ) and geographic origin was seen for 38/41 isolates , separating the NE and SE parasites into two large groups . SNP restricted to NE and SE groups were associated with genes involved in viability and parasite resistance to drugs . Unique copy number variation ( CNV ) were also associated with NE and SE parasites , respectively . One striking example is the folate transporter ( FT ) family genes ( LdBPK_100390 , LdBPK_100400 and LdBPK_100410 ) on chromosome 10 that are single copy in all 13 SE isolates , but either double copy or higher in 39/41 NE isolates ( copy number 2–4 ) . High copy number ( = 4 ) was also found for one Sudanese strain examined . This was confirmed by quantitative polymerase chain reaction for LdBPK_100400 , the L . donovani FT1 transporter homolog . Good correlation ( p = 0 . 005 ) between FT copy number and resistance to methotrexate ( 0 . 5 mg/ml MTX ) was also observed with the haploid SE strains examined showing higher viability than the NE strains at this concentration . Our results emphasize the advantages of whole genome analysis to shed light on vital parasite processes in Leishmania .
Leishmania donovani , together with L . infantum , are the main causative agents of visceral leishmaniasis ( VL ) . The World Health Organization ( WHO ) estimates that this disease causes an estimated 200 , 000 to 400 , 000 new VL cases worldwide , and >40 , 000 deaths yearly . The majority of VL cases occur on the Indian subcontinent , Brazil , and East Africa with most cases in the latter region found in Sudan , South Sudan and Ethiopia [1] . While treatment regimens for VL , including combination therapy based on existing drugs , have improved safety and prognosis , they are still suboptimal , and new drugs are urgently needed . High parasite resistance on the Indian subcontinent to the pentavalent antimonial sodium stibogluconate ( SSG ) has led to its discontinuation , however SSG is still part of the primary treatment regimen for VL in Ethiopia . The situation in Ethiopia is further complicated by the presence of AIDS , a leading cause of adult illness and death in this country [2 , 3] . Between 20–40% of VL patients are co-infected with HIV and relapses , up to 50% at a year post-treatment , are frequently observed [2 , 4] . Treatment following relapse normally utilizes alternative drugs like liposomal amphotericin B , pentamidine and paromomycin . Paromomycin is an antibiotic recently approved to treat VL in India and is in clinical trials in Africa [5] . Differences in the dose of paromomycin required to treat VL patients from northern Ethiopia ( NE ) and Sudan , as compared to southern Ethiopia ( SE ) and Kenya have been reported [5 , 6] . Interestingly , other differences in the ecology , sand fly vectors and parasites have been described between NE and SE . Endemic regions of NE are typically semi-arid , with commercial monoculture fields and scattered Acacia–Balanite forests [7–9] . Phlebotomus orientalis is the primary vector in this region . On the other hand , transmission in SE occurs in areas of savannah and forest where termite mounds abound; and Phlebotomus martini and Phlebotomus celiae have been implicated as vectors [7 , 8 , 10 , 11] . Molecular characterization including multilocus enzyme electrophoresis ( MLEE ) , multilocus microsatellite typing ( MLMT ) , protein and DNA sequence analysis of individual genes , and k26—PCR targeting the hydrophilic acylated surface protein B ( HASPB ) repeat region have been used to characterize the L . donovani complex in East Africa [7 , 12–15] . MLMT analysis indicated that different genetic populations and subpopulations are present in NE and SE [13] . Recent developments in whole genome sequencing ( WGS ) and computational analysis allow the in-depth exploration and comparison of leishmanial genomes at a high level of resolution and accuracy [16–18] . Genomes of individual Leishmania species [18]; of L . infantum or L . donovani strains in limited geographic regions of Turkey or India/Nepal respectively [16 , 19 , 20] , and strains showing differences in drug resistance and tropism [16 , 20–24] have been analyzed by WGS . In this report 41 patient strains and clones from NE and SE are analyzed and compared by WGS . This study provides insights into the population structure , and genetic differences of parasites circulating in the distinct ecologies of Ethiopia . The evidence of genomic variation between the two L . donovani populations ( NE and SE ) may provide an additional insight about parasite virulence , development of drug resistance and give new directions for new treatment strategies .
Chromosome copy number was predicted based on whole chromosome median read coverage as described in Material and Methods . The predicted values for each chromosome in the patient isolates and their clones are given in Fig 1 and S2 Table . Normalized read depth , showed that 68 . 5% of the chromosomes had a predicted chromosome ( PCHR ) copy number of 2 ± 0 . 5 , i . e . disomic , with smaller percentages showing higher copy numbers; i . e . , trisomic ( 3 ± 0 . 5 ) in 23 . 4% , tetrasomic ( 4 ± 0 . 5 ) in 6 . 7% , pentasomic ( 5 ± 0 . 5 ) in 1% and hexasomic ( 6 ± 0 . 5 ) in 0 . 4% , similar to what was previously reported for Nepalese L . donovani strains [16] . Several strains , mostly patient isolates and clones belonging to the SE population; show intermediate ploidy ( mixoploidy ) for specific chromosomes , e . g . chromosomes 1 , 6 and 23 ( S2 Table ) , suggestive of parasite populations with mixed polysomic diversity , perhaps due to variation in chromosomal amplification between individual cells in culture . Differences in chromosome aneuploidy between SE patient strain and its clones was not significant ( unpaired two samples student's t-test , p = 0 . 2 ) , suggesting that aneuploidy in the clonal population is not due to selection of clones exhibiting different ploidy for identical chromosomes . On the other hand , there is a significant difference in chromosome aneuploidy ( unpaired two samples student's t-test , p = 0 . 028 ) when SE parasites , patient and clones , were compared to NE parasites , patient and clones . Cluster analysis based on chromosome copy number provides insight on three levels: first , that similarities and differences exist between all parasites examined; second , validation that clones derived from the same patient strain are highly similar; and third , that differences in chromosome copy are not correlated with the parasite geographic origin . Similar to earlier studies [16 , 19 , 20 , 25] where aneuploidy was examined in clinical isolates of Leishmania from India and Nepal ( L . donovani ) , in sand flies from Turkey ( L . infantum ) , and in laboratory strains ( L . major , L . braziliensis , L . donovani , L . infantum , L . mexicana and L . panamensis ) ; all the Ethiopian L . donovani lines examined showed aneuploidy , and each has a different karyotype . Seven chromosomes ( 17 , 25 , 27 , 30 , 32 , 34 and 36 ) were disomic in all lines examined , as was chromosome 3 with the exception of one strain AM554 . Four of these chromosomes ( 30 , 32 , 34 and 36 ) were used for normalization of average chromosome read coverage as described by Rodgers et al [18] . Interestingly , disomy was also observed for five of these chromosomes , 17 , 25 , 30 , 34 and 36 , in all the 17 Indian and Nepalese L . donovani lines originally studied [16] , and in almost all 206 strains from the Indian subcontinent recently examined [20] . Several other chromosomes ( 18 , 19 , 21 and 28 ) that were disomic in all the Indian and Nepalese lines showed somewhat more diverse ploidy ( 2 to 3 copies ) in the Ethiopian lines . Chromosome 31 was polysomic in all the lines used in this study . Even GR363sk/cl . I and GR363sk/cl . II , which showed the least aneuploidy of all the lines examined , were still trisomic for chromosome 31 . Chromosome 31 is polysomic in every Old World Leishmania strain examined to date [16 , 19 , 25] . Chromosome copy number was compared using clones from several strains ( AM560 , n = 4; GR356 , n = 9; GR363sp , n = 3; GR363sk , n = 3; GR364sp , n = 3; GR383 , n = 5 ) . In one case ( GR364sk , n = 3 ) two clones and the original patient strain were examined . Validation of aneuploidy similarities was carried out using clustering based on ploidy patterns taking into account all 36 chromosomes . What is readily apparent , from both the heat map and dendrogram ( Fig 1 ) , that in most cases karyotypes of clones isolated from the same strain are highly similar . For instance , the karyotypes of the five GR383 clones ( I , II , X , XII and XIII ) are almost identical ( unpaired student's t-test , p > 0 . 73 ) , and fall in a tight cluster . This is also seen for all the clones of GR363sp , GR363sk , GR364sk and AM560 , and 8/9 clones of GR356 . Only two clones , GR356/cl . I and GR364sk/cl . II , show karyotypes significantly different from their sister lines or the patient strain from which they were derived , and fail to cluster with the former ( Fig 1 ) . Interestingly , clone GR356/cl . 1 groups with its sister lines based on SNP analysis ( Figs 2 and 3 ) , and exhibits a k26-PCR amplicon identical to the other NE strains ( 290 bp ) . Of note , clone GR364sk/cl . II had a k26-PCR amplicon ( 450 bp ) similar in size to SE strains , even though it was derived from GR364sk , a NE strain with a 290 bp amplicon typical of the NE region [7] . This strain was isolated from a HIV-VL patient , and the sister clone , GR364sk/cl . I which is very similar to the patient strain also has a k26—PCR product of 290 bp . Clone GR364sk/cl . II also groups with the SE strains by SNP analysis ( Figs 2 and 3 ) , but is distinct from them suggesting that this patient might have had a mixed infection . Cluster analysis of the karyotype data doesn’t separate the SE and NE strains by geographic region instead they are mixed together , interspersed among each other . Despite this , some differences in chromosome copy number between the two populations are apparent . Chromosomes 13 , 15 , 16 , 23 , 28 , and 31 show significantly higher average ploidy for SE strains compared to NE strains , while chromosome 4 is the only chromosome where the NE strains show a significantly higher average ploidy than the SE population ( Table 1 and S2 Table ) . In addition , we found that SE strains show a significantly higher average total chromosome somy ( 2 . 52 ± 0 . 09 ) than the NE strains , ( 2 . 35 ± 0 . 06; paired t-test , p = 0 . 0016 ) , perhaps indicating that the SE strains tend towards higher polyploidy than the NE strains ( S2 Table ) . Finally , parasites from different organs of three HIV-VL co-infected patients were examined . Parasites isolated from the skin or spleen of the same patient form separate groups , and the karyotypes of parasites isolated from the respective sites show greater differences , in most cases , than clones generated from the same site , either skin or spleen . GR364 spleen and skin strains , with the exception of GR364sk/cl . II , form separate clusters ( Fig 1 ) . Overall these five lines ( skin–original patient strain and clone I , versus spleen—all three clones ) show no significant difference in chromosome ploidy distribution , i . e . karyotype . However , when each GR364 spleen and skin chromosome was compared on an individual basis , 6 out of 36 chromosomes ( Ld4 , 5 , 8 , 14 , 20 and 31 ) show significant differences in ploidy ( p = 0 . 0004 , 0 . 04 , 0 . 01 , 0 . 05 , 0 . 01 and 0 . 001 , respectively ) . This probably accounts for the fact that the skin and spleen strains form separate subgroups ( Fig 1 ) . Likewise , GR363sk and GR363sp taken from the skin and spleen , respectively , of the same patient cluster in separate branches of the dendrogram ( Fig 1 ) . Significant overall differences in ploidy between the GR363 skin and the spleen clones ( two tailed paired t-test , p = 0 . 0067 ) was observed . Interestingly , the spleen clones from this patient demonstrate on average higher ploidy than the skin clones . Finally , strains isolated from the spleen and bone marrow of one patient , LDS373sp and LDS373bm respectively , also show different karyotypes ( 7/36 chromosomes differ ) , even though they cluster together on the dendrogram . These parasites also show different k26—PCR fragment sizes , gene CNV and SNP profiles . An overall difference in ploidy was found in chromosomes 1 , 4 , 6 , 20 and 35 by the comparison of all spleen against skin clones . The differences in chromosome ploidy of strains isolated from different organs may result from clonal selection of the parasites in the host due to specific selective pressures at the infection site . SNP calling , compared to the L . donovani reference strain ( BPK282A1 ) , for each of the strains and clones was carried out as described in material and methods . The two parasite populations , SE and NE , show significantly different number of SNPs on average , ~153K and ~168K ( p < 0 . 043 ) respectively , compared to the Indian reference strain ( R ) . In addition , the percentage of homozygous and heterozygous SNPs within each geographic population ( S3 Table ) , represented by a single alternate allele ( A ) , show significant differences i . e . , for the SE ( mean homozygous AA = 87 . 2% and heterozygous RA = 12 . 7% , respectively , p<0 . 05 ) and the NE populations ( mean homozygous AA = 83 . 3% and heterozygous RA = 16 . 6% , respectively , p<0 . 05 ) . The relationship between SE and NE strains and clones based on whole genome SNP pair-wise analysis is shown in Fig 2 . Each colored square in the matrix indicates the percent SNP similarity for a strain/clone listed on the left compared to strain/clone listed along the bottom of the matrix . Unlike the chromosomal aneuploidy profiles ( Fig 1 ) , SNP population analysis divides the L . donovani population into large clades or groups based on geographical distribution ( Fig 2 ) . This is easily seen both in the hierarchical cluster tree where SE and NE parasites each form separate groups with clones from each strain showing highest similarity to each other ( Fig 2A ) and the heat map ( Fig 2B ) . The only exceptions are three atypical strains/clones ( AM422 , AM553 , and LDS373bm ) which fall outside the main clades , and clone GR364sk/cl . II , as mentioned above , which groups with the SE rather than the NE parasites . The two atypical SE strains; AM422 and AM553 fall closest to the NE clade , yet are distinct from the NE strains . Interestingly , LDS373bm does not cluster with the spleen strain , LDS373sp , isolated from the same patient , even though the karyotypes are similar . AM422 , AM553 and LDS373bm seem to have SNP profiles falling between the NE and SE populations . Principal component analysis on the SNPs was also used to examine the population structure . SNPs showing high linkage disequilibrium were removed prior to analysis by SNP pruning [26] ( S4 Table ) . As can be seen in Fig 3A , two clusters or near-clades containing most the NE ( black circles ) or SE ( red circles ) strains and clones are observed . The two atypical SE strains , AM422 and AM553 , are outliers falling far outside both clusters ( EV1 = 0 . 229 , EV2 = -0 . 954 and EV1 = 0 . 945 EV2 = 0 . 265 respectively ) , while the two atypical NE strains , GR364sk/cl . II and LDS373bm , group together with the rest of the SE population confirming the results shown in Fig 2 . PCA was repeated excluding the two atypical SE strains to allow better separation of the remaining 39 isolates ( Fig 3B ) . All the SE strains still group together in one dense cluster that includes GR364sk/cl . II suggesting that these strains are more homogenous , however the NE strains show more diverse distribution with each strain and its clones forming a separate cluster . LDS373bm no longer groups with the SE strains . SNPs in protein coding regions were examined , and SNPs unique to the SE and/or NE populations identified . No significant difference in the percentage of synonymous , nonsynonymous or nonsense mutations was found between SE and NE parasite populations: 47% , 52 . 6% and 0 . 4% versus 50 . 0% , 49 . 8% and 0 . 2% , respectively . Altogether 683 common genes containing at least one SNP causing either a nonsynonymous or a nonsense mutation are present in both NE and SE parasites . The remaining SNPs resulting in nonsynonymous or nonsense mutations are only found in either SE ( 412 genes ) or NE ( 595 genes ) parasite populations ( S5 Table ) . As such , SNPs in these genes are unique markers for parasites in each geographic region . Gene Ontology enrichment analysis of the “unique” SNP containing genes found in each population indicates that the proteins are involved in different biological processes ( S6 Table ) . A web based semantic cluster algorithm , REVIGO , was used to remove redundant GO terms [27] . After removal of redundant GO terms the remaining terms were graphed as scatterplots in two-dimensional space according to semantic similarity . Semantically similar GO terms should remain close together in the plot , and size of the circle indicates the frequency of GO term . Unique SNPs in NE parasites ( Fig 4A and S7 Table ) are associated with biological processes such as tRNA aminoacylation for protein translation , glutamine family metabolism , regulation of transferase activity e . g . protein kinases , and phosphate ion transport , while those in SE parasites are primarily associated with cation transmembrane transport , purine nucleoside triphosphate and nucleobase metabolism and DNA conformation ( Fig 4B ) . Similar differences are also noted when the molecular functions of the genes with unique SNPs are analyzed . Unique SNPs in the NE population are concentrated mainly in genes involved in glutamine family biosynthesis and metabolism , tRNA aminoacetylation , pyrimidine metabolism , and cyclins involved in protein kinase regulation during cell division . On the other hand , unique SNPs associated with the SE population are found in genes such as glutathione metabolism , protein translation initiation and elongation factors , transport and oxidoreductase activity ( S5–S7 Tables ) . Several genes associated with the development of leishmanial drug resistance also contain nonsynonymous SNPs and/or nonsense mutations . A unique SNP , only present in the NE population , was identified in the aquaglyceroporin ( LdBPK_310030 ) gene , a protein that plays a role in trivalent antimony ( SbIII ) uptake , located on chromosome 31 [20] . This unique heterozygote nonsynonymous mutation g . 7444A>T causes an amino acid exchange ( Ser251Thr ) in TML-5 of aquaglyceroporin , and is only found in the NE population ( S5 Table ) . The MRPA gene ( PGPA ) encodes an ABC-thiol transporter ( LdBPK_230290 . 1 ) that sequesters thiol-Sb conjugates and is also involved in antimony resistance [28] . This gene contains several unique nonsynonymous SNPs unique to the NE ( four homozygote and one heterozygote ) , and SE ( two homozygote ) populations ( S5 Table ) . It is not clear how these unique SNPs affect transporter function , as no difference in response to antimonial chemotherapy between L . donovani isolates from NE and SE has been reported . Comparative read coverage was examined for 41 SE and NE isolates using a sliding window ( 5000 bp ) in order to detect genomic copy number variation ( CNV ) as described in Material and Methods . Chromosome somy was not taken into account at this stage . While both increases , and decreases in CN were observed ( S8 Table ) , increases in CN ( >2 ) were more prevalent occurring 83% of the time . In addition , a significant overall difference ( p < 0 . 00001 ) in average CNV between the NE and SE populations was noted ( Table 2 ) . Sixty-two different genes showed significant differences in CN between the SE and NE populations ( S9 Table and S1 Fig ) . In the SE strains , genes with an average CN < 1 . 5 are primarily found on chromosomes 10 , 11 , 12 , 22 , 27 , 31 , 34 , and 36; and include the folate-biopterin transporters , ABC transporters , ATP-binding cassette protein , D-lactate dehydrogenase , branched-chain amino acid aminotransferase , amastin-like proteins , phosphoglycerate mutase , tartrate-sensitive acid phosphatase , mitogen activated protein kinase homolog , as well as numerous uncharacterized proteins . Genomic CNV of the atypical NE strains was very similar to that observed for the SE strains . On the other hand , only one gene , an amastin-like protein ( LdBPK_341700 ) on chromosome 34 , shows an average CN <1 . 5 in a majority of NE strains . Interestingly , low copy number genes were more prevalent in the SE population with 84% of all strains and clones exhibiting an average CN < 1 . 5 over all genes . One striking difference between the NE and SE strains and clones is in the number of folate/biopterin transporter ( FBT ) gene ( s ) on chromosome 10 ( Table 3 , S10 Table and S2 Fig ) . Leishmania are auxotrophs for folic acid , and 14 different members of FBT family have been identified in L . infantum [29] . Several of these genes are known to play roles in parasite drug resistance and viability . Eight of the 13 L . donovani FBT homologs are located on chromosome 10 , of which 7/8 are present in a tandem array . This chromosome is disomic in most leishmanial strains examined to date [16 , 18–20 , 25] . Interestingly , three of the FBT genes present in this tandem array on chromosome 10 ( LdBPK_100390 , LdBPK_100400 and LdBPK_100410 ) show gene amplification in several NE ( GR364sk , GR364sp and GR356 ) and Sudanese parasites ( S10 Table ) . In addition , LdBPK_355160 on chromosome 35 , an ortholog of L . infantum biopterin transporter 1 , also a member of the FBT family , is amplified in the NE strain GR383 ( CN = 5 ) , but not the other NE isolates . SE parasites exhibit the opposite trend for these three genes ( LdBPK_100390 , LdBPK_100400 and LdBPK_100410 ) on chromosome 10 showing loss of heterozygosity in eight , ten , and ten out of eleven SE strains , respectively ( S10 Table ) . Loss of heterozygosity was also observed for one additional FBT gene on chromosome 10 ( LdBPK_100380 ) in the SE strain AM553 . Interestingly , two atypical NE strains , LDS373bm and GR364sk/cl . II , which group with the SE strains by SNP analysis also show loss of heterozygosity for the same three FBT genes on chromosome 10 . The average haploid CN taking into account chromosome somy for these three genes is 2 . 75 in the NE strains versus 1 . 05 , 1 . 25 and 1 . 25 respectively in the SE strains ( Table 3 ) . Genomic CN for LdBPK_100400 ( L . infantum FT1 homologue ) in the NE and SE leishmanial strains was also determined by qPCR ( Fig 5 ) in 20 strains and clones using a novel dual priming oligonucleotide system [30] . qPCR tended to give higher CNs for this gene than found by computational analysis ( cn . mops ) , however there was a good correlation overall between FT1 CN based on computational estimation with cn . mops [31] and qPCR ( ρ = 0 . 91 ) . Strain LDS373bm also showed loss of heterozygosity by qPCR , similar to what was found above by computational analysis . In addition , both methods show significant difference in FT1 CN between the SE and NE populations . The mean FT1 CN for the two different methods and populations is as follows: qPCR; SEmean = 0 . 79 , NEmean = 2 . 44 , p = 0 . 00034; cn . mops; SEmean = 1 , NEmean = 2 . 6 , p = 0 . 00009 confirming the trend toward loss of heterozygosity in the SE and amplification in the NE strains / clones examined . FT1 is the main transporter for folate . Resistance to methotrexate ( MTX ) is correlated with reduced folate uptake [32 , 33] , and CN for this gene was reduced in some resistant parasites [29 , 34] . Therefore , the effect of MTX on the viability of eight SE and NE strains/clones that vary in FT1 CN was examined ( Fig 6 ) . Several of the SE and NE strains examined also show CNV for other FBT genes on chromosome 10 flanking FT1 ( S10 Table ) . All of the SE strains/clones tested are single copy for FT1 and are significantly less sensitive ( 6–30% growth inhibition ) to MTX ( 0 . 5 mg/ml ) than the NE strains/clones ( 42–78% growth inhibition ) , p = 0 . 005; and a linear correlation ( r2 = 0 . 937 ) between CN , for the genes demonstrating CNV on chromosomes 10 ( LdBPK_100380 , LdBPK_100390 , LdBPK_100400 and LdBPK_100410 ) and 35 ( LdBPK_355160 ) , and sensitivity to MTX was observed ( Fig 6 and S11 Table ) . NE parasites are significantly more sensitive ( p = 0 . 02 to 0 . 0009 ) to inhibition by MTX over a wide range of concentrations ( 33 to 900 μg/ml ) when grown at limiting folate concentrations ( S3 Fig ) . A high correlation between FT1 CN and sensitivity to MTX was found ( Pearson's correlation coefficient ρ = 0 . 85 , p = 0 . 007 ) . Plasticity in gene organization has been reported for several Leishmania species with the number of gene copies varying between isolates from the same species [35–37] and changes in gene dosage may be correlated with differences in protein expression [18] . For instance , the region on chromosome 10 containing LdBPK_100480 , LdBPK_100510 , LdBPK_100520 and LdBPK_100521 encodes a Zn-binding protein whose function is unknown , two tandem copies of gp63 and an uncharacterized protein , respectively ( S8 and S9 Tables ) . This region is amplified ( CN = 3 ) in 3/10 SE strains and one SE-like NE clone , GR364sk/cl . II that clusters by SNP analysis with the SE strains . All other strains are diploid for this region . Gp63 is a protease involved in parasite virulence and survival [38 , 39] , and is frequently present on chromosome 10 in other species as a multicopy gene family e . g . , L . infantum ( LinJ . 10 . 0490 , 10 . 0500 , 10 . 0510 , 10 . 0520 and 10 . 0530 ) or L . major ( LmjF . 10 . 0460 , 10 . 0465 , 10 . 0470 and 10 . 0480 ) . Likewise , on chromosome 19 there are two glycerol uptake proteins ( LdBPK_191340 and LdBPK_191350 ) that have an additional gene copy ( CN = 3 ) in 9/10 SE strains and the SE-like clone ( GR364sk/cl . II ) . Interestingly , in other species these genes are part of a tandem multicopy gene family ( L . infantum 7 genes , L . major 6 genes , L . braziliensis 8 genes ) that may be involved in the remodeling of lipids on glycerol phosphoinositol lipid anchors . Amplification of the 48 kb H-region on chromosome 23 has been associated with drug resistance in vitro [40 , 41] . Part of this region is also amplified in some wild-type strains [40 , 41] . Deletions ( CN = 1 ) or duplications ( CN = 4 ) of part of the H-region ( 9 kb ) were seen in several SE and NE parasites , respectively . The deleted region was found in 3/10 SE strains and contains the genes coding for the ABC-thiol transporter ( MRPA ) ( LdBPK_230290 ) , involved in resistance to antimony [42] , and argininosuccinate synthase ( LdBPK_230300 ) , involved in arginine synthesis [43] . Interestingly a similar region is amplified in 8 clones from 2 different NE patient strains , and contains the genes coding for argininosuccinate synthase ( LdBPK_230300 ) , a putative uncharacterized protein ( LdBPK_230270 ) , the Terbinafine resistance locus protein ( Yip1 ) ( LdBPK_230280 ) , and the PTR1 gene ( LdBPK_230310 ) . These genes are present in the H-region and frequently amplified in some drug resistant cell lines [44] , however they were unchanged , diploid , in all the other parasites belonging to NE and SE populations . This is similar to CN analysis of antimony resistant and sensitive L . donovani strains from Nepal where amplification was not observed for the H-region genes [16] , even though MRPA , and in some cases the PTR1 gene , were shown to be amplified in naturally resistant parasites examined by other techniques [45 , 46] . Finally , CNV was also found in part of a 15 . 8 kb region located on chromosome 36 known as the MAPK locus ( LdBPK_366740 , LdBPK_366750 , LdBPK_366760 and LdBPK_366770 ) . Amplification of this region was found in antimony resistant L . donovani from Nepal and associated with higher gene dosage in drug resistant lines [16] [47] . Interestingly , CN of 3/4 genes found in this locus were significantly lower ( p ≤ 0 . 5 x 10−7 ) in the SE and SE-like NE strains/clones than the NE strains/clones ( S8 and S12 Tables ) . No significant different in CNV between the NE and SE parasites , CN = 2 in 40/41 strains and clones , was observed in the case of the histidine secretory acid phosphatase ( LDBPK_366770 ) which is considered part of the MAPK-locus and amplified in antimony resistant parasites [16] . The only exception was seen with the SE-like NE strain ( LDS373bm ) that show a complete deletion of LDBPK_366770 , as well as LDBPK_366780 ( CN = 0 ) . When haploid gene CN is calculated , taking into account both gene CNV and chromosome ploidy , most of the differences between the NE and SE parasite populations ( Table 3 and S13 Table ) still remain even though chromosome polyploidy is statistically more common in SE parasites .
Genome wide sequencing ( WGS ) and analysis of pathogens has proven widely useful for investigations on molecular epidemiology and evolution; genotype—phenotype associations; identification of genes involved in various biological processes such as drug resistance and virulence; as well as new targets for drug and vaccine development [16–18 , 21 , 48 , 49] . Developments in next generation sequencing over the last two decades have provided a relatively low cost , fast pipeline for the exploration and comparison of Leishmania genomes . This study focused on comparison and analysis of WGS data from a large number of L . donovani strains and clones ( n = 41 ) originating from fifteen VL patients in southern and northern Ethiopia . Previous studies on population genetics using multilocus microsatellite typing ( MLMT ) or individual gene sequences suggest that L . donovani is comprised of distinct populations associated with specific geographic regions in East Africa [7 , 15 , 50] , and that African parasites are in large part distinct from those found on the Indian subcontinent [13 , 17] . Differences have also been documented in the parasites , sand fly vectors and host responses between these geographic regions e . g . , sensitivity of antigen based serodiagnostic assays [51] , clinical response to paromomycin [6] , incidence of PKDL [52 , 53] . Our whole-genome sequence data confirms the presence of two very different populations of L . donovani in the region , exemplified by an absolute difference of ~15 , 000 SNPs between the NE and SE populations . These parasite populations likely arose due to unique evolutionary pressures associated with local sand fly species , hosts , reservoirs , ecology , and other factors . A unique advantage of whole-genome data is that it gives us a comprehensive catalog of genetic variation that could underpin these adaptations . When chromosome aneuploidy is analyzed , a picture appears suggesting great diversity among the Ethiopian strains within each population . This picture is unlike that shown for the Ethiopian reference strain LV9 where all 35 chromosomes , except for chromosome 31 , were disomic [18] . This reference strain was extensively passaged in numerous laboratories since first isolated from a VL patient in 1967 . Unlike the reference strain , all the isolates used in this study were rapidly cryopreserved and only briefly cultured under identical conditions prior to DNA purification for WGS , yet they still show unique , highly variable karyotypes compared to strains from the same geographic population or strains isolated from different organs of an identical patient . This indicates that chromosome aneuploidy , unlike SNPs , cannot be used to map leishmanial population genetics . Interestingly , MLMT analysis of L . donovani strains from Libo Kemkem , a previously non-endemic region in NE where an outbreak of VL occurred in 2004–2005 , also demonstrated high genetic diversity among parasites isolated from patients , including a unique genetic group that shared several alleles with strains from SE [50] . Leishmania chromosome ploidy in individual cells can change rapidly in response to environmental conditions , even routine culture , resulting in mosaic aneuploidy [54] , however in this study individual clones generated from patient strains generally showed similar karyotypes clustering together , and when examined , were highly similar to the parental patient isolate . These results suggest that the average karyotype for each strain is relatively stable i . e . , minimally affected by culturing and/or cloning prior to DNA extraction . Downing et al [16] also reported that chromosome aneuploidy was stable in culture for 17 Nepalese L . donovani strains even though they also showed diverse karyotypes . This suggests that the karyotypes observed for the parasites in this study are probably very similar to the original patient isolate , assuming changes don’t take place upon differentiation from intracellular amastigote to extracellular promastigote . However , this can only be confirmed by direct measurement of aneuploidy in parasites taken directly from patients without prior culturing , something not currently possible . Similar to previous reports , chromosome 31 was supernumerary in all 41 Ethiopian strains and clones studied . This appears to be a defining characteristic in all Leishmania species examined so far [16 , 18 , 19 , 25 , 55] . As genes involved in iron metabolism and related functions are highly enriched on chromosome 31 , it has been suggested the chromosome polyploidy arose to expedite iron uptake , and that expression of Iron–Sulfur proteins that are important in oxidation-reduction reactions , and synthesis of metabolites essential for parasite survival and growth [55] . One interesting finding is that strains concurrently isolated from different organs of identical patients , in the two cases examined , have significantly different karyotypes . Thus , while clones and/or parental strain from spleens of each patient clearly grouped together , they clustered separately from clones originating from the skin of the same patient . While changes in specific chromosome ploidy associated with parasite tropism were not identified , these results suggest that the aneuploidy patterns observed are a result of parasite origin ( spleen or skin ) , and the differing conditions , perhaps temperature or host immune responses , to which the parasite is exposed . SNP analysis , similar to MLMT [15] , clearly shows that the Ethiopian L . donovani strains group , in large part , into two main populations , NE and SE , delineated by geography rather than clinical history ( VL or HIV-VL co-infection; spleen or skin ) . Interestingly , the NE population appears to be more polymorphic than the SE population ( Figs 2 and 3 ) , reflecting the finding from MLMT data that inbreeding is higher for SE strains than NE strains [15] . In most cases , clones generated from an individual strain ( GR363sp/sk , GR364sp/sk , GR383 , GR356 , AM560 , etc ) , show more limited genetic polymorphism than that observed between strains , generally clustering together regardless of the method used for analysis ( chromosome aneuploidy , SNPs or gene CNV ) . This was the case even when the patient strain ( s ) were isolated from different organs , such as skin and spleen , of the same HIV-VL co-infected patient , showing that the genotypes present in visceral organs can spread systemically in immunosuppressed patients to the skin where they get transmitted to sand flies . Only in one case , GR364sk/cl . II , did a cloned line fail to cluster with other clones generated from the patient strain . Instead , this clone grouped with SE strains both by SNP and CNV analysis . While contamination during cloning can’t be ruled out , parasites isolated from HIV co-infected patients have been shown to be more polymorphic than those isolated from patients with VL , and differences following patient treatment have been noted [56–58] . The chromosome karyotype and SNPs for this clone are distinct from all the SE strains suggesting that contamination , if it occurred , did not take place during generation of the cloned line . SNP analysis also identified three strains , AM422 , AM553 and LDS373bm , that didn’t fall , as expected , together with their respective geographic genotypes , SE and NE . LDS373bm and LDS373sp were isolated in parallel from different organs , bone marrow and spleen respectively , of the same HIV co-infected patient . The latter parasite ( sp ) is genetically similar to other parasite strains belonging to the NE population , while the former ( bm ) belongs to another genotype . These parasites are also different by k26 PCR typing of the HASP B repeat region [7] . This patient was apparently infected by at least two genotypes , with the genotype present in the bone marrow perhaps less virulent and only surviving in immune suppressed hosts . While several reports using MLMT , multilocus sequence typing and kDNA RFLP show that HIV-VL patients can be sequentially infected with genetically different parasites [58–60] , to our knowledge this is the first time that an HIV-VL patient was shown to be simultaneously infected with two genetically different parasites . The amplicon ( 290 bp ) seen for LDS373sp was typical of most NE strains examined ( 37/41 ) , while for LDS373bm it was larger ( 410 bp ) , and observed in 4/41 NE strains , all HIV-VL co-infected patients . WGS of other parasites exhibiting the 410 bp amplicon was not carried out . It would be interesting to analyze more of these parasites and see if they form a separate genetic group . AM422 and AM553 , both isolated in SE , fell outside the main NE and SE populations when SNPs were analyzed by two methods ( Figs 2 and 3 ) . Neither of these isolates was from patients co-infected with HIV . AM422 showed a k26 PCR amplicon typical of NE strains ( 290 bp ) and originated in the Omo valley near the border with South Sudan , while AM553 had a unique k26 amplicon ( 360 bp ) . The unique SNP profiles for these two isolates suggest that additional genotypes are circulating in SE , perhaps a result of the more varied ecology in this region . Gene CNV analysis also identifies differences that are typical of each geographic parasite population , NE and SE . Candidate genes that can be attributed to essential biological processes like drug resistance , virulence and parasite viability demonstrate differential CN among SE and NE strains and clones . While it is not clear which environmental and host factors resulted in the selective amplification of different genes in the NE and SE populations , many of them are essential genes important for parasite survival . Amplification or deletion of specific genes may give the parasites a growth advantage in the sand fly vector or human host . In the NE parasites , there are three times more copies of folate/biopterin transporter ( FBT ) genes on chromosome 10 . Leishmania are folic acid auxotrophs , and LDBPK_100400 is a homologue to the Leishmania infantum FT1 transporter that was defined as the main folate transporter in this Leishmania species . It is also known that FT1 transporter expression is upregulated in log phase of promastigote stage [34 , 44] , the stage found in sand fly midgut . Therefore , increased folate concentration in sand fly midgut may result in better parasite growth in the vector and provide the parasite with a better chance for survival and infection .
This study was conducted according to the Helsinki declaration , and was reviewed and approved by the Institutional Review Board ( IRB ) , Medical Faculty , Addis Ababa University . Written informed consent was obtained from each adult study participant . For this work 18 L . donovani strains isolated from 15 patients with VL in Ethiopia during the years 2009–2010 were selected for WGS ( S1 Table ) . The selection was based on three criteria: 1 ) geographical origin ( northern or southern Ethiopia ) ; 2 ) Patient's pathology such as HIV/VL co-infection versus VL; and 3 ) source of parasites , skin versus spleen . Parasites were cultivated in M199 medium with supplements and rapidly frozen [7] . Additional Ethiopian ( GR373 [7] ) and Sudanese ( LEMS3570 , kindly provided by Prof . Patrick Bastein , National Reference Center of Leishmania , University Hospital Centre of Montpellier , France ) strains were included in analysis of FT1 copy number , and are also listed in S1 Table . All parasites used in this study were characterized by ITS1 - , cpb—and k26—PCR ( [7] and S4 Fig ) . Eight patient strains were cloned prior to DNA extraction for WGS . The cloning procedure was carried out essentially as described [61] . DNA was purified from Leishmania promastigotes that were harvested in their stationary growth stage in ~20ml M199 medium . DNA extraction was carried out as described by [7] Genomic DNA was sheared into 400–600-base pair fragments by focused ultrasonication ( Covaris Adaptive Focused Acoustics technology ( AFA Inc . , Woburn , USA ) ) and standard Illumina libraries were prepared . 100 base pair paired end reads were generated on the HiSeq 2000 v3 according to the manufacturer’s standard sequencing protocol [62] . Raw sequence data was deposited in the European Nucleotide Archive with the accession number ERP016010 . Sequence reads were mapped against the reference genome Leishmania donovani_21Apr2011 [16] using SMALT ( version 0 . 7 . 4 https://sourceforge . net/projects/smalt/ ) to produce bam files . SMALT was used to index the reference using a kmer size of 13 and a step size of 2 ( -k 13 -s 2 ) and the reads aligned . Reads were mapped if they had an identity of at least 90% to the reference genome and mapped uniquely to the genome . Reads in pairs were mapped independently , and marked as properly paired if they mapped in the correct orientation no more than 1 . 5 kb apart . PCR duplicate reads were identified using Picard v1 . 92 ( 1464 ) and flagged as duplicates in the bam files . Aneuploidy was predicted based on whole chromosome median read coverage . For the normalization of median read coverage over all 36 chromosomes for a given strain , the average median coverage of four stable diploid chromosomes ( chromosome 30 , 32 , 34 and 36 ) was calculated and taken as the mean read coverage for a diploid chromosome ( DCmean ) . These four chromosomes have been previously shown to be diploid in almost all L . donovani isolates examined , and have been used for prediction of chromosome copy number [18 , 20] . The predicted chromosome copy number is calculated as the fold change compared to DCmean . This prediction was applied to all 41 L . donovani sequences over 36 chromosomes , and saved in a 41*36 chromosome copy number matrix . We used R ( version 3 . 1 . 3 ) [63] to evaluate of similarities and differences between strains and clones , and their chromosome aneuploidy patterns and computed a heat map over the chromosome copy number matrix with R heatmap . 2 ( ) function from the gplots ( version 2 . 17 . 0 ) R package . The numerical data for the creation of the heat map ( Fig 1 ) is given in the supporting information ( S2 Table ) . Median chromosome ploidy was used to compare average ploidy between NE and SE strains in Table 1 . For isolates with multiple clones , average chromosome ploidy was calculated by determining the median somy of all the clones from an individual strain separately for each of the 36 chromosomes ( S2 Table ) . For the identification of population typical SNPs a procedure was implemented based on SNP and indel calling with the Genome Analysis Toolkit ( GATK version 3 . 1 ) [64] , VCFtools ( version 0 . 1 . 12b ) [65] and a custom R script based on Bioconductor packages ( www . bioconductor . org ) ( Release ( 3 . 2 ) ) . The parameters for the first filtering procedure with GATK were set as follows: Emission confidence threshold > 10 , Calling confidence threshold >50 , read-depth > 500 . A calculation of level of similarity between all 41 samples based on SNP profiles was computed with VCFtools , and processed with R based procedures into a similarity matrix . Finally , this matrix was visualized with heatmap . 2 ( ) function from the gplots R package . Principal component analysis ( PCA ) following pruning of SNPs with high linkage disequilibrium was run using the Bioconductor package SNPRelate [26] . For the creation of unique SE or NE SNP profiles , only SNPs that were identified in >4 or >7 of the SE or NE clones and strains , respectively , were taken for final analysis . This protocol created a consensus SNP profile for each parasite population , as repetition of SNPs in more than 1/3 of the strains and clones for each population supported the accuracy of SNP calling and served as an additional quality control step . As a final step , unique SNP profiles were detected with VCFtool for each population . Unique SNPs present in coding regions that affect protein translation , namely non-synonymous or nonsense mutation ( s ) that change the amino acid or cause a stop codon were identified by a self-implemented R procedure based on Bioconductor packages . The mean absolute number of SNPs was compared between the SE and NE parasite populations , as well as to the Indian reference strain . Mean absolute SNPs for an individual patient isolate was calculated by averaging the SNPs from all clones of the respective strain . Variation in the number of SNPs between clones of an individual isolate was small , and % standard error varied from = 0 . 34–6 . 0 x 10−3 , except for GR364sk ( % s . e . = 0 . 064 ) when the atypical clone GR364sk/cl . II was included . In the absence of the atypical clone the % s . e . = 0 . 001 . The detection of copy number variations ( CNV ) and aberrations was done using the R- bioconductor [66] ( www . bioconductor . org ) package cn . mops ( version 1 . 16 . 1 ) ( Copy Number estimation by a Mixture Of PoissonS ) . cn . mops detected copy number variation as the normalized read depth variation at a certain genomic position over all 41 strains and clones . For that cn . mops calculated the read count matrices across all BAM files . For this analysis , the genomic window length was set to 5 Kbp and used as a sliding window for the prediction of genomic CNV . Therefore , a genomic position of certain strain or clone is considered as one with "CNV" if it shows a significant change in normalized read depth ( > or < two i . e . , diploidy ) in a window length of 5 Kbp compared to other strains or clones at the same given genomic position . Further analysis genomic CNV that is localized in coding regions was carried out . Parasites 2 x 106 / ml were added in triplicate to 96-well plates and incubated with 0 . 5 mg/ml MTX ( Sigma catalog number M8407 ) and in non-drug treated medium in final volume of 200 μl for 66 hours at 26°C . AlamarBlue ( 25 μl/well; AbD Serotec ) was added and the viability was measured after four hours ( λex = 544; λem = 590; Fluroscan Ascent FL , Thermo ) [67] . The percentage of killing was calculated as the fraction of fluorescence level of MTX treated wells compared to the non-drug treated wells . The polycistronic folate/biopterin transporters ( FT ) on chromosome 10 have high DNA sequence similarity [29] . FT1 ( LDBPK_100400 ) dual priming oligonucleotides ( FT1-DPO ) were used to specifically evaluate genomic CN for this gene by qPCR . FT1-DPO primers , forward FT1-DPO 5'-CGCCAGAACCCGAAGCCTGIIIIIGCACTGG-3' and reverse FT1-DPO 5'-GTTCATCACAGTCGCGATGAGTIIIIIAATCATTATG-3' , were designed to include a polydeoxyinosine linker ( IIIII ) [30] that allows the specific primer annealing to the LDBPK_100400 ( FT1 ortholog ) gene , and not to the other LD FT homologues . Specificity of the FT1-DPO PCR product was confirmed by cloning and sequencing of the amplicon . The L . donovani housekeeping gene alpha-tubulin was used for normalization . The qPCR conditions were the same for both FT1-DPO and housekeeping genes , and was carried out as follows: DNA ( ~10–20 ng ) or no DNA control was added to HRM PCR Kit reaction mix ( 10 μl , QIAGEN GmbH , Germany ) containing the FT1—DPO primers ( 1 μM each final concentration ) , and ultra-pure PCR-grade water ( final volume 25 μl/PCR ) . Amplification conditions were as follows: 3 min denaturation at 95°C , followed by 40 cycles of denaturation 1 s at 95°C; annealing 20 s at 55°C; and extension 1 s at 65°C . HRM Ramping was carried out at 0 . 2°C/s from 65 to 95°C . HRM PCR and analysis were performed using a Rotor-Gene 6000 real-time PCR analyzer ( Corbett Life Science , Australia ) . All reactions were carried out in duplicate and a negative-control reaction without parasite DNA was included in each experiment . For the calculation of the FT1 relative copy number ( CNrel ) the threshold ( Ct ) for all FT1 amplified samples were compared with their corresponding alpha-tubulin amplified samples as followed: CNrel = 2Ct ( alphatubulin ) -Ct ( FT1 ) . The CNrel was further normalized based on the mean of the six lowest predicted relative CN . The mean value was considered as GCN = 1 .
|
Approximately 200 , 000–400 , 000 new cases of visceral leishmaniasis ( VL ) occur annually resulting in an estimated 40 , 000 deaths . Almost 90% of the reported cases are caused by the Leishmania donovani occurring primarily in East Africa and the Indian subcontinent . Parasites in East Africa are more polymorphic than those isolated in other regions , and differences in vectors , biotopes and patient response to drugs are found in Ethiopia . Large-scale whole genome sequence ( WGS ) analysis of L . donovani strains and clones isolated from VL and HIV+-VL co-infected patients in Ethiopia was carried out . Single nucleotide polymorphism ( SNP ) and gene copy number variation ( CNV ) analysis shows genetic differences correlated with geographic regions in Ethiopia . These differences are associated with distinct biological processes and molecular functions , and may be associated with genes involved in drug resistance and parasite survival .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"medicine",
"and",
"health",
"sciences",
"immune",
"physiology",
"spleen",
"population",
"genetics",
"ploidy",
"tropical",
"diseases",
"cloning",
"departures",
"from",
"diploidy",
"parasitic",
"protozoans",
"parasitic",
"diseases",
"protozoans",
"leishmania",
"copy",
"number",
"variation",
"molecular",
"biology",
"techniques",
"population",
"biology",
"neglected",
"tropical",
"diseases",
"molecular",
"genetics",
"research",
"and",
"analysis",
"methods",
"aneuploidy",
"genome",
"complexity",
"infectious",
"diseases",
"zoonoses",
"protozoan",
"infections",
"leishmania",
"donovani",
"molecular",
"biology",
"eukaryota",
"physiology",
"leishmaniasis",
"genetics",
"biology",
"and",
"life",
"sciences",
"genomics",
"evolutionary",
"biology",
"computational",
"biology",
"organisms"
] |
2018
|
Genome wide comparison of Ethiopian Leishmania donovani strains reveals differences potentially related to parasite survival
|
RNA-binding proteins ( RBP ) regulate numerous aspects of co- and post-transcriptional gene expression in cancer cells . Here , we demonstrate that RBP , fragile X-related protein 1 ( FXR1 ) , plays an essential role in cellular senescence by utilizing mRNA turnover pathway . We report that overexpressed FXR1 in head and neck squamous cell carcinoma targets ( G-quadruplex ( G4 ) RNA structure within ) both mRNA encoding p21 ( Cyclin-Dependent Kinase Inhibitor 1A ( CDKN1A , Cip1 ) and the non-coding RNA Telomerase RNA Component ( TERC ) , and regulates their turnover to avoid senescence . Silencing of FXR1 in cancer cells triggers the activation of Cyclin-Dependent Kinase Inhibitors , p53 , increases DNA damage , and ultimately , cellular senescence . Overexpressed FXR1 binds and destabilizes p21 mRNA , subsequently reduces p21 protein expression in oral cancer cells . In addition , FXR1 also binds and stabilizes TERC RNA and suppresses the cellular senescence possibly through telomerase activity . Finally , we report that FXR1-regulated senescence is irreversible and FXR1-depleted cells fail to form colonies to re-enter cellular proliferation . Collectively , FXR1 displays a novel mechanism of controlling the expression of p21 through p53-dependent manner to bypass cellular senescence in oral cancer cells .
Cellular senescence is a critical biological process occurring in normal and aging cells either due to developmentally programmed or DNA damage-induced causes . Cancer cells escape senescence by utilizing either transcriptional and/or co-transcriptional gene regulatory processes to control gene expression . For example , transcriptional activators including p53 [1 , 2] promote senescence by activating subset of genes and also get affected by upstream stress responses such as the DNA damage response ( DDR ) . A majority of the transcriptionally activated genes such as p21 ( CIP1/CDKN1A ) , p27 ( CDKN1B ) , p16 ( CDKN2A ) , and PTEN ( Phosphatase and tensin homolog ) are well-characterized for promoting cellular senescence through either activating p53 or p16-mediated senescence pathways [3] . Although changes in transcription play a major role in cellular senescence , the post-transcriptional changes associated with cellular senescence has not been well studied . The post-transcriptional gene regulation is often controlled by RBPs in conjunction with noncoding RNAs [4] . Most importantly , aberrant expression of RBPs can alter the gene expression patterns and , subsequently , involve in carcinogenesis in multiple cancers including HNSCC [5] . A very few RBPs are known to be associated with senescence pathway by controlling mRNA processing , transport , stability , and translation of proteins responsible for senescence in mammalian cells . For example , RBPs like HuR , AUF1 and TTP can directly or indirectly control turnover and translation of mRNAs encoding senescence proteins [6 , 7 , 8] . In addition , the involvement of RBPs in DDR is rapidly growing and now they are considered as the major players in the prevention of genome instability [9] . RBPs prevent harmful RNA/DNA hybrids and are involved in DDR , and many different cell survival decisions . For example , in response to DNA damage , p53 induces RNPC1 expression and PCBP4 [poly ( rC ) -binding protein 4] , which in turn represses translation of the mRNA encoding p53 and stability of the mRNA encoding p21 , respectively [10 , 11] . Thus , RBPs are known to contribute to the cell fate decisions such as apoptosis and/or permanent cell cycle arrest to induce cellular senescence . A pro-senescence approach to cancer therapy is an attractive alternative approach to chemotherapeutic strategies [12] . However , abundant reports indicate that cellular senescence occurs in the pre-malignant stage of oral squamous cell carcinoma ( OSCC ) but is lost once malignant transformation has occurred [13 , 14 , 15 , 16 , 17] . In contrast , stress or oncogene-induced senescence ( OIS ) also reported in OSCC and indicated that OIS and its markers could play a role in OSCC tumor progression [18 , 19 , 20] . Furthermore , OSCC cells expressing high-risk p53 mutations are sensitized to cisplatin therapy by the selective wee-1 kinase inhibitor , MK-1775 , which subsequently promoted mitotic arrest and cellular senescence [21] . Thus , understanding the molecular mechanisms that underpin RBP-mediated senescence may yield invaluable data for the management of OSCC . FXR1 belongs to the Fragile X-Related ( FXR ) family of RBPs , which also includes Fragile X Mental Retardation 1 ( FMRP ) and Fragile X-Related 2 ( FXR2 ) . FXR1 is frequently amplified in chromosome 3q26-27 in lung squamous cell carcinomas [22] . A recent observation indicates that FXR1 is a key regulator of tumor progression and is critical for growth of non-small cell lung cancer cell ( NSCLC ) , and head and neck squamous cell carcinoma ( HNSCC ) [23] . Similar to the functions of other RBPs , FXR1 is involved in mRNA transport , translational control , and mRNA binding via AU-rich elements ( ARE ) or G4 RNA structures [24 , 25] . FXR1 is shown to bind to G4-RNA structure at the 3’-UTR of p21 and reduce its half-life in mouse C2C12 cells [26] . The G4 RNA structure containing human telomerase reverse transcriptase ( hTERT ) and its RNA component TERC RNA [27] , are suppressors of cellular senescence in a variety of cells as deregulation of their function leads to the progressive shortening of telomere [28] . The regulatory mechanisms controlled by RNA G4 structures involve the binding of protein factors that modulate G4 RNAs turnover and serve as a bridge to recruit additional protein regulators . For example , G4 structure forming sequences protect TERC from degradation and interact with RNA helicase associated with AU-rich element ( RHAU ) , a DEAH-box RNA helicase that exhibits G quadruplex-RNA binding and resolving activity [29] . In this report , we have identified that FXR1 , overexpressed in oral squamous cell carcinoma , binds and destabilizes G4 containing RNA p21 and in turn reduces its protein expression in oral cancer cells . Thus controls cell cycle at G0/G1 phase , maintains cancer cell proliferation and evades cellular senescence . In addition , FXR1 associates and stabilizes non-coding RNA TERC resulting in suppression of cellular senescence and increased cancer growth . Thus , FXR1 is an important protein that regulates RNAs such as p21 and TERC to promote cancer progression .
To determine whether expression of RBPs is different in HNSCC , we utilized the cbioportal cancer genomics database ( www . cbioportal . org ) to examine the Cancer Gene Atlas ( TCGA ) in Head and Neck cancer study . We first analyzed copy number variation of the predicted and well-conserved 424 RBPs [30] . The TCGA HNSCC dataset contains tumor samples from 516 patients , of which 302 were analyzed for copy number alterations and mutation status with 5% cut off ( Fig 1A , S1 Table ) . Next , to test the mRNA expression pattern of 424 RBPs , we set an mRNA expression onset of two standard deviations above or below the mean z-score , to identify patients with highly altered RBP mRNA levels . Using an arbitrary cut-off ( RBP EXP > = 1 . 5 ) , we identified 123 RBPs which were altered in 10% ( 51/516 ) or more of HNSCC patients ( Fig 1B , S2 Table ) . Among those shown significant alteration , FXR1 showed a 31% alteration in a combined DNA copy number and mRNA in 279 tumor samples . Moreover , patients without FXR1 mRNA alteration showed a significant ( p<0 . 01 ) overall survival rate compared to the ones with mRNA alteration , by Kaplan- Meier estimates ( S1A Fig ) . DNA copy number status of FXR1 was independently verified by fluorescence in situ hybridization ( FISH ) analysis in a HNSCC tissue microarray ( TMA ) . As shown in Fig 1C ( S3 Table ) , FXR1 is highly expressed in tumor compared to normal adjacent tissues . Next , we used UCSC Cancer Genome Browser to compare the mRNA expression levels of tumor and normal tissues in a large cohort of patients ( Normal = 43 and Tumor = 521 ) . FXR1 mRNA levels along with two other FXR1 families of proteins FMR1 and FXR2 were determined in 521 tumor samples . As shown in Fig 1D ( S4 Table ) , FXR1 and FMR1 mRNAs are significantly ( p<0 . 0001 ) expressed in tumor samples compared to normal . However , we did not observe a significant difference in expression for FXR2 in normal adjacent and HNSCC tumor tissues . Next , we tested the mRNA levels of FXR1 in eight matched tumor vs normal adjacent samples ( obtained from HNSCC patients from MUSC biorepository ) by qRT-PCR ( clinical parameters are tabulated in S5 Table ) . As shown in Fig 1E , FXR1 mRNA is overexpressed in tumor compared to normal adjacent tissues , whereas FMR1 and FXR2 mRNA levels are comparable to their normal mRNA expression . All the values were normalized to 1 corresponding to their normal adjacent tissues . To confirm the above observations , the levels of FXR1 , FMR1 , and FXR2 proteins from eight representative matched HNSCC tumor and normal adjacent samples were analyzed . As expected the level of FXR1 is highly amplified in cancer tissues compared to normal adjacent tissues and we do not see differential expression of FMR1 and FXR2 ( Fig 1F ) . Next , we tested the mRNA levels of FXR1 , FXR2 and FMR1 in eight HNSCC cell lines compared to the normal primary human oral keratinocytes ( HOK , value was taken as 1 ) . As shown in Fig 1G , FXR1 mRNA is significantly ( p<0 . 05 ) overexpressed in HNSCC cells compared to HOK cells , whereas FMR1 and FXR2 mRNAs are not significantly overexpressed . Finally , the protein levels for FXR1 , FXR2 and FMR1 were determined in HNSCC cell lines compared to HOK . FXR1 protein expression is high in all the cell lines tested compared to HOK ( Fig 1H ) . Unlike the mRNA expression pattern , FXR2 does not uniformly express in cell lines ( Fig 1H ) . The FMR1 protein is not detected in these cell lines . Collectively , our data show that FXR1 DNA , mRNA , and protein is amplified and expressed at high levels in HNSCC tumor tissues and cell lines . We have utilized two different shRNA constructs and both shRNAs are able to silence FXR1 protein in HNSCC cells ( S1B Fig ) . We selected shRNA-2 ( TRCN0000159153 ) for further gene silencing experiments in this report . However , in order to delineate the off target effects of shRNAs , we used additional shRNA-1 ( TRCN0000158932 ) to ascertain the important experiments ( S1C , S1D and S1E Fig ) . First , to test whether knock down ( KD ) of FXR1 has any effect on cell viability , we used MTT ( 3- ( 4 , 5-dimethylthiazol-2-yl ) -2 , 5-diphenyltetrazolium bromide ) colorimetric assay . As shown in S1F Fig , a significant decrease in number of viable cells is observed in both UMSCC74A ( p<0 . 05 ) and UMSCC74B ( p<0 . 01 ) cells with FXR1 KD compared to control , indicating FXR1 plays a key role in oral cancer cell viability and/or survival . To investigate the underlying mechanism of reduction in number of viable cells following FXR1 KD , we performed cell cycle analysis of the FXR1 KD and control cells by flow cytometry . As shown in Fig 2A , FXR1 KD induces cell cycle arrest in G0/G1 providing evidence that FXR1 might regulate cell division in oral cancer . Interestingly , FXR1 KD does not induce apoptosis in UMSCC74A and UMSCC74B cells , as demonstrated by the absence of cleaved PARP and Caspase-3 ( S1G Fig ) . Cell cycle arrest is one of the key features of cellular senescence [31] . Hence , to test whether FXR1 KD-induced cell cycle arrest is associated with induction of cellular senescence , we assessed the expression of senescence-associated β-galactosidase ( SA-β-gal ) activity . As shown in Fig 2B , FXR1 KD UMSCC74A and UMSCC74B exhibit increased SA-β-gal staining compared to control cells . In addition , silencing of FXR1 in multiple oral cancer cells also promotes senescence by positive SA-β-gal staining ( S2A Fig ) . Furthermore , to quantify the β-gal enzyme activity , we measured MUG ( 4-Methylumbelliferyl β-D-Galactopyranoside ) conversion by senescence associated β-galactosidase to 4-MU as described by [32] . As shown in Fig 2C , both FXR1 KD UMSCC74A and UMSCC74B cells , the 4MU fluorescence per microgram is significantly high ( p<0 . 05 ) compared to control shRNA treated cells . To confirm that cells underwent DNA damage associated cellular senescence , we used immunofluorescence to study DNA damage . An important step during the cellular response to DNA double stand break ( DSB ) is the phosphorylation of histone H2AX at the break site , giving rise to discrete nuclear foci , termed γ-H2AX foci and also phospho-ATM ( pATM ) foci , accumulation at the break sites and can also be visualized as distinct foci [33] . Here , we silenced FXR1 and estimated the level of γ-H2AX and pATM foci in both oral cancer cell lines . As shown in Fig 2D , the appearance of spontaneous γ-H2AX and pATM foci in FXR1 depleted cells demonstrate that DSBs occur after silencing of FXR1 compared to control shRNA treated cells . Representative quantitative information of the foci formation is shown under each cell line . Cells containing two or more foci are counted as positive [34] . Next , to confirm that depletion of FXR1 promotes cellular senescence; we have used FXR1 knockout mouse embryonic fibroblasts ( MEFs ) for SA-β-gal qualitative assay . As expected , FXR1 KO MEFs showed bright staining of SA-β-gal compared to WT MEFs ( S2B Fig ) . Collectively , our analyses indicate that silencing of FXR1 in oral cancer cells led to DNA damage , cell cycle arrest and cellular senescence . To test if FXR1 regulated cellular senescence occurs through alteration of post-transcriptional gene expression; we analyzed gene expression of senescence markers . As shown in Fig 3A , qRT-PCR analysis of p21 , p27 , p53 , and PTEN revealed that their mRNA levels have increased in the absence of FXR1 in both UMSCC74A and UMSCC74B cells . Intriguingly , the level of TERC RNA has decreased significantly ( p<0 . 05 ) in the absence of FXR1 . Consistent with this analysis the protein levels of p53 , PTEN , p21 , and p27 ( CDKN1B ) increased upon FXR1 KD in UMSCC74A and UMSCC74B cells ( Fig 3B ) . In addition , reduced levels of pAkt ( Ser-473 ) is observed in FXR1KD UMSCC74A and UMSCC74B cells compared with control and total Akt ( Fig 3B ) , indicates that FXR1 regulated cellular senescence is possibly aided through inactivation of phosphatidylinositol 3 kinase/Akt signaling pathway . As we observe an increase in p53 protein upon FXR1 KD ( Fig 3B ) , next we tested whether p53 plays a role in promoting senescence in the absence of FXR1 . Many human tumors are not entirely lacking p53 , but instead they have “hot spot” p53 mutations which serve as tumor suppressors . Here , we used two isogenic oral cancer cell lines in the background of PCI13 where they express wild type ( Wt ) and mutant p53 ( C238F ) , respectively , as described [35] . Fig 3C illustrates the levels of p21 and p53 mRNAs upon FXR1 KD . Both mRNAs exhibit a significant increase in p53Wt cells in comparison with p53 mutant cells . To test the mRNA changes alter the expression of proteins , we tested the protein expression patterns of p53 and p21 in FXR1 KD cells . Interestingly , upregulation of p53 and p21 protein levels are observed in the absence of FXR1 in WT p53 cell line . Moreover , silencing of FXR1 in WT p53 cells exhibit SA-β-gal staining compared to the mutant ( Fig 3E ) . This observation demonstrates that FXR1-regulated senescence utilizes p53 activated senescence pathway in oral cancer cells . Next , to corroborate our observation in Fig 2D that silencing of FXR1 promotes DNA damage; we determined the H2AX expression ( phosphorylation of H2AX at Ser 139 ( γ-H2AX ) correlates well with each double stranded DNA break ) under FXR1 KD condition . As shown in Fig 3F , FXR1 KD UMSCC74A and 74B cells express γ-H2AX compared to control indicating that DNA damage occurs in the absence of FXR1 . Next , to determine whether the senescent protein coding mRNAs are associated with FXR1 to exert their function , we employed RNP IP assay as described [36] . As shown in Fig 3G , both p21 and TERC are associated with FXR1 in comparison with p27 and p53 . FXR1 IP data in the figure is added to show that FXR1 efficiently binds to the beads and elutes out with the bound mRNAs under RNP IP conditions . Interestingly , both the 3’-UTR of p21 and full-length TERC RNAs contain G4 RNA sequences ( S2D Fig ) , identified by using QGRS mapper software [37] . Agarose gel analyses of PCR amplified RNAs obtained from FXR1 RNA IP samples ( Fig 3G ) show that p21 and TERC bind to FXR1 protein ( Fig 3H ) . Altogether , these studies indicate that FXR1 coordinates the expression of several senescence-associated genes; most importantly it binds and regulates the expression of both p21 and TERC in oral cancer cells . First , to estimate the levels of p21 at the DNA copy number , we used FISH analysis in HNSCC TMA . As shown in Fig 4A , compared to normal ( left panel ) , p21 is not amplified in HNSCC TMA tested in this study ( S3 Table ) . Next , the copy number changes of p21 was verified at the mRNA level with the data obtained from Cancer Genome Browser , and as shown in Fig 4B p21 levels are highly comparable with normal tissue samples . The expression of this mRNA is not significant in cancer genome browser . This observation is well correlated with the TCGA data , where p21 ( DNA copy number and mRNA combined ) expression is only 3% from 279 patients . As shown in Fig 4C , p21 levels are downregulated , though not significantly , in eight representatives matched normal adjacent and HNSCC tumor tissue samples . Furthermore , the levels of p21 protein were tested from the same eight representative matched HNSCC tumor and normal adjacent samples . As shown in Fig 4D , p21 is mainly expressed in the eight normal adjacent samples compared to tumor tissues . We did observe a discrepancy in p21 mRNA and protein expression patterns in normal and tumor tissues . In addition to mRNA changes , there is a possibility that p21 protein is altered at the post-translational level . And p21 protein analyses of the tumor samples correlated with the mRNA data shown in Fig 4C . Thus , p21 is downregulated in HNSCC compared to normal adjacent tissues tested here . Second , based on our data in Fig 3G that FXR1 binds to p21 as well as previous report showing association of FXR1 with G4 RNA structure in the 3'–UTR region p21 [26] , we therefore probed the relationship between FXR1 and p21 in HNSCC . Based on our RNA IP data ( Fig 3G ) , p21 is associated with FXR1 . Hence , we planned to determine whether silencing of FXR1 influences the expression of p21 mRNA . As shown in Fig 3A , FXR1 KD has induced the expression of p21 in both the oral cancer cell lines . Next , to test if FXR1 KD was directly correlated with p21 mRNA expression , we used a time course assay . As shown in Fig 4E , 0hrs of post transduction with shFXR1 exhibits a steady and significant ( p<0 . 05 ) increase in p21 mRNA as tested until 72 hrs in UMSCC74B cells . Next , to test the changes in p21 exerted by FXR1 in translation , we tested p21 protein levels at different time points . FXR1 KD promotes p21 protein expression over the course of 0 to 72hrs ( Fig 4F ) . Altogether , these data indicate that silencing of FXR1 promotes the expression of p21 in oral cancer cells . To estimate the post-transcriptional changes caused by FXR1 to control cellular p21 stability , we treated shcontrol- or shFXR1-transduced UMSCC74B cells with the transcription inhibitor actinomycin D ( ActD ) , and measured the half-life of p21 by qRT-PCR . Linear regression on semi-log values of p21 mRNA decay rate in shcontrol-transfected cells provided an estimated half-life of approximately 2:30±0:54 hrs compared to shFXR1 exhibited a statistically significant ( p<0 . 05 , n = 3 ) increased half-life of 4:30±0:48 hrs ( Fig 4G ) . Next , in order to determine the specific G4 sequences in human p21 and their association with FXR1 , first , we measured the G-scores within the RNAs . Based on high and low G-scores , we cloned G4 regions of p21 3’UTR in the 3’UTR of Renilla luciferase plasmid ( S2C and S2E Fig ) . The segment 1 ( seg1 ) of p21 3’UTR has highest G-score compared to seg2 . 3’UTR of human p21 shows different G4 containing regions with high and low G-scores compared to mouse p21 3’UTR where the G4 region is enriched in one location [26] . As shown in Fig 4H , the luciferase activity of seg1 in control cells is lower than seg2 because FXR1 binds and destabilizes seg1 compared to seg2 . However , in the absence of FXR1 seg1 exhibits increased luciferase activity compared to seg2 which corroborates with total mRNA levels as shown in Fig 3A . Furthermore , seg2 in control cells exhibits increased luciferase activity indicating that FXR1 preferentially binds to seg1 compared to seg2 and promote destabilization of the RNA . Next , we wanted to show a direct binding of FXR1 to these luciferase constructs containing seg1 and seg2 of p21 3’UTR by RNP-IP assay . UMSCC74B cells are transfected independently with 3’UTR-empty or 3’UTR-p21seg1 or 3’UTR-p21seg2 . 48hrs of post-transfection , cells are collected for RNP-IP analyses . As shown in Fig 4I , qRT-PCR analysis for luciferase RNA shows that seg1 binds to FXR1 more efficiently ( p<0 . 05 , n = 2 ) compared to seg2 with a low G4 sequences . As shown in S2D Fig , qRT-PCR for luciferase in these input samples shows that the transfection efficiency is comparable in all samples . Thus , silencing of FXR1 in oral cancer cells facilitates an increase in steady-state level of p21 and subsequently promotes its protein expression , indicates that overexpressed FXR1 in HNSCC destabilizes p21 mRNA and reduces its protein expression . First , we determined the TERC DNA copy number ( chromosomal locus is 3q26 . 2 ) status which is independently verified by FISH analysis in a HNSCC TMA . As shown in Fig 5A , compared to normal ( left panel ) , TERC DNA is amplified in multiple loci of the tumor tissue samples ( Fig 5A and S3 Table ) . Next , we tested the RNA levels of TERC in eight tumor tissue samples compared to normal adjacent tissues . Our analyses indicate that TERC is overexpressed in HNSCC tumor tissues compared to normal adjacent tissues ( Fig 5B ) . A similar trend is also observed in TCGA where the combined DNA copy number and RNA expression is amplified in 25% of 279 tissue samples . Collectively , these observations indicate that TERC is overexpressed in HNSCC tissues . Second , our initial analysis presented above demonstrates that FXR1 depletion correlates with downregulation of TERC . Given that TERC associates with FXR1 , we sought out to determine whether FXR1 directly regulates TERC accumulation in HNSCC cells by utilizing RNA turnover pathway . To understand the correlation between FXR1 and TERC levels over the course of the time , we tested both FXR1 and TERC simultaneously in FXR1 KD UMSCC74B cells . As shown in Fig 5C , an equally steady decrease of both TERC and FXR1 is observed under FXR1 depleted oral cancer cells . To estimate the post-transcriptional changes caused by FXR1 to control endogenous TERC stability , we treated shcontrol- or shFXR1-transduced UMSCC74B cells with the transcription inhibitor actinomycin D ( ActD ) , and measured the half-life of TERC by qRT-PCR . Linear regression on semi-log values of TERC mRNA decay rate in shFXR1-transfected cells provided an estimated half-life of approximately 15 . 3±0:58 min compared to shControl exhibited a statistically significant ( p<0 . 05 , n = 3 ) half-life of 26 . 3±2 . 1 min ( Fig 5D ) . Taken together , these observations possibly suggest that the observed upregulation of TERC in HNSCC primarily at the post-transcriptional level through increased RNA stability that is mediated by FXR1 . Next , in order to determine the specific G4 sequences and their association with FXR1 , first , we measured the G-scores within the TERC RNA . Based on high and low G-scores , we cloned full-length and mutant TERC at 3’UTR of Renilla luciferase plasmid ( S2C and S2E Fig ) . When full-length and truncated TERC ( 28 base deletion at 5’-end , TERCmut ) ( S2C and S2E Fig ) are used for luciferase assay , TERC exhibits increased luciferase activity in control cells compared to TERCmut ( Fig 5E ) . However , in FXR1 KD cells , TERC exhibits a decreased luciferase activity compared to TERCmut indicating that FXR1 binds to specific G-rich sequences in these RNAs and possibly controls their turnover . Next , we wanted to establish a direct binding of FXR1 to these luciferase constructs containing TERC and TERCmut by RNP-IP assay . UMSCC74B cells are transfected independently with 3’UTR-empty or 3’UTR- TERC or 3’UTR-TERCmut . 48hrs of post-transfection , cells are collected for RNP-IP analyses . As shown in Fig 5F , qRT-PCR analysis for luciferase RNA shows that full-length TERC binds to FXR1 more efficiently ( p<0 . 05 , n = 2 ) compared to TERCmut with low G4 sequences . As shown in S2D Fig , qRT-PCR for luciferase in these input samples shows that the transfection efficiency is comparable in all samples . As TERC deregulation is often associated with telomere length [38] , down regulation of TERC in HNSCC cells prompted us to determine the telomerase activity by using TRAPeze® Telomerase Detection Kit ( Millipore , USA ) . FXR1 KD cells showed an appearance of the internal control ( 36bp ) band compared to control which is correlated with a reduced telomerase activity ( Fig 5G and 5H ) . We quantified both the internal control ( 36bp ) and the first telomerase activity ( * ) bands in shControl and shFXR1 lanes . The data was normalized against the internal control bands from the two heat inactivated sample lanes for each experiment set , respectively ( Fig 5F ) . Thus , silencing of FXR1 reduces the level of TERC and subsequently interferes with the telomerase activity . Altogether , these data indicate that overexpression of FXR1 in HNSCC play a key role in stabilizing TERC to bypass cellular senescence . Based on the two independent experiments described above , FXR1 concurrently destabilizes p21 ( Fig 4E–4G ) and stabilizes TERC ( Fig 5C and 5D ) to repress cellular senescence in HNSCC . Upregulation of p21 induces cell cycle arrest during replicative senescence in cell culture [39 , 40] . In addition , TERC is an essential RNA component of the telomerase enzyme complex that has been directly implicated in the maintenance of telomere length and in the prevention of premature senescence and aging . In support of this function , TERC-deficient mice displayed short telomeres , chromosomal instability , and premature aging [41] . To test whether these two coordinated events such as down-regulation of p21 and up-regulation of TERC in cancer cells , independently or in combination to control senescence , we overexpressed p21 and silenced TERC by individual and combinatorial transfections in HNSCC cells . Overexpression of p21 by plasmid transfection and silencing of TERC by siRNA were verified by qRT-PCR analyses . As shown in Fig 6A , p21 is overexpressed more than 18-fold ( p<0 . 05 ) and TERC is significantly ( p<0 . 05 ) downregulated in oral cancer cells . We see changes in FXR1 levels after these transfections but the protein levels did not change . In addition , silencing TERC by siRNA does not alter the expression of p21 ( Fig 6A ) . We further confirmed the levels of FXR1 and p21 protein levels in UMSCC74B cells ( Fig 6B , additional cell line UMSCC74A- S3A and S3B Fig ) ; and the protein expression is also quantified as a mean of two separate western blots ( Fig 6C ) . The data indicate that ectopic expression of p21 increases the expression of p21 protein significantly without altering the levels of FXR1 or TERC . Next , to study whether these changes alter cellular senescence , we stained the cells with SA-β-gal . The data indicate that , independent overexpression of p21 did not show SA-β-gal staining , however , silencing of TERC showed weak staining ( Fig 6D ) ( additional cell line UMSCC74A- S3C Fig ) . Quantitation of MUG conversion to 4-MU by senescence associated β-galactosidase for Fig 6D is shown in Fig 6E . To further confirm that FXR1 is a key regulator of senescence in these oral cancer cell lines and it does so by modulation p21 and TERC RNA , we set up the following experiment . As shown in Fig 6F , we treated UMSCC74B cells with shControl and shFXR1 . And at the same time , the treated cells are also treated with shp21 and/or transfected with TERC overexpression plasmid . 72h of post-treatment , the treated cells were stained with SA-β-gal . Strong SA-β-gal staining was observed again in shFXR1 only treated cells . Light staining was also observed in cells treated with both shFXR1and shp21 . Here , the light staining with SA-β-gal is similar to our observation in Fig 6D where the use of siTERC showed light staining in UMSCC74B cells . TERC RNA expression was estimated in all the plasmid transfected and/or shRNA transduced cells ( Fig 6G ) . As shown in Fig 6H , FXR1 and p21 protein levels were determined in the treated cells by western blot analyses . Nevertheless , concurrent overexpression of p21 and silencing of TERC significantly promoted senescence evidenced by staining of SA-β-gal ( Fig 6D ) . Furthermore , the 4MU fluorescence per microgram are significantly high ( UMSCC74A , p<0 . 05 and UMSCC74B , p<0 . 005 ) in those with concurrent overexpression of p21 and silencing of TERC compared to independent changes ( Fig 6E and S3D Fig ) . Taken together , these data indicate that FXR1-regulated repression of senescence involves both down-regulation of p21 and up-regulation of TERC in oral cancer cells . Senescence has been shown to be either reversible or irreversible depending on cell type and exposure to cytotoxic agents [42 , 43] . To test whether FXR1-dependent senescence is reversible or irreversible , we used inducible clones of shcontrol and shFXR1 to silence FXR1 under Isopropyl β-D-1-thiogalactopyranoside ( IPTG , 0 . 5mM ) promoter . First , the stable UMSCC74B cells , transfected with shcontrol and shFXR1 ( MISSION 3X LacO Inducible Non/Target shRNA ) , were treated with 1mM IPTG for 6 days to test the phenotype . Second , IPTG was removed from the medium to induce FXR1 expression back in the cells . The cells were then grown for additional 6 days to test senescence . Under both the conditions , the levels of FXR1 , p21 , and TERC are quantified by qRT-PCR . As shown in Fig 7A , IPTG-shFXR1 treated cells indicate that both FXR1 mRNA and TERC are significantly ( p<0 . 05 ) downregulated and p21 mRNA is significantly ( p<0 . 05 ) upregulated compared to non-induced control cells . However , when IPTG is removed , the RNA levels return back to comparable levels with the non-induced control cells ( Fig 7A ) . Next , the protein levels were measured to ensure that the FXR1 shRNA inducible cells respond to the treatment of IPTG . Protein p21 is increased as FXR1 protein is silenced under the treatment of IPTG compared to control and IPTG removed cells ( Fig 7B ) . Next , we have stained the cells with SA-β-gal to estimate the senescence . The SA-β-gal staining shows an appearance of bluish green stain in both IPTG incubated and removed FXR1 KD cells compared with induced control ( Fig 7C ) . To note , the IPTG removed cells express FXR1 protein comparable to induced control cells ( Fig 7B ) , hence , it was interesting to test whether the cells are reverting back from senescence by estimating their proliferation ability and survival through colony formation assays . As expected , the IPTG incubated FXR1 KD cells fail to form colonies after 18 days ( longer time is given to form adequate number of colonies ) . Surprisingly , IPTG removed FXR1 expressing cells also fail to form colonies in comparison with non-induced control cells which form large colonies ( Fig 7D ) . The number of colonies are reduced from 337 to 118 ( 35% decrease ) upon FXR1 KD . Moreover , IPTG removed FXR1 expressing cells also exhibit reduced colony number of 123 ( 36% decrease ) in UMSCC74B cells ( Fig 7E ) . Taken together , these data indicate that FXR1-regulated senescence is not reversible in oral cancer cells , even after expressing FXR1 back into the cultured cells .
Post-transcriptional control of gene expression is gaining much attention due to the fact that RBPs are critical regulators of genes involved in DDR and genome instability [9] . Till date , there are few RBPs that have been implicated in DDR and functionally involved in promoting or suppressing cellular senescence [44] . In this report , we show that knockdown of RBP FXR1 is a major factor involved in cell cycle arrest and promoting cellular senescence through turnover of two distinct RNA targets in oral cancer cells . These findings indicate that in addition to changing the transcriptional landscape of RNAs through DDR , overexpression of certain RBPs are critically involved in increasing the life span of cancer cells . As RBPs are widely recognized for their extensive roles in several cancer biological processes such as survival , apoptosis and metastasis [45 , 46] , a better understanding of RBPs role in cellular senescence will provide a new insight into the post-transcriptional gene regulation . Firstly , cellular senescence , one of the hallmarks of cancer and aging , can be induced by telomere dysfunction that specific DNA damage , chromatin instability , and oncogene activation [47] . Our findings indicate , specific shRNA mediated knockdown of FXR1 induces the expression of mRNAs of p53 , p27 and p21 and their encoding proteins ( Fig 3A and 3B ) . An increased stabilization of p21 , in particular , is a marker of cancer cell senescence [48] . An increased p21 protein levels is also associated with reduced cell growth in cancer [49] . Interestingly , it has been noted that in mouse C2C12 myoblasts a reduced level of FXR1 promotes p21 expression by association with G4-RNA structures present in the 3' UTR of p21 [26] . Taken together it suggests that the overexpression of FXR1 protein in cancer may aid in an important mechanism for evasion of cellular senescence through reduced mRNA and protein levels of p21 . Although recent work that examined FXR1 in human cancers showed silencing of FXR1 exhibited reduced cancer cell growth in vitro and in vivo [23] , the precise molecular mechanism of FXR1-regulated cancer cell growth was not addressed . Our proposed model ( Fig 7F ) demonstrates that overexpression of FXR1 post-transcriptionally facilitates p21 mRNA destabilization and reduces its expression in HNSCC , possibly promoting cancer cell proliferation . Secondly , cancer cell senescence is shown to be associated with DDR and correlated with p53-mediated gene expression patterns and also telomere shortening in multiple cancer models [44 , 50 , 51 , 52] . Here , we show that , loss of FXR1 results in DNA damage ( Figs 2D , 2E and 3F ) , induces p53 mRNA and protein ( Fig 3A and 3B ) , and ultimately resulting in senescence in oral cancer cells . Increase in p53 and p21 are correlated with DDR-induced senescence [3 , 31] , and our data demonstrate that silencing of FXR1 promotes double stranded DNA breaks by yH2AX foci formation ( Figs 2D , 2E and 3F ) . In addition , upregulation of p21 by the p53 tumor suppressor gene has been well documented [39 , 49 , 53] . Here , we show that FXR1-mediated downregulation of p21 plays a role in repressing p53-dependent cellular senescence . Furthermore , our data indicates that p53 appears to play a critical role in p21 induction in FXR1 depleted cells ( Fig 3C–3E ) . In addition , we have observed destabilization of TERC and slightly reduced telomerase activity ( Fig 5C–5I ) which indicates that TERC degradation could be an important biological process that promotes senescence in part with p21 . Treatment with ActD shows a significant decrease in TERC RNA half-life in FXR1 KD cells ( Fig 5D ) . This data refers that FXR1 plays a role in the stability of TERC which is consistent with previous work identifying RBP Dyskerin as a key regulator of TERC that in turn controls the mammalian telomerase activity [54 , 55 , 56] . Interestingly , Dyskerin is the only well-characterized RBP that has shown to bind to TERC , but our study has now identified FXR1 as another controller of TERC which binds and stabilizes the RNA . Additional work is needed to warrant the recruitment of TERC by FXR1 and how this process controls telomere length in cancer . Finally , studies demonstrate a link between p21 and TERC , increased telomere erosion , and DDR . For example , knockout of TERC causes progressive telomere shortening that persistently activates DDR and leads to numerous abnormalities in stem cell function and accelerated aging [57 , 58] . At the cellular level , DDR promotes a permanent cell-cycle arrest and initiates senescence [31 , 59] . Interestingly , loss of p21 in TERC -null mice with dysfunctional telomeres leads to improved stem cell function and increased lifespan without accelerating tumor formation [60] . In this regard , our findings provide a physiological basis by which FXR1 prevents cellular senescence through loss of p21 and upregulation of TERC . Our data also indicate that , overexpression of p21 alone is not sufficient for promoting senescence in oral cancer cells ( Fig 6D and 6E ) ; it also requires down-regulation of TERC ( Fig 6D and 6E ) . This is also clear from Fig 6F where senescence is observed when only FXR1 alone is knocked down . Correlative with Fig 6D and 6E , we also see some senescent cells where both FXR1 and p21 are knockdown suggesting down-regulation of TERC can still bring about senescence but at a lower degree . RBPs play a major role in genome instability and DDR to control gene expression patterns [45 , 61 , 62] . The action of DDR-mediated activation of p53/p21 activated senescence requires down-regulation of TERC by FXR1 which also provides a basis for RBPs’ role in DDR and genome instability . Studies strongly support that G-4 RNA structures present in telomere RNAs [63 , 64] , play a critical role in promoter activity as well as its expression . Our observation on G4 RNA structures , which are strongly enriched in 3' UTR sequences including that of p21 and full length TERC ( more the G-score stronger the G4 structure , Figs 4H and 4I , 5F and 5G and S2E Fig ) , provides an opportunity to shed light on their importance in senescence and aging . Our data clearly implicate that both G4 structure containing p21 and TERC bind to FXR1 ( Figs 4H and 4I , 5F and 5G and S2E Fig ) , providing a basis for post-transcriptional control of two distinct mechanisms ( Fig 7F ) . Cellular senescence is considered irreversible in the sense that known physiological stimuli cannot force senescent cells to re-enter the cell cycle [59] . Our data supports that FXR1-regulated elucidation of senescence is irreversible based on the colony formation assay ( Fig 7D and 7E ) . Furthermore , FXR1 promotes cellular senescence in WT p53 expressing cells compare to p53 mutant stable HNSCC cells ( Fig 3C–3E ) . Thus , FXR1 possibly plays a role in suppressing p53 for checkpoint control . Therefore , our data highlight an important unifying role of FXR1 towards the p53/p21-TERC-pathway in dictating cell growth over cellular senescence in HNSCC ( Fig 7F ) .
Human tissues were obtained from Hollings Cancer Center ( HCC ) biorepository with written informed consent and local MUSC Internal Review Board approval ( Pro00009235 ( CT ) #101547 ) . Frozen tumor tissues are micro-dissected to assure that > 80% of tumor contained HNSCC . The HNSCC and normal adjacent tissues contained tissue microarrays that are used for the evaluation of FXR1 and p21 , and TERC DNA expression using FISH . Samples are subjected to protein and RNA extraction for immunoblotting and qPCR analyses , respectively . HNSCC cell lines UMSCC-11A , -11B , -74A and -74B were obtained from University of Michigan and SCC4 , SCC9 , SCC25 and CAL27 were obtained from ATCC . Cell lines were routinely grown in Dulbecco’s modified Eagle medium ( DMEM-Hyclone ) containing 10% fetal bovine serum ( FBS ) with 100U/ml penicillin and 100 μg/ml streptomycin . HOK cells ( Science Cell ) were grown in keratinocyte serum-free medium supplemented with BPE and EGF ( Gibco , BRL ) . SCC cell lines were grown in DMEM: F12 ( 1:1 ) containing 400 ng/ml hydrocortisone , 10% FBS , and 100U/ml penicillin and 100 μg/ml streptomycin . Different shRNA constructs for FXR1 ( TRCN0000158932 and TRCN0000159153 ) and p21 ( TRCN0000287021 ) were obtained from Sigma Mission . FXR1 inducible shRNA clone with TRCN0000159153 was obtained from Sigma Mission . p21 , pCEP-WAF1 was a gift from Bert Vogelstein ( Addgene plasmid # 16450 ) and TERC , pBABEpuro U3-hTR-500 was a gift from Kathleen Collins ( Addgene plasmid # 27666 ) , over-expression plasmids are obtained from Addgene . siTERC RNAs ( 100uM; GGGCGUAGGCGCCGUGCUU and CCCACUGCCACCGCGAAGA ) were purchased from Sigma Mission whereas control siRNA ( 20nM; GTTCAATTGTCTACAGCTA ) was from Dharmacon RNAi Technologies . Regular transfection was done with lipofectamine-2000 ( life technologies ) . siRNA transfections were done with HiPerfect ( QIAGEN ) transfection reagent , following the manufacturer’s protocol . FXR1 antibodies were obtained from Cell Signaling Technology ( CST ) and EMD Millipore , FMR1 was from Abgent and FXR2 was from Bethyl Laboratories . p21 and p27 antibodies were from BD Pharminogen . P53 was from Santa Cruz . AKT , p-AKT ( S473 ) , PTEN , γ-H2AX , and GAPDH were from CST . β-Actin was purchased from Sigma . Alexa Fluor 488 was bought from life technologies . SA-β-gal assay kit was purchased from CST . MUG was purchased from Sigma-Aldrich . Horseradish peroxidase-conjugated anti-mouse and anti-rabbit immunoglobulinG were procured from GE Healthcare Biosciences ( Uppsala , Sweden ) . Protein A/G beads were purchased from Santa Cruz Biotechnology . Fugene HD transfection reagent and LightSwitch Luciferase Assay kit ( LS010 ) were purchased from Switchgear Genomics . FISH assays are performed on unstained TMA sections . BAC clones ( FXR1: BAC clones: RP11-314I4 ( green ) RP11-480B15 ( red ) ; p21: RP11-265F6 ( green ) RP11-624F22 ( red ) ; TERC RNA: RP11-990E14 ( green ) RP11-480B15 ( red ) are selected from the UCSC genome browser and purchased through BACPAC resources ( Children's Hospital , Oakland , CA ) . Following colony purification DNA is prepared using QiagenTips-100 ( Qiagen , Valencia , CA ) . DNA is labeled by nick translation method with biotin-16-dUTP and digoxigenin-11-dUTP for 3' and 5' probes and locus and control probes respectively ( Roche , USA ) . Probe DNA is precipitated and dissolved in hybridization mixture containing 50% formamide , 2X SSC , 10% dextran sulphate , and 1% Denhardt's solution . Approximately 200ng of labeled probe is hybridized to normal human chromosomes to confirm the map position of each BAC clone . FISH signals are obtained using anti-digoxigenin-fluorescein and AlexaFluor-594 conjugate to obtain green and red colors , respectively . Fluorescence images are captured using a high resolution CCD camera controlled by ISIS image processing software ( Metasystems , Germany ) . SA-β-gal activity is measured according to the manufacturer’s instructions ( Cell Signaling Technology , Beverly , MA , USA ) . SA-β-Gal activity is detected using X-gal ( 5-bromo-4-chloro-3-indolyl β-D-galactoside ) staining at pH 6 . 0 at 72 hours post-transduction with shRNAs unless otherwise mentioned . Using light microscope , three representative fields are captured under white light for three independent experiments . The senescence associated β-gal activity in UMSCC74A and UMSCC74B is quantified by a method as described elsewhere [32] . Briefly , SA-β-gal is measured by the rate of conversion of 4-methylumbelliferyl-α-D-galactopyranoside ( MUG ) to a fluorescent hydrolysis product 4-methylumbelliferone ( 4-MU ) at pH 6 . 0 . Treated UMSCC74A and UMSCC74B cells grown in 60-mm plates are washed three times with Hank’s balanced salt solution . Cells are then lysed by 200μl of lysis buffer , scraped , transferred to a 1 . 5-ml tube , vortexed , and centrifuged at 12 , 000g for 5min . The clear supernatant is then used for the assay after measuring the total protein by Biorad spectrophotometer . Reaction buffer at 2X strength is mixed with 1 . 7mM of MUG added immediately prior to use from a 34mM stock in dimethyl sulfoxide . For final reaction the 2X reaction buffer ( 150μl ) is mixed with 150μl of clarified lysate ( 100μl of lysate diluted with 50μl of lysis solution ) and carried out at 37°C water bath for 0 , 1 , 2 , and 3 hours . At the end of each time points the reaction is stopped with 400mM sodium carbonate . The stopped reaction mixture is read by using150μl per well in a 96-well plate using a plate reader with excitation at 385 nm , emission at 465nm , and gain held constant at 460 . Normalized SA-β-gal activity is expressed as observed fluorescence divided by micrograms of total protein in the assay . FXR1 RNP IP is performed as previously described [36] with some modifications . Briefly , cell lysates are prepared from exponentially growing UMSCC74B cells . Equal amounts of protein are used ( 750–1000μg ) . FXR1 monoclonal antibody ( Millipore ) or isotype control IgG ( Santa Cruz ) are pre-coated onto protein A/G Sepharose beads ( PAS ) and extensively washed using NT2 buffer [50mM Tris–HCl , 150mM NaCl , 1mM MgCl2 , 0 . 05% Nonidet P-40 ( NP-40 ) , pH 7 . 4] . Individual pull-down assays are performed at 4°C for 1–2 h to minimize potential reabsorbing of mRNAs . For RNA analysis , the beads are incubated with 1ml NT2 buffer containing 20 U RNase-free DNase I ( 15 min , 30°C ) , washed twice with 1ml NT2 buffer and further incubated in 1 ml NT2 buffer containing 0 . 1% SDS and 0 . 5mg/ml proteinase K ( 15 min , 55°C ) to digest the proteins bound to the beads . RNA is extracted using phenol and chloroform , and precipitated in the presence of glycogen . For analysis of individual mRNAs , the RNA isolated from the IP is subjected to reverse transcription ( RT ) using random hexamers and SuperScriptII reverse transcriptase ( Biorad ) . Total RNA is prepared from oral cancer tissues and HNSCC cell lines using Trizol ( Ambion ) or RNeasy mini kit ( QIAGEN ) by following manufacturer’s protocol . qRT-PCR for all m/RNA targets is performed using an Applied Biosystems StepOne Plus system with the SYBR green master mix RT-PCR kit ( SA Biosciences ) . Primer sequences are provided in S6 Table . The cell cycle analyses of UMSCC74A and 74B-FXR1 knockdown cells was performed by flow cytometry using propidium iodide . After 72hrs of shRNA treatment , a total of 50 , 000 FXR1 KD and control cells were fixed and stained with propidium Iodide ( PI ) , and analyzed by fluorescence-activated cell sorting ( BD Fortessa X-20 Analytic Flow Cytometer ) to evaluate the number of cells in different stages of cell cycles . Cell cycle analysis was done using the ModFit LT software . UMSCC74A and 74B-FXR1 knockdown and control cells were washed and fixed with 4% paraformaldehyde . Fixed cells were blocked with 10% normal donkey serum followed by incubation with yH2AX and pATM primary antibodies for 1hr . Finally , the cells were washed and incubated with Alexa Fluor 488 secondary antibody and 4 , 6-diamidino-2-phenylindole . Stained cells were subjected to analysis by using Olympus BX61 Microscope with Green and DAPI-FITC filter . The shRNA mediated 74B-FXR1 knockdown and control cells were used for luciferase assay . Different segments of human 3′UTRs of p21 , TERC , and GAPDH were systematically identified ( S2C and S2D Fig ) based upon the G-scores ( QGRS mapper tool ) and cloned into a luciferase reporter vector system , pLightswitch-3’UTR from Switchgear Genomics . The segments were cloned between Nhe1 and Xho1 sites to express chimeric m/RNAs spanning two of the luciferase p21 3′UTR segments and TERC RNAs based upon high and low G-scores . The luciferase GAPDH 3′UTR and 3’UTR empty vector negative controls were included in all assays . Each construct was transfected in triplicates separately with either 74B-FXR1 knockdown and control cells with Fugene HD transfection reagent . Plates were incubated at 37°C for 48 h post-transfection before being removed . 100 μl of luciferase assay ( buffer + substrate ) reagent ( LightSwitch Luciferase Assay ) was added to each well of 96 well solid bottom white plates , and was incubated at room temperature for 30 min . Luminescence was measured by using a VICTOR3 1420 Multilabel Counter ( PerkinElmer ) and the data obtained was normalized using Lightswitch normalization protocol using GAPDH 3′UTR and 3’UTR empty vector controls . Cell viability rate upon FXR1 KD in UMSCC74A and UMSCC74B cells are determined using MTT cell proliferation assays ( Invitrogen ) . Briefly , post-shRNA transfected 5×103 cells were inoculated into each well of a 96-well plate ( well area = 0 . 32cm2 ) . Right after plating ( considered as 0hr ) and after that every 24h , medium was replaced with experimental medium ( 100μl ) . MTT solution was prepared fresh ( 5 mg/ml in H2O ) , filtered through a 0 . 22-μm filter , and kept for 5 min at 37°C . The MTT solution ( 10μl ) was added to each well , and plates were incubated in the dark for 2 h at 37°C . Then reaction was stopped using MTT solution ( 10% SDS in 1N HCl ) and further incubated overnight at 37°C . Next morning the absorbance was measured at A570 nm using a plate reader ( Bio-Rad ) . UMSCC74B inducible control and FXR1 KD ( two wells ) cells were counted and 1 , 000 cells were plated on a 6-well dish with 1mM IPTG for 9 days . After 9 days IPTG was removed from one well containing FXR1 KD cells and left for another 9 days . At the end the colonies were fixed and stained with crystal violet ( 0 . 5%w/v ) in 20% methanol for 30min , plate was washed , and counted using a microscope . Data are expressed as the mean ± the standard deviation . Two-sample t-tests with equal variances are used to assess differences between means . Results with p values less than 0 . 05 is considered significant .
|
Understanding the mechanisms underlying evasion of cellular senescence in tumor cells is expected to provide better treatment outcomes . Here , we identify RNA-binding proteins FXR1 ( Fragile X-Related protein 1 ) , that is overexpressed in oral cancer tissues and cells bypasses cellular senescence through p53/p21-dependent manner . Once FXR1 is amplified in oral cancer cells , protein p21 is suppressed and non-coding RNA TERC expression is aided , resulting in reduction of cellular senescence and promotion of cancer growth . Here , we demonstrate the importance of FXR1 in antagonizing tumor cell senescence using human head and neck tumor tissues and multiple oral cancer cells including the cells expressing p53 wild-type and mutants . This finding is important as FXR1/TERC overexpression is associated with proliferation of HNSCC and poor prognosis , pointing to possible stratification of HNSCC patients for therapies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"transfection",
"rna-binding",
"proteins",
"medicine",
"and",
"health",
"sciences",
"luciferase",
"senescence",
"enzymes",
"cell",
"cycle",
"and",
"cell",
"division",
"carcinomas",
"cell",
"processes",
"enzymology",
"cancers",
"and",
"neoplasms",
"oncology",
"physiological",
"processes",
"developmental",
"biology",
"organism",
"development",
"head",
"and",
"neck",
"tumors",
"molecular",
"biology",
"techniques",
"research",
"and",
"analysis",
"methods",
"specimen",
"preparation",
"and",
"treatment",
"staining",
"head",
"and",
"neck",
"squamous",
"cell",
"carcinoma",
"proteins",
"oxidoreductases",
"gene",
"expression",
"molecular",
"biology",
"aging",
"biochemistry",
"cell",
"staining",
"cell",
"biology",
"physiology",
"genetics",
"biology",
"and",
"life",
"sciences",
"squamous",
"cell",
"carcinomas"
] |
2016
|
RNA-Binding Protein FXR1 Regulates p21 and TERC RNA to Bypass p53-Mediated Cellular Senescence in OSCC
|
The Caenorhabditis elegans spermatheca is a myoepithelial tube that stores sperm and undergoes cycles of stretching and constriction as oocytes enter , are fertilized , and exit into the uterus . FLN-1/filamin , a stretch-sensitive structural and signaling scaffold , and PLC-1/phospholipase C-ε , an enzyme that generates the second messenger IP3 , are required for embryos to exit normally after fertilization . Using GCaMP , a genetically encoded calcium indicator , we show that entry of an oocyte into the spermatheca initiates a distinctive series of IP3-dependent calcium oscillations that propagate across the tissue via gap junctions and lead to constriction of the spermatheca . PLC-1 is required for the calcium release mechanism triggered by oocyte entry , and FLN-1 is required for timely initiation of the calcium oscillations . INX-12 , a gap junction subunit , coordinates propagation of the calcium transients across the spermatheca . Gain-of-function mutations in ITR-1/IP3R , an IP3-dependent calcium channel , and loss-of-function mutations in LFE-2 , a negative regulator of IP3 signaling , increase calcium release and suppress the exit defect in filamin-deficient animals . We further demonstrate that a regulatory cassette consisting of MEL-11/myosin phosphatase and NMY-1/non-muscle myosin is required for coordinated contraction of the spermatheca . In summary , this study answers long-standing questions concerning calcium signaling dynamics in the C . elegans spermatheca and suggests FLN-1 is needed in response to oocyte entry to trigger calcium release and coordinated contraction of the spermathecal tissue .
Mechanotransduction , the conversion of physical forces into biochemical signals , is a critical component of cell signaling [1] , [2] . Force sensation is essential during organism development and guides cell migration , differentiation , and morphogenesis [3] , [4] . Mechanotransduction is essential for normal physiological functioning of the cardiovascular , musculoskeletal , and digestive systems; for example , blood vessel diameter decreases in response to pressure increases to maintain consistent blood volume flow [5] , [6] . Cytoskeletal proteins are interconnected in a dynamic , cell-wide structure , and are optimally positioned to sense and transduce changing mechanical parameters [7] . In addition to acting as primary mechanosensors , cytoskeletal proteins are required to anchor and organize stretch-activated membrane ion channels [1] . Filamins are large cytoskeletal scaffolding proteins that consist of an N-terminal actin-binding domain ( ABD ) , followed by a species- and isoform-dependent number of immunoglobulin-like repeats ( IgFLN ) [8] , [9] . Human filamins contain 24 IgFLN domains , and mutations are associated with a broad spectrum of human diseases , including periventricular heterotopia ( FLNA ) , boomerang dysplasia ( FLNB ) , and various myopathies ( FLNC ) [10]–[13] . Filamin knockout mice show a similar spectrum of phenotypes [14]–[16] . The Drosophila filamin cheerio is composed of 20 IgFLN domains and is important for formation and function of ring canals and follicle cell motility during oogenesis [17]–[19] . Filamins organize the actin cytoskeleton into an elastic three-dimensional network that is responsible for maintaining cell structure and resisting mechanical forces [20] , [21] . Experimental evidence suggests that filamin may act as a force-sensitive molecular scaffold [8] , [9] , [22] . Filamin contains cryptic binding sites that are obscured by adjacent domains [23] , [24] . Atomic force microscopy data reveal that filamin molecules unfold when stretched and refold when tension is relieved [25] . Stretching of the filamin rod domain exposes binding sites for integrins and other proteins and leads to strengthening of focal adhesions [23] , [26] , and a force-dependent filamin-integrin interaction has been observed in cell culture [3] . In addition to acting as a direct mechanosensor , filamin also acts to connect stretch-activated ion channels , such as polycystins , with the cytoskeleton [6] . Our previous work focused on the initial characterization of a well-conserved C . elegans filamin ortholog FLN-1 [27] , [28] . FLN-1 consists of an N-terminal ABD followed by 20 IgFLN domains , and is expressed in the spermatheca and uterus , where it colocalizes with F-actin [27] , [28] . The allele fln-1 ( tm545 ) deletes a portion of the ABD , and a frameshift disrupts translation of all 20 of the IgFLN domains . Therefore , tm545 is a likely strong hypomorph or a null allele [27] . The most striking phenotype of the fln-1 ( tm545 ) animals is the failure of fertilized embryos to exit from the spermatheca [27] . The spermatheca , as part of the C . elegans gonad , serves as the site of sperm storage and fertilization [29] . It consists of three distinct regions: the distal constriction , a central accordion-like bag , and the spermatheca-uterine ( sp-ut ) valve [30]–[33] . The spermatheca , along with a large portion of the oviduct , is enveloped by a single layer of myoepithelial cells [33] . As oocytes are ovulated over the lifetime of the animal , the spermatheca undergoes numerous cycles of stretching , constriction , and relaxation , making it an ideal system to study the role of FLN-1 in cell response to stretch and coordination of cell signaling in an intact tissue . During each ovulatory cycle , the most proximal oocyte is ovulated into the spermatheca , fertilized , and then released into the uterus [29] . Oocyte entry depends on complex signaling between the oocytes , the sperm , and the sheath cells . LIN-3/EGF is secreted by the proximal oocyte and acts on the proximal sheath cells [34] . In the sheath , LET-23/EGF receptor is predicted to activate PLC-3/phospholipase C-γ , which generates inositol 1 , 4 , 5-triphosphate ( IP3 ) and diacylglycerol ( DAG ) [34] , [35] . The IP3 signal is negatively regulated by IPP-5/inositol 5′-phosphatase and LFE-2/IP3 3′-kinase [34] , [36] . ITR-1/IP3 receptor releases calcium from the endoplasmic reticulum when stimulated by IP3 [34] . Calcium likely controls the sheath cell myosin contraction by regulating troponin and tropomyosin [37] . The contraction of the proximal sheath cells propels the oocyte into the spermatheca , where fertilization immediately occurs [29] . After fertilization , directional constriction of the spermatheca propels the embryo into the uterus [29] . The molecular mechanism responsible for initiating and regulating spermathecal constriction is poorly understood , but PLC-1/phospholipase C-ε [38] is required for this process . Loss of PLC-1 results in trapping of embryos in the spermatheca [38] . PLC-1 , like PLC-3 , generates IP3 and DAG from PIP2; however , PLC-ε enzymes are regulated by small GTPases , while PLC-γ enzymes are regulated by receptor tyrosine kinases [39]–[41] . The specific usage of PLC-3 and PLC-1 in the sheath and the spermatheca suggests that the pathways may be differentially regulated . An increase in cytosolic IP3 likely activates ITR-1/IP3 receptor ( IP3R ) , a tetrameric complex in the endoplasmic reticulum membrane [34] , [42] . IP3 binding to IP3R is insufficient for full activation , which requires concomitant calcium binding [42] , [43] . Activation of one IP3R in turn activates neighboring IP3Rs by elevating the local calcium concentration [42] . Although intermediate calcium concentration stimulates IP3R , high calcium concentration has an inhibitory effect [42] . This biphasic response of IP3R to calcium can create regenerating calcium waves in the presence of constant IP3 levels [42] . We propose that the release of calcium by the IP3R in the spermathecal cells induces constriction of the spermatheca by activating myosin contraction . In contrast to the sheath cells , the spermatheca does not appear to express a muscle myosin [37] . Smooth muscle regulatory components LET-502/Rho-activated kinase ( ROCK ) and MEL-11/myosin light chain phosphatase subunit are required for spermathecal function [44] , suggesting that the spermathecal myosin belongs to the non-muscle myosin class [45] , [46] . NMY-1/non-muscle myosin II is expressed in the spermatheca [39] , and here we show NMY-1 is required for spermathecal constriction . In this study we use GCaMP , a genetically-encoded calcium indicator , to show that oocyte entry stretches the spermathecal cells and triggers coordinated pulses of calcium transients . The calcium transients originate in the distal constriction and appear to propagate proximally across the spermathecal bag . FLN-1 and PLC-1 are required to trigger calcium signaling , and ITR-1 is required downstream of PLC-1 to produce the calcium oscillations . The signal is coordinated across the tissue via gap junctions to produce a directional wave . The directional wave of calcium results in contraction of the actomyosin network and expulsion of the embryo into the uterus . Given the modular protein structure , sub-cellular localization , genetic interaction data , and known mechanosensory functions of filamin , we postulate that FLN-1 is required to convert physical information about the presence of the oocyte into a calcium signal that controls the directional constriction of the spermatheca .
Previous studies have revealed an important role for phosphatidylinositol signaling during ovulation and spermathecal transit in C . elegans , and demonstrated that PLC-1/phospholipase C-ε is required for spermathecal transit [34] , [35] , [38] . PLC-1 generates IP3 , which is thought to trigger calcium release from the endoplasmic reticulum via the IP3 receptor ITR-1 [34] , [38] . We have shown previously that fln-1 ( tm545 ) and plc-1 ( rx1 ) single and double mutants show a very similar phenotype , in which embryos are retained in the spermatheca [27] . Because PLC-1 and FLN-1 are both required in the spermatheca for transit of fertilized oocytes , we explored the possibility that FLN-1 functions in the IP3 signaling pathway to regulate spermathecal function . Strong itr-1 loss-of-function alleles result in ovulation entry defects , complicating observation of spermathecal transit . To circumvent this problem , we used itr-1 gain-of-function alleles [34] , [35] . The itr-1 gain-of-function alleles are located in or near the IP3-binding domain of ITR-1 and are thought to increase the affinity of ITR-1 for IP3 [34] , [47] , [48] . Using brood size assays , we tested five putative itr-1 gain-of-function alleles for suppression of the fln-1 ( tm545 ) brood size defect [27] . itr-1 alleles sy327gf , sy328gf , and sy290gf suppressed the brood size defect ( Figure 1 ) , while sy291gf and sy331gf did not ( unpublished data ) . We chose to focus on the itr-1 ( sy290gf ) allele for subsequent experiments because it affects a well-characterized residue critical for IP3 binding [49] . Biochemical characterization suggests that the sy290 recombinant protein has a two-fold increase in IP3 binding affinity [48] . The itr-1 ( sy290gf ) animals do not exhibit overt ovulation or spermathecal transit defects; however , the sheath cell contractions are more frequent in these animals and they show a reduced brood size ( 173±17 SD , n = 6 ) compared to wildtype animals ( 301±26 SD , n = 14 ) [35] . To control for possible effects of the marker phenotypes we used itr-1 ( sy290gf ) strains marked with dpy-20 ( e1282 ) ( dumpy ) or unc-24 ( e138 ) ( kinker ) . No brood size differences were observed between the differentially marked strains . Similarly , the brood size of fln-1 ( tm545 ) unc-24 ( e138 ) ( 20±4 SD , n = 12 ) animals is not significantly ( p = 0 . 08 , Student's t-test ) different from fln-1 ( tm545 ) animals . fln-1 ( tm545 ) itr-1 ( sy290 ) unc-24 ( e138 ) and fln-1 ( tm545 ) itr-1 ( sy290 ) dpy-20 ( e1282 ) animals have a significantly ( p<0 . 0001 , Student's t-test ) higher average brood size ( 46±22 SD , n = 18 , and 46±12 SD , n = 15 , respectively ) than fln-1 ( tm545 ) animals ( Figure 1 ) . LFE-2 negatively regulates IP3 signaling by phosphorylating IP3 into inositol 1 , 3 , 4 , 5-tetrakisphosphate ( IP4 ) [34] . Therefore , lfe-2 ( sy326 ) , a loss-of-function allele , is predicted to have longer duration or intensity of IP3 signals [34] . Like itr-1 ( sy290gf ) , lfe-2 ( sy326 ) does not result in obvious ovulation or spermathecal transit defects , but does exhibit a reduced brood size ( 174±90 SD , n = 6 ) compared to wildtype animals ( 301±26 SD , n = 14 ) . We speculated that increased IP3 levels in the lfe-2 ( sy326 ) background would also suppress the fln-1 ( tm545 ) spermathecal transit defect . We found that , indeed , fln-1 ( tm545 ) ; lfe-2 ( sy326lf ) animals have a significantly ( p<0 . 0001 , Student's t-test ) increased average brood size ( 43±27 , n = 32 ) compared to fln-1 ( tm545 ) animals ( Figure 1 ) . Because we observed a genetic interaction between fln-1 and components of the phosphatidylinositol signaling pathway , we next examined whether calcium signaling plays a role during spermathecal transit . It has been hypothesized that IP3R-regulated calcium release results in sheath cell contractions , however , IP3R-regulated calcium release has not been observed directly in the sheath or the spermatheca . To monitor calcium levels during spermathecal transit we used GCaMPv3 ( GFP-Calmodulin-M13 Peptide , version 3 ) , a genetically-encoded calcium indicator [50] . GCaMP has been previously used in C . elegans neurons and hypodermal cells to image calcium transients [50] , [51] . We created transgenic nematodes expressing GCaMP under the control of the fln-1 promoter ( xbIs1101[fln-1p::GCaMP] ) , imaged immobilized animals using wide-field epifluorescence with standardized acquisition parameters , and quantified the GCaMP signal by calculating mean pixel intensity ( pixel intensity/area ) and normalizing to the initial fluorescence ( Figure 2A ) . Importantly , animals expressing GCaMP exhibit wildtype oocyte entry , ovulation transit times , and normal brood sizes ( 282±51 SD , n = 6; compare Video S1 and Video S2 ) . Animals expressing regular calcium-insensitive fln-1p::GFP were used as controls to determine whether spermathecal shape changes or photobleaching would affect the GCaMP signal ( Figure 2C , Video S2 ) . No alteration in GFP fluorescence signal due to spermathecal shape changes was observed , and photobleaching was not detected over many hours of imaging ( n = 6 ) ( Figure 2C , Video S2 ) . As an additional control for possible effects of changing cell shapes on measured intensities , we expressed tdTomato and GCaMP in the spermatheca and performed ratiometric imaging . Because the tdTomato signal remained constant throughout the duration of imaging , normalization of GCaMP to tdTomato signal did not result in any significant differences in signal compared to non-ratiometric imaging ( n = 3 ) ( Figure S1 ) . Time-lapse imaging of GCaMP reveals that oocyte entry into the spermatheca initiates a characteristic and reproducible sequence of calcium oscillations ( n = 26 ) ( Figure 2 , Video S1 ) . Out of necessity we focused our analysis of calcium signaling on the first ovulation; however , in wild type animals , generally similar calcium transients are observed in subsequent ovulations ( Figure S2 ) . Oocyte entry into the spermatheca consistently triggers a single pulse of calcium in the sp-ut valve ( Figure 2A′ , Video S1 ) . The single pulse of calcium in the sp-ut valve may serve to constrict the valve to prevent premature exit of the oocyte . Neither fertilization nor egg shell formation are required to initiate spermathecal calcium signaling ( Figure S3 ) . Following complete entry of the oocyte into the spermatheca , the calcium transients increase in intensity as the oocyte progresses through the spermatheca ( Figure 2A and B , Video S1 ) . Embryo exit is concomitant with the strongest calcium pulses , suggesting that the calcium pulses trigger spermathecal constriction ( Figure 2A ) . The final pulse of calcium coincides with constriction of the sp-ut valve following embryo exit ( Figure 2A′ ) . Quantitative analysis of the time-lapse image sequences shows that the calcium transients appear to initiate in the distal spermatheca and propagate proximally ( Figure 2A′–2B′ ) . To determine if the calcium transients are directional we measured the fluorescence intensity in the distal and proximal spermatheca ( Figure 2B ) . Calcium pulses are first detected in the distal spermatheca , and then in the proximal spermatheca several seconds later ( Figure 2A′–2B′ ) . The calcium transients occur in the direction of oocyte movement , suggesting that directional calcium pulses may control spermathecal constriction . The distal spermathecal cells may act as a pacemaker to trigger and synchronize calcium release in other spermathecal cells . We predicted that the observed distal to proximal spread of the calcium signal would require cell-cell communication and tissue level coordination . To test this idea , we used RNAi to sequentially deplete the 25 gap junction subunits [52] , [53] , and determined that loss of the innexin INX-12 results in spermathecal transit defects . In inx-12 ( RNAi ) animals , oocytes enter the spermatheca normally , but variably change direction several times before returning into the ovary or proceeding into the uterus ( Figure 3 , Video S3 ) . Calcium imaging of the inx-12 ( RNAi ) ( n = 4 ) animals revealed that each spermathecal cell is capable of producing calcium pulses , but that the resulting calcium waves are asynchronous and non-directional ( Figure 3A′ , Video S3 ) . The random calcium pulses likely result in the observed uncoordinated spermathecal constriction . These results suggest that a small molecule , such as calcium or IP3 , propagates through the spermatheca via gap junctions to produce synchronous and directional calcium transients . To investigate whether FLN-1 is required for normal calcium signaling during spermathecal transit , we introduced the fln-1p::GCaMP transgene into fln-1 ( tm545 ) animals . Although the initial entry pulse of calcium within the sp-ut valve occurs normally ( Figure 4A and 4A′ , Video S4 ) , filamin-deficient animals fail to initiate calcium transients in the spermatheca itself , with few calcium signals observed during the time normally required for oocyte transit ( n = 19 ) ( Figure 4A , Video S4 ) . Abnormal and highly variable transients are observed in fln-1 ( tm545 ) animals approximately 15 minutes after oocyte entry—well after the time a wildtype zygote would have exited ( Figure 4A ) . These delayed calcium pulses fail to produce significant constriction of the spermatheca ( Figure 4A′ , Video S4 ) , suggesting that the contractile mechanism may be compromised in filamin-deficient animals . These data suggest that filamin is required for timely initiation of calcium signaling and for the contractile mechanism , but not for the calcium release mechanism per se . Homology and genetic interaction data suggest that hydrolysis of PIP2 by PLC-1 generates IP3 in the spermatheca , triggering intracellular calcium release via the IP3R [38] , [54] . Consistent with this idea , plc-1 ( rx1 ) animals fail to produce calcium signals following oocyte entry into the spermatheca ( n = 5 ) ( Figure 4B , Video S5 ) . plc-1 ( rx1 ) animals also do not produce the initial entry pulse of calcium in the sp-ut valve . Likewise , a temperature-sensitive reduction-of-function allele of itr-1 ( sa73ts ) results in abnormal calcium signaling at the semi-permissive temperature of 20°C [55]–[57] . Phenotypes observed range from mild perturbations ( Figure 5A ) to grossly abnormal calcium transients ( n = 6 ) ( Figure 5B ) . The grossly abnormal calcium signaling is of lower intensity , and results in trapping of embryos within the spermatheca . Additionally , itr-1 ( sa73ts ) animals do not produce the initial pulse of calcium in the sp-ut valve during oocyte entry , the timing between pulses is longer , and the calcium release is restricted to the distal spermatheca ( Figure 5 ) . These results suggest that the observed calcium transients in the spermatheca require IP3-regulated release of calcium from internal stores , and are consistent with previous findings in the C . elegans intestine [55] , [56] . Unlike fln-1 ( tm545 ) single mutant animals , which eventually initiate abnormal calcium pulses , fln-1 ( tm545 ) ; plc-1 ( rx1 ) double mutant animals behave like plc-1 ( rx1 ) single mutants and fail to produce any calcium transients ( n = 3 ) ( Figure 4C , Video S6 ) . This suggests that the delayed calcium pulses seen in fln-1 ( tm545 ) animals are generated via the canonical phosphatidylinositol signaling pathway . Although FLN-1 is required for timely initiation of calcium pulses upon oocyte entry , it appears that calcium signaling can eventually be activated by a parallel , filamin-independent pathway . Because gain-of-function mutations that sensitize ITR-1 to IP3 suppress the fln-1 ( tm545 ) brood size defects ( Figure 1 ) , we next determined the effect of these mutations on calcium signaling in the spermatheca . We speculated that increased sensitivity of ITR-1 to IP3 would trigger increased calcium release . itr-1 ( sy290gf ) only has a moderate effect on GCaMP intensity in the wildtype background ( n = 5 ) ( Figure S4A ) , which is consistent with the lack of a strong phenotype . We do not detect overt changes in itr-1 ( sy290gf ) calcium dynamics , such as increased propagation speed nor increased frequency of calcium release; however , it is possible that there are higher frequency changes not captured by our imaging parameters . Surprisingly , fln-1 ( tm545 ) itr-1 ( sy290gf ) double mutants have markedly increased calcium signaling immediately following embryo entry ( n = 3 ) ( Figure 6A , Video S7 ) , and display a novel partial exit phenotype with the embryo held in place by a partially closed sp-ut valve ( Figure 6A′ ) . Sp-ut valve constriction around the zygote during eggshell formation results in bow tie-shaped embryos ( Video S7 ) . lfe-2 ( sy326 ) animals , like itr-1 ( sy290gf ) , have marginally increased intensity of calcium signaling in the wildtype background ( n = 4 ) ( Figure S4B ) . However , the calcium transients in lfe-2 ( sy326 ) animals are variable from animal to animal , which is consistent with our brood size data ( Figure 1 ) , and may reflect incomplete penetrance of the sy326 allele . Similar to the results with itr-1 ( sy290gf ) , fln-1 ( tm545 ) ; lfe-2 ( sy326 ) animals exhibit increased calcium signaling compared to fln-1 ( tm545 ) alone ( n = 3 ) ( Figure 6B , Video S8 ) , and partial exit of embryos from the spermatheca ( Figure 6B′ , Video S8 ) . Importantly , these observations indicate that the fln-1 ( tm545 ) spermatheca and valve may be structurally capable of constriction if sufficient calcium is present . Cell contractility is generated by the actomyosin cytoskeleton , which consists of myosin , myosin regulatory proteins , and F-actin . Two non-muscle myosin regulatory proteins , Rho-activated kinase LET-502 and a subunit of myosin light chain phosphatase MEL-11 , are known to be required for normal spermathecal function [44] . The non-muscle myosin NMY-1 , redundantly expressed with NMY-2 during embryonic elongation , is strongly expressed in the spermatheca [45] , [46] . NMY-1 , MEL-11 , and LET-502 have been extensively studied in the context of embryonic elongation where they are required to fine-tune contractility of the hypodermal cells [44] , [45] , [58]–[61] . We speculated that this contractile module also functions in the spermatheca and is responsible for constriction of the spermatheca . Similar to the phenotype seen in fln-1 ( tm545 ) animals , depletion of nmy-1 by RNAi results in a poorly contractile spermatheca and an sp-ut valve that fails to constrict and completely expel the embryo ( Figure 7 ) . Embryos are pushed out of nmy-1 ( RNAi ) spermathecae through a relaxed sp-ut valve due to back pressure from newly ovulated oocytes . In contrast , in mel-11 ( sb56 ) animals , oocytes fail to enter into a hyper-constricted spermatheca [44] . We speculated that mel-11 ( RNAi ) might produce a weaker phenotype than the sb56 allele . Indeed , mel-11 ( RNAi ) animals are able to ovulate , allowing observation of the spermathecal transit process ( Video S9 ) . Depletion of mel-11 in the spermatheca results in hyper-constriction of the spermatheca around the zygote , rupture of the spermatheca , and escape of the zygote into the body cavity ( Figure 8A , Video S9 ) . The distal constriction and the sp-ut valve also appear to hyper-constrict , forcing the embryo in this unusual direction . The mel-11 spermathecal rupture phenotype is strongly suppressed in the fln-1 ( Figure 8B ) and plc-1 ( Figure 8C ) backgrounds , consistent with the idea that FLN-1 and PLC-1 are required for spermathecal contractility .
Our previous work described the C . elegans filamin orthologs , and established that FLN-1 is required for function of the spermatheca , a smooth muscle-like tissue in the C . elegans gonad [27] , [28] . Filamin-deficient spermathecae are unable to constrict , and as a result trap fertilized embryos [27] . In this study , we show that oocyte entry into the spermatheca triggers calcium oscillations that are likely instructive for spermathecal constriction . We find that FLN-1 , an actin-binding protein and a known mechanosensitive scaffold , is required to trigger timely IP3-dependent calcium release in response to oocyte entry . We identify a gap junction subunit , INX-12 , required for signal propagation across the spermatheca and the non-muscle myosin , NMY-1 , required for spermathecal constriction . Our working hypothesis is that filamin is required in the spermatheca to transduce the physical presence of an oocyte into a biochemical signal , thereby triggering constriction of the spermatheca and expulsion of the embryo ( Figure 9 ) . Constriction of the spermatheca in response to stretch is reminiscent of myogenic response seen in vascular smooth muscle cells , where increased intraluminal pressure in blood vessels results in vasoconstriction [1] , [62] . The myogenic response is triggered via mechanically-sensitive ion channels that stimulate IP3-dependent calcium release . Filamin is required for cytoskeletal anchoring of an inhibitory polycystin channel subunit [6] . Filamin also interacts with other transmembrane channels , such as cystic fibrosis transmembrane regulator ( CFTR ) [63] , Ca ( v ) 1 . 4 subunit of a voltage-gated L-type channel [64] , pacemaker channel HCN1 [65] , G protein-coupled calcium-sensing receptor [66] , and potassium channels Kir2 . 1 [67] and Kv4 . 2 [68] . Filamin therefore appears to be required for normal channel function , and may mechanically couple the channels to the cytoskeleton , as well as controlling their localization [9] , [69] . Our calcium signaling and genetic interaction data are consistent with the possibility that FLN-1 might act as a top-level component in the spermatheca signal transduction pathway ( Figure 9 ) . However , the molecular details of how filamin might initiate this cascade are unknown . One possibility is that filamin may be a necessary adaptor between stretch-gated ion channels and the cytoskeleton . Strain on the cytoskeleton would then be communicated to the ion channels , allowing a brief influx of calcium ions which could activate PLC-1 either directly via its EF hand domain [70] or indirectly through a calcium/calmodulin-activated protein . In addition to connecting the stretch-gated channels to the cytoskeleton , filamin might also scaffold downstream effectors required to sense or amplify ion channel opening . Another possibility is that filamin is a direct mechanosensor , and that stretch of the spermathecal cells by oocyte entry directly stretches the filamin molecule , thereby revealing cryptic binding sites . Evidence from biophysical experiments with purified components [22] , [24] , and study of the mechanosensory role of filamin in the context of focal adhesions in cultured cells support this idea [9] , [71]–[73] . Stretch-activated binding sites could localize a RhoGEF , such as Trio [74] , to the cortex and increase the level of Rho-GTP , which has been shown to activate PLC-ε [75] , [76] . Because PLC-ε also contains a GEF domain , activation of PLC-1 may lead to prolonged activation and increased levels of Rho-GTP in addition to IP3 and DAG [77]–[79] . Activation of ROCK and calcium release would both act to promote contraction . Other downstream pathways could also be activated by DAG and calcium , such as Protein Kinase C ( PKC ) [80] . Filamin may perform a partially separable signaling and structural role in the spermatheca . We have shown previously that loss of filamin results in a progressive disorganization of filamentous actin in the spermatheca ( Figure 9 ) [27] . F-actin organization is relatively normal initially; however , filamin is required to maintain cytoskeletal structure as the spermatheca is repeatedly stretched by incoming oocytes [27] . Because our calcium measurements are made during the first ovulation , before the actin cytoskeleton becomes grossly abnormal , and because calcium signaling can be strongly disrupted , for example , by loss of PLC-1 , in spermathecae with intact actin cytoskeletons , we suspect that the calcium signaling defects in filamin-deficient animals are not simply a consequence of cytoskeletal defects , but we cannot entirely exclude this possibility . While our results suggest FLN-1 is needed to trigger normal calcium release in the spermatheca , FLN-1 may be acting in parallel with PLC-1 to activate calcium release via ITR-1 . We show itr-1 ( sy290gf ) and lfe-2 ( sy326 ) ameliorate the effects of fln-1 ( tm545 ) , suggesting that they function downstream of fln-1 . Consistent with this result , over-expression of LFE-2 under a heat-shock promoter results in an exit defect similar to fln-1 ( tm545 ) [34] . The brood size defect of plc-1 ( rx1 ) animals is not suppressed by itr-1 ( sy290gf ) nor lfe-2 ( sy326 ) , presumably due to complete absence of IP3 [38] , [54] . This suggests that fln-1 ( tm545 ) animals possess sufficient IP3 to activate the sensitized ITR-1 receptor . Therefore a key role of FLN-1 might be to regulate some aspect of ITR-1 response to IP3 , ultimately resulting in calcium release and spermathecal constriction . Although IP3 appears to be needed to initiate calcium signaling , we do not know whether IP3 levels oscillate , or whether IP3 simply triggers the first calcium transient . Increased IP3 levels due to inactivation of LFE-2 , an IP3 kinase , or a hypersensitive IP3 receptor do not cause abnormal calcium oscillations in the wildtype background , suggesting that precise control of IP3 level is not required . Once triggered , IP3R may be capable of generating self-sustaining calcium oscillations [42] , [43] , [81] , [82] . IP3 binding to IP3R stimulates the release of calcium into the cytosol , which initially stimulates IP3R , but becomes inhibitory at high concentrations ( Figure 9 ) [42] , [43] . Endoplasmic reticulum Ca2+-ATPase pumps then remove calcium from the cytosol , returning calcium levels to the stimulatory range . This repeating cycle results in oscillating calcium levels . Sensitivity of the IP3R to IP3 and calcium may be modulated by accessory proteins [43] , which may explain the increasing amplitude of calcium release in the spermatheca . With each round of calcium release , ITR-1 may become more activated , leading to larger pulses of calcium . The calcium oscillations may be terminated by an extrinsic signal or a threshold effect of calcium and IP3 . Our observations suggest that calcium pulses are initiated in the distal spermatheca and spread proximally . Although loss of the gap junction subunit INX-12 disrupts the synchronous transients , all spermathecal cells appear to be capable of producing stochastic calcium pulses cell-autonomously . Gap junctions generally permit passive diffusion of small solutes , such as calcium and IP3 . Interestingly , the diffusion of calcium within a cell is limited to small domains by the buffering effects of calcium-binding proteins [82] , [83] , while the diffusion rate of IP3 is much greater , allowing it to act as a global messenger [84] . Given these diffusion rates it seems likely that IP3 is primarily responsible for synchronization of calcium signaling in the spermatheca . We observed that strengthening and synchronization of the calcium signal coincides with a steady , coordinated contraction of the spermathecal tissue and expulsion of the fertilized embryo . Spermathecal contraction requires the non-muscle myosin NMY-1 . Smooth muscle cell contraction is regulated by phosphorylation of the regulatory myosin light chain ( rMLC ) by MLC kinase ( MLCK ) [85] . The C . elegans genome lacks an obvious MLCK homolog , suggesting that rMLC phosphorylation is regulated by other kinases , such as ROCK ( Figure 9 ) [86] . In C . elegans loss of LET-502/ROCK leads to loss of contractility of the spermatheca [44] , [58] , [87] . Contractility is negatively regulated by dephosphorylation of the rMLC by MLCP , and in C . elegans loss of MEL-11 , an MLCP subunit , leads to hyper-constriction of the spermatheca . Understanding how this contractile module is regulated by calcium signals is an exciting future area of study . In summary , in this study we demonstrate that oocyte entry leads to dynamic calcium signaling and coordinated contraction of the tissue , ultimately leading to expulsion of the fertilized embryo . We further demonstrate that FLN-1 , PLC-1 , ITR-1 and the gap junction component INX-12 are required for normal calcium signaling in the spermatheca . These results establish filamin as a regulator of calcium signaling , and suggest disruption of filamin may result in defective cell response to stretch . This is important because human filamin mutations result in severe myopathies , cardiovascular , and neurological conditions , but it is unclear how loss of filamin results in these diverse pathologies . Our study shows that filamin , in addition to being a cytoskeletal protein , may modulate calcium signaling pathways in spermathecal and other mechanically-sensitive cells . In addition to providing mechanistic insight into how the spermatheca functions , this study helps to establish the spermatheca as an in vivo model system for the study of how cells coordinate tissue-level responses to mechanical input .
C . elegans strains were cultured on NGM agar plates with OP50 Escherichia coli at 20°C . Nematode observations and manipulations were performed at 20°C unless otherwise noted . For a complete list of strains used in this study please see Table S1 . Standard genetic techniques were used to manipulate C . elegans genotypes . Point mutations were tracked with marker alleles . unc-24 ( e138 ) , a weak kinker allele , was used to follow the itr-1 gain-of-function alleles . dpy-20 ( e1282 ) , a dumpy allele , was also used to follow itr-1 ( sy290gf ) to control for any marker phenotypes . unc-57 ( ad592 ) , another weak kinker allele was used to follow lfe-2 ( sy326 ) . Deletion and insertion alleles were genotyped using polymerase chain reaction ( PCR ) . RNA interference was performed by feeding animals dsRNA-expressing HT115 DE3 E . coli as described [27] , [88] . The RNAi bacteria were seeded onto NGM plates supplemented with carbenicillin and isopropyl β-D-1-thiogalactopyranoside ( IPTG ) . Eggs were obtained from gravid hermaphrodites using alkaline hypochlorite solution and placed on the RNAi plates . RNAi targeting constructs for fln-1 [27] , nmy-1 , and plc-1 were constructed by PCR amplification of wildtype cDNA using engineered restriction sites , and subsequently cloned into pPD129 . 36 ( Fire Vector Kit ) . Primer sequences used for plasmid construction are shown in Table S2 . mel-11 RNAi targeting construct was isolated from an open reading frame RNAi library ( Open Biosystems; Huntsville , AL , USA ) . Empty pPD129 . 36 vector was used as a negative control in RNAi experiments . We used RNA interference to individually deplete the 25 predicted gap junction genes [52] , [53] in xbIs1101[fln-1p::GCaMP] animals . RNAi experiments were performed as described above . RNAi targeting constructs were obtained from an open reading frame RNAi library ( Open Biosystems; Huntsville , AL , USA ) or constructed by PCR amplification of wildtype cDNA and subsequent cloning into pPD129 . 36 ( Fire Vector Kit ) . Primer sequences are provided in Table S2 . We used a low-magnification screen to identify animals with distended spermathecae or embryos present in the ovary as indicators of abnormal spermathecal function . We excluded genes that grossly affected animal development or gonad morphology . Primary screen hits were selected for detailed calcium imaging as described below . We define brood size as the number of hatched progeny . The total number of hatchlings was determined by segregating L4 animals to individual , freshly seeded plates . Progeny were counted and aspirated beginning two days after the initial transfer , and continuing for two days after end of egg laying . Brood sizes are reported as the mean ± standard deviation . Two-tailed , unpaired t-tests were used to test for statistical significance between relevant genotypes . Statistical analyses were performed using GraphPad Prism 5 . GCaMP3 was obtained from Addgene plasmid 22692 [50] . PCR was used to amplify GCaMP with primers IK189 and IK190 ( Table S2 ) containing engineered restriction endonuclease sites XbaI and XmaI . The XbaI-XmaI fragment was cloned downstream of the fln-1 promoter in pUN85 [27] to generate pUN107 . pUN107 contains the fln-1 promoter , GCaMP , and the fln-1 3′ UTR . Transgenic animals were created by microinjecting a DNA solution containing 40 ng/µL of pUN107 and 100 ng/µL of pRF4 ( rol-6 marker ) . Progeny displaying the roller phenotype and green fluorescence in the spermatheca were segregated to establish transgenic lines . A strain ( UN1037 ) with low levels of GCaMP expression and moderate transmission frequency was integrated using UV irradiation to generate strain UN1101 xbIs1101[fln-1p::GCaMP] II . UN1101 was outcrossed ten times to create strain UN1108 . Standard genetic crosses were used to introduce xbIs1101 into various genetic backgrounds .
|
During organism development and normal physiological function cells sense , integrate , and respond to a variety of cues or signals including biochemical and mechanical stimuli . In this study we used Caenorhabditis elegans , a small transparent worm , to study filamin ( FLN-1 ) , a structural protein that may act as a molecular strain gauge . The C . elegans spermatheca is a contractile tube that is stretched during normal function , making it an ideal candidate for study of how cells respond to stretch . Oocytes are ovulated into the spermatheca , fertilized , and then pushed into the uterus by constriction of the spermatheca . The ability of the spermatheca to constrict depends on inositol 1 , 4 , 5-triphosphate ( IP3 ) , a signaling molecule produced by the enzyme phospholipase C ( PLC-1 ) that triggers calcium release within cells . In animals with mutated FLN-1 or PLC-1 the spermathecal cells fail to constrict . Using genetic analysis and a calcium-sensitive fluorescent protein , we show that FLN-1 functions with PLC-1 to regulate IP3 production , calcium release , and contraction of the spermatheca . Filamin may function to sense stretch caused by entering oocytes and to trigger constriction . These findings establish a link between filamin and calcium signaling that may apply to similar signaling pathways in other systems .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"animal",
"models",
"cellular",
"structures",
"caenorhabditis",
"elegans",
"signal",
"transduction",
"animal",
"genetics",
"model",
"organisms",
"signaling",
"in",
"cellular",
"processes",
"genetics",
"biology",
"molecular",
"cell",
"biology",
"calcium",
"signaling",
"gene",
"networks",
"cytoskeleton",
"gene",
"function"
] |
2013
|
Filamin and Phospholipase C-ε Are Required for Calcium Signaling in the Caenorhabditis elegans Spermatheca
|
Group A Streptococcus ( GAS ) has developed a broad arsenal of virulence factors that serve to circumvent host defense mechanisms . The virulence factor DNase Sda1 of the hyperinvasive M1T1 GAS clone degrades DNA-based neutrophil extracellular traps allowing GAS to escape extracellular killing . TLR9 is activated by unmethylated CpG-rich bacterial DNA and enhances innate immune resistance . We hypothesized that Sda1 degradation of bacterial DNA could alter TLR9-mediated recognition of GAS by host innate immune cells . We tested this hypothesis using a dual approach: loss and gain of function of DNase in isogenic GAS strains and presence and absence of TLR9 in the host . Either DNA degradation by Sda1 or host deficiency of TLR9 prevented GAS induced IFN-α and TNF-α secretion from murine macrophages and contributed to bacterial survival . Similarly , in a murine necrotizing fasciitis model , IFN-α and TNF-α levels were significantly decreased in wild type mice infected with GAS expressing Sda1 , whereas no such Sda1-dependent effect was seen in a TLR9-deficient background . Thus GAS Sda1 suppressed both the TLR9-mediated innate immune response and macrophage bactericidal activity . Our results demonstrate a novel mechanism of bacterial innate immune evasion based on autodegradation of CpG-rich DNA by a bacterial DNase .
The Gram-positive bacterium Group A Streptococcus ( GAS ) is a leading human pathogen , annually causing over 700 million cases of superficial infections such as pharyngitis or pyoderma , and more than 650 , 000 cases of invasive infections , including the potentially lethal conditions of necrotizing fasciitis ( NF ) and streptococcal toxic shock syndrome ( STSS ) [1] . Increased reports of severe GAS disease in recent decades have been in large part attributable to the emergence of a globally disseminated clone of the M1T1 serotype [2] . M1T1 strains are the most common cause of GAS pharyngitis and are strongly overrepresented in severe cases such as NF and STSS [3] . The ability of invasive GAS to produce life-threatening infections even in previously healthy individuals reflects a diverse array of virulence factors that together allow the bacterium to invade host cellular barriers and resist innate immune clearance [2] , [4] . One important distinguishing feature of the globally-disseminated M1T1 GAS clone compared to less pathogenic GAS strains is the acquisition of a prophage encoding a potent secreted DNase , Sda1 [5] . Sda1 activity has been shown to promote GAS escape from phagocytic killing with DNA-based neutrophil extracellular traps ( NETs ) [6] , [7] , [8] , frameworks of DNA containing antimicrobial peptides , histones and proteases that are generated by neutrophils to capture and eliminate bacteria at tissue foci of infection [9] . To control an infection quickly and to prevent disease progression , timely and accurate recognition of bacteria by the host innate immune system is crucial . Pattern recognition receptors ( PRRs ) such as Toll like receptors ( TLRs ) recognize conserved molecular patterns from pathogens . The Toll-like receptor 9 ( TLR9 ) is located intracellularly and recognizes unmethylated CpG-rich DNA motifs commonly present in microorganisms but absent in the host genome [10] . Due to its intracellular localization , TLR9 was first appreciated to respond to intracellular pathogens such as Listeria monocytogenes and Legionella pneumophila [11] , [12] . However , TLR9 has recently been shown to enhance resistance against the common Gram-positive bacteria Streptococcus pneumoniae [13] and GAS [14] . Following this lead , we hypothesized that the presence of the potent DNase Sda1 in the hyperinvasive M1T1 GAS clone could modify its own unmethylated extracellular CpG-rich DNA fragments and alter TLR9-mediated recognition by host innate immune cells . Combining studies with M1T1 GAS and an isogenic strain with loss of Sda1 expression with macrophages derived from WT and TLR-9 deficient mice , we demonstrate a novel mechanism of bacterial innate immune evasion based on autodegradation of a key pattern-recognition molecule .
DNA was purified from GAS strain 5448 , representative of the globally disseminated hyperinvasive M1T1 clone , and incubated with murine bone marrow-derived macrophages ( BMDMs ) . Cytokine release into the medium was used as readout for BMDM activation . GAS DNA induced time-dependent release of interferon type 1 ( IFN-1 ) , and specifically interferon-α ( IFN-α ) , from the macrophages ( Fig . 1A , B ) , peaking at 12 h of exposure . GAS DNA also induced BMDM TNF-α secretion , with maximal levels already detected after 6 h of incubation and remaining elevated for at least 24 h ( Fig . 1C ) . Induction of IFN-α and TNF-α release by GAS DNA was also dose-dependent ( Fig . 1D ) . In contrast , human DNA did not induce IFN-1 or TNF-α secretion from BMDMs ( Fig . 1A–C ) . We did not detect specific induction of the cytokines IL-6 , IL-1β , IL-10 or MIP-2 from BMDMs exposed to GAS DNA ( data not shown ) . Unmethylated CpG-rich DNA motifs have previously been reported to induce macrophage secretion of proinflammatory cytokines including TNF-α and IFN-1 [10] , [15] . Further studies have shown that macrophages exposed to live GAS , DNA isolated from GAS or antibiotic-killed group B Streptococcus release IFN-β and TNF-α [16] , [17] . However , bacterial DNA has not previously been shown to stimulate IFN-α secretion , a finding relevant to innate immune defense since IFN-α is known to provide protection against Gram-positive bacterial infections [18] . The experiments above showed that GAS DNA , containing unmethylated CpG motifs , but not human DNA , induced IFN-α and TNF-α release by BMDM . Since IFN type 1 secretion is partially mediated by TLR9 [19] , we tested whether cytokine release in murine BMDMs expressing TLR9 [20] , [21] , [22] , occurred in a TLR9-dependent manner . Chloroquine blocks endosomal acidification and is a known inhibitor of TLR9 [23] , [24] . We observed a significant decrease of IFN-α and TNF-α secretion in response to GAS DNA and to the TLR9 agonist ODN2395 in BMDMs pretreated with chloroquine , whereas TLR4-mediated responses to LPS were unaffected ( Fig . 2A ) . Similar results were obtained with the synthetic TLR9 antagonist G-ODN ( Fig . 2B ) . To further corroborate the TLR9 dependency , experiments were repeated with BMDMs extracted from TLR9-deficient mice . Stimulation using the TLR9 agonist ODN2395 induced BMDM secretion of IFN-α and TNF-α only in the presence of a functional TLR9 pathway , whereas responses to LPS were not influenced ( Fig . 2C ) . Similarly , after stimulation with GAS DNA , a significantly lower release of IFN-α and TNF-α was observed from TLR9-deficient compared to WT BMDMs ( Fig . 2C ) . The stimulation of IFN-α secretion from TLR9-deficient BMDMs , albeit at a reduced level , is most likely explained by a ubiquitous interferon response to immunostimmulatory nucleic acids , mediated by cytosolic DNA sensors amongst others [25] . Similarly , recent work shows that IFN-β is secreted after challenge of TLR9-deficient macrophages with live GAS or GAS DNA complexed with RNA [16] . An important characteristic of the hypervirulent globally disseminated M1T1 clone of GAS is the presence of a prophage-encoded secreted DNase , sda1 [5] . Sda1 has been shown to promote M1T1 GAS virulence via degradation of NETs , allowing the bacteria to escape neutrophil killing and the tissue focus of infection , thus facilitating systemic spread of the pathogen [2] , [6] , [7] . Functional TLR9 is important in defense against GAS infection [14] and the DNA size required for optimal stimulation varies among host cells . Whereas B-cells are stimulated by small DNA fragments [26] , macrophages show enhanced uptake and subsequent responses with increasing DNA length [26] . Having observed efficient BMDM activation by crude GAS DNA ( above ) we hypothesized that degradation by Sda1 could reduce stimulation of macrophage and thus be an additional immune evasion function of Sda1 . To test this , we engineered recombinant GAS Sda1 ( rSda1 ) in E . coli . Purification yielded a 45 kD recombinant protein which showed DNase activity at the expected size when analyzed by zymography ( Fig . 3A ) . Recombinant Sda1 degraded GAS DNA in a time and concentration dependent manner ( Fig . 3B–C ) . Recombinant Sda1 at around 4 µg/mL was similarly efficient in degrading DNA as the natively or overexpressed Sda1 in GAS supernatants ( Fig . 3C ) . Degradation of GAS DNA by Sda1 abolished induction of TNF-α and IFN-α in BMDM's ( Fig . 3D ) . DNase Sda1 on its own did not influence cytokine secretion ( Fig . S2 ) . Similarly DNase Sda1 treatment of GAS DNA did not affect the residual level of IFN-α and TNF-α induction when TLR9-deficient BMDMs were studied ( Fig . 4A ) . We speculate that the decreased TLR9-dependent cytokine responses to Sda1-treated GAS DNA was mainly due to decreased average DNA size ( Fig . 3B ) , which has also been shown by others to be crucial for cellular uptake of DNA and subsequent TLR9 stimulation [26] . In addition direct elimination of CpG motifs by the efficient enzymatic action of the bacterial DNase [10] could potentially further contribute to the differences observed . Since it has been reported that Sda1 can degrade RNA [27] and recent work shows that IFN-β is secreted by macrophages after challenge of GAS DNA complexed with RNA [16] we investigated the action of Sda1 against RNA , in addition to DNA , wondering if this could be a two-pronged approach to promote GAS infection . RNA co-incubated with our rSda1 showed no degradation when visualized by agarose gel electrophoresis ( Fig . S1 ) , suggesting that Sda1 possesses negligible or minor RNA-degrading activity under our assay conditions . To study the influence of Sda1 on TLR9-mediated macrophage responses to live GAS infection , BMDMs were challenged with the wild type M1TI GAS parent strain M1 5448 ( M1WT ) , the isogenic GAS DNase sda1 knockout ( M1Δsda1 ) and the sda1 complemented strain ( M1Δsda1pDcsda1 ) using the pDcsda1 plasmid [6] . A significant increase in IFN-α and TNF-α secretion was observed from WT BMDMs challenged with the M1Δsda1 mutant strain compared to the parent and complemented strains ( Fig . 4B ) . The observed Sda1-dependent reduction of cytokine responses to GAS was diminished in TLR9-deficient macrophages ( Fig . 4B ) . Similarly , heterologous expression of sda1 in a less virulent M49 GAS strain diminished BMDM IFN-α and TNF-α secretion in a TLR9-dependent manner ( Fig . 4C ) . Our paired loss- and gain-of-function analyses indicate that Sda1 is both necessary and sufficient to promote GAS avoidance of TLR9-dependent macrophage recognition [10] . TLR9 is activated by CpG-rich DNA motifs present in most bacteria . Evolution of reduced CpG content ( CpG suppression ) has been described in other microorganisms including nonpathogenic viruses , Plasmodium falciparum and Entamoeba histolytica [28] . In contrast GAS DNA possesses a high CpG content . By acquiring a potent secreted DNA-degrading enzyme , GAS has come across an alternative means to circumvent TLR9 activation in the host innate immune response . To date , DNase Sda1 has been appreciated to promote M1T1 GAS resistance to neutrophil extracellular killing due to its capacity to digest NETs [6] , [7] , [8] . Since we here identified a capacity of Sda1 to diminish TLR9-mediated macrophage responses , we hypothesized that the DNase activity could blunt the innate immune killing capacity of macrophages to kill GAS . Mice depleted of macrophages or treated with inhibitors of macrophage phagocytosis cannot clear GAS infections even at relatively low challenge doses [29] , demonstrating the essential first line defense function of these immune cells against the pathogen . WT and TLR9-deficient BMDMs were challenged with live M1 or M49 GAS either expressing or not DNase and total , intra and extracellular bacterial killing was quantified . GAS strains expressing Sda1 survived significantly better in both the total and intracellular killing assays compared to the strains in which Sda1 was not expressed ( Fig . 5A , B and S3 ) . The Sda1-mediated survival advantages for GAS were much more pronounced in WT compared to TLR9-deficient BMDMs . Sda1-mediated resistance to total macrophage killing could be caused by interference with DNA-based extracellular traps , which , we have recently observed , are generated by macrophages [30] though to a much lesser extent than observed in neutrophils or mast cells exposed to GAS . To investigate if the bacterial DNase Sda1 interferes with extracellular killing by macrophages we pretreated the macrophages with cytochalasin D to inhibit phagocytosis . No difference between GAS WT and the isogenic GAS DNase sda1 knockout strains were observed for the extracellular killing indicating that the Sda1-dependent survival advantage seen in vitro is indeed mainly intracellular ( Fig . S4 ) . To further explore the Sda1-dependent survival advantage of GAS intracellularly following phagocytotic uptake into the macrophages , we measured oxidative burst activity , which has been reported to be a TLR9-induced mediator of intracellular killing in murine macrophages [14] . Oxidative burst activity was measured in WT and TLR9-deficient BMDMs after infection with the isogenic pairs of GAS strains either expressing or lacking DNase Sda1 . BMDMs infected with GAS strains possessing Sda1 displayed a significantly reduced oxidative burst response compared to BMDMs infected with GAS strains lacking Sda1 ( Fig . 5C ) . We propose that reduced oxidative burst is an additional mechanism by which Sda1 can contribute to M1T1 GAS resistance to macrophage killing . In order to test if blocking IFN-α and TNF-α can prevent phagocytic killing mediated by GASΔsda1 we repeated the BMDM killing assays with WT BMDM challenged with WT GAS M1 and GASΔsda1 bacteria after having pre-incubated the BMDM with either the neutralizing antibodies against TNF-α or IFN-α or their respective controls . Addition of neutralizing IFN-α antibodies increased the survival of GAS and GASΔsda1 when challenged with BMDMs from WT mice . The effect of neutralizing TNF-α antibodies was smaller and not statistically significant upon challenge with WT GAS and GASΔsda1 mutant bacteria ( Fig . S7 ) . These results suggest that certain cytokines may themselves contribute to enhance the phagocytic killing of bacteria . Viability of the BMDMs was >90% after 4 and 12 h of stimulation with the bacteria at MOI of 1 . No significant differences were observed in survival of WT or TLR9 deficient BMDMs stimulated with either GAS WT or the GASΔsda1 mutant ( Fig . S6 ) . All GAS strains are known to express DNase activity , and some strains produce up to 4 different DNases . As first described by Wannemaker [27] , [31] these proteins were designated DNase A , B , C and D . However the role of theses DNases remained unclear until 50 years later when it was shown that GAS DNase activity , particularly that of GAS DNase D ( now known as Sda1 ) was important for virulence [6] , [8] . By creating knockout mutants of the three DNases present in the GAS MGAS5005 strain [8] , Sumby et al . determined that Sda1 was the most active . Sda1 very efficiently degraded DNA in vitro . In murine skin infection models , engineered GAS strains expressing Sda1 alone were found to be as virulent as wild-type GAS , supporting the conclusion that Sda1 but no other DNases mediate virulence in vivo . The strong activity of Sda1 compared to the weaker DNA-degrading activity of the other DNases found in GAS , may help to explain the pronounced phenotype we have observed in enhancing TLR9-mediated clearance when only Sda1 , and no other DNases , is knocked out . However our data may underestimate the full collective potential of GAS DNases in TLR9-mediated innate immune evasion . To provide in vivo corroboration of the ex vivo experiments carried out using BMDMs , we examined IFN-α and TNF-α levels in skin homogenates of mice infected subcutaneously with GAS . Despite the important contribution of Sda1 to GAS proliferation and necrotic ulcer development in this model [6] , [7] , WT mice infected with the GAS M1Δsda1 mutant showed higher levels of IFN-α and TNF-α in the skin samples than mice infected with the WT parent GAS expressing Sda1 ( Fig . 6A , B ) . Parallel experiments performed in TLR9-deficient mice showed much lower cytokine levels in the infected skin compared to WT mice , again underlining the importance of TLR9 in mediating cytokine responses . However , in contrast to the WT mice , the presence or absence of Sda1 did not affect the level of cytokines produced in response to GAS in the TLR9-deficient mice ( Fig . 6A , B ) . We had shown previously [14] that more bacteria are found in the skin of TLR9-deficient mice compared to WT mice , and that more surviving GASM1 WT bacteria compared to GASM1Δsda1 are present following experimental challenge of WT mice [6] . We also found more WT than ΔSda1 mutant bacteria present following injection into TLR9- deficient mice ( Fig . S8 ) . The observation that the TLR9-deficient mice injected with the GASM1Δsda1 mutant demonstrated similar bacterial counts compared to WT mice could be due to a large initial influx of neutrophils efficiently clearing the DNase-deficient mutant strain within extracellular traps . The increased cytokine levels detected in WT mice injected with GASM1Δsda1 mutant compared to WT bacteria are not explained by differences in bacterial counts , nor do bacterial levels account for increased cytokine levels in WT mice compared to TLR9- deficient mice . In sum , we documented that increased tissue expression of IFN-α and TNF-α in the mouse necrotizing skin infection model occurred in both a DNase- and TLR9-dependent manner . In contrast to our ex vivo data and tissue culture experiments carried out by others [25] , IFN-α and TNF-α secretion in our in vivo experiments was strictly TLR9-dependent . This finding suggests that TLR9 recognition of GAS is of true physiological relevance , and the described TLR9-independent pathways elicited ex vivo may be of diminished importance in the in vivo setting . Our experiments emphasize the critical nature of innate immune recognition at tissue foci of infection . It is important to note that while much evidence exists that IFN-α is beneficial to innate immune cells in combating bacterial infection [18] , if IFN-α is produced systemically at high levels or in an uncontrolled fashion and deleterious effects on antibacterial clearance may be observed [32] . In our work we have focused on the cytokine responses and killing activities of isolated macrophages vs . GAS and the expression of cytokines at the site of GAS subcutaneous infection . We hypothesize that GAS Sda1 contributes to disease in multiple ways , including interfering with TLR9 recognition ( blunting the initial innate immune response ) and degrading extracellular traps ( promoting phagocyte evasion ) . Together , these Sda1-dependent virulence phenotypes increase the risk of bacterial proliferation to produce severe necrotizing infections , septicemia or toxic shock syndrome , where ultimately high cytokine levels develop in response to the uncontrolled infection [33] . Additionally , variation in cytokine responses to GAS superantigens influences the severity of streptococcal toxic shock syndrome [34] . To summarize , we here describe a novel mechanism by which a bacterial pathogen can directly elude TLR9 recognition . The GAS virulence factor DNase Sda1 leads to decreased production of the proinflammatory cytokines IFN-α and TNF-α and to decreased killing efficiency of macrophages , which are key contributors for innate immunity to GAS infection [29] . DNase production is now recognized to be a virulence factor of a number of bacterial pathogens including Streptococcus pneumoniae [35] , Staphylococcus aureus [36] and Pseudomonas aeruginosa [37] and it could be fruitful to determine whether evasion of TLR9-based detection complements NET degradation in the infectious pathogenesis of these species . Previously , inhibition of Sda1 activity by G-actin boosted neutrophil extracellular killing of the WT GAS bacteria and reduced lesion size in the necrotizing skin infection model , providing proof-of-principle that this DNase can represent a pharmacological target for virulence factor neutralization [6] . Our current data , demonstrating that loss of Sda1 enhances both TLR9-mediated innate immune responses and macrophage bacterial killing , provides additional rationale toward such a therapeutic strategy .
C57BL/6 wild-type ( WT ) and C57BL/6 TLR9-deficient mice were bred and handled in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Institutional Animal Care and Use Committee of the University of California , San Diego ( Animal Welfare Assurance Number: A3033-01 ) . All efforts were made to minimize suffering of animals employed in this study . C57BL/6 TLR9-deficient mice were originally developed by Dr . Shizuo Akira ( Osaka University , Japan ) ; WT mice were purchased from Charles River Laboratories . The GAS strain 5448 , a well-characterized M1T1 clinical isolate from a patient with necrotizing fasciitis and toxic shock syndrome [38] and the GAS M49 strain NZ131 [39] were used . In addition , to analyze gain and loss of function of Sda1 , GAS strains expressing Sda1 ( GASM1T1 WT , GASM1T1 Δsda1pDcsda1 and GASM49 pDcsda1 ) and lacking Sda1 ( GASM1T1 Δsda1 and GASM49 WT pDcerm ) were used in the assays as described previously [6] , [40] Growth curves showed that all strains used in the experiments grew identically . GAS strains were propagated in Todd-Hewitt broth ( THB ) ( Difco , BD Diagnostics ) or Todd-Hewitt agar plates . For use in macrophages and mouse challenge studies , bacteria were grown to logarithmic phase in THB ( OD600 = 0 . 4 corresponding to ∼2×108 cfu/ml ) , pelleted , washed and resuspended in PBS or tissue culture media at the desired concentration . GAS genomic DNA was prepared using Bactozol kit ( Molecular Research Center Inc . ) with minor modifications . GAS strains were incubated overnight in THB medium , 2 ml of the overnight culture pelleted and resuspended in Bactozol buffer+50 U mutanolysin and 10 U Proteinase K , then incubated at 45°C for 90 min . Bactozol enzyme was added and the preparation incubated for 60 min at 45°C . From this step on , the standard Bactozol kit protocol was followed . Human genomic DNA was prepared from buffy coats of healthy volunteers from the blood donation center in Zurich , Switzerland . Cells were pelleted by centrifugation at 1000 g for 10 min . Genomic DNA was then extracted using blood and tissue DNA easy kit ( Qiagen ) following the manufacturer's protocol . Remaining RNA was digested by adding RNase during DNA purification . Purity of the isolated DNA , bacterial or human , was confirmed by lack of any cytokine stimulation after digesting the DNA with DNase I ( Roche ) ( Fig . S5 ) . Genomic DNA integrity was confirmed by agarose gel . The sda1 gene was amplified from GAS M1T1 genomic DNA using primers forward 5′-TCGAGCTCTCTAAACATTGGAGACATCTAATTATTCACTCTG-3′ and reverse 5′-TGGTCGACTTATTCTATATTTTCTTGAGTTGAATGATG-3′ . The PCR product was subcloned into vector pQE30 and the newly created plasmid transformed into the E . coli strain M15-pREP4 ( Qiagen ) for protein production . Bacteria were grown to OD600 = 0 . 5 at 30°C in the presence of 100 µg/ml ampicillin and 25 µg/ml kanamycin and the expression of Sda1 induced for 1 h via addition of 1 M IPTG . Bacteria were then harvested , resuspended in 30 ml lysis buffer ( 50 mM NaH2PO4 , 300 mM NaCl , 20 mM imidazole pH 8 ) and lysed by sonication at full power ( 20 cycles of 15 seconds each ) . Cell debris were spun down at 12 , 000 g for 30 min , the supernatant filtered through a 0 . 45 µm PVDF filter , then run on a HiTrap nickel bead column ( GE Healthcare ) at a 1 ml/min speed . The column was then washed with 10 volumes lysis buffer and with 10 volumes wash buffer ( 50 mM NaH2PO4 , 300 mM NaCl , 50 mM imidazole pH 8 ) . Sda1 was eluted with 5 ml elution buffer ( 50 mM NaH2PO4 , 300 mM NaCl , 250 mM imidazole pH 8 ) , dialysed against storage buffer ( 50% glycerol in PBS ) and stored at −20°C . The quality and activity of the purified recombinant Sda1 were checked by performing a zymogram . Briefly , 1 µg of Sda1 and 1 µg of DNaseI , used as a control for activity , were loaded on a 12% polyacrylamide gel containing 10 µg/ml of calf thymus DNA . The gel was washed 2 times in ddH2O and then incubated overnight in 50 mM TRIS·HCl pH 7 . 4 . The gel was then incubated ( 35 hours , 37°C ) in Sda1 reaction buffer ( 50 mM TRIS·HCl pH 7 . 4 , 5 mM CaCl2 ) containing 1 µg/ml EtBr . DNA degradation showed on gel as a dark band and was taken as a proof of nuclease activity . Genomic DNA ( 2 . 5 µg ) was incubated with DNase I from bovine pancreas ( Roche ) at 37°C for 6 hours . Furthermore , 2 . 5 µg of genomic DNA were incubated with purified recombinant Sda1 at 37°C for 0 to 6 hours . After 1 , 2 , 4 and 6 hours , 1 M EDTA was added to stop the reaction and the samples were loaded on an agarose gel or added to the BMDMs . DNA alone and DNase buffer without adding recombinant Sda1 served as controls . Degradation of genomic DNA was confirmed by agarose gel electrophoresis . The GAS DNase Sda1 activity was tested as previously described with minor modifications [6] . 5 µl of a 1∶100 dilution of filtered supernatants taken at OD600 0 . 4 were mixed with 3 µl reaction buffer ( 50 mM Tris-HCl , 5 mM CaCl ) , 20 µl of water and 2 µl of GAS genomic DNA ( 125 ng/µl ) and incubated for five minutes at 37°C . The reaction was stopped by addition of 1 M EDTA . The DNA was run on 1% agarose gel for visualisation . Murine bone marrow-derived macrophages ( BMDMs ) were isolated as previously described [41] with some modifications . Bone marrow cells were collected from mice legs and cultured for 7 days in Dulbecco's modified Eagle's medium ( high glucose ) supplemented with 30% L-929 cell conditioned medium . The adherent cells ( BMDM ) were then collected , split to assay settings , and cultured in Dulbecco's modified Eagle's medium ( high glucose ) until being used for experiments on day 10 . BMDM ( 5×105 ) were seeded into each well of a 48 well plate in 500 µl medium . On day 10 , 2 h before the inoculation of genomic DNA or bacteria , BMDM were washed twice with PBS , and 200 µl DMEM+10% FBS ( 70°C heat inactivated ) were added to each well . GAS strains and genomic DNA , prepared as described above , were inoculated into wells at a multiplicity of infection ( MOI ) of 1 and 5 µg/ml respectively . In addition 80 µl of the DNA samples obtained after digestion with rSda1 for 0 , 1 , 2 , 4 and 6 hours were used . Media without addition of DNA or rSda1 as well as media containing rSda1 alone served as controls . Plates inoculated with bacteria were centrifuged at 800 g for 10 min , incubated at 37°C in a CO2 incubator for 2 h , and penicillin G and gentamicin added to each well to a concentration of 10 and 100 µg/ml , respectively . As TLR9 specific agonist and antagonist , 5 µg/ml CpG-ODN 2395 ( Microsynth , 5′-tcg tcg ttt tcg gcg gcg ccg-3′ with phosphorothioate on all bases ) and G-ODN ( Microsynth , 5′- ctc cta ttg ggg gtt tcc tat -3′ with phosphorothioate on all bases ) were used . Challenged macrophages were incubated at 37°C with 5% CO2 for 12 h . The plates were centrifuged at 800 g for 10 min before the supernatants were taken and stored in −80°C until they were used in ELISA assays . IFN-α and TNF-α ELISA: Levels of IFN-α in culture supernatants were analyzed by a standard sandwich ELISA using a monoclonal mouse IFN-α capture antibody ( Hycult biotech ) and polyclonal rabbit IFN-α antibody ( PBL interferon source ) together with a goat anti-rabbit antibody conjugated with HRP ( Invitrogen ) . A serial dilution of recombinant mouse IFN-α ( PBL interferon source ) was used to calculate the absolute concentration in the supernatants . Levels of TNF-α were measured using mouse TNF-α ELISA kit ( R&D ) following the manufacturer's protocol . Interferon type 1 cell luciferase assay: Luciferase cell reporter assay of IFN-1 was carried out using the LL171 luciferase reporter cell line as described [42] . Macrophages were harvested and seeded in 48 well plates as described above . Two hours before adding bacteria , macrophages were washed twice with PBS and 400 µl of DMEM+2% FBS were added to each well . Logarithmic phase bacteria were added to the wells at final MOI of 1 and plates were centrifuged for 5 minutes at 1500 rpm . For total killing , the plate was incubated for 4 hours . For intracellular killing assays , 100 µg/ml penicillin G and 100 µg/ml gentamicin were added to the wells and the plate was incubated for another 2 h at 37°C in 5% CO2 before macrophages were detached with trypsin and lysed with 0 . 025% Triton-X100 . Serial dilutions of the lysates were plated on THA for enumeration of surviving bacterial colony forming units ( cfu ) . Reactive oxygen species were measured following the protocol described before [14] . An established murine model of necrotizing skin infection was used [43] . Briefly , logarithmic phase GAS were resuspended in PBS , mixed 1∶1 with sterile Cytodex beads ( Sigma ) and an inoculum of 5×107 cfu of GAS was injected subcutaneously into one flank of 10–12 week old WT or TLR9-deficient mice . At day four the mice were euthanized and skin from the lesion was collected , homogenized and IFN-α and TNF-α measured by ELISA and bacterial counts assessed after serial dilutions and plating on THA plates . Data were analysed and edited using the SPSS ( SPSS 11 . 5 Inc . , Chicago , Illinois , USA ) , the NCSS ( Kaysville , Utah , USA ) and Graphpad prism 5 software ( Graphpad Software Inc , La Jolla , California , USA ) packages . Two-sample two-tailed homoscedastic t-tests were used to calculate the indicated p-values except for the animal studies ( Fig . 6 ) for which analysis of variance ( ANOVA ) followed by Bonferroni comparison and a factorial analysis ( 2-way ANOVA ) were used to calculate indicated p-values .
|
Group A Streptococcus ( GAS ) ranks among the top ten human pathogens causing fatal disease . GAS possesses an arsenal of virulence factors that circumvent the primary mammalian defence strategies , the innate immune system . Toll-like receptors ( TLRs ) , allow the host to detect pathogens by recognizing structures or patterns abundant in pathogens but lacking in the mammalian host , including unmethylated CpG-rich bacterial DNA recognized by TLR9 . Here we show that GAS DNA but not host DNA triggers TNF-α and interferon type 1 cytokine secretion by monocytic cells , and that this secretion is dependent on the presence of functional TLR9 . The highly virulent M1T1 GAS clone expresses the virulence factor DNase Sda1 . Sda1-mediated bacterial DNA degradation was shown to prevent TLR9-dependent cytokine release in monocytes , which then fail to effectively phagocytose and kill bacteria . In a mouse necrotizing fasciitis model , the streptococcal DNase Sda1 suppressed TLR9-dependent INF-α and TNF-α induction . Inhibition of TLR9 recognition by a bacterial DNase thus illustrates a novel mechanism of microbial innate immune evasion .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"biology"
] |
2012
|
DNase Sda1 Allows Invasive M1T1 Group A Streptococcus to Prevent TLR9-Dependent Recognition
|
Probe-based or mixed solvent molecular dynamics simulation is a useful approach for the identification and characterization of druggable sites in drug targets . However , thus far the method has been applied only to soluble proteins . A major reason for this is the potential effect of the probe molecules on membrane structure . We have developed a technique to overcome this limitation that entails modification of force field parameters to reduce a few pairwise non-bonded interactions between selected atoms of the probe molecules and bilayer lipids . We used the resulting technique , termed pMD-membrane , to identify allosteric ligand binding sites on the G12D and G13D oncogenic mutants of the K-Ras protein bound to a negatively charged lipid bilayer . In addition , we show that differences in probe occupancy can be used to quantify changes in the accessibility of druggable sites due to conformational changes induced by membrane binding or mutation .
Identification of a suitable ligand-binding site on a drug target is a crucial first step in structure-based computer aided drug discovery [1] . This is not a trivial task if the desired target site is an allosteric one that is not readily observable in average experimental structures [2] . Recently , a number of techniques have been developed that allow for the identification of ( allosteric ) ligand binding sites in target proteins [3–6] . Because ligand binding site identification usually requires sampling of the target’s configurational space , considerable effort has also been made toward integrating molecular dynamics ( MD ) simulation into the site identification process ( e . g . [6] ) . In particular , MD-based computational solvent mapping [7–12] is attracting wide attention as a convenient means of binding site identification in dynamic targets . Interest in this approach will likely increase with the expanding scope of MD simulations and because it recapitulates multi-solvent crystallographic [3] and fragment-based NMR screening experiments [5] . A typical MD-based computational solvent mapping entails carrying out MD simulations in the presence of small organic molecules in the solvent ( e . g . [7 , 8] ) . The goal is to use the small organic molecules as probes to search for binding sites on an ensemble of MD-sampled target structures . The probability of contact ( or interaction ) between probe and protein atoms is then used to evaluate the druggability of sites . The method has been described in a number of recent reports under various names: probe-based MD [8] , mixed-solvent MD [12] , solvent competition [7] , co-solvent MD [10] and ligand competitive saturation [9 , 13] . We use the term probe-based MD ( pMD ) throughout this report . Surprisingly , thus far pMD has been applied only to soluble proteins despite the fact that some of the most important drug targets require membrane binding for their biological activity [14–19] . A major goal of the current work is to extend the applicability of pMD to membrane-bound drug targets . This requires mitigating possible effects of the probe molecules on membrane structure and dynamics . For example , we previously found that small organic molecules such as ibuprofen , indomethacin and cholic acid partition into the hydrophobic core of DPC micelles [20–22] . Others found that similar small organic molecules partition into bilayers [23 , 24] . Here we describe pMD-membrane , a method that avoids membrane partitioning of probe molecules and enables allosteric ligand binding site identification in proteins bound to a bilayer surface . Another challenge in current efforts of computational binding site identification is the difficulty in discriminating between closely related homologs or mutations that are associated with different disease phenotypes . Whether pMD can capture small changes in the properties of binding sites due to conformational changes induced by membrane-/substrate-binding or mutation has not been examined . We introduce analysis techniques to evaluate differential probe occupancy that inform on the changes in potential druggability of a site . We tested pMD-membrane and the new analysis tools on G12D and G13D mutants of K-Ras . We chose these K-Ras mutants as model systems for a number of reasons . First , K-Ras is a prototypical example of membrane-associated small GTPases for which there exist abundant experimental structure data [25] . Secondly , we recently found that the interaction of K-Ras with membrane involves at least two distinct conformations ( Prakash and Gorfe , unpublished results ) . Third , K-Ras is a key regulator of numerous signaling pathways involved in cell division and proliferation [25–27] , and therefore it is physiologically and therapeutically highly relevant . In fact , 15–25% of all cancer cases are associated with mutations in the homologous K- , N- and H-Ras proteins [28]; K-Ras mutations represent 85% of these [29] . Previous efforts to inhibiting aberrant Ras function have failed [30 , 31] , but a number of allosteric Ras ligands have been discovered recently [32–38] . While these ligands are promising starting points , none have the necessary potency and selectivity to become a lead compound . Therefore , the search for Ras inhibitors continues . Desirable properties of a potential Ras inhibitor may include the following: ( i ) Ability to directly bind to membrane-associated cellular Ras . Inhibitor activity in solution is not sufficient because membrane binding is essential for the biological function of Ras , and there is evidence that signaling specificity among isoforms may involve distinct membrane localization and therefore differential accessibility to effectors and modulators [39–42] . It is therefore important that changes in conformation and dynamics upon membrane binding are explicitly considered in binding site identification / drug discovery efforts against Ras proteins . ( ii ) Specificity toward a given Ras isoform . This is because , as we alluded to above , different Ras isoforms are associated with distinct cancer types [29] despite the fact that they share a catalytic domain that is nearly identical in sequence and average structure [17 , 43] . For instance , K-Ras mutations are prevalent in lung , colorectal and pancreatic carcinomas [44–47] , N-Ras mutations in melanomas and hematologic malignancies [48–50] , and H-Ras mutations in bladder and thyroid cancers [51 , 52] . ( iii ) Specificity toward a mutation . This is because different Ras mutants , such as G12D and G13D , are associated with different cancer types [25 , 29 , 53] . The ability to identify unique ligand binding sites on each Ras isoform or mutant is the first step toward addressing the issues listed above . We demonstrate that pMD-membrane helps achieve this goal , and illustrate its robustness and sensitivity using two of the most common oncogenic mutants of K-Ras: G12D and G13D . We also show that differential membrane binding leads to altered propensity of probes for binding sites .
Previous simulation [54] and experimental studies [55 , 56] have shown that the full-length H-Ras protein interacts with membrane in a non-random fashion; it adopts two distinct orientations with respect to the membrane plane depending on the bound nucleotide [57] . In a separate work ( Prakash and Gorfe , to be published ) , we examined the bilayer interaction of GTP-bound G12D K-Ras based on a total of ~7 . 5 μs all-atom MD simulations . The analysis yielded two predominant modes of membrane binding that differ in the membrane orientation of the catalytic domain ( Fig 1 ) . Because these orientation differences can potentially be exploited for the development of isoform- and mutation-specific small molecule inhibitors , we used the two distinct conformations as the starting structure for the current pMD-membrane analysis of G12D and G13D K-Ras , as described below . We performed two sets of simulations: reference set and target set . The reference set involved two 60 ns pMD-membrane simulations of G12D K-Ras starting from the two conformations shown in Fig 1 . These simulations were performed without any modification to the force field parameters . The target set involved three 100 ns-long pMD-membrane simulations with the Lennard-Jones non-bonded interaction between selected atoms of the probe and lipid molecules modified as described in the following section . Two of the target simulations were on G12D K-Ras while the third was on G13D K-Ras . One of the G12D simulations was started from a conformation in which helices 3 and 4 directly interact with the bilayer ( Fig 1A ) , and the second from a conformation where part of the beta-sheet and helix 2 lie on the surface of the bilayer ( Fig 1B ) . The G13D target simulation was started from the orientation shown in Fig 1A after mutating Gly to Asp at position 13 and reverting the Asp on position 12 back to Gly . Since cellular K-Ras interacts with negatively charged inner leaflet of the plasma membrane via its polybasic and farnesylated C-terminus , we built a heterogeneous lipid bilayer made up of 320 POPC ( 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine ) and 96 POPS ( 1-palmitoyl-2-oleoyl-sn-glycero-3-phoserine ) lipids . The resulting symmetric bilayer was equilibrated through a 250 ns production simulation . We then embedded full-length G12D or G13D K-Ras4B in one leaflet of the pre-equilibrated bilayer . Membrane insertion was guided by previous reports [58] to determine the insertion depth of the farnesyl tail into the bilayer core . The resulting system was placed in a 114 x 112 x 110 Å3 box containing 26299–27573 TIP3P water molecules and 1337–1423 isopropanol probe molecules . In each system , we maintained a 20:1 water to probe ratio and neutral charge by adding 96 sodium ions . Additional sodium and chloride ions were added to mimic physiological ionic strength . The total number of atoms varied between 153316 and 158178 depending on the initial conformation of the protein . Following system construction and 3000 steps of conjugate gradient energy minimization , we used simulated annealing to homogenize the probe and water molecules around the protein and the bilayer . The annealing process involved the application of a harmonic restraint with a force constant of 4 kcal/mol/Å2 on the protein and lipid heavy atoms to prevent protein unfolding and bilayer instability , and incrementing the temperature every 5000 steps by 50 K until a temperature of 650 K was reached , followed by gradual cooling by 10 K every 5000 steps until a final temperature of 310 K was achieved . The resulting system was equilibrated for 1 ns while gradually decreasing the restraint force constant to zero . This was followed by a production run of 60 ns for the reference simulations and 100 ns for the target simulations . A non-bonded cutoff of 12 Å was used during both the equilibration and production phases of each simulation . Long-range electrostatic interactions were calculated by the Particle Mesh Ewald ( PME ) method [59] with SHAKE [60] restraints applied on bonds involving hydrogen atoms . Simulations were performed with a 2 fs timestep in the NPT ensemble ( constant number of particle N , temperature T = 310 K , and pressure P = 1 bar ) . Nose-Hoover Langevin piston for pressure control was used to maintain constant pressure and Langevin thermostat to maintain constant temperature . Short-range non-bonded forces were computed every timestep and long-range electrostatic forces every other step . All simulations were performed with the NAMD2 . 9 program [61] using the CHARMM27 force field for proteins [62] and CHARMM36 for lipids [63]; isopropanol was parameterized as described in ref [11] . pMD-membrane simulation with the unmodified CHARMM force field led to partitioning of a fraction of the probe molecules into the bilayer ( see Fig 2 and Results and Discussion ) . To prevent this diffusion of probe molecules into the bilayer interior , we modified the vdW interaction between the central carbon atom of the probe and the CTL2 atom type of the POPC and POPS lipids . After several tests ( see for example S1 Fig ) , we arrived at the following protocol: the well depth of the Lennard-Jones potential was reduced to a very small value of 0 . 01 kcal/mol ( see ref . 9 ) , and the minimum inter-particle distance among the selected atoms was increased to 7 Å ( S1 Fig ) . The former ensures that attraction between the apolar atoms of the lipids and probe molecules is almost completely eliminated , while the 7 Å distance yields a reasonable balance between allowing the probe to access the polar bilayer surface where the protein sits and preventing it from penetrating into the hydrophobic core ( S1 Fig ) . This modification was made utilizing the NBFIX correction term in the CHARMM force field . This approach is similar in principle to the modifications MacKerell and colleagues made via dummy atoms to prevent aggregation of probe molecules [9] . We calculated the extent of protein-probe interactions using both distance-based and grid-based measures of probe occupancy . To assess the relative polarity of putative ligand binding sites , we calculated the ensemble-averaged orientation of probe molecules with respect to the surface of the protein . Specifically , we calculated <cos ( θr ) > , where θr is defined as the angle between the vector radiating from the central carbon atom to the O atom of an isopropanol probe molecule and the vector connecting the center of the catalytic domain of the protein ( residues 1–166 ) and a given atom on the protein surface . Only protein atoms whose probe occupancy was above an empirically determined threshold were considered for this analysis ( in this work we used Ri ≥ 0 . 24 ) . Convergence of protein-probe interactions was evaluated by monitoring the time evolution of the atom-averaged probe occupancy Rave where the summation is over all protein atoms M with R > 0 . 05 . The 0 . 05 cutoff ensures that approximately all of the atoms with non-zero R-value are included in the statistics . ( Note that the profile of Rave would be unaffected even if atoms with zero R-values were also included . ) S3 Fig ( left ) shows that Rave has equilibrated within the first ~20 ns in all three of our target simulations . Moreover , comparison of the mean ( <Rave> ) in 20 ns blocks yielded very small differences among all blocks except the first one . For instance we obtained <Rave>±S . D of 0 . 20±0 . 05 , 0 . 21±0 . 02 , 0 . 22±0 . 04 , 0 . 24±0 . 02 and 0 . 24±0 . 03 for the 1–20 , 20–40 , 40–60 , 60–80 and 80–100 ns blocks of the G12D simulation in membrane binding mode 1; similar results were obtained for G12D mode 2 and G13D simulations . This suggests that the simulations were well equilibrated in terms of probe binding , and that any portion of the last 80 ns data can be used to compute average occupancies . For a better statistics , however , we used all frames in the last 80 ns of the trajectories unless stated otherwise . Statistical uncertainty in Ri was estimated based on an analysis of block standard error ( BSE ) following the procedure described by Grossfield and Zuckerman [65] . In this analysis , BSE was calculated at different sizes of time blocks ( bn ) . The convergence of BSE versus bn was used to evaluate the quality of our sampling and to determine the maximum value of the BSE , which serves as a measure of our sampling error . In S3 Fig ( right ) , we show several BSE vs . bn plots for a few atoms chosen for illustration of the diverse convergence rates and error values . For a more rigorous analysis of errors in the relative probe accessibility of each atom in trajectories x and y , i . e . , the uncertainty in ΔRi , we first calculated BSE in Rix and Riy for multiple block sizes bn . We then used nonlinear fitting of the dependence of BSE on bn to the following functional form: a0 ( 1-a1exp ( -a2bn ) ) , where a0 , a1 and a2 are three fitting parameters with a0 being an estimate of the asymptotic value of BSE . We then computed the uncertainty in ΔRi by combining the BSEs in Rix and Riy ( Eq 6 ) .
To our knowledge pMD has not been previously applied to membrane proteins . Because molecular probes are completely or mostly nonpolar and small , we reasoned that one of the challenges might be the possibility that they partition into and modulate the structure of the bilayer . To test this hypothesis , we ran two 60 ns pMD-membrane simulations without the Lennard-Jones non-bonded interaction modifications described above . We found that a significant fraction of our test probe , isopropanol , quickly partitioned to the POPC/POPS bilayer ( Fig 2A ) . Moreover , the interaction of the probe molecules with the membrane lipids is non-random ( Fig 2A ) . This is quantified by the number density distribution of the probes along the bilayer normal ( Fig 2B ) , where the peaks within the bilayer indicate preferential accumulation near the glycerol region . To complement this observation , we calculated the average orientation of the probe molecules along the bilayer normal based on the cosine of the angle between a vector along the bond connecting the central carbon and the hydroxyl oxygen of the probe molecule and the membrane normal . As shown in Fig 2C , the OH moiety of the probe appears to be donating a hydrogen bond to the carbonyl oxygen of lipid glycerol . Thus , in contrast to the random mixing of the probe with water ( see the blue shade in Fig 2A ) , isopropanol-lipid interaction is specific , as illustrated in Fig 2C . As a result , the average area per lipid increased by more than 10% ( 60 . 8 ± 0 . 7 Å2 vs . 68 . 6 ± 3 . 8 Å2 in the absence and presence of probe , respectively ) . Correspondingly , the bilayer thickness decreased from 40 . 5 ± 0 . 3 Å to 38 . 0 ± 1 . 4 Å . While the impact of the isopropanol-lipid interaction on the bilayer structure might appear relatively small , it can have substantial impact on the dynamics of the bound protein . Moreover , we anticipate larger effect for bigger and more lipophilic probes such as benzene or cyclohexane . Therefore , it is desirable to avoid probe partitioning into the bilayer in order to ensure that pMD-membrane will have broad application . To achieve this , we modified the Lennard-Jones potential between selected atoms of the probe and lipids ( see Methods ) . As shown in Fig 3 , this modification led to a smooth decline in the number of probe molecules that approach the polar head group , and exclusion of probe molecules from the hydrophobic core . This is reflected in the average area per lipid and bilayer thickness , both of which remained unaffected ( 59 . 7 ± 0 . 4 Å2 vs . 60 . 8 ± 0 . 7 Å2 and 41 . 2 ± 0 . 2 Å and 40 . 5 ± 0 . 3 Å in the presence and absence of probes , respectively ) . The very small polarization of the few probe molecules near the bilayer surface ( Fig 3C ) can be eliminated if needed by using a larger non-bonded inter-particle distance for the modified atom pairs . Our choice of parameters was meant to ensure that probe molecules can approach the protein from the side of the membrane surface as well as from bulk . In summary , comparison of Figs 2 and 3 makes it clear that a simple modification of some of the vdW terms on selected atoms of the probe and bilayer extends the applicability of pMD to membrane proteins , a major focus of many drug discovery campaigns ( e . g . [19] ) . In the subsequent sections we demonstrate the application of the method on membrane–bound K-Ras , a highly sought after anti-cancer drug target [30 , 66] . Protein motion can be affected by the composition of the surrounding solvent [67 , 68] . As can be surmised from Fig 1 , the dynamics of the catalytic domain of K-Ras G12D is different before and after it formed direct contact with the bilayer ( i . e . , when fully in water and after part of the surface is restrained by interaction with lipids ) . Therefore , we checked if ( i ) pMD-membrane qualitatively reproduces binding sites on Ras that have been previously characterized by other solvent mapping techniques [69 , 70] , and ( ii ) these sites/sub-sites are modulated by conformational change induced by membrane binding . In the previous pMD analysis of G12D in solution [11] , we identified five druggable sites and three sub-sites ( see Fig 3 in ref . [11] ) . A detailed comparison with known ligand binding pockets indicated that three of the predicted druggable sites overlap well with pockets p1 , p2 and p3 while two of the predicted sub-sites were found to be parts of p1 and p4 , respectively ( see Fig 4 of ref . [11] ) . Allosteric pockets p1 to p4 have been previously described in detail: p1 is the binding site of ligands reported by Maurer et al [32] , Sun et al [33] and Shima et al [34]; p3 is near the C-terminus of the catalytic domain where Cu2+-cylen binds [35 , 36]; p4 is the proposed target site of Andrographolide derivatives [38] and Zn ( II ) -bis ( 2 picolyl ) amines [36]; there is no known non-covalent binder that targets p2 but covalent ligands that target this region have been reported [37] . Direct comparison of the calculated probe occupancies in membrane-bound K-Ras with experimental results is not possible because one cannot turn on in experiment non-physical repulsive interactions to prevent bilayer partitioning of isopropanol . Nonetheless , the following analysis provides a strong evidence that pMD-membrane is able to identify true drug binding sites . In order to compare the current pMD-membrane with the previous pMD-solution , we performed grid free energy analysis on the last 10 ns data from the two current simulations of G12D K-Ras and the previous pMD-solution run of G12D K-Ras ( we chose the longest , 100 ns run ) . The results are displayed in Fig 4 , where grid densities that yielded grid free energies of -1 kcal/mol or lower are shown in blue and green for the simulations in membrane and solution , respectively . Pockets p1 to p4 are labeled where possible . One can see that there is a remarkable overall agreement between the membrane and solution simulations ( see overlaps between the blue and green iso-surfaces ) . We take this as validation of pMD-membrane , because pockets p1–p4 are all confirmed ligand binding sites for which there exist crystallographic or solution NMR structures of K-Ras in complex with ligands [32–36] . However , there are also clear differences . The most significant differences include the following . ( i ) In membrane binding mode 1 ( Fig 4A ) , pocket p1 is completely invisible . Instead , a new putative site appears very close to the P-loop but distinct from the nucleotide-binding site . ( ii ) In membrane binding mode 2 ( Fig 4B ) , p2 is absent but no new site is discovered . Taken together , these results demonstrate that pMD-membrane captures known druggable sites , and that protein-membrane interaction modulates binding site accessibility . Whether the observed differences in some of the sites will translate into differential ligand binding in the soluble and membrane-bound K-Ras is yet to be determined . Nonetheless , this observation highlights the importance of incorporating the effect of membrane in Ras drug discovery efforts . For the analysis in the previous section , we included only probe molecules that lie within 4 Å of protein heavy atoms . In principle , grid occupancy can be calculated over the entire system ( see Methods , Eqs 3 and 4 ) , so that all high-density grid points around the protein can be considered . Then , the probe density can be visualized at the desired concentration cutoff . An example of this is shown in S4 Fig . There is a clear overlap between the high-density iso-surfaces and known pockets p1 to p4 , as well as the sites highlighted in Fig 4A . However , there are also a large number of other high-density regions that , though unlikely to bind drug-like molecules , clutter the picture . In Fig 5 , we show overlays of probe-occupancies derived from distance-based and grid-based analyses ( see Methods ) . As expected , the two techniques yielded very similar results ( notice the overlap between the red and white contours representing high probe densities from distance-based and grid-based analysis , respectively ) . White isosurfaces circumscribed by the red contours are likely pocket-like , suggesting that a combined use of distance-based and grid-based occupancy analyses would help localize relevant sites somewhat . However , it is still difficult to unambiguously isolate potentially druggable pocket–like sites . This can be regarded as a limitation of probe-based analyses in cases where there is no prior knowledge of druggable sites . This suggests that it is prudent to complement pMD with analysis of geometric/chemical features such as curvature , volume and polarity . There are a number of useful tools to perform structure-based pocket analysis , such as SiteMap [71] , MDpocket [72] and AutoGrow [73] . The use of more than one type of probes or mixtures thereof may also be helpful . For the purposes of the current work , where we are interested in the relative druggabilty of different mutants/orientations of membrane-bound K-Ras , an inherently less cluttered differential probe occupancy ( or density ) is most relevant . Both grid-based and distance-based occupancy measures can be used for such an analysis , but we found the latter to be more convenient . The following sections will therefore focus on changes in distance-based probe occupancies . As noted earlier , the current work was motivated in part by the observation that bilayer interactions of H-Ras G12V [54] and K-Ras G12D ( Prakash and Gorfe , to be published ) involve at least two distinct modes . The prime difference between the modes is the orientation of the catalytic domain with respect to the membrane plane so that , in the case of K-Ras G12D , either helix 3/4 or helix 2 directly contact the bilayer ( Fig 1 ) . We wanted to see if these two membrane-binding modes differ in ligand binding potential when assessed by pMD-membrane . To this end , we calculated the difference in atomic probe occupancy between the simulations started from the conformation in Fig 1B ( mode 2 ) and from the conformation in Fig 1A ( mode 1 ) : ΔRconf = R2 –R1 . Thus , negative ΔRconf at a given atom means that the atom is more accessible to probes in membrane binding mode 1 than 2 ( positive ΔRconf is the opposite ) . The data in Fig 6A shows that the two membrane binding modes substantially differ in probe occupancy , particularly at helices h2 , h3 , h4 , the hvr and to a lesser extent between h1 and β2 . Coloring the 3D structure by ΔR further shows that the differences are confined to four surface patches ( Fig 6B ) . Three of these patches correspond to previously described pockets , including p1 , p3 and part of p2 . Pocket p3 is more accessible in mode 1 than in mode 2 ( negative ΔRconf ) while p1 is more accessible in mode 2 than in mode 1 . There are some changes in the accessibility of p4 as well . Apart from these pockets , variations in probe accessibility include surface sites that may not be druggable , such as the sharp positive ΔRconf peak on helix 4 arising from the fact that it is engaged with the bilayer in mode 1 but not in mode 2 . Overall , this analysis demonstrates that sites’ accessibility to probe molecules is a function of membrane orientation of the protein , and that pMD-membrane is capable of capturing those differences . We propose that , at least for Ras proteins , ligand accessibility will likewise depend on the details of membrane binding . In an unpublished study , we observed that the active sites of G12D and G13D K-Ras significantly differ . While the active site of G12D K-Ras is similar to wild type , switch 1 is open and some functionally critical residues , such as Tyr32 , have re-oriented in G13D K-Ras . At the functional level , G12D and G13D K-Ras differ in intrinsic GTPase activity [74] and oncogenicity [25] . Therefore , we ran a pMD-membrane simulation on G13D starting from the conformation shown in Fig 1A ( mode 1 ) and calculated ΔRseq = RG13D –RG12D . We found major differences in probe accessibility of the two mutants ( Fig 7A ) , indicating that the two simulations started from the same initial configuration have drifted apart , leading to different probe binding propensities . The differences are largely confined to helices 2 , 3 , and 4 ( Fig 7A ) , representing two surfaces on the 3D structure ( Fig 7B ) . Part of the surface of helix 2 where p1 is located is more accessible in G13D than G12D whereas the region between helices 3 and 4 is significantly more probe-accessible in G12D than G13D . This is despite the fact that these regions are far away from the site of the mutation . We propose that these observations highlight potential differences in the druggability of the two mutants and thereby the possibility of isoform-specific drug leads . We find the region between helices 3 and 4 especially interesting as it might represent a potentially unique new ligand-binding site . We have seen that isopropanol has preferred orientations at the glycerol and head group regions of the POPC/POPS bilayer ( Figs 2 and 3 ) . This was because the OH functional group of the probe prefers to interact with lipid oxygen atoms which the CH3 groups tend to avoid . For the same reason , interaction of the probes with protein atoms is likely to be polarized so that the OH group points away from hydrophobic surface cavities but points toward polar cavities . Therefore , we wondered if the local orientation of the probe contains information about the polarity/hydrophobicy of individual sites . To check this , we calculated the average orientation of the probe taking into account every protein atom that is in contact with a probe molecule . In this analysis , positive <cos ( θr ) > indicates that the hydroxyl oxygen points away from the protein ( see Methods ) . We found that the ensemble averaged cos ( θr ) is positive for the vast majority of the highly probe-accessible surface protein atoms ( Fig 8A and 8B ) , suggesting that the probe-binding sites are mostly hydrophobic and therefore potentially druggable . Negative <cos ( θr ) > was found only at a couple of surface sites that are unlikely to bind to ligands . We introduced a technique referred to as pMD-membrane as a novel approach for the analysis of ligand binding potential of surface cavities in membrane proteins . This represents a major expansion of the scope of probe-based molecular dynamics simulation approaches . The goal of pMD-membrane , and probe-based simulations in general , is to map fragment positions in pockets that may then be used by medicinal chemists to design specific binders . Extensive analysis involving multiple types of co-solvents and multiple drug targets found a strong correlation between probe occupancies and binding affinities of true binders in most cases ( refs 7–9 ) . Similarly , we have shown that , following modification of selected vdW interaction terms in the force field , pMD-membrane was able to identify allosteric ligand binding sites ( including known binding sites ) on the surface-bound K-Ras without any significant effect on the structure and dynamics of the bilayer or the protein . We have also demonstrated that pMD-membrane can capture the impact of conformational changes induced by membrane binding or mutation on the probe accessibility of putative druggable sites . This is important because the ultimate goal of any site identification scheme is to differentiate cryptic binding sites based on changes in size , location or chemical feature . Such changes can result from small differences in protein motion in water versus membrane environments , as well as from mutations , substrate binding , posttranslational modification etc . Our method thus extends the scope of probe-based molecular dynamics simulation in two majors ways: as a novel means by which to find ( allosteric ) ligand binding sites in membrane proteins and as a tool with which to probe differential ligand accessibility in closely related targets . The method can be easily expanded to any type of probe or mixture of probes through similar modifications of non-bonded terms . Therefore , pMD-membrane and the analysis tools described in this study are applicable to a wide variety of membrane proteins , whether trans-membrane or surface-bound .
|
We introduce a simulation-based method to identify allosteric ligand binding sites in membrane-associated proteins for which existing methods are inadequate . We applied the method on two mutant forms of an oncogenic protein called K-Ras . We show that the way in which the protein interacts with membrane is an important determinant for the accessibility of selected ligand binding sites . We also describe techniques to quantify changes in the ligand binding potential of cavities on the surface of proteins induced by mutation or membrane binding .
|
[
"Abstract",
"Introduction",
"Methods",
"Results/Discussion"
] |
[] |
2015
|
pMD-Membrane: A Method for Ligand Binding Site Identification in Membrane-Bound Proteins
|
Polyunsaturated fatty acids ( PUFAs ) form a class of essential micronutrients that play a vital role in development , cardiovascular health , and immunity . The influence of lipids on the immune response is both complex and diverse , with multiple studies pointing to the beneficial effects of long-chain fatty acids in immunity . However , the mechanisms through which PUFAs modulate innate immunity and the effects of PUFA deficiencies on innate immune functions remain to be clarified . Using the Caenorhabditis elegans–Pseudomonas aeruginosa host–pathogen system , we present genetic evidence that a Δ6-desaturase FAT-3 , through its two 18-carbon products—gamma-linolenic acid ( GLA , 18:3n6 ) and stearidonic acid ( SDA , 18:4n3 ) , but not the 20-carbon PUFAs arachidonic acid ( AA , 20:4n6 ) and eicosapentaenoic acid ( EPA , 20:5n3 ) —is required for basal innate immunity in vivo . Deficiencies in GLA and SDA result in increased susceptibility to bacterial infection , which is associated with reduced basal expression of a number of immune-specific genes—including spp-1 , lys-7 , and lys-2—that encode antimicrobial peptides . GLA and SDA are required to maintain basal activity of the p38 MAP kinase pathway , which plays important roles in protecting metazoan animals from infections and oxidative stress . Transcriptional and functional analyses of fat-3–regulated genes revealed that fat-3 is required in the intestine to regulate the expression of infection- and stress-response genes , and that distinct sets of genes are specifically required for immune function and oxidative stress response . Our study thus uncovers a mechanism by which these 18-carbon PUFAs affect basal innate immune function and , consequently , the ability of an organism to defend itself against bacterial infections . The conservation of p38 MAP kinase signaling in both stress and immune responses further encourages exploring the function of GLA and SDA in humans .
Polyunsaturated fatty acids ( PUFAs ) are a class of long chain fatty acids of 18 carbon atoms or more in length that contain two or more double bonds . PUFAs are classified into two groups , the omega-6 ( n-6 ) or the omega-3 ( n-3 ) fatty acids , depending on the position of the double bond ( n ) closest to the methyl end of the fatty acid chain . In mammals , the 18-carbon and longer omega-6 and omega-3 PUFA families cannot be synthesized de novo . They are produced , instead , from the dietary essential fatty acids linoleic acid ( LA , 18:2n6 ) and alpha-linolenic acid ( ALA , 18:3n3 ) through a series of desaturation and elongation reactions catalyzed by desaturase and elongase enzymes , respectively [1] , [2] . Omega-6 PUFAs , such as arachidonic acid ( AA , 20:4n6 ) are converted into eicosanoids , leukotrienes and prostanoids through the actions of lipoxygenase and cyclooxygenase enzymes [3] . In vertebrates , these eicosanoids variously exert stimulatory and inhibitory influences and have profound effects on multiple aspects of organismal physiology , including immunity [4] , [5] . For example , prostaglandins and leukotrienes are pro-inflammatory mediators that are vital for the initial containment of an infection and for the recruitment of phagocytes and other immune cells to a site of infection [6] . Omega-3 fatty acids such as eicosapentaenoic acid ( EPA , 20:5n3 ) influence the T cell response to infection and demonstrate strong anti-inflammatory effects [7] . Dietary fatty acids and eicosanoids have also been shown to bind nuclear receptors , such as the Peroxisome Proliferator Activated Receptor γ ( PPAR-γ ) , which modulates activation of dendritic cells , NK cells and T cells [8]–[10] . The influence of PUFAs on immune functions also extends to other organisms that possess only an innate immune response . For example , eicosanoids are crucial mediators and coordinators of insect cellular immune reactions to bacterial , fungal , and parasitoid invaders , specifically microaggregation , nodulation , and encapsulation [11] . In the silkworm Bombyx mori , eicosanoids are involved in the expression of the antibacterial proteins cecropin and lysozyme in the fat body [12] . In Drosophila , a functional coupling between eicosanoid biosynthesis and the IMD pathway for the induction of the antibacterial peptide diptericin by LPS has been reported [13] , [14] . An analogous fatty acid-derived signaling pathway has also been shown to be important for defense in plant . However , instead of the 20-carbon AA , which is a minor PUFA in plants , 18-carbon PUFAs serve as major precursors for the synthesis of jasmonates and other oxylipins that play important roles in pathogen defense [15] . Jasmonates regulate the expression of defense genes that are essential for survival against insects and necrotrophic pathogens [16] . Oxylipins , such as crepenynic and dehydrocrepenynic acids are biologically active anti-fungal compounds [17] . Innate immunity forms a common first line of defense for most organisms , providing a highly conserved but generally non-specific response to pathogens and parasites . The innate immune system can be distinguished into two separate but overlapping components , the constitutive or basal branch of innate immune defense , and the pathogen-induced responses [18] , [19] . Constitutive or basal immunity involves the constant production of effector molecules such as defensins and other antimicrobial peptides , providing a preventative barrier and allowing the organism to instantaneously respond to an immunological insult [20]–[22] . The inducible branch of the innate immune system , on the other hand , is only activated after the host has encountered a pathogen , and typically includes the induction of additional effector molecules , and where present , the recruitment and activation of phagocytic cells [23] . Both constitutive and inducible innate immunity has been described in the soil nematode C . elegans . For example , a number of antimicrobial peptides are constitutively expressed in healthy worms , including lysozymes [24] , the ABF-2 defensin [25] and the SPP-1 saposin [24] . A subset of these constitutively-expressed antimicrobials , and a suite of additional effector molecules , including members of the C-type lectin family , are up-regulated at different time points after infection [26]–[28] . The ability of C . elegans to defend against infections requires several conserved signaling pathways [19] , [29] , [30] . They include a MAP kinase cascade , resulting in the activation of the p38 MAP kinase homologue PMK-1 [29] , an insulin-like defense pathway that activates the FOXO transcription factor homologue DAF-16 [31] and a TGF-β pathway [26] . These pathways are required for the elevated production of a number of effector molecules , including antimicrobial peptides , lysozymes and lectins , to levels above those seen under basal conditions , in healthy worms [24] , [28] . The p38 MAP kinase pathway also plays a vital role in maintaining the basal immune response , and mutants in this pathway , such as the p38 MAP kinase mutant pmk-1 , show defects in the constitutive expression of lysozymes , lectins and other effector molecules [28] . In addition to the innate immune response , pathways for lipid synthesis and metabolism are also largely conserved in C . elegans [32]–[34] , making the worm an ideal model to investigate the effects of lipids on immune function . Unlike mammals , C . elegans is able to synthesize all its required long chain fats from its bacterial food source ( Figure 1A ) , allowing for the manipulation of lipid synthesis and content in the worm [32] , [35] . Synthesis of these fatty acids is catalyzed by elongase and desaturase enzymes , which in C . elegans are encoded by elo and fat genes , respectively , and the C . elegans genome contains the full complement of enzymes required for the synthesis of long chain fatty acids ( LCFAs ) [32] , [35] . The absence of obvious mammalian orthologs of cyclooxygenases and lipoxygenases or of prostanoid and leukotriene receptors in the C . elegans genome [36] provides the opportunity to investigate the roles for PUFAs in innate immunity that could otherwise be masked by the dominant influences of the prostaglandin and leukotriene eicosanoids . Here , we use the infection of C . elegans by a human Gram-negative bacterial pathogen , Pseudomonas aeruginosa as an experimental system to investigate the interplay between PUFAs and innate immunity , in the context of the whole organism . We identify two long chain PUFAs , gamma-linolenic acid ( GLA , 18:3n6 ) and stearidonic acid ( SDA , 18:4n3 ) , as vital for C . elegans defense against P . aeruginosa infection . Disrupting the production of these two fatty acids results in increased mortality following exposure to the pathogen . We demonstrate , by deficiency and exogenous supplementation studies , that GLA and SDA are required for both the basal activity of the p38 MAP kinase pathway and the basal expression of immunity genes .
Although lipids are known to play multiple roles in immunity , relatively little evidence exists for the specific manipulation of the lipid metabolism in response to infection . Detailed analysis of a whole genome microarray study for gene expression in P . aeruginosa-infected C . elegans [27] revealed an enrichment for genes required for the synthesis of LCFAs . This modulation of the lipid metabolism in response to infection hinted at potential roles for fatty acids in C . elegans immunity . To confirm and extend the microarray observations , we used quantitative real time PCR ( qRT-PCR ) to compare mRNA levels of 16 LCFA synthesis genes in age-matched adult animals raised on E . coli OP50-1 , the standard laboratory food source , or following infection by P . aeruginosa strain PA14 ( Figure 1B ) . Since the activity of lipid metabolism genes could be greatly influenced by available nutritional sources , and having determined that the fatty acid contents of E . coli and P . aeruginosa were different ( Figure S1A ) , we also quantified the mRNAs of elo and fat genes in worms exposed to PA14ΔgacA , an isogenic strain of P . aeruginosa PA14 in which the global virulence gene gacA , has been deleted [37] . PA14ΔgacA mutants were highly attenuated in their ability to kill C . elegans ( Figure S1B ) [38] , but had a fatty acid composition very similar to the parental PA14 strain ( Figure S1A ) , thus providing a useful control for changes due to nutritional differences between E . coli and P . aeruginosa . Of the nine C . elegans genes known to be involved in the synthesis of the majority of 18- and 20-carbon PUFAs and monounsaturated fatty acids ( MUFAs ) , fat-6 , fat-2 , fat-3 and fat-4 were expressed at higher levels in worms exposed to P . aeruginosa than to E . coli or PA14ΔgacA ( Figure 1B ) . These represent genes whose expressions were significantly induced under infection conditions , indicating a modulation of PUFA synthesis by P . aeruginosa infection . Of the five elo genes of unknown function , elo-7 and elo-8 were also significantly induced under infection conditions ( Figure 1B ) . Although expression of fat-5 , elo-9 and the branched chain fatty acid ( BCFA ) biosynthetic genes ( elo-5 and elo-6 ) were lower in animals exposed to P . aeruginosa compared to E . coli ( Figure 1B ) , they were also lower in animals exposed to attenuated PA14ΔgacA , suggesting that these changes in expression may be due to differences in fatty acid content between the bacterial species . These results confirmed a specific modulation of host LCFA synthesis in response to P . aeruginosa infection . We next determined the effect of infection on the abundance of specific fatty acids in the worm . Gas chromatography followed by mass spectrometry ( GC-MS ) [32] was used to identify and compare the content of individual species of LCFAs in age-matched P . aeruginosa-infected worms and worms grown on E . coli . To rule out changes caused by nutritional differences between the two bacterial species , we also determined LCFA content of worms exposed to PA14ΔgacA mutant bacteria . We conclude that the higher levels of vaccenic acid ( VA , 18:1n7 ) in P . aeruginosa-infected worms is most likely due to nutritional differences between P . aeruginosa and E . coli because the same increase was seen in worms that were exposed to the relatively avirulent PA14ΔgacA ( Figure 1C ) . This is consistent with GC-MS results showing that both the P . aeruginosa and PA14ΔgacA strains had more than twice the VA content compared to E . coli ( Figure S1A ) . Worms infected with P . aeruginosa had significantly lower levels of stearic acid ( SA , 18:0 ) , oleic acid ( OA , 18:1n9 ) , LA , ALA and GLA compared to worms exposed to E . coli or the attenuated PA14ΔgacA strains ( Figure 1C ) . These changes in PUFA content also corresponded with the previously observed infection-induced changes in gene expression . Three of the genes up-regulated in response to infection , fat-6 , fat-2 and fat-3 , are involved in the synthesis of fatty acids listed above , potentially indicating a feedback loop , where decreases in LCFA levels during infection could induce increased expression of corresponding biosynthetic genes . The infection-specific decreases in fatty acid levels led us to hypothesize that these LCFAs may be involved in immunity against pathogens . To determine if specific LCFAs could be important for immune function in vivo , we analyzed a series of mutants that were unable to synthesize specific MUFAs and/or PUFAs for their ability to survive infection by P . aeruginosa ( Figure 2A ) . These strong or complete loss-of-function mutants in the fat and elo genes were also analyzed by GC-MS to confirm that the genetic lesion or RNAi knockdown resulted in the expected alterations in the fatty acid profile ( Figure 2A ) . The ELO-2 elongase is thought to catalyze the elongation of palmitic acid ( PA , 16:0 ) to SA ( Figure 1A ) . Reducing elo-2 expression by RNAi resulted in significant changes in LCFA profile that is consistent with a previous report [39] and a significant increase in susceptibility to killing by P . aeruginosa ( Figure 2A ) . The next step in PUFA synthesis , the conversion of SA to OA is catalyzed by two functionally-redundant desaturases , encoded by fat-6 and fat-7 ( Figure 1A ) [40] , [41] . We verified previous reports that neither the loss of fat-6 nor fat-7 function resulted in any significant alteration in PUFA composition , and showed that neither mutant was susceptible to P . aeruginosa infection ( Figure 2A ) . By contrast , the fat-6 ( tm331 ) ; fat-7 ( wa36 ) double mutant , which lacked OA and the 18- and 20-carbon PUFAs derived from OA [41] , was highly susceptible to killing by P . aeruginosa . fat-2 ( wa17 ) animals that lacked all 18- and most 20-carbon PUFAs were also significantly more susceptible to P . aeruginosa ( Figure 2A ) . Loss of fat-3 ( wa22 ) function resulted in animals that lacked two specific 18-carbon PUFAs , GLA and SDA , as well as all the 20-carbon PUFAs . fat-3 ( wa22 ) animals were also significantly more susceptible to infection , suggesting that GLA , SDA and/or 20-carbon PUFAs that were missing in these animals could be vital for infection response in C . elegans ( Figure 2A ) . Interestingly , two different elo-1 mutants , elo-1 ( gk48 ) and elo-1 ( wa7 ) , that had decreased levels of all the 20-carbon PUFAs but accumulated the upstream 18-carbon precursors GLA and SDA [32] , were significantly more resistant to killing by P . aeruginosa ( Figure 2A ) . These results suggest that a lack of 20-carbon PUFAs does not compromise immune function . Consistent with this interpretation , neither the fat-1 ( wa9 ) mutant lacking two 20-carbon PUFAs , dihomo-γ-linolenic acid ( DGLA , 20:3n6 ) and EPA , nor two fat-4 mutants , fat-4 ( wa14 ) and fat-4 ( ok958 ) , that lacked AA and EPA , were significantly different from wild-type animals for susceptibility to P . aeruginosa ( Figure 2A ) . Collectively , resistance of the elo-1 mutants and increased susceptibility of the fat-3 ( wa22 ) mutants to P . aeruginosa , suggest that GLA and SDA that accumulated in the elo-1 mutants but were absent in the fat-3 ( wa22 ) mutant may be required for immune function . PUFA levels in fat and elo mutants could be restored through dietary supplementation of the missing fatty acids [42] . To confirm the requirement of GLA and SDA for C . elegans to survive a pathogen challenge , fat-2 ( wa17 ) , fat-3 ( wa22 ) and elo-1 ( gk48 ) mutants were raised from embryos to 1-day-old adults in the presence of exogenously supplied PUFAs . A sub-population of these PUFA-supplemented adults was subjected to GC-MS to confirm that the procedure effectively restored the levels of the missing PUFAs ( Figure S2 ) while the remaining population was subjected to survival assays . In parallel , wild-type worms were also supplemented with the respective PUFAs and the PUFA levels following supplementation were determined by GC-MS ( Figure S2A ) . PUFA-supplemented wild-type animals were not significantly different from untreated wild-type for pathogen survival ( Table 1 , Figures S3A and S3B ) . Supplementation with ALA completely restored PUFA levels ( data not shown ) and survival of fat-2 ( wa17 ) animals on P . aeruginosa to that of wild-type ( Figure 2B ) . ALA supplementation , however , failed to rescue fat-3 ( wa22 ) susceptibility to P . aeruginosa ( Figure 2D , Table 1 ) . These results were expected because the fat-3 gene remained functional in the fat-2 ( wa17 ) mutant and could convert the exogenously added ALA into the required downstream fatty acids , thus rescuing the immune defects of fat-2 ( wa17 ) animals . The fat-3 ( wa22 ) mutant , on the other hand , was unable to process the supplied ALA , and consequently remained susceptible to P . aeruginosa . We , therefore , conclude that ALA is not directly required for immune function . Instead , ALA is likely to be modified by the FAT-3 Δ6-desaturase enzyme into functional molecules that affect immune function . Supplementation with either GLA or SDA that were absent in both the fat-2 ( wa17 ) and fat-3 ( wa22 ) mutants , resulted in a partial rescue of pathogen susceptibility ( Figure 2B , C ) . GLA supplementation increased the mean survival period of both the fat-2 ( wa17 ) and fat-3 ( wa22 ) mutants to approximately 90% of wild-type . GLA supplementation limited to only the adult stage was also sufficient to partially rescue the susceptibility of the fat-3 ( wa22 ) mutant ( Figure S3C ) , suggesting that the presence of GLA during growth and development is not necessary for its effect on the survival against P . aeruginosa infection . Addition of SDA alone increased the mean survival period of both fat-2 ( wa17 ) and fat-3 ( wa22 ) mutants on P . aeruginosa to approximately 85% of wild-type ( Figure 2B , C ) . Supplementation with both GLA and SDA , however , completely rescued fat-3 ( wa22 ) survival against P . aeruginosa infection ( Figure 2C , Table 1 ) , indicating that GLA and SDA together are required for optimal infection response . We also note that , similar to the association between pathogen resistance and accumulation of GLA and SDA seen with elo-1 mutants ( Figure 2A ) , wild-type and fat-3 ( wa22 ) animals supplemented with both GLA and SDA were marginally more resistant to P . aeruginosa , although these increases were not statistically significant ( Table 1 ) . The P . aeruginosa-resistant elo-1 ( gk48 ) animals were also supplemented with ALA , GLA and SDA . The elo-1 ( gk48 ) mutant already accumulated these same fatty acids ( Figure 2A ) , and additional supplementation did not enhance pathogen resistance ( Figure S3D ) . Pathogen resistance of elo-1 ( gk48 ) , coupled with wild-type phenotypes of the fat-1 ( wa9 ) , fat-4 ( wa14 ) and fat-4 ( ok958 ) mutants on P . aeruginosa ( Figure 2A ) , indicate that 20-carbon PUFAs are not necessary for C . elegans immunity . To further support these conclusions , we analyzed the effect of supplementation with AA and EPA on the fat-3 ( wa22 ) mutant . Dietary supplementation of either AA or EPA to fat-3 ( wa22 ) animals effectively restored the respective PUFAs in these animals ( Figure S2C , S2D ) , but could not rescue pathogen sensitivity of the fat-3 ( wa22 ) mutant ( Figure 2D ) , confirming that the 20-carbon PUFAs do not have any detectable roles in immune function . These results further implicate the requirement for both GLA and SDA in C . elegans immunity . The fat-3 gene is expressed in multiple tissues , including the intestine , pharynx and body wall muscles , as well as some head and tail neurons [42] . To determine the tissue in which the fat-3 gene is required for immune function , we obtained transgenic strains that express a functional fat-3 gene only in the neurons , the muscles or the intestine of a fat-3 mutant using well-established tissue-specific promoters [36] and assayed the ability of these animals to survive P . aeruginosa infection . We first confirmed that the two deletion alleles of fat-3 used to generate the tissue-specific rescue strains , fat-3 ( lg8101 ) and fat-3 ( lg8101/qa1811 ) [36] , demonstrated equivalent susceptibilities as fat-3 ( wa22 ) [32] to P . aeruginosa ( Figure 3A ) . The fat-3; [Pfat-3::fat-3] strain , carrying a transgene consisting of the endogenous fat-3 promoter and the fat-3 coding region in the fat-3 ( lg8101 ) mutant [36] , showed wild-type survival on P . aeruginosa , confirming that pathogen sensitivity is a direct consequence of loss of fat-3 function ( Figure 3A , Table 2 ) . fat-3; [Punc-119::fat-3] transgenic animals expressing the fat-3 coding sequence under the control of the neuron-specific unc-119 promoter , however , remained significantly more susceptible to P . aeruginosa ( Figure 3B , Table 2 ) . Expression of fat-3 under the control of the muscle-specific myo-3 promoter also failed to rescue the fat-3 mutant sensitivity to P . aeruginosa ( Figure 3B , Table 2 ) . Together , these results indicate that fat-3 gene expression and fat-3-dependent PUFA synthesis in the muscles or neurons does not significantly affect immune function . By contrast , fat-3; [Pelt-2::fat-3] transgenic animals expressing the fat-3 gene under the control of the intestine-specific elt-2 promoter showed survival kinetics on P . aeruginosa that were indistinguishable from wild-type ( Figure 3B , Table 2 ) . Intestine-specific rescue of fat-3 pathogen sensitivity indicates that fat-3-dependent synthesis of PUFAs in the intestine is sufficient for normal immune function in response to bacterial infection . Animals that have lost fat-3 gene function display pleiotropic abnormalities , including impaired motility , a weakened cuticle , decreased defecation rate and irregular expulsion [36] , [42] . Many of these defects are associated with impaired neurotransmission due the loss of fat-3 function in the neurons [36] , [42] . We also found that fat-3 ( wa22 ) animals had a marginal but significant decrease in adult lifespan ( Table 1 ) , contrary to a previous report [42] . Together , these defects may indicate a general poor health of fat-3 mutants that could indirectly impact their ability to survive P . aeruginosa infection . To determine if these pleiotropies could be dissociated from immune defects , we first analyzed the effects of PUFA supplementation in fat-3 ( wa22 ) animals on these defects , in addition to survival on P . aeruginosa . We note that , with the possible exception of AA on adult life span , PUFA supplementations did not have any significant effects on wild-type animals ( Table 1 ) . Consistent with a previous report , supplementation with GLA [42] or GLA and SDA combined rescued the defecation and locomotion defects , and lifespan of fat-3 ( wa22 ) animals ( Table 1 ) . GLA and SDA , however , failed to rescue aldicarb resistance indicating that these PUFAs were not sufficient to restore synaptic transmission , as measured by acetylcholine release [43] ( Table 1 ) . By contrast , supplementation with either of the 20-carbon PUFAs , AA or EPA rescued fat-3 ( wa22 ) for all the phenotypes tested: adult lifespan , aldicarb resistance , defecation and locomotion defects ( Table 1 ) . Yet , fat-3 ( wa22 ) animals supplemented with either EPA or AA remained sensitive to P . aeruginosa ( Figure 2D , Table 1 ) . Failure to rescue the fat-3 ( wa22 ) immune defect was not due to insufficient incorporation of EPA or AA because the levels of these 20-carbon PUFAs in the fat-3 ( wa22 ) mutants following supplementation was equivalent to , or higher than , in wild-type ( Figure S2C and S2D ) . Since AA or EPA could rescue fat-3 ( wa22 ) neuronal and muscular defects and adult lifespan but not pathogen sensitivity , while GLA and SDA rescued pathogen sensitivity , but not neurotransmission ( Figure 2C and 2D , Table 1 ) , we can conclude that pathogen susceptibility of the fat-3 ( wa22 ) mutant was not due to neuromuscular defects or a shortened adult lifespan . Instead , pathogen sensitivity of fat-3 mutants is likely to be caused by factors dependent on levels of GLA and SDA . This conclusion is further supported by tissue-specific rescue experiments using transgenic animals . Intestinal expression of the fat-3 gene only partially rescued the locomotion defects ( Table 2 ) despite completely rescuing the pathogen sensitivity of the fat-3 ( lg8101 ) mutant ( Figure 3B , Table 2 ) . Full rescue of the defecation defect and the partial rescue of locomotion by intestinal expression of fat-3 are not surprising because most FAT-3 protein is in the intestine [42] and it is therefore likely that PUFAs synthesized in the intestine could be transported to other parts of the body . As with pathogen sensitivity , muscle-specific expression of fat-3 was not sufficient to rescue defecation and movement defects ( Table 2 ) . By contrast , neuronal expression of the fat-3 gene that also failed to rescue pathogen susceptibility ( Figure 3B ) , could fully rescue the defecation and locomotion defects of the fat-3 ( lg8101 ) mutant ( Table 2 ) , indicating neuromuscular and immune functions may be independently regulated by fat-3 . Together , the PUFA supplementation and tissue-specific rescue experiments indicate that the susceptibility of fat-3 mutants to P . aeruginosa infection is not associated with neuromuscular and lifespan defects . To further rule out the possibility that the increased pathogen sensitivity of fat-3 ( wa22 ) mutants was a consequence of a general increased sensitivity to any insults , we determined the ability of fat-3 ( wa22 ) animals to survive or develop under a number of additional stress conditions . We assayed the sensitivity of fat-3 animals to heavy metal stresses by determining the proportion of embryos that could develop into adults in the presence of toxic concentrations of cadmium or copper metals [44] . Exposure to toxic levels of cadmium results in cell damage and is thought to induce the transcription of a number of defense and repair genes [45]–[47] . Following exposure to 30 µM cadmium chloride , less than 65% of fat-3 ( wa22 ) embryos successfully developed into adults . By contrast , approximately 75% of wild-type embryos grew to adults , indicating that fat-3 ( wa22 ) animals were more sensitive to cadmium ( Table 3 ) . fat-3 ( wa22 ) animals were also more sensitive to copper , with significantly fewer fat-3 ( wa22 ) adults than wild-type developed from embryos following exposure to 250 µM copper sulfate ( Table 3 ) . The fat-3 ( wa22 ) mutant was also more susceptible to a 1% solution of the detergent Triton X-100 . Approximately 26% of fat-3 ( wa22 ) animals survived a 1-hour incubation with the detergent , compared to almost 83% for wild-type ( Table 3 ) . This susceptibility may be associated with the compromised cuticle of the fat-3 mutant [42] , but may also indicate defects in membrane structure and permeability in fat-3 ( wa22 ) animals due to the absence of long chain unsaturated fatty acids . Supplementation with GLA and SDA , as well as AA or EPA fully rescued fat-3 ( wa22 ) susceptibility to both heavy metals and to detergent ( Table 3 ) . This may indicate that susceptibility to these stresses is not specific to a particular PUFA species but dependent , instead , on the total level of unsaturated fatty acids in the animal . Importantly , that AA or EPA rescued fat-3 ( wa22 ) susceptibility to these abiotic stresses but not susceptibility to pathogens further dissociated immune function from general stress resistance in the fat-3 ( wa22 ) mutant . The physiological temperature that supports C . elegans development ranges from 15–25°C [48] . To determine the ability of fat-3 ( wa22 ) animals to tolerate extreme temperatures , we assayed for the number of one-day old adults that remained alive following exposure to 36°C and 0°C for a defined period . In contrast to heavy metal and detergent stresses , fat-3 ( wa22 ) animals were more resistant than wild-type to extreme temperatures . A significantly higher proportion of fat-3 ( wa22 ) than wild-type animals survived the 36°C heat stress for 10 hours ( Table 3 ) and 12 hours ( data not shown ) . Similarly , following a 24-hour exposure to 0°C cold stress , significantly more fat-3 ( wa22 ) than wild-type adults remained alive ( Table 3 ) . The findings that supplementation with GLA and SDA did not restore cold and heat resistance ( Table 3 ) , but effectively restored pathogen sensitivity of the fat-3 ( wa22 ) mutant to wild-type ( Table 1 ) further disassociates resistance to extreme temperatures from pathogen susceptibility . The observations that fat-3 ( wa22 ) animals were not always more sensitive than wild-type to all the abiotic insults tested , and that heavy metal and detergent sensitivity but not immune functions could be rescued by AA or EPA , further support the hypothesis that susceptibility of the fat-3 ( wa22 ) animals to P . aeruginosa is likely to be due to specific immune defects . The requirement for fat-3 in the intestine , the primary site of P . aeruginosa infection in C . elegans , raised the possibility that GLA and SDA could influence immune gene expression . To provide a further link between fat-3 gene function and innate immunity , we compared the expression of 50 infection-response genes [49] by qRT-PCR , in 1-day-old adult wild-type and fat-3 ( wa22 ) animals ( Table S1 ) . These 50 genes were selected based on one or more of the following criteria: a ) genes with known or predicted antimicrobial activity , including spp-1 [50] and abf-2 [25] , b ) genes required for survival against P . aeruginosa infection [27] , [28] , and c ) genes known to be differentially regulated in response to P . aeruginosa infection [27] , [28] . We quantified the expression of these genes under normal growth conditions on E . coli to determine basal or constitutive mRNA levels , and following a 12-hour exposure to P . aeruginosa to compare mRNA levels in infected animals ( Table S1 ) . The constitutive expression of 22 genes ( 44% ) was significantly different between age-matched fat-3 ( wa22 ) and wild-type animals raised on E . coli . Of these , 12 genes were expressed at significantly lower levels ( Figure 4A ) and 10 were expressed at significantly higher levels ( Table S1 ) in the fat-3 ( wa22 ) mutant compared to wild-type . These results indicated that the missing PUFAs in the fat-3 ( wa22 ) mutant are required for proper basal or constitutive expression of a significant subset of infection-response genes tested . Genes expressed at lower levels in fat-3 ( wa22 ) included three antimicrobial peptide homologs , spp-1 , encoding a saposin-like protein , and two lysozymes , encoded by lys-2 and lys-7 ( Figure 4A ) . The reduced expression of these putative antimicrobial genes in uninfected animals raised the possibility that basal immune function of the fat-3 ( wa22 ) mutant may be compromised . To address this hypothesis , we first determined if the 12 constitutively down-regulated genes were required for immunity in wild-type animals . We found that RNAi-mediated knockdown of spp-1 , lys-2 , lys-7 , dct-17 and F08G5 . 6 resulted in significantly increased sensitivity to P . aeruginosa-mediated killing ( Table 4 ) . The remaining genes that did not induce any survival defects on P . aeruginosa following RNAi knockdown were further tested using a colonization assay . Comparing the degree of intestinal colonization by PA14-GFP , a derivative of P . aeruginosa PA14 that expresses the GFP protein [38] , provides a more sensitive measure of the infection process , allowing us to detect smaller defects in worm immunity . RNAi-mediated knockdown of lec-11 and F49F1 . 1 resulted in a significant increase in the rate of colonization by PA14-GFP ( Figure S4A ) , despite a wild-type survival phenotype on the pathogen ( Table 4 ) . We henceforth refer to these seven infection-response genes as immunity genes , due to their role in protecting C . elegans from infection . The demonstration that a majority of the genes that were expressed at reduced levels in fat-3 ( wa22 ) animals were functionally important for immunity against P . aeruginosa provides a potential molecular basis for the sensitivity of the fat-3 ( wa22 ) mutant to infection and suggests that the absence of GLA and SDA can compromise basal immunity . We next compared expression levels of the 50 infection-response genes following a 12-hour infection with P . aeruginosa . The mRNA levels of only seven genes ( 14% ) were significantly different between P . aeruginosa-infected fat-3 ( wa22 ) and wild-type animals ( Figure S4B , Table S1 ) , indicating that majority of the genes in the fat-3 ( wa22 ) mutant , including a number of genes misregulated under basal conditions , responded to P . aeruginosa infection to reach levels similar to the wild-type worm . With the exception of lys-7 , the mRNA levels of all the genes that were constitutively expressed at lower levels in uninfected fat-3 ( wa22 ) animals were indistinguishable from wild-type following P . aeruginosa infection ( Figure 4B , Table S1 ) , indicating that , at the level of gene expression , the ability of fat-3 ( wa22 ) mutants to respond to infection remained largely intact . Taken together , these results indicate that despite displaying a largely normal inducible response to infection , the significant reduction in constitutive expression of immunity genes was sufficient to render fat-3 ( wa22 ) animals more susceptible to P . aeruginosa-mediated death . These results underscore the importance of basal or constitutive immunity for protection from pathogens . Given that fat-3 expression in the intestine is required to protect C . elegans from P . aeruginosa-mediated killing ( Figure 3B ) , we wondered if expressing fat-3 in the intestine would be sufficient to restore the expression of infection-response genes in the fat-3 mutants . Infection-response gene expression was quantified by qRT-PCR in transgenic fat-3 strains that specifically express the fat-3 transgene in the intestine , muscles or neurons . As these transgenic strains were constructed in the fat-3 ( lg8101 ) background , we first confirmed that , with the exception of lec-11 , the basal gene expression of the 12 genes assayed were similarly misregulated in fat-3 ( lg8101 ) and fat-3 ( wa22 ) relative to wild-type ( Table S2 ) . The reason for this allele-specific effect on lec-11 expression is currently unclear . Excluding lec-11 from the remaining analysis with transgenic animals , we note that the expression of the fat-3 gene under the control of its own promoter was sufficient to rescue the expression of all but one of the 11 infection-response genes tested ( Figure S5A ) , indicating that the requirement for fat-3 in immune function is strongly correlated with the expression of infection-response genes . Intestine-specific expression of fat-3 restored the expression of seven of the eight the down-regulated infection-response genes , including the immune-specific genes spp-1 , lys-7 and F08G5 . 6 ( Figure S5B ) , indicating that fat-3 is required in the intestine to regulate basal gene expression . By contrast , and consistent with the pathogen survival assay ( Figure 3B ) , expression of fat-3 specifically in the muscles failed to restore the expression of any of the genes tested , with the exception of F35E12 . 8 ( Figure S5C ) . Expression of fat-3 in neuronal tissues was similarly ineffective at restoring infection-response gene expression; expression of only two genes , F35E12 . 8 , and F08G5 . 6 were restored to wild-type ( Figure S5D ) . Analysis of spp-1 expression in these transgenic animals is revealing , as spp-1 is expressed only in the intestine [24] . Expression of spp-1 was restored to wild-type levels when fat-3 was expressed specifically in the intestine ( Figure S5B ) but not in the muscles ( Figure S5C ) or neurons ( Figure S5D ) . Together , these data confirm our hypothesis that fat-3 functions in the intestine to influence the expression of a number of infection-response genes that contribute to the protecting C . elegans from P . aeruginosa infection . Of the 12 genes that are positively regulated by fat-3 ( Figure 4A ) , the expression of lys-2 , dod-19 , ZK6 . 11 and F08G5 . 6 has been reported to be dependent on the p38 MAP kinase pathway [28] . To determine if altered constitutive gene expression in the fat-3 ( wa22 ) mutant correlated with defects in p38 MAP kinase signaling , we compared mRNA levels between fat-3 ( wa22 ) and sek-1 ( km4 ) , a p38 MAP kinase kinase mutant [29] , adults raised on E . coli . Using the set of 22 genes that were significantly altered in fat-3 ( wa22 ) animals , we found that basal gene expression between fat-3 ( wa22 ) and sek-1 ( km4 ) animals was highly correlated ( Figure 4C ) , with the expression of 18 out of 22 genes being similarly altered in both strains . A majority of these genes , however , were expressed at lower levels in sek-1 ( km4 ) compared to fat-3 ( wa22 ) animals ( Figure 4A and C ) . A similarly significant correlation was seen between fat-3 ( wa22 ) animals and another MAP kinase pathway mutant , the p38 MAP kinase homolog , pmk-1 ( km25 ) ( R2 = 0 . 4409 , p = 0 . 0008 ) . Significant correlations in basal gene expression were also seen between fat-3 ( wa22 ) and sek-1 ( km4 ) ( R2 = 0 . 332 , p = 0 . 0001 ) , and between fat-3 ( wa22 ) and pmk-1 ( km25 ) ( R2 = 0 . 259 , p = 0 . 0003 ) animals when the analysis was extended to the entire 50 gene-set . In addition to the p38 MAP kinase pathway , the Sma/TGF-beta and Insulin/Insulin growth factor signal transduction pathways also play important roles in C . elegans immunity [19] , [51] , [52] . However , basal gene expression in fat-3 ( wa22 ) animals was not significantly correlated with the null allele of the FOXO transcription factor of the insulin pathway , daf-16 ( mu86 ) ( Figure 4D ) , or the null allele of the Sma/TGF-beta receptor , sma-6 ( wk7 ) ( Figure 4E ) . This high concordance in altered basal gene expression between fat-3 ( wa22 ) and the sek-1 ( km4 ) or pmk-1 ( km25 ) mutants led us to hypothesize that the basal activity of the p38 MAP kinase pathway may be compromised in fat-3 ( wa22 ) animals . As a direct measure of the effect of the fat-3 mutation on p38 MAP kinase pathway activity , we used immunoblot analyses to determine the levels of activated PMK-1 protein in fat-3 ( wa22 ) and wild-type age-matched adults raised on E . coli . The sek-1 ( km4 ) mutant , previously shown to have a complete loss of PMK-1 phosphorylation and increased susceptibility to infection [29] , was used as a control . Wild-type worms had detectable levels of phosphorylated PMK-1 indicating some basal p38 MAP kinase activity under normal physiological conditions . By contrast , fat-3 ( wa22 ) had decreased levels of phosphorylated PMK-1 protein ( Figure 4F ) , indicating a reduction in basal activity of the p38 MAP kinase pathway . This decrease in the basal levels of activated PMK-1 in fat-3 ( wa22 ) animals , as opposed to the complete loss of phosphorylated PMK-1 protein in sek-1 ( km4 ) animals , is consistent with the trends indicated by the qRT-PCR analysis , showing that the expression levels of infection-response genes in the fat-3 ( wa22 ) mutant were not as low as in the sek-1 ( km4 ) mutant ( Figure 4A ) . The decrease in PMK-1 phosphorylation and immune gene expression indicate that although the fat-3 ( wa22 ) null mutation does not completely abolish PMK-1 activity , it is sufficient to compromise immune function in the worm . As shown in Figure 4B and Table S1 , a majority of the infection-response genes were expressed at wild-type levels in infected fat-3 ( wa22 ) animals . Consistent with this gene expression data , immunoblot analysis of PMK-1 activation in fat-3 ( wa22 ) and wild-type lysates following a 12-hour exposure to P . aeruginosa revealed that PMK-1 phosphorylation in the infected fat-3 ( wa22 ) mutant was restored to 81% of that seen in infected wild-type animals ( Figure 4F ) . By contrast , in sek-1 ( km4 ) animals , the level of phosphorylated PMK-1 protein remained at background following infection , ( Figure 4F ) , and immunity genes that were expressed at low levels under basal condition remained low following PA14 infection ( Figure 4B ) . Thus , both the gene expression and PMK-1 phosphorylation analyses support the conclusion that FAT-3 Δ6-desaturase is necessary to maintain basal activation of PMK-1 but appears to be dispensable for PMK-1 activation and the associated immune gene expression during infection . Since the loss of fat-3 gene function resulted in the reduced phosphorylation of PMK-1 , fat-3 ( wa22 ) mutants are expected to manifest phenotypes that are associated with a loss or reduction in p38 MAP kinase signaling . A well-characterized defect of the sek-1 ( km4 ) mutant that is associated with a complete loss of PMK-1 phosporylation is an increased susceptibility to arsenic-induced oxidative stress [53] . We therefore compared the ability of 1-day-old adult sek-1 ( km4 ) and fat-3 ( wa22 ) mutants to survive on 3 mM arsenic . As expected , fat-3 ( wa22 ) and sek-1 ( km4 ) animals had similar survival rate following exposure to arsenic ( Figure 4G ) , further indicating that the p38 MAP kinase pathway is functionally compromised in fat-3 ( wa22 ) animals . The increased sensitivity of fat-3 loss-of-function mutants to pathogen infection and arsenic stress is associated with reduced basal p38 MAP kinase signaling . Among the genes that positively regulated by fat-3 are three antimicrobial peptide homologs: spp-1 , which encodes a saposin-like protein , and lys-2 and lys-7 that are predicted to encode for lysozymes ( Figure 4A ) . This raises the possibility that the influence of fat-3 on immune function may be distinct and separable from its arsenic-induced oxidative stress response . To identify fat-3-regulated genes that are specifically require for immunity , we inactivated each of the 12 genes down-regulated in the fat-3 ( wa22 ) mutant individually by RNAi and determined the effects of gene knockdown on pathogen and arsenic sensitivity . As shown in Table 4 , four groups of genes were identified . Members of the first group , dct-17 and F49F1 . 1 , were like sek-1 ( km4 ) and fat-3 ( wa22 ) in that they were required to protect C . elegans from both pathogen and arsenic . By contrast , inactivation of the group 2 genes ZK6 . 11 , dod-19 and T01D3 . 6 , had no detectable effect on pathogen or arsenic survival . Of particular interest are members of group 3 , spp-1 , lys-2 and lys-7 , F08G5 . 6 and lec-11 , that are specific to immune functions; they were required to protect C . elegans from P . aeruginosa infection but not from arsenic-induced oxidative stress . F35E12 . 8 and gst-38 are members of group 4 that were not required for C . elegans survival against infection , but were required for the response to oxidative stress . Interestingly , gst-38 is predicted to encode a glutathione-S-transferase that plays an important role in protection from oxidative stress . We are thus able to distinguish among the fat-3-regulated genes , a set of immune-specific genes that are distinct from those required for protection from arsenic toxicity . These results strongly indicate that fat-3 influences the expression of genes that have specific role in innate immunity . The specific rescue of fat-3 ( wa22 ) survival on P . aeruginosa by GLA and SDA led us to hypothesize that basal PMK-1 phosphorylation and expression of infection-response genes would be restored with the supplementation of these PUFAs . As with the pathogen survival assay , we determined the effect of PUFA supplementations on the basal expression of 10 infection-response genes , 6 that were down-regulated and 4 that were significantly up-regulated in the fat-3 ( wa22 ) mutant , by qRT-PCR ( Figure 5 ) . As expected , individual addition of GLA or SDA fatty acids resulted in a partial restoration of immune gene expression in uninfected fat-3 ( wa22 ) worms , while simultaneous addition of both fatty acids completely restored the majority of basal immune gene expression in the fat-3 ( wa22 ) mutant to wild-type levels ( Figure 5A ) , including spp-1 , lys-2 , lys-7 and lec-11 that are specifically required for immune function ( Table 4 ) . By contrast , supplementation with ALA , AA or EPA , the PUFAs that did not rescue fat-3 ( wa22 ) pathogen sensitivity ( Figure 2D ) , also had no significant effect on the expression of these misregulated infection-response genes , with the exception of lec-11 ( Figure 5B ) . Two genes that had no effect on survival when knocked down by RNAi; clp-1 and ZK39 . 6 ( data not shown ) , also did not appear to be affected by the addition of any of the above PUFAs . The conclusion that both GLA and SDA are specifically required for survival against PA14 infection , through the regulated expression of infection response genes , was further supported by immunoblot assays that determined the effect of fatty acid supplementation on PMK-1 phosphorylation ( Figure 5C ) . Supplementation with both GLA and SDA completely restored the level of phosphoryated PMK-1 in the fat-3 ( wa22 ) mutant to wild-type , indicating that both fatty acids are required to maintain basal PMK-1 activation , and thus the basal PMK-1-dependent MAP kinase immune function . Supplementation with ALA , AA or EPA , on the other hand , had no detectable effect on the levels of phosphorylated PMK-1 in the fat-3 ( wa22 ) mutant . Supplementation with GLA and SDA also rescued the fat-3 ( wa22 ) response to oxidative stress , again functionally confirming the restoration of p38 MAP kinase activity with the supplementation of the two missing fatty acids ( Figure S6 ) . Supplementation with AA and EPA had no effect on the oxidative stress response , as expected from their lack on effect on PMK-1 phosphorylation or gene expression in the fat-3 ( wa22 ) mutant ( Figure S6 ) . We thus provide strong genetic evidence that two specific 18-carbon PUFAs , GLA and SDA play a vital role in maintaining basal activity of the p38 MAP kinase pathway and consequently influence both immune and stress responses in C . elegans . That the fat-3 gene , through the synthesis of SDA and GLA , influences the basal expression of immune-specific genes , such as spp-1 , lys-2 and lys-7 , and lec-11 , further indicates that fat-3 has a specific role in innate immunity , independent of its influences on oxidative stresses .
Using C . elegans mutants defective in PUFA biosynthesis , and detailed analysis of the Δ6-desaturase mutant fat-3 ( wa22 ) , we identified two 18-carbon PUFAs , GLA , an omega-6 fat , and SDA , an omega-3 fat , that play critical roles in basal immunity . Depletion of GLA and SDA resulted in disrupted basal activity of the p38 MAP kinase pathway and defective basal immune gene expression , leading to increased susceptibility to infection by P . aeruginosa . We also demonstrated that fat-3 is required in the intestine , the site of P . aeruginosa infection , to protect C . elegans from pathogen-mediated death and to regulate the expression of immunity genes . The p38 MAP kinase pathway is required to protect C . elegans from infection and oxidative stress . Importantly , we showed that fat-3 , through the synthesis of GLA and SDA , affects the expression of a subset of genes that are specifically required for immune function but not oxidative stress response . We further showed that loss of fat-3 gene function does not result in a general loss of defense against stresses , and provided evidence that support an independent role for GLA and SDA in innate immunity . Fatty acid desaturases have previously been shown to have important roles in innate immunity in mammals and plants . In mice , the stearoyl-Coenzyme A desaturase protein SCD1 is required for the production of immune effector molecules . SCD1 catalyses the Δ9 desaturation of 16- and 18-carbon saturated fatty acids into the monounsaturated palmitoleic ( PLA , 16:1n9 ) and OA that are bactericidal against Gram-positive pathogens . Consequently , mice carrying loss of function SCD1 mutations are defective in clearing skin infections by Streptococcus pyogenes and Staphylococcus aureus [54] . Whether these MUFAs are also involved in immune signaling remains to be investigated . In plants , mutants in the Arabidopsis SSI2/FAB2 gene , which encodes a Δ9 desaturase , show enhanced resistance to bacterial and biotrophic oomycete fungal pathogens but increased susceptibility to a necrotrophic fungal pathogen [55]–[57] . The immune phenotypes of the ssi2 mutant are due to low levels of OA , which leads to the constitutive activation of the salicylic acid-dependent immune pathway and repression of the jasmonic acid ( JA ) -dependent pathway by unknown mechanism ( s ) [55] , [57] , [58] . Disruption of another desaturase that catalyzes the conversion of LA to ALA , encoded by the spr2 gene in tomato plants and fad-7 and fad-8 in Arabidopsis , also results in diminished JA signaling and a reduced response to wounding by insects and infection by fungal pathogens [59]–[61] . Similar to the lipid-dependent manipulation of immune signaling in plants , we showed for the first time that GLA and SDA , the products of FAT-3 , an animal Δ6 desaturase , are required to maintain basal expression of immunity genes through their effect on the phosphorylation of a C . elegans p38 MAP kinase homolog , PMK-1 . In mammals , the omega-6 and omega-3 18-carbon PUFA families cannot be synthesized de novo . They must be produced from the dietary essential fatty acids , LA and ALA through a series of elongation and desaturation reactions . LA and ALA have relatively little pharmacologic action of their own; their effects derive largely from metabolic processing to more active end products . The human ortholog of the C . elegans FAT-3 enzyme , fatty acid desaturase 2 ( FADS2 ) regulates production of GLA and SDA from their LA and ALA precursors [62] . This reaction is slow and can be further impaired by numerous factors , including aging , nutrient deficiencies , diabetes , hypertension , and life style factors , such as stress , smoking and excessive alcohol consumption [63] , [64] . Thus , reduced dietary intake of LA and ALA , coupled with any of these conditions could lead to insufficient production of GLA and SDA in the body , potentially leading to compromised basal immunity analogous to the C . elegans fat-3 ( wa22 ) mutant . Reduced activity of FADS2 could also result in the decreased production of down-stream metabolites , such as the inflammatory mediators AA and EPA [64] . As noted above , we have provided several lines of evidence that the decreased ability of fat-3 mutants to survive infection by P . aeruginosa is a consequence of diminished synthesis of GLA and SDA ( Figure 2 ) . By contrast , the 20-carbon PUFAs , AA and EPA appear to have minimal effects on the infection response to P . aeruginosa . Mutants deficient in different 20-carbon PUFAs , such as elo-1 ( gk48 ) , elo-1 ( wa7 ) , fat-1 ( wa9 ) , fat-4 ( ok958 ) and fat-4 ( wa14 ) show no defects in their response to infection ( Figure 2A ) . Although supplementation with AA or EPA was sufficient to restore many of the additional defects displayed by the fat-3 ( wa22 ) mutant , neither of these PUFAs had any significant effects on the immune defects of fat-3 ( wa22 ) , as measured by survival on pathogen , expression of immune-specific genes and phosphorylation of PMK-1 . In mammals , AA can be metabolized by cyclooxygenase , lipoxygenase and cytochrome P-450 ( CYP ) enzymes to produce important signaling molecules [3] . Since the C . elegans genome does not contain obvious orthologs of mammalian cyclooxygenases and lipoxygenases or of prostanoid and leukotriene receptors , a role for prostaglandin and leukotrienes in lipid signaling can be largely excluded . However , C . elegans shares with mammals the capacity to produce CYP-dependent eicosanoids . Recently , it was demonstrated that C . elegans contains microsomal monooxygenase systems , consisting of CYP-29A3 and CYP-33E2 cytochromes and an EMB-8 microsomal NADH-cytochrome c reductase that catalyze the epoxidation and hydroxylation of EPA and AA to specific sets of epoxy- and hydroxy-derivatives [65] . The ability of C . elegans to generate endogenous CYP-dependent eicosanoids could be blocked by inhibitors , such as adamantyl-3-dodecyl urea ( ADU ) developed against mammalian soluble epoxide hydrolases [65] suggesting that this component of eicosanoid metabolism may be conserved between C . elegans and mammals [66] . CYP-derived eicosanoids have been implicated in a variety of critical biological processes in humans , including homeostasis and inflammation [67] . Although our genetic analysis indicates that AA and EPA have no significant effect on the ability of C . elegans to survive infection by bacterial pathogens , we cannot not rule out other , as yet unidentified , roles for these 20-carbon fatty acids in the immune response . CYP enzymes also play a role in the synthesis of oxylipins , oxygenated fatty acids synthesized from precursor PUFAs [68] . Oxylipins are typically derived from cis PUFAs , such as LA , ALA or AA [15] , and act as signaling and effector molecules . Among the best known oxylipins are jasmonic acid and its derivatives that form vital signaling and effector molecules in plant immune responses [16] . In mammals , eicosanoids form one of the major groups of oxylipins , and are potent modulators of various physiological processes , including the regulation of inflammation [4]–[6] . Many oxylipins also show direct antimicrobial activities against bacteria , fungi and oomycetes [69]–[71] . A recent report indicated that in Cyanobacteria , GLA and SDA can be converted to oxylipins by CYP enzymes , but this process is not well characterized [72] . Little is known of oxylipin synthesis in C . elegans , but the presence of functional cytochrome P-450 enzymes leaves open the possibility that GLA and SDA could be processed into functional signaling molecules or immune effectors that directly influence the immune response . Future work will focus on determining if deficiency in CYP-derived eicosanoids or oxylipins could affect innate immune function in C . elegans . The disruption of the FAT-3 Δ6-desaturase also resulted in altered immune gene expression and defective basal p38 MAP kinase activity ( Figure 4 ) . We demonstrate that this reduction in basal activity of p38 MAP kinase signaling and the concomitant increased susceptibility to both infection and oxidative stress , due to loss of fat-3 function , are associated with GLA and SDA deficiencies . In C . elegans , the p38 MAP kinase is required for both the basal and induced expression of genes in response to infection [28] and functions through the activation of the p38 MAP kinase ortholog , PMK-1 . Under normal growth conditions , this pathway is active as low levels of phosphorylated PMK-1 can be detected . We present the first evidence that the maintenance of PMK-1 basal activity requires GLA and SDA . Depletion of GLA and SDA in the fat-3 ( wa22 ) mutant significantly reduced the levels of phosphorylated PMK-1 , without affecting the PMK-1 protein levels . This disruption further resulted in the altered basal expression of a number of immunity genes , as well as an increased susceptibility to oxidative stress . Despite retaining an intact response to infection in the absence of GLA and SDA , reduction in basal p38 MAP kinase signaling in the fat-3 mutant was sufficient to cause increased susceptibility to both infection and oxidative stress , highlighting the vital importance of basal immunity . Previous research has similarly demonstrated the importance of this constitutive response in mammals and other invertebrates . In mammalian systems , beta-defensins form a major part of the constitutive immune response , and are continuously expressed in many epithelial tissues . Mice deficient in the production of the lung β-defensin-1 ( mBD-1 ) showed defects in their ability to clear H . influenzae infections from the lung [73] . In this case , however , the mBD-1 mutant mice were defective in both the constitutive as well the inducible expression of the single effector molecules . Here , with the fat-3 mutant , we demonstrate the essential requirement of a constitutive immune response pathway for survival against the pathogen , despite the presence of a functional inducible infection response in C . elegans . It would be additionally interesting to determine if GLA and SDA deficiencies in humans are also associated with reduced p38 MAP kinase activity and hypersensitivity to infection , and if these pathophysiological conditions could be restored through dietary supplementation of GLA and SDA . The mechanism by which GLA and SDA affect the activity of p38 MAP kinase signaling and immune gene expression is currently unknown . GLA and SDA have a range of actions , and future work will be required to determine if their effects are direct or indirect . Lipids form a major constituent of cell membranes , and the effects of GLA and SDA may be associated with their influence on the physical properties of these membranes . The extent of membrane fatty acid unsaturation is known to influence membrane structure , fluidity and permeability [74] . Membrane fluidity is the extent of molecular disorder and molecular motion within the lipid bilayer [75] . This physical state of the membrane lipid can act directly to regulate membrane-bound proteins , such as receptor-associated protein kinases and ion channels , leading to alteration of gene expression [76] , [77] . Thus , the effect of GLA and SDA depletion on reduced signaling through the p38 MAP kinase pathway may be linked to their effects on membrane fluidity , perhaps analogous to osmoregulation in yeast . When glucose was added to yeast medium to raise osmolarity , an associated reduction in membrane fluidity was observed [78] . When shifted to high osmolarity , yeast cells rapidly stimulate a MAP kinase cascade , the high-osmolarity glycerol ( HOG ) pathway , which orchestrates part of the transcriptional response [79] . Alternatively , the levels of SDA and GLA could affect lipid-protein interactions of membrane receptors and thus the intensity of signaling , analogous to the effects of OA on G protein coupled receptor ( GPCR ) -associated signaling . Addition of OA alters membrane structure and results in reduced G protein receptor activity in 3T3 cell derived membranes [80] . GPCRs are capable of activating MAPKs using an intricate signaling network [81] . It would be interesting to determine if depletion of GLA and SDA results in changes in membrane structure or fluidity that leads to reduced p38 MAP kinase signaling , through their effects on GPCRs or other membrane-associated signaling molecules . Another important aspect of a cell membrane is its selective permeability , which plays a vital role in maintaining cell integrity and preventing entry of toxins [82] . Given that most pathogens secrete toxins and hydrolytic enzymes that can harm host cells , membrane permeability might affect the outcome of an infection . The fat-3 ( wa22 ) mutant is more sensitive to the detergent Triton X-100 , potentially pointing to a defect in cell membrane permeability . However , the detergent sensitivity of the fat-3 ( wa22 ) mutant could be rescued without affecting its sensitivity to P . aeruginosa infection ( Table 3 , Figure 2C , D ) , indicating that the potentially altered cell membrane permeability of the fat-3 ( wa22 ) mutant does not impact immune function . Of note is that the fat-3 ( wa22 ) mutant also has a defective cuticle [42] , which could account for , or partly influence , the detergent sensitivity of the fat-3 ( wa22 ) mutant , rather than a defect in membrane permeability . Lipids perform a multitude of roles in the immune system , influencing both the innate and adaptive immune responses to infection . While their roles as inflammatory precursors is well known , studies have also identified lipid derived ligands that function through the mammalian Peroxisome Proliferators Activated Receptors ( PPARs ) to modulate the adaptive T cell response [83] and activate NK cells and dendritic cells [9] , [10] . PPARs are a subset of nuclear hormone receptors ( NHRs ) , a family of transcription factors activated by small lipophilic ligands that control a number of metabolic and systemic processes . In mammals , GLA is primarily converted to DGLA , a precursor of anti-inflammatory eicosanoids [64] . In keratinocytes , however , GLA treatment also results in the induction of COX-2 expression in a PPAR-γ-dependent manner . Addition of GLA results in the translocation of PPAR-γ to the nucleus and a consequent increase in COX-2 promoter activity and COX-2 protein levels in the cell [84] . This suggests a possible direct signaling role for GLA in regulating expression of the COX-2 gene , through PPAR-γ to mediate inflammatory immune responses . C . elegans has no known inflammatory response but does posses 284 putative NHRs [85] , several of which affect the fat content [33] or the lipid metabolism of the worm [34] , [86] . A number of these NHRs are differentially regulated in response to infection [27] , [28] , and reducing expression of nhr-112 , by RNAi , results in increased sensitivity to infection by P . aeruginosa [27] . The interaction between lipid ligands , NHRs and the MAP kinase pathways has been explored previously in the context of the PPAR receptors in mammalian systems . In CD4+ T cells , unliganded PPARα suppresses p38 MAP kinase phosphorylation . Activation of PPARα by its lipid ligand relieves this restraint , allowing phosphorylation and activation of the MAP kinase pathway to induce cytokine production in these T cells [87] . Conversely , the p38 MAP kinase pathway has also been implicated in the control of PPARα activation and function . In vitro analysis shows that phosphorylation by p38 MAP kinase enhances activity of PPARα in cardiomyocytes [88] , suggesting the possibility for similar complex interactions between the GLA and SDA PUFAs , NHRs and the p38 MAP kinase pathway in C . elegans innate immune function . In summary , the demonstration that GLA and SDA are required for basal immunity adds to out understanding of the varied roles for lipids in immunity . Disrupting the synthesis of GLA and SDA leads to an increased sensitivity to infection , and the disrupted basal activity of the p38 MAP kinase pathway . Given that numerous conditions , including aging , diabetes , stress and smoking could lead to GLA and SDA deficiencies , it will be of interest to explore the roles for these PUFAs in other organisms , including humans .
The strains fat-2 ( wa17 ) , fat-3 ( wa22 ) , elo-1 ( wa7 ) , elo-1 ( gk48 ) , fat-1 ( wa9 ) , fat-4 ( ok958 ) , fat-4 ( wa14 ) , daf-16 ( mu86 ) , sma-6 ( wk7 ) , sek-1 ( km4 ) , pmk-1 ( km25 ) and pha-1 ( e2123 ) were obtained from the Caenorhabditis Genome Center ( CGC ) . The fat-6 ( tm331 ) strain was obtained from Dr . Shohei Mitani ( National BioResource Project , Japan ) . The fat-7 ( wa36 ) and the fat-6 ( tm331 ) ; fat-7 ( wa36 ) double mutant were gifts from Dr . Jennifer Watts ( Washington State University ) . fat-3 ( lg8101 ) and the tissue specific rescue strains were gifts from Dr . Giovanni M Lesa ( University College London ) . All strains were grown on nematode growth media ( NGM ) plates at 25°C and fed with the E . coli strain OP50-1 unless noted otherwise . For the assays described below , unless noted otherwise , all the worms were grown at 25°C on E . coli HT115 expressing the pos-1 RNAi construct to prevent the production of progeny [89] . Bacteria expressing dsRNA directed against pos-1 , sek-1 , lys-7 and lec-11 were part of a C . elegans RNAi library expressed in E . coli strain HT115 ( Geneservice , Cambridge , U . K . ) . Bacteria expressing dsRNA directed against spp-1 , lys-2 , dct-17 , ZK6 . 11 , dod-19 , F49F1 . 1 , F35E12 . 8 , F08G5 . 6 , gst-38 , T01D3 . 6 were part of a C . elegans library expressed in E . coli strain HT115 ( Open Biosystems , Huntsville , Alabama ) . All bacterial strains were cultured under standard conditions at 37°C . ALA , AA and EPA supplements were obtained from NuChek Prep Inc . , GLA was obtained from Sigma-Aldrich Co . , while SDA was obtained from Cayman chemicals Co . Fatty acids were dissolved in 95% ethanol , and were added to a final concentration of 4 mM to E . coli HT115 carrying the pos-1 RNAi construct and allowed to dry overnight in the dark . Wild-type animals fed pos-1 RNAi bacteria supplemented with an equivalent amount of ethanol were used as controls . Worms were allowed to grow on the supplements from egg to one-day-old adults at a temperature of 25°C . For adult supplementation assays , young adult animals were placed on supplement plates for 48 hours before transfer . Supplementation , in each case , was verified by GC-MS , and collected worms were used for multiple assays . Survival assays were performed as described [27] . Plates were scored every 12 hours , and worms that showed no response to touch were scored as dead . Worms that died due to desiccation or by bagging due to live progeny were excluded from the analysis . Statistical analyses were performed using a Kaplan-Meier non-parametric comparison and a Logrank test , using Statview ( Version 5 . 0 . 1 , SAS Institute Inc . ) . All assays were repeated a minimum of three times , with approximately 120 worms tested per condition in each assay . Synchronized populations of several thousand adult worms were harvested at appropriate time points and washed with M9 buffer to remove excess bacteria . Worm pellets were treated with 3% H2SO4 in methanol and incubated at 80°C for 2 hours . Fatty acids were extracted as described previously [32] and analyzed by GC-MS using an HP 6890 gas chromatograph equipped with an HP-5MS column ( 30 m×0 . 25 mm×25 µm ) . One-day-old adult animals were exposed to OP50-1 , PA14 or PA14ΔgacA for 12 hours . For supplementation assays , worms were allowed to develop from embryos to young adults in the presence of fatty acids prior to analysis . RNA extraction and qRT-PCR were performed as previously described [27] . 25 µl reactions were performed using the iScript One-Step RT-PCR kit with SYBR green according to the manufacturer's instructions ( BioRad Laboratories , Hercules , CA ) . Cycling threshold ( Ct ) values were normalized to mRNA levels of three primer pairs , pan actin ( act-1 , 3 , 4 ) , F44B9 . 5 and ama-1 , which did not change with infection . Values and statistical analyses were calculated from normalized cycle threshold values prior to conversion to relative fold change . Colonization assays were performed on slow killing plates using a GFP-expressing PA14 strain ( PA14-GFP ) [38] and the pha-1 ( e2123 ) temperature sensitive mutant strain , to avoid the presence of progeny on the assay plates at the restrictive temperature of 25°C . Adult worms were exposed to PA14-GFP for 24 hours and the intestinal bacterial load was determined under a fluorescence microscope . The degree of colonization was determined as follows: worms with a lumen completely packed with PA14-GFP were classified as fully colonized , worms that showed a limited presence of GFP in the intestine were classified as partially colonized and worms with no detectable GFP expression in the intestine were classified as having undetectable levels of colonization . A minimum of 2 independent experiments was performed with a total of 60 worms per sample per time point for each experiment . Statistical analyses were performed using Chi-square tests . Life span assays were performed on NGM plates containing 0 . 1 mg/ml FUDR to prevent progeny from hatching [90] . Plates were seeded with concentrated OP50-1 and allowed to dry overnight . A synchronized population of L4 worms was placed onto the plates and scored every 24 hours . All strains were compared to the wild-type Bristol N2 strain and approximately 120 worms were used per strain per experiment . Statistical analyses were performed using a Kaplan-Meier non-parametric comparison and a Logrank test , using Statview ( Version 5 . 0 . 1 , SAS Institute Inc . ) . Adult worm samples were washed with M9 and frozen for analysis . Animals were homogenized in M9 buffer and protein content was measured with a BCA Protein Assay Kit ( Thermo Fisher Scientific Inc . ) before loading . A phospho p38 specific monoclonal antibody ( Cell Signaling Technology , Inc . ) , a p38 specific antibody ( Cell Signaling Technology , Inc . ) and an anti-actin antibody ( Sigma-Aldrich Co . ) were used at concentrations of 1∶1000 , 1∶250 and 1∶250 respectively . Slow killing plates were coated with a final concentration of 3 mM sodium arsenite and allowed to dry overnight [53] . Plates were then seeded with E . coli OP50-1 and approximately 30 adult worms were placed on each plate , for a total of 120 worms per strain . Plates were scored every 12 hours and worms that showed no response to touch were counted as dead . Aldicarb ( 2-methyl-2-[methylthio]- propionaldehyde O-[methylcarbamoyl]oxime; Chem Services , West Chester , PA ) stocks were dissolved in acetone and added to a final concentration 0 . 7 mM onto NGM plates [91] . Plates were allowed to dry overnight in the dark and then seeded with E . coli OP50-1 . 30 adult worms were placed on each plate and monitored every 4–6 hours for paralysis , with approximately 120 worms used per strain/treatment for each experiment . Statistical analyses were performed using Kaplan-Meier non-parametric comparisons and Logrank tests , using Statview ( Version 5 . 0 . 1 , SAS Institute Inc . ) . Defecation assays were performed as described [42] . Defecation cycles were measured as the time between successive posterior body contractions over a period of five minutes . All assays were conducted in closed Petri dishes seeded with OP50-1 , and a minimum of six adult animals was scored for per strain for each fatty acid treatment . Movement assays were performed as described [92] with M9 buffer in 96-well microtiter plates . A minimum of six animals was scored for total number of thrashes within a period of 2 minutes . One ‘thrash’ was defined as a change in the direction of bending at the mid-body . Metal toxicity assays were performed as described [44] . Briefly , sets of three 1-day-old adults were allowed to lay eggs on plates containing either CdCl2 ( 30 µM ) or CuSO4 ( 250 µM ) , for 3 hours . Adult worms were then removed , and the number of eggs on each plate was determined . After incubation at 25°C for 48 hours , the number of surviving adults was counted . The percentage of adults was determined as total number of adults divided by total number of eggs . For PUFA supplementation assays , fatty acids were added to the bacteria before seeding the plates . One-day-old adult animals were incubated in a solution of 1% Triton X-100 for one hour . Following removal from the detergent solution and one-hour recovery on NGM plates at 25°C , the number of survivors was determined . For supplementation assays , worms were grown in the presence of different fatty acids , before being placed in the detergent solution . Heat and cold stress assays were carried out as described [93] . One-day-old adult animals were exposed to 0°C or 36°C for a period of 24 hours and 10 hours , respectively . Number of survivors was determined following one-hour recovery at 25°C . Significant differences in thermal tolerance were determined using a Student's t-test .
|
Polyunsaturated fatty acids are vital for optimal physiological functions , including immunity . Much of these effects are mediated by eicosanoids , which are metabolites of arachidonic acid ( AA ) and eicosapentaenoic acid ( EPA ) . In mammals , PUFAs cannot be synthesized de novo . They are produced from essential dietary fatty acids , which are first converted to gamma-linolenic acid ( GLA ) and stearidonic acid ( SDA ) by a rate-limiting step catalyzed by a Δ6-desaturase , FADS2 . Activity of FADS2 is impaired under numerous conditions—including aging , diabetes , stress , and smoking—and could lead to reduced production of GLA and SDA . In this study , we examined the effects of loss-of-function mutations in PUFA biosynthetic genes on the ability of C . elegans to survive infection by the Gram-negative human pathogen P . aeruginosa . We show that the enhanced pathogen susceptibility of the C . elegans Δ6-desaturase mutant fat-3 is associated with decreased basal expression of immunity genes and disrupted activity of the p38 MAP kinase . These defects could be fully restored when both GLA and SDA , but not AA or EPA , were added into the diets of fat-3 mutants , further supporting the conclusion that GLA and SDA are required for basal immunity in C . elegans .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunology/genetics",
"of",
"the",
"immune",
"system",
"immunology/immunity",
"to",
"infections",
"immunology/innate",
"immunity"
] |
2008
|
Gamma-Linolenic and Stearidonic Acids Are Required for Basal Immunity in Caenorhabditis elegans through Their Effects on p38 MAP Kinase Activity
|
In the enterobacterial species Escherichia coli and Salmonella enterica , expression of horizontally acquired genes with a higher than average AT content is repressed by the nucleoid-associated protein H-NS . A classical example of an H-NS–repressed locus is the bgl ( aryl-β , D-glucoside ) operon of E . coli . This locus is “cryptic , ” as no laboratory growth conditions are known to relieve repression of bgl by H-NS in E . coli K12 . However , repression can be relieved by spontaneous mutations . Here , we investigated the phylogeny of the bgl operon . Typing of bgl in a representative collection of E . coli demonstrated that it evolved clonally and that it is present in strains of the phylogenetic groups A , B1 , and B2 , while it is presumably replaced by a cluster of ORFans in the phylogenetic group D . Interestingly , the bgl operon is mutated in 20% of the strains of phylogenetic groups A and B1 , suggesting erosion of bgl in these groups . However , bgl is functional in almost all B2 isolates and , in approximately 50% of them , it is weakly expressed at laboratory growth conditions . Homologs of bgl genes exist in Klebsiella , Enterobacter , and Erwinia species and also in low GC-content Gram-positive bacteria , while absent in E . albertii and Salmonella sp . This suggests horizontal transfer of bgl genes to an ancestral Enterobacterium . Conservation and weak expression of bgl in isolates of phylogenetic group B2 may indicate a functional role of bgl in extraintestinal pathogenic E . coli .
The species Escherichia coli includes commensal strains residing in the intestine of humans and animals , as well as pathogenic strains causing various intestinal and extra-intestinal infections . This diversity in the life-style of E . coli is based on a significant genetic variability of their genomes . Sequencing of E . coli genomes including that of the laboratory strain K12 ( MG1655 ) , the uropathogenic ( UPEC ) strain CFT073 , and the enterohaemorrhagic ( EHEC ) strains O157∶H7 EDL933 and Sakai , demonstrated that the E . coli genome , like that of other bacteria , consists of a conserved core genome and a variable pool of genes [1]–[4] . Genes of the core genome are present in all E . coli isolates , while variable genes are interspersed in the core genome as genomic islands ( also named islets or loops ) and only present in a subgroup of strains or in single isolates [2]–[4] . The extensive difference in the gene content of bacterial genomes is caused by horizontal gene transfer and gene loss , which contribute dominantly to bacterial evolution , as evident for the evolution of γ-proteobacteria and for the diversification of E . coli [5] , [6] . Furthermore , the species E . coli is subdivided into four phylogenetic groups ( A , B1 , B2 , and D ) . These groups were initially detected by multi locus enzyme electrophoresis ( MLEE ) , and are also reflected by multi locus sequence typing ( MLST ) [7]–[9] . Furthermore , MLST typing demonstrated frequent recombination of strains of different phylogenetic groups resulting in hybrid strains ( AxB1 and ABD ) [8] . Genome and phylogenetic analysis also demonstrated that Shigella strains belong to the species E . coli [5] , [10] . In addition , E . coli strains have been identified , which form a second population distinct from the main E . coli population with its 4 phylogenetic groups . These rare strains presumably represent descendents of a subpopulation that diverged early in evolution of E . coli , prior to the generation of the 4 ‘modern’ phylogenetic groups A , B1 , B2 , and D [8] , [11] . Among the variable gene pool of E . coli , pathogenicity islands have been best characterized and they provide models for the locus specific analysis of genome evolution by horizontal gene transfer [12] . Less is known about genomic islands which encode gene products not apparently related to pathogenicity and genes of unknown function . A locus of this type maps next to the E . coli pst-phoU operon [1] , where two alternative islands ( or islets ) exist . In the laboratory strain K12 and the UPEC strain CFT073 an island is present which carries the bgl operon encoding the gene products for uptake and hydrolysis of aryl-β , D-glucosides ( Figure 1 ) . In E . coli O157∶H7 EDL933 another island of four open reading frames of unknown function ( Z5211 to Z5214 ) is present instead of the bgl locus ( Figure 1 ) . The Z5211 to Z5214 open reading frames represent ORFans with no close homologs in any other genome which are sequenced up to date [5] . Our interest in the E . coli bgl locus is based on the finding that the operon is silent ( ‘cryptic’ ) [13]–[16] . The bgl operon is repressed by the nucleoid-associated protein H-NS , a global regulator and ‘genome sentinel’ [17] , [18] , and for E . coli K12 no laboratory growth conditions are known allowing its expression [14] , [19]–[21] . Silencing of the bgl operon by H-NS can be overcome and the operon can be ‘activated’ by mutation of the hns gene or by mutations that interfere with repression by H-NS [21]–[25] . The latter includes mutations causing constitutive expression of bglJ and leuO , respectively . LeuO and BglJ are positive regulators , which presumably bind next to the bgl promoter and counteract repression by H-NS [24] . In addition , mutations mapping in cis to the bgl promoter occur , which include integration of insertion elements , deletions within the H-NS binding region , and point mutations which improve the binding site for the cAMP-dependent regulator protein ( CRP ) [20] . Once ‘activated’ , the bgl operon becomes inducible by substrate demonstrating that it is maintained in a functional but silent state in E . coli K12 [13] , [14] . However , up to date the biological significance of silencing of the bgl operon has remained puzzling . Early , it was speculated that the bgl operon may be cryptic because of the abundance of cyanogenic β , D-glucosides in nature , whose hydrolysis by the operon encoded phospho-β , D-glucosidase BglB would release the toxic aglycon , and that mutational activation of bgl in some cells might provide a selective advantage for the population at certain conditions [14] . Then , it turned out that the sugar-specific control of the bgl operon by transcriptional antitermination , and the control of the activity of the operon-encoded specific antiterminator protein , BglG , by the PTS ( phosphoenolpyruvate-dependent phosphotransferase system ) is a regulatory mechanism typical of low GC-content Gram-positive bacteria [26] , [27] . The further findings that the codon usage of bgl is atypical for E . coli but similar to Bacillus subtilis , and that the activity of BglG , in contrast to that of other PTS-regulated proteins in E . coli , can be well controlled by PTS proteins from Bacillus subtilis [28] , [29] , may suggest that the bgl operon originates from a horizontal transfer event from low GC-content Gram-positive bacteria . Repression of bgl by H-NS may also support the idea that the bgl locus was horizontally transferred to E . coli . H-NS prevents the un-controlled expression of horizontally transferred AT-rich DNA including that of pathogenicity islands in E . coli and Salmonella enterica [17] , [18] , [30]–[32] . In general , repression by H-NS can be relieved by binding of specific transcription factors and changes in the local DNA conformation , processes which depend on specific environmental stimuli [18] , [33] . Several H-NS repressed loci are expressed in the host-environment only [18] , [33] , and bgl operon expression was detected in a septicemic E . coli isolate when infecting mouse liver indicative of a role of the bgl operon in the host [34] . To characterize the fate of the bgl operon in evolution , we typed the chromosomal locus by PCR and sequencing in a collection of 174 strains , comprised of 171 E . coli isolates including strains of the ECOR collection [35] , and 3 representatives of the closely related species Escherichia albertii [8] , [36] . Different types of the locus were identified by this approach and their clonal divergence in E . coli was traced by mapping onto a minimal spanning tree representing the clonal structure of the strain collection . In addition , all the strains were analyzed for their aryl-β , D-glucoside phenotype , and the phenotypes were likewise correlated with the clonal structure of the collection . These analyses demonstrated clonal inheritance of bgl in E . coli and further phylogenetic analyses suggest that the bgl operon originates from a horizontal transfer event from low GC-content Gram-positive bacteria to an ancestral Enterobacterium . Weak expression of bgl in strains of the phylogenetic group B2 of E . coli may indicate a functional role of bgl in an ecological niche occupied by extra-intestinal pathogenic E . coli ( ExPEC ) .
For the analysis of the evolution of the bgl operon in E . coli we chose a collection of E . coli strains which includes the ECOR reference strains [35] , as well as 96 human E . coli strains isolated in the local medical microbiological diagnostic center . These latter strains include 51 commensals isolated from healthy humans , as well as 24 septicemic and 21 uropathogenic isolates ( Table S1 ) . In addition , two uropathogenic strains J96 and 536 [37] were analyzed , as well as the septicemic strain i484 in which expression of bgl upon infection of mouse liver was shown [34] . Furthermore , two E . coli strains ( RL325/96 and Z205 ) of a second E . coli population , presumably representing descendents of a subpopulation that diverged early in evolution of E . coli , and three representatives of the closely related species Escherichia albertii were included in the analysis [8] . The population structure of this collection was established by multi locus sequence typing ( MLST ) , as described [8] ( for details see Materials and Methods ) , and is visualized by a minimal spanning tree ( MSTREE ) ( Figure 2 ) . The strain collection represents 91 sequence types ( STs ) and 25 ST complexes , and thus is representing the E . coli diversity . Interestingly , one of the human commensal isolates , E10083 ( sequence type ST546 ) , mapped next to the two strains RL325/96 ( ST133 ) and Z205 ( ST125 ) of the second E . coli population , which were isolated from dog and parrot , respectively [8] ( shown in grey in Figure 2 ) . This suggests that the human isolate E10083 is probably another representative of the second population of E . coli , which presumably diverged early in evolution of E . coli prior to formation of the 4 phylogenetic groups A , B1 , B2 , and D [8] . Further , the concatenated sequences of the 7 MLST loci of each strain were used for phylogenetic analysis by construction of neighbor-joining ( NJ ) trees ( Figure S1 ) . As a reference , the sequences of the MLST loci extracted from published E . coli genome sequences ( Table S2 ) were included . The structure of the NJ tree of the local isolates was very similar to that of the ECOR strains ( Figure S1 , compare A and B ) . Four major clades representing the known phylogenetic groups A , B1 , B2 and D of E . coli were apparent [7] , [38] ( Figure S1 ) . Again , strain E10083 from the collection of local isolates diverged from the four major clades and clustered with the strains RL325/96 and Z205 representing the second population of E . coli [8] ( Figure S1 ) . Furthermore , for each isolate the phylogenetic group was either extracted from the MLST database or determined , as described [8] ( listed in Table S1 ) . In total , 48 strains of the collection belong to the phylogenetic group A , 17 strains to B1 , 48 to B2 , and 21 to D , while 16 strains belong to hybrid group AxB1 and 13 to ABD . For 5 strains the assignment was ambiguous , and 3 strains represent the second E . coli population ( Table S1 ) . The NJ trees and the representation of the phylogenetic groups likewise suggest that the strain collection is representing the diversity of E . coli . For typing the chromosomal locus at which bgl is located , we first analyzed by PCR whether the bgl operon is present , whether it is replaced by a cluster of 4 genes ( Z5211 to Z5214 , in the following named Z-locus ) as in the O157∶H7 strains ( Figure 1 ) , or whether the locus has another structure . The PCR revealed that 77% of the strains ( 135 of 174 ) carry the bgl operon and that 19% of the strains ( 33 of 174 ) carry the Z-locus . The three strains representing the second population of E . coli and the three E . albertii strains carried neither the bgl nor the Z locus ( Figure 1 ) . The PCR analysis further demonstrated that in strains that carry the bgl operon two variants exist: in some strains the structure is similar to the one in K12 with two genes yieI ( cbrB ) and yieJ ( cbrC ) present downstream of bgl , while in other strains the structure is similar to the bgl locus in CFT073 , where only the yieI ( cbrB ) gene is present downstream of bgl ( Figure 1 ) . In several strains the bgl-yieIJ locus and the Z-locus , respectively , carried deletions and/or were disrupted by insertion elements . These mutations were characterized in detail by PCR and sequencing , and the results are summarized in the supplement ( Figure S2 ) . Furthermore , Southern blots were performed of all locally isolated strains which did not carry bgl at its normal locus ( Figure S3 and Table S1 ) . The Southern blots performed with probes for the bglG-bglF genes ( Figure S3 ) and for all other genes present in the bgl-yieIJ locus ( not shown ) demonstrated that these strains do not carry the bgl genes elsewhere in the genome . This analysis included 17 strains which carried a Z locus and also strain E10083 , the representative of the second population of E . coli , which does neither carry bgl nor the Z locus ( Figure S3 , Table S1 , and [39] ) . In a second step of typing , fragments encompassing the ends of the bgl and the Z gene cluster , respectively , were sequenced to examine the diversity of these loci ( Figure 1 ) . For strains which carry the bgl island , the sequence of 534 bp derived from the left end and 277 bp derived from the right end of the island were concatenated . These 811 bp sequences were aligned and used for construction of NJ trees ( Figure S4 ) . Strains , in which the analyzed region of the bgl locus was disrupted by insertions and deletions , were omitted . Separate NJ trees were generated for ECOR strains and the remaining strains , and sequences derived from published E . coli genomes were included in both trees ( Figure S4 ) . The sequences clustered into three major clades , demonstrating the presence of three types of the bgl locus in modern E . coli isolates which were designated as types Ia , Ib , and II . The Z5211-5214 locus was analyzed similarly , but no sub-types were assigned because of a high degree of sequence variations and limiting number of sequences ( not shown ) . Thus , all strains harboring the Z5211-5214 locus were assigned as type III . The strains of the second E . coli population and the E . albertii strains lack the bgl operon and the Z5211-5214 locus , as analyzed by PCR and sequencing ( Figure 1 ) . The sequences of the three strains of the second E . coli population , including E10083 isolated here , are identical with only one SNP ( single nucleotide polymorphism ) . These strains were assigned as bgl-Z locus type IV . As stated above , the presence of bgl genes in strain E10083 was excluded by Southern analysis . The E . albertii strains carry the yieJ ( cbrC ) gene next to phoU and were assigned as locus type V ( Figure 1 ) . Further , no homologs to the genes of the bgl and Z loci were found by TBLASTN on the genome sequence of E . albertii ( Table S2 ) indicating the absence of bgl and Z genes in E . albertii ( data not shown ) . To analyze the diversification of the bgl and Z loci in relation to the clonal structure of the E . coli collection , the bgl-Z-locus types Ia , Ib , II , III , and IV were mapped color-coded onto the minimal spanning tree ( MSTREE ) ( Figure 2 ) . This revealed a strong correlation of the structure and diversification of the bgl-Z-locus with the clonal structure of the population . All bgl type Ia strains ( shown in dark green ) mapped to the ST10 complex , and all these strains belong to the phylogenetic group A . The type Ib strains ( shown in light green ) mapped to several ST complexes , which mainly represent strains of the phylogenetic group B1 , as well as AxB1 and ABD hybrid strains , and some A strains . The bgl type II ( shown in red ) mapped to the ST73 , ST95 and ST12 complexes as well as related STs , which all belong to the phylogenetic group B2 . The bgl-Z-locus type III strains ( which carry the Z5211-5214 gene cluster , shown in blue ) mapped to different ST complexes , like ST31 , ST38 , and ST59 , which represent the phylogenetic group D or ABD hybrid strains . Importantly , there is only one case indicative of a recombination event: Strain F905 , a ST10 strain belonging the phylogenetic group A carries a Z5211-Z5214 gene cluster instead of a bgl type Ia locus . Taken together , these analyses revealed a strong congruence of evolution of the bgl-Z-locus with the species . Typing of the bgl locus based on sequences of small fragments revealed a strong congruence with the clonal structure and phylogeny of E . coli . To further analyze the correlation of the phylogeny of bgl with that of the species , the sequence of the entire bgl-locus including genes bglG , bglF , bglB , bglH , bglI ( yieL ) , and bglK ( yieK ) as well as the downstream genes yieJ and yieI ( crbBC ) , was extracted from the genome sequences of 17 E . coli and Shigella strains ( Table S2 ) . Of these sequences a multiple alignment was generated and a NJ tree was constructed ( Figure 3 ) . In some of these strains ( including S . flexneri strains 2A-301 and 2457T , as well as the E . coli strains E22 , E110019 , and 53638 ) insertion elements map within the bgl locus . The sequences of these insertion elements were manually removed to allow alignment . The NJ tree again clustered into 3 clades ( Figure 3 ) and was very similar to the NJ tree which was based on sequence fragments of the bgl locus ( Figure S4 ) . To correlate the phylogeny of the whole locus with the species phylogeny , the sequences of the seven MLST loci were also extracted from the 17 genome sequences , concatenated and used for construction of a NJ tree ( Figure 3 ) . The comparison of the NJ tree based on the bgl locus with the NJ tree based on the MLST loci revealed a strong congruence with minor deviations ( Figure 3 ) , in agreement with the results shown above ( Figure 2 ) . A major incongruence concerned strain 101-1 , which indicates a recombination event . In Escherichia coli K12 expression of the bgl operon is repressed by H-NS under all laboratory growth conditions tested so far . However , spontaneous Bgl-positive mutants , in which repression of bgl by H-NS is relieved , can be easily isolated on salicin indicator plates , where the mutants appear as papillae . The spectrum of mutations which relieve repression include point mutations and small deletions mapping in cis to the bgl promoter . These mutations are expected to occur in all strains , in contrast to mutation of the hns gene and transposition events , which may occur in dependence on the gene repertoire of specific strains . Thus papillae formation is a strong indicator for the presence of a functional but silent ( cryptic ) bgl operon . To analyze whether the bgl operon is silent but functionally intact or whether it is mutated , the Bgl phenotype of all strains of the collection was tested on salicin indicator plates . In this analysis three phenotypes could be distinguished , two of which were as expected . Firstly , the formation of Bgl-positive papillae within Bgl-negative colonies was observed indicating that the bgl operon is functional but silent . Secondly , a Bgl-negative phenotype was observed for strains which do not carry the bgl operon and for strains which presumably carry a mutated , non-functional bgl operon . The wide spectrum of mutations which relieve silencing of bgl should allow papillae formation in all strain backgrounds , as long as the operon is intact . All strains with deletions or insertions in the bglGFB genes ( Figure S2 ) did not form Bgl-positive papillae . Interestingly , some strains showed a third phenotype . These strains were Bgl-negative on day one of incubation but turned weakly Bgl-positive after 2 to 4 days of incubation at 37°C ( Figure 4A ) . To verify that this phenotype is not caused by mutations , the Bgl-positive colonies were re-streaked . Upon re-streaking the colonies again had a negative phenotype on day one and turned weakly positive after 2 to 4 days of incubation ( Figure 4A ) . Quantification of this weak positive phenotype from colonies is difficult . However , the expression level was sufficiently high to prevent outgrowth of Bgl-positive papillae at 37°C . A similar result was obtained by Brooks et al . ( 1980 , 1981 ) who analyzed uropathogenic E . coli [40] , [41] ( and see below ) . Intriguingly , one of the strains with a weak Bgl-positive phenotype at 37°C was the septicemic strain i484 , for which expression of bgl was shown upon infection of mouse [34] . However , all strains with a weak Bgl-positive phenotype at 37°C were Bgl-negative when grown at 28°C . In addition , at 28°C Bgl-positive mutants appeared as papillae . Of strain i484 two Bgl-positive mutants which grew as papillae at 28°C were picked , re-streaked and analyzed . One mutant carried a 47 bp deletion of the H-NS binding region located upstream of the bgl promoter and CRP-binding site , and a second mutant carried a point mutation within the CRP-binding site identical to a mutation isolated before in E . coli K12 [22] . This suggests that the bgl operon in i484 is repressed by H-NS , and that repression by H-NS is relaxed at 37°C . In order to associate the Bgl-phenotype with the clonal structure of the collection , the phenotypes were color-coded and mapped on the MSTREE ( Figure 4B ) . This visualization demonstrated a strong correlation of the functionality of bgl with the diversification of the bgl locus and with the clonal structure of the E . coli collection . Remarkably , in strains belonging to the ST73 , ST95 , and ST12 complexes and closely related STs ( which all correspond to the phylogenetic group B2 ) , the bgl operon was functional ( i . e . structurally intact ) in all but two strains , in contrast to strains belonging to other phylogenetic groups ( see below ) . Furthermore , only in strains of these and related sequence types silencing of bgl was relaxed and the operon was weakly expressed in approximately 50% of the isolates . The prevalence of the weak Bgl-positive phenotype was highest in strains of the clonal groups ST73 and 12 , which may suggest that the presence of this phenotype provides an advantage for these strains . In contrast , in strains of the ST10 and ST23 complexes as well as in other STs which correspond to the phylogenetic groups A , B1 , and AxB1 , the bgl operon was functional ( papillation ) in only 80% of the strains suggesting that 20% of type Ia or Ib bgl loci acquired mutations rendering the bgl operon non-functional ( Figure 4B and Table S1 ) . Further , in strains which carry a bgl type Ia locus integration of insertion elements in the bglHIK-yieJI genes is frequent ( 10 of 33 strains ) ( Figure S2 , Table S1 ) . Our analysis demonstrated that the bgl and Z5211-5124 loci are clonally inherited within the modern group of E . coli strains , while neither the bgl-yieIJ nor the Z5211-Z5214 gene clusters are present in strains of the second E . coli population and in E . albertii . Salmonella sp . likewise does not contain these genes . To analyze the ancestry of the bgl-yieIJ and Z5211-Z5214 genes , the NCBI non-redundant database including the completed proteobacterial genome sequences , and the UniProt database [42] were searched for orthologs . As query the deduced protein sequences encoded by the E . coli K12 bgl-yieIJ locus and the E . coli 0157∶H7 EDL933 Z5211-5214 locus , respectively , were used . This search identified orthologs of the bgl operon genes bglG , bglF , and bglB in the enterobacterial species Klebsiella , Enterobacter , and Erwinia ( Table S3 ) . Orthologs of bglF and bglB were also found in the γ-proteobacterium Photorhabdus luminescens and a bglB ortholog was identified in Vibrio harveyi ( Table S3 ) . In addition , orthologs of likewise high similarity were found for bglH and bglI ( yieL ) in Klebsiella and Erwinia species , and for bglK ( yieK ) in Klebsiella ( Table S3 ) . The chromosomal context of these orthologous genes in Klebsiella , Enterobacter , and Erwinia species is shown in Figure 5 . Interestingly , in all enteric bacteria in which the first three genes of the bgl operon ( bglGFB ) are present they form similar units including two terminator sequences for regulation by transcriptional antitermination ( Figure 5 ) . However , the presumptive promoter regions located upstream of the first terminator are not homologs ( not shown ) . The bglGFB homologs map at different chromosomal locations in E . coli , Klebsiella , Erwinia , and Enterobacter , while the orthologs of genes bglH , yieL , and yieK map at the same chromosomal position in E . coli and Klebsiella ( Figure 5 ) . Homologs of the bglG , bglF , and bglB genes , as well as of bglK are also present in low GC-content Gram-positive bacteria ( Firmicutes ) ( Table S3 ) . For bglG , bglF , and bglB and their orthologs NJ trees were constructed for phylogenetic analysis ( Figure S5 ) . The phylogeny of the orthologs identified in the γ-proteobacteria was rather similar to the species phylogeny . However , a bglG homolog in Photorhabdus luminescens was less similar than homologs identified in Gram-positive bacteria , and in the BglF tree the ortholog present in Erwinia carotovora seems closely related to E . coli BglF ( Figure 5 ) . Taken together the data indicate that the bglG-bglF-bglB gene cluster was assembled in a common ancestor of Erwinia , Klebsiella , Enterobacter , and E . coli . The homologies to proteins of Gram-positives indicate that the genes were acquired by γ-proteobacteria by one or several horizontal transfer events from low-GC-content Gram-positives . In contrast to the bgl operon genes , no orthologs for genes yieI ( cbrB ) and yieJ ( cbrC ) were found in enterobacterial genomes other than E . coli and Shigella sp . For YieJ , homologs of 40 to 50 percent identity are present in Firmicutes ( Table S3 ) . In contrast , a BLAST search for homologs of YieI yielded only weak hits in Salmonella ( 30% identity ) ( Table S3 ) . Taken together the data suggest that the yieI and yieJ genes were acquired by horizontal transfer events , as proposed before [43] . For genes Z5211 to Z5214 no homologs were identified in the entire non-redundant NCBI-database in agreement with a previous analysis in which these genes were defined as ORFans [5] . It is interesting though that the proteins putatively encoded by Z5211 and Z5214 are 50% homologous to each other . Further , the GC-content of the Z5211-5214 cluster is only 30% and thus significantly lower than the average GC-content of the E . coli K12 genome ( 50 . 4% ) . Taken together , this suggests that the Z5211 to Z5214 genes were acquired horizontally .
The bgl operon of E . coli is a classical example of a locus which is repressed by H-NS , and is often referred to as being cryptic , since no laboratory conditions are known which induce its expression . Here we have shown that the evolution and functional state of the bgl operon is tightly coupled to the phylogeny of E . coli . The bgl operon is maintained functionally in strains of the phylogenetic group B2 of E . coli , and silencing of bgl by H-NS is less strict in roughly half of the strain belonging to this group . In contrast , the bgl operon is subject to erosion in the phylogenetic groups A and B1 , and was presumably replaced by a cluster of ORFan genes ( Z-locus ) in strains belonging to the phylogenetic group D . Taken together these results indicate that the bgl operon provides a selective advantage in strains of the phylogenetic group B2 , which includes uropathogenic and other extra-intestinal pathogens . Possibly , in strains of this group relief of silencing by transcriptional regulator proteins LeuO and BglJ may occur under certain conditions in vivo . Erosion of bgl in commensal E . coli and intestinal pathogens belonging to the phylogenetic groups A and B1 and loss of bgl in D strains may suggest that the locus is evolving neutrally or that it may even provide a selective disadvantage under certain conditions . Additional phylogenetic analyses suggest that bgl operon genes were acquired by horizontal transfer from low GC-content Gram-positive bacteria to an ancestral Enterobacterium . Sequence based typing of the bgl operon and comparison of the bgl operon sequences from 17 genomes revealed the existence of 3 types ( Ia , Ib , and II ) of the operon with characteristic differences in their sequence . Mapping of these bgl sequence types onto a minimal spanning tree of a representative collection of E . coli uncovered a strong correlation of the bgl types with the clonal structure and phylogeny of E . coli . Likewise , comparison of a NJ tree based on the bgl sequences extracted of 17 genomes with a phylogenetic tree based on 7 house keeping genes revealed a strong congruence . Among the 171 strains of the collection and among the 17 sequenced strains only two recombination events between strains of different phylogenetic groups became apparent . Analysis of the functional state of the bgl operon in the representative collection of E . coli using a papillation assay revealed a further interesting correlation . The bgl operon was found to be non-functional in 20% of the A and B1 strains as well as in hybrid strains , which carry type Ia or Ib bgl loci . Strains which carry the Z-locus instead of bgl were Bgl-negative , as expected . However , in the phylogenetic group B2 bgl was functional in almost all strains , with only 2 mutants among 48 strains . Furthermore , at 37°C approximately 50% of the B2 strains revealed a weak Bgl-positive phenotype . At 28°C , these strains were Bgl-negative , and Bgl-positive papillae appeared . Two such Bgl-positive papillae isolated of strain i484 were characterized and found to carry a deletion of the H-NS binding site and a point mutation in the CRP-site , respectively . Both mutations are known to relieve H-NS mediated repression in E . coli K12 [20] . Taken together these data suggest that silencing by H-NS is less strict ( ‘relaxed’ ) in B2 strains at 37°C . Interestingly , this relaxed phenotype is most prevalent in B2 strains belonging to the ST73 complex and to STs 127 and 12 . Most MLST typed UPEC strains also belong to these STs ( as listed in the E . coli MLST database ) . A similar correlation of uropathogenicity with the ability to ferment aryl-β , D-glucosides was reported before [40] , [41] . Silencing of the bgl operon is also relaxed in some septicemic and other isolates , including the septicemic strain i484 , for which expression of bgl was detected upon infection of mouse liver [34] . The molecular mechanism underlying the relaxed phenotype is unlikely to be caused by single nucleotide polymorphisms between the type II bgl operon present in B2 strains and the type Ia and Ib bgl loci prevalent in A and B1 strains . The bgl operon from strain i484 ( and other strains in which bgl is weakly expressed ) is silent in the laboratory strain K12 , as tested using lacZ fusions to the bgl promoter and regulatory region ( data not shown ) . Thus , the relaxed phenotype is presumably strain-specific . However , presently the molecular basis of the relaxed phenotype remains unclear . A genetic screen for mutants of i484 in which bgl is silent at 37°C yielded mutations in genes having pleiotropic effects ( not shown ) . Genome comparisons are unlikely to allow the identification of loci , which may be important for the relaxed phenotype , since the gene repertoire of strains belonging to the same phylogenetic groups differ by more than 15% from strain to strain ( data not shown ) [5] . The bgl operon is often referred to as cryptic , as for E . coli K12 no laboratory growth conditions are known at which expression of bgl can be induced . However , the transcriptional regulators LeuO and BglJ counteract repression of bgl by H-NS [24] , [44] , [45] . Relief of repression by LeuO and BglJ requires constitutive expression of leuO and bglJ , respectively , since both genes are likewise repressed by H-NS at laboratory growth conditions [46] , [47] . However , LeuO is a known pathogen determinant in Salmonella enterica [48]–[50] , while BglJ is co-encoded in an operon with YjjQ , which is presumably important for infections by avian pathogenic E . coli [51] . Taken together , it is conceivable that silencing of bgl can be relieved under certain conditions in vivo , in agreement with the finding that bgl becomes induced in the septicemic strain i484 upon infection of mouse liver [34] . Considering that bgl is conserved in extra-intestinal pathogenic E . coli , conditions encountered in the extra-intestinal environment may be crucial . Indeed it was found that expression of the bgl operon can provide a selective advantage at certain conditions . This was analyzed in E . coli K12 were the presence of a mutationally ‘activated’ bgl operon provided a selective advantage in stationary phase in an rpoS mutant , although not in the K12 wild-type [52] . Furthermore , expression of the wild-type bgl operon in K12 occurs at a low level in stationary phase and is reduced in a bglJ mutant [53] . The laboratory strain K12 belongs to the phylogenetic group A of E . coli . In K12 the bgl operon is functional and can be ‘activated’ by mutations which relieve repression by H-NS . This phenomenon was discovered long before a general awareness of in vivo induction of genes in the host environment and of bacterial genome variation was developed . Therefore , it was assumed that mutational activation is required for expression of bgl , and it was speculated that mutational activation may provide a selective advantage for the population . However , the present study does not add to this model . The bgl operon can be activated by mutations under laboratory growth conditions in all E . coli strains in which it is present in a functional state , as evident by papillae formation on salicin plates . Activation of bgl occurs in strains belonging to the phylogenetic groups A , B1 and B2 . However , the operon is conserved in a functional state in B2 strains only , while it is mutated in 20% of the other strains . This suggests that activation of bgl by mutations and a concomitant rare phenotypic variation does not provide a fitness advantage sufficiently high to positively select for a functional operon in A and B1 strains as well as in AxB1and ABD recombinants . The bgl operon is inactivated by mutations in all Shigella strains ( which belong to the E . coli species ) . Further , in all strains of the phylogenetic group D ( which includes many intestinal pathogens ) the bgl operon was presumably replaced by a cluster of ORFan genes . Similarly , early analyses of the prevalence and functional state of bgl in E . coli demonstrated that the operon is present in many strains and silent in almost all of them . It was also detected that the bgl operon was inactive or lost and replaced by another fragment of DNA in some strains [15] . Erosion of the bgl operon may indicate that it does not provide a significant fitness advantage in the intestinal habitat , while the accumulation of bgl mutants or the replacement of bgl in enteroinvasive ( EIEC ) and enterohemorrhagic E . coli ( EHEC ) may be indicative of a fitness disadvantage of bgl in these pathogenic E . coli . The evolution of the bgl locus strikingly correlates with the clonal structure and phylogeny of E . coli . Interestingly , bgl is absent in the closely related species E . albertii and it is also absent in the rare representatives of a second population of E . coli which presumably diverged early in evolution . However , orthologs of more than 70% similarity are present in the enterobacterial species Klebsiella , Enterobacter , and Erwinia . Less similar homologs were detected in Bacillus and Listeria and other low GC-content Gram positives . This suggests that the bgl operon genes were transferred to an ancestral enterobacterial species from low GC-content Gram-positives , then vertically inherited and retained in Erwinia , Klebsiella , and Enterobacter . One possibility is that bgl was vertically inherited to E . coli and in parallel lost in the closely related enterobacterial species Salmonella sp . , Escherichia albertii , and also in representatives of the second E . coli population . Another possibility is that the bgl locus was lost before Salmonella and Escherichia diverged and that it was regained by E . coli by a second horizontal transfer event from an Enterobacterium . In this respect , it is interesting that the bglGFB genes and their homologs in Klebsiella , Enterobacter , and Erwinia are encoded as operons of similar structure although at different chromosomal locations . The homologous operons all contain the regulatory signals required for regulation by transcriptional antitermination by the operon encoded antiterminator ( BglG in E . coli ) which binds to the RNA and prevents termination at two terminators located in the leader and between the regulatory and the structural genes [54] . This mechanism of regulation of catabolic operons by antitermination is prevalent in low GC-content Gram positive bacteria [27] , and thus further supports that bgl originates from a horizontal transfer event from low GC-content Gram-positives . However , the promoter region of the E . coli bgl operon is different from that of Erwinia , Klebsiella , and Enterobacter . The arb operon in Erwinia is not silent [55] , [56] . Similarly , the bgl homologs are presumably not silent in Klebsiella and Enterobacter strains , which show a β-glucoside positive phenotype [57] , [58] . The fate of the bgl operon in E . coli and in evolution of Enterobacteriaceae differs from other loci which were analyzed at the population level . For example , in evolution of type 1 fimbrial genes several independent horizontal transfer events are likely to have occurred [59] . Further , the bgl-yieJI and the Z5211-Z5214 loci lack any apparent mobilization functions and they are not inserted next to a tRNA gene in contrast to many genomic and pathogenicity islands [12] . However , silencing by H-NS is a feature which is common for loci acquired by horizontal transfer [17] , [18] . Further , horizontal transfer of genes for metabolic functions probably occurred repeatedly , for which transfer of genes coding for the phosphoenolpyruvate-dependent phosphotransfer system during the evolution of γ-proteobacteria provides one example [60] . The route of gain , inheritance , erosion and loss of bgl by enterobacteria and within E . coli is in agreement with genome scale analyses of gene gain and loss in the evolution of γ-proteobacteria as well as of E . coli [5] , [6] . Our analysis of a single locus of the variable gene pool at the population level in combination with phylogenetic reconstruction provides a snapshot of ongoing evolution of a locus which was presumably acquired horizontally and then evolved clonally and differentially in commensal and pathogenic E . coli .
The E . coli strain collection analyzed in this study includes the strains of the ECOR reference collection [35] ( obtained from Dr . Whittam , Michigan State University , USA ) , the uropathogenic strains 536 and J96 ( obtained from Dr . Dobrindt , Universität Würzburg , Germany ) , representatives of a second population of E . coli [8]; the septicemic strain i484 [34] ( obtained from Dr . Isaacson , University of Illinois , USA ) , the E . albertii strains ( provided by Dr . Wieler , FU Berlin , Germany ) , and E . coli strains isolated at the local Institute for Medical Microbiology , Immunology and Hygiene . The strains are listed in supplementary Table S1 . Multi locus sequence typing ( MLST ) data for the strains of the ECOR collection , as well as the uropathogenic strains J96 and 536 , were taken from the E . coli MLST database ( http://www . ucc . ie/mlst ) . MLST of the remaining strains was performed , as described [8] . Briefly , PCR primers and PCR reaction conditions were used according to the protocol available at the E . coli MLST database ( http://www . ucc . ie/mlst ) . For sequencing of adk , fumC , and recA additional internal primers were used ( S776 and S777 for adk; S778 for fumC; S766 and S767 for recA; Table S3 ) . DNA sequencing was performed using BigDye Terminator Cycle Sequencing Kit ( v1 . 1 and v3 . 1 , Applied Biosystems ) and an automated DNA sequencer run by the Cologne Center for Genomics . Analysis of the sequences including the assignment of alleles , sequence types , and ST complexes was performed using Bionumerics software ( Applied Maths , NV ) . Minimum spanning trees ( MSTREE ) were generated using the Bionumerics software ( Applied Maths , NV ) , as described [8] . Likewise , phylogenetic analysis of the collection and assignment of phylogenetic groups to new strains was performed , as described [8] . Briefly , for phylogenetic analysis the sequences of the 7 MLST loci were concatenated and aligned using ClustalW , and phylogenetic trees were constructed using the neighbor-joining algorithm with default parameters and 1000 bootstrap replicates using the MEGA4 ( http://www . megasoftware . net/ ) [61] . The assignment of the phylogenetic groups was performed using STRUCTURE , as described [8] . The sequences used for phylogenetic analyses are provided in the supplement ( Dataset S1 ) . Typing of the bgl operon and the Z5211-5214 locus was performed by PCR with a collection of primers ( Table S4 ) matching to the flanking genes of the core genome and within the bgl-yieIJ and Z5211-Z5214 loci . For some strains the PCR typing revealed insertions or deletions within the bgl-yieI-yieJ and Z5211-Z5214 loci . These were further characterized by sequencing ( Figure S2 ) . For phylogenetic analysis of the bgl-yieI-yieJ and the Z5211-Z5214 islands , PCR fragments encompassing the fusions of the core genes phoU and yieH , respectively , to the island were sequenced on both strands . The sequences were manually curated using the ContigExpress program of Vector NTI Suite ( Invitrogen ) and Bionumerics software ( Applied Maths NV ) . Subsequently , the sequences derived from the two flanking regions of the bgl-yieI-yieJ and Z5211-5214 islands , were trimmed to include only island specific sequences . These trimmed sequences were concatenated , aligned and analyzed by construction of NJ trees with the MEGA4 ( http://www . megasoftware . net/ ) using default parameters and 1000 bootstrap replicates . The sequences obtained for E . albertii and the rare E . coli strains representing the second population were deposited at the NCBI Genbank database ( accession numbers EU056311 , EU056312 , EU056313 , and EU056314 ) . For identifying homologs of the genes encoded by the bgl operon and by yieI and yieJ , as well as for the putative genes of the Z5211-Z5214 locus , the deduced protein sequences from E . coli K12 MG1655 and O157∶H7 EDL933 , respectively , were used as query to search the NCBI microbial genomes database as well as the NCBI non-redundant nucleotide database using TBLASTN . In parallel , the UniProt database [62] was searched for homologs using BLASTP . Similar results were obtained in these searches and the protein sequences of the homologs were downloaded for phylogenetic analysis , by alignment and construction of NJ trees . The sequences used are provided in the supplement ( Dataset S1 ) . For comparison , 16S rDNA sequences of enterobacterial representatives were obtained from the Integrated Microbial Genomes ( IMG ) database ( http://img . jgi . doe . gov/cgi-bin/pub/main . cgi ) [63] , and used for construction of a species tree . For analysis of the β-glucoside ( Bgl ) phenotype , the strains were streaked on Bromthymol Blue ( BTB ) salicin ( β-glucoside ) indicator plates [29] . The Bgl phenotypes and the appearance of Bgl-positive papillae , which are indicative of a functional but silent bgl operon , were documented up to 4 days of incubation at 37°C and 28°C , respectively .
|
Horizontal gene transfer , an important mechanism in bacterial adaptation and evolution , requires mechanisms to avoid uncontrolled and possibly disadvantageous expression of the transferred genes . Recently , it was shown that the protein H-NS selectively silences genes gained by horizontal transfer in enteric bacteria . Regulated expression of these genes can then evolve and be integrated into the regulatory network of the new host . Our analysis of the catabolic bgl ( aryl-β , D-glucoside ) operon , which is silenced by H-NS in E . coli , provides a snapshot on the evolution of such a locus . Genes of the bgl operon were presumably gained by horizontal transfer from Gram-positive bacteria to ancestral enteric bacteria . In E . coli , the bgl operon co-evolved with the diversification of the species into four phylogenetic groups . In one phylogenetic group the bgl operon is functional . However , in two other phylogenetic groups , bgl accumulates disrupting mutations , and it is absent in the fourth group . This indicates that the H-NS–silenced bgl operon evolved differently in E . coli and is presumably positively selected in one phylogenetic group , while it is neutrally or negatively selected in the other groups .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/microbial",
"evolution",
"and",
"genomics",
"evolutionary",
"biology/microbial",
"evolution",
"and",
"genomics",
"microbiology/microbial",
"evolution",
"and",
"genomics"
] |
2009
|
Fate of the H-NS–Repressed bgl Operon in Evolution of Escherichia coli
|
Praziquantel remains the drug of choice for the worldwide treatment and control of schistosomiasis . The drug is synthesized and administered as a racemate . Use of the pure active enantiomer would be desirable since the inactive enantiomer is associated with side effects and is responsible for the extremely bitter taste of the pill . We have identified two resolution approaches toward the production of praziquantel as a single enantiomer . One approach starts with commercially available praziquantel and involves a hydrolysis to an intermediate amine , which is resolved with a derivative of tartaric acid . This method was discovered through an open collaboration on the internet . The second method , identified by a contract research organisation , employs a different intermediate that may be resolved with tartaric acid itself . Both resolution procedures identified show promise for the large-scale , economically viable production of praziquantel as a single enantiomer for a low price . Additionally , they may be employed by laboratories for the production of smaller amounts of enantiopure drug for research purposes that should be useful in , for example , elucidation of the drug's mechanism of action .
Schistosomiasis ( bilharziosis ) is termed a "neglected" tropical disease owing to the continuing low level of investment in treatments , prevention and research , yet the disease accounts for an extraordinarily high level of suffering around the world . [1] , [2] Schistosomiasis has been called a "silent pandemic" . [3] Over the past decades several compounds have been used for the treatment of schistosomiasis , [4]–[6] but today there is only one drug of choice , a highly effective small molecule called praziquantel ( PZQ ) . [7] , [8] PZQ is produced on a very large scale ( 300 metric tons worth of API per year ) and is used primarily in veterinary medicine . In human medicine , PZQ is used essentially as preventive ( mass ) chemotherapy for all forms of schistosomiasis - whereby school-aged children or entire communities are given a dose of PZQ once a year . Such mass treatment programs ( e . g . that coordinated by the Schistosomiasis Control Initiative ) [9] deploy 100 million tablets annually , and there is expected to be a further large growth in the demand for PZQ in the coming years . [10] With increasing use comes an increased risk of the development of resistance or tolerance by the parasite . Decreased drug sensitivity was developed via an artificial selection experiment in the laboratory , [11] and reports of similar decreases have already been noted in the field . [12]–[15] Reliance on a single drug for intensive mass treatment is risky . While there have been attempts to find bioactive PZQ analogs , [16]–[18] as well as the discovery of new compounds for the treatment of schistosomiasis based on different modes of action , [19] , [20] in the short term it is sensible to continue to use PZQ in a way that maximizes its life as a useful drug . PZQ is synthesized and administered as a racemate . The L- ( – ) -enantiomer is the eutomer[21]–[24] and has the ( R ) configuration . [7] , [23] Administration of the pure eutomer resulted in fewer side effects than the racemate . [22] The inactive ( + ) -enantiomer is associated with side effects and is also primarily responsible for the extremely bitter taste of the pill;[25] factors such as taste and large pill size contribute to there being a compliance problem with PZQ in the affected communities . [26]–[27] The typical dose per pill ( 40 mg kg−1 , pill contains 600 mg active pharmaceutical ingredient ( API ) ) is large . The pill is difficult to swallow for children ( who are the main target of mass chemotherapy campaigns ) often requiring tablets to be split and crushed , which brings out the bitter taste even further . Decreasing the pill size , reducing side effects and removing the bitter taste , while having the right amount of the active ingredient , could be accomplished were the drug to be made available as a single enantiomer . For these reasons investigations into the viability of a process-scale route to enantiopure PZQ were included in the WHO/TDR business plan for 2008–2013 . [28] Availability of the separate enantiomers would be a valuable tool for the elucidation of the mechanism of action of the drug , still unknown after more than 30 years of use;[29] in such experiments the inactive enantiomer would act as the perfect control . There are typically four methods available for the conversion of a racemic synthesis to one that generates a single enantiomer ( Figure 1 ) : 1 ) Enantioselective synthesis , 2 ) Chromatographic separation , 3 ) Stereoablation ( destruction and selective reconstruction of the stereocenter ) and 4 ) Resolution . To date , reports of the preparation of enantiopure PZQ either have insufficient detail to allow for their appraisal , or likely do not have the potential for the large-scale production of the drug given the severe price constraint;[25] , [30]–[34] for example with enantioselective chromatographic approaches significant quantities of solvents would be required . Racemic praziquantel is off-patent . Through market forces , and its production on such a large scale , the racemate is available for approximately US10¢ per gram . A reasonable price for wide distribution of the enantiopure compound would therefore be approximately US20¢ per gram since half the dose is required of the enantiopure compound . Can enantiopure PZQ be obtained without a significant increase in price ? It is a challenge for either academia or industry to solve this problem , for different reasons . This article describes the discovery of two solutions , one by an open collaborative project that starts from rac-PZQ , and one conducted by a contract research organization that employs a commercially-available precursor . We term these “resolutions of praziquantel” for simplicity . Formally both processes involve the resolution of a precursor or derivative that is then converted to praziquantel .
To a solution of ( R ) - ( – ) -PZQ ( c = 1 , EtOH ) was added a solution of ( S ) - ( + ) -PZQ ( c = 1 , EtOH ) to give a total volume of 1 mL ( Table S1 ) . The results indicate a linear relationship between optical purity and optical rotation ( Figure S5 ) . To a solution of ( S ) - ( + ) -PZQamine ( c = 1 , DCM ) was added a solution of rac-PZQamine ( c = 1 , DCM ) to give a total volume of 1 mL ( Table S2 ) . The results indicate a linear relationship between optical purity and optical rotation ( Figure S6 ) . rac-Praziquanamine ( 10 . 0 g , 49 . 5 mmol ) and ( – ) -dibenzoyl-L-tartaric acid•2 i-PrOH ( 23 . 7 g , 49 . 5 mmol ) were dissolved in isopropanol ( 450 mL ) and water ( 90 mL ) by heating the stirred mixture . The solution was allowed to cool to rt and after 2 h the colourless crystals were filtered and dried to yield the salt as pale yellow crystals ( 12 . 1 g , 44% ) . m . p . 145 . 5–147 . 5°C . Small-scale liberation of amine ( procedure below ) gave [α]D20 ( liberated amine ) = -242° ( c = 1 , DCM ) , implying 79% ee ( determined by polarimetry ) . The salt was recrystallized from a mixture of isopropanol ( 180 mL ) and water ( 90 mL ) . The crystalline precipitate was kept at 5°C for 12 h before filtration , though the crystallization is essentially complete after 2 h . This procedure gave the salt as colourless spicular crystals ( 10 . 2 g , 85% from this procedure , 37% overall ) . m . p . 147 . 3–148 . 5°C . To an ice-cooled solution of R- ( – ) -PZQamine ( 3 . 27 g , 16 . 2 mmol ) and triethylamine ( 2 . 45 g , 3 . 38 mL , 24 . 3 mmol , 1 . 5 eq . ) in dichloromethane ( 80 mL ) was added dropwise cyclohexanoyl chloride ( 2 . 62 g , 2 . 39 mL , 17 . 8 mmol , 1 . 1 eq . ) at 0°C and stirring was continued for 14 h at rt . The solution was quenched with water ( 10 mL ) and stirred for a further 30 min . The layers were separated and the organic layer was washed with saturated sodium carbonate solution , 0 . 5 N HCl solution and brine , dried over magnesium sulfate and concentrated under reduced pressure . The remaining yellow oil became solid after drying under high vacuum and storing at 5°C . The pale yellow solid was recrystallized from acetone/hexane ( 35 mL , 1∶1 mixture ) and two further batches of analytically identical crystals were obtained from the mother liquor after concentration and recrystallization . R- ( – ) -PZQ was thus obtained as colourless crystals ( 4 . 56 g , 90% , 97% ee ) . ( Figure S11 ) m . p . 113 . 5–114 . 5°C . [α]D20 = -136° ( c = 1 , EtOH ) . An outline description of this procedure can be found online . [50]
A coordination website was created on which was posted the problem of the preparation of praziquantel as a single enantiomer . [51] While suggestions were received , input was initially low . In mid-2008 the project was funded by a government/NGO consortium . The resulting raw experimental data were posted in full to an open , online electronic lab notebook ( based on the open source electronic lab notebook system , Labtrove , developed by the University of Southampton , UK . [52] ) Periodic updates were posted on the coordination website , and the project was popularised to increase traffic ( For a description of how the open science project was conducted , see the accompanying paper [53] ) . Two approaches were begun in the laboratory that have so far proved intractable . The first , a community suggestion , relied on oxidation of PZQ to an enamide , which was to be subsequently hydrogenated asymmetrically[54] ( a similar approach was described in a patent , employing Raney Nickel modified with tartaric acid , giving products with low optical purities – see reference [34] ) ; this is a strong approach owing to the highly effective use of asymmetric hydrogenation in process chemistry . [55] Through an online collaborative process , catalysts are being screened for this reduction[56] but the reaction is difficult owing to the lack of a well-placed coordinating group able to direct the metal catalyst to the double bond . The second approach was based on an asymmetric Pictet-Spengler reaction . [57] Catalysts for similar reactions are known , [58] and the relevant starting material ( a peptide acetal ) is an intermediate in two known syntheses of PZQ . [39] , [59] Unfortunately this substrate contains an unreactive aromatic ring ( i . e . lacking electron donating groups ) , and at the time of writing no known asymmetric catalyst has given conversion to PZQ . The third possibility was resolution . Such an approach is widely used in the process-scale production of enantioenriched intermediates because the relevant chiral resolving agents are frequently inexpensive and/or can be recycled . Inputs to the collaborative website and elsewhere suggested this approach was more likely to lead to an economically viable solution to the problem . [60] In response , this approach was prioritized . To effect a resolution , PZQ should be hydrolysed to praziquanamine ( PZQamine , Figure 2A ) . The process must employ only crystallizations ( rather than chromatography ) to be practicable . The use of procedures that avoid the synthesis of complex catalysts , chromatographic purifications and NMR-based assessments of purity would also assist laboratories in underdeveloped countries to access enantiopure PZQ locally on smaller scales . In the corresponding author's laboratory , PZQamine could be generated with ease , but the enantiomers could not be baseline separated by enantioselective HPLC due to a limited range of chiral stationary phases being available . This precluded a convenient local assay for resolution trials . In addition several attempts to resolve PZQamine with a range of chiral acids had met with mixed success . [61]–[62] To find a suitable chromatographic assay , an appeal for assistance was posted in several online discussion boards . In particular , the Process Chemists Group on LinkedIn furnished multiple offers of help . One company , Syncom B . V . , a contract research organization in the Netherlands , additionally offered to perform a free screen of chiral acids for the resolution of PZQamine in order to discover a lead structure for the project . One gram of racemic PZQamine was shipped to Syncom . An effective chiral stationary phase was found , [36] followed by a chiral resolving agent ( ( – ) -di-p-anisoyl-L-tartaric acid ) that permitted the isolation of the desired ( R ) -enantiomer of PZQamine from the mother liquor in ca . 66% ee , which could be increased to 95% ee after one recrystallization . [63] With this lead in hand , optimization of the process was carried out . The resolving agent in question is commercially available ( reasonably expensive on a small scale ) but could be synthesised from tartaric acid . However , purification away from the p-methoxybenzoic acid byproduct formed during its synthesis was non-trivial . It was also thought that isolation of the desired enantiomer of PZQamine from the resolved solid , rather than the mother liquor , would be more desirable; hence ( + ) -di-p-anisoyl-D-tartaric acid was prepared[46] and used for the resolution of praziquanamine to give the desired ( R ) - ( – ) -praziquanamine in the first-precipitated salt . [64] Such an approach is sub-optimal since this resolving agent must be obtained from unnatural enantiomer of tartaric acid . It was found that the simple expedient of using ( – ) -dibenzoyl-L-tartaric acid solved both these problems , allowing the isolation of ( R ) -PZQamine in 44% yield and 80% ee without recrystallization and 33% yield and 97% ee after one recrystallization ( the maximum yield for a resolution is 50% ) . Although we did not expect ( – ) -dibenzoyl-L-tartaric acid and ( – ) -di-p-anisoyl-L-tartaric acid to give opposite enantiomers of praziquanamine in the first-precipitated salts based on our experience with Dutch resolution and the “family” behaviour of resolving agents , this is not an isolated example and non-familiar behaviour has been observed in other resolutions . [65]–[66] No Horeau effect[67] is observed for either PZQ[41] or PZQamine[42] in common solvents and concentrations at room temperature , meaning that for analytically pure samples of either , optical activity can be used as an assessment of optical purity in laboratories without access to enantioselective HPLC . ( R ) -PZQamine can be converted to ( R ) -PZQ with commercially-available cyclohexanoyl chloride in 90% yield , [49] thus completing the formal resolution of PZQ . The resolving agent can be recycled in 89% yield . Conditions to effect the racemization of the undesired ( + ) -PZQamine are now being sought . [68] At the same time as this procedure was being discovered by an open approach , another contract research organisation was asked ( by WHO/TDR ) to look into solutions to the same problem without communication to the open project . This led to the discovery of a complementary resolution ( Figure 2B ) . From an investigation of compounds available in bulk , a resolution of a commercially-available intermediate ( 3 ) was assayed . Tartaric acid could effect this resolution to provide the enantioenriched intermediate in 37% yield and 94% ee . PZQ could be synthesized from enantioenriched 3 by cyclization with chloroacetyl chloride and removal of the benzoyl group , generating ( R ) -PZQamine , which can be taken on to provide enantiopure ( R ) -PZQ as before . A summary of this method was posted to the coordination website when complete . [50] Full experimental details for the open process may be found in this paper . Readers are encouraged to review , evaluate and contribute to refining the resolutions online by addressing current weaknesses ( e . g . , the need for a chlorinated solvent extraction process in the initial PZQ hydrolysis ) . Both processes show sufficient promise in terms of cost on a lab scale ( simple methodology , inexpensive resolving agents , good yields and efficiencies ) that costs approaching those needed should be attainable upon scale-up; the processes are therefore being examined by WHO/TDR on a kilogram scale for economic viability . The routes found are quite similar . An advantage of the approach discovered by the CRO is its use of tartaric acid itself , as opposed to a derivative , but the derivatization employed in the open approach is straightforward . Which route is adopted depends to some extent on the method ( s ) currently employed in the commercial manufacture of the API , and perhaps surprisingly this information is not readily available . The ton-scale availability of 3 implies its use in the synthesis of PZQ , presumably via the original Merck process , [7] yet to the best of our knowledge the CRO manufacturing PZQ for the Schistosomiasis Control Initiative ( Shin Poong , South Korea ) were employing a different approach[39] that generated PZQamine 2 as an intermediate , implying a similar availability of that material in quantity . The open source approach is the basis of an educational project in which students from around the world are encouraged to collaborate in further optimization . ( Interested students and laboratory instructors can view the experiments and collaborate on the relevant website[69] ) . It is clear that the availability of a new synthetic route , even if it is economically viable , does not translate automatically into a product available to the end-user . Additional elements must be taken into consideration including the regulatory requirements for further studies ( chemistry , manufacturing & control; non-clinical; and clinical ) . While the time and costs associated with this process are expected to be significantly less than with a typical new chemical entity , they are yet to be quantified and supported . WHO/TDR is actively seeking commercial partners potentially interested in pursuing this project as well as sources of funding .
|
The drug praziquantel ( PZQ ) is used very widely in both animal and human medicine , where it is the mainstay of the treatment of the neglected tropical disease schistosomiasis . The drug is currently manufactured and administered as a racemate ( 1∶1 mixture of enantiomers ) but for various reasons the large-scale production of PZQ as the single active enantiomer is very desirable . We describe here the preparation of praziquantel as a single enantiomer using classical resolution . The protocols are experimentally simple and inexpensive . One method was found and validated by an unusual research mechanism—open science—where the details of the collaboration ( involving academic and industrial partners ) and all research data were available on the web as they were acquired , and anyone could participate . The other route was found in parallel by a contract research organisation . Besides being possible routes by which praziquantel may be produced in large quantities for the affected communities , it is also hoped that these methods can be used for the production of smaller quantities of enantiopure PZQ for pharmacological studies .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"and",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"schistosomiasis",
"medicinal",
"chemistry",
"stereochemistry",
"organic",
"chemistry",
"neglected",
"tropical",
"diseases",
"chemistry",
"heterocycle",
"structures",
"synthetic",
"chemistry",
"organic",
"compounds"
] |
2011
|
Resolution of Praziquantel
|
Rift Valley fever virus ( RVFV ) is an arthropod-borne phlebovirus reported to be circulating in most parts of Africa . Since 2009 , RVFV has been suspected of continuously circulating in the Union of Comoros . To estimate the incidence of RVFV antibody acquisition in the Comorian ruminant population , 191 young goats and cattle were selected in six distinct zones and sampled periodically from April 2010 to August 2011 . We found an estimated incidence of RVFV antibody acquisition of 17 . 5% ( 95% confidence interval ( CI ) : [8 . 9–26 . 1] ) with a significant difference between islands ( 8 . 2% in Grande Comore , 72 . 3% in Moheli and 5 . 8% in Anjouan ) . Simultaneously , a longitudinal entomological survey was conducted and ruminant trade-related information was collected . No RVFV RNA was detected out of the 1 , 568 blood-sucking caught insects , including three potential vectors of RVFV mosquito species . Our trade survey suggests that there is a continuous flow of live animals from eastern Africa to the Union of Comoros and movements of ruminants between the three Comoro islands . Finally , a cross-sectional study was performed in August 2011 at the end of the follow-up . We found an estimated RVFV antibody prevalence of 19 . 3% ( 95% CI: [15 . 6%–23 . 0%] ) . Our findings suggest a complex RVFV epidemiological cycle in the Union of Comoros with probable inter-islands differences in RVFV circulation patterns . Moheli , and potentially Anjouan , appear to be acting as endemic reservoir of infection whereas RVFV persistence in Grande Comore could be correlated with trade in live animals with the eastern coast of Africa . More data are needed to estimate the real impact of the disease on human health and on the national economy .
Rift Valley fever ( RVF ) is an arthropod-borne zoonotic disease caused by a RVF virus ( RVFV ) , a member of the Phlebovirus genus of the family Bunyaviridae [1] . RVFV causes significant morbidity and mortality among sheep , goats , cattle and also affects humans . In livestock , abortion storms and high mortality observed among the younger animals cause significant economic losses [2] , [3] . Humans are usually infected by contact with infectious animal tissues through inhalation or aerosols generated by slaughtering and necropsy [4] . Arthropod vectors play an important role during the onset of epidemic and inter-epidemic periods [5] . In endemic areas , RVFV is maintained in the environment through an enzootic vertebrate-arthropod cycle [6] . RVFV has been isolated from many vectors in the field [7] , such as ticks and sand flies which are able to transmit the virus in experimental conditions [8] , [9] . However , mosquitoes are the main insects involved in the spread of RVFV during epidemics . RVFV has been isolated from at least 40 species of mosquitoes belonging to 8 genera but only some of them are susceptible and able to transmit RVFV under laboratory conditions [10] . RVF is widely present in Africa and has been spreading to Madagascar and the Arabian Peninsula [11] , [12] . In 2007 , RVF outbreaks were reported in several eastern and southern African countries [13] . A few weeks later , and for the first time , RVFV was detected in the Comoros archipelago following the hospitalization of a young Grande Comorian boy showing symptoms of severe encephalitis [14] . In addition , during the 2008 and 2009 rainy seasons , outbreaks due to RVFV strains imported from mainland Africa were reported in Madagascar causing 59 confirmed human cases and seven deaths [11] , [15] . In Mayotte , the French overseas territory that belongs to the Comoros archipelago , a retrospective study conducted in 2008 confirmed the presence of the disease with 10 human cases infected with RVFV strains genetically closely linked to the 2006–2007 Kenyan isolates [16] . It was also found that the Mayotte livestock has been infected by RVFV prior to 2004 [17] . Regarding the Union of Comoros , in 2011 , Roger et al . reported widespread exposure of Comorian livestock with 32 . 8% of animals shown to be RVFV-seropositive without any notifications of massive abortions or abnormal mortality in the younger animals by the Comorian Animal Health Services . However , the origin of this infection remains unknown [18] . The Union of Comoros is located in the South West Indian Ocean at the northern end of the Mozambique Channel and is considered to be a gateway to islands in the Indian Ocean for various infectious agents imported from mainland Africa . Since 2002 , live ruminants are imported from Tanzania and have entered the country without a period of quarantine or a clinical examination [18] . Finally , in the past , animal trade has already affected the country health status on several occasions , with regard to many diseases , like blackleg in 1970 and 1995 , the contagious ecthyma in 1999 , and the East Coast fever in 2003 and 2004 [19]–[21] . Some of the Culicidae species described in the Comoros archipelago [22] have already been shown to be involved in RVFV transmission . The establishment of RVFV in the Union of Comoros remains unconfirmed and the threat to the Comorian population and neighboring countries needs to be considered . The trade and resulting movements of ruminants , the composition and abundance of the vector population and many other environmental and anthropological factors determine the nature of the RVF viral cycle . In order to elucidate how RVFV persists in the Union of Comoros , longitudinal and cross-sectional livestock surveys were conducted between April 2010 and August 2011 in six separate geographical zones . Mosquito populations were categorized in parallel over the same period via a longitudinal entomological survey . Additionally trade frequencies were analyzed , providing an estimate of regional ruminant flux and allowing for evaluation of the risk associated with animal importation , and the likelihood of RVFV persistence in the Comoros islands .
The research protocol was implemented with the approval of the Vice-Presidency of Agriculture , Fisheries and Environment of the Union of Comoros . No endangered or protected species were involved in the survey . Farmers in each zone gave their verbal consent to be included in the study . Permissions for the blood sample collection were obtained . The animals were bled without suffering . Regarding the trade survey , no personal data were collected , and only information concerning the number of animals travelling from one island to another was taken into account . The Comoros islands form an archipelago of volcanic islands located off the southeastern coast of Africa , east of Mozambique and northwest of Madagascar . The archipelago is divided between the sovereign state of the Union of Comoros composed of three islands named Grande Comore , Moheli , and Anjouan , and the French overseas department of Mayotte . The tropical climate of the Comoros islands is characterized by daytime temperatures around 26°C at sea level , with limited variation during the year , and by annual heavy rainfall ( 2 , 679 mm ) with two seasons: a humid season from November to April , and a dry season from May to October . Based on the results of a previous RVFV antibody prevalence study in 2009 [18] , six zones were selected in the Union of Comoros ( Figure 1 ) . Four zones were selected on the island of Grande Comore: zones 1 and 2 located in the center of the island where low RVFV antibody prevalence was found , and zones 3 and 4 located in the south with high RVFV antibody prevalence [18] . Zones 2 and 4 are located along the coast ( 0–200 m above sea level ( asl . ) ) where ruminants are mostly goats stall reared or ranging free within and outside villages . Zones 1 and 3 are located at a moderate altitude ( 500–650 m asl . ) where ruminants are mostly cattle reared in pastures ( zone 1 ) or raised in stalls in the forest ( zone 3 ) . Zone 5 , which was located on the southern coast of the island of Moheli , was selected because of its highest RVFV antibody prevalence observed during the 2009 survey [18] . On this island , cattle are reared in stalls on an old coconut plantation . Finally , in zone 6 located close to the airport on Anjouan island , cattle were raised in stalls in vegetable production areas . Five ml of whole blood was collected from the jugular vein of goats and cattle in Vacutainer tubes ( Becton Dickinson , USA ) . Samples were allowed to clot at 15°C and serum was separated from whole blood by centrifugation; samples were stored in liquid nitrogen in the field and at −80°C in the laboratory . The livestock longitudinal survey was conducted in the six separate zones detailed in Figure 1 . From 20 to 30 ruminants were individually identified in each zone using ear tags . The number of animals sampled per zone was based on the previous survey , with a RVFV antibody prevalence ranging from 20% to 50% [18] with 70% relative precision [23] . To avoid colostral immunity , animals were selected as follows: cattle were between 10 months and one-year of age , and small ruminants were between three to eight months of age . Animals were sampled monthly from April 2010 to August 2010 and every four months from August 2010 to August 2011 . The first series of serological tests determined the RVF serological status of each sampled animal . Only RVFV antibody negative animals were included in the livestock longitudinal survey and continued to be sampled until their IgG RVFV antibody positive status and were then excluded from the study . When possible , new ruminants were included in the study to substitute lost , dead or RVFV IgG positive animals . The RVFV antibody prevalence based on the different study zones was estimated in August 2011 . The sample size was based on the previously estimated prevalence [18] with a relative precision of 20% and a confidence level of 95% giving a required minimum of 385 animals to be collected [23] . Without any particular Comorian livestock census , animals were selected on the farmer's willingness to cooperate during the study . Blood-sucking insects were sampled every four months from November 2010 to August 2011 along with the longitudinal serological survey using double-net goat baited traps placed from 4:00 pm to 10:00 am . The sampling was carried out for three consecutive days in the study zones numbered 1 , 3 , 5 and 6 ( Figure 1 ) . No sampling was performed in zones 2 and 4 for logistic reasons . In order to generate hypotheses on potential associations between the estimated RVFV incidence and prevalence with environmental risk factors for RVF infection , we collated climatic variables [24] . Two remotely-sensed MODerate-resolution Imaging Spectroradiometer ( MODIS ) data sets were sourced from the National Aeronautics and Space Administration ( http://modis . gsfc . nasa . gov/ ) , namely the Daytime Land Surface Temperature ( DLST ) and the Nighttime Land Surface Temperature ( NLST ) , both with spatial and temporal resolution of 1 km and 8 days . In addition , rainfall data were obtained from the Malaria Early Warning System ( MEWS ) program , freely available in the MEWS repository ( http://iridl . ldeo . columbia . edu/expert/SOURCES/ . NOAA/ . NCEP/ . CPC/ . FEWS/ . Africa/ . TEN-DAY/ . RFEv2/ . est_prcp/ ) , with a spatial and temporal resolution of 11 km and 10 days respectively . DLST , NLST and rainfall values were extracted within a 5-km radius buffer around each farm corresponding to the maximum daily distance for cattle ( grazing and watering ) . For each sampled animal that became RVFV antibody positive , MODIS and MEWS data recorded at the time of the seroconversion in the zone concerned were compared with MODIS and MEWS data recorded at the same time in the other zones . The aim of the trade survey was to estimate the movement of live animals between continental Africa and the Comoros archipelago and among the islands of the archipelago themselves . To date , only approximate figures are known without any quantitative data available [17] . The number of imported ruminants was collected monthly between November 2010 and August 2011 as follows i ) the local veterinary authorities provided records of animal movements through the official ports of Moroni ( Grande Comore ) , Fomboni ( Moheli ) , and Mutsamudu ( Anjouan ) , ii ) one interviewer per island had the task of identifying undeclared animal arrivals on the coast , either in the field or from information provided by village chiefs . All statistics were performed using R . 3 . 0 . 1 [29] . For both Fisher's exact test and the Student-t test , a value of P<0 . 05 was considered significant . A seroconversion was defined as an animal found with either a positive IgM ELISA result or a positive IgG ELISA result or both following a previous negative RVFV ELISA sample result .
A total of 191 ruminants ( 88 cattle and 103 goats ) were included in the livestock longitudinal survey: 135 animals in Grande Comore , 27 in Moheli and 29 in Anjouan . Detection of RVFV antibodies ( IgM and IgG ) was performed by ELISA for a total of 849 serum samples over the duration of study . Table 1 presents by date and per zone the number of animals that acquired RVFV antibodies over the duration of the livestock longitudinal survey . A total of 15 animals out of the 191 sampled acquired RVFV antibody during the study . Each of the 13 RVFV IgG ELISA positive samples were confirmed by VNT . Only one RVFV IgM ELISA positive sample was not confirmed by VNT ( July 200 , Moheli ) . This animal was confirmed RVFV IgG ELISA positive and VNT positive four months later in November 2010 . Out of the 112 RVFV IgG ELISA negative samples randomly chosen , all were found negative by VNT . RVFV IgM antibodies acquisition was detected in three animals and RVFV IgG antibodies acquisition in 12 animals . Only one RVFV IgM ELISA positive animal in Moheli converted to RVFV IgG antibodies . The two others RVFV IgM ELISA positive ruminants were lost or slaughtered before the next sampling session ( Table 1 ) . Nine out of the 15 , which acquired RVFV antibody , were recorded in Moheli , five in Grande Comore and one in Anjouan . Nine out of those fiftteen occurred during the dry season ( six in Moheli , one in Anjouan , two in Grande Comore ) . The overall annual incidence of RVFV antibody acquisition for the Union of Comoros was estimated at 17 . 54% ( n[animal risk time] = 91 ) , with a 95% confidence interval ( CI ) [8 . 95–26 . 14] ) ( Table 2 ) . A significant difference was found when incidence of RVFV antibody acquisition was compared between zones ( Fisher exact test , p<0 . 001 ) or between islands ( Fisher exact test , p<0 . 001 ) ( Table 2 ) . Zone 5 ( Moheli ) incidence of RVFV antibody acquisition ( 72 . 3% 95% CI [0 . 255–1 . 000] ) was significantly higher than in others zones ( Table 2 ) . The statistical analysis did not reveal any significant difference in incidence of RVFV antibody acquisition between the rainy ( from November to April , ) and the dry season ( from May to October ) either for the Union of Comoros as a whole or per zone ( Table 2 ) . DLST , NLST ( MODIS data ) and cumulative rainfall ( MEWS data ) were similar in all six zones at the time of fourteen out of fifteen seroconversions occurred . There was one exception when the last RVFV seroconversion was recorded in Grande Comore in May 2011 ( zone 3 ) . Between March and May 2011 , DLST , NLST and cumulative rainfall recorded in Grande Comore ( 29°C , 25°C and 730 mm respectively ) were higher than those recorded in Moheli and Anjouan at the same time ( DLST : 24°C , NLST : 22°C and cumulative rainfall : 420 mm ) . No RVFV seroconversion was recorded on Moheli and Anjouan during this period . In August 2011 , to determine the RVFV antibody prevalence , a total of 275 ruminant samples ( i . e . 163 cattle and 112 goats ) were tested for the presence of RVF IgG antibodies . A total of 37 ruminants ( 20 cattle and 17 goats ) came from the longitudinal follow-up study and 238 ruminants ( 143 cattle and 95 goats ) were randomly selected in the six separate study zones . The overall RVFV antibody prevalence in the Union of Comoros study zones in 2011 was 27 . 6% ( n = 275 , 95% CI , [22 . 3–32 . 9] ) . We found a significant difference of RVFV antibody prevalence between islands ( Fisher exact test , p = 0 . 007 ) , with a higher RVFV antibody prevalence in Moheli ( 45 . 8% , 95% CI , [33 . 7–57 . 9] , Table 3 ) . Twelve trapping days were conducted in each of the four zones under study ( zones 1 , 3 , 5 and 6 , see Figure 1 ) . Blood-sucking insects were trapped in five out of the twelve trapping days in central Grande Comore ( zone 1 ) , in eight trapping days in southern Grande Comore ( zone 3 ) , eleven trapping days in Moheli ( zone 5 ) , and in seven trapping days in Anjouan ( zone 6 ) ( Table 4 ) . Out of the 1 , 568 blood sucking insects caught with the double-net goat baited trap , 1 , 548 were identified as mosquitoes and 20 were identified as Stomoxys niger . A total of 1 , 133 insects were collected in Moheli ( zone 5 ) , 291 in Anjouan ( zone 6 ) , 108 in southern Grande Comore ( zone 3 ) and 36 in central Grande Comore ( zone 1 ) . Although the number of comparisons was not large , the average number of trapped mosquitoes per trapping day per zone was significantly higher in Moheli ( average was 113 insects ) and Anjouan ( average was 42 insects ) compared to Grande Comore zones 1 ( average was 7 insects ) and zone 3 ( average was 14 insects ) ( Table 5 ) . The diversity and number of blood-sucking insects caught with the double net goat baited trap per trapping day per zone are presented in Table 4 . A total of seven genera and 16 species were caught of which 14 could be morphologically identified . Fifteen species out of the 16 caught were collected in Moheli ( zone 5 ) , nine species were collected in Anjouan ( zone 6 ) , three and eight in central and southern Grande Comore respectively ( zone 1 and zone 3 ) . Eighty-seven percent of the total number of insects caught belonged to three species with 52% belonging to two Eretmapodites species ( E . quinquevittatus and E . subsimplicipes , ) and 35% to Aedes cartroni . No RVFV RNA was detected in any of the 442 pools tested . The study highlighted movements of live ruminants between the three islands of the Union of Comoros , the African mainland , Mayotte and Madagascar ( Figure 2 ) . Data recorded by veterinarians and technicians showed movements of live ruminants from i ) the east coast of Africa to Union of Comoros and ii ) between the three islands of the Union of Comoros ( Figure 2A . ) . Animals were observed being landed on beaches without any controls or in secondary “ports” like Chindini in the south of Grande Comore . Figure 2B represents the dynamics of live animal importations in Union of Comoros from May 2010 to July 2011 . We recorded up to ten fold more ruminants imported in Grande Comore than in Moheli or Anjouan .
Rift Valley fever was detected for the first time in Grande Comore in the human population in 2007 [14] and in livestock in 2009 [18] . Our study demonstrates that RVFV is still circulating in the Union of Comoros despite of the absence of apparent clinical signs in livestock . Fifteen RVFV seroconversions were observed in the Union of Comoros between 2010 and 2011 giving an overall incidence of RVFV antibody acquisition of 17 . 5% . These results suggest continuous circulation of RVFV on the three islands . However , significant differences in incidence were observed between islands ( p<0 . 001 ) . The incidence of RVFV antibody acquisition was higher in Moheli ( 72 . 3% ) than in Anjouan ( 5 . 8% ) and in Grande Comore ( 8 . 2% ) . This is in accordance with differences in RVFV antibody prevalence between the Union of Comoros islands recorded in 2009 and 2011 . In 2011 , RVFV antibody prevalence in Anjouan was still below the one in Grande Comore , whereas RVFV antibody prevalence remained the highest in Moheli . However , in Grande Comore and Anjouan RVFV antibody prevalence in 2011 appeared to have decreased whereas in Moheli , RVFV antibody prevalence remained similar to the level recorded in 2009 , despite herd replacement estimated at 12% ( L . Cavalerie , personal communication ) . These results suggest the existence of island specific RVF circulation patterns . Seasonality of the incidence of RVFV antibody acquisition needs to be explored . The Comorian livestock farming characteristics ( small herd size and small total number of ruminants ) as well as the field issues did not allow a sufficient number of young ruminants ( nrisk too small ) reducing the power of the statistical analysis . No clinical signs were reported in the Union of Comoros during the period of our study , as reported in Madagascar , Tanzania , and Mozambique in recent years [33]–[35] , but the fifteen seroconversions observed suggest that RVFV could be circulating in the Comorian environment thanks to local mosquito-mammalian host cycles even if the numbers of caught mosquitoes were not large nor positive for RVF RNA . Out of the 1 , 568 blood-sucking insects caught , none were found to be RVFV RNA positive by PCR but in the absence of RVF outbreaks , chances of detecting RVFV in vector populations are known to be very low [36] . In 1978 , Bruhnes described 30 mosquito species in the Union of Comoros [22] . Four of them: Ae . aegypti , Ae . fowleri , Ae . circumluteolus and Cx . quinquefasciatus are considered as RVFV potential vectors because the virus has been already isolated in these species in the field and because of their capacity to transmit RVFV under laboratory conditions [37]–[39] . All these species , except Ae . fowleri , have been caught at least on one island during our study , suggesting a role for this mosquito species to be involved in the transmission cycle on each of the islands . Five other mosquito species caught during our study , Er . quinquevittatus , An . arabiensis , M . uniformis , An . coustani and Ae . simpsoni were previously identified as RVFV RNA positive by PCR in the field [40]–[44] . An . coustani and Ae . simpsoni were found RVFV RNA carrier for the first time in the Indian Ocean area: respectively in Madagascar in 2011 and in Mayotte in 2009 [43] , [44] . Thus , some of these mosquito species may play a role in RVFV transmission in the Union of Comoros . Geological inaccessibility , sampling design and climatic conditions likely explain the small number of specimens caught and the heterogeneity of entomological findings between islands [45] . These volcanic islands are characterized by a tropical climate with only slight variations in daily temperatures and abundant rainfalls , which theoretically should enable populations of Culicidae species to persist throughout the year . Nevertheless , each island has its own environmental characteristics , as the age of the three islands decreases westward: Moheli is 2 . 73±0 . 20 million years old , Anjouan , 1 . 18±0 . 03 million years old , and Grande Comore is 0 . 13±0 . 02 million years old [46] . On Moheli and Anjouan , the oldest islands , the landscape includes permanent rivers [47] and , as a result , many artificial and natural breeding mosquito sites exist . Moheli has a wide variety of natural and artificial sites in which mosquitoes can breed all year round [47] , [48] . The presence of clay , resulting from the decomposition of volcanic soils , ensures the presence of abundant surface water impoundments . It allows the cultivation of irrigated rice hence and favors the development of diversified mosquito populations [47] . A greater number of mosquito species were caught in Moheli ( 15 species ) than in the other islands which is in agreement with Brunhes' inventory in 1978 , including two mosquito species known as RVFV potential vectors . Thus , favorable conditions for RVFV persistence being present a better chance for a possible RVFV cycle involving vectors and animals is suggested . The abundance of mosquitoes trapped in Anjouan ( zone 6 ) was similar to that in Moheli ( zone 5 ) and three mosquito species known as RVFV potential vector have been caught during our study . However , RVFV antibody prevalence in Anjouan was the lowest and appeared to be decreasing . Moreover in 2011 , only one ruminant exhibited a RVFV seroconversion . Anjouan shares some similar environmental characteristics with Moheli that could allow mosquitoes to survive all year round but Anjouan has some characteristics that could limit the circulation of RVFV . For example , the landscape is comprised of hill slopes and irrigated field rice is not cultivated on the island . Ruminants are mainly reared in stalls in the highlands in the eastern part of the island . For that reason , the probability of contact between infected vectors and ruminants may be lower in Anjouan than in Moheli and the maintenance of a vector-ruminant cycle may be harder to get . More investigations in other cattle-rearing areas are thus needed to conclude on RVF circulation in Anjouan . Incidence of RVFV antibody acquisition and the RVFV antibody prevalence in Grande Comore are hard to explain based only on entomological parameters . Presence of steep slopes with decomposed and highly permeable soils characterize Grande Comore , the youngest island of the country [47] . Surface water is rare and only artificial containers ( such as tanks and troughs ) and some natural breeding sites ( such as coconut shells and hollow trees ) enable the development of Culicidae . Our results were in accordance with these observations as fewer blood-sucking insects were caught in Grande Comore when compared to Moheli and Anjouan . Thus , mosquito abundance in Grande Comore was likely correlated with the number of breeding sites that appeared after rainy episodes , as observed for the seroconversions we detected in Grande Comore following on from a major increase in cumulative rainfall . Two out of eight mosquito species caught during our study have been described as RVFV potential vectors . Consequently , environmental conditions for a local mosquito-mammalian host cycle could be met after important rainy episodes but a continuous circulation of RVFV in Grande Comore all year round is less likely to happen . However , regular introductions of the virus through the arrival of live animals from Tanzania [49] , Anjouan , and Moheli may play a role in the persistence of RVFV in Grande Comore . Analysis of trade in live animals confirmed observations reported by Cêtre et al . , in 2012 in an overview of the movement of live ruminants between east Africa and the Comoros archipelago , as well as within the archipelago . Per year , more than 3000 live ruminants are imported from Tanzania ( Chief Veterinary Officer of Comorian Vet services , personal communication ) , where RVF is endemic [34] . These animals enter the Union , mostly Grande Comore , without any quarantine or clinical examination . The risk of the introduction of new exotic strains of RVFV is consequently quite high and could affect the country in the same way as many other diseases in the past [19] . Tanzanian ruminants are imported for “great weddings” which are usually celebrated in July and August in Grande Comore . During these traditional weddings , villagers sacrifice ruminants without any particular sanitary rules . However , no major cases in humans and no ruminant seroconversions were reported during the “great weddings” period during our study but to date , human and veterinary health surveillance networks remain not very efficient . Occasional imports of Tanzanian ruminants into Moheli and Anjouan have also been reported; so new RVFV strains could have been also introduced on these islands . The regular introduction of live ruminants from Anjouan and Moheli could also contribute to the regular introduction of RVFV in Grande Comore as well . Rift Valley fever epidemiology in the Union of Comoros is complex and further virological investigations should help to explain the origin of the RVFV strain ( s ) circulating within the islands . However , based on the results of the present study , RVFV seems hardly to persist on Grande Comore through a local vector cycle only but repeated reintroduction of viruses is possible . The situation regarding Rift Valley fever in Anjouan and Moheli appeared to look like that in Mayotte , Madagascar , Tanzania , and Mozambique [33]–[35] , [50] where RVFV seroconversions have also been observed in the dry season without any apparent clinical signs . These findings could identify Moheli and Anjouan as endemic areas for RVFV . Given the incidence of RVFV seroconversions and antibody prevalence , RVFV is more likely to be circulating in Moheli than in Anjouan . However , additional data are needed to firmly conclude on the circulation of RVFV in the Union of Comoros . Wildlife such as bats and lemur species in our zone should be investigated even though no wildlife reservoir has been identified in any other country so far [51] , [52] . Rift Valley fever is still a burden for the Union of Comoros as new human cases were diagnosed as RVFV positive in 2011 and in 2012 either by IgM or RVFV RNA detection with clinical signs [53] , [54] . The real impact of the disease on human health and on the national economy is still unknown . Human and veterinary health networks need to be strengthened including the establishment of quarantine for imported ruminants .
|
Rift Valley fever ( RVF ) is a viral disease transmitted by mosquitoes to ruminants . The disease may affect humans and has a great impact on the economy of the affected country . RVF occurs mostly in African countries , but epidemics have been reported in Madagascar and in the Arabian Peninsula . In the Union of Comoros , RVF virus ( RVFV ) has been suspected of continuously circulating since 2009 without any notifications of the typical clinical signs by the Comorian Animal Health Services . From April 2010 to August 2011 , we conducted a livestock longitudinal survey in Grande Comore , Moheli and Anjouan . Our study aimed to detect RVFV-specific antibody acquisitions in cattle and goats . Simultaneously , a longitudinal entomological survey was conducted to describe the diversity of mosquitoes in the study zones and ruminant trade-related information was collected . Our investigations showed that Comoros ruminants acquired RVFV-specific antibodies all along the year and particularly in Moheli during the dry season . Our findings suggest a complex RVFV epidemiological cycle in the Union of Comoros with probable inter-islands differences in RVFV circulation patterns . The disease appears to be endemic in Moheli and potentially Anjouan , but the persistence of the disease in Grande Comore could be correlated with trade in live animals with the eastern coast of Africa .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"veterinary",
"diseases",
"zoonoses",
"veterinary",
"epidemiology",
"entomology",
"biology",
"and",
"life",
"sciences",
"zoology",
"veterinary",
"science"
] |
2014
|
Evidence for Circulation of the Rift Valley Fever Virus among Livestock in the Union of Comoros
|
Over 400 , 000 people across the Americas are thought to have been infected with Zika virus as a consequence of the 2015–2016 Latin American outbreak . Official government-led case count data in Latin America are typically delayed by several weeks , making it difficult to track the disease in a timely manner . Thus , timely disease tracking systems are needed to design and assess interventions to mitigate disease transmission . We combined information from Zika-related Google searches , Twitter microblogs , and the HealthMap digital surveillance system with historical Zika suspected case counts to track and predict estimates of suspected weekly Zika cases during the 2015–2016 Latin American outbreak , up to three weeks ahead of the publication of official case data . We evaluated the predictive power of these data and used a dynamic multivariable approach to retrospectively produce predictions of weekly suspected cases for five countries: Colombia , El Salvador , Honduras , Venezuela , and Martinique . Models that combined Google ( and Twitter data where available ) with autoregressive information showed the best out-of-sample predictive accuracy for 1-week ahead predictions , whereas models that used only Google and Twitter typically performed best for 2- and 3-week ahead predictions . Given the significant delay in the release of official government-reported Zika case counts , we show that these Internet-based data streams can be used as timely and complementary ways to assess the dynamics of the outbreak .
The rapid spread of Zika virus has led to more than 400 , 000 suspected cases across the Americas since its introduction to Brazil in 2014 , and has triggered alerts around the globe[1] . This event has led to diverse interventions and travel warnings to affected areas , underscoring the importance of proactive disease surveillance . While cases of sexual transmission of Zika virus have been documented[2] , the virus is primarily transmitted through the bite of the Aedes aegypti mosquito and causes nonspecific flu-like symptoms and skin rashes[3 , 4] . Of particular concern is the possible link between Zika virus and neurological disorders such as microcephaly , a birth defect in which babies of infected pregnant women are born with abnormally small heads[5–8] . Over 1800 cases of Zika-related microcephaly and central nervous system disorders in newborns have been reported since the beginning of the epidemic , and the virus has spread to 70 countries globally[9] . In February 2016 , the World Health Organization declared Zika a global public health emergency[10] . With no existing vaccinations or treatment for Zika infections , control of the Aedes aegypti mosquito is critical to curb the spread of the virus , as has been observed in dengue fever studies[11 , 12] . This requires continuous and up-to-date surveillance of cases to drive vector control interventions accordingly[13] . In countries with now autochthonous transmission , the surveillance of Zika infections is predominantly passive; cases are identified on the basis of hospitalizations and clinical symptom reports . The Pan American Health Organization ( PAHO ) currently streamlines reports from ministries of health , and reports weekly confirmed and suspected cases of Zika by country[14] . The release of these reports and those produced by the ministries , however , is typically delayed by three or more weeks due to systematic processing and data collection . As a consequence , the changing dynamics of Zika are frequently hard to be assessed in a timely manner , and thus , the availability of current data on Zika to the public and public health officials is limited . In the past decade , the near real-time availability of novel and disparate internet-based data sources has motivated the development of complementary methodologies to track the incidence and spread of diseases . These approaches exploit near real-time information from internet search engines[15–18] , news reports[19–21] , clinician’s search engines[22] , crowd-sourced participatory disease surveillance systems[23–25] , Twitter microblogs[26–29] , Electronic Health Records[30] , and satellite images[31] to estimate the presence of a disease in a given location . Some of the biases and errors observed when using these alternative data sources as individual indicators of disease incidence have been recently mitigated by using ensemble approaches that combine information from multiple data sources to produce a more robust disease estimate[32] . In parallel , multiple improvements have been proposed to disease tracking methodologies based on Google searches[33–38] . Finally , it has been shown that in the absence of information from traditional government-lead disease reporting , the combined use of news reports and Google’s search activity of the word “zika” in Colombia led to reasonable estimates of cumulative cases of Zika[20] . To the best of our knowledge , however , no attempts have been made to date to harness these and other digital data sources for near-real time weekly forecasting of Zika infections . Here we assess the feasibility of using Zika-related Google search queries , Zika-related Twitter microblogs , and information from news reports collected by the web-based surveillance system HealthMap[16] , in the prospective monitoring of Zika in five countries: Colombia , El Salvador , Honduras , Venezuela , and Martinique . In addition , we evaluate the ability of a collection of multivariable models that use information from these three data sources as input , to dynamically track and forecast the incidence of Zika virus up to 3 weeks ahead of the release of reports from PAHO , using multiple evaluation metrics .
We obtained weekly reports from the Pan American Health Organization ( PAHO ) that document the number of laboratory-confirmed and suspected cases of Zika in the Americas from the website ( http://ais . paho . org/phip/viz/ed_zika_epicurve . asp ) and from weekly epidemiological updates[39] . In the absence of this information , we obtained suspected and lab-confirmed Zika cases from epidemiological bulletins produced by the national Ministries of Health ( MOH ) of Colombia and Martinique[40 , 41] . Throughout the manuscript , we refer to these data as “official case count” . Due to the lack of robust diagnostic capabilities across the Americas and the estimated large number of asymptomatic cases[4 , 42] , the present study focuses on predicting suspected Zika cases , which can be used as a proxy for potential hospital visits in each locality . This information could be useful for public health decision-makers when designing resource allocation plans . Under PAHO criteria , cases were classified as suspected if the patient presented a rash and two or more of the following symptoms: fever , conjunctivitis , arthralgia , myalgia , and peri-articular edema[43] . The time series of suspected cases spans the entire epidemic period of each country , beginning with the earliest reported cases through the last available epidemiologic week in the data ( last accessed August 3 , 2016 ) . Data profiles for each country can be seen in Table 1 . The selection process of potentially useful search terms to track Zika avoided forward-looking bias and was performed via the Google Correlate and Google Trends tools ( https://www . google . com/trends/correlate/;https://www . google . com/trends/ ) . We identified the most highly correlated terms with the time evolution of Zika incidence in Colombia and Venezuela on Google Correlate within the time period of May 2015 to Jan 2016 , and used Google Trends to identify search terms related to the term “Zika” for all five countries . The time window for the selection of these terms did not exceed the training period of each model . Because the output of Google Trends and Google Correlate consists of country-specific search terms , these are different for each country . All highly correlated terms to the query “Zika” were selected as model inputs without discrimination , including some potential misspellings of the disease such as “sika” and “sica” . We obtained weekly fractions of all identified Google search terms using the Google Trends website . The selected search terms were used as independent variables in the models and are shown in S1 Table . We leveraged a custom script to access the free Twitter Public API to collect the maximum allowed number of tweets ( up to 1% total Twitter volume ) with any geographical coordinates . We then searched these tweets by country , using Twitter’s assigned country code and restricting to tweets in which this parameter was present , for the weekly volume of Twitter micro-blogs containing any of the words “Zika” , “microcephaly” , and “microcefalia” , but only Colombia and Venezuela had relevant Zika-related tweets , within the weeks of the epidemic outbreak , to merit the inclusion of Twitter data in our models . The fraction of tweets containing the Zika-related words when compared to the total number of tweets for each country was computed for every week and used as an independent variable in the models . We obtained cumulative reported case counts of Zika virus disease in all countries via the HealthMap digital disease surveillance system ( www . healthmap . org ) , which reports non-governmental media alerts of infections[16] . From these alerts , we calculated the weekly incidence of Zika infection for use as an independent variable in the models . In order to assess whether the selected Google search terms , Twitter microblogs , and HealthMap-reported cases could be useful for weekly prediction of Zika incidence , we computed the Pearson’s correlation between each predictor and the official Zika case count , first for the training period of each country and later for the entire time series . In addition , we evaluated the autocorrelation of the signal itself ( as lag-1 , lag-2 , and lag-3 terms ) . To determine the optimal linear relationship between the predictors and cases , we applied a series of simple transformations to these data and selected the transformation which produced the highest Pearson’s correlation . The results of this preliminary analysis was used for variable selection and to inform the dynamic transformation of variables process within the model , detailed below . A collection of multivariable models , inspired by those introduced in the Flu prediction literature[30 , 37] , were considered to estimate and forecast weekly suspected cases of Zika in the aforementioned five countries . These models used as input the weekly Google search frequencies of Zika-related terms , the fraction of Zika-related Twitter microblogs , cumulative Zika case counts as recorded by the HealthMap disease surveillance system , and the available historical official case count data at a given point in time . For consistency and comparability , all models ( i ) automatically select the most relevant search terms for prediction , ( ii ) incorporate new information on Zika cases as reports are released every week , and ( iii ) identify the best functional relationship between each input variable and the outcome variable , every week . The selection of the most predictive input variables was performed using a penalized LASSO regression approach as described in[44] . While avoiding the use forward-looking information , we incorporated the most recently available information on Zika cases every week by dynamically expanding the time window of the training set of the models . Finally , at each week , we analyzed whether transforming each input variable would increase its correlation with the output variable . If this were the case , then the transformed value of the input variable producing the highest correlation with case data would be used as input for the model . As more epidemiological information becomes available , this dynamic transformation process allows the model to recursively recalibrate and incorporate changes in the relationships between the input variables and the case count information observed so far . The transformations we considered were not exhaustive and included the log ( x ) , x2 , and sqrt ( x ) . In addition to the models that used the aforementioned data streams as input , we built a collection of baseline models for comparison and context . We considered models that only used historical observation of Zika cases to predict cases on the subsequent weeks and models that incorporated information from these various data streams . Given the success of Google search terms in tracking other diseases as observed in [27 , 28] , our models utilized Google search as a central predictor , and we explored the additions of Twitter and HealthMap data for the improvement of model predictions . Specifically , we considered ( i ) AR: a baseline lag-3 autoregressive model that used only Zika surveillance information from the prior 3 weeks to predict suspected cases , ( ii ) G+T: a model which used only Google search and Twitter ( if available ) data for prediction as introduced in[33] ( iii ) ARGO+T: a model which used autoregressive information and Google and Twitter ( if available ) data , adapted from[37] , and ( iv ) ARGO+TH: a model which combined all data streams ( Twitter if available , Google , HealthMap ) with lag-3 autoregressive terms . For the two countries ( Colombia and Venezuela ) which had available Twitter data , we also constructed identical models ( ii—iv ) without this data source; that is , using Google and HealthMap data only . Our models are described by the following equation y^t= αt+ ∑i=1Nγiy ( t−i ) + ∑j=1KβjXj , t+τTt+ηHt+ εt εt~N ( 0 , σ2 ) where we expand an autoregressive model of lag N with the inclusion of the fraction of Google search frequency X for each term j , the fraction of Twitter volume T , and HealthMap-reported cases H . As described in[37] , autoregressive terms generally help maintain predictions within a reasonable range , while Google and Twitter information help the models to respond more rapidly to sudden changes in the dynamics . Due to the novelty of the Zika outbreak , stationarity was not used as a way to assess the appropriateness of using autoregressive models as a baseline; instead , we relied on the observed high autocorrelation of the signal with recent time lags of case counts and evidence of similar mosquito-borne outbreaks modeling approaches[45 , 46] . At each week , we used our models to generate predictions for 1 , 2 , and 3 weeks ahead of current time . To avoid future-looking bias in our predictions , forecasts were made using only the information available to each model at each week t; and for each time horizon our case count estimate was obtained using a different model . For instance , all models with autoregressive terms are restricted , in further week-ahead predictions , from accessing weeks of case data that have not yet occurred relative to week t . Thus , 3-week ahead ( t+3 ) forecasts for model ( i ) were generated using only the lag-3 term ( AR3 ) of official cases from 3 weeks prior to t+3: that is , using the observed cases available exactly at week t . 1-week ahead ( t+1 ) forecasts for model ( i ) , meanwhile , utilized all three AR1 , AR2 , and AR3 terms , which contain information on reported cases from the strictly observable weeks t , t-1 , and t-2 . In other words , data that would be unavailable in real-time for predictions—in our case , data on future infections—are excluded from each model . This same rule applies to models ( iii ) and ( iv ) , which also include autoregressive information . Reflecting the delay in the release of case reporting , the models do access future weeks ( relative to week t of case reporting ) of Google searches , Twitter microblogs , and HealthMap-reported cases , since these digital streams are available closer to real-time than are official case data . All models were trained through the same week in the time series and evaluated over the same time window , although the number of training weeks differed based on the information required in each model . Models containing autoregressive information began training 4 weeks into each epidemic , as opposed to training from the first week of reported cases , in order to necessarily inform the one- , two- , and three-week lag terms . A summary of dates and data used by country is shown in Table 1 . Models were fit as multiple generalized linear models with the glmnet package[47] in R v3 . 2 . 4[48] , validated using k-fold cross validation , and evaluated for their out-of-sample predictive performance . For each model , we report three evaluation metrics: root mean square error ( RMSE ) , the relative RMSE ( rRMSE ) , and the Pearson correlation of predictions with observed cases , as detailed in[32] . Equations for each metric can be found in S1 Equations .
In order to evaluate the feasibility of using Zika-related Google searches , Twitter microblogs , HealthMap news reports , and historical official case counts to track Zika , we calculated the Pearson correlation between ( a ) the observed suspected case counts and each input variable , and ( b ) the observed suspected case counts and three transformations: log ( x ) , x2 , and sqrt ( x ) , for each input variable . These transformations were observed to sometimes lead to better correlation values than the original raw variables for different time periods . S1 Fig displays in each country the best transformation of each input variable and suspected Zika case counts . From the multiple panels for each country , it can be seen that at least a subset of these ( transformed ) variables showed potential to be useful to track Zika . Indeed , correlations ranged from 0 . 93 to 0 . 56 in Colombia; 0 . 90 to 0 . 18 in Honduras; 0 . 39 to 0 . 29 in Venezuela; 0 . 69 to 0 . 13 in Martinique; and 0 . 92 to 0 . 41 in El Salvador . The lowest-correlation predictors tended to be the lag-3 autoregressive term , HealthMap-reported cases , and non-specific Google search terms like “Virus . ” For each country , we produced out-of-sample predictions for the one , two , and three-week ahead time-horizons with the four models introduced in the previous section . We evaluated models according to the maximum number of data sources available , and thus assessed all models with Twitter data , where available ( Colombia and Venezuela ) . In addition , we evaluated models with and without the inclusion of Twitter data . Plots comparing model predictions with the official Zika case count , by time horizon and country , are shown in Figs 1–3 . Table 2 summarizes the out-of-sample predictive performance of the four models for each of the three week-ahead time horizons and for all countries , as captured by the three evaluation metrics . Note that while some model predictions showed high correlation values with official case counts , their predictions showed large discrepancies with the data . As a consequence , we relied on the relative RMSE ( rRMSE ) to establish the quality of model prediction given the short time span of the outbreaks . The rRMSE provides an estimate of the prediction error relative to the number of true cases observed in each week over the evaluation period , and , from our perspective , allows for better comparisons across models and time horizons . We henceforth judge model performance using this metric . As seen in the evaluation metric values , no single model performed best across metrics , time horizons , and countries . Based on the rRMSE , models that combined Google ( and Twitter data where available ) with autoregressive information showed better predictive accuracy for 1-week ahead predictions . Meanwhile , models that only used Google ( and Twitter where available ) typically performed best for two and three-week ahead predictions . The ARGO+T or ARGO+TH models outperformed all other models in 1-week forecasts for all countries with the exception of Venezuela and Martinique . In Venezuela and Martinique , the ARGO+T model ( rRMSE = 38 . 8 and 43 . 0 , respectively ) slightly underperformed relative to the G+T model ( rRMSE = 35 . 3 and 40 . 1 , respectively ) , with a difference in rRMSE of about 3 percent points . In Colombia and El Salvador , the difference in rRMSE was less than 2% between the ARGO+TH and the ARGO+T models , with both models improving the rRMSE substantially compared to the G+T model . In further week-ahead predictions , the Google and Twitter only ( G+T ) model outperformed models that also incorporated autoregressive information , exhibiting the lowest rRMSE in 3 of 5 countries for 2-week forecasts , and in 4 of 5 countries for 3-week forecasts . Across models , prediction accuracy decreased as predictions were made further into the future , resulting in increases in rRMSE ( and RMSE ) and declines in model correlations across time horizons . Of all countries studied , Colombia had the best model performance in each week-ahead horizon for every model , with the exception of 3-week G+T forecasts; of all time horizons , the 1-week ahead predictions performed best in each country and model . In most cases , the autoregressive model over-predicted Zika incidence and underperformed all other models . S2 Table shows the performance of additional versions of these models ( i . e . , the ARGO+T model with and without Twitter data ) . It can be seen that the inclusion of Twitter microblog data into our models improved or was comparable to ( within 0 . 2 rRMSE ) the performance of all models lacking Twitter data in Colombia ( range of rRMSE reduction: -0 . 13 , 1 . 6 ) , and of the ARGO+T and ARGO+TH models in Venezuela ( range of rRMSE reduction: 8 . 14 , 125 . 1 ) , for all time horizons . Conversely , incorporating HealthMap digital cases improved the rRMSE by no more than 3 . 8 points , or 7% ( range: 0 . 06% , 6 . 8% ) across models , time horizons , and countries , but worsened the rRMSE by up to 25 . 1 points , or 60% ( range: 1 . 4% , 59 . 8% ) . The relative predictive power of each variable , as given by their standardized model coefficients , at each week in the out-of-sample predictions , is displayed in a collection of heatmaps in S2 Fig .
We have shown that Internet-based data sources can be used to track and forecast estimates of suspected weekly Zika cases , weeks ahead of the publication of official case counts . Models that rely exclusively on Google searches have among the lowest error ( rRMSE ) of all models , indicating that Google search terms alone have the potential to track Zika cases . The heatmaps shown in S2 Fig confirm that Google search terms have significant predictive power in most countries and time horizons . In Colombia and Venezuela , where robust Twitter data were available , we found that Twitter improved predictions compared to models that lacked the data source . Meanwhile , though HealthMap news reports have been found to be good estimators of Zika cumulative incidence[20] , the effect of incorporating HealthMap news reports into our models was marginal across countries and generally did not reduce prediction error in any of the weeks-ahead forecasts; where it did reduce prediction error , in El Salvador , it did by less than 2% compared to the next-best model lacking HealthMap data . We noted early evidence of HealthMap’s weak predictive power in its low correlation with official case counts , as shown in S1 Fig . Likewise , the heatmaps of S2 Fig reveal that news reports data generally had low influence in models after the first several weeks of out-of-sample predictions . We noted , however , in a post-hoc analysis , that news of Zika infections were 2–3 weeks delayed with respect to the time when cases had occurred . This fact suggests that in the absence of official case count reports , one may use ( a potentially lagged version ) of news reports to track Zika activity as found previously by[20] . In the future , we would expect to improve model predictions by incorporating HealthMap data lagged back in time by 2–3 weeks . As seen in flu forecasting studies[32] , the quality of predictions decreased as the time horizon of prediction increased . Specifically , for one-week predictions , we found that the model that uses Google ( and Twitter where available ) combined with autoregressive terms ( the ARGO+T model ) performs best in most countries , and its performance is better than or comparable to the equivalent model that lacks autoregressive information . Thus , the use of historical case information ( autoregressive terms ) improves predictions in the near future , a finding that has been documented in prior studies[26 , 30 , 37] . However , for 2–3 week-ahead predictions , models that use exclusively data from Google and Twitter ( G+T ) , without autoregressive terms , perform best . This is likely because the 2–3 week old official case information is no longer crucial to refine the accuracy of predictions , and changes in Google search and Twitter activity better respond to fluctuations in Zika dynamics . Consequently , relying on historical case data becomes less useful in making predictions further into the future . This is also observed in the low relevance of lag terms in the 2- and 3-week heatmaps of all models ( S2 Fig ) . Additionally , as automatically identified by our term selection methodology ( LASSO ) , the predictive power of Google search terms is stronger in 1 week-ahead predictions than in 2 and 3 week-ahead predictions . This can be observed in the heatmaps shown in S2 Fig . This finding confirms the appropriateness of using a real-time hidden Markov process as a modeling framework , as discussed in [37] . From this perspective , people affected by Zika will search for Zika-related terms when affected by the virus or when they may suspect risk of exposure to it . This population search behavior suggests that monitoring search activity may help track disease incidence . The decreased relevance of search activity in 2 and 3 week-ahead predictions may suggest that autoregressive case count information may have a stronger role in future occurrences . Our models improve upon prior methodologies[32 , 33 , 38] that use internet-based data sources to track flu by adding an internal dynamic variable transformation process to reassess the relationship of all input variables with the official Zika case count each week . Indeed , the heatmaps of variable coefficients show that model forecasts depended on an ensemble of terms whose predictive power changed magnitude and direction week by week . Given that Google queries were selected on the basis of their relationship to case data or to the term “Zika” exclusively in the training period , it is likely that these relationships change and perhaps even weaken in later weeks . We thus emphasize the importance the need for dynamic transformation of the input variables to recursively reassess these relationships and readjust predictors to their best linear fit with the data . Some of the limitations of our approach include , for example , the inherent population biases of Internet search engines and Twitter microblog users . Internet searches patterns may also reflect media coverage and situational awareness that may not coincide with the dynamics of the disease being tracked . Also , different countries and locations frequently have distinct news reporting practices . Local media in regions with endemic mosquito-borne diseases may react differently to outbreaks than regions where these diseases are less frequent . Media attention thus has the potential to dramatically influence our weekly predictions . The dynamic reassessment of the predictive power of each input variable , via LASSO and the dynamic transformation approach discussed earlier , is built in our model to mitigate these events . Terms that may peak during a week of high media attention can be thrown out of the influence of the model for the subsequent week of prediction if their relationship with case count information has weakened . Only the terms with high predictive power are selected by the LASSO . In this way , our models are self-correcting . Nonetheless , we note that since our predictions rely largely on user search and media activity , our work is meaningful only in time periods when the population is aware of the disease; to this point , it has been demonstrated that Zika virus was introduced to Brazil and the Americas at least one year before the epidemic was recognized by health ministries and the public at large[49] . Another important consideration is the time lag between peaks in Zika virus incidence and microcephaly , of up to 5 months[50 , 51] . Our models capture search activity surrounding the Zika epidemic , and thus end up using search terms like “microcephaly” as input . These terms may be related to broader awareness of Zika activity . Given the estimated lag , however , evaluating microcephaly-related queries synchronously with cases has the potential to introduce a bias in the model . Further work must explore the effect of lagging these terms compared to our synchronous use of them . As mentioned in the Methods section , Twitter data was not sufficient for use in the models for all countries . To improve upon this , future work could explore keyword queries that incorporate symptoms of Zika infection . In addition , to increase the total volume of tweets we plan to collect historical data based on these new query strings and explore ways to geocode the data ourselves , instead of relying on the current Twitter-generated subset of tweets with coordinate information . Another challenge lies in the prediction of very low case numbers . In several weeks of the countries studied , official case counts of Zika fell below 50 suspected cases per week; this is very low relative to the thousands of cases experienced per week at the height of the epidemics . We observe that the quality of predictions decreases during time periods with low case numbers , and the model tends to under-predict cases . Our prediction approaches worked best in locations with highest Zika incidence , independently of Internet penetration . This tendency was also observed in the assessment of the Google Dengue Trends system in[38][45] . Limitations on the use of official suspected case counts from PAHO as our prediction goal include under-reporting . Indeed , Zika has been observed to be asymptomatic in at least 80% of infected persons[42] . As a consequence , our models likely underestimate the true number of Zika infections that exist , while reasonably estimating the actual number of suspected cases that seek medical attention . Unfortunately , no surveillance system has yet reported estimates of asymptomatic Zika infections , and it is unclear whether asymptomatic infections can result in the same consequences of birth and neurological defects as do symptomatic infections . The predictions of our model should be compared to those of SIR-type models and epidemiologic models that evaluate Zika incidence in the context of important , known drivers of Zika , such as climate and ecological factors . In this paper , we explore whether digital data streams are viable estimators of Zika cases . In future inquiry , we believe that these methods could be incorporated into , and enhance , traditional epidemiologic methods to track the virus . Given the need of early interventions to curb mosquito-borne disease transmission , our model predictions fill a critical time-gap in existing Zika surveillance since official case count reports will , most likely , continue being published multiple weeks after the occurrence of Zika cases . Moreover , access to real-time and likely future estimates of Zika activity provide an opportunity for health and government officials to allocate resources differently when potential changes in Zika dynamics are likely to occur , even ahead of official case documentation . The models presented here show promise to be expanded to any country at any time to track Zika cases and signal changes in transmission for public health decision-makers . Our models currently predict Zika activity at the country level , which we feel is useful for national decision-makers and surveillance purposes; however , our methodology can be extended to finer spatial units , such as the regional or municipal level . Performing predictions with higher spatial resolution will allow more targeted interventions and allocation of resources to the areas with the greatest projected burden of disease . To produce these predictions in a publicly available and timely manner , we will work to create a website that displays Zika estimates for multiple countries continuously updated in real-time , similar to content published on www . healthmap . org/flutrends and www . healthmap . org/denguetrends .
|
In the absence of access to real-time government-reported Zika case counts , we demonstrate the ability of Internet-based data sources to track the outbreak . Our model predictions fill a critical time-gap in existing Zika surveillance , given that early interventions and real-time surveillance are necessary to curb mosquito transmission . Official Zika case reports will likely continue to be delayed in their release; thus , it is important that health and government officials have access to real-time and future estimates of Zika activity in order to allocate resources according to potential changes in outbreak dynamics . The methodologies presented here may be expanded to any country–and perhaps finer spatial resolutions–to identify changes in Zika transmission for public health decision-makers .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"microcephaly",
"venezuela",
"pathology",
"and",
"laboratory",
"medicine",
"pathogens",
"sociology",
"geographical",
"locations",
"microbiology",
"social",
"sciences",
"social",
"media",
"viruses",
"developmental",
"biology",
"rna",
"viruses",
"network",
"analysis",
"social",
"networks",
"social",
"communication",
"infectious",
"disease",
"control",
"morphogenesis",
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"computer",
"and",
"information",
"sciences",
"south",
"america",
"twitter",
"medical",
"microbiology",
"epidemiology",
"birth",
"defects",
"communications",
"microbial",
"pathogens",
"congenital",
"disorders",
"people",
"and",
"places",
"infectious",
"disease",
"surveillance",
"colombia",
"flaviviruses",
"viral",
"pathogens",
"disease",
"surveillance",
"biology",
"and",
"life",
"sciences",
"organisms",
"zika",
"virus"
] |
2017
|
Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data
|
Diarrhoea is a leading cause of death in Nigerian children under 5 years . Implementing the most cost-effective approach to diarrhoea management in Nigeria will help optimize health care resources allocation . This study evaluated the cost-effectiveness of various approaches to diarrhoea management namely: the ‘no treatment’ approach ( NT ) ; the preventive approach with rotavirus vaccine; the integrated management of childhood illness for diarrhoea approach ( IMCI ) ; and rotavirus vaccine plus integrated management of childhood illness for diarrhoea approach ( rotavirus vaccine + IMCI ) . Markov cohort model conducted from the payer’s perspective was used to calculate the cost-effectiveness of the four interventions . The markov model simulated a life cycle of 260 weeks for 33 million children under five years at risk of having diarrhoea ( well state ) . Disability adjusted life years ( DALYs ) averted was used to quantify clinical outcome . Incremental cost-effectiveness ratio ( ICER ) served as measure of cost-effectiveness . Based on cost-effectiveness threshold of $2 , 177 . 99 ( i . e . representing Nigerian GDP/capita ) , all the approaches were very cost-effective but rotavirus vaccine approach was dominated . While IMCI has the lowest ICER of $4 . 6/DALY averted , the addition of rotavirus vaccine was cost-effective with an ICER of $80 . 1/DALY averted . Rotavirus vaccine alone was less efficient in optimizing health care resource allocation . Rotavirus vaccine + IMCI approach was the most cost-effective approach to childhood diarrhoea management . Its awareness and practice should be promoted in Nigeria . Addition of rotavirus vaccine should be considered for inclusion in the national programme of immunization . Although our findings suggest that addition of rotavirus vaccine to IMCI for diarrhoea is cost-effective , there may be need for further vaccine demonstration studies or real life studies to establish the cost-effectiveness of the vaccine in Nigeria .
Globally , diarrhoea is the second leading cause of death in children under 5 years [1] . There are about 1 . 7 billion annual cases of diarrhoea in the world and 760 , 000 annual deaths of children under 5 years due to diarrhoea [2] . In Nigeria , 11% of childhood deaths are caused by diarrhoea while only 1% of these children with diarrhoea receive the right treatment [3] . Diarrhoea kills over 90 , 900 children under the age of 5 yearly in Nigeria , which translates to about 249 deaths daily [3] . A plausible cause of the high diarrhoeal mortality could be the use of wrong medications . These medications include anti-motility agents ( e . g . loperamide or tincture of opium ) , adsorbents ( e . g . kaolin & pectin ) and antibiotic ( e . g . co-trimoxazole , ciprofloxacin ) . In Nigeria for instance , more than 62% of caregivers were prescribed antibiotics while 35% prescribed anti-motility drugs for childhood for diarrhoea [4] . Anti-motility agents are not suitable for childhood diarrhoea because they are ineffective in treating the pathogenic causes of diarrhoea and can cause partial or complete blockage of the bowel , resulting in an inability to pass stool and lethargy [5] . They do not prevent dehydration and their mode of action can lead to build-up of pathogenic toxins in the intestine and make the illness last longer [6] . The World Health Organization ( WHO ) and United Nations International Children’s Emergency Fund strongly discourage its use in infants and children [6] . Similarly , adsorbents attract water , toxins and bacteria from the digestive tract [7] . They do not help to replenish the water and electrolyte that are lost and they have not been proven safe and efficacious in cases of paediatric diarrhoea . The right approach to management of childhood diarrhoea includes prevention through rotavirus vaccine and use of oral rehydration salt ( ORS ) or Intravenous fluid ( IVF ) . Rotavirus vaccine protects against rotavirus infections , the leading cause of severe diarrhoea among young children [8] . The vaccine prevents 15 to 34% of severe diarrhoea in the developing world and 37 to 96% of severe diarrhoea in the developed world [9] . The vaccine is recommended by WHO for inclusion in national programme of immunization especially for diarrhoea endemic countries [9] . Low osmolarity ORS plus zinc are recommended by the WHO as the first-line treatment for childhood diarrhoea [10] , and is the adopted approach for diarrhoea management under the integrated management of childhood illness ( IMCI ) . ORS plus zinc have been proven to speed recovery , restore strength , energy and appetite and help keep children thriving [11] , [12] . WHO also recommend the inclusion of breastfeeding and retinol to the management approach [13] , [14] . Although the inclusion of zinc to ORS in the management is gaining acceptance in Nigeria , the inclusion of retinol and breast feeding practices are still poor [15] . Most recent studies on cost-effectiveness analysis of diarrhoea management using the right treatment approaches failed to reflect the combined effect of other components of IMCI for diarrhoea , i . e . breastfeeding , zinc tablets and retinol in addition to ORS or IVF . They considered zinc alone [16] , ORS alone , ORS plus zinc alone [17] , [18] , or ORS plus rotavirus vaccine alone [19] . It is necessary to evaluate the holistic effect of these components in a cost-effectiveness analysis . Furthermore , to the best of our knowledge , no study on cost-effectiveness of diarrhoea management in Nigeria has been conducted . As a disease with high prevalence in Nigeria , there is need to evaluate the best approach to its management . This study evaluated the cost-effectiveness of various approaches to diarrhoea management namely: the ‘no treatment’ ( NT ) approach; the preventive approach with rotavirus vaccine; the IMCI approach; and rotavirus vaccine + IMCI approach .
Participants were an estimated population of 33 million Nigerian children under five years at risk of having diarrhoea ( well state ) . This figure was based on the 2016 population report which indicated that about 18% of Nigerians are between 0–5 years and this group are at risk of having diarrhoea [20] . The study was carried out in Nigeria using a decision analytic model ( Markov cohort model ) and depicted the Nigerian scenario . The model incorporated data to simulate a real life scenario . This simulation based decision analytic Markov model used retrospective data to compare four treatment approaches . Cost was estimated from the payer’s perspective ( e . g . Health Maintenance Organisations , Government , Insurance companies etc ) . Cost items involved in this perspective included direct medical cost [21] . Diarrhoea management approaches or interventions considered in this decision analytic model were based on the recommendation of the WHO [9] , [10] . The specific details of these approaches are shown in Table 1 . The four competing approaches in the decision analysis include: A decision analytic Markov model was used to evaluate the four treatment approaches . The model has four states , namely: well state , moderate state , severe state and death . The starting age in the model was one week . Patients were modelled to start from the well state . They can move to or remain in a health state or die from diarrhoea . See Fig 1 . Nigerian specific data were used to construct the model except where not available . The weekly probabilities of staying in any of the health state depended on the risk profile ( as shown in Table 2 ) . The transition probability from well to moderate diarrhoea was obtained from age specific incidence for Nigeria [22] . The transition probability of progressing from moderate to severe diarrhoea , recurrent moderate diarrhoea and recurrent severe diarrhoea were obtained from systematic reviews [23] , [24] . The transition probability from all cause diarrhoea to death was obtained from a United Nations International Children’s Emergency Fund report on childhood diarrhoea mortality in 2015 in Nigeria [25] . The mortality rate from other causes of disease was calculated from the 2013 Nigerian life table [26] . The model was built using 2013 Microsoft Excel . This model approach was preferred because it has the ability to represent repetitive events and it is time dependent . Diarrhoea is a disease whose risk is continuous over time . The administration of the vaccine is time bound ( 6 to 32weeks ) and the disease occurs up to 3 times per year . Representing these in a decision tree for instance will affect the quality of the result . In the model , we assumed that the children will start from the well state and with each week that passes ( Markov cycle ) , they may remain well; they may experience moderate or severe diarrhoea , they may remain in diarrhoea ( non-fatal ) ; or they may die from diarrhoea or other causes not related to diarrhoea . The model assumed that all mothers will breastfeed their children up to 1 year in accordance with the recommendation of WHO and UNICEF and deemed practicable in Nigeria [27] , [28] . L-ORS and IVF were usually given until diarrhoea stops or improves but in our model they were given for 3 days while zinc was given for 10 days [6] , [10] . The model was designed such that a child will have an average of 3 diarrhoea episodes per year [2] . In the NT approach , we assumed that the mother/caregiver will visit the physician but fail to treat . She will rather administer breast milk to the child . The Markov cohort model was employed to simulate clinical outcomes and costs during a life cycle of 260 weeks ( since most cases of childhood diarrhoea occur between the ages of 0 to 5 years of age ) for an estimate of 33 million children under the different alternative intervention scenarios . The cost and health outcome for the interventions were discounted at a rate of 3% based on the WHO CEA guideline [21] . Health outcome was presented in disability adjusted life years ( DALYs ) . The DALY calculation was based on the recent Global Burden of Disease 2010 study and used recently updated disability weights [29] , [30] . DALYs were calculated for each cycle , accumulated over the model time horizon and then averaged to obtain the DALYs per patient . This was repeated for each diarrhoea management approach . A comprehensive review indicated that promotion of breastfeeding was one of the most important interventions for controlling diarrhoea among children [13] , [31] and thus , it was used as the base case scenario . We calculated the relative risk for moderate diarrhoea from studies in Nigeria that presented treatment success with ORS with a utilization rate of 74 . 6% [32] , [33] . Risk difference between ORS and IVF of 4% was used to calculate relative risk for severe state [32] , [34] . A recent systematic review provided the relative risk of rotavirus vaccine on all cause diarrhoea for Nigeria , Ethiopia and Democratic Republic of Congo [35] . We used diphtheria-tetanus-pertussis ( DTP3 ) immunization coverage rate of 70% in Nigeria as a proxy for coverage rate of rotavirus vaccination [36] . The implementation coverage rate of IMCI for diarrhoea ( 58 . 6% ) was obtained from a Nigerian based study [15] . The relative risk of zinc was obtained from the final estimate of a commentary [37] , which analysed three systematic reviews on the effect of zinc supplementation on diarrhoea treatment [38] , [39] , [40] . The relative risk of breastfeeding on diarrhoea was obtained from the WHO library [13] . The relative risk of zinc and L-ORS on diarrhoea was combined to obtain the resultant relative risk for moderate diarrhoea . The relative risk of IVF and zinc was also combined to obtain the relative risk for severe diarrhoea . Details of input parameters and their distributions are shown in Table 2 . Cost was estimated from the payer’s perspective which included direct medical cost ( medications cost , health professionals services , hospitalization ) [21] . The economic definition of cost based on the concept of opportunity cost was applied in the cost valuation . Cost of medications were obtained from the Nigerian National Health Insurance Scheme ( NHIS ) drug price list , published in 2005 and 2013 [41] , [42] . Cost of ORS , Ringer’s lactate , and retinol were obtained from the 2013 NHIS drug price list while cost of physician consultancy , physician review , nursing service and hospital-stay were obtained from the 2005 NHIS drug price list . Cost of zinc supplement and RV1 were obtained from the 2013 International Drug Price Indicator guide [43] . Cost obtained from the NHIS were adjusted to reflect the future ( 2016 ) value using interest rate of 3% ( range of 0% - 6% ) [21] , [44] . For cost obtained from the International Drug Price Indicator guide , the median price was used and adjusted to reflect the 2016 price . Price adjustment entails inflating price using the consumer price index inflation calculator . [45] , [46] , [47] . Gamma distribution was used to capture the uncertainty inherent in the cost parameter . All costs were converted to 2016 US dollar and a discount rate of 3% was used for all future cost . Treatment course/episode cost for each of the treatment approaches was calculated . Cost for each approach was obtained by summing up the cost components . For each cycle for each treatment approach , cost was obtained by summing up the number of patients with diarrhoea and multiplied by the cost of management and then discounted . The cost from cycle 1 to 260 was then summed up and averaged to obtain the cost to manage a patient ( standard cost ) . The standard cost of each treatment approach was then used to perform the probabilistic sensitivity analysis ( PSA ) . DALY was also calculated by combining years lived with disability ( YLD ) and years of life lost ( YLL ) for each weekly cycle . YLD was calculated as follows: YLD = Number of cases × duration till remission or death × disability weight [29] , [48] . The recently updated disability weights were used [30] . Children in the well or asymptomatic were assigned a disability weight of 0 [30] . YLL was calculated as follows: YLL = Number of deaths due to diarrhoea × life expectancy at the age of death [48] . Standard life expectancy ( 0–4 years ) of 57 . 5 years was obtained from the 2013 Nigerian life table [26] . The DALYs across each cycle was summed and averaged to obtain the standard DALYs which was used in the PSA . DALYs averted was calculated as the difference between the NT DALYs and the DALYs of each of the other interventions . We identified cost-effective approaches to management of childhood diarrhoea in Nigeria by calculating the incremental costs-effectiveness ratio ( ICER ) of each of the intervention against the next best effective approach . ICER represents the average incremental cost associated with 1 additional DALY averted . As the threshold for an intervention to be cost-effective is currently still being debated , specifically the traditional 1–3 times GDP per capita used by WHO-CHOICE , the alternative 0 . 52 times GDP per capita suggested by the University of York was also used in our analysis [49] . In this case , interventions with an ICER below 0 . 52 times the GDP per capita are considered very cost-effective . The mean ICERs with their 95% confidence interval from the 10 , 000 iterations were calculated for each intervention . We performed a univariate sensitivity analysis to know the parameters and assumptions the result was sensitive to using the variables upper and lower limit at 95% confidence interval . For variables without confidence interval like primary cost data +/- 25% was used . PSA was used to assess simultaneous uncertainty in many variables . This approach is well suited to express overall parameters uncertainty [50] . A total of 10 , 000 iterations of Monte Carlo simulations was conducted and for each iteration a value was drawn randomly from each distribution and net health benefits calculated [50] . We used cost-effectiveness acceptability ( CEA ) frontier to illustrate the degree of uncertainty in the estimates . The CEA frontier explored relative efficiency of the interventions , thus showing the likelihood of an intervention being acceptable by the decision-maker . In order words , the CEA frontier illustrated the probability of any intervention being optimal compared to all other competing alternatives . Sixty-five ( 65 ) iterations of simulations were conducted for different willingness-to-pay threshold ratio . For each iteration , the probability that the cost-effectiveness of any intervention being optimal compared to other competing interventions was calculated for all the alternative interventions from the NMB [50] .
Cost analysis over a life cycle of 260 weeks showed that IMCI approach has the least cost per patient ( $9 . 08 ) after NT ( $5 . 20 ) . Rotavirus vaccine + IMCI approach has the highest cost ( $32 . 32 ) followed by the rotavirus vaccine approach ( $20 . 61 ) . In all , NT has the least cost when compared to the other interventions . The NT approach has no DALY averted ( since it was used as baseline ) . The rotavirus vaccine + IMCI approach averted the highest DALYs . Table 3 shows details of the result . As shown in Table 3 , the rotavirus vaccine approach was strongly dominated and was excluded in ICER analysis . the ICER of the IMCI and rotavirus vaccine + IMCI interventions were less than 0 . 52 times the GDP per capita [49] of Nigeria which was US$2 , 177 . 99 in 2016 [51] . Thus , IMCI and rotavirus vaccine + IMCI approaches were all very cost-effective . IMCI approach had the smallest ICER and is cost-saving relative to the rotavirus vaccine approach . The result also showed that rotavirus vaccine + IMCI approach had the highest ICER below the threshold and thus the most cost-effective . The univariate sensitivity analysis showed that the effectiveness of ORS-zinc was the most influential parameter followed by cost of rotavirus vaccine . At lower limit of ORS-zinc effectiveness ( 0 . 083 ) the ICER increased from $80/DALY to $180/DALYs while at higher limit ( 0 . 305 ) the ICER reduced to $32/DALYs . Other parameters with significant influence on the result of the model were transition probability from well to moderate diarrhoea , and transition probability from all-cause diarrhoea to death . Outcome discount rate and cost of IMCI severe diarrhoea had insignificant effect on the result . Details are shown in Fig 2 . Fig 3 further illustrates the relative efficiency of the interventions in optimizing health care resources allocation . Under parameters uncertainty and over some willingness-to-pay values , the CEA frontier illustrated which intervention for management of childhood diarrhoea had the highest probability of being cost-effective . In other words , it shows the decision uncertainty surrounding the optimal choice . The NT approach had the highest probability of being cost-effective at no willingness-to-pay value . When the payer is willing to provide at least $8 to avert a DALY , the IMCI approach had the highest probability of being cost-effective . Rotavirus vaccine + IMCI had the highest probability of being cost-effective when the payer is willing to pay above $80 to avert one extra DALY over IMCI . Rotavirus vaccine alone was dominated as it showed a zero probability of being cost-effective at any willingness to pay .
This study aimed to identify cost-effective approaches to childhood diarrhoea management in Nigeria using a decision analytical model . The study compared the ICER of three approaches to the 0 . 52 times GDP/capita threshold by Woods et al . [49] in order to determine which approaches were cost-effective . The acceptability frontier was also used to check the relative efficiency between the interventions . IMCI approach was cost-effective while rotavirus vaccine + IMCI approach was a more cost-effective approach . IMCI and rotavirus vaccine + IMCI approaches were more efficient than rotavirus vaccine alone in optimizing health care resources allocation and thus rotavirus vaccine alone was deemed dominated . Based on the univariate analysis result , uncertainty surrounding effectiveness of ORS-zinc; cost of rotavirus vaccine and transition probability from well to moderate diarrhoea had the highest effect on the result of the cost-effectiveness analysis . Therefore obtaining more precise information about these most influential parameters would be worthwhile in order to inform the decisions . The IMCI for diarrhoea provides simple and effective methods to manage diarrhoea which is a leading cause of illness and mortality in young children . The implementation guideline of IMCI promotes evidence-based assessment and treatment using syndromic approach that support the rational , effective and affordable use of drugs [14] . The guideline involves checking the child’s nutritional status , certain symptoms like fever , sunken eyes , lethargic or unconscious; teaching parents how to give treatment at home; assessing a child’s feeding and counseling to solve feeding problem; and advising parent when to return to clinic . Basically , this approach is designed for use in outpatient clinical settings with limited diagnostic tools , limited medications and limited knowledge and skills to practice uncomplicated clinical procedures [14] . Since IMCI is a cost-effective approach , payers like NHIS and other health maintenance organisations in Nigeria should ensure the spread of IMCI in health facilities and ensure wide uptake of IMCI by all nursing mothers . As an integrated approach , IMCI will impact positively on other childhood diseases and the general wellbeing of children and thus will be a worthwhile approach to promote . Unfortunately , the awareness and uptake of IMCI in Nigeria is still not optimal [52] . In a study in Ibadan , Nigeria , only 50 . 9% of nurses had a high positive attitude towards the IMCI strategy [52] . There is need to step-up training coverage on IMCI for Nigerian health workers who will educate mothers and caregivers . Radio jingles and television adverts will help facilitate the awareness , knowledge and practice at home . For additional benefit , the inclusion of rotavirus vaccine to the Nigerian national immunization program should be considered since its combination with diarrhoea treatment using IMCI was more cost-effective from our findings . Nigeria is eligible for Global Alliance for Vaccinations and Immunisations ( GAVI ) support and in principle should be able to exploit the low vaccine cost offered by GAVI to procure the vaccine . Unfortunately , GAVI support for Nigeria was suspended due to systemic weaknesses regarding the operation of controls and procedures used to manage GAVI cash-based support [53] . It is of uttermost importance that the National Primary Health Care Development Agency work with urgency to remedy the weaknesses in the operation of controls and procedures used to manage GAVI cash-based support . Our analyses have limitations which are governed by data availability and our assumptions . Certain data used in the model were not specific to Nigeria . Examples include the relative risk ratio of RV1 and some transition probabilities . Though these data were obtained from sub-Saharan Africa’s studies and systematic reviews , they may not represent a true picture for Nigerian scenario . More importantly , for a disease like diarrhoea , the inclusion of outbreaks of other causes of diarrhoea like bacteria ( Clostridium . difficile , E . coli , shigella etc ) , parasites ( giardiasis ) , food allergy etc in addition to rotavirus would have been relevant . This static model will underestimate the indirect benefit of rotavirus vaccine and therefore underestimate its cost-effectiveness [54] . Furthermore , the perspective of our analyses was the payer’s perspective and not the societal . Thus , indirect cost like cost of transportation , extra-nutritional child requirements , cost of diapers which would have been incurred by the mother/caregiver were excluded in our analyses . Taking such cost into consideration would have yielded a more practical cost effectiveness result . Similar to our result , some studies established rotavirus vaccine paired with diarrhea treatment as the most cost-effective option . For instance , a recent study in Ethiopia found that diarrhoea treatment paired with rotavirus vaccine is more cost-effective than diarrhoea treatment alone [55] . Another Tanzanian based study showed that rotavirus vaccine provided as a package with diarrhoea treatment is highly cost-effective compared to the implementation of diarrhoea treatment alone or only providing Rotavirus vaccine [19] . However , the cost of rotavirus vaccine assumed within this analysis was higher compared to other studies . The reason for the difference in cost of vaccine between our study and others is because rotavirus vaccine is currently not subsidized in Nigeria . In conclusion , our model suggests that in the Nigerian context , inclusion of rotavirus vaccination to IMCI for diarrhoea management was the most cost-effective approach to childhood diarrhoea management . IMCI for diarrhoea should be highly advocated in Nigeria since it is cost-effective . Training programs for mothers , antenatal mothers and radio jingles may be necessary to increase practice of IMCI at homes . Nigerian government should consider rotavirus vaccination as part of national programme of immunization as it could provide additional benefit to diarrhoea management . Although our findings suggest that addition of rotavirus vaccine to IMCI for diarrhoea was the most cost-effective approach , there may be need for further vaccine demonstration studies or real life studies to establish the actual cost-effectiveness of the vaccine in Nigeria .
|
‘‘Cost-effectiveness analysis of diarrhoea management approaches in Nigeria: a decision analytical model” was an original research carried out due to the high prevalence and mortality rate due to diarrhoea in Nigeria . The study aims to determine which treatment approach for diarrhoea would be cost-effective for Nigerians to implement due to limited resources available . Rotavirus vaccine plus integrated management of childhood illness for diarrhoea approach ( rotavirus vaccine + IMCI ) was the most cost-effective treatment approach .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"neonatology",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"cost-effectiveness",
"analysis",
"maternal",
"health",
"markov",
"models",
"economic",
"analysis",
"pathogens",
"immunology",
"geographical",
"locations",
"microbiology",
"social",
"sciences",
"reoviruses",
"pediatrics",
"vaccines",
"diarrhea",
"viruses",
"preventive",
"medicine",
"women's",
"health",
"signs",
"and",
"symptoms",
"rna",
"viruses",
"mathematics",
"gastroenterology",
"and",
"hepatology",
"infectious",
"disease",
"control",
"vaccination",
"and",
"immunization",
"africa",
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"rotavirus",
"medical",
"microbiology",
"microbial",
"pathogens",
"economics",
"probability",
"theory",
"nigeria",
"people",
"and",
"places",
"breast",
"feeding",
"diagnostic",
"medicine",
"viral",
"pathogens",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"organisms"
] |
2017
|
Cost-effectiveness analysis of diarrhoea management approaches in Nigeria: A decision analytical model
|
Ubiquitination and deubiquitination are reciprocal processes that tune protein stability , function , and/or localization . The removal of ubiquitin and remodeling of ubiquitin chains is catalyzed by deubiquitinating enzymes ( DUBs ) , which are cysteine proteases or metalloproteases . Although ubiquitination has been extensively studied for decades , the complexity of cellular roles for deubiquitinating enzymes has only recently been explored , and there are still several gaps in our understanding of when , where , and how these enzymes function to modulate the fate of polypeptides . To address these questions we performed a systematic analysis of the 20 Schizosaccharomyces pombe DUBs using confocal microscopy , proteomics , and enzymatic activity assays . Our results reveal that S . pombe DUBs are present in almost all cell compartments , and the majority are part of stable protein complexes essential for their function . Interestingly , DUB partners identified by our study include the homolog of a putative tumor suppressor gene not previously linked to the ubiquitin pathway , and two conserved tryptophan-aspartate ( WD ) repeat proteins that regulate Ubp9 , a DUB that we show participates in endocytosis , actin dynamics , and cell polarity . In order to understand how DUB activity affects these processes we constructed multiple DUB mutants and find that a quintuple deletion of ubp4 ubp5 ubp9 ubp15 sst2/amsh displays severe growth , polarity , and endocytosis defects . This mutant allowed the identification of two common substrates for five cytoplasmic DUBs . Through these studies , a common regulatory theme emerged in which DUB localization and/or activity is modulated by interacting partners . Despite apparently distinct cytoplasmic localization patterns , several DUBs cooperate in regulating endocytosis and cell polarity . These studies provide a framework for dissecting DUB signaling pathways in S . pombe and may shed light on DUB functions in metazoans .
Posttranslational modifications govern protein function by modulating their structure , localization , dynamics , and/or stability . Ubiquitination of substrate proteins induces an array of specific responses depending on the extent and architecture of the modification . Proteins can be modified by addition of a single ubiquitin on a single site ( monoubiquitination ) or multiple sites ( multiple monoubiquitination ) or by polymerization of ubiquitin monomers into chains of specific linkages ( polyubiquitination ) [1] . Specific ubiquitin configurations elicit unique cellular responses and affect essential processes including protein degradation , DNA repair , chromatin remodeling , endocytosis , and cell cycle regulation [1] , [2] . Due to the vital roles of ubiquitination , this process is highly regulated and requires a cascade of three enzymes , culminating in a substrate- and site-specific modification [2] . Likewise , cleavage of ubiquitin moieties or chains by deubiquitinating enzymes ( DUBs ) must be tightly regulated in space and time [3] . DUBs are highly conserved cysteine proteases or metalloproteases that can be classified based on their catalytic domain structure: ubiquitin C-terminal hydrolases ( UCHs ) , ubiquitin-specific proteases ( USPs ) , ovarian tumor proteases ( OTUs ) , Machado-Joseph disease proteases , and JAB1/MPN/Mov34 metalloenzymes ( JAMMs ) [4] . The diversity of DUB catalytic core and domain structures , as well as their number ( approximately 95 DUBs encoded by the human genome ) , reflects their involvement in multiple essential roles including ( 1 ) processing of ubiquitin precursor proteins , ( 2 ) recycling of ubiquitin trapped in modified , inactivatable forms , ( 3 ) cleavage of ubiquitin from target proteins , and ( 4 ) regeneration of monoubiquitin from free polyubiquitin chains [3]–[5] . Specific functions of several DUBs have been elucidated . A trio of DUBs ( Rpn11/PSMD14 , Uch2/UCHL5 , and Ubp6/USP14 ) act at the proteasome to remodel or remove ubiquitin chains prior to substrate degradation [6]–[10] . Other DUBs play roles in transcriptional regulation ( Ubp8p/USP22 ) , downregulation of the NFκB pathway ( CYLD ) , DNA repair ( USP1 ) , or membrane trafficking between the endoplasmic reticulum ( ER ) and the Golgi complex ( Ubp3p ) [11]–[16] . Although a role for DUBs in several pathways has been defined , their enzymatic targets and modes of regulation remain largely unknown [17] . A recent proteomic study of human DUBs assigned potential roles to previously uncharacterized DUBs by placing them in putative cellular contexts defined mainly by the nature of their interactors [18] . However , despite such efforts to link various DUBs to different cellular functions in several organisms , there are still significant gaps in our understanding of the action and regulation of these enzymes . In this study , we characterize the entire family of DUBs in the fission yeast Schizosaccharomyces pombe . In contrast to mammalian cells , the S . pombe genome encodes only 20 putative DUBs belonging to four of the five DUB subfamilies ( UCH , USP , OTU , and JAMM; Figure 1 ) . A handful of other proteins in the S . pombe genome encode DUB domains ( Ubp10 , Ubp13 , Rpn8 , Csn5 , Cwf6 , eIF3f , and eIF3h ) , but they are either lacking the full complement of catalytic residues necessary for protease function ( Figure S1 ) or , in the case of the signalosome component Csn5 , have activity towards other ubiquitin-like proteins and have been excluded from our consideration [4] , [19] , [20] . All S . pombe DUBs are nonessential for viability , except for one of the proteasomal DUBs , Rpn11 [21]–[25] . We chose to study the S . pombe DUB family because of the limited number of DUBs encoded by this genome , the conservation of catalytic core structures and some non-catalytic domain modules ( Figure 1 ) [4] , and the genetic tractability of S . pombe , which allows endogenous gene tagging and simple genetic manipulation . These attributes confer a significant advantage for a genome-wide study and the potential to comprehensively assign DUB activities to functional networks . We took a multifaceted approach to investigate S . pombe DUBs , combining the determination of endogenous localizations , evaluation of their in vitro activity , and proteomic analysis of protein interactions . To our knowledge , this work provides the first systematic localization study of a complete DUB family and reveals that S . pombe DUBs are present in nearly every cellular compartment . Moreover , our proteomic approach identified stable protein–protein interactions for over 55% of the S . pombe DUBs . By means of subcellular localization studies and activity assays we show how three uncharacterized DUBs are regulated by non-catalytic partners , including a potential interactor for human USP7/HAUSP , which controls the tumor suppressor p53 [26] , [27] . We also found that a conserved DUB complex participates in endocytosis , actin organization , and cell polarity and that these cellular functions are shared by at least five different DUBs . The powerful combination of experimental approaches utilized in this study reveals new examples of regulation for this important protein family .
Only a few S . pombe DUBs have been studied in detail , in particular those associated with the 26S proteasome or the COP9 signalosome [21]–[23] , [28] , [29] . With sparse information available for S . pombe DUBs , we reasoned that the localization of these proteins would be a first step in placing each DUB into a functional category . We examined the localization of all 20 putative S . pombe DUBs , endogenously tagged with green fluorescent protein ( GFP ) at their C-termini , as well as the localization of five of these DUBs tagged with GFP at their N-termini ( Figure 2; Table 1 ) . Ubp6 , Ubp8 , Ubp14 , Ubp16 , Rpn11 , and Uch2 are exclusively nuclear ( Figure 2A and 2B ) , while Uch1 , Ubp12 , Ubp15/Ubp21 , Ubp9 , and Otu1 are present both in the nucleus and the cytoplasm ( Figure 2C and 2D ) . Ubp6 , Ubp8 , and Ubp14 are present in the nucleoplasm but excluded from the nucleolus ( Figure 2A ) , whereas Ubp16 localizes exclusively in the nucleolus , where it co-localizes with the nucleolar marker Nog1 [30] ( Figure 3A ) . As shown previously , Rpn11 and Uch2 localize primarily to the nuclear envelope ( Figure 2B ) , where they interact with the proteasome [31] , [32] . The existence of DUBs that localize to both the nucleus and the cytoplasm suggests that shuttling between the two compartments might regulate their activity . Moreover , the abundance of nuclear DUBs ( both in terms of number and apparent concentrations as estimated by GFP intensity ) highlights the importance of deubiquitination activity inside the nucleus , e . g . , for proteasome function , COP9 signalosome function , histone deubiquitination and transcriptional regulation , cell cycle control , ubiquitin homeostasis , and DNA repair . Seven S . pombe DUBs localize to distinct cytoplasmic structures or organelles ( Figure 2D and 2E ) . In addition to localizing to the nucleus , Ubp9 localizes to septa and cell tips ( Figure 2D ) . Ubp4 , Ubp5/Ubp22 , Sst2 , and Ubp15 ( also nuclear ) localize to cytoplasmic spots reminiscent of vesicular structures . Ubp4-positive structures are adjacent to early endocytic sites , labeled with Pan1 , suggesting that these structures are indeed endosomes ( Figure 3B ) [33] . This is consistent with the fact that USP8/UBPY , the mammalian homolog of Ubp4 , interacts with endosomal sorting complex required for transport ( ESCRT ) components on multi-vesicular bodies [34] . Sst2/AMSH is another DUB that interacts with ESCRT components in mammalian cells [35] , [36] . Multi-vesicular body sorting is defective in sst2-null S . pombe cells [22] , [34] , [36] , suggesting that Sst2-positive structures ( Figure 2E ) are also endocytic . In addition , Ubp4 , Sst2 , and Ubp15 , as well as Ubp9 , localize to septa ( Figure 2D and 2E ) , a site of active endocytosis in S . pombe [37] , indicating an important role for deubiquitinating activity during cell division . Co-localization of Ubp5 with Vrg4 , a Golgi protein [38] ( Figure 3C ) , shows that Ubp5 is the first yeast DUB , to our knowledge , detected mainly at Golgi cisternae . Ubp1 ( visualized best with an N-terminal tag ) localizes to the ER ( Figure 2E ) , as shown by its co-localization with Ost1 [39] ( Figure 3E ) , whereas Ubp11 localizes to mitochondria ( Figures 2E and 3F ) . Finally , Ubp2 , Ubp3 , Ubp7 , and Otu2 exhibit a diffuse cytoplasmic localization ( Figure 2F ) ; it is possible that one or more of these DUBs is involved in scavenging ubiquitin that has been trapped in inactivated forms in the cytoplasm ( [3] and references therein ) . The S . pombe DUB localization data indicate that deubiquitination takes place in multiple cellular compartments . To address how DUBs might be targeted to , and regulated at , these discrete subcellular locations , we performed a comprehensive proteomic analysis of these enzymes using endogenously tandem affinity purification ( TAP ) –tagged forms of all 20 S . pombe DUBs . We purified the DUBs using TAP and detected interacting partners by 2D liquid chromatography–tandem mass spectrometry ( LC-MS/MS ) . The DUB-TAP constructs we used were detectable by immunoprecipitation ( IP ) followed by immunoblotting ( Figure 4A ) , except for Ubp7 , which was detected by silver staining and LC-MS/MS after the TAP purification , but does not appear to transfer efficiently to polyvinylidine fluoride membranes under our experimental conditions ( Figure 4E ) . Moreover , 14 of the TAP C-terminal fusion proteins displayed DUB activity towards the DUB artificial substrate ubiquitin 7-amido-4-methylcoumarin ( Ub-AMC; Figure 4B ) or polyubiquitin chains ( Figure 4C ) , showing that DUB activity was not compromised in these cases . For the C-terminal DUB-TAP fusion proteins that did not have detectable in vitro enzymatic activity we constructed N-terminal fusion proteins expressed at low levels under the control of the weak nmt81 promoter . Three of the N-terminal TAP fusion proteins ( Ubp1 , Ubp7 , and Ubp11; Figure 4D ) were able to hydrolyze Ub-AMC ( Figure 4F ) . Thus , we purified them using the N-terminal TAP epitope and included them in our proteomic analysis . Each TAP/LC-MS/MS analysis was performed in duplicate , and the results are summarized in Table S1 . Only proteins detected in both biological replicates are included . In addition , nonspecific proteins ( false-positive interactors ) identified in background runs or in over 50% of other unrelated TAP/LC-MS/MS analyses performed in our laboratory are denoted by gray shading in Table S1 . To confirm the new binding interactions for Ubp4 , Ubp5 , Ubp9 , and Ubp11 , we performed co-IP and reciprocal TAP experiments using the potential DUB interactors as baits . Ubp4 , Ubp5 , and Ubp11 co-immunoprecipitate their partners Sfp47 , Ftp105 , and Tom70 , respectively ( Figure S13A and S13B ) . Ftp105-TAP also co-purified Ubp5 ( Table S2 ) , but the Sfp47-TAP construct was unstable and not useful for confirming an interaction with Ubp4 . Each WD-repeat-containing ( Bun ) protein co-purified with Ubp9 and the other Bun protein in similar amounts ( Tables S1 and S2 ) , suggesting that the Ubp9–Bun62–Bun107 complex is stoichiometric . As expected , Ubp9 , Bun62 , and Bun107 co-immunoprecipitate the other two components of the complex in a wild-type background ( Figure S13D , lanes 1–4 and 6–9 ) . Recent studies indicate that deubiquitinating enzymes can be regulated through their association with non-catalytic protein subunits . For example , S . cerevisiae Ubp6p activity is enhanced upon binding to Rpn1p ( S . pombe Rpn1/Mts4 ) , a proteasomal base subunit [43] . Similarly , UCH37 , the human homolog of S . pombe Uch2 , is activated by Rpn13 , another proteasomal base subunit [45]–[47] . Therefore , we assessed how Ubp4 , Ubp5 , and Ubp9 activities are modulated upon formation of their respective complexes . We first examined whether the binding partners influence DUB localization . For this purpose we deleted the genes coding for Ubp4 , Ubp5 , Ubp9 , or their interactors . The levels of each DUB or interactor in wild-type and null mutants were quantitated on an Odyssey instrument and found not to change by more than 25% in any case ( Figure S14A–S14C ) . Ubp4 and Sfp47 display a punctate localization on vesicular structures ( Figure 7A ) . However , in an sfp47-null mutant Ubp4 localization is diffuse ( Figure 7A ) . In contrast , Sfp47 localization is not affected by ubp4Δ1 deletion ( Figure 7A ) , indicating that Sfp47 recruits Ubp4 to endosomes , but not vice versa . Ubp5 and Ftp105 co-localize on vesicular structures overlapping with Golgi cisternae ( Figures 3C , 3D , and 7B ) . In ftp105-null mutants , Ubp5 localizes diffusely in the nucleus and cytoplasm , but this is not the case for Ftp105 , which localizes independently of Ubp5 ( Figure 7B ) . Thus , similar to Sfp47 , Ftp105 recruits Ubp5 to a specific cell compartment . Ubp9 and Bun62 localize to the nucleus , septa , and cell tips , while Bun107 localizes to septa and cell tips but is excluded from nuclei at steady state ( Figure 7C ) . Ubp9 and Bun62 localization depends on Bun107 , because in bun107-null mutant cells Ubp9 and Bun62 are predominantly nuclear ( Figure 7C ) . Conversely , Ubp9 controls the localization of the other two components , which localize diffusely in the cytoplasm in ubp9-null cells ( Figure 7C ) , even though their abundance is not significantly altered ( Figure S14C ) . Thus , the localization of the Ubp9–Bun62 module and Bun107 is interdependent . These localization data are consistent with biochemical analysis of the Ubp9 complex . Bun107 is not required for the Ubp9–Bun62 interaction as this sub-complex is still detected in a bun107-null mutant background . However , in bun62- or ubp9-null mutants the Ubp9–Bun107 and Bun62–Bun107 interactions , respectively , are disrupted ( Figure S13D , lanes 5 and 10 ) . These findings indicate that Ubp9 and Bun62 most likely form a pre-complex essential for the association with Bun107 and for cytoplasmic retention . Of note , the localization of Ubp9 , Bun62 , and Bun107 is regulated by Crm1-mediated nuclear export , since all three components are predominantly nuclear after leptomycin B treatment ( data not shown ) . This suggests that even Bun107 , the cytoplasmic anchor of the ternary complex , is shuttling between nucleus and cytoplasm , although its dynamic equilibrium is largely shifted towards the cytoplasm under physiological conditions . Moreover , we found that in wild-type cells , Ubp9 is phosphorylated , accounting for its variable SDS-PAGE mobility ( Figure S14D ) , but this modification is lost in bun62- or bun107-null mutants ( Figure S14C , lanes 1–4 ) . Next , we determined if the enzymatic activities of Ubp4 , Ubp5 , and Ubp9 are regulated by their interacting partners using the artificial substrate Ub-AMC . All of the above enzymes display DUB activity towards Ub-AMC ( Figures 4 and 8 ) , but their activity is affected differently by their interactors . Namely , Ubp5 activity is not significantly altered in ftp105-null cells , signifying that Ftp105 functions in recruitment of Ubp5 to the Golgi but not in its activation ( Figure 8B ) . On the other hand , Ubp4 activity is enhanced in the absence of Sfp47 ( Figure 8A ) , suggesting that Sfp47 recruits Ubp4 to endosomes where either Sfp47 itself or some other factor functions as an inhibitor . In contrast , Ubp9 is active only when in complex with both interactors ( Figure 8C ) , demonstrating that the Ubp9–Bun62–Bun107 complex is required not only for Ubp9 recruitment to septa and cell tips but also for its enzymatic activity at these specific locations . A model of the dynamic localization of the Ubp9 DUB complex is presented in Figure 8D . The presence of Ubp9–Bun62–Bun107 at septa and cell tips suggests that this complex might be involved in endocytosis . To test this hypothesis we examined genetic interactions between ubp9 and end4/sla2 , myo1 , and wsp1 , which all have roles in cortical actin organization and endocytosis , two processes known to be interrelated in yeast cells [61]–[63] . Indeed , we observed that ubp9Δ end4/sla2Δ double-deletion mutant grows slower than the end4/sla2Δ simple mutant ( Figure S15A ) . Moreover , ubp9Δ wsp1Δ and ubp9Δ myo1Δ double mutations are lethal at 36° C . Wsp1 and Myo1 activate the Arp2/3 complex , a known actin nucleator [63] . When actin polymerization is inhibited by Latrunculin B , the growth of ubp9Δ wsp1Δ and ubp9Δ myo1Δ double mutants is severely affected compared to single mutants ( Figure S15B ) . FM4-64 internalization is decreased in ubp9Δ myo1Δ double-mutant cells as compared to the single mutants ( Figure S15C and data not shown ) . Interestingly , ubp9Δ myo1Δ cells have prominent polarity defects , as shown by their aberrant cell shapes ( Figure S15C ) . Together , these data show that Ubp9 is involved in regulating actin dynamics and/or endocytosis at cell tips and septa . Although ubp9Δ myo1Δ , ubp9Δ wsp1Δ , ubp9Δ sla2Δ double-mutant cells display clear endocytosis and/or polarity defects ( Figure S15 ) , the ubp9Δ single mutant ( Figure S15A ) and the ubp9Δ bun62Δ bun107Δ triple mutant ( data not shown ) do not have growth defects . This is very likely due to a high degree of redundancy among the DUBs [64] , and suggests that elucidating the role of any DUB might only be possible in a genetic context where many redundant DUB activities are “silenced . ” Therefore , we set out to delete multiple DUBs that localize to vesicular structures and might be expected to have overlapping functions . The largest multiple mutant tested was the quintuple deletion ubp4Δ1 ubp5Δ ubp9Δ ubp15Δ sst2Δ . This strain displayed severe growth defects both at high and low temperatures ( Figure 9A ) . It also displayed endocytosis and polarity defects , as shown by the decreased rate and number of ectopic sites of FM4-64 internalization , the small size of endosomal structures , and the aberrant cell shape ( Figure 9B ) . Interestingly , the loss of all five DUB activities contributes to the severe growth phenotype , as none of the quadruple or triple mutant combinations was as defective as the quintuple mutant ( Figure S16A and S16B ) . For example , the ubp4Δ1 ubp5Δ ubp15Δ sst2Δ strain does not display growth or endocytosis deficiencies ( Figures 9B and S16A ) , suggesting that deletion of ubp9 contributes significantly to the severe phenotype of the quintuple mutant . To determine whether the growth and polarity defects correlated with increased ubiquitination of target proteins , cell lysates were produced under fully denaturing conditions and blotted for ubiquitin . There were increases in ubiquitinated proteins in triple- and quadruple-deletion mutants ( Figure S16C ) , but the level of ubiquitinated proteins in ubp4Δ1 ubp5Δ ubp9Δ ubp15Δ sst2Δ cells was 20-fold increased compared to that in control cells ( Figure 9C ) . It has been well established that endocytic pathways are regulated by ubiquitination . Some targets of this modification include transmembrane nutrient receptors and regulators of the endocytic machinery [65] . Therefore , we tested whether the arginine transporter Can1 and the E3 ligase Pub1 ( the ortholog of S . cerevisae Rsp5p ) are similarly regulated by ubiquitination and whether their ubiquitination status is different in the ubp4Δ1 ubp5Δ ubp9Δ ubp15Δ sst2Δ mutant . Our in vivo ubiquitination assays using Histidine6-Biotin-Histidine6 ( HBH ) C-terminally tagged proteins show that polyubiquitinated Can1 levels are significantly increased in the quintuple mutant ( Figure 9D ) . Pub1 is monoubiquitinated to the same extent in wild-type and ubp4Δ1 ubp5Δ ubp9Δ ubp15Δ sst2Δ cells , however , its polyubiquitination is 2 . 5-fold increased in the quintuple mutant ( Figure 9D ) . Together , these results indicate that S . pombe Ubp4 , Ubp5 , Ubp9 , Ubp15 , and Sst2 DUBs contribute to the deubiquitination of both cargo and regulatory molecules during endocytosis .
Our GFP localization data show that deubiquitination takes place in almost every cell compartment . More than 50% of the S . pombe DUBs , including the most abundant ones , localize to different compartments of the nucleus , whereas 35% localize to specific cytoplasmic structures ( Figures 2A–2E and 3; Table 1 ) . Almost 50% of the nuclear DUBs reside in the cytoplasm as well , suggesting that their transport to and from the nucleus might be regulated ( Figure 2C and 2D ) . Nucleo-cytoplasmic shuttling of the mammalian DUB USP4 has been described [68] , and it has also been shown that a subdomain within the USP domain of the DUB CYLD is necessary for its localization in the cytoplasm [69] . However , a role for interacting partners in regulating the nucleo-cytoplasmic transport of these proteins has not been reported . We have demonstrated that anchoring of Ubp5 to the Golgi and Ubp9 to cell tips/septa is mediated by their partners , Ftp105 and Bun107 , respectively ( Figure 7 ) . These results define a mechanism for DUB cytoplasmic retention by interacting partners . We also examined the localization of DUBs during the cell cycle using cells arrested in prometaphase via the nda3-KM311 ( β-tubulin ) mutation or in S-phase after addition of hydroxyurea , a chemical agent that indirectly induces DNA damage . We did not observe any significant change in DUB localization ( data not shown ) , suggesting that their recruitment to various cellular compartments , and especially their nucleo-cytoplasmic transport , is not strongly affected under these conditions . Exploration of several protein–protein interactions reported in this study have revealed new examples of DUB regulation . Ubp4 interacts with Sfp47 , an SH3-domain-containing protein that is required for its localization to vesicular structures ( Figures 6 and 7A ) . This finding is of particular interest , because Ubp4 homologs in S . cerevisiae and H . sapiens , Doa4p and USP8/UBPY , respectively , use very different endosomal “recruitment strategies . ” The Doa4p N-terminus contains four conserved motifs that are required for its localization to endosomes , and its recruitment is mediated by its co-factor Bro1p , a component of the multi-vesicular body sorting machinery , which may also activate Doa4p [70] , [71] . In contrast , Ubp4 enzymatic activity is reduced when targeted to endosomes by Sfp47 , suggesting that some Ubp4 inhibitor analogous to Rfu1p , the Doa4p inhibitor in S . cerevisiae , might be present on this compartment ( Figure 8A ) [72] . On the other hand , human USP8 recruitment to the endosomes is dependent on its N-terminal MIT ( microtubule interacting and transport ) domain that associates with components of the ESCRT [73] . S . pombe Ubp4 does not have an extended non-catalytic N-terminus like Doa4p and USP8; however , it possesses a PXXP motif , which could mediate association with the Sfp47 SH3 domain ( Figure S17 ) . These results suggest that at least three independent mechanisms of DUB recruitment to endosomes have emerged during eukaryotic evolution , highlighting the importance of regulated deubiquitination in this compartment . Another example of DUB regulation by localization is the recruitment of Ubp5 to the Golgi by Ftp105 . Ftp105 contains five or six putative transmembrane helices ( http://www . ch . embnet . org/software/TMPRED_form . html ) . To our knowledge , this is the first observation of a DUB being recruited to a compartment via interaction with a potential integral membrane protein . Ftp105 has a clear human homolog , C17orf28 , “down-regulated in multiple cancers , ” which is a putative tumor suppressor [26] ( Figure S18 ) . ftp105 deletion results in Ubp5 mislocalization to the cytoplasm and the nucleus without affecting its activity . It would be interesting to explore whether other proteins containing domains of the dymeclin superfamily ( PFAM 09742 ) have similar roles in other organisms , especially if they sequester DUBs by recruitment to specific structures , preventing them from functioning elsewhere . It is intriguing to note that Ubp5′s human ortholog , USP7/HAUSP , is a DUB regulating p53 and MDM2 stability and PTEN localization , as these proteins are associated with tumorigenesis and cancer progression [27] , [74] , [75] . Similar to Ubp5 , the shuttling of Ubp9 between the nucleus and the cytoplasm and its anchoring at cell tips and septa are regulated by interaction with its WD repeat partners ( Figure 7C ) . In contrast to Ubp5 , the enzymatic activity of Ubp9 depends on its interaction with both partners ( Figure 8C ) , indicating that Ubp9 is not functional in the nucleus and may be sequestered there . Ubp9 has clear orthologs in budding yeast ( Ubp9 and Ubp13 ) and humans ( USP12 and USP46 ) that interact with WD repeat proteins [18] , [76]–[79] . Moreover , the human ortholog of Bun107 activates USP12 and USP46 [78] . Interaction of DUBs with WD repeat proteins is an intriguing new concept , as suggested by their abundance in human cells [18] . Ubp9 is intimately linked to the interrelated processes of cortical actin organization , endocytosis , and cell polarity in S . pombe , and it will be exciting to determine whether this mode of regulation and function is conserved in the S . cerevisiae and H . sapiens Ubp9 complexes . Although multiple negative genetic interactions suggest that Ubp9 is involved in actin dynamics , endocytosis , and cell polarity , the ubp9Δ single mutant and the ubp9Δ bun107Δ bun62Δ triple mutant do not show any phenotypic abnormalities . This result is not surprising in the light of work done in S . cerevisiae that has shown that deletion of single or multiple DUBs results in only a mild or no growth phenotype [64] . Given the substantial functional overlap among these enzymes , it is obvious that exploring DUB function in yeast requires combination of multiple mutations . For that purpose we generated multiple mutants of DUBs residing on vesicular structures and revealed that five of these enzymes share a common function in maintaining cell polarity and endocytosis efficiency ( Figure 9B ) . This approach allowed us to identify two endocytosis-related substrates of these enzymes and could be a powerful tool for the discovery of several other deubiquitination targets , especially ones involved in actin dynamics and cell polarity . Recently , Sowa et al . reported a proteomic analysis of approximately 80% of putative human DUBs [18] . The putative human DUBs were overexpressed as N-terminal Flag-HA fusion proteins and purified by anti-HA IP , and proteins were detected using LC-MS/MS . Sixteen of the 20 S . pombe DUBs are conserved in H . sapiens and seven of the 16 appear to be involved in the same protein complexes in both organisms ( Ubp3 , Ubp8 , Ubp9 , Ubp6 , Rpn11 , Uch2 , and Otu1 ) ( Figures 5 , 6 , and S3–S5; Tables 1 and S1; [18] ) . Moreover , TAP-LC-MS/MS analysis of proteins containing nonfunctional or non-ubiquitin-specific DUB domains ( Ubp10 , Rpn8 , eIF3f , and Csn5 ) shows that the human interaction networks are conserved in S . pombe ( data not shown; [18] ) . However , the two datasets contain some important differences , namely: ( 1 ) USP4 and USP15 , the human orthologs of Ubp12 , seem to be part of a pre-mRNA processing module in human cells , but no such interaction is detected in S . pombe; ( 2 ) USP7 , the human ortholog of Ubp5 and Ubp15 , interacts with DNA damage modules in human cells , whereas S . pombe Ubp5 and Ubp15 are involved in membrane trafficking/polarity control , and Ubp5 is targeted to the Golgi by its partner Ftp105; ( 3 ) S . pombe Ubp4 interacts with an SH3 domain protein ( Figures 6 and S13A ) , as does its human ortholog , USP8 [34] , but Sowa et al . did not detect this interaction . Additionally , there were several E3 ligases detected in the human dataset , whereas only three were identified in our study ( Ubp11 purification; Table S1 ) . This might reflect some evolutionary divergence between human and S . pombe DUBs and/or may result from the many technical and analytical differences between the two studies . Finally , neither study was able to detect DUB substrates , likely because of the transient , dynamic nature of enzyme–substrate interactions . Our genome-wide screen of S . pombe deubiquitinating enzymes allowed the detailed description of their subcellular localization , the identification of previously uncharacterized S . pombe protein complexes essential for DUB function , and the establishment of these family members as bona fide deubiquitinating enzymes . This combination of experimental approaches provides new insight into how the activity of deubiquitinating enzymes is finely tuned by non-catalytic partners . Some of the protein–protein interactions described here are conserved between S . pombe , S . cerevisae , and mammalian cells . This suggests that the modes of regulation and function assigned to these enzymes are likely valid in other organisms and highlights the usefulness of combined approaches and simple systems to understand complex biological phenomena .
Yeast strains ( Table S3 ) were grown in yeast extract ( YE ) medium . For expression of N-terminally tagged proteins , strains were transformed with pREP expression vectors , containing a thiamine-repressible promoter , using a standard sorbitol transformation procedure [80] . Transformed strains were first grown on minimal medium containing thiamine to suppress expression . To induce expression , cells were grown in liquid minimal medium lacking thiamine for 18h [81] . Cell cultures used for TAP purifications were grown in 2 l of 4× YE medium ( C-terminally TAP-tagged proteins ) or in 8 l of EMM supplemented with the appropriate nutrients ( N-terminally TAP-tagged proteins ) . For in vivo ubiquitination assays , strains were grown in 100 ml of 4× YE medium . All 20 DUBs and bun62 , bun107 , ftp105 , sfp47 , pob1 , pan1 , tom70 , can1 , and pub1 were tagged endogenously at the 3′ end with GFP , TAP , FLAG3 , V5 , mCherry , HBH , linker-TAP , or linker-GFP , as previously described [82] . The linker sequence in the linker-TAP and linker-GFP tag cassettes translates to ILGAPSGGGATAGAGGAGGPAGLI [83] . DNA coding for Ubp1 , Ubp7 , Ubp11 , Otu1 , or Otu2 was amplified by PCR from genomic S . pombe DNA . The PCR products were digested with the appropriate restriction enzymes ( SalI/BamHI for Ubp1 , NdeI/XmaI for Ubp7 , Ubp11 , and Otu2 , and XmaI for Otu1 ) , sublconed into pREP81-TAP and pREP81-GFP vectors , and verified by sequencing . Disruption of genes ( ubp4 , sfp47 , ubp5 , ftp105 , ubp9 , bun107 , bun62 , and sst2 ) was achieved by PCR-based one-step homologous recombination [82] , targeting the entire open reading frames . In the case of ubp4Δ1 , however , only the sequence corresponding to amino acids 156–593 was removed because of the presence of previously undetected 5′ exons . These genes were targeted for deletion using ura4+ as the selectable marker , stable integrants were selected , and the deletions were confirmed by PCR . A lithium acetate method was used for yeast cell transformations [84] . For gene replacement at the endogenous locus , the entire ORF plus at least 500 bp of 5′ and 3′ flanking nucleotides was sub-cloned into the pIRT2 vector containing the leu2+ marker , and the mutations were inserted by site-directed mutagenesis and sequenced . Haploid strains ( ubp4::ura4 , ubp5::ura4 or ubp9::ura4 ) were transformed with pIRT2-ubp4 ( C236S ) , pIRT2-ubp5 ( C222S ) , or pIRT2-ubp9 ( C50S ) , stable integrants were selected by resistance to 5-Fluoroorotic acid ( 5-FOA ) , and the integrations were confirmed by PCR . Strain construction and tetrad analysis were accomplished through standard methods . Cell pellets were frozen in a dry ice/ethanol bath and lysed by bead disruption in NP-40 lysis buffer under either native ( Figures 4 , 8 , and S13 ) or denaturing ( Figures 8D and S14A–S14C ) conditions as previously described [85] , except with the addition of 0 . 1 mM diisopropyl fluorophosphate ( Sigma-Aldrich ) . Proteins were immunoprecipitated by anti-GFP ( Roche ) , anti-V5 ( Invitrogen ) , and anti-FLAG ( M2; Sigma-Aldrich ) antibodies and Protein G Sepharose beads ( GE Healthcare ) or IgG Sepharose beads ( GE Healthcare ) . Immunoblot analysis was performed as previously described [86] , except that secondary antibodies were conjugated to Alexa Fluor 680 ( Invitrogen ) and visualized using an Odyssey Infrared Imaging System ( LI-COR Biosciences ) . For in vivo ubiquitination assays ( Figure 9D ) can1 and pub1 were tagged at their endogenous C-termini with an HBH affinity tag . Tagged proteins were purified using a modified version of the two-step tandem affinity purification under fully denatured conditions [87] . For each strain , cell pellets were lysed by bead disruption into Buffer 1 ( 8 M Urea , 300 mM NaCl , 50 mM NaPO4 , 0 . 5% NP40 , and 4 mM Imidazole [pH 8] ) and incubated with Ni-NTA agarose beads ( Qiagen ) for 4 h at room temperature . After incubation , beads were washed 4× with Buffer 3 ( 8 M Urea , 30 0mM NaCl , 50 mM NaPO4 , 0 . 5% NP40 , and 20 mM Imidazole [pH 6 . 3] ) and eluted in Buffer 4 ( 8 M Urea , 200 mM NaCl , 50 mM NaPO4 , 0 . 5% NP40 , 2% SDS , 100 mM Tris , and 10 mM EDTA [pH 4 . 3] ) . The pH of the eluate was adjusted to 8 before adding streptavidin ultra-link resin ( Pierce ) and incubating overnight at room temperature . After the second incubation , streptavidin beads were washed 4× with Buffer 6 ( 8 M Urea , 200 mM NaCl , 2% SDS , and 100 mM Tris [pH 8] ) and 1× with Buffer 7 ( 8 M Urea , 200 mM NaCl , and 100 mM Tris [pH 8] ) . Purified proteins were detected by immunoblotting using a ubiquitin anti-serum ( Sigma ) and fluorescently labeled streptavidin ( LI-COR Biosciences ) . For comparison of ubiquitinated protein levels ( Figures 9C and S16C ) , 40 OD cell pellets were lysed by bead disruption into Buffer 1 ( 8 M Urea , 300 mM NaCl , 50 mM NaPO4 , 0 . 5% NP40 , and 4 mM Imidazole [pH 8] ) , and lysates were analyzed by immunoblotting ( polyclonal anti-ubiquitin antibody , Sigma ) and Coomassie blue staining to normalize for protein quantities . Protein quantification ( ubiquitinated species as measured by anti-ubiquitin immunoblot/total protein as measured by Coomassie staining ) was performed using the Odyssey v3 . 0 software . For phosphatase collapse ( Figure S14D ) , immunoprecipitated Ubp9-TAP was incubated with lambda phosphatase ( New England Biolabs ) in 25 mM HEPES-NaOH ( pH 7 . 4 ) , 150 mM NaCl , and 1 mM MnCl2 for 30 min at 30°C . For DUB activity assays , cell pellets were lysed under native conditions as described above with some differences: NaCl concentration was increased to 300 mM in the NP-40 lysis buffer and TAP-tagged proteins were immunoprecipitated by tosylactivated Dynabeads ( Invitrogen ) coated with rabbit IgG ( MP Biomedicals ) . Immunoprecipitates were washed 3× in lysis buffer and 3× in DUB assay buffer ( see next section for DUB assay buffer composition ) . For TAPs , cells were lysed under native conditions and proteins were purified as described previously [88] . After purification , DUBs were TCA precipitated and resuspended in 8 M Urea , 50 mM Tris ( pH 8 ) , reduced with Tris ( 2-caroxyethyl phosphine ) , alkylated with iodoacetamide , and digested overnight at 37°C with Trypsin Gold ( Promega ) after diluting to 2 M urea with 50 mM Tris ( pH 8 ) . MS was performed as previously described [89] with the following modifications . Peptides were loaded onto columns with a pressure cell and were separated and analyzed by three-phase multidimensional protein identification technology on a linear trap quadrupole instrument ( Thermo Electron ) . An autosampler ( FAMOS ) was used for 12 salt elution steps , each with 2 µl of ammonium acetate . Each injection was followed by elution of peptides with a 0%–40% acetonitrile gradient except the first and last injections , in which a 0%–90% acetonitrile gradient was used . Eluted ions were analyzed by one full precursor MS scan ( 400–2 , 000 mass-to-charge ratio ) and four tandem MS scans of the most abundant ions detected in the precursor MS scan under dynamic exclusion . Centroided peak lists for MS2 spectra were extracted from THERMO RAW files using Scansifter v . 2 . 1 . 1 ( software developed in-house by Vanderbilt University Medical Center ) and converted to DTA files . Spectra with less than six peaks were excluded from our analysis . If 90% or less of spectral intensity of a tandem mass spectrum was detected at m/z values lower than the precursor ion , then the precursor ion was assumed to be +1 . All other spectra were processed using precursor charge states of +2 and +3 . Protein identification was performed with the SEQUEST algorithm [90] ( v . 27 , rev . 12 ) on a high-performance computing cluster ( Advanced Computing Center for Research & Education at Vanderbilt University ) using the GeneDB/Sanger Institute S . pombe protein database , created October 2009 . Contaminant proteins ( e . g . , keratin and IgG; 73 total ) were added , and all database sequences were reversed and concatenated to allow estimation of FDRs ( total of 10 , 186 entries ) . SEQUEST parameters were as follows: strict tryptic cleavage , maximum of ten missed cleavage sites , maximum of four amino acid modifications per peptide , allowed modification of cysteine ( +57 . 05 for carboxamidomethylation ) and methionine ( +16 for oxidation ) , the average mass of precursor ions was required to fall within a 1 . 25-m/z window , and fragment ions were required to fall within 0 . 5 m/z of their monoisotopic masses . SEQUEST out files were converted to pepXML files by SQter ( spectral data SEQUEST search results ) [91] for analysis in IDPicker 2 . 4 . 0 [92] , [93] using the following filters: maximum FDR per result , 0 . 01; maximum ambiguous IDs per result , 2; minimum peptide length per result , 5; minimum distinct peptides per protein , 5; minimum additional peptides per protein group , 2; indistinct modifications , M 15 . 994 C 57 . 05 . Parsimony rules were applied to generate a minimal list of proteins to explain all of the peptides that passed our entry criteria . No reversed proteins passed our criteria so that zero proteins were estimated to be falsely identified in this list , i . e . , a 0% FDR . Duplicate DUB and negative control purifications ( no TAP tag for C-terminal or empty pREP81-TAP for N-terminal ) were processed as described above . Cross-species contaminant proteins ( e . g . , keratin ) have been removed from all protein ID lists . In addition , only proteins identified in both biological replicates are included in the protein ID table ( Table S1 ) . Gray-shaded rows denote proteins identified in the negative controls or in over 50% of other unrelated TAP/LC-MS/MS analyses performed in our laboratory . Blue-shaded rows indicate proteins identified in over 50% of all the DUB purifications and , in the case of the N-terminal TAPs , proteins identified in all six N-terminal TAP purifications . This method of background estimation is likely conservative because at least two proteins identified with low spectral counts as “background” are also identified as interactors with high relative abundance to bait ( Nxt3 , Ubp3′s partner , and Rpt6 , a proteasomal component ) ; when Nxt3 and Rpt6 are present at high relative abundance to bait , they are shaded orange in Table S1 to denote this distinction . Yellow-highlighted rows indicate proteins that interacted with the bait ( denoted by bold ) that have been validated by co-IP and/or reciprocal TAP or reported in the literature for S . pombe DUBs or their homologs . We analyzed the networks of proteins identified in each of the duplicate DUB TAP/LC-MS/MS analyses ( excluding background , unshaded rows in Table S1 ) using the Schizosaccharomyces_pombe BioGRID database v3 . 0 . 65 [94] and generating network diagrams using Cytoscape v2 . 7 . 0 [95] . Interactions between each protein identified in the DUB TAP/LC-MS/MS analyses were queried using the BioGRID Plugin 2 . 0 for physical interactions ( 4 , 007 total interactions in BioGRID for S . pombe ) in Cytoscape . We merged the BioGRID interactions with our TAP/LC-MS/MS data to generate Figures 5 , 6 , and S3–S11 . The edge widths of protein interactions identified by TAP/LC-MS/MS in Figures 5 and 6 are coded according to the TSC . The top MS hits ( TSC ) /validated partners ( our study ) and interactors reported in the literature for DUB homologs are highlighted in yellow and placed close to the DUB to mark this distinction . In vitro enzymatic assays with 1 µM Ub-AMC ( Boston Biochem ) were performed using the DUB-TAP IPs ( left on dynabeads ) in 50 µl of reaction buffer ( 20 mM HEPES-KOH [pH 7 . 8] , 20 mM NaCl , 0 . 1 mg/ml BSA [Sigma-Aldrich] , 0 . 5 mM EDTA , and 10 mM DTT ) at 32°C for 15 min ( Figure 4B ) , 50 min ( Figure 4F ) , or the indicated times ( Figure 8 ) . Fluorescence was monitored in a Molecular Devices FlexStation 3 fluorometer after dynabeads were removed . Fluorescence corresponding to a control reaction ( reaction mixture containing immunoprecipitate from untagged cells ) was subtracted ( Figure 4 ) . For the analysis of Ub-AMC hydrolysis kinetics , the control reaction used for background fluorescence subtraction contained immunoprecipitate from strains encoding catalytically inactive DUBs ( Ubp4 C236S , Ubp5 C222S , or Ubp9 C50S; Figure 8 ) . To compare the enzymatic activities of Ubp4 , Ubp5 , and Ubp9 in different genetic backgrounds , the immunoprecipitates were analyzed by immunoblotting , and the proteins were quantified using the Odyssey v3 . 0 software , and fluorescence measurements ( enzyme activity ) were corrected for protein amount . In vitro enzymatic assays with polyubiquitin ( Ub1–7 ) chains ( Boston Biochem ) were performed using the DUB-TAP IPs ( left on dynabeads ) in 20 µl of reaction buffer at 32°C for 4 h . K63-linked polyubiquitin ( Ub1–7 ) chains ( Sst2 DUB assay ) ( 50 ng ) were added to 20 µl of reaction buffer ( 50 mM Tris-HCl [pH 7 . 4] , 25 mM KCl , 5 mM MgCl2 , and 10 mM DTT ) . K48-linked or K63-linked polyubiquitin ( Ub1–7 ) chains ( Ubp14 DUB assay ) ( 25 ng ) were added to 20 µl of reaction buffer ( 50 mM Tris-HCl [pH 7 . 8] , 25 mM KCl , 5 mM MgCl2 , and 10 mM DTT ) . Reaction mixtures containing immunoprecipitate from untagged cells were used as negative controls . The reactions were stopped by addition of SDS sample buffer . Ubiquitin chains and monomers were analyzed by immunoblotting after dynabead removal , as described above . Cells were grown to mid-log phase and imaged live at 25°C using a spinning disk confocal microscope ( Ultraview LCI; PerkinElmer ) with a 100× NA 1 . 40 Plan-Apochromat oil-immersion objective and a 488-nm argon ion laser ( GFP ) or a 594-nm helium neon laser ( mCherry , FM4-64 , MitoTracker Red ) . Images were captured on a charge-coupled device camera ( Orca-ER; Hamamatsu Photonics ) and processed using Metamorph 7 . 1 software ( MDS Analytical Technologies ) . Z-section slices were 0 . 5 µm . Visualization of endocytosis with FM4-64 was essentially as described [96] . Briefly , cells were grown in YE medium to an optical density ( OD600 ) of 0 . 5 , harvested by centrifugation , resuspended at OD595 3–5 and placed on ice for 10 min . FM4-64 stock solution ( 1 . 63 mM in DMSO; Molecular Probes ) was added to 400 µl of cold cells to a final concentration of 8 . 15 µM . A small sample of cells was immediately transferred to a microscope slide at room temperature and imaged by confocal microscopy as described above . Visualization of mitochondria was performed as in Jourdain et al . [97] . Briefly , MitoTracker Red CMXRos ( Molecular Probes ) was dissolved in DMSO at a concentration of 1 mM and diluted in minimal medium to 1 µM . Mid-log phase cells were incubated with MitoTracker Red ( final concentration 100 nM ) for 30 min . Cells were washed 3× in minimal medium , before being transferred to a microscope slide and imaged by confocal microscopy as described above . Sequence alignments were performed using the Multalin software ( http://bioinfo . genopole-toulouse . prd . fr/multalin/multalin . html ) [98] . The GeneDB ( http://old . genedb . org/genedb/pombe/ ) accession numbers for the previously unnamed proteins discussed in this paper are Bun107 , SPAC31A2 . 14; Bun62 , SPAC12B10 . 03 , Ecm29 , SPAC1782 . 01; Ftp105 , SPAC17A5 . 16; Rpn1301 , SPBC342 . 04; Rpn1302 , SPCC16A11 . 16c; and Sfp47 , SPAC7D4 . 02c . All the DUB UniProt accession numbers are provided in Table 1 , and all DUB and interactor GeneDB accession numbers are provided in Table S1 .
|
The post-translational modification of proteins by conjugation of monomers or chains of ubiquitin is a regulatory mechanism for tuning protein stability , localization and function . Given these vital functions , ubiquitination has to be highly regulated so that protein degradation and cell signaling are controlled in space and time . Although the ubiquitin-conjugation machinery has been thoroughly studied , there are still several gaps in our understanding of when , where and how ubiquitin is removed by deubiquitinating enzymes ( DUBs ) . To address these questions we performed a systematic analysis of the 20 DUBs in the fission yeast Schizosaccharomyces pombe using confocal microscopy , proteomics and enzymatic activity assays . We first showed that S . pombe DUBs are present in almost all cell compartments and that the majority are part of stable protein complexes essential for their function . Then , we constructed strains mutant for a number of the DUBs involved in the newly identified protein complexes and showed that five cytoplasmic DUBs have redundant roles in controlling endocytosis and cell polarity . We postulate that regulatory networks identified in our study might be conserved and hence shed light on DUB function in metazoans .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry/cell",
"signaling",
"and",
"trafficking",
"structures",
"cell",
"biology"
] |
2010
|
A Global Census of Fission Yeast Deubiquitinating Enzyme Localization and Interaction Networks Reveals Distinct Compartmentalization Profiles and Overlapping Functions in Endocytosis and Polarity
|
Fluoroquinolones are the most commonly used group of antimicrobials for the treatment of enteric fever , but no direct comparison between two fluoroquinolones has been performed in a large randomised trial . An open-label randomized trial was conducted to investigate whether gatifloxacin is more effective than ofloxacin in the treatment of uncomplicated enteric fever caused by nalidixic acid-resistant Salmonella enterica serovars Typhi and Paratyphi A . Adults and children clinically diagnosed with uncomplicated enteric fever were enrolled in the study to receive gatifloxacin ( 10 mg/kg/day ) in a single dose or ofloxacin ( 20 mg/kg/day ) in two divided doses for 7 days . Patients were followed for six months . The primary outcome was treatment failure in patients infected with nalidixic acid resistant isolates . 627 patients with a median age of 17 ( IQR 9–23 ) years were randomised . Of the 218 patients with culture confirmed enteric fever , 170 patients were infected with nalidixic acid-resistant isolates . In the ofloxacin group , 6 out of 83 patients had treatment failure compared to 5 out of 87 in the gatifloxacin group ( hazard ratio [HR] of time to failure 0 . 81 , 95% CI 0 . 25 to 2 . 65 , p = 0 . 73 ) . The median time to fever clearance was 4 . 70 days ( IQR 2 . 98–5 . 90 ) in the ofloxacin group versus 3 . 31 days ( IQR 2 . 29–4 . 75 ) in the gatifloxacin group ( HR = 1 . 59 , 95% CI 1 . 16 to 2 . 18 , p = 0 . 004 ) . The results in all blood culture-confirmed patients and all randomized patients were comparable . Gatifloxacin was not superior to ofloxacin in preventing failure , but use of gatifloxacin did result in more prompt fever clearance time compared to ofloxacin . Trial registration: ISRCTN 63006567 ( www . controlled-trials . com ) .
Enteric fever is endemic in Nepal and many other developing countries [1] , [2] , [3] . In industrialised countries , it is usually a disease imported by returning travellers [4] , most frequently from South Asia [5] . Enteric fever is a systemic infection caused by Salmonella enterica serovars Typhi ( S . Typhi ) and Paratyphi A ( S . Paratyphi A ) [6] . For the treatment of uncomplicated enteric fever , the WHO recommends fluoroquinolones for fully sensitive and multidrug resistant ( MDR , resistance to chloramphenicol , ampicillin and trimethoprim-sulfamethoxazole ) isolates [7] . However , the widespread use of fluoroquinolones for enteric fever has been followed by the emergence of S . Typhi and S . Paratyphi A isolates with reduced susceptibility to ciprofloxacin ( minimum inhibitory concentration ( MIC ) ≥0 . 125 µg/mL ) and ofloxacin ( MIC≥0 . 25 µg/mL ) across Asia [8] , [9] and parts of Africa [10] , [11] . These strains can be identified by high level resistance to nalidixic acid and are associated with specific point mutations in gyrA ( DNA gyrase ) gene , and occasionally the parC ( topoisomerase IV ) gene [12] , [13] [8] . Despite these findings , ofloxacin continues to be the standard of care in health facilities in many parts of South and Southeast Asia for the treatment of uncomplicated enteric fever [14] , [15] , [16] . Gatifloxacin is an 8-methoxyfluoroquinolone which targets both GyrA and topoisomerase IV and hence is less inhibited by the common mutations of the gyrA gene of S typhi than are ciprofloxacin and ofloxacin . [17] . In addition , gatifloxacin had the lowest MICs against nalidixic acid-resistant strains of S . Typhi and S . Paratyphi A in comparison to other fluroquionolones [8] . In randomized controlled trials ( RCTs ) carried out in Nepal and Vietnam , gatifloxacin has been shown to be very effective , safe and inexpensive for the treatment of enteric fever [18] , [19] , [20] . Although WHO recommends fluoroquinolones for the treatment of enteric fever , a direct comparison between two fluoroquinolones in a large randomized trial designed with clinically relevant endpoints has not been performed . The most recent Cochrane review remarks , “There is some evidence that the newest fluoroquinolone , gatifloxacin , remains effective in some regions where resistance to older fluoroquinolones has developed . However , the different fluoroquinolones have not been compared directly in trials in these settings” [15] . We therefore chose to compare ofloxacin because of its widespread use in the treatment of enteric fever with the newer gatifloxacin . The objective of this trial was to conduct an open label , randomised clinical comparison of gatifloxacin versus ofloxacin for the treatment of uncomplicated enteric fever in an area with a high proportion of nalidixic acid-resistant isolates . This trial was performed in an outpatient setting , reflecting the “real life situation” in resource-poor countries where enteric fever is endemic .
The trial was approved by the Nepal Health Research Council , Kathmandu , Nepal and the Oxford Tropical Research Ethics Committee , Oxford , UK and was conducted according to the principles of the declaration of Helsinki . The trial was registered as ISRCTN63006567 ( www . controlled-trials . com ) . The Independent Data and Safety Monitoring Board ( DSMB ) provided oversight of the study and reviewed the data from the first 50 patients with blood culture-confirmed enteric fever in each treatment group . A full written informed consent was obtained from all the study participants [18] , [20] . Written informed consent was obtained by the parent or guardian of participating children ( under 18 years of age ) . Patients with fever for more than three days who were clinically diagnosed to have enteric fever ( undifferentiated fever with no clear focus of infection on preliminary physical examination and laboratory tests ) , presenting to the outpatient or emergency department of Patan Hospital , Lalitpur , Nepal from July 2008 to August 2011 , whose residence was in a designated area of 20 km2 in urban Lalitpur and who gave fully informed written consent were eligible for the study [18] , [20] . Exclusion criteria were pregnancy or lactation , age under 2 years or weight less than 10 kg , shock , jaundice , gastrointestinal bleeding or any other signs of severe enteric fever , previous history of hypersensitivity to either of the trial drugs , or known previous treatment with chloramphenicol , fluoroquinolones , third generation cephalosporins , or macrolides within one week of hospital admission . Patients pretreated with amoxicillin or cotrimoxazole were included as long as they did not show evidence of clinical response . Randomisation was performed in blocks of 50 without stratification by a clinical trial administrator who was not involved in the study . Random allocations were placed in sealed opaque envelopes , which were kept in a locked drawer and opened by trained community medical auxiliaries ( CMAs ) who were responsible to administer the drugs , once each patient was enrolled into the trial after meeting the inclusion and exclusion criteria and giving written consent . The treating study physicians were blinded throughout the study regarding the treatment allocation . Patients were enrolled in the order they presented and the sealed envelopes were opened in strict numerical sequence . Masking was not possible because of the differing drug intake schedule . Each enrolled patient was randomly assigned to treatment with either gatifloxacin ( 400 mg tablets , Square Pharmaceutical Limited , Bangladesh ) at 10 mg per kg per day in a single oral dose for 7 days or ofloxacin ( 200 mg or 400 mg tablets , National Healthcare Pvt . Ltd . , Nepal ) at 20 mg per kg per day in two divided oral doses for 7 days . Gatifloxacin and ofloxacin tablets were cut and weighed and the patients' daily doses were prepared in sealed plastic bags . For example , for the gatifloxacin arm , each patient was given doses nearest to 10 mg/kg for that particular patient erring on the higher side but not exceeding by 10 mg . After enrolment , patients were managed as outpatients as described previously [20] , [18] . The CMAs made a visit to each patient's house twice a day ( morning and evening ) for 10 days or until the patient was afebrile and without symptoms . The intake of each dose of ofloxacin or gatifloxacin was directly observed by the CMAs . The physicians re-examined the patients on days 8 and 15 and at 1 , 3 , and 6 months . All examinations were standardized and entered on case record forms . Complete blood counts were performed on days 1 and 8 . On day 1 , serum creatinine , bilirubin , aspartate aminotransferase ( AST ) and alanine aminotransferase ( ALT ) were measured . Random plasma glucose was measured on day 1 , day 8 , day 15 and 1 month . On days 2 to 7 , during the evening home visit , blood glucose was measured by finger-prick testing ( One Touch Sure Step , Johnson and Johnson , USA ) by the CMAs . Heamoglobin A1c was measured at 3 months . Three ( for children under 12 years ) or seven mL ( for those above 12 years ) of blood were collected for microbiological blood culture from all patients at enrolment , from culture positive patients on day 8 , and if symptoms suggested a clinical relapse . Blood samples were inoculated into media containing tryptone soya broth and sodium polyanethol sulphonate , up to a total volume of 50 mL . The bottles were incubated at 37°C and examined daily for bacterial growth over seven days . On observation of turbidity , media was sub-cultured onto MacConkey agar plate to isolate Salmonella serotypes . Isolates were screened using standard biochemical tests and S . Typhi and S . Paratyphi A were identified using AP120E ( Bio Merieux , Paris , France ) and slide agglutinaton with specific antisera ( Murex Biotech , Dartford , UK ) . Stool cultures were performed on day 1 in all patients , in blood culture-positive patients after completion of treatment and at the 1 , 3 and 6 months visits . Stool specimens were inoculated into 10 mL of Selenite F broth and incubated at 37°C . After the overnight incubation , the broth was subcultured onto MacConkey agar and xylose lysine decarboxylase agar media . MICs of nalidixic acid , ofloxacin , ciprofloxacin , gatifloxacin , azithromycin , chloramphenicol , ampicillin and ceftriaxone were determined by E-test ( AB Biodisk , Solna , Sweden ) according to the manufacturer's instructions . The primary endpoint of this study was the composite endpoint of treatment failure , which was defined by the occurrence of any of the following: persistence of fever of more than 37 . 5°C at day 10 of treatment; need for rescue treatment with ceftriaxone or azithromycin as judged by the treating physician; microbiological failure , defined as a positive blood culture for S . Typhi or S . Paratyphi A on day 8; relapse , defined as the reappearance of symptoms of enteric fever between day 8 to day 31 in patients who were initially categorized as successfully treated , this included culture-confirmed ( including mismatch of serotypes [e . g . , day 1 blood culture positive for S . Typhi and relapse blood culture positive for S . Paratyphi A or vice versa] ) and syndromic enteric fever , and occurrence of enteric fever related complications . Time to treatment failure was defined as the time from the first dose of treatment until the date of the earliest failure event of that patient , and patients without an event were censored at the date of their last follow-up visit . Secondary endpoints were: fever clearance time ( FCT , time from the first dose of treatment given until the temperature is for the first time ≤37 . 5°C and the patient remained afebrile for at least 48 hours ) ; time to relapse until day 31 , day 62 , or 6 months of follow-up; and faecal carriage at the follow-up visits at 1 , 3 and 6 months . The patients' FCTs were calculated electronically on the basis of twice-daily recorded temperatures . Patients without recorded FCT or relapse were censored at the date of their last follow-up visit . To reduce possible bias , an investigator who was not involved in the recruitment of patients decided patients' final outcomes by use of a masked database . The analysis plan also predefined a modified secondary definition ( “modified analysis” ) of the primary endpoint of this study , treatment failure ( see above ) , in which persistent fever of more than 37 . 5°C at day 7 replaced persistent fever on day 10 as part of the composite endpoint . This was done to allow comparison with previous studies [21] and to explore the modification of this endpoint for future definitions of outcomes for standardisation of clinical trials in enteric fever . The trial was powered as a superiority trial to detect a 20% decrease in the risk of treatment failure due to gatifloxacin ( from 25% for ofloxacin to 5% for gatifloxacin ) in the treatment of enteric fever patients infected with nalidixic acid-resistant isolates . To achieve 90% power at the two-sided 5% significance level , 75 patients per group would be required and the original protocol specified a sample size of 100 patients with culture-confirmed enteric fever in each arm . A blinded interim observation was performed after 510 patients had been recruited and based on this , the study team decided to amend the protocol and increase the sample size to obtain 110 blood culture positive patients in each arm so that at least 75 patients with nalidixic acid-resistant S . Typhi or S . Paratyphi A in each arm could be followed up for one month and analysed . On the basis of results from a previous study [18] , we assumed that approximately 40% of recruited patients had culture-confirmed enteric fever . To allow for some loss to follow-up , a total of 629 patients with suspected enteric fever were recruited to the trial . The times to treatment failure , fever clearance , and relapse , were summarised by Kaplan-Meier estimates and compared between interventions using Cox regression models with the treatment group as the only covariate . For the primary endpoint ( treatment failure ) , we also compared the absolute risk of treatment failure until day 31 based on Kaplan-Meier estimates and standard errors according to Greenwood's formula [22] . Additionally , the times to treatment failure and FCT were analysed in the subgroups defined by culture result , pathogen ( S . Typhi or S . Paratyphi A ) , age ( <16 years or ≥16 years ) , MICs of gatifloxacin and ofloxacin , and heterogeneity of the treatment effect was tested with Cox regression models that included an interaction between treatment and subgroup . The primary analysis population was the population infected with nalidixic acid-resistant isolates ( a subgroup of the population with blood culture-confirmed enteric fever ) . Statistical analyses were also performed for all blood culture positive patients ( blood culture positive population ) and all patients who were assigned treatment , with the exception of those patients who were mistakenly randomised or withdrew before the first dose of study treatment ( intention to treat population , ITT , this included patients with negative blood culture result ) for treatment failure and safety . All reported tests were done at the two-sided 5% significance level , and 95% CIs are reported . All analyses were performed with the statistical software R version 2 . 15 . 1 [23] .
The study flow is displayed in Figure 1 . Of the 1494 patients who were assessed for eligibility , 865 were excluded prior to randomisation , primarily due to residence outside the designated study area . Two randomised patients were excluded from all analyses ( Figure 1 ) , leaving 627 patients in the intention to treat population ( ITT ) . Table 1 shows the baseline characteristics of these patients . Only 2 patients in the ofloxacin arm and 4 patients in the gatifloxacin arm had a positive stool culture for S . Typhi or S . Paratyphi A before the start of treatment ( Table 1 ) . The outcomes for the primary analysis population , the 170 patients infected with nalidixic acid-resistant isolates , are summarised in Table 2 and Figure 2 . The number of patients with treatment failure was 6/83 in the ofloxacin group and 5/87 in the gatifloxacin group ( Hazard Ratio , HR = 0 . 81 , 95% CI 0 . 25 to 2 . 65; p = 0 . 73 ) . One patient in the gatifloxacin arm had persistent fever on day 10 and received azithromycin treatment ( 1 g per day ) starting on day 11 . There were 9 relapses ( Table 2 ) within 31 days after the start of treatment ( 5 in the ofloxacin group and 4 in the gatifloxacin group ) and all nine patients responded well to azithromycin ( 20 mg/kg , up to 1 g per day ) for 7 days . One patient in the ofloxacin group had severe abdominal pain on day 2 and was admitted to hospital with the presumed diagnosis of appendicitis . He stayed in hospital overnight for observation and azithromycin treatment was started . The next day , the patient had improved significantly and went home . This was the only patient in this trial who had possible enteric fever related complications ( Table 2 ) and needed hospitalization . There was also no evidence of difference in treatment failure rates between treatment groups amongst all patients with blood culture confirmed enteric fever ( Table S1 ) , the ITT population ( Table S2 ) or in any of the predefined subgroups , which were age ( less than 16 years or 16 years and above ) , pathogen ( S . Typhi or S . Paratyphi A ) and MIC of the isolates ( Table 3 ) . In contrast , fever clearance times ( FCT ) were significantly shorter in the gatifloxacin arm of the study . In patients infected with nalidixic acid-resistant isolates , the median FCT was 4 . 70 ( IQR 2 . 98 to 5 . 90 ) days in the ofloxacin arm and 3 . 31 ( IQR 2 . 29 to 4 . 75 ) days in the gatifloxacin arm ( HR = 1 . 59 , 95% CI 1 . 16 to 2 . 18; p = 0 . 004 ) . The comparison also reached statistical significance in patients with blood culture confirmed enteric fever and the ITT population and there was no convincing evidence of heterogeneity in any of the predefined subgroups ( Tables S1 and S2 , Table 4 ) . Of note , in the predefined modified analysis that we conducted , in which persistent fever on day 7 replaced persistent fever on day 10 as part of the composite primary endpoint , there was a significant difference in the number of patients with treatment failure in favour of gatifloxacin in all three groups ( see also footnotes Tables S1 and S2 ) . Using this seven-day cut off , in the population infected with nalidixic acid-resistant isolates , there were 21 out of 83 patients with treatment failure in the ofloxacin group versus 11 patients out of 87 in the gatifloxacin group ( HR = 0 . 46 , 95% CI 0 . 22 to 0 . 96 , p = 0 . 04; 16 versus 7 patients were still febrile on day 7 ) . During the six months of follow up , only one patient in the blood culture positive group had a positive stool culture . This occurred at the end of one month and the patient was treated with ofloxacin . Only syndromic relapses were documented after day 62 in all three patient populations ( Table 2 , Tables S1 and S2 ) , with the exception of one culture negative patient ( ITT population ) in the gatifloxacin group who experienced a culture confirmed relapse on day 92 . Adverse events were analysed in the ITT population . 215 out of 316 ( 68% ) patients in the ofloxacin group and 223 out of 311 ( 72% ) patients in the gatifloxacin group experienced an adverse event ( Table S3 ) . Most adverse events were mild ( grade 1 or grade 2 ) . Two patients , one from the gatifloxacin and one from the ofloxacin group developed generalized skin rash on day 3 , which disappeared after stopping the drugs . Another patient in the gatifloxacin arm had generalized discomfort and treatment was stopped on day 4 . He was eventually diagnosed with pulmonary TB . Another patient ( described in the outcomes paragraph above ) had abdominal pain and was admitted to hospital with the presumptive diagnosis of appendicitis . Finally a patient treated with gatifloxacin had a random blood glucose level of 280 mg/dl on two different occasions ( days 3 and 5 ) and gatifloxacin was stopped on day 5 . In total only five patients , four blood cultures negative and one blood culture positive patient had their treatment discontinued due to presumed adverse events . All of them , except the patient with TB , were started on azithromycin ( 20 mg/kg up to 1 g per day ) for 7 days and improved . The proportion of patients with haemoglobin A1c levels >6% at the end of three months was similar in both groups ( 48/262 ( 18% ) patients in the ofloxacin group and 48/248 ( 19% ) patients in the gatifloxacin group ) . The MIC results for the 218 available S . Typhi and S . Paratyphi A isolates are shown in Table 5 . Eighty-four out of 86 ( 97 . 6% ) of the S . Paratyphi A and 86 out of 132 ( 65 . 1% ) of the S . Typhi strains were nalidixic acid resistant . None of the isolates were MDR or demonstrated ceftriaxone resistance . The MIC50s and MIC90s were consistently higher for the S . Paratyphi A isolates than for S . Typhi isolates . Higher ( log-transformed ) MICs to ofloxacin and gatifloxacin were associated with a prolonged FCT in both study arms: ofloxacin group ( p = 0 . 0003 for ofloxacin MIC; 0 . 0006 for gatifloxacin MIC ) and significant in the gatifloxacin group ( p = 0 . 03 for both ofloxacin MIC and gatifloxacin MIC ) ( Figure 3 ) .
Gatifloxacin was not superior to ofloxacin in preventing treatment failure . Ofloxacin with adequate dosing ( 20 mg/kg per day ) treated enteric fever caused by nalidixic acid resistant strains successfully , but with longer fever clearance times than gatifloxacin . In the context of the data of this trial , we would like to discuss some key issues in the treatment of enteric fever . The emergence and spread of MDR and nalidixic acid-resistant S . Typhi and S . Paratyphi A in Asia and parts of Africa has limited the number of effective antimicrobials available for treatment [8] , [9] , [10] . The other issues relate to the design of clinical trials in enteric fever , especially the definition of efficacy outcomes and the implications of those definitions on the results . We have conducted a series of randomized controlled trials to document the best treatment options for enteric fever caused by nalidixic acid-resistant S . Typhi and S . Paratyphi A [18] , [19] . In these trials , gatifloxacin has shown to be an effective and safe treatment for enteric fever . Despite a high proportion of nalidixic acid-resistant isolates , the older generation fluoroquinolone ofloxacin is still used as standard of care in health facilities in South and South East Asia . Clinical trials in Vietnam showed a reduced efficacy of ofloxacin in the treatment of nalidixic acid-resistant enteric fever [21] , [24] . Studies have shown that gatifloxacin works against mutated forms of the gyrA and ParC against which the older fluoroquinolones like ciprofloxacin do not work [17] . Although other fluoroquinolones like ciprofloxacin and ofloxacin also target gyrA and ParC , the C-8-methoxy group in gatifloxacin works to inhibit the resistant mutants not inhibited by the older fluoroquinolones [8] , [17] . Therefore we hypothesized that gatifloxacin may perform better clinically with lower treatment failure rates than the older fluoroquinolone ofloxacin in a setting where there is a high ( 80% ) proportion of nalidixic acid resistance . We therefore conducted a direct comparison of ofloxacin and gatifloxacin , and our primary population of interest was the patients infected with nalidixic acid–resistant isolates . The continued use of ofloxacin in Asia is also partially caused by the lack of availability of gatifloxacin . Gatifloxacin has been withdrawn from the US and some other countries in 2006 , following a retrospective report of an increased risk of dysglycaemia in elderly Canadian outpatients [25] . In 2011 , gatifloxacin was banned in India . Previous case reports have highlighted an effect on glucose homeostasis in patients with non-insulin-dependent diabetes on therapy and elderly patients with age-related decreases in renal function [26] . However , patients with enteric fever are typically children and young adults , who are generally healthy and have good kidney function . Over the last few years , more than 1 , 123 patients ( children and adults ) suffering from enteric fever [18] , [19] , [20];and this trial ) , 249 children with shigellosis [27] and 15 adult patients with TB meningitis [28] have been treated with gatifloxacin in registered randomised clinical trials in Nepal and Vietnam , and no problems in glucose homeostasis have been observed . In a previous study [18] and in this currently reported trial , as an additional safety measure , random blood glucose was monitored daily for 7 days , at day 15 and one month and HbA1c was measured at 3 months . One patient out of 628 patients who received gatifloxacin and were monitored in these 2 trials showed hyperglycemia . She was a 35 year old woman who did not reveal on enrollment that she was intermittently taking oral hypogylcemic drugs for diabetes . Her fever improved with azithromycin that was started on day 5 and she was followed as an outpatient for diabetes . Gatifloxacin is also under investigation as an alternative drug in short-course tuberculosis regimen . In a multicentre trial in Africa , 917 patients received gatifloxacin daily for four months as part of a drug combination regimen for the treatment of pulmonary tuberculosis . Dysglycemia has not emerged as an adverse event in this population [29] . Clearly , the risk-benefit ratio of gatifloxacin is very different in the two patient populations; on one side , the elderly and multi-morbid Canadian population and on the other side , a young and otherwise healthy population suffering from infectious diseases , like enteric fever and tuberculosis . To conduct these trials , we have considered very carefully the design of clinical trials in enteric fever . Previous Cochrane reviews have criticised the small number of patients enrolled and the varying methodological quality of enteric fever trials [15] , [16] . To address the technical issue of the low sensitivity of microbiological blood culture ( an estimated 40 to 60% of clinical suspected enteric fever ) , we have included the culture negative population in all analyses and added symptomatic relapse ( not confirmed by culture ) to the outcome events of all our studies . We used a composite endpoint , treatment failure , evaluated at 1 month , which included the following unfavourable events: persistent fever at day 10 , need of rescue treatment , positive blood culture for S . Typhi or S . Paratyphi A at day 8 , development of complications and relapse ( re-occurrence of symptoms within 31 days after the start of treatment , both culture positive and negative ) . Using these definitions , the number of treatment failures between the ofloxacin and gatifloxacin group were similar ( Table 2 , Tables S1 and S2 ) . However , there was a statistically significant difference in FCT , defined as secondary endpoint , in favour of gatifloxacin in all three analysed populations , the patients infected with nalidixic acid-resistant isolates ( median FCT , 4 . 70 days versus 3 . 31 days , Table 2 ) , the culture confirmed population ( 3 . 99 days versus 3 . 30 days , Table S1 ) and also in the ITT population ( 2 . 15 days versus 1 . 97 days , Table S2 ) . Indeed , in the predefined modified analysis , in which persistent fever on day 7 replaced persistent fever on day 10 in the composite endpoint , there was a significant difference in favour of gatifloxacin in all three groups . This highlights that the conclusions derived from such studies critically depend on the definitions chosen in the design of a clinical trial . At the present time there is no standardisation for the design of clinical trials in enteric fever . Hence in this study , the main difference between ofloxacin and gatifloxacin was the speed of resolution of fever , by ten days there was no difference . The slower resolution of fever in patients infected with nalidixic acid-resistant isolates during treatment with ofloxacin is corroborated by two previous studies [24] , [21] . A trial conducted in adult patients in Vietnam between 1997 and 1998 [24] , at which time the proportion of nalidixic acid-resistant strains increased from 10% to 76% ( 6 ) , used a lower dose at 200 mg ofloxacin twice a day ( an estimated 8 mg/kg/day ) for a shorter duration of 5 days . Forty-four patients received ofloxacin , 53% were infected with nalidixic acid-resistant strains . The mean fever clearance time was 5 . 6 days in all 44 patients recruited , but it was prolonged to 7 . 25 days in the 21 patients infected with nalidixic acid-resistant isolates ( 60 ) . Four out of 21 ( 19% ) patients infected with nalidixic acid-resistant strains failed in the ofloxacin group . Three patients had “clinical treatment failure” , defined as the persistence of fever and symptoms for more than 5 days after the end of treatment ( i . e . fever on day 10 ) and one patient relapsed . In 41% of patients , a transient stool carriage immediately after treatment was present . Another trial conducted from 1998 to 2001 in Vietnam used ofloxacin at 20 mg/kg/day for seven days ( the same dose as used in this trial ) , and reported a “clinical treatment failure” rate of 36% ( 23 out of 63 patients ) using the definitions “persistence of fever and at least one more symptom for more than 7 days after the start of treatment or the development of severe complications during treatment requiring a change in therapy” [21] . Ninety-eight percent of the isolates were nalidixic acid-resistant . All of the patients who failed had persistent fever and symptoms and 14 of those patients required retreatment . The mean FCT for patients treated with ofloxacin was 8 . 2 days . There was a high rate of faecal carriage immediately after treatment of 19% ( 12/62 ) , potentially allowing transmission of isolates to close contacts and family members . The results of this study [21] are comparable to our data in the patients infected with nalidixic acid-resistant isolates , with the predefined modified analysis . When we applied the seven-day cut off for FCT , there were 21 out of 83 ( 25% ) patients with treatment failure in the ofloxacin group , with 16 out of 83 ( 19% ) patients still febrile on day 7 . The reason for these slightly better results of ofloxacin in the enteric fever patients infected with nalidixic acid-resistant isolates in our trial could be that the tablets were weighed and pre-packed for each individual patient , whilst in the Vietnam studies the dose was estimated and patients may have received doses lower than the planned 20 mg/kg/day . While all ofloxacin failures occurred in isolates with ofloxacin MIC>−0 . 125 mg/ml , 2 of the cases of gatifloxacin failure occurred even in MIC<0 . 19 mg/ml . One reason may be different gatifloxacin pharmacokinetics in these two patients . These trials [24] , [21] with a high proportion of nalidixic acid resistant-strains were included in a meta-analysis that analysed 7 trials ( 540 patients ) that used ofloxacin for treatment [11] . There was a clear relationship between elevated ofloxacin MIC ( MIC≥0 . 25 µg/mL ) and prolonged fever clearance time and higher risk of treatment failure . This is corroborated by our data , Table 4 shows that patients infected with isolates with higher ofloxacin MICs ( between 0 . 25 µg/mL and 0 . 75 µg/mL ) [30] had longer median fever clearance times when treated with ofloxacin ( median 4 . 76 days ) than with gatifloxacin ( median 3 . 31 days; p = 0 . 004 ) . Crucially , patients and their guardians consider the fever to be the major symptom associated with enteric fever and clearly a prompt resolution of fever is an important issue in favour of gatifloxacin . We have data from our patients about their subjective perception of being cured from enteric fever and the majority of patients correlate this with the time the fever has subsided ( A . Arjyal , manuscript in preparation ) . In addition , prolonged fever clearance times have been associated with microbiological failure , increased complication and relapse rates when using ciprofloxacin or ofloxacin for the treatment of enteric fever [31] , [32] . Our study has a number of limitations . First , it was an open labelled randomized trial . Also , patients with severe enteric fever were not included in the study . Although faecal carriage rates were low in our study , in previous studies [21] , [24] , faecal carriage immediately after successful treatment of typhoid fever with ofloxacin was high and this may be a worrisome aspect of ofloxacin use . The lower fecal carriage in our population may be due to earlier presentation when stool tests are less likely to be positive or it may also be due to the intermittent nature of salmonella excretion in the stool . Notwithstanding these limitations , the findings of this study are of practical importance in many resource poor countries where enteric fever is endemic , nalidixic acid-resistant strains are common , and where ofloxacin is a standard drug for treatment of enteric fever [3] . Our patient population comprised of outpatients with uncomplicated enteric fever which reflects the situation of the majority of enteric fever patients receiving treatment in endemic countries . Our study also describes the ITT population which includes blood culture negative patients and shows that the results were consistent with the outcome in the blood culture-confirmed population . This is an important issue because undifferentiated fever of more than 3 to 4 days is treated empirically in most settings . A previous study from our hospital revealed that besides enteric fever , leptospirosis , and rickettsial ( murine and scrub typhus ) illnesses are other causes of such undifferentiated fever [1] . This present study would suggest that adequately-dosed gatifloxacin or ofloxacin would be an effective drug to empirically treat undifferentiated fever in our setting Ofloxacin at a dose of 20 mg/kg/day remains an option to treat enteric fever , even in settings with high rates of nalidixic acid-resistance but leads to a slower resolution of symptoms compared to gatifloxacin . The convenience of once daily dosing of gatifloxacin and faster resolution of symptoms would suggest that gatifloxacin has advantages compared to ofloxacin for the treatment of young otherwise healthy patients with enteric fever in areas of nalidixic-acid-resistance .
|
Enteric fever , which comprises of typhoid and paratyphoid fevers , is common in many developing countries . It is also sometimes seen in the Western world in returning travellers . This present study of uncomplicated enteric fever in an outpatient setting in a hospital in Kathmandu , Nepal compared the newer gatifloxacin with the widely-used ofloxacin ( two drugs of the fluroquinolone class ) in the treatment of this illness . Although fluroquinolones are commonly considered the main group of drugs in the treatment of enteric fever , there have not been comparisons of efficacy between two drugs in this same class in the treatment of enteric fever . Furthermore , certain strains of enteric fever organism called nalidixic-acid resistant strains are proving very difficult to treat in both the local population and the Western travellers . The study focused primarily on the efficacy of the 2 drugs against these particular strains . The results revealed that both drugs were effective but gatifloxacin decreased the patient's fever more rapidly than ofloxacin . Dysglycemia was noted in a 35-year-old woman taking gatifloxacin who did not disclose a pre-existing diagnosis of diabetes at time of enrollment , but not in any other healthy child or young adult .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2013
|
Gatifloxacin Versus Ofloxacin for the Treatment of Uncomplicated Enteric Fever in Nepal: An Open-Label, Randomized, Controlled Trial
|
Recent gene expression QTL ( eQTL ) mapping studies have provided considerable insight into the genetic basis for inter-individual regulatory variation . However , a limitation of all eQTL studies to date , which have used measurements of steady-state gene expression levels , is the inability to directly distinguish between variation in transcription and decay rates . To address this gap , we performed a genome-wide study of variation in gene-specific mRNA decay rates across individuals . Using a time-course study design , we estimated mRNA decay rates for over 16 , 000 genes in 70 Yoruban HapMap lymphoblastoid cell lines ( LCLs ) , for which extensive genotyping data are available . Considering mRNA decay rates across genes , we found that: ( i ) as expected , highly expressed genes are generally associated with lower mRNA decay rates , ( ii ) genes with rapid mRNA decay rates are enriched with putative binding sites for miRNA and RNA binding proteins , and ( iii ) genes with similar functional roles tend to exhibit correlated rates of mRNA decay . Focusing on variation in mRNA decay across individuals , we estimate that steady-state expression levels are significantly correlated with variation in decay rates in 10% of genes . Somewhat counter-intuitively , for about half of these genes , higher expression is associated with faster decay rates , possibly due to a coupling of mRNA decay with transcriptional processes in genes involved in rapid cellular responses . Finally , we used these data to map genetic variation that is specifically associated with variation in mRNA decay rates across individuals . We found 195 such loci , which we named RNA decay quantitative trait loci ( “rdQTLs” ) . All the observed rdQTLs are located near the regulated genes and therefore are assumed to act in cis . By analyzing our data within the context of known steady-state eQTLs , we estimate that a substantial fraction of eQTLs are associated with inter-individual variation in mRNA decay rates .
Substantial variation in gene expression levels exists in natural populations [1]–[5] . Over the past decade , we have learned that much of this inter-individual regulatory variation is associated with specific genetic polymorphisms , which can be identified by mapping expression quantitative trait loci ( eQTLs ) [6]–[10] . Expression QTL mapping studies in different organisms have led to important insights into the genetic basis for gene regulation and , in a number of cases , into the mechanistic basis for complex phenotypes . In particular , recent eQTL mapping studies in humans have identified thousands of genetic variants affecting gene expression levels [11]–[14] , some of which are loci that are also associated with complex diseases [15]–[18] . Nearly all human eQTLs , regardless of the tissue in which they were found , have been identified near the regulated genes and hence are assumed to act in cis . A partial explanation for the relatively small number of trans eQTLs that have been identified is the low power to map such loci compared to cis acting eQTLs ( due to the stringent significance criteria required to avoid false positives when mapping across the entire genome , and generally small effect sizes of trans-QTLs [8] , [19]–[25] ) . Despite the recent success in mapping gene expression phenotypes , we still know little about the specific regulatory mechanisms that underlie eQTLs [26]–[29] . Partly , this gap is being addressed by a growing number of large-scale mapping studies of inter-individual variation in genetic and epigenetic regulatory mechanisms ( which complement studies of gene expression variation [13] , [30]–[34] ) . Yet , even by incorporating such studies , the processes underlying regulatory variation and their relative importance remain difficult to infer , because all eQTL studies to date – regardless of the model system or species - have relied on measures of steady-state gene expression levels . Steady-state gene expression levels are generally the result of two opposing biological processes: mRNA transcription , which includes transcript initiation , elongation , and processing , and mRNA decay , which includes spontaneous and targeted degradation of transcripts , as well as dilution [35] , [36] . Using only measurements of steady-state gene expression levels , it is impossible to determine the relative contribution of variation in transcription rates and mRNA decay rates to overall regulatory variation . In other words , without additional data , the particular mechanisms underlying steady-state expression level QTLs cannot be inferred with confidence . To better understand the basis for variation in steady-state gene expression levels requires data on specific aspects of gene regulatory mechanisms . Most recent studies that have done so ( though only rarely in the context of QTL mapping ) , have focused on understanding transcriptional processes contributing to gene expression variation , such as splicing , DNA methylation , histone modification , chromatin accessibility , and transcription factor binding . Results from this emerging body of work indicate that although transcriptional processes contribute substantially to steady-state measurements of gene expression , neither the independent or combinatorial effects of these mechanisms can completely account for variation in steady-state gene expression levels [28] , [29] , [37] , [38] . It is likely that a better account of regulatory variation can be obtained once transcription initiation and RNA decay mechanisms are considered together . While the details of transcriptional regulation are becoming increasingly understood , the mechanisms influencing variation in mRNA decay rates have thus far received less attention , particularly in mammalian systems [11] , [37]–[39] . This bias may reflect the prevalent assumption that transcription initiation rates are the major determinants of overall gene expression levels [40]–[43] . Yet , a few recent studies of mRNA decay mechanisms have challenged this historical view [3] , [33] , [44]–[47] . In particular , it has been argued that the regulation of mRNA decay processes might be a key determinant of the expression patterns of a large subset of genes . Recent studies in eukaryotic cells have revealed a wide variability of mRNA decay rates across transcripts – with individual mRNA half-lives ranging from a few minutes to several hours – which can often be tied to differences in the functional role of the regulated genes [44] , [48]–[50] . For example , studies in yeast , worms , plants , and human primary cells have all found that genes involved in the regulation of transcription tend to produce mRNA that decays faster than mRNA from genes involved in cell cycle or metabolic pathways [1] , [3] , [41] , [48] , [51] , [52] . Furthermore , the steady-state mRNA levels of the lowest or highest expressed genes are strongly correlated with mRNA decay rates [41] , [44] , [49] , [50] , suggesting that in these cases , regulation of mRNA decay is likely an important determinant of gene expression levels . A number of mechanisms are known to contribute to variation in mRNA decay rates among genes . These include the roles of certain RNA-binding factors such as small RNAs , RNA-binding proteins , and larger RNA-binding complexes , all of which have been shown to bind to both general ( such as the AU-rich 3′ untranslated region elements; AREs [15] , [26] , [53] ) and specific RNA motifs [11] , [37] , [54] . For example , many RNA-binding small RNAs , including miRNAs , have been shown to expedite decay of specific transcripts by creating double stranded RNA that is targeted for degradation by endonuclease enzymes [11] , [38] , [47] . Similarly , certain interactions between RNA binding proteins and mRNA have been shown to contribute to either higher ( “destabilizing proteins” ) or lower decay rates ( “stabilizing proteins” ) , though the mechanisms by which they act are not yet fully understood [11] , [54] , [55] . More generally , we now appreciate that , much like transcription rates , mRNA decay rates are regulated by a combination of trans elements ( such as proteins , complexes , or small RNAs ) binding to a collection of cis binding motifs ( typically included within the transcript itself ) [6] , [56] , [57] . However , despite increasing understanding about mechanistic details of mRNA decay processes , we still know little about inter-individual variation in mRNA decay rates , in any species .
As a first step of our analysis , we characterized the genome-wide distribution of mRNA decay rates . To do so , for each gene we used the median decay rate across individuals as a measure of the gene-specific mRNA decay rate . We observed a wide range of mRNA decay rates across genes ( Figure 1A ) , consistent with findings of previous studies . We also observed a substantial amount of variation in decay rates across individuals within each gene ( Figure 1B ) , consistent with expectations from previous studies in human cells [1] , [35] , [40] . We classified genes as either consistently slow or fast decaying when their decay rates in at least 80% of individuals in our study were classified as slow or fast relative to the individual-mean decay rate ( see Methods ) . We thus identified 146 genes that consistently decayed slower than average across individuals and 716 genes that consistently decayed faster than average . In agreement with previous observations , we found that genes with related biological functions often decayed at similar rates [1] , [52 , 52] . Genes with slower decay rates tend to be involved in cellular and organelle-related housekeeping processes , such as cytoplasmic and mitochondrial processes ( Table S2 ) . Genes with faster decay rates are enriched for gene regulatory functions that might require rapid mRNA decay to ensure rapid turnover of expression levels in response to changing cellular conditions ( Table S3 ) . This includes enrichments for functional annotations such as metabolic processes , regulation of gene expression , and regulation of transcription . We next investigated possible mechanisms that could account for variation in mRNA decay rates across genes . Previous studies have suggested that increased transcript length [3] , [41] , and specifically 3′UTR length [1] , [3] , might significantly influence mRNA decay rates . Indeed , we find that both are slightly but significantly positively correlated with decay rates across genes ( Spearman ρ = 0 . 17 , P<10−16 for gene length and Spearman ρ = 0 . 09 , P<10−16 for 3′UTR length ) . This association is also evident when we limit this analysis only to genes classified as decaying slower or faster than the mean decay rate ( Figure 2A; Figure S4; Spearman ρ = 0 . 15; P<10−16 for gene length and Spearman ρ = 0 . 09; P<10−8 for 3′UTR length ) . The increased 3′ UTR length in faster decaying genes is thought to indicate an increase in potential regulatory space that could harbor RNA-decay regulatory elements ( reviewed in [6] ) . Studies of mRNA decay of individual genes have previously identified two main classes of cis regulatory elements that might play roles in decay processes: microRNA ( miRNA ) binding sites [11] and AU-rich elements [15] , [17] . To determine the possible influence of miRNA binding on decay rates in the LCLs , we curated several miRNA databases [19] , [20] , [22]–[25] to create a list of confident miRNA target binding sites ( see Methods S1 ) . To account for the confounding effect of transcript length ( more binding sites in longer 3′UTRs ) , we standardized the number of miRNA target binding sites by the 3′UTR length ( see Methods ) . Using this approach , we found a slightly positive correlation between the density of miRNA target sites and decay rates . Again , when we focused exclusively on the genes classified as decaying slower or faster than the mean decay rate , we observed a stronger association ( Figure 2B , Spearman ρ = 0 . 16; P<0 . 003 ) . We then considered the presence of AU-rich elements ( AREs ) in slower versus faster decaying genes . To do so , we used the AREScore algorithm [26] , which searches within 3′UTRs for features associated with typical type-II AREs , to assign an AREScore to each gene . A larger AREScore essentially implies increased potential for binding by an ARE-recognizing RNA binding protein to regulate the decay processes of the gene . We found that there is a significantly increased median AREScore in faster decaying genes compared to slower decaying genes ( Figure 2C , Spearman ρ = 0 . 14; P<10−16 ) . As our findings support the general notion that cis regulatory elements , such as miRNA bindings sites or AU-rich elements , are important determinants of mRNA decay rates , we next searched for additional sequence motifs that might represent novel binding sites for specific decay factors in LCLs . To do so , we used the FIRE algorithm [30] to search for motifs in the 146 slow decaying genes and 716 fast decaying genes . We identified three significantly enriched motifs – one enriched in the fast decaying genes , and two enriched in the slow decaying genes ( Figure 2D ) . We performed the motif search across the entire promoter and transcript region for each gene , yet all three enriched motifs are located in 3′UTRs . The motif enriched in fast decaying genes closely resembles a typical AU-rich element sequence . The two motifs enriched in slow decaying genes could not be linked to any currently known miRNA seed sequence or RNA-binding protein motif and hence might be novel regulatory elements . We are specifically interested in the effect that mRNA decay has on steady-state expression levels ( in these analyses , we defined “steady-state expression” as the mean expression across all time points so that our estimates of steady-state expression levels would be statistically independent of the estimated decay rates when the null hypothesis of no association between steady-state levels and decay rates is true; see Methods ) . Considering this relationship across all genes ( Figure 3A ) , we found little or no correlation between decay rates and gene expression levels . However , we observed a significant difference in expression levels between genes classified as decaying significantly slower or faster than the mean decay rate ( as defined above; P<6×10−6 , Figure 3B; Figure S5 ) . This difference in expression levels is in the expected direction – that is , genes with slower decay rates have higher steady-state expression levels than genes with faster decay rates . We also observed a small number of cases in which genes with faster decay rates are highly expressed ( we refer to this as a ‘discordant’ relationship between gene expression levels and decay rates ) . One example is the BTG1 gene , which is involved in regulating the glucocorticoid receptor autoregulatory pathway [35] , and has both a significantly increased decay rate and a high expression level ( Figure S5 ) . Interestingly , seven of the top nine genes with discordant patterns ( both the expression levels and decay rates of these nine genes are within the top 5% of the genome-wide distributions of gene expression and decay rates respectively; Figure 3C; see Methods ) have been experimentally shown to be involved in auto-regulatory or regulatory feedback pathways ( Table 1 ) [61]–[69] . More broadly , the top 49 genes with discordant patterns ( constituting the top 10% of both the genome-wide distributions of gene expression levels and decay rates; Figure 3C ) are enriched for genes with functions related to signaling pathways , stress response , and immune function ( when genes expressed in LCLs are used as the background for the analysis; Table S4 ) . We next examined the extent to which variation in decay rates might contribute to overall variation in steady-state expression levels across individuals . For each gene , we calculated the correlation between gene expression levels and mRNA decay rates across individuals and focused on genes with a significant ( FDR = 10% ) correlation between the two measurements ( Figure 4A ) . We found a significant negative correlation between expression levels and decay rates for 695 genes . It is reasonable to assume that inter-individual variation in steady-state expression levels of these 695 genes is driven by corresponding variation in decay rates . Based on gene ontology functional annotations , these 695 genes are enriched for genes involved in endopeptidase inhibitor and regulator activity ( Table S5 ) . On the other hand , we also found a discordant relationship between gene expression levels and decay rates across individuals for 989 genes ( 10% FDR; Figure 4A ) . This finding may seem counter-intuitive as it contradicts our expectation that higher decay rates should result in lower steady-state gene expression levels . However , genes with a discordant relationship between expression and decay are enriched for processes involved in the regulation of cellular , metabolic , and transcriptional activities ( Table S6 ) . A similar observation of discordant relationships between decay rates and expression levels that are enriched for genes in the same functional categories ( metabolic , and transcriptional activities ) has been previously reported in yeast [37] , [38] . Put together , these results suggest a role for mRNA decay in complex regulatory circuits that have the property of fast response time , for instance auto-regulation by negative feedback loops . Studies across yeast species [37] , [38] have further suggested that positive correlations between gene expression levels and decay rates are often coupled with correspondingly increased transcription rates – presumably to increase response speed [40] . To test this notion in our system , we used a combination of previously published [33] and newly generated PolII occupancy ChIP-seq data from seven of the same Yoruba LCLs as a proxy measurement of gene-specific transcription rate ( Table S7 ) . Our hypothesis , based on the observations from the yeast studies , was that transcription and decay rates are often positively correlated in genes with discordant relationship between expression levels and RNA decay rates across individuals . Indeed , we found a significant increase in positive correlations between transcription and mRNA decay rates for genes with discordant compared to genes with a concordant relationship between expression and decay ( P<10−3; Figure 4B; Figure S6 ) and compared to the distribution of correlations between transcription and mRNA decay rates of all genes in the data set ( P<10−16 ) . Finally , we investigated the genetic basis for inter-individual variation in mRNA decay rates . To do so , we treated the mRNA decay rates as a quantitative trait and mapped genetic loci influencing variation in this trait . We tested for association between individual-specific estimates of mRNA decay rates and genotypes in a cis candidate region of 25 kb centered around the target transcript boundaries . Using this procedure , we found 31 genes with significant RNA decay quantitative trait loci ( rdQTLs ) at a 15% FDR ( Figure 5A ) . Expanding our mapping procedure to include genome-wide polymorphisms , we found no evidence for significant trans-acting rdQTLs , likely because our experiment is underpowered to detect trans effects ( see Methods S1 ) . Given the observed significant correlation between steady-state gene expression levels and decay rates across individuals , we hypothesized that we might have better power to detect more rdQTLs at a given FDR if we focused on SNPs already identified as steady-state expression QTLs . To do so , we first mapped eQTLs using the mean expression data across time points . We identified 1 , 257 eQTLs ( at 15% FDR; see Methods ) , most of which were previously observed in these cell lines . Within this set , 195 ( 16% ) of the eQTLs were also significantly ( at 15% FDR ) associated with variation in mRNA decay rates ( Figure 5B , Table S8 ) . In other words , 195 of the steady-state gene expression QTLs are also classified as rdQTLs using our approach; a significant enrichment of decay effects compared to that expected by chance ( P<0 . 001 ) . Using the method of Storey et al . to conservatively estimate the proportion of tests where the null hypothesis is false ( while accounting for incomplete power [48] ) , we estimate that 35% of the most significant eQTL SNPs are also associated with decay rates ( Figure S7 ) . We asked whether SNPs that are identified as rdQTLs are enriched in particular genomic annotations , especially when compared to eQTL SNPs . Since our mapping approach does not allow us to identify with confidence the causal site , we proceeded by considering and comparing the strength of association with decay rates across SNPs in different genomic annotations . Using this approach we found that , in general , the same functional annotations that were previously found to be enriched for eQTLs are also enriched for rdQTLs ( e . g . , exons , UTRs , and promoter regions; Figure S8A ) . Yet , while eQTL are generally enriched in 3′ UTRs ( Figure S8B ) , rdQTLs are specifically enriched in predicted miRNA binding sites within 3′ UTRs ( Figure 6 ) . This observation is consistent with the hypothesized importance of miRNA-mediated regulation of mRNA decay . We next examined the relationship between eQTLs and rdQTLs in more detail . We found that in the majority of the joint QTLs ( 55% ) , the allele that is associated with lower steady-state expression level is also associated with faster mRNA decay rate , as expected if differences in decay rates drive differences in expression levels across individuals ( Figure 5C ) . However , in the remaining 45% of cases , the allele that is associated with lower gene expression levels is associated with slower mRNA decay rates ( Figure 5D ) . This implies a more complicated regulatory mechanism , which counters the effect of decay at these loci to drive opposite patterns of gene expression across individuals ( see Discussion ) . We thus focused only on the 55% of eQTLs-rdQTL sites with concordant genotypic effects , for which a more intuitive and simple mechanistic explanation is likely . We again used the method of Storey et al . [48] and estimated that as many as 19% ( 95% CI by bootstrapping: 15%–21% ) of eQTLs might be regulated , at least in part , by differences in decay rates . We acknowledge that ( as with any comparison and combination of results from genome-wide mapping studies ) any factor that affects the power to find associations may result in a biased estimate of the proportion of eQTLs that are also classified as rdQTLs . It is unclear how one could identify and test for all possible relevant factors . In our analysis , we have taken into account the possible effect of overall gene expression levels on eQTL/rdQTL mapping ( see Methods ) , and confirmed that the distributions of the number of SNPs in the proximal window are similar whether one considers sites classified as either eQTLs only or as eQTLs/rdQTLs ( Figure S9 ) . On the other hand , we did find a difference in the distribution of minor allele frequency , and the distributions of the number of individuals that are homozygote to the minor allele , between eQTLs and eQTLs/rdQTLs ( Figure S9 ) , but this would be conservative with respect to the estimated proportion of eQTLs that are also rdQTLs ( namely , the true overlap might be higher than 19% ) . Using a similar approach , we have previously found that up to 55% of eQTLs might be explained by variation in DNase sensitivity ( these eQTLs were also classified as dsQTLs [32] ) . We expected that the combination of RNA decay data and DNase sensitivity profiles might explain a larger proportion of inter-individual variation in gene expression levels . To test this using LCLs from the 66 individuals used in both the DNase sensitivity [32] and the current study , we first examined the overlap between SNPs identified as either eQTLs , rdQTLs or dsQTLs . In order to standardize the analyses , we re-mapped eQTLs , rdQTLs , and dsQTLs using only the set of 66 YRI LCLs used in both our study and Degner et al . [32] . We identified 1 , 147 eQTLs ( 15% FDR ) , of which 171 were also classified as rdQTLs ( 15% FDR ) and 168 as dsQTLs ( 15% FDR; Figure S10 ) . There is a slight enrichment in the overlap of eQTLs classified as both rdQTLs and dsQTLs ( 33 SNPs; 25 are expected by chance along; P = 0 . 03 ) . This might reflect variation that affects gene expression levels through coupled transcription and decay processes . Put together , 26 . 7% eQTLs are also classified as either rdQTLs and/or dsQTLs . Combining all three annotations ( see Methods; Figure S11 ) we estimated ( by using the Storey method [48] ) that up to 63% of eQTLs could be driven , at least in part , by either decay or chromatin accessibility-related mechanisms . We note that for this comparison we are including both concordant and discordant rdQTLs , since both patterns could be representative of either simpler or complex mechanisms underlying gene expression variation .
In many cases , our observations across genes were consistent with the intuitive model whereby faster mRNA decay rates are associated with lower steady-state gene expression levels . Accordingly , we observed lower and higher steady-state gene expression levels for the most rapidly and slowly decaying genes , respectively . Focusing only on these intuitively simple regulatory interactions across QTLs , we estimated that up to 19% of eQTLs might influence gene expression variation through an effect on mRNA decay rates . Incorporating rdQTLs with data on DNase sensitivity QTLs ( dsQTLs ) , we estimated that a combination of variation in RNA decay rates and chromatin accessibility might explain the majority ( 63% ) of eQTL effects . In addition , we find that SNPs within miRNA binding sites show an enrichment for association with variation in decay rates compared to all 3′UTR SNPs , leading to a hypothesis that variation in miRNA binding plays a particularly important role in regulating decay rate variation . Interestingly , however , we observed many instances of the opposite ( discordant ) relationship between mRNA decay rates and steady-state gene expression levels . Overall , 59% of genes with a significant correlation between decay rates and expression levels across individuals show a discordant relationship ( though only 45% of eQTL/rdQTL pairs ) . The frequency of this phenomenon seems somewhat unexpected especially given the stronger overall concordant relationship between decay and expression when all genes are considered . It may also cast doubt on the mechanistic explanation we offered for the more intuitive – concordant – relationship between RNA decay and gene expression levels . On the other hand , prevalent discordant decay rates and expression levels across genes have been previously observed in yeast . We speculate that these discordant patterns are the result of complex regulatory circuits , which have evolved to address the need for shorter response time or to stabilize steady-state gene expression levels within the cell . Indeed , the majority of genes with discordant decay and expression patterns are known to be involved in biological processes that require fast response time ( Table S3 ) . In a subset of these cases , an auto-regulatory or regulatory feedback circuit has been demonstrated ( Table 1 ) . Since many stress and immune response pathways are activated ( namely , these genes are highly expressed [53] ) in LCLs due to the EBV infection which causes immortalization , we hypothesize that we were able to identify discordant patterns of decay and gene expression at a higher frequency than otherwise expected in resting cells . Discordant differences in the rates of transcription and mRNA decay could be achieved by a coupling of decay and transcriptional regulatory mechanisms . Dori-Bachash and colleagues suggested that discordant patterns between two closely related yeast species might be due to such coupling whereby the same cis elements may regulate both processes [37] . Supporting these findings , Shalem et al . found that PolII binding in yeast could regulate coordinated mRNA synthesis and degradation processes [38] , building on work from Harel-Sharvit et al . that implicated PolII as a factor linking both transcription and mRNA decay to translation in yeast [55] . Additional evidence has pointed to an intrinsic role for the same promoter binding elements promoting both mRNA synthesis in the nucleus and mRNA degradation in the cytoplasm [56] , [57] . Our observations also lend support to an explanation based on coupling of the transcription and RNA decay processes . Such mechanistic coordination implies complex regulatory circuitry , which suggests that decay processes might be playing an important role in maintaining an upper limit of steady-state gene expression , while allowing for rapid transcriptional response - a classical auto-regulatory feedback loop motif [36] . Coupling different regulatory mechanisms to cause such regulatory motifs has been suggested as a way by which cells optimize systems-level functionalities [40] . This is especially important in the context of transcriptional responses to external stimuli or stress . In these situations , coupling of transcription and mRNA decay might be an efficient strategy that allows rapid and precise control of cellular response to external perturbations [40] . Previous studies provided evidence for the important role of mRNA decay in regulating cellular response . For instance , Raghavan et al . found that activation-induced genes in human T-lymphocytes cells , which are enriched for transcriptional regulatory functions , tend to have fast decay rates [52] . Shalem and colleagues evaluated changes in mRNA decay and transcription rates in yeast subjected to either transient or enduring stresses [70] . Yeast subjected to the enduring stress displayed an expected behavior whereby most induced genes were stabilized , while under the transient stress , most induced genes exhibited faster decay rates regardless of their increased steady-state expression levels [70] . Our rdQTL data suggest that variation in regulatory elements that affect mRNA decay rates may play an important role in the individual-specific efficiency of response regulatory circuitry . We have taken some of the first steps towards characterizing the impact of variation in mRNA decay rates on variation in gene expression levels . Our results indicate that decay processes might play a crucial role in fine-tuned genome-wide regulation of gene expression variation in humans . In particular , we found that a moderate proportion of eQTLs might be due to variation in decay rates , and that negative feedback regulatory circuits involving mRNA decay processes may be common in humans . Further study of the mechanisms underlying variation in mRNA decay rates is needed to increase our understanding of the genetic basis of steady-state gene expression levels and the underlying regulatory circuits .
Cell lines were grown using standard procedures ( as recommended by Coriell ) by culturing cells in RPMI 1640 ( supplemented with 2 mM L-glutamine and 15% fetal bovine serum ) . Each of the cell lines was treated with Actinomycin D ( ActD ) to inhibit transcription , with one biological replicate from each cell line . Because ActD terminates active transcript elongation by binding directly to DNA in a reversible manner [12]–[14] , [71] , [72] , it is generally thought to be the most effective transcriptional inhibitor [16] , [18] , [72]–[74] . ActD treatment was performed by culturing cells at a concentration of 750 , 000 cell/ml with 7 . 5 ug/ml of ActD . Based on the results from a pilot experiment ( see Methods S1 , Figure S1 , Figure S2 , Figure S3 ) , we extracted RNA at a total of five timepoints: before the treatment with ActD ( 0 hours ) and after treatment ( 0 . 5 hours , 1 hour , 2 hours , and 4 hours ) . To account for the decrease in total RNA resulting from the treatment and to obtain enough RNA from each timepoint for subsequent microarray hybridization , we increased the number of cells from which we extracted RNA over the timecourse ( Figure S1 ) . Total RNA was extracted using an RNeasy Mini Kit ( Qiagen ) and RNA quality was assessed using an Agilent Bioanalyzer . We estimated gene expression levels in all samples ( 350 total samples across all 5 time points and 70 cell lines ) by hybridizing RNA to the Illumina HT-12 v4 . Expression BeadChip arrays . As RNA yield is expected to change across samples from different time points ( due to RNA decay ) , previous microarray based studies of RNA decay have typically normalized their data using spiked-in samples [3] , [8] , [21] . The Illumina HT-12 arrays , however , do not include non-human probes that would allow us to use spike-ins . Instead , we hybridized the same quantity of RNA from each time point to the microarrays using standard Illumina hybridization protocols . Subsequently , we normalized the array data using standard approaches across all the arrays [27]–[29] , [75] , [76] . All low-level microarray analyses were performed in R using the Bioconductor software package lumi [13] , [31]–[34] , [77] . Specifically , we performed a log2 variance stabilizing transformation and robust spline normalization ( RSN ) . Following normalization , we removed probes with intensities indistinguishable from background noise in either the 0 and/or 4 hour time points on the array ( as measured by the negative controls present on each array ) . In addition , we mapped the Illumina 50 bp probe sequences using BWA v . 0 . 4 . 6 [36] , [78] and retained only probes that mapped uniquely with 100% identity to an exon within an annotated gene from the Ensembl database ( 2009-12-31 version ) . Following filtering based on detection and probe mapping ( see Supplemental Materials ) , data from 23 , 065 probes corresponding to 16 , 823 genes were used for all further analyses . For gene-based analyses , we considered the mean expression across the set of probes corresponding to a single gene as the expression level of that gene . For all genotype analyses , SNPs located within probes could bias probe hybridization and downstream measures of steady-state gene expression across individuals . For the 3 , 327 probes overlapping one or more SNPs , we aimed to remove the effect of SNPs on probe hybridization by regressing steady-state expression levels on the genotype of the SNP located within the probe . In cases where this regression was significant ( P<0 . 05 ) , we used the residual of the regression as the steady-state expression measurement [28] , [29] , [79] . After all normalization and filtering steps , genes whose transcripts decayed at an “average” rate appeared to be expressed at a constant level through the timecourse measurements ( Figure S2 ) . For ease of visualization , the expression levels across time points in all decay profiles plotted throughout this manuscript have been standardized by the total number of cells from which RNA was extracted ( Figure S1 ) . Because mRNA decay has been shown to exhibit properties of first-order decay [11] , [39] , [80] , [81] , we estimated gene-specific RNA decay rates in each cell line by using a regression equation of the form ( a linear transform of the first-order exponential decay model ) : ( 1 ) where y ( t ) is the mRNA abundance at time t , B0 is the mRNA abundance at the untreated time point ( time point ‘0’ ) , k is a gene-specific decay rate constant , and variance ε∼N ( 0 , σ2 ) . For subsequent analyses , we used the gene-specific decay rate constant k as an estimate of a decay rate . Under these conditions , genes with decay rates close or equivalent to the mean cellular decay rate are represented by k = 0 . To identify genes that decay significantly faster or significantly slower than the mean mRNA decay rate in LCLs , we identified genes for which k significantly differed from zero ( mean decay rate ) . We fit gene-wise decay rates for each cell line and identified genes for which least 80% of individuals had estimated values of k that differed significantly from 0 ( P<0 . 1 ) in the same direction ( either faster or slower decay than the mean decay rate ) . To rank genes by their combined gene expression and decay values , we examined the genome-wide distributions . For example , genes with discordant patterns are those with high ( or low ) expression levels and whose mRNA decays rapidly ( or slowly ) . To classify such patterns , we independently identified genes within the top 5% and 10% tails of the decay rate and steady-state gene expression distributions and then considered the overlaps across the two data sets ( Figure S5B ) . We identified 9 and 49 genes at the top 5% and 10% , respectively , of both the gene expression and decay rate distributions . To determine the effect of gene length and 3′UTR length on mRNA decay rates , gene lengths and 3′UTR lengths were calculated using information extracted from the Ensembl gene database ( 2009-12-31 version ) . [41]–[43] , [82] . Total gene length was defined as the distance between the upstream most TSS and the downstream most transcription end site ( inclusive of both exons and introns ) . Total 3′UTR length was calculated as the number of bases annotated as being within a 3′UTR in any isoform of the given gene . In order to create a comprehensive set of microRNA ( miRNA ) binding site predictions , we downloaded the miRNA binding predictions from three databases: microRNA . org , PicTar , and targetScan [3] , [19] , [20] , [22]–[25] , [44]–[47] . By parsing the predictions for all miRNAs in these three databases , we obtained a combined set of miRNA predictions that were present in one , two , or all three databases . Because each of these databases uses different sets of annotations and identifiers , we applied a series of conversion and filtering steps for each database ( see Methods S1 for details ) . We used the AREScore algorithm ( http://arescore . dkfz . de/arescore . pl ) [26] , [44] , [49] , [50] to calculate an AREScore as a proxy for the number of AU-rich elements present in 3′UTRs . The program was run with default parameters on RefSeq defined 3′UTR regions for all genes in our dataset [1] , [3] , [41] , [51] , [52] , [83] . To identify significantly over- or under-represented motifs in either fast or slow decaying genes , we used the FIRE algorithm ( https://tavazoielab . c2b2 . columbia . edu/FIRE/ ) [30] , [41] . We tested for motif enrichment in promoter regions and full gene bodies of both fast and slow decaying genes , using default FIRE parameters . In all tests , we compared against a background set of all genes that were present in our study . We used GeneTrail ( http://genetrail . bioinfo . uni-sb . de ) [15] , [26] , [84] to test for enrichments of functional annotations among different classes of genes: ( a ) genes consistently decaying faster or slower than the mean cellular decay rate , ( b ) genes at the top 10% of both the gene expression and decay rate genome-wide distributions , and ( c ) genes showing either concordant or discordant relationships between decay rates and gene expression levels . In all tests , we used a background set of all genes that were present in our study and detected as expressed in either the zero or four hour timepoints . The tests were performed using all GO categories and KEGG pathways . We calculated p-values using a hyper-geometric distribution and report false discovery rates for each p-value . To investigate the contribution of variation in decay rates to overall variation in steady-state gene expression levels across individuals , we identified genes whose expression levels and decay rates were significantly correlated . Specifically , for each gene , if yi denotes the steady-state expression level ( defined here as the mean of the expression levels across all time points in order to increase statistical independence from the estimated decay rates ) for individual i and ri denotes the corresponding decay rate estimate , we fit a linear model of the form: ( 2 ) where the coefficient , β , measures the strength of the association between decay rate and steady-state gene expression levels . In order to identify genes where the coefficient , β , represents a significant association , we repeated the analyses with 3 sets of permuted decay rates , recorded the significance of β from each permutation , and used these permuted p-values as an empirical null distribution . We estimated the FDR by comparing the true distribution of p-values of β to this null distribution . PolII ChIP-seq data on six YRI LCLs ( GM18505 , GM18522 , GM19141 , GM19193 , GM19204 , and GM19238 ) were collected within the context of another study within the lab . ChIP-seq libraries were prepared as described previously [11] , [54] , [85] , using the non PolII antibody H-224 ( Santa Cruz Biotechnology , sc-9001x ) . In addition , raw PolII ChIP-seq reads from a seventh YRI LCL , GM19099 , was obtained from a previously published study [11] , [33] , [47] and analyzed in a similar fashion to the PolII ChIP-seq data generated in-house . Raw PolII ChIP-seq reads were mapped back to human genome ( hg18 ) using BWA v . 0 . 4 . 6 [11] , [54] , [78] and reads from multiple lanes from the same individual were combined into a single mapped file . For each individual , we used Samtools [6] , [86] to isolate reads in genic regions ( as defined in the Genomic Annotations section above ) and promoter regions ( defined as 1 kb upstream and 1 kb downstream of the transcription start site ) . For genic regions , read counts were normalized by the total length of the genic region to be able to compare across genes with varying length . For individual-specific measures of PolII occupancy for each gene , read counts were normalized by the total number of mapped reads per individual . For all QTL mapping analyses , we used close to full genotype information for each of the 70 YRI individuals , achieved by combining available datasets and imputing missing genotypes with the BimBam software [58] , [87] , [88] as described previously [32] , [59] , [60] . Briefly , we built a reference panel consisting of the largest set of all 210 YRI HapMap individuals and gathered genotypes for any SNP or short insertion/deletion ( indel ) called in either HapMap ( Release 28; October 2010 , [1] , [35] , [59] ) or 1000 Genomes ( May 2011 interim phase 1 release , [1] , [52] , [60] ) datasets . Missing genotypes in the individuals in this study were imputed using this reference panel , resulting in a total of approximately 15 . 8 million variants genome-wide . All associations between genotypes and either decay rates or gene expression were examined using a linear regression model in which each phenotype was regressed against genotype . For all analyses , we only tested association under the assumption that SNPs affected the resulting phenotype in an additive manner ( i . e . heterozygote phenotypic mean equals the average of the two homozygote means ) . For each gene , we tested for association of the phenotype with the genotypes of SNPs and indels within a cis-candidate region of 25 kb around the gene ( 25 kb upstream of the TSS and 25 kb downstream of the TES ) . We chose this definition of a cis-candidate region to map variation in mRNA decay rates in an unbiased manner by including SNPs outside of transcript regions . Indeed , recent reports have indicated that elements in intergenic promoter elements [56] and RNA binding proteins binding intronic regions [89] could regulate mRNA decay mechanisms . To evaluate genotypic effects on decay variation for a given gene , we tested associations with SNPs or indels with a minimum allele frequency greater than 10% , using the following model: ( 3 ) where ri is defined as in model ( 2 ) and gij corresponds to the genotype of individual i at variant j , coded as 0 , 1 , or 2 copies of the minor allele . In this model , the coefficient γ indicates the strength of association between the mRNA decay rate of the gene and genotypes at variant j . To estimate the false discovery rate , we permuted phenotypes three times , re-performed the linear regressions , and recorded the minimum p-value ( across SNPs/indels ) for each gene for each permutation . These sets of minimum p-values were used as our empirical null distribution . We estimated the FDR by comparing the true distribution of the minimum p-values to this null distribution , as previously described . Previous studies mapping cis-associations have found that statistical power to detect associations can be dramatically increased by accounting for unmeasured confounders within quantitative measure of the phenotype [3] , [12] , [13] , [31] , [32] , [41] , [90] , [91] . When considering decay as the phenotype , we did so by performing principal components analysis ( PCA ) on the ( 70 by 70 ) correlation matrix of decay rate estimates . We found the strongest rdQTL signal ( largest number of findings at a fixed FDR ) when 13 principal components ( PCs ) were regressed out . When considering steady-state gene expression as the phenotype , we performed all analyses on mean expression levels across all time points per individual in order to reduce the variance of expression measurements and increase the statistical independence between the eQTL estimates and the estimates of decay rates . We quantile normalized these measurements and performed PCA to account for unmeasured confounders . For the eQTL analyses , we again found the most QTL signal when 13 PCs were regressed out . The eQTL analyses were performed by testing for association between mean expression levels and SNPs or indels with a minimum allele frequency greater than 10% , using the following model: ( 4 ) where yi is defined as in model ( 2 ) and gij corresponds to the genotype of individual i at variant j . In this model , the coefficient γ indicates the strength of association between the mean steady-state expression level of the gene and genotypes at variant j . FDR calculations were performed as described above . To assess whether the enrichment of significant mRNA decay effects among eQTL SNPs could occur by random chance , we performed a permutation based significance test . Specifically , we evaluated the effect of genotype on mRNA decay variation using the most significant cis-eQTL SNP for all genes in our dataset ( regardless of the genome-wide significance of the SNP ) . Then , we randomly chose 1 , 257 SNPs from this full set ( representing the number of genome wide significant eQTLs identified ) and calculated the number that showed significant association with mRNA decay variation among this set . We also ensured that the distribution of gene expression levels associated with the randomly sampled SNPs matched the distribution of expression levels for genes with significant eQTLs . By repeating this 1 , 000 times , we were able to arrive at a permutation-based expectation for the enrichment of significant mRNA decay effects among eQTL SNPs . In order to look at overlaps between the set of identified rdQTLs and previously identified dsQTLs , we focused on the set of 66 YRI LCLs that were used in both studies . Using mean gene expression measures from this study , we re-mapped eQTLs as described above in this set of 66 LCLs and identified 1 , 147 steady-state eQTLs ( 15% FDR ) . Using these 1 , 147 eQTL SNPs , we tested for association between each SNP and DNaseI sensitivity as described previously [32] and between each SNP and RNA decay rates ( as described above ) . To obtain an estimate of the total proportion of eQTLs we might be able to account for by either RNA decay variation or variation in DNaseI sensitivity , we assessed , for each SNP , the evidence for association with either data type . We then chose the minimum p-value for the association with decay rates or DNaseI sensitivity and compared the resulting distribution to the following analytical transformation:We then applied the Storey et al . qvalue approach to account for incomplete power [48] to this transformed distribution of p-values . All raw data and tables of all rdQTLs are available under GEO accession number GSE37451 .
|
Recent studies of functional genetic variation in humans have identified numerous loci that are associated with variation in gene expression levels , called expression quantitative trait loci ( eQTLs ) . The mechanisms by which these loci affect gene expression , however , are still largely unknown . Specifically , since most studies rely on measures of steady-state gene expression levels , they are unable to distinguish between the relative influences of either transcriptional- or decay-related processes . To address this gap , we examined the specific impact of mRNA decay processes on steady-state gene expression levels for over 16 , 000 genes in human lymphoblastoid cell lines . By characterizing decay rates in 70 individuals , we show that steady-state expression levels are significantly influenced by variation in decay rates for 10% of genes . Yet , for roughly half of these genes , we find that individuals with higher expression levels also have faster decay rates . This pattern points to a non-simple mechanistic interplay between transcriptional and decay processes , especially for genes involved in rapid cellular responses . Finally , we identify 195 genetic variants that are significantly associated with both gene expression variation and variation in mRNA decay rates . Using these data , we estimate that that a substantial fraction of eQTLs are associated with inter-individual variation in mRNA decay rates .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"genome-wide",
"association",
"studies",
"genome",
"expression",
"analysis",
"functional",
"genomics",
"rna",
"stability",
"genome",
"analysis",
"tools",
"gene",
"expression",
"biology",
"molecular",
"biology",
"microarrays",
"genomics",
"molecular",
"cell",
"biology",
"computational",
"biology",
"genetics",
"and",
"genomics"
] |
2012
|
The Contribution of RNA Decay Quantitative Trait Loci to Inter-Individual Variation in Steady-State Gene Expression Levels
|
Pathogenesis studies of SIV infection have not been performed to date in wild monkeys due to difficulty in collecting and storing samples on site and the lack of analytical reagents covering the extensive SIV diversity . We performed a large scale study of molecular epidemiology and natural history of SIVagm infection in 225 free-ranging AGMs from multiple locations in South Africa . SIV prevalence ( established by sequencing pol , env , and gag ) varied dramatically between infant/juvenile ( 7% ) and adult animals ( 68% ) ( p<0 . 0001 ) , and between adult females ( 78% ) and males ( 57% ) . Phylogenetic analyses revealed an extensive genetic diversity , including frequent recombination events . Some AGMs harbored epidemiologically linked viruses . Viruses infecting AGMs in the Free State , which are separated from those on the coastal side by the Drakensberg Mountains , formed a separate cluster in the phylogenetic trees; this observation supports a long standing presence of SIV in AGMs , at least from the time of their speciation to their Plio-Pleistocene migration . Specific primers/probes were synthesized based on the pol sequence data and viral loads ( VLs ) were quantified . VLs were of 104–106 RNA copies/ml , in the range of those observed in experimentally-infected monkeys , validating the experimental approaches in natural hosts . VLs were significantly higher ( 107–108 RNA copies/ml ) in 10 AGMs diagnosed as acutely infected based on SIV seronegativity ( Fiebig II ) , which suggests a very active transmission of SIVagm in the wild . Neither cytokine levels ( as biomarkers of immune activation ) nor sCD14 levels ( a biomarker of microbial translocation ) were different between SIV-infected and SIV-uninfected monkeys . This complex algorithm combining sequencing and phylogeny , VL quantification , serology , and testing of surrogate markers of microbial translocation and immune activation permits a systematic investigation of the epidemiology , viral diversity and natural history of SIV infection in wild African natural hosts .
Over 40 African nonhuman primate ( NHP ) species are naturally infected with simian immunodeficiency viruses ( SIVs ) [1]–[3] . Among these , African green monkeys ( AGMs ) ( Chlorocebus genus ) are the most numerous , most widely geographically spread and most commonly infected with SIV in the wild [1] . According to Groves [4] , [5] , AGMs are divided into species that are phenotypically and geographically distinct: vervets ( C . pygerythrus ) are the most widely spread in East and Southern Africa , ranging from the eastern Rift Valley in Ethiopia , Somalia and extreme southern Sudan to the Cape region in South Africa; grivets ( C . aethiops ) inhabit the area east of the White Nile in Ethiopia , Somalia from Khartoum to Mongalla , Eritrea and Ethiopia south to the Omo; tantalus monkeys ( C . tantalus ) are the prevalent species in north Central Africa from Ghana to Sudan and Kenya; green monkeys ( C . sabaeus ) reside in West Africa from Senegal to the Volta River , and have been introduced to Cape Verde Island as well as to the Caribbean [4] . A fifth AGM species , the malbrouck ( C . cynosuros ) , is located in Central and South-Central Africa ranging from the Albertine Rift in the Democratic Republic of Congo to the Atlantic coast and Northern Namibia and Zambia . Finally , a sixth species , the Bale Mountain vervet ( C . djamdjamensis ) has a very limited distribution in the bamboo forests of highland Ethiopia . This taxonomic classification , however , is not universally accepted [6] . With the exception of the malbrouck and the Bale mountain vervet , each of the AGM species have been shown to be infected in the wild with species-specific SIVagm ( defined as SIVagmVer , SIVagmGri , SIVagmTan and SIVagmSab ) [7]–[11] , with the reported prevalence rates ranging from30 to 50% [8] , [12]–[19] . Phylogenetic analyses of SIVagm strains have shown that the spectrum of genetic diversity of SIVagm surpasses that of other primate lentiviruses [7] , [9] , [19]–[21] , presumed to be due to codivergence/host-dependent evolution ( i . e . , the evolution of SIVagm from grivet , vervet , tantalus and green monkey species occurred in concert with host speciation ) [8] , [10] , [11] . Together , these findings indicate that AGMs have coexisted with SIVagm for a long period of time , possibly even before their radiation and divergence from their common ancestor , approximately 1 . 5–3 million years ago [22] . Pathogenesis studies support an ancient coevolutionary relationship by showing that SIVagm are highly adapted to their hosts and that SIVagm-infected AGMs generally do not progress to AIDS [23] , [24] . Key features of SIVagm infection in AGMs , as established by experimental studies performed on captive AGMs , include: ( i ) active viral replication , with set-point viral loads ( VLs ) similar to or higher than those found in HIV-infected patients [25]–[29]; ( ii ) significant depletion of CD4+ T cells during acute infection [25] , [26] , [30] , [31] , followed by rapid restoration to near preinfection levels in the peripheral blood [17] , [25] , [26] , [30] , [31] and delayed and incomplete restoration at mucosal sites [30]; ( iii ) maintenance of the balance between Th17 and T regulatory cells , due to preservation of the Th17 cell subset [32]; ( iv ) vigorous but transient inflammatory responses to the virus during acute infection , which are resolved with the transition from acute-to-chronic infection [30] , [33] , [34]; ( v ) productive infection of short-lived cells [31]; ( vi ) partial control of virus replication by the adaptive immune responses to SIV [35]–[41]; ( vii ) no significant increase in CD4+ T cell apoptosis during either acute or chronic infection [30] , [42] , [43] . These normal levels of CD4+ T cell apoptosis together with preservation of Th17 cells probably allow AGMs to avoid enteropathy , breaches in the mucosal barrier and subsequent microbial translocation ( MT ) [30] , as well as chronic immune activation and disease progression , while allowing CD4+ T cell recovery in the presence of high VLs [30] , [44] . Furthermore , similar to other natural hosts of SIVs [45] , AGMs have a number of adaptations that spare CD4+ T cells from virus-mediated killing in vivo . These features include a lower fraction of CD4+ T cells expressing the CCR5 coreceptor [46] , [47] and down-regulation of the CD4 molecule by T helper cells as they enter the memory cell pool [48]–[50] . Altogether , these adaptations support the concept that the benign course of SIV infection in natural hosts is the result of coevolution over millennia [1] , [51] . The ancestry of SIV infections and the codivergence of SIV types with their host species , however , could be accounted for by a model of preferential host-switching [52] . In the case of AGMs it has recently suggested that the phylogenetic profiles of SIVagm can be explained by a pattern of west-to-east transmission of the virus across existing AGM geographic ranges and that the viral divergence may have occurred more recently than previously suggested [53] . This study included only a small number of SIV strains covering a limited geographical distribution , which may have biased a full appreciation of the phylogenetic relationships and ancestry of SIVagm from different AGM species and likely altered the timing calculations for SIVagm emergence . A recent study in which calibration of molecular clocks was based on biogeographical features , reported that SIVs are actually older than estimated based on molecular clock calculations only [2] . The major focus of studies carried out thus far in wild African NHP species has been on identification and characterization of species-specific SIVs [54] , [55] . A common denominator of these studies has been the difficulty of obtaining samples from wild animals and the lack of research infrastructure for pathogenesis studies in the field . Several approaches have been used to circumvent these limitations: ( i ) estimation of the SIV prevalence in captive monkeys , which significantly underestimates the prevalence in the wild , as most monkeys are captured at a young age and maternal-to-infant transmission rates are low in African NHP species [56]; ( ii ) use of bush meat samples . These are easy to obtain and thus this strategy has proven instrumental in identifying numerous SIVs and generating meaningful prevalence data [2] , [57]–[62] . However , bush meat samples tend to be from adult populations and do not permit viral isolation or assessment of critical parameters of infection , such as VLs , immunophenotyping or assessment of the levels of immune activation; and ( iii ) use of noninvasive sampling ( i . e . , collection of fecal or urine samples ) , which has also been instrumental in assessing the prevalence of SIV infection in natural hosts , most notably in identifying and characterizing the animal reservoir of pandemic HIV strains [63]–[67] . However , similar to the use of bush meat samples , noninvasive samples cannot be used to assess key parameters of SIV infection . Thus , although SIVs have been identified and characterized for over two decades , studies of the natural history of SIV infection in the wild have only been performed at a cursory level [1] , [54] , [68] . Here , we performed for the first time in an African NHP host , a comprehensive large-scale characterization of the epidemiology and natural history of SIV infection in vervet monkeys living freely in different parks , nature reserves and farms from three provinces of the Republic of South Africa , to validate the virological and immunological features of experimental studies in natural hosts .
Blood samples were collected from two hundred and twenty-five wild-trapped vervets over a 4 . 5 month period . Details on monkey capture and sample collection are presented as Supplementary information . The samples included represent 11 populations from 9 parks , game reserves and farms located in 3 provinces of South Africa–the Free State , KwaZulu-Natal , and Eastern Cape–covering majority significant proportion of vervet habitat in this region ( Figure 1 ) . Both sexes were equally represented . Samples from infants ( <1 year old ) and juvenile AGMs were included ( Figure 1 ) . Diagnosis of SIVagmVer infection was performed by PCR , which allows for the evaluation of SIVagm diversity in addition to prevalence estimates . Also , in infants , PCR permits the diagnosis of infected offspring ( as opposed to serological assays which are not specific , i . e . , may also detect passively transmitted maternal antibodies ) . RNA was extracted from all plasma samples and subjected to RT-PCR analysis using consensus primers designed to amplify a 600-bp fragment in pol integrase and a 900-bp fragment in the gp120 gene encompassing the V3–V5 regions and the 5′ end of the gp41 gene . In addition , gag PCR ( 846 bp fragment in the p24 gene ) was performed on selected samples from each location . This analysis identified 103 AGMs that were virion RNA ( vRNA ) positive using one , two or three primer sets ( Table 1 ) , giving an overall prevalence of SIVagmVer infection of 59% ( 73/123 ) in females and 29% ( 30/102 ) in males , in the range of those found in previous reports in AGMs [8] , [15] , [17] . Prevalence levels were relatively similar between different locations ( Table S1 ) and higher than in a cohort of semifree animals ( Table S2 ) . SIVagm prevalence was very uneven in different age groups: 7% ( 3/44 ) in infants ( males: 4% , 1/26; females: 11% , 2/18 ) , 16% ( 9/58 ) in juveniles ( males: 15% , 5/34; females: 21% , 4/21 ) and 71% ( 91/128 ) in adults ( males: 57% , 24/42; females: 78% , 67/86 ) . Thus , we confirmed on a very large number of samples previous results reporting that a dramatic increase in the SIVagm prevalence and incidence occurs with the passage to sexual maturity in AGMs [16] . Interestingly , and different from previous reports , we identified cases of SIVagmVer infection in very young AGMs , which may be suggestive of vertical transmission of the virus in the wild . To determine the relationships of the newly identified SIVagm strains to each other and to previously characterized SIVagm strains , we constructed phylogenetic trees from amplified pol and env nucleotide sequences using a maximum likelihood approach ( Figure 2 and Figure S1 ) . While newly identified SIVagmVer strains naturally infecting vervets from South Africa exhibited a high genetic diversity , with average genetic distances in the pol gene of 16 . 2±4 . 8% , phylogenetic analyses also identified SIVagm strains that differed in less than 2% of their pol and env nucleotide sequences , indicating epidemiologically linked infections ( Figure 2 and Figure S1 ) . In general , strains originating from vervets from the same area clustered together ( Figure 2 ) with a few exceptions that are probably due to male migration between groups when they reach sexual maturity . As expected , phylogenetic analyses showed that SIVagmVer strains from South Africa clustered with the SIVagmVer reference strains ( Figure 2 and Figure S1 ) and were only distantly related to the SIVagm strains from other AGM species ( Figure 2 ) . Furthermore , the newly characterized SIVagmVer strains from South Africa formed a subcluster within the SIVagmVer group , in agreement with the fact that all the reference strains available thus far have a distinct geographical origin , being collected from vervets in Kenya , Ethiopia and Tanzania [9] , [19] , [20] . Average genetic distances between the reference SIVagmVer strains ( collected from Ethiopia , Kenya and Tanzania ) and the newly characterized SIVagmVer strains were 25 . 4±2 . 1% , significantly higher than the overall genetic distances between South African strains ( p<0 . 0001 ) ( Table S3 ) . Similar to previous reports [66] , comparison between the pol and env tree topologies showed numerous differences ( Figure 2 and Figure S1 ) , indicating extensive recombination within the SIVagm radiation ( Figure S2 ) . Mosaic branches occurred both near the tips of the trees and deeper in the trees , indicating that extensive recombination events have occurred throughout the evolutionary history of SIVagmVer [66] . This high frequency of recombinations between divergent SIVs indicates that SIVagm coinfection and/or superinfection occur frequently in wild vervets . Remarkably , a geographically-associated clustering pattern can be defined for the South African SIVagmVer strains , with all but one of the SIVagmVer sequences from AGMs inhabiting different areas in the Free State forming a monophyletic cluster in the phylogenetic trees ( Figure 2 and Figure S1 ) . Bootstrap analysis strongly supports a single origin of the Free State cluster , however parental nodes were associated with lower bootstrap support in the pol tree , suggesting ambiguity as to where the root of the Free State cluster should be placed . Lower bootstrap support may be indicative of recombination; a SplitsTree analysis shows that some KwaZulu-Natal sequences are likely to be recombinants of East Coast sequences , indicating a mixing between these two populations ( Figure S2 ) . Interestingly , the SplitsTree analysis also identified one Free State sequence ( VMT17083-IM-Gariep_FS ) as potentially stemming from a distant recombination event with outgroup SIVagmVer sequences , this may suggest that this sequence is in fact a recombinant with an unknown parent ( Figure S2 ) . The most likely explanation for these phylogenetic relationships is that the Drakensberg Mountains acted as a barrier to separate the vervet populations . We estimate that this separation could have occurred in a time frame ranging from 3 million years ago ( during the AGM spread throughout sub-Saharan Africa ) to 100 , 000 years ago ( during the mass migrations that occurred in the Plio-Pleistocene glacial periods ) . We tested this hypothesis by calibrating a relaxed molecular clock to specify the time to the most recent ancestor ( TMRCA ) of the SIVagm samples surrounding the Drakensberg Mountains range to a time-frame spanning 100 , 000 to 3 , 000 , 000 years since the present for the env tree , and in the pol tree we additionally included SIV strains from several species and further calibrated the tree based on isolates from Bioko Island [2] . According to this analysis , divergence of the Free State lineage is likely to be closer to the 100 , 000 year mark , with mean most recent common ancestor ( MRCA ) for the South African SIVagm strains estimated at 329 thousands of years ( kYa ) ( with 95% highest posterior density of 100–1 , 077 kYa ) and 104 kYa ( 100–112 kYa ) , in the env tree ( Table S4 ) and pol tree ( Figure 3 and Table S4 ) , respectively . This analysis places the root of the SIV tree older than previous studies [2] , with the env tree giving a time estimate of SIV endemicity in simian species for 790 kYa ( range: 151–2 , 595 kYa ) , and the pol tree indicating 248 kYa ( range: 189–317 kYa ) ( Table S4 ) . SIVagmVer envelope sequences ( 909 bp ) encompassing the V3–V5 regions of the surface ( SU ) envelope glycoprotein and the 5′ end of the transmembrane ( TM ) domain were amplified by nested PCR from 48 plasma samples . Alignment of their deduced amino acid sequences with those of published reference SIVagm strains from all four species of AGMs identified hypervariable ( V3–V5 ) as well as conserved envelope domains ( Figure 4 ) , as reported previously [10] . Regions corresponding to HIV-1 envelope domains of known function , including the envelope glycoprotein precursor cleavage site , the CD4 binding domain and the viral fusion peptide ( N-terminus of gp41 ) were all highly conserved ( Figure 4 ) . Also conserved were the majority of cysteine residues ( 11 of 12 ) and , as reported previously [10] , [18] , there was very little sequence variability in the region that corresponds to the hypervariable V3 loop of HIV-1 . Pairwise amino acid sequence comparisons were performed to examine the extent of SIVagmVer genetic diversity in the PCR amplified envelope fragment . As for the pol sequence analysis , env analysis revealed that SIVagmVer sequences collected from monkeys in the Free State form a distinct cluster from the monkeys living on coastal areas from both KwaZulu Natal and Eastern Cape provinces ( Figure S1 ) . This separate cluster was supported by both specific sequence signatures in the Free State-originating strains and by smaller genetic distances between these strains ( Figure 4 and Figure S1 ) . Thus , sequence analysis identified: ( i ) a high diversity of SIVagm in South Africa , with the viruses collected from AGMs in the Free State forming an independent cluster , clearly separated from the strains collected from AGMs on the Indian Ocean coast; ( ii ) high frequency of recombination , suggestive of extensive transmission of the virus; and ( iii ) occurrence of highly related strains , suggestive of identifiable transmission clusters . It is generally assumed that SIV infection is nonpathogenic in natural hosts [23] , [51] , [56] . However , this paradigm was recently challenged by studies demonstrating that SIVcpz has a substantial negative impact on the health , reproduction and lifespan of chimpanzees in the wild [68]–[70] . We therefore took advantage of this unique sample set to assess for the first time the natural history of SIV infection in a natural host monkey species in the wild . During sample collection , all included AGMs had a thorough clinical assessment . None of the vervets presented with any of the clinical signs associated with SIV infection , including fever , weight loss , lymphadenopathy or opportunistic infections . Although the cross-sectional nature of this study precludes assessment of changes in monkey weight and thus a direct assessment of weight loss , we performed comparative analyses of the body mass index ( BMI ) between SIV-positive and SIV-negative monkeys and showed that SIV status does not have an impact on normal weight of wild vervets ( Figure S3 ) . Coreceptor usage by the different SIV strains may have a significant impact on the natural history of SIV infection in the wild . Previous studies reported that SIVagmSab strains have the ability to use the CXCR4 coreceptor for viral entry , in addition to CCR5 [26] . Since the amounts of plasma available from the AGMs in South Africa precluded in vitro phenotypic testing of coreceptor usage by these new strains , we estimated coreceptor use in silico by analyzing the V3 region . V3 sequence impacts SIVmac and SIVagm tropism [71]–[73] . The algorithms for genotypic assessment of coreceptor usage based on the HIV-1 V3 sequences cannot be implemented for SIV [74] , [75] . We therefore assessed the overall net charges of the V3 loop for these sequences and found that all the viruses exhibited the same V3 loop net charge ( +7 ) , similar to that of other SIV strains that are documented to use CCR5 [1] . No significant differences in the potential N-glycosylation sites located in the V3–V5 region could be documented for the newly derived SIVagmVer strains from South Africa ( Figure 4 ) . We therefore inferred that SIVagmVer strains identified here likely use CCR5 as the major coreceptor for entry , similar to the majority of SIV isolates [26] , [40] , [76] . The levels of chronic viral replication are highly predictive of the outcome of HIV-1 infection [77] , [78] and as we previously reported , may also predict the outcome of SIV infection in natural hosts , as the handful of African NHPs reported to progress to AIDS exhibited higher chronic VLs than nonprogressors [79] . To date , VLs in natural hosts of SIVs such as AGMs , sooty mangabeys and mandrills have only been assessed in either experimentally intravenously-infected monkeys [25] , [80]–[84] or captive naturally infected monkeys [17] , [28] , [29] , [79] , [85] , [86] . Only one study reported VLs in wild African monkeys on a very limited number of samples [85] . We used the generated SIVagmVer pol sequences to design specific primers and probes for viral quantification . The integrase region amplified by the pol primers used in our study is relatively well conserved; thus , the primers and probe had an excellent coverage of SIVagmVer diversity . We then quantified the VLs in 87 available samples from the 103 SIVagmVer-infected vervets . Results are shown in Figure 5 . Plasma SIVagmVer VLs ranged from 104 to 107 copies/ml and were higher in the juvenile than in adult AGMs , albeit this difference was not statistically significant . At least 23 of the 49 SIVagm-infected dams for which the VLs were available ( 47% ) were documented as lactating at the time of sampling ( Figure 5 ) . The VLs of lactating dams are detailed in Figure 5 and demonstrate a large exposure of infant AGMs to SIV through breastfeeding . While VLs of the majority of SIVagm-infected animals fell within a relatively close range , consistent with the range previously reported in experimentally infected African NHPs that are natural hosts of SIV [27] , VLs were higher than expected in approximately 10% of vervets ( Figure 5 ) . Since such high VLs were observed in the majority of juvenile AGMs , we reasoned that they may be recent infections [27] . High levels of viral replication observed around the peak of VLs during acute HIV/SIV infection generally occur prior to seroconversion [87] and correspond to the Fiebeg II stage of HIV-1 infection [87] . Hence , to stage the SIVagm infection in AGMs with high VLs , we further designed a gp41 peptide ELISA and assessed the levels of anti-SIVagm antibodies in the available samples . As shown in Figure 6 , the majority of SIVagm-infected AGMs harbored detectable levels of anti-gp41 antibodies . Conversely , most of the AGMs presenting with high VLs were seronegative . Altogether , these results strongly suggest that AGMs with high VLs were in the acute stage of infection [87] . Note , however , that definitive proof in support of this conclusion would rely on serial sampling and demonstration of seroconversion and partial control of viral replication [87] . Interestingly , serological testing showed that the majority ( 72% ) of the plasma samples collected from infant AGMs were seropositive for SIVagm ( Figure 6 ) , while SIVagm could be amplified from only 3 of the infant samples ( Figure 2 and Table 1 ) , suggesting passive transfer of maternal antibodies and documenting massive in utero exposure of AGM offspring to SIVagm . In conclusion , monitoring the viral replication and the anti-gp41 antibodies in SIVagmVer-infected AGMs allowed us to demonstrate that: ( i ) naturally occurring chronic SIV infection in a natural host is characterized by high VLs , which are in the same range as in experimentally-infected animals [27]; ( ii ) SIVagm transmission is very active in the wild; and ( iii ) the relatively low prevalence of SIVagm infection in offspring strongly contrasts with their massive in utero and breastfeeding exposure . Both SIV-infected AGMs and SMs were reported to maintain the integrity of mucosal barrier and thus to control MT [30] , [84] , which has been reported to be the main factor behind increased immune activation that drives disease progression in pathogenic HIV/SIV infections [88] , [89] . To assess MT in wild vervets , we tested the levels of sCD14 as a surrogate biomarker . As shown in Figure 7 , the levels of sCD14 were similar between SIV-infected and SIV-uninfected AGMs and were in the range of those we previously documented in captive uninfected and experimentally-infected AGMs . Even the samples collected from acutely infected monkeys did not show a significant increase in the levels of sCD14 , in agreement with our previous results from captive experimentally infected AGMs [30] , [90] , and suggesting that wild SIVagm-infected AGMs maintain the integrity of the mucosal barrier . Finally , to assess the immune activation status between SIVagm-infected and uninfected AGMs in the wild , we measured and compared the levels of a large array of cytokines and chemokines in the available samples collected from the two groups in a Luminex assay . As shown in Figure 8 , there was no significant increase in the cytokine/chemokine levels between SIV-infected and uninfected AGMs , with the exception of IL-6 . In general , these cytokine/chemokine levels were in the same range of those previously reported by us and others [34] in captive uninfected and experimentally-infected AGMs during the chronic stage of SIVagm infection . This difference was mainly due to elevated levels of IL-6 in four of nine acutely-infected monkeys tested . When these samples were removed from the analysis , there were no significant differences in the levels of IL-6 between infected and uninfected AGMs . The increases in IL-6 probably reflect the transient increase in the levels of immune activation previously reported to occur during acute SIV infection in natural hosts [30] , [33] , [34] , [91] . Thus , our analyses demonstrate the maintenance of the mucosal barrier and the lack of increased immune activation in acutely and chronically-infected AGMs in the wild . Immune activation being the major determinant of disease progression in pathogenic HIV/SIV infections , our results further support the clinical assessment of a benign outcome of SIV infection in wild AGMs .
Vervets are abundant throughout East Africa along the Indian Ocean coast . However , most studies carried out thus far focused only on vervets from Northeast Africa ( Kenya , Ethiopia and Tanzania ) [14] , and reported an SIVagmVer prevalence rate of 50% [17] . Conversely , our large-scale survey of SIVagm prevalence and diversity in vervets includes samples collected from all age groups and from multiple locations in South Africa . We confirm that the overall prevalence of SIVagm infection in the wild is high ( 46% ) , supporting the notion that SIVagm is uniformly distributed and widespread in AGMs [15] , [16] , [93] . These prevalence levels are similar to those previously reported for sooty mangabeys [66] , [94] , [95] and mandrills [96] , which are among the most commonly infected NHP species known to date . For the first time , we document that one of the reasons for such extensive spread of SIV in wild vervets is the high steady-state SIVagm replication which probably facilitates virus transmission between AGMs through sexual contact [97] . SIVagm prevalence is higher in AGM females than in males . This difference is not surprising given that SIVagm transmission has lower efficacy through the foreskin compared to vaginal exposure [98] and that most males are expected to have significantly lower exposure , as only a few attain the dominance status necessary for sexual access to breeding females [99] . Note , however , that the robust levels of prevalence in males may be explained by the observation that despite the sexually restrictive nature of male dominance hierarchies in vervets , many subordinate males in multimale , multifemale groups can gain sexual access to females through a number of strategies [100]–[102] , and thus become infected [103] . The relatively long breeding season , which lasts up to three months , may also reduce the ability of the alpha male to effectively monopolize fertile females , and increase the chances of transmission through sexual contact in subordinate males [104] . Furthermore , SIVagm transmission between males probably also occurs through aggressive , blood-exposing contacts for dominance , similar to other species [105] , as many of the males sampled had open wounds or scars from such contact . Additionally , many females show marked aggression against dispersing males attempting to migrate into their social groups , often resulting in serious injury , providing another route of infection between males and infected females [106] . The very uneven distribution of SIVagm infection among different age groups strongly supports the sexual route as the main transmission route for SIVagm , together with a significantly less effective maternal-to-infant transmission . The low rates of mother-to-infant transmission are paradoxical , as our study documented large SIVagm exposure of the offspring both in utero and through breastfeeding . The rates of maternal-to-infant transmission in wild AGMs are significantly lower than the 35 to 40% mother-to-infant transmission rates reported in HIV infection ( http://www . unaids . org ) or 40–70% transmission rates in rhesus macaques [107] and are likely the result of virus-host coadaptation [97] . It is also possible that , similar to previous reports in captive sooty mangabeys and AGMs [108] , [109] , SIV infection of infant AGMs is associated with significantly lower levels of viremia than infection of adult monkeys , which may therefore go undetected by our assay . Also conceivable is that , in addition to sexual and maternal-to-infant routes , a nonnegligible proportion of SIVagmVer transmissions occur through biting or fighting , as injuries are frequent ( in our study sample , 10% of vervets showed signs of recent injuries that could result in exposure , such as deep lacerations ) . Injuries preponderantly occur during the mating season , due to both male transfer and to contests for dominance between males , and are usually cleaned by licking , which may involve many different individuals and may explain identification of near-identical viruses in vervets which are not direct mating partners . Studies have shown that monkeys are highly susceptible to SIV infection through oral exposure [110] , [111] , and the high levels of systemic viral replication documented in wild vervets may facilitate oral transmission during wound cleaning . At least 10% of the cases of SIVagmVer infection in our group were recent infections ( defined by high levels of viral replication close to the peak VL and negative serologies ) . Recent infections tend to occur in a narrow time frame ( 10–12 days postinoculation in experimentally infected macaques and African NHPs [27] and 3 weeks postinfection in HIV-1-infected patients [87] ) ; therefore our results point to relatively high rates of SIVagm transmission in the wild . Note , however , that most transmissions are probably condensed in the time frame of the mating season , and thus the overall incidence of SIV infection in AGMs is not as high as suggested by our cross-sectional analysis . Our study identified a significant degree of divergence between strains collected from relatively homogenous groups of vervets , similar to previous reports for other species of African NHPs hosts , such as mandrills and sooty mangabeys [61] , [66] , [95] , [96] . Also , we have identified closely related strains , suggestive of identifiable chains of transmission . In some instances , such highly related strains were observed in mother-offspring pairs , and probably occurred as a result of direct mother-to-infant transmission of the virus . In other instances , clusters of closely related viruses included a strain collected from a monkey documented as being recently infected . No clear association could be established for several of the closely related strains , and , as previously mentioned , these infections might have occurred during other social interactions , such as grooming or wound licking . SIVagmVer strains from different locations were generally separated on the phylogenetic trees . Intermixing of strains was also observed , suggestive of SIVagm spread between communities by dispersing males . Indeed , although in vervet populations males range with their social group , they also migrate between groups upon or shortly after reaching sexual maturity ( sometimes multiple times during the males lifetime ) [106] , [112] . Interestingly , the SIVagmVer strains collected from Free State locations ( west of the Drakensberg Mountains ) clustered differently within pol and env trees ( Figure 2 and S1 ) as well as in the gag tree ( data not shown ) from those collected from monkeys situated along the Indian Ocean coast ( east of the Drakensberg Mountains ) . Given that the geographical spread between coastal monkeys and those from Free State is similar , the most likely explanation for these phylogenetic relationships is that the Drakensberg Mountains acted as a barrier ( through low temperatures in the elevated areas ) to separate the vervet populations on the two sides . The Drakensberg Mountains are very old , with an estimated age of 280 million years , which implies that a separation of the vervet populations could have occurred in a time frame ranging from 3 million years ago ( during the AGM spread throughout sub-Saharan Africa ) to 100 , 000 years go ( during the mass migrations that occurred in the Plio-Pleistocene glacial periods ) . The Drakensberg Mountains may also have acted as an effective barrier to separate different populations of at least two other species , the common impala ( Aepyceros melampus melampus ) [113] and the chacma baboon ( Papio ursinus ) [114] . We therefore performed relaxed molecular clock analyses to specify TMRCA of the SIVagm samples surrounding the Drakensberg Mountains range to a time-frame spanning 100 , 000 to 3 , 000 , 000 years since the present for the env tree , and in the pol tree we additionally included SIV strains of several species and further calibrated the tree based on isolates from Bioko Island [2] . Molecular clock analysis using Bayesian techniques is highly dependent on priors that are specified [115]; however our analysis is in agreement with another study in which the use of biogeography showed that SIVs are very old [2] , and refuted timing calculations based exclusively on molecular clocks without regards to biogeographical calibration points [53] . Taken together , these observations strongly suggest that SIVagm infection of vervets is more ancient than the most recent previous estimate [53] and suggests that the concept of host-dependent evolution ( supported by the observation that the four SIVagm types cluster together in the SIV trees ) cannot be discarded using current molecular clock calibrations , but may possibly be discernible through the integration of further biogeographical divergence estimates . It is generally assumed that SIV infection is nonpathogenic in natural hosts [1] , [23] , [44] , [51] , [54] . Data supporting this assumption are derived from the study of captive monkeys and a very limited number of species ( AGMs , sooty mangabeys and mandrills ) [1] , [23] , [44] , [51] . Sporadic cases of progression to AIDS were reported in each of these species upon infection with their species-specific viruses [116]–[118] or with cross-species transmitted SIVs [119] . Large scale studies in wild animals are needed to draw definitive conclusions about pathogenicity of SIVs in their natural hosts in the wild , as demonstrated by recent observation that SIVcpz infection is pathogenic in naturally-infected chimpanzees [68] , [69] , [120] . The fact that such a major effect went undetected for decades supports the need for systematic assessment of the natural history of SIV infection in African NHPs in their native habitat , and not in captive environments ( where health status is controlled , nutrition is monitored and exposure to adventitious agents that may impact clinical status is limited ) , to provide significant information regarding the clinical outcome of SIV infection in natural hosts . The main limitation of our assessment of natural history of SIVagmVer infection in vervets is that only plasma samples were available , and thus we could not perform immunophenotypic characterization or in vitro replication studies . We circumvented this limitation by employing a combination of biomarkers that could be monitored in plasma . We report that SIVagmVer infection most likely has a benign outcome in vervets . BMI were not different between SIV-infected and SIV-uninfected vervets . Detected levels of viral replication were high , but in the range of those reported during experimental studies [27] . In the documented cases of acute SIVagmVer infection , the VL levels were also in the range of those observed in experimentally infected monkeys during acute infection [27] . We measured levels of sCD14 to assess the levels of MT , which is one of the proposed mechanisms of excessive immune activation that drives HIV/SIV infection to progress to AIDS [88] , [89] . sCD14 is a surrogate marker for direct measurement of endotoxin or Gram negative bacteria , and numerous studies have shown a strong association of increasing sCD14 levels and increasing LPS levels in plasma in both pathogenic HIV and SIV infections ( presumably due to loss of barrier function in the gut in turn due to HIV-mediated destruction of GALT ) [88] , [89] , and lack of increase in both markers in the setting of nonpathogenic SIV infections in natural hosts [30] , [84] , [90] , [121] . It is critical to assess the integrity of the mucosal barrier in a natural host in the wild , as we and others have previously reported that lack of MT during chronic infection in AGMs and sooty mangabeys may be one mechanism of controlling chronic immune activation and disease progression [30] , [84] . These studies have been done using captive NHPs . Wild monkeys are exposed to many pathogens in a significantly more hostile environment than are captive animals , which may impact the ability of SIV-infected monkeys to maintain the barrier . However , we found no significant difference in the levels of sCD14 between infected and uninfected vervets in the wild . In addition to being a surrogate marker of MT , sCD14 is a marker of macrophage activation , and thus our results also suggest that there are no significant differences in the levels of macrophage activation between SIV-infected and uninfected AGMs in the wild . Lack of chronic immune activation was also supported by the similar levels of cytokines and chemokines tested in SIVagmVer-infected and uninfected wild vervets . The only exception was represented by an increased level of IL-6 in SIVagmVer-infected animals , which was driven by high levels of this cytokine in acutely infected monkeys . We and others reported that a transient increase in immune activation occurs during acute SIV infection in natural hosts [33] , [35] , [36] , [91] , [122] , which is rapidly resolved with the transition to chronic infection [30] . Therefore , the similar levels of cytokine in plasma between SIV-infected and uninfected animals are somewhat surprising in the context of a significant number of acute infections in our study sample . This apparent discrepancy with the results of experimental studies may be due to the fact that most of the experimental studies involved intravenous administration of large amounts of virus that may trigger inflammation and immune activation . Alternatively , as we have previously shown , the acute increases in levels of plasma cytokines and chemokines are very transient in natural hosts , being thus likely that our cross-sectional samples missed such increases . Altogether , sCD14 and cytokine/chemokine testing data support the conclusion that SIVagmVer infection of wild vervets is not associated with significant increases in levels of immune activation . Immune activation being the main driver of HIV disease progression , our results corroborate the clinical assessment and support a nonprogressive outcome of SIVagmVer infection in the wild . Both clinical experience and a growing medical literature indicate that some persons who have been exposed to HIV infection remain uninfected [123] . Although in some instances this may simply represent good fortune , cohorts of uninfected persons have been reported who are considered at high risk for infection . Clarifying the determinants of protection against HIV infection is a high priority that will require careful selection of high-risk uninfected cohorts , which should undergo targeted studies of plausible mediators and broad screening for unexpected determinants of protection . An animal model for ESN/EU may permit such an assessment while circumventing the major ethical boundaries to the study of ESN/EU humans . Such an animal model is not currently available . The SIVmac/RM model is not relevant for ESN/EU studies because this model was derived for pathogenesis and vaccine studies ( thus employing strains selected for pathogenicity and not for their transmission characteristics ) [124] . On the other hand , de novo development of such a model in RMs would be extremely expensive and face major macaque availability restrictions . In this context , the SIVagmVer-infected wild vervet cohorts that we identified in South Africa may serve as a useful model for ESN/EU studies . In these populations , there is an enormous exposure to SIVagm . However , while up to 80% of sexually-active adult females are infected with SIVagmVer , the remaining 20% are uninfected in spite of the presumably massive potential for exposure to SIV throughout their lives . Thus , field studies to assess the prevalence and incidence of SIV infection in the wild and prospectively confirm resistance to infection in a subset of ESN/EU monkeys , combined with genetic , immunologic and virologic assessment of the monkeys in the cohorts , may permit identification of correlates of ESN/EU , an instrumental leap for designing new therapeutic strategies aimed at preventing HIV infection . In conclusion , we report that SIVagmVer is highly prevalent in wild vervet populations from South Africa , that the virus has long been present in this population and that coevolution between SIVagmVer and its natural host , the vervet monkey , resulted in an infection which has a benign outcome in the wild . More importantly , our study has identified a potential model for the study of ESN/EU cases , which has a strong potential to identify correlates of protection against HIV/SIV infection .
All the animals sampled in this study were used according to regulations set forth by the Animal Welfare Act . The animal sampling protocols were approved by the University of Wisconsin-Milwaukee Institutional Animal Care and Use Committee ( IACUC ) . Studies at the UCLA and University of Pittsburgh were carried out through an agreement with the UWM . At the University of the Free State UFS , ethical clearance was provided by the Interfaculty Animal Ethics Committee ( project no . 13/2010 ) . The study was carried out in feral and semifree vervets ( n = 225 ) living in different areas in South Africa , aged between 6 months and 10 years ( Figure 1 ) . Animals were individually trapped using established methods [125] . Details on animal capture are provided as Text S1 . Blood was collected through venous puncture . Details are provided as Text S1 . Each monkey included in the study had a microchip implanted for further identification and to prevent duplicate sampling . Detailed clinical assessment of the monkeys ( including signs associated with immunodeficiency , i . e . , lymphadenopathy , low weight , fever or rashes ) was performed at the time of blood collection . Details are provided as Text S1 . Upon collection , plasma was immediately stored at −80°C . A 500 µl aliquot of plasma from each monkey was available for this study . Upon arrival , plasma samples were thawed for RNA extraction and separated into three aliquots: the first aliquot was used for testing the prevalence levels of SIV by PCR . Additional SIV ELISA testing was performed using this aliquot to establish the stage of acute SIV infection and infant exposure to SIVagm . The second aliquot was used for quantification of SIVagm VLs by real-time PCR . Primers and probes were designed based on the SIVagm integrase sequences . Correlation between VLs and serology enabled identification of acutely SIV-infected AGMs [87] . Finally , the third aliquot was used to assess the natural history of SIVagm infection in the wild by testing surrogate markers for microbial translocation and immune activation ( sCD14 and cytokine/chemokine levels ) . From each plasma specimen , viral RNA was extracted using the QIAamp Viral RNA Mini kit ( QIAGEN , Germantown , MD ) . RNA was eluted and immediately subjected to cDNA synthesis . Reverse transcription of RNA to single-stranded cDNA was performed using SuperScript III reverse transcription according to the manufacturer's recommendations ( Invitrogen , Carlsbad , CA ) . In brief , each cDNA reaction included 1×RT buffer , 0 . 5 mM of each deoxynucleoside triphosphate , 5 mM dithiothreitol , 2 U/ml RNaseOUT ( RNase inhibitor ) , 10 U/ml of Super-Script III reverse transcriptase , and 0 . 25 µM antisense primers SIV-POL-OR ( 5′-ACB ACY GCN CCT TCH CCT TTC-3′ ) , SIV-GAG-B ( 5′-CCT ACT CCC TGA CAG GCC GTC AGC ATT TCT TC-3′ ) and SIV-ENV-B ( 5′-AGA GCT GTG ACG CGG GCA TTG AGG TT-3′ ) . The mixture was incubated at 50°C for 60 min , followed by an increase in temperature to 55°C for an additional 60 min . The reaction was then heat-inactivated at 70°C for 15 min and treated with 2 U of RNase H at 37°C for 20 min . The newly synthesized cDNA was used immediately or frozen at −80°C . SIVagm RNA was amplified byPCR using Platinium Taq Polymerase High Fidelity ( Invitrogen , Carlsbad , CA ) . A 600 bp pol integrase fragment was amplified by nested PCR using outer primers POL-IS4 ( 5′-CCA GCN CAC AAA GGN ATA GGA GG-3′ ) and POL-OR and inner primers SIV-POL-IS4 and SIV-POL-Unipol2 ( 5′-CCC CTA TTC CTC CCC TTC TTT TAA AA-3′ ) [59] , [126] . An 846 bp gag fragment was amplified by nested PCR using outer primers GAG-A ( 5′-AGG TTA CGG CCC GGC GGA AAG AAA A-3′ ) and GAG-B , and inner primers GAG-C ( 5′-AGT ACA TGT TAA AAC ATG TAG TAT GGG C-3′ ) and GAG-F ( 5′-CCT TAA GCT TTT GTA GAA TCT ATC TAC ATA-3′ ) [127] . Finally , a 900-bp env fragment encompassing the V3-V5 gp120 region and the 5′ end of gp41 envelope regions was amplified by nested PCR using outer primers ENV-A ( 5′-GAA GCT TGT GAT AAA ACA TAT TGG AT-3′ ) and ENV-B , and inner primers ENV-C ( 5′-GTG CAT TGT ACA GGG TTA ATG AAT ACA ACA G-3′ ) and ENV-D ( 5′-TTC TTC TGC TGC AGTA TCC CAG CAA G-3′ ) [128] . Nested PCR products were subjected to 1% agarose ( Invitrogen , Carlsbad , CA ) gel electrophoresis and extracted and purified by QIAquick Gel Extraction kit ( QIAGEN , Germantown , MD ) . SIV gene amplicons were directly sequenced by the University of Pittsburgh Genomics and Proteomics Core laboratories ( GPCL ) using the nested PCR primers . Individual sequence for each amplicon was edited and inspected using BioEdit 7 . 1 . 3 . Sequences were translated for analyses on the V3–V5 region of the SIVagmVer envelope with BioEdit . The gag , pol and env nucleotide sequence alignments were aligned with reference sequences obtained from the Los Alamos National Laboratory HIV Sequence Database ( http://hiv-web . lanl . gov ) . The alignment for the pol region included nucleotide sequences sampled from the island of Bioko [2] . Newly derived SIV sequences were aligned using MUSCLE sequence alignment software [129] and alignments were edited manually where necessary . Separate phylogenetic trees for each of the genes were inferred by maximum-likelihood using PhyML 3 . 0 [130] , with a GTR substitution model , gamma-distributed rate heterogeneity at sites and an SPR tree search . Nonparametric bootstrap analysis with 1 , 000 replicates was performed to assess the reliability of branching order . In addition , calibrated molecular clock trees were calculated using BEAST v1 . 7 . 3 [115] to infer likely MRCA dates between different lineages . For molecular clock analysis , we used an HKY substitution model with gamma-distributed rate heterogeneity among sites and an uncorrelated lognormal relaxed molecular clock . A Yule tree prior was used for the pol region , and a constant size coalescent for the env region . Evolutionary rate was calibrated by setting a uniform prior bounded by 10 , 000 and 3 , 000 , 000 years , as TMRCA of SIVagm isolates sampled from areas surrounding the Drakensberg Mountains . For the pol region , a normal distribution with a mean of 10 , 000 years and a standard deviation of 1 , 000 years was additionally used to calibrate TMRCA of Bioko and mainland SIVdrl sequences . Chains were run for 107–108 states and ESS values were high ( >300 ) . Analysis of the molecular clock trees was performed using Tracer v1 . 5 ( http://tree . bio . ed . ac . uk/software/tracer/ ) , and trees were inferred by maximum clade credibility with mean node heights using TreeAnnotator v1 . 7 . 3 , and visualized using FigTree v1 . 3 . 1 ( http://tree . bio . ed . ac . uk/software/figtree/ ) . To test for signals of recombination in the dataset , we ran the Neighbor-Net algorithm implemented in SplitsTree [131] to infer phylogenetic networks for the env and pol regions . We used the generated pol alignment to design specific primers and probe for VL quantification in wild vervets: pol-F ( 5′-GTA GCC AGT GGG TTC ATA GAA GCA-3′ ) , pol-R ( 5′-CAT TGC CTT TAC TTC CTG TGA AAT GA-3′ ) and pol-Probe ( 5′-/56-FAM/TAG AGA AAC/ZEN/AGG AAA AGA AAC AGC AA/3IABkF/-3′ ) . Primers and probe were synthesized by IDTDNA ( Coralville , IA ) and were used in a one-step real-time PCR assay with TaqMan One Step PCR Master Mix ( Applied Biosystems , Branchburg , NJ ) . Real-time PCR was performed in MicroAmp Optical 96-well plates ( Applied Biosystems , Branchburg , NJ ) by mixing the OneStep RT-PCR Enzyme Mix with 5 µl isolated RNA in a 50 µl final reaction volume . Real-time PCR conditions were as follows: 30 min at 50°C , 15 min at 95°C , followed by 45 cycles of 95°C for 15 s and 60°C for 1 min . Dilutions of all components were made using sterile RNase-free water . Data were collected and analyzed using the PE Applied Biosystems software provided . RNA copies/well were adjusted to copies per milliliter of original plasma . Samples were tested in duplicate and the number of RNA copies determined by comparison with a standard curve obtained using known amounts of SIV-pol RNA . The SIVagm RNA standard was produced by cloning one of the SIVagmVerpol gene fragments into Vector pBluescript SK+ and linearizing it by Xba I as a DNA template for RNA in vitro transcription . Standard RNA was produced by using MEGAscript kit ( Applied Biosystems , Branchburgh , NJ ) , according to the manufacturer's instructions . Briefly , the transcription reaction system was assembled at room temperature and mixed thoroughly , followed by incubation at 37°C for 4 hours . One microliter of TURBO DNase was added to the reaction mixture followed by incubation at 37°C for 15 minutes to digest the DNA template . RNA was recovered by Lithium chloride precipitation . The amount of RNA was quantified at A260 , aliquoted and immediately stored at −80°C . Detection limit of the SIVagmVer quantification assay was 100 copies/ml . Based on the env sequence data , a peptide mapping the immunodominant region in the Gp41 transmembrane glycoprotein was synthesized and used in a peptide enzyme linked immunosorbent assay ( ELISA ) , as described [132] . The inferred peptide sequence was TALEKYLEDQARLNVWGCAWKQVC , and this sequence was very well conserved between different SIVagmVer isolates , including previously reported reference strains from Kenya and Ethiopia [9] , [10] , [93] . The Gp36 peptide was synthesized to a purity of at least 90% ( Fisher Scientific , USA ) and the assay was performed as previously reported [132] . The cut-off of the reaction was arbitrarily set at 0 . 20 , as per previous reports [132] . MT was assessed using the levels of soluble CD14 ( sCD14 ) as a surrogate marker [89] . CD14 is a transmembranous protein , which also exists in a soluble form ( sCD14; both as a shed membrane form and an alternatively spliced form ) , as a part of the complex that presents endotoxin ( lipopolysaccharide or LPS ) to TLR4 on monocytes . When monocytes are activated , ectodomain shedding results in increased sCD14 levels . sCD14 is therefore surrogate for direct measurement of endotoxin or Gram negative bacteria which translocate from the intestinal lumen to general circulation as a result of the immunologic injury inflicted at the mucosal level by the pathogenic HIV/SIV infection [88]–[90] , [121] . sCD14 levels were measured using a quantitative sandwich enzyme immunoassay technique ( Quantikine Human sCD14 Immunoassay , R&D Systems , Minneapolis , MN ) . The detection limit of this kit is 200 ng/mL and can range up to 5000 ng/mL , with an interassay coefficient of variability ranging between 7 . 19% and 10 . 9% . Cytokine testing in plasma was done using a sandwich immunoassay-based protein array system , Cytokine Monkey Magnetic 28-Plex Panel ( Invitrogen , Camarillo , CA ) , as instructed by the manufacturer , and results were read by the Bio-Plex array reader ( Bio-Rad Laboratories , Hercules , CA ) , which uses Luminex fluorescent-bead-based technology ( Luminex Corporation , Austin , TX ) . Statistical analyses were performed to analyze the results of viral load , sCD14 and cytokine testing using Mann-Whitney U-tests and Prism 4 . 0 software ( Prism , Irvine , CA ) . The nucleotide sequences of the pol and env sequences from SIVagmVer-infected vervets from South Africa were deposited in the GeneBank ( accession numbers: JX462308-JX462444 ) .
|
We simultaneously assessed , for the first time in a natural host , the epidemiology , diversity and natural history of SIVagmVer infection in wild vervet populations from South Africa . We report that African green monkeys ( AGMs ) have likely been infected with SIVagm for a long period , ranging from the time of their speciation to Plio-Pleistocene migrations , refuting previous molecular clock calculations suggesting SIVagm to be of recent occurrence . As a result of virus-host coadaptation , SIVagmVer infection is characterized by a lack of disease progression in spite of robust viral replication . We show that very active SIVagm transmission in adult AGMs contrasts with a very limited transmission to their offspring , in spite of massive exposure to SIVagm both in utero and through breastfeeding . The observation that some AGMs remain uninfected in spite of life-long exposure to SIVagm identifies wild vervets as an acceptable animal model for the exposed uninfected individuals , which can be used to identify correlates of resistance to HIV/SIV infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"viral",
"transmission",
"and",
"infection",
"immunology",
"microbiology",
"host-pathogen",
"interaction",
"immunodeficiency",
"viruses",
"viral",
"load",
"animal",
"models",
"of",
"infection",
"biology",
"pathogenesis",
"microbial",
"ecology",
"ecology",
"immunity",
"virology"
] |
2013
|
SIVagm Infection in Wild African Green Monkeys from South Africa: Epidemiology, Natural History, and Evolutionary Considerations
|
Imported cases threaten rabies reemergence in rabies-free areas . During 2000–2005 , five dog and one human rabies cases were imported into France , a rabies-free country since 2001 . The Summer 2004 event led to unprecedented media warnings by the French Public Health Director . We investigated medical practice evolution following the official elimination of rabies in 2001; impact of subsequent episodic rabies importations and national newspaper coverage on demand for and delivery of antirabies prophylaxis; regular transmission of epidemiological developments within the French Antirabies Medical Center ( ARMC ) network; and ARMC discussions on indications of rabies post-exposure prophylaxis ( RPEP ) . Annual data collected by the National Reference Center for Rabies NRCR ( 1989–2006 ) and the exhaustive database ( 2000–2005 ) of 56 ARMC were analyzed . Weekly numbers of patients consulting at ARMC and their RPEP- and antirabies-immunoglobulin ( ARIG ) prescription rates were determined . Autoregressive integrated moving-average modeling and regression with autocorrelated errors were applied to examine how 2000–2005 episodic rabies events and their related national newspaper coverage affected demand for and delivery of RPEP . A slight , continuous decline of rabies-dedicated public health facility attendance was observed from 2000 to 2004 . Then , during the Summer 2004 event , patient consultations and RPEP and ARIG prescriptions increased by 84% , 19 . 7% and 43 . 4% , respectively . Moreover , elevated medical resource use persisted in 2005 , despite communication efforts , without any secondary human or animal case . Our findings demonstrated appropriate responsiveness to reemerging rabies cases and effective newspaper reporting , as no secondary case occurred . However , the ensuing demand on medical resources had immediate and long-lasting effects on rabies-related public health resources and expenses . Henceforth , when facing such an event , decision-makers must anticipate the broad impact of their media communications to counter the emerging risk on maintaining an optimal public health organization and implement a post-crisis communication strategy .
Media-communicated health alerts are being used more-and-more frequently by public health decision-makers to prevent consequences of a sudden event , such as , emerging and episodic zoonotic diseases . The medical community must now consider these communications to be preventive intervention tools for public health officials [1]–[3] . Obviously , as during any effective health intervention , undesired effects may also occur , such as rapidly rising numbers of potential cases to treat , leading , in turn , to health-resource saturation , especially if the pathogen involved is rare [4] , [5] . Rabies is a viral encephalitis [6] that is considered to be a reemerging zoonosis throughout much of the world [7] . In Western Europe , rabies in non-flying terrestrial mammals was a well-known illness that has now become a rare disease , because many countries have succeeded in eradicating it . The major risk of rabies is now due to translocation of infected animals , mainly dogs , from rabies-enzootic areas and humans with rabies infection acquired abroad [8] . Although untreated rabies is invariably fatal , death can be avoided by proper administration of rabies post-exposure prophylaxis ( RPEP ) , e . g . , antirabies vaccine , with or without antirabies immunoglobulins ( ARIG ) , before disease onset [6] . Thus , rapid identification of individuals potentially exposed to rabies is critical and media alerts can be extremely useful to identify people who were in contact with the rabid animal . In France ( 60 , 000 , 000 inhabitants , 675 , 417 km2 ) , primary health-care management of patients seeking RPEP is delivered through an official national network of Antirabies Medical Centers ( ARMC ) , which are distributed throughout the country . RPEP is administered , predominantly according to the Zagreb schedule , to people bitten by an animal suspected of being infected with rabies or exposed to its saliva . Clinicians conduct a risk assessment for each exposed patient , and decide to administer RPEP according to the general recommendations , epidemiological data and grade of the bite [9] . The French network for rabies prophylaxis provides exhaustive national data collected by ARMC [10] , and laboratory diagnoses of humans suspected of having rabies [11] and animals suspected contaminating humans . From 1968 to 1998 , a period during which rabies was endemic in French foxes , more than 45 , 600 animals were diagnosed as rabid . In 2001 , France was declared free of rabies in non-flying terrestrial mammals based on World Organisation for Animal Health ( OIE ) criteria and , as a consequence , the number of RPEP began to decline progressively . However , in summer 2004 , one imported rabid dog generated unprecedented media communications by the Public Health Director , whose official press release , dated 31 August 2004 , warned , “At least , nine people are at risk of death and are actively and intensively being sought by the health authorities…” During this episode , antirabies vaccine stocks in ARMC were almost exhausted , leading to a temporary marketing license for the multidose Verorab vaccine ( Sanofi Pasteur ) , which had not previously been authorized in France . That ARIG supplies were dangerously low is illustrated by the postponement of ARIG injections in some ARMC until day 7 after starting RPEP [12] , [13] for several patients . Controlling rabies reintroduction and communicating the risk of rabies spread remain a challenge to public health officials in rabies-free areas . In this study , we analyzed why and how the French rabies-control organization became so oversaturated . In particular , we examined the impact of newspaper reports on the numbers of patients consulting at ARMC , and their RPEP and ARIG prescriptions .
This research has complied with the French national guidelines and Institut Pasteur policy . The analysis of data collected by the National Reference Center for Rabies ( NRCR ) from the AMRC was done anonymously and approved by the Commission Nationale Informatique et Liberté ( Agreement #416031 , dated 28 March 1996 ) . This specific project was submitted to the Institut Pasteur Biomedical Research Committee ( RBM/2006 . 025 ) and was approved on 19 December 2006 . French veterinary and human authorities work in close collaboration to detect cases and organize the medical responses to rabies ( Figure 1 ) , with a territorial network of 96 veterinary services and 74 ARMC disseminated throughout continental France , in 2004 ( Figure 2 ) . On the one hand , each animal responsible for human exposure is confined under veterinary surveillance . If dead and for whatever the reason , diagnostic laboratory tests are conducted at the NRCR , Institut Pasteur , Paris , France . On the other hand , ARMC are the only primary care centers allowed to prescribe RPEP . For each patient , a standard case-report form ( Table S1 ) is systematically filled out describing important epidemiological features , such as geographic location , consultation date , type of exposure , animal species , contact date with the animal , medical decision concerning RPEP . Based on the data collected by ARMC , annual reports are written , which describe the patients visiting ARMC and those receiving RPEP ( http://www . pasteur . fr/sante/clre/cadrecnr/rage/rage-actualites . html ) . Our analysis of the behavior patterns of patients consulting ARMC , and the RPEP and ARIG prescribed to them between 1989 and 2006 was based on those annual data . Among the 74 French ARMC , 56 systematically entered their data into the NRCR database between 2000 and 2005 . The following statistical analysis is based on the exhaustive weekly information provided by these 56 ARMC . The ARMC network also constitutes an effective communication infrastructure coordinated by the NRCR , including conference calls and regular exchanges of information via the internet . When rabies is suspected in a human , biological specimens are sent to the NRCR . Articles on rabies-related news published in three major national daily newspapers , Le Monde , Le Figaro and Libération , were retrieved from the French Association for Auditing Media Circulation: an on-line service: http://www . factiva . fr . Weekly numbers of patients consulting at ARMC , as a function of the date each was in contact with a potentially rabid animal , were used to construct times series . Autoregressive moving average ( ARMA ) [14] modeling was used to determine the significance of event-associated modification of ARMC weekly patient numbers and its duration . Because several known events could have affected the series , a step-by-step procedure was undertaken [15] , [16] . Before the onset of event #2 , trend and/or seasonality were estimated and removed , so that the time series was obtained in a stationary mode and , autoregressive integrated moving-average ( ARIMA ) modeling was done using Box–Jenkins procedure from SAS/ETS [17] ) . The model was then used to predict ARMC consultations and their 95% confidence intervals ( 95% CI ) . An event was considered to have an impact when the number of consultations during 2 consecutive weeks exceeded the upper 95% CI . Observed values were then replaced by forecasts , to obtain analyses of the subsequent weeks . Similarly , 2 consecutive weeks within the 95% CI defined the end of the event's impact period . Relative differences between observed and predicted values were calculated . For impacting events , the number of cases attributed to the event ( NCAE ) was estimated by subtracting the prediction from the observed data during the impact period . An increase rate ( IR ) was then calculated as the ratio of the NCAE/number predicted for the impact period . With the aim of evaluating potential repercussions of an identified event impacting on RPEP prescriptions , two other time series were investigated: the weekly RPEP rate , defined as the number of RPEP prescribed/the number of consulting ARMC patients , e . g . rabies vaccine with or without ARIG; and the weekly ARIG rate , corresponding to the ratio of the number of ARIG/the number of consulting ARMC patients . During the period associated with modified ARMC weekly numbers , weekly RPEP and ARIG rates and mean numbers of consultations were analyzed using regression with autocorrelated errors to account for the regression residuals ( ARIMA procedure ) . To explore whether care provided by the ARMC might be influenced by experience in previous French endemic enzootic areas , we divided the country into three areas based on the French administrative regions: area 1 , the former enzootic rabies-infected–fox region from 1968 to 1998; area 2 , a region that has always remained rabies-free , and area 3 , the region where event #6 occurred ( Figure 2 ) . All analyses were performed using R ( www . r-project . org ) and SAS software .
After the reintroduction of rabies into France in 1968 , the number of rabid animal cases increased to reach a maximum of 4 , 212 cases in 1989 [18] , followed rapidly by a maximum of 9 , 763 RPEP prescribed for 15 , 948 patients consulting at ARMC recorded in 1990 ( Figure 3 ) . In 2001 , France was declared free of rabies in non-flying terrestrial mammals based on OIE criteria [19] and , as a consequence , the number of patients consulting ARMC and receiving RPEP began to decline progressively to respective minima of 7 , 788 and 3 , 378 in 2003 ( Figure 3 ) . However , the numbers of patients consulting at ARMC and given RPEP suddenly rose in 2004 . Therefore , 2000–2005 data were further investigated using ARIMA modeling to describe in greater detail the trends observed . Between 1 January 2000 ( week 1 ) and 31 December ( week 312 ) 2005 , five rabid dogs illegally imported from Morocco and one rabies-infected human from Gabon were detected in France . During the period examined , the first event #1 dog ( 5 months old ) was confirmed as being rabid in May 2001 ( week 74 ) and the second , event #2 dog ( 3 months old ) in September 2002 ( week 139 ) ; they entered France from Morocco , 2 months and 2 weeks before their deaths , respectively . The human case ( event #3 ) was a 5-year-old boy , who traveled from Gabon and died 2 months later , in October 2003 ( week 199 ) [20] . Event #4 , #5 and #6 dogs were diagnosed as being rabid , respectively , in February 2004 ( week 213 ) , May 2004 ( week 229 ) , and August 2004 ( week 243 ) [21] . Event #6 was a 4-month-old puppy , illegally imported by car from Morocco to Bordeaux , France , via Spain , who died of rabies in August 2004 ( week 243 ) ; he was not officially vaccinated . Between 1 January 2000 and 31 December 2005 , 56 , 924 rabies-exposed individuals in France ( all patients exposed abroad were excluded from the analysis ) consulted in an ARMC , among whom 56 , 446 had valid exposure dates and bite/contact locations . Among them , 50 , 930 had valid consultation dates and 56 , 406 had valid treatment information ( Figure 4 ) . Because the data presented 52-week seasonality , the time preceding event #1 was too short to be analyzed . In such a case , Box and Jenkins recommend using at least two seasonality periods to calibrate the model [14] . Data analyses concerning events #1 , #2 , #4 and #5 , corresponding to rabid dog importations , were simple and rapidly done , as these dogs had had no known contact with animals and humans other than their owners during their communicable risk periods . As a consequence , events #2 , #4 and #5 were not reported in the major national newspapers and were not associated with any significant increase of ARMC activity . In contrast , events #3 and #6 were reported in 6 and 54 published articles retained for this study , respectively , and significantly affected the numbers of patients consulting at an ARMC ( Figure 5 ) . Until event #3 ( October 2003 ) , the weekly number of patients consulting an ARMC declined significantly ( slope = −0 . 34; p<0 . 0001 ) , with 52-week seasonality that peaked during the summer ( Figure 5 ) . In October 2003 , the weekly number of ARMC patients was significantly higher than the predicted number during the 6 weeks surrounding event #3 ( weeks 198–203 ) , with an estimated NCAE of 355 ( IR = 54 . 7% , 95% CI = 30 . 0–83 . 0 ) . Furthermore , event #3 was followed by a significant flattening of the decreasing slope of ARMC activity ( −0 . 23 versus −0 . 34; p = 0 . 0003 ) . No RPEP- or ARIG-rate modification associated with event #3 was observed . In the summer of 2004 ( event #6 ) , the weekly number of ARMC patients differed significantly from the predicted number during the 26 weeks surrounding it ( weeks 238–263 ) . The total 26-week number of additional ARMC patient load was estimated at 2 , 928 ( IR = 84 . 0% , 95% CI = 57 . 0–123 . 3 ) over the model predicted 3 , 486 ( Figure 5 ) . During that period , the observed mean RPEP and ARIG rates were significantly higher than those recorded during the period preceding event #6 , IR = 19 . 7% and 43 . 4% , respectively ( Table 1 ) . The slopes of the ARMC-consultation decline after week 263 and before week 238 were estimated at −0 . 12 and −0 . 23 , respectively; p<0 . 001 . Surprisingly , between weeks 264 and 312 , the mean RPEP rate remained persistently and significantly higher than before the reference period , as did the ARIG rate , which was more than two-fold higher than before week 237 ( Table 1 ) . The increased number of patients consulting at an ARMC in response to the newspaper articles concerning event #6 peaked at the same time as the media coverage in the three different French areas defined according to their rabies experience ( Figure 6A ) . In area 3 , the exposure dates reported by ARMC patients corresponded to the risk period coinciding with the dog's movements and infectivity , whereas in areas 1 and 2 , patients reported exposure dates more compatible with newspaper coverage than with the risk period ( Figure 6B ) .
France progressively eliminated rabies in foxes and became rabies-free for indigenous non-flying terrestrial mammals in 2001 [19] . Consequently , use of public health facilities dedicated to the disease decreased steadily from 1990 until 2003 , suggesting a continuous impact of rabies elimination on related public health resources and expenses . However , the very mild decline of the 2000–2003 slope probably reflects the difficulties in convincing the public and adapting medical practice to the changing risk . Although elimination of rabies in foxes reduced the number of rabid pets and other domestic animals , and thus exposure to rabies , pet bites continue . Importation of rabid animals and infected travelers returning from abroad also regularly challenge the French public health organization of rabies control . Therefore , the number of RPEP prescriptions and the associated costs will not decline significantly until there is adequate assurance that the probability of a pet being rabid is sufficiently low that such therapy is not warranted , even when the pet's status cannot be verified [22] , [23] , [24] . Regardless of potential French specificities , public health decision-makers are obliged to consider such potential events and their ensuing demand on medical community resources when attempting to predict and maintain the efficacy of rabies-control policies even in rabies-free countries [24]–[28] . Among the six rabies events occurring during 2000–2005 in France , only two significantly affected ARMC activities and RPEP rates . The human case imported from Gabon in 2003 ( event #3 ) was associated with enhanced ARMC activity during a brief period and also changed ARMC's declining activity , which had been observed since 2000 . The boy's demise was reported 6 times in the newspapers , further confirming that “death makes news” for rare and acute diseases [29] . In contrast , the illegally imported rabid dog from Morocco in August 2004 ( event #6 ) had a significant and rapid impact on rabies public health resources . Indeed , the critical shortage of prophylactic drugs resulted from the 84% IR of patients consulting at an ARMC with a 62 . 5% RPEP rate for those patients over 26 weeks . This influx explains the bottleneck observed in ARMC . Similarly , laboratory rabies-diagnosis workload for animals increased by >40% during the same period ( data not shown ) . To comply with the threatened shortage of RPEP and ARIG due to the cumulative effect of enhanced patient influx and their more frequent prescriptions , a specific communication strategy was established for the ARMC network to provide information concerning the evolution of the epidemiological situation and to recall the indications of RPEP . This information was disseminated via the websites of the NRCR , the Ministry of Health ( MOH ) , the National Institute for Health Surveillance and the Ministry of Agriculture , which were regularly updated as of 28 August , fax on 2 September , and phone conferences on 3 and 9 September . To complete this plan , temporary licensing of a multidose vaccine ( Verorab , Sanofi Pasteur ) was accorded and ARIG injections were postponed , as necessary , in accordance with WHO guidelines [12] . Unfortunately , it was not feasible to quantitatively analyze the extent of that adaptation . However , RPEP and ARIG never became completely unavailable . Notably , the risk of a potential ARIG shortage in the event of an unplanned increase of demand or a limitation of supply is shared by many countries in Europe and on other continents [30] , [31] . Compared to similar events occurring during 2000–2005 in France , event #6 has several particularities . While only restricted contacts with humans ( owners , neighbors… ) were suspected for cases #2 , #4 and #5 , the event #6 dog traveled through southwestern France during the communicable risk period , and had been roaming unleashed at three large summer music festivals , each with at least 10 , 000–20 , 000 participants [21] . According to immediate inquiries made by veterinary and medical services , this trajectory potentially led to extensive contacts between the rabid dog and humans and animals . Therefore , the public health authorities' concern triggered extensive media alerts . First , the MOH wanted to identify and contact each individual with confirmed contact with the event #6 dog . National and local authorities coordinated several news conferences and newspaper reports to inform the French population about the risk and recommendations concerning errant dogs in general , and how to react to potential exposure to a rabid dog . A European-wide alert was launched through the European warning and response system . Second , beginning in early September 2004 , this intensive communication frenzy of 54 newspaper articles heightened public awareness of the rabies risk . Third , additional public concern might also have been heightened by controversies surrounding the crisis management . Notably , event #6 occurred just before the annual opening of hunting season , in a strongly traditional hunting region . An initial decision was made to forbid hunting with dogs in the counties where the rabid dog had traveled during his infectious period . That restriction led to a passionate public debate , angering hunters and ending with hunting organizations successfully blocking the ban . Fourth , public health authorities decided to eradicate free-roaming dogs . Finally , press releases issued by the Minister of Rural Affairs and the MOH were contradictory concerning the implementation of mandatory antirabies vaccination of dogs and cats . The constant media attention drawn by these different players during event #6 may have contributed to enhancing the sense of rabies risk , thereby prompting people to associate dog bites with rabies and to consult at an ARMC [3] , [32] , [33] . Furthermore , public health crises , e . g . that generated by severe acute respiratory syndrome , demonstrated how conflicting messages can create confusion and uncertainty in both the media and the general public [21] . However , this event #6 newspaper coverage , initiated and promoted by public health authorities , reached its primary and immediate objective , e . g . , no secondary dog or human rabies case was reported following the dog's arrival in France . Eight of the 13 identified individuals , who had been exposed to the rabid dog , were located and contacted and 49 dogs and 8 cats identified as having been in direct contact with the event #6 dog were killed . We would have expected this unusual news coverage of a rabies event to have raised public awareness about the risks of illegally importing animals from endemic countries . Between 2000 and 2005 , France was the only rabies-free European country to have so many imported cases . Unfortunately , in 2007–2008 , two new dog-importation episodes were reported in France , clearly illustrating the short persistence of this type of information disseminated to the public . Because of one of these events , France lost its rabies-free status according to OIE criteria in 2008 . We only examined national newspaper stories available in Factiva but not local newspaper reporting or television , radio and internet stories , and , thus , probably underestimated the global coverage of these episodes . In response to national newspaper coverage , people who are far from the event location can become concerned and start taking precautions as if they were in the affected area [3] , [4] , [32] . This phenomenon is particularly well illustrated by event #6 , for which exposure dates reported by patients consulting at AMRC in areas 1 and 2 corresponded to the period of newspaper coverage rather than to the risk-of-transmission period during the dog's movements . Lastly , long-term modifications of ARMC activity and RPEP- and ARIG-prescription rates were observed . In particular , 2005 RPEP and ARIG rates ( ARIMA study herein ) and even those for 2006 had not yet returned to 2003 levels . This finding strongly suggests a persistent and unjustified heightened perception of the risk by individuals and physicians , even those specialized in rabies treatment , and this despite regular information provided by the NRCR to the ARMC network and a rapidly controlled situation with no recorded secondary animal and human cases during the following 2 years . In conclusion , event #6 and its associated national newspaper coverage profoundly perturbed health services , with excessive consulting at ARMC and durably increased antirabies drug rates for several months , along with more animal diagnostic testing . This crisis highlighted a lack of experienced manpower and insufficient vaccine stocks . Outbreaks of emerging and/or deadly infections , like severe acute respiratory syndrome [34]–[38] , anthrax [39] , [40] and rabies ( herein ) , have shown that media messages dramatically influence both the public's and health-care workers' perceptions of the risk with potential implications for health-care resources . Our observations underscore to what extent , under such circumstances , public health decision-makers have to anticipate the depth and scope of potential consequences of emerging or reemerging infectious diseases and their related press communications , and the need to prepare appropriate responses to keep the public health organization effective . It also illustrated that , despite communication efforts implemented by the French public health authorities and messages released through the ARMC network , long-term modifications of ARMC activities and prescriptions were observed , further emphasizing that a post-crisis communication strategy is essential .
|
Rabies has been eliminated from a large part of the European Union and , thus , any newly imported cases threaten its reemergence . The 2000–2005 data derived from the exhaustive surveillance system implemented in France was analyzed to evaluate the impact on demand for and delivery of antirabies prophylaxis following introduction of five rabies-infected dogs and one infected human into this rabies-free area . Using these events , we were able to illustrate the difficulties encountered in reducing the demand for and prescription of post-exposure rabies prophylaxis in this context of episodic importation . Moreover , we highlighted the need for public health decision-makers to anticipate the broad spectrum of consequences of their media communications and to prepare appropriate responses ( in terms of health resources ) to maintain an optimally effective public health organization after importation of an exotic infectious agent or its emergence . These responses are particularly relevant in the context of limited availability of rabies post-exposure prophylaxis , especially antirabies immunoglobulin .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"health",
"and",
"epidemiology/infectious",
"diseases"
] |
2010
|
Imported Episodic Rabies Increases Patient Demand for and Physician Delivery of Antirabies Prophylaxis
|
Comparative genomics can be used to infer the history of genomic rearrangements that occurred during the evolution of a species . We used the principle of parsimony , applied to aligned synteny blocks from 11 yeast species , to infer the gene content and gene order that existed in the genome of an extinct ancestral yeast about 100 Mya , immediately before it underwent whole-genome duplication ( WGD ) . The reconstructed ancestral genome contains 4 , 703 ordered loci on eight chromosomes . The reconstruction is complete except for the subtelomeric regions . We then inferred the series of rearrangement steps that led from this ancestor to the current Saccharomyces cerevisiae genome; relative to the ancestral genome we observe 73 inversions , 66 reciprocal translocations , and five translocations involving telomeres . Some fragile chromosomal sites were reused as evolutionary breakpoints multiple times . We identified 124 genes that have been gained by S . cerevisiae in the time since the WGD , including one that is derived from a hAT family transposon , and 88 ancestral loci at which S . cerevisiae did not retain either of the gene copies that were formed by WGD . Sites of gene gain and evolutionary breakpoints both tend to be associated with tRNA genes and , to a lesser extent , with origins of replication . Many of the gained genes in S . cerevisiae have functions associated with ethanol production , growth in hypoxic environments , or the uptake of alternative nutrient sources .
Inferring the genome organization and gene content of an extinct species has the potential to provide detailed information about the recent evolution of species descended from it . If we know what was present in the genome of an ancestor , we can deduce how a current-day descendant differs from it . We can then ask questions about how it came to be different . The most recent changes in a genome are often the most interesting ones , because they reflect the most recent ( or even current ) evolutionary pressures acting on that genome [1] , [2] . Yeast species offer the potential for the precise reconstruction of ancestral genomes , because many genomes have been sequenced and they show extensive colinearity of gene order among species [3]–[6] . As the number of sequenced genomes from related species rises , so does the precision with which we can reconstruct their history . In this study we compare the genomes of a group of species in the subphylum Saccharomycotina , spanning an evolutionary time-depth that is comparable to that of the vertebrates [7] . A whole-genome duplication ( WGD ) event occurred during the evolution of this subphylum [8] , and we can compare the genomes of several species ( including S . cerevisiae ) that are descended from this event to the genomes of several species that branched off before the WGD occurred . We focus on an ancestor that existed approximately 100–200 Mya , at the point immediately before the WGD occurred . The evolutionary period beginning with this ancestor corresponds to a time during which the S . cerevisiae lineage became increasingly adapted to rapid fermentative growth [9] , [10] and extensive rearrangement of the genome occurred ( including the deletion of thousands of redundant copies of duplicated genes ) [11] . Previous studies in other systems have employed both manual and computational approaches to reconstructing ancestral genomes . One of the most successful applications of computational methods has been the estimation of the ancestral order of orthologous genes in the common ancestor of 12 Drosophila species [12] , [13] . Ancestral reconstruction is more difficult when ancient polyploidizations are present [14] . In studies of the 2R duplications in vertebrates , for example , the emphasis has been on establishing the ancestral gene content of paralogous chromosomal regions rather than on their precise gene order [15] , [16] . We chose to use a manual , parsimony-based , approach to reconstructing the yeast ancestor at the point of WGD . The manual approach has the attractions of being tractable ( whereas computational methods are still under development [17] , [18] ) , of providing an independent result to which computational results can be compared , and of forcing us to examine every rearrangement event without prejudice as to what mechanism might have caused it . Sankoff and colleagues [14] , [17] , [18] have developed computational methods that aim to reconstruct ancestral gene order in datasets that include polyploidizations . In recent work [18] , they evaluated their ‘guided genome halving’ ( GGH ) algorithm by comparing its results to ours , using a preliminary version of the manually-derived ancestral yeast gene order that we report here as a ‘gold standard’ . As currently implemented , the GGH algorithm can only consider input from a single post-WGD genome and 1–2 non-WGD outgroups , and only considers genes that are duplicated in the post-WGD genome . Inferring the set of genes that existed in a yeast ancestor , and the order of those genes along the chromosomes , is of interest from both genome-evolutionary and organismal-evolutionary standpoints . Knowing the ancestral gene order enables us to trace all the inter- and intra-chromosomal rearrangements that occurred en route from this ancestor to the current S . cerevisiae genome , which is informative about the molecular mechanisms of evolutionary genome rearrangement and is also phylogenetically informative . Knowing the ancestral gene content allows us to identify genes that have been added to , or lost from , the S . cerevisiae genome during the past 100 Myr . Previous studies have shown that changes in gene content can provide a strong indication of changing evolutionary circumstances , either in cases of gene loss ( such as the losses of GAL , DAL and BNA genes in Candida glabrata [1] , [19] , [20] ) or in cases of gene gain ( such as the ADH2 and URA1 genes of S . cerevisiae [9] , [21] , [22] ) . Even though it may not be possible to conclude that any particular gene gain was adaptive , the clear links between the functions of the gained genes ADH2 and URA1 and the adaptation of S . cerevisiae to a fermentative lifestyle [23] suggested to us that a systematic search for all the genes that were gained by S . cerevisiae since WGD would be worthwhile .
We used a manual parsimony approach to reconstruct the gene order and gene content of the yeast ancestor that existed immediately prior to WGD ( Figure 1 ) . The reconstruction was made by visually comparing the local gene orders in every region of the genome , stepping through the genome in overlapping 25-gene windows using the Yeast Gene Order Browser [YGOB; 6] . Initially , during 2007–08 , we compared data from five post-WGD species ( S . cerevisiae , S . bayanus , C . glabrata , Naumovia castellii and Vanderwaltozyma polyspora ) and three non-WGD species ( E . gossypii , Kluyveromyces lactis and Lachancea waltii ) and inferred an ancestral genome based on these data . Later , in 2009 , we added the genomes of three more non-WGD species ( Zygosaccharomyces rouxii , L . thermotolerans and L . kluyveri [24] ) and re-examined the whole genome window-by-window using YGOB . This process confirmed that our initial ancestral reconstruction was largely correct , but identified a few places where the gene content or local gene order in the ancestor needed to be revised . In particular , by adding data from more non-WGD species we were able in some cases to detect non-WGD orthologs of S . cerevisiae genes that are short and rapidly-evolving , which previously appeared to be unique to S . cerevisiae ( for example , YLR146W-A ) . The gene order and content of the ancestor were inferred as shown in Figure 1B , C . We first established the gene content , and then examined the adjacency relationships among these genes . Within any post-WGD species such as S . cerevisiae , most of the genome can be sorted into pairs of sister regions that have a double-conserved synteny ( DCS ) relationship with any non-WGD species such as L . waltii [25] , [26] . Breaks in the DCS pattern correspond to two types of event , called single-breaks and double-breaks of synteny [26] . For each single-break of synteny ( Figure 1B ) , because we have genome sequences from multiple post-WGD species , and because the endpoints of the chromosomal rearrangements in different species generally do not coincide , we can infer the species and chromosomal track on which the break happened . This inference also tells us the ancestral gene order across the site of breakage: in general , for a single break , the ancestral order has been disrupted in one track in one post-WGD species , but it is still conserved in the same track from the other post-WGD species , in the sister track from all the post-WGD species , and in the non-WGD species . Similarly for each double-break of synteny ( Figure 1C ) , because we have multiple genome sequences from non-WGD species we can in general identify the break as having occurred in one particular non-WGD species . A small number of double-breaks of synteny are caused by situations where all the non-WGD species show one gene order but both of the tracks from all the post-WGD species show a different order . These breaks correspond to rearrangements that occurred on the branch between the Z . rouxii divergence and the common ancestor of the post-WGD species ( before the WGD happened ) . We do not include these breaks in our analysis because we are only interested in events that occurred after the WGD . Manual reconstruction by this method resulted in an inferred ancestral genome with eight chromosomes , containing 4703 protein-coding genes . The ancestral gene set represents the intersections of orthologous genes between non-WGD and post-WGD species , and between ohnologs ( paralogs formed by WGD ) across the post-WGD species . The ancestral genome is listed in Table S1 and can be browsed using YGOB ( http://wolfe . gen . tcd . ie/ygob ) . Genes in this genome were given names such as Anc_1 . 125 , meaning the 125th gene on chromosome 1 of the ancestor . The ancestral gene set accounts for 5158 ( 92% ) of the 5601 genes currently present in S . cerevisiae ( 1088 ohnologs and 4070 single copy genes ) , which covers all genomic regions in S . cerevisiae except for the subtelomeric regions ( discussed below ) . The S . cerevisiae genome can be mapped onto the inferred ancestral genome in 182 DCS blocks that tile together in an unambiguous 2∶1 fashion across the ancestral genome ( Figure 2 ) . Similarly , the other post-WGD species and non-WGD species can be mapped onto the ancestral genome , with 2∶1 and 1∶1 mappings , respectively , by the numbers of blocks shown in Figure 1A . The C . glabrata genome is much more rearranged ( 582 blocks ) than S . cerevisiae as previously noted [19] , [27] . The L . kluyveri genome is remarkably unrearranged , with the whole genome mapping into just 57 blocks relative to the ancestor . Our inferred ancestral genome is incomplete in some regards: Using the breakpoints between S . cerevisiae synteny blocks in the ancestral genome , we inferred the large scale chromosomal rearrangements that have occurred in the S . cerevisiae lineage since the WGD . Most rearrangement events could be classified as either reciprocal translocations ( Figure 3 ) or inversions . Note that it is impossible to count inversions and reciprocal translocations with absolute precision , because if a genomic region that contains one endpoint of a reciprocal translocation subsequently undergoes inversion , the result is identical to one that could be produced by two successive reciprocal translocations ( Figure S1 ) . We counted these situations as two reciprocal translocations , so we have probably misclassified some inversions as reciprocal translocations . Inversions were defined as events where the two endpoints of the rearrangement were on the same ancestral chromosome and on the same post-WGD track . In total we inferred 73 inversion events and 66 reciprocal translocations events on the evolutionary path from the ancestor to S . cerevisiae ( Table 1 ) . Five of the inversions have endpoints at telomeres . There were also five non-reciprocal translocations , which we call ‘telomeric translocations’ because they involved an exchange between a telomere and an internal region of another chromosome , which moved the end of an arm from one chromosome to another ( one of these events occurs at a shared inversion/translocation breakpoint ) . The data indicate that some intergenic regions were re-used as breakpoints in more than one rearrangement event . We classified the rearrangements as consisting of 34 simple inversion events ( not overlapping other inversions or reusing breakpoints ) , 39 complex inversion events ( overlapping other rearrangements and/or reusing breakpoints ) , 44 simple reciprocal translocation events , and 22 reciprocal translocation events involving breakpoint reuse ( Figure 4 ) . These results are in reasonable agreement with our estimate from a decade ago of 70–100 rearrangement events , based only on S . cerevisiae data [33] . If some post-WGD species share a rearrangement relative to the ancestor but others retain the ancestral gene order , the rearrangement event is a phylogenetically informative character [34] , [35] . We searched for rearrangements shared by any pair of post-WGD species . As described below , we found many that support the branching order of the post-WGD species shown in Figure 1A ( Table S2 ) . We did not find any shared rearrangements supporting alternative topologies . This result supports our previous conclusion , based on shared patterns of gene losses , that N . castellii is an outgroup to a clade containing C . glabrata and S . cerevisiae [11] , [36] . In contrast , phylogenies based on sequence analysis tend to place C . glabrata outside N . castellii and S . cerevisiae [1] , [37] , [38] , a result that we believe is an artifact . Given this phylogeny , the post-WGD species define four temporal intervals for rearrangements ( Figure 1A ) : ( i ) no rearrangements are shared by all the post-WGD species relative to the ancestor; ( ii ) 8 rearrangement events are shared by N . castellii , C . glabrata and S . cerevisiae ( 6 inversions , 1 reciprocal translocation , 1 telomeric translocation ) ; ( iii ) 19 rearrangements are shared only by C . glabrata and S . cerevisiae , with N . castellii and V . polyspora retaining the ancestral organization ( 13 inversions , 6 reciprocal translocations ) ; and ( iv ) 117 rearrangements are unique to S . cerevisiae or shared by this species and S . bayanus ( 54 inversions , 59 reciprocal translocations , 4 telomeric translocations ) . Most of the rearrangements that are specific to S . cerevisiae are temporally ambiguous relative to each other . We did not subdivide the group of 117 events into those that occurred before and after the S . bayanus divergence because the S . bayanus genome assembly is quite fragmented . The above analysis does not include gene transpositions , which we find to be relatively rare in yeast genomes but which are difficult to count precisely because to identify a transposed gene in a particular species , we need to be certain that it is orthologous to a gene at a non-syntenic location in the ancestral genome . The lack of rearrangements in the first time interval is notable because it indicates that V . polyspora separated from the other lineages soon after the WGD . We also found that no rearrangements occurred on one genomic track of all the post-WGD species , relative to the other track and the ancestor , prior to this speciation . This observation argues against the possibility that the WGD event was an allopolyploidization rather than an autopolyploidization ( see ref . [11] for discussion ) : if it was an allopolyploidization , then the two hybridizing genomes must have been completely colinear . It was necessary to infer breakpoint reuse at the ends of some synteny blocks . Reused breakpoints appear as cycles in the map of breakpoint pairs ( Figure 4 ) . The evolutionary re-use of breakpoints has previously been identified in studies on mammals and Drosophila [13] , [39] . We find that for both reciprocal translocations and inversions , there are fewer breakpoints than expected if every event had unique ends ( Table 1 ) . The average number of breaks per used site is 1 . 12 for reciprocal translocations and 1 . 16 for inversions . Some sites were used as endpoints of both an inversion and a reciprocal translocation , and if we pool these two categories there are only 228 unique breakpoints instead of the expected 278 , implying an average of 1 . 22 breaks per site ( Table 1 ) . We identified 96 sites in the ancestral genome at which genes are inferred to have been gained subsequently in the lineage leading to S . cerevisiae . The total number of gained genes is 124 , because some sites contain groups of consecutive gained genes ( Figure 5 ) . We were surprised to find that 33 ( 34% ) of these ‘gene gain’ sites are beside tRNA genes . tRNA genes have previously been linked to sites of genomic rearrangement between E . gossypii and S . cerevisiae [26] . Furthermore , it is known that origins of replication in yeast are often located near tRNA genes [40] , and it seems plausible that origins might be fragile sites for evolutionary breakage and/or integration of new DNA . We used computer simulation to test the significance of the associations among tRNA genes , origins of replication , evolutionary breakpoints , and sites of gene gain ( see Methods ) . tRNA genes are present at breakpoints and gain sites about three times more often than expected by chance ( Table 2 , rows 2 and 3 ) , and origins are present about twice as often ( Table 2 , rows 4 and 5 ) . It should be noted however that the locations of all the tRNA genes are known whereas it is probable that many origins have not yet been identified [41] . There are several plausible mechanisms by which tRNA genes could precipitate genomic rearrangements . tRNA genes exist in multiple near-identical copies in the genome , so illegitimate recombination between these sequences could result in reciprocal translocations [42] , [43] . Ty retroelements tend to integrate beside tRNA genes and provide long sections of near-identical sequence scattered around the genome that could be substrates for ectopic recombination , as seen in S . cerevisiae irradiation experiments [44] . Ty LTRs , tRNA genes , and origins of replications have also all been associated with the endpoints of spontaneous segmental DNA duplications in S . cerevisiae [45] . Replication forks tend to stall near highly-expressed genes ( such as tRNA genes ) , and sites of replication fork collapse are hotspots for chromosomal rearrangements [46] , [47] . It is also possible that the Ty-encoded reverse transcriptase has played a direct role in the integration of new genes into sites beside tRNA genes , similar to the way that cDNA fragments of transcribed genes are sometimes captured at sites of double-strand break repair in S . cerevisiae experiments [48] . We identified 124 genes , excluding those in subtelomeric regions , that are inferred to have been gained on the lineage leading to S . cerevisiae during the time since WGD ( Figure 5 ) . The S . cerevisiae gene set that we used in this study consists only of genes that are conserved between S . cerevisiae and at least one of the other Saccharomyces sensu stricto species ( dN/dS ratio<1 in the analysis of Kellis et al . [49] ) , or that are duplicates of other genes in S . cerevisiae ( again with dN/dS<1 ) , so we can be confident that the all the gains we identity are real genes and not annotation artifacts . Some of the gained genes are unique to S . cerevisiae and sensu stricto species , while others are shared by the other post-WGD species ( Figure 5 ) . The 124 gained genes range from those with high similarity to another gene in the S . cerevisiae genome to those with no similarity to any known gene from any organism . We classified the gained genes into nine groups as described in Figure 5 , and then into three larger categories according to their apparent mechanism of formation . The three large categories are: Analysis of the functions of the gained genes should provide insight into the evolutionary pressures that have acted on S . cerevisiae in the period since WGD but , remarkably , there is no functional information in the Saccharomyces Genome Database ( SGD ) for almost half of the recently gained genes . None of the 124 genes is essential when deleted , according to SGD . The non-essentiality of gained genes is not surprising because they were gained by an organism that was already fully functional in its environment before they were gained . It is particularly notable that only 16 of the 51 orphans in Figure 5 have been assigned genetic names , which would indicate that something is known about their function . In the sections below , we discuss some of the functional groups of gained genes . The gene information in these sections is derived primarily from summaries in the SGD and YPD databases [52] , [53] , and from a MIPS ( Munich Information Centre for Protein Sequences ) catalog analysis . Reconstructing the content and gene order of the ancestral yeast genome just prior to WGD has provided a mechanism for studying the structural rearrangements that occurred subsequent to WGD . Our reconstruction is dependant on the set of extant genomes available for comparison , so it is likely that our list of candidate gene gains includes some false positives that will turn out to have been present at the time of WGD . As more genome sequences become available the ancestral gene set will become progressively more complete and the list of gains may shrink . From a biological perspective , the main shortcoming of our work is that we were unable to reconstruct the telomeric regions of the genome , corresponding to the last ∼10 genes on each arm of each chromosome in S . cerevisiae . These regions turn over so dynamically that synteny breaks down almost completely between the species considered here . This is unfortunate because many of the most interesting evolutionary events such as the gain of genes by horizontal gene transfer ( HGT ) from other species [22] , seem to occur preferentially near telomeres . Our set of candidate gene gains in S . cerevisiae contains only two possible cases of gene gain by HGT at internal chromosomal sites ( YLR011W/LOT6 and YLR012W; we did not study these in detail ) , whereas Hall et al . [22] found eight examples of apparent transfer of bacterial genes into telomeric sites . A second shortcoming is that we relied on sequence conservation ( dN/dS<1 ) among the sensu stricto species as a way of distinguishing between genuine S . cerevisiae genes and annotation artifacts , which had the inadvertent effect that we overlooked any genes that may have been gained by S . cerevisiae in the time since it diverged from the other sensu stricto species; one such case is BSC4 , which appears to have been formed de novo in S . cerevisiae [87] . The set of genes inferred to have been gained on the S . cerevisiae lineage is relatively small ( 2% of the gene set ) and their functions point squarely towards increasing adaptation to the ‘fermentative lifestyle’ [23] . They indicate increasing throughput of the glycolysis and fermentation pathways , and adaptation towards growth in conditions with little oxygen , including modifications to the cell wall and the bypass of biochemical pathways that require molecular oxygen by importing substances from outside the cell . There are also many gained genes in our set that we have not discussed in detail here because they did not fall into larger functional groups . Further analysis of these gains on an individual basis may reveal insights into the evolution of S . cerevisiae and the other species in the WGD clade .
In this paper we have adopted the revised genus nomenclature proposed by Kurtzman [88]: Saccharomyces castellii becomes Naumovia castellii; Kluyveromyces polysporus becomes Vanderwaltozyma polyspora; Ashbya gossypii becomes Eremothecium gossypii; Kluyveromyces waltii becomes Lachancea waltii; Kluyveromyces thermotolerans becomes Lachancea thermotolerans; and Saccharomyces kluyveri becomes Lachancea kluyveri . In this scheme each genus name refers to a monophyletic group , whereas previously Saccharomyces and Kluyveromyces were polyphyletic . We did not change any gene names , even though in many species the gene names have a prefix that is an acronym of the obsolete species name . The numbers of double-conserved synteny ( DCS ) and synteny blocks between the reconstructed ancestor and each other species ( Figure 1A ) were counted automatically using an algorithm that smoothes over small inversions and other interruptions in cases where endpoints are ≤20 genes apart in the ancestral genome . For S . cerevisiae our manual analysis identified 228 breakpoints ( Table 1 and Figure 4 ) , which subdivide the 16 linear chromosomes into 244 segments . The discrepancy in numbers between these 244 segments and the 182 DCS blocks in S . cerevisiae ( Figures 1A and 2 ) is due to the use of the smoothing algorithm . We described the inferred ancestral gene order in terms of synteny blocks of current Saccharomyces cerevisiae genes . We manually identified intrachromosomal rearrangements ( inversions ) between the ancestor and S . cerevisiae and reversed them , revising our synteny blocks , in order to more easily identify the endpoints of reciprocal translocations . For each synteny block end not at a telomere , the location is at a position in the ancestral genome that underwent a reciprocal translocation in its transition towards the current S . cerevisiae genome . Each synteny block end in the ancestral genome is bordered by another synteny block found elsewhere in the current S . cerevisiae genome . The two breakpoints at the ends of two ancestral synteny blocks now adjacent in the current S . cerevisiae genome were created by a reciprocal translocation event that joined them together from different ancestral locations . Concurrently the other synteny blocks that border each breakpoint in the ancestral genome were joined together by the same event . We ordered the synteny blocks in the manner in which they are found along each chromosome in S . cerevisiae , thus inferring all the interchromosomal rearrangements between the ancestral polyploid genome and S . cerevisiae ( Figure 4 ) . To confirm that the inferred reciprocal translocation events were correct , we found the location in S . cerevisiae of the other synteny block ends joined by each event . In cases where these synteny blocks are not adjacent in the S . cerevisiae genome , we found the ancestral breakpoint locations of the blocks that are adjacent to each of these blocks in S . cerevisiae , inferring another reciprocal translocation event . If the synteny blocks bordering each breakpoint were again not adjacent , this process was repeated . To obtain a set of likely gene gains ( Figure 5 ) we subtracted the set of S . cerevisiae genes represented in the ancestral genome from the curated set of 5601 S . cerevisiae genes currently used in YGOB . YGOB's S . cerevisiae gene set is based on the SGD annotation ( ‘verified’ and ‘uncharacterized’ protein-coding loci only ) with some additional manual curation . It omits loci that failed Kellis et al . 's test of reading frame conservation among sensu stricto species [49] . S . cerevisiae genes that are present in YGOB set but absent from the inferred ancestral set are candidates for having been gained in the S . cerevisiae lineage after the WGD . We did not include subtelomeric genes from the YGOB set , as orthologous relationships across species break down at the telomeres [49] . This candidate set of gains was then manually checked to ensure that there were no possible non-syntenic homologs that were ancestral but missing from our ancestral genome reconstruction due to a breakdown of synteny information . Any cases where a good candidate non-syntenic homolog was found were removed from the gained set and flagged as a likely transposition event . It is possible that the set of candidate gained genes may also contain ancestral genes that were lost in all of the non-WGD species used here but have orthologs in more distantly related outgroups . We compiled lists of the 245 S . cerevisiae intergenic regions that contain one or more tRNA genes [from SGD; 52] , the 228 intergenic regions that contain evolutionary breakpoints on the S . cerevisiae lineage , the 96 sites of gene gain in S . cerevisiae , and 267 intergenic regions that contain an origin of replication in S . cerevisiae ( from OriDB [41]; we included origins that overlap with genes ) . We counted the numbers of intergenic regions that contain combinations of multiple types of site . We then used computer simulation to estimate the significance of the observed numbers of coinciding sites ( Table 2 ) . In each of 1 million replicates we simulated a genome with 5100 intergenic spacers ( the estimated number of intergenic spacers between S . cerevisiae genes that are at an ancestral locus ) . We placed the same numbers of tRNA genes , origins , breakpoints , and gene gain sites as above into randomly chosen spacers in the simulated genome . Each type of site was placed randomly and independently of the other types of site . We then counted the numbers of spacers containing all possible combinations of types of site in the replicate . Finally , we compared the observed numbers of coinciding sites in the real data to the distribution of results from the simulation ( Table 2 ) . The proportion of simulated genomes in which the number of sites with a particular colocalization pattern matches or exceeds the observed number of such sites in the real genome is an empirical measure of the statistical significance of the observation , under the null hypothesis of a random distribution of sites . We then applied a false discovery rate correction to these empirical P-values .
|
Genomes evolve in structure as well as in DNA sequence . We used data from 11 different yeast species to investigate the process of structural evolution of the genome on the evolutionary path leading to the bakers' yeast S . cerevisiae . We focused on an ancestor that existed about 100 million years ago . We were able to deduce almost the complete set of genes that existed in this ancestor and the order of these genes along its chromosomes . We then identified the complete set of more than 100 structural rearrangements that occurred as this ancestor evolved into S . cerevisiae and found that some places in the genome seem to be fragile sites that have been broken repeatedly during evolution . We also identified 124 genes that must be relatively recent additions into the S . cerevisiae genome because they were not present in this ancestor . These genes include several that play roles in the unique lifestyle of this species , as regards the intensive production and consumption of alcohol .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"genetics",
"and",
"genomics/microbial",
"evolution",
"and",
"genomics",
"genetics",
"and",
"genomics/comparative",
"genomics",
"computational",
"biology/genomics",
"evolutionary",
"biology/genomics"
] |
2009
|
Additions, Losses, and Rearrangements on the Evolutionary Route from a Reconstructed Ancestor to the Modern Saccharomyces cerevisiae Genome
|
Robust reference values for fecal egg count reduction ( FECR ) rates of the most widely used anthelmintic drugs in preventive chemotherapy ( PC ) programs for controlling soil-transmitted helminths ( STHs; Ascaris lumbricoides , Trichuris trichiura , and hookworm ) are still lacking . However , they are urgently needed to ensure detection of reduced efficacies that are predicted to occur due to growing drug pressure . Here , using a standardized methodology , we assessed the FECR rate of a single oral dose of mebendazole ( MEB; 500 mg ) against STHs in six trials in school children in different locations around the world . Our results are compared with those previously obtained for similarly conducted trials of a single oral dose of albendazole ( ALB; 400 mg ) . The efficacy of MEB , as assessed by FECR , was determined in six trials involving 5 , 830 school children in Brazil , Cambodia , Cameroon , Ethiopia , United Republic of Tanzania , and Vietnam . The efficacy of MEB was compared to that of ALB as previously assessed in 8 , 841 school children in India and all the above-mentioned study sites , using identical methodologies . The estimated FECR rate [95% confidence interval] of MEB was highest for A . lumbricoides ( 97 . 6% [95 . 8; 99 . 5] ) , followed by hookworm ( 79 . 6% [71 . 0; 88 . 3] ) . For T . trichiura , the estimated FECR rate was 63 . 1% [51 . 6; 74 . 6] . Compared to MEB , ALB was significantly more efficacious against hookworm ( 96 . 2% [91 . 1; 100] , p<0 . 001 ) and only marginally , although significantly , better against A . lumbricoides infections ( 99 . 9% [99 . 0; 100] , p = 0 . 012 ) , but equally efficacious for T . trichiura infections ( 64 . 5% [44 . 4; 84 . 7] , p = 0 . 906 ) . A minimum FECR rate of 95% for A . lumbricoides , 70% for hookworm , and 50% for T . trichiura is expected in MEB-dependent PC programs . Lower FECR results may indicate the development of potential drug resistance .
The soil-transmitted helminths ( STHs , Ascaris lumbricoides , Trichuris trichiura , and the two hookworm species , Necator americanus and Ancylostoma duodenale ) are responsible for the highest burden among all neglected tropical diseases ( NTDs ) [1] . Recent global estimates indicate that in 2010 more than 1 . 4 billion people were infected with at least one of the four STH species , resulting in a global burden of approximately 5 . 2 million disability-adjusted life years ( DALYs ) ( 20% of the total number of DALYs attributable to NTDs ) [2] . Mass drug administration ( MDA ) programmes in which a single oral dose of albendazole ( ALB ) or mebendazole ( MEB ) - the drugs of choice for STHs - are periodically administered to pre-school and school aged children , are the main strategy for controlling the morbidity caused by STH [3] , [4] , and these programmes have recently received increased political and scientific attention [5] , [6] . While the laudable long-term aim is to eliminate soil-transmitted helminthiasis as public problem by 2020 [7] , the pledges of drug donations on this scale re-enforce the necessity for thoroughly designed monitoring systems that allow detection of any changes in anthelmintic drug efficacy that may arise through the evolution of anthelmintic drug resistance in these parasites . Both ALB and MEB belong to the same pharmaceutical group ( benzimidazole drugs , BZ ) sharing the same mode of action ( the inhibition of the polymerisation of microtubules ) . Thus , development of resistance against any BZ drug would most likely by accompanied by poor anthelmintic drug efficacy of the other BZ drugs . It is pertinent also that there is a paucity of anthelmintic drugs licensed for the treatment of STH infections in humans and available commercially , and hence should anthelmintic resistance against BZ drugs eventually emerge and spread , chemotherapy based control of STHs will be even more limited than at present with few acceptable alternative options [8] . Currently , assessment of the reduction in fecal egg counts following drug administration ( fecal egg count reduction ( FECR ) syn . egg reduction rate ) is the recommended method for monitoring the efficacy of anthelmintic drugs against STHs [9] . In contrast to other available assays , it allows for the assessment of drug efficacy against all three STHs ( vs . in vitro assays and molecular assays ) with a minimum of laboratory equipment ( vs . molecular assays ) [10]–[12] . However , the interpretation of the results from the FECR tests remains difficult , since reliable reference efficacy values for BZ drugs ( which can act as standard reference points for comparison with new data ) for each of the STH species are still lacking . In a systematic review and meta-analysis of published efficacy trials targeting STH infections , Keiser and Utzinger ( 2008 ) [13] highlighted that there is a lack of high-quality trials to determine these reference values . The available efficacy data have been obtained through a variety of widely differing study protocols , including protocols that used different diagnostic methods , different durations in follow-up periods , differing origin of the drugs ( i . e . , different manufactures and therefore different quality ) , and statistical analyses , all of which impede a robust meta-analysis of drug efficacy based on FECR [13] . As a response to these earlier limitations , our consortium has recently reported on the efficacy of a single oral dose of ALB ( 400 mg ) against STH in seven trials across sub-Saharan Africa , Asia , and Latin America based on a protocol standardized in respect to the origin of the drug ( Zentel , GlaxoSmithKline , batch N° L298 ) , the follow-up period ( 14 to 30 days ) , the egg counting method ( McMaster egg counting method ) , the statistical analysis , and the interpretation of the data ( group based FECR using arithmetic means ) [14] . This study suggested that a FECR of 95% for A . lumbricoides and 90% for hookworm should be the expected minimum in all future drug efficacy studies , and that FECR rates below these levels following a single dose of ALB , should be viewed as danger signs of potential development of drug resistance . For T . trichiura , reference FECR values could only be provided for specified mean fecal egg count ( FEC ) values at pre-intervention , as the drug efficacy measured by FECR decreased as a function of increasing mean FEC at the pre-intervention survey . For T . trichiura , we therefore expect FECRs of at least 90% , 70% , and 50% , in populations where the mean FECs are below 275 eggs per 1 g of stool ( EPG ) , 550 EPG , and 800 EPG , respectively , and even lower in settings where baseline infection intensities are higher [15] . Data derived from such standardized multi-center efficacy trials that establish reliable reference FECR values and assess the impact of infection intensity are still currently lacking for MEB . Therefore , in the present study we assessed the efficacy measured by means of FECR of a single oral dose of MEB ( 500 mg ) against STHs in six trials in sub-Saharan Africa , Asia , and Latin America using a protocol that we previously standardized in assessing the drug efficacy of a single dose of ALB , and compared the drug efficacy of both BZ drugs against each of the STHs .
The overall protocol of both the ALB and MEB trials was approved by the Ethics Committee of the Faculty of Medicine , Ghent University ( reference nos . B67020084254 and 2011/374 ) and was followed by local ethical approval for each trial site . For Brazil , approval was obtained from the Institutional Review Board from Centro de Pesquisas René Rachou ( no . 21/2008 ) , for Cambodia from the National Ethics Committee for Health Research ( no . 185 NECHR ) , for Cameroon from the National Ethics Committee ( nos . 072/CNE/DNM08 , 147/CNE/DNM/11 ) , for India from the Institutional Review Board of the Christian Medical College ( Vellore ) ( no . 6541; participated in the ALB study only ) , for Ethiopia from the Ethical Review Board of Jimma University ( Jimma ) ( no . RPGE/09/2011 ) , for United Republic of Tanzania from the Zanzibar Health Research Council ( nos . 20 , ZAMREC/0003/JUNE/2012 ) , and for Vietnam by Ethical Committee of National Institute of Malariology , Parasitology and Entomology ( Ha Noi ) and the Ministry of Health ( no . 752/QD-VSR ) . The parents of all subjects included in the studies signed an informed consent form . In Brazil and Ethiopia an informed consent form was obtained from children aged 10 or 11 years and above . In Cambodia and Ethiopia , a verbal assent was obtained from all children , and this procedure was approved by the respective ethics boards . Our studies assessing ALB and MEB are registered under ClinicalTrials . gov , identifiers nos . NCT01087099 and NCT01379326 , respectively ( CONSORT Checklist S1 ) . The MEB multi-center study reported here was carried out in six countries located in sub-Saharan Africa ( Cameroon , Ethiopia , and United Republic of Tanzania ( Zanzibar ) ) , Asia ( Cambodia and Vietnam ) , and Latin America ( Brazil ) . However , it is important to note that , while we refer to individual countries to identify results from particular trials , names of countries are used only to distinguish between six separate trials that were conducted in six geographically distinct regions of the world . These six STH-endemic countries were selected because of the presence of investigator groups/institutions with extensive experience in the diagnosis , and control of STH . These same six investigator groups were also involved in the earlier evaluation of the efficacy of a single-oral dose 400 mg ALB against STH in children , based on an identical standardized protocol [14] . Since study designs can have a significant effect on the subsequent calculation of efficacy and to ensure that our values for ALB and MEB were not confounded by study design , the protocol described by Vercruysse and colleagues for assessment of ALB was also used here to evaluate the drug efficacy of MEB [14] . In short , schools were selected based on previous STH surveys . Within schools , children were recruited on a voluntary basis . School children aged 4–18 years at each of the different trial sites were asked to provide a stool sample during a pre-intervention survey . For the initial sampling the aim was to enroll at least 250 STH-infected children for at least one species . This sample size was selected based on statistical analysis of study power , using random simulations of correlated over-dispersed FEC data reflecting the variance-covariance structure in a selection of real FEC data sets . This analysis suggested that a sample size of up to 200 individuals ( alpha = 0 . 05 , power = 80% ) was required to detect a 10% point drop from a null efficacy of 80% ( mean FECR individual ) over a wide range of infection scenarios . Standard power analyses for proportions also indicated that the detection of a 10% point drop from a null cure rate required sample sizes up to 200 ( the largest samples being required to detect departures from null efficacies of around 50% ) . Given an anticipated non-compliance rate of 25% , a total of at least 250 individuals was therefore considered necessary at each study site . A single oral dose of 500 mg MEB ( Vermox ) from the same manufacturer ( Janssen-Cilag , Latina , Italy , batch no: BCL2F00 ) was administered to the subjects at all study sites . Seven to 15 days after the pre-intervention survey ( Brazil: 7–14 days; Cambodia: 11–15 days; Cameroon: 9–11 days; Ethiopia: 14 days; United Republic of Tanzania: 14 days; Vietnam: 11–12 days ) , stool samples were again collected from the subjects . Subjects who were unable to provide a stool sample at follow-up , or who were experiencing a severe intercurrent medical condition or had diarrhea at the time of the first sampling , were excluded from the study ( Study Protocol S1 ) . All stool samples were individually processed by the McMaster egg counting method . McMaster is a flotation technique that is commonly used in veterinary parasitology both to assess intensity of gastro-intestinal parasite infections and to evaluate drug efficacy against these parasites . For the diagnosis and enumeration of STHs in public health , it has been found to be user-friendly ( vs . FLOTAC [16] ) robust ( vs . Kato-Katz thick smear [17] ) and accurate for enumeration of STHs , but less sensitive when intensity of infection is low ( vs . Kato-Katz and FLOTAC [16] , [17] ) ) Complementary data indicate that FECR estimates obtained by the McMaster are comparable to those using the Kato-Katz thick smear [18] , [19] . The standard operating procedure to perform a McMaster on human stools is described in more detail elsewhere [15] . Briefly , 2 g of stool were suspended in 30 ml of saturated salt ( NaCl ) solution at room temperature ( density: 1 . 2 ) . The fecal suspension was poured three times through a tea sieve to remove large debris . After thorough mixing 10 times , 0 . 5 ml aliquots were added to each side of a McMaster slide chamber . Both chambers were examined under a light microscope using 100x magnification and the FEC , expressed as EPG for each helminth species , was obtained by multiplying the total number of eggs counted under the microscope by a factor 50 . A detailed tutorial can be found on http://www . youtube . com/watch ? v=UZ8tzswA3tc . The efficacy of a single dose of MEB ( 500 mg ) against each of the three STH species ( the two hookworm species were treated as one species since the eggs of A . duodenale and N . americanus cannot be distinguished by conventional microscopy ) , as measured by FECR , was calculated for the different trials . We have not summarized the efficacy of MEB by means of cure rate ( CR; the proportion of the subjects who are not excreting eggs after drug administration ) . This is because an intervention may fail to cure STH infections ( CR = 0% ) , but may result in a FECR of 99% , which is satisfactory . Second , it has been shown that estimates of CR are highly affected by both sampling and diagnostic effort , estimates being overestimated when the sampling and diagnostic effort is minimized . This was in sharp contrast to FECR estimates , which remained unchanged regardless of both sampling and diagnostic effort [20] . To-date , a wide range of formulae has been used to calculate FECR , each differing in terms of the statistical unit ( individual vs . group ) and how the mean FEC is calculated ( arithmetic vs . geometric ) . However , recent studies suggest that the group-based formula using the arithmetic mean , as described below , is a suitable metric for evaluating drug efficacy . Compared to the other formulae , it represents a robust indicator ( vs . individual-based formula [14] ) that provides accurate estimates of drug efficacy ( vs . group-based formula using geometric mean ) [14] , [21] . Moreover , it is important to note that there is no common formula for calculating the variance for each of these FECR formulae . The formula used here to calculate variance for the group-based FECR using the arithmetic mean is described below and is based on the Delta method [22] . We first analyzed the trial outcomes for each of the three STHs separately using FECR data at the trial level , and its corresponding variance and sample size , and secondly we compared data from both the current trials with MEB and our earlier trials with ALB , employing meta-analytical approaches . In addition , the impact of infection intensity at the pre-intervention survey on the FECR rate of both BZ drugs was evaluated . To assess the FECR rate of MEB , generalized mixed effect models were fitted for each of the three STH species in turn , with the FECR rate at the trial level as the dependent variable , and the mean FEC at the pre-intervention survey as a covariate . To compare the FECR rates between ALB and MEB , generalized mixed effect models were fitted for each of the three STH species with FECR at the trial level as the dependent variable , and BZ drug ( two levels: ALB and MEB ) and mean FEC at the pre-intervention survey as covariates , and the interaction between these covariates . For both analyses , we only included trials for which at least 50 subjects who had been treated and provided stools at both pre- and post-intervention surveys were available . The different MEB and ALB trials included in the analyses are listed in Table 1 and Table 2 , respectively . These tables also describe for each trial the sample size , mean age , sex ratio ( number of female subjects/number of male subjects ) , mean FEC , and the level of infection intensity at the pre-intervention survey for each of the three STH species separately . The levels of infection intensity correspond to the low , moderate , and high intensity of infection ranges , as described by WHO [23] . For A . lumbricoides these were 1–4 , 999 EPG , 5 , 000–49 , 999 EPG , and ≥50 , 000 EPG; for T . trichiura these levels were 1–999 EPG , 1 , 000–9 , 999 EPG , and ≥10 , 000 EPG; and for hookworm these were 1–1 , 999 EPG , 2 , 000–3 , 999 EPG , and ≥4 , 000 EPG , respectively . The ALB trials have been described previously by Vercruysse et al . ( 2011 ) [14] and Mekonnen et al . ( 2013 ) [24] , targeting A . lumbricoides ( five trials ) , T . trichiura ( five trials ) , and hookworm ( 7 trials ) . Each of these trials report FECR rates of a single dose ALB ( 400 mg ) , all were based on the aforementioned trial design , and with the exception of one trial ( India ) the same laboratories which assessed the FECR rates in current study were also involved in these ALB trials . The meta-analysis was carried out using the ‘metafor’ package of the statistical software R [25] . The level of significance was set at p<0 . 05 .
Figure 2 illustrates the outcome of the analyses of FECR of MEB by means of forest plots for A . lumbricoides , T . trichiura , and hookworm infections . Overall , the estimated FECR rate [95% confidence interval [CI]] of MEB was the highest for A . lumbricoides ( 97 . 6% [95 . 8–99 . 5] ) , followed by hookworm ( 79 . 6% [71 . 0–88 . 3] ) . For T . trichiura , the estimated FECR rate was lower , namely 63 . 1% [51 . 6–74 . 6] . An association between the mean FECs at pre-intervention and the FECR rate was observed for A . lumbricoides only . For this STH species , the model predicted that the FECR rate would drop by 0 . 4% as mean FECs at pre-intervention increase by increments of 1 , 000 EPG ( z = -2 . 97 , p = 0 . 003 ) . For the remaining two STHs , there was no significant relationship between FECR rate and mean FEC at pre-intervention ( T . trichiura: z = 1 . 46 , p = 0 . 144; hookworm: z = 1 . 00 , p = 0 . 316 ) . Figures 3 to 5 illustrate the outcome of the meta-analyses of the FECR rate against STHs for ALB and MEB by means of forest plots for A . lumbricoides , T . trichiura , and hookworm infections , respectively . Overall , ALB resulted in statistically higher FECR rates against A . lumbricoides ( ALB: 99 . 9% [99 . 0–100] vs . MEB: 98 . 0% [96 . 9–99 . 1] , z = −2 . 5 , p = 0 . 012 ) and hookworm infections ( ALB: 96 . 2% [91 . 1–100] vs . MEB: 80 . 6% [74 . 4–86 . 8] , z = 37 . 4 , p<0 . 001 ) . For T . trichiura there was no significant difference in FECR rate ( ALB: 64 . 5% [44 . 4–84 . 7] vs . MEB: 62 . 7% [40 . 8–84 . 6] , z = −0 . 1 , p = 0 . 906 ) . Associations between mean FEC at pre-intervention and the FECR rate were observed for both A . lumbricoides and T . trichiura but in respect of different AE , ( Figure 6 ) . For A . lumbricoides , the model predicted that the FECR rate after treatment with ALB should remain unchanged across mean FEC at pre-intervention , but that the FECR rate after MEB treatment should fall on average by 0 . 4% for each 1 , 000 EPG incremental increase in mean FEC at pre-intervention ( interaction term between BZ drug and mean FEC at the pre-intervention survey , z = −2 . 93 , p = 0 . 033 ) . For T . trichiura , the model predicted that the FECR rate following treatment with ALB should decrease on average by 7 . 8% per incremental increase of 100 EPG in mean FEC at pre-intervention ( = main effect of mean FEC at the pre-intervention , z = −9 . 1 , p<0 . 001 ) . However , there was a significant interaction between BZ drug and mean FEC at pre-intervention ( z = 6 . 9 , p<0 . 001 ) , indicating a significant difference between the two BZ drugs in the rate of fall of the FECR rate with increasing pre-intervention FEC . In contrast to the 7 . 8% fall/100 EPG increment for ALB , for MEB , the model predicted a net fall in FECR rate of only 1 . 1%/100 EPG increment , which as shown earlier when assessed separately from ALB , did not represent a significant association . For hookworm , the FECR rate of both BZ drugs did not depend significantly on the mean FEC at pre-intervention .
This is the first study that has generated a robust , reliable estimation of the FECR rate following treatment with MEB , and has compared thoroughly the efficacy of MEB with that of ALB , against STH infections . Although we must acknowledge some variation in follow-up period across the trials , both the ALB and MEB trials were standardized at a level unprecedented in the scientific literature [14] . Moreover , most previous studies evaluating drug efficacy of BZ drugs against STHs have generally not summarized their efficacy results by means of the group-based FECR formula , using the arithmetic mean and its corresponding 95% CI , which are now recognized as a suitable , indeed the most informative metric , for the outcome of such trials [14] and are needed to enable a meta-analysis of drug efficacy against STHs [13] , . Overall , the results of this study indicate that a single oral dose of MEB is most efficacious against A . lumbricoides infections , followed by hookworm , but that it is relatively inefficacious for infections with T . trichiura , thus confirming the earlier efficacy studies reviewed by Bennett and Guyatt [26] and Keiser and Utzinger [13] . The relatively poor efficacy of a single dose treatment with either MEB or ALB in reducing T . trichiura FECs is not a novel finding [13] , [26] , and has resulted in ongoing research on the development and evaluation of new drugs or drug combinations that reduce T . trichiura worm burdens more effectively following single dose application , e . g . pyrantel/oxantel [27] , mebendazole/ivermectine [28] , oxantel , [29] , and papaya cysteine proteinases [30] . Based on the overall drug efficacy results for the three STH species , we recommend that monitoring programs of single-dose MEB-dependent PC use a minimum FECR ( group-based formula using arithmetic mean ) of 95% for A . lumbricoides , 70% for hookworm , and 50% for T . trichiura as appropriate reference values ( as they are below the lower limit of the 95% CI of overall estimates ) , and that efficacy levels below this should raise concern about the possible emergence of drug resistance . Compared to a single oral dose of ALB , MEB was significantly less efficacious against hookworm and to a lesser extent against A . lumbricoides infections , but equally inefficacious for T . trichiura infection . In addition , the efficacies of both ALB and MEB were dependent on the intensity of A . lumbricoides and T . trichiura infection , decreasing with increasing infection intensity . However , the magnitude of this loss of efficacy as a function of increasing infection intensity differed between the two BZ drugs and the STH species . Between the BZ drugs , the change in drug efficacy was more pronounced for MEB with A . lumbricoides , whereas for T . trichiura the decrease was more pronounced for ALB . Among STHs , the overall impact of infection intensity on treatment with BZ was pronounced for T . trichiura ( 1 . 2–7 . 8% per 100 EPG ) , but almost negligible for A . lumbricoides ( 0 . 4% per 1 , 000 EPG ) . For hookworm , the efficacy did not depend on the infection intensity . This could be explained by either a true constant efficacy across infection intensities or a low number of moderate and high infection intensities in these trials ( see Table 1 ) . The bases of these differences in efficacy between the BZ drugs and their effects on STHs remain unclear , mainly due to the paucity of detailed pharmacokinetic and pharmacodynamics studies in pediatric populations in STH-endemic countries [31] . Currently , recommendations in PC programs are solely based on the overall prevalence of STHs , with these drugs being administered once a year when the STH prevalence is ≥20% and <50% , and twice a year when the prevalence is ≥50% [4] . Although this study indicates that the best choice of BZ drug depends on the relative prevalence and species of STH infections ( ALB: hookworm> T . trichiura; MEB: T . trichiura> hookworm ) , practical experience with both drugs in the field over several years indicates that both are equally effective in controlling all three STH species irrespective of their initial prevalence and intensity of infection [32] , [33] . However , future studies are required to ( i ) evaluate the difference between BZ drugs in long-term impact ( prevalence , infection intensity , and occurrence of single nucleotide polymorphisms in the β-tubulin gene associated with BZ resistance ) ; ( ii ) determine STH-specific thresholds for infection intensity to justify choice of BZ drugs; and ( iii ) assess the cost-effectiveness of distributing more than one class of BZ to different regions in a country [12] , [34] . In conclusion , our findings suggest that FECR rates exceeding 95% for A . lumbricoides , 70% for hookworm , and 50% for T . trichiura should be expected in all future surveys , and that any FECR rate below these levels following a single oral dose of MEB ( 500 mg ) should be viewed with concern in light of potential development of drug resistance . In addition , the study highlights the need for detailed pharmacokinetic/pharmacodynamic studies for single-oral dose of BZ drugs in pediatric populations in countries where STHs are endemic to gain additional insights into the observed differences in drug efficacy between ALB and MEB across the various STH species . Finally , additional recommendations advising those running PC programs about which of the BZ drugs to administer in a given setting ( i . e . , depending on the extent of T . trichiura and hookworm infections in a specific location/population ) may improve the long-term benefits accruing from PC programs .
|
Soil-transmitted helminths ( STHs; roundworms , whipworms , and hookworms ) infect millions of children in sub-tropical and tropical countries , resulting in malnutrition , growth stunting , intellectual retardation , and cognitive deficits . To fight against STH , large-scale deworming programs are implemented in which anthelmintic drugs ( either albendazole ( ALB ) or mebendazole ( MEB ) ) are administered . Currently , these large-scale programs are intensifying , highlighting the need to closely monitor the efficacy of anthelmintic drugs to detect changes in drug efficacy that may arise through the evolution of anthelmintic drug resistance in the parasites . We have previously defined the minimum expected efficacy of ALB based on the fecal egg count reduction ( FECR ) rate , but these reference values are lacking for MEB . Therefore , we therefore evaluated the FECR rate of MEB against STHs in six STH endemic countries . In addition , we compared the results of the FECR rate for MEB with those we obtained previously for ALB . The results confirm that MEB treatment was highly efficacious against roundworms , and to a lesser extend against hookworms , but not against whipworms . Compared to ALB , MEB is less efficacious against hookworm , but equally efficacious against roundworms and whipworms . Based on this study we propose the minimum expected FECR rate for MEB-dependent large-scale deworming programs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases",
"biology",
"and",
"life",
"sciences",
"microbiology",
"medicine",
"and",
"health",
"sciences"
] |
2014
|
Assessment of Anthelmintic Efficacy of Mebendazole in School Children in Six Countries Where Soil-Transmitted Helminths Are Endemic
|
Animal welfare requires the adequate housing of animals to ensure health and well-being . The application of environmental enrichment is a way to improve the well-being of laboratory animals . However , it is important to know whether these enrichment items can be incorporated in experimental mouse husbandry without creating a divide between past and future experimental results . Previous small-scale studies have been inconsistent throughout the literature , and it is not yet completely understood whether and how enrichment might endanger comparability of results of scientific experiments . Here , we measured the effect on means and variability of 164 physiological parameters in 3 conditions: with nesting material with or without a shelter , comparing these 2 conditions to a “barren” regime without any enrichments . We studied a total of 360 mice from each of 2 mouse strains ( C57BL/6NTac and DBA/2NCrl ) and both sexes for each of the 3 conditions . Our study indicates that enrichment affects the mean values of some of the 164 parameters with no consistent effects on variability . However , the influence of enrichment appears negligible compared to the effects of other influencing factors . Therefore , nesting material and shelters may be used to improve animal welfare without impairment of experimental outcome or loss of comparability to previous data collected under barren housing conditions .
The provision of species-appropriate environmental enrichment—which can be defined as additions to the cage environment that allow natural motivated behaviors enabling the animals to control their environment [1]—is generally promoted as a way to improve animal welfare [1 , 2] and is also legally requested within the European Union by Directive 2010/63/EU [3] . However , there are various kinds of enrichment items available , and their imprudent application might interfere with the comparability of scientific results as even “seemingly minor alterations in the environment can have significant effects on experimental outcomes” [4] . A study by Macri et al . suggests that the adoption of environmental enrichment according to Directive 2010/63/EU might strongly influence the conclusions drawn from pharmacological and behavioral studies . In their study , they tested a synthetic cannabinoid compound and concluded that “whether the compound shall be considered a cannabinoid agonist may strongly depend on the specific conditions in which mice are reared” [5] . This underlines the potential risk following the implementation of inconsiderate enrichment strategies without preceding evaluation . The term environmental enrichment is widely applied and also includes experimental paradigms , where intensive environmental enrichment strategies are used to explore effects of a more complex environment [6] . This so-called “super-enrichment”—as , for example , described in a protocol by Slater et al . [7]—induces behavioral [8] , emotional [9 , 10] , physiological [11] , and neurobiological [10 , 12 , 13] changes in mice compared to barren housing . Moreover , such environmental enrichment can improve pathological conditions . For example , enrichment can suppress tumor growth and reduce adiposity [7] and alleviate the intensities of various phenotypes in animal models ( see [14] for an overview ) . Besides such use of ( super ) enrichment as an experimental tool , simple enrichment is regularly used in laboratory animal facilities to ensure health and well-being of the animals and to meet their physiological and ethological needs as much as possible . It is thus applied as a refinement strategy according to the Three Rs ( 3Rs ) of Russell and Burch [15] . The results of studies that determine the effects of those more commonly used forms of enrichment are varied . Some authors found that nesting material influenced behavioral parameters of mice [16] or affected the scientific outcome in a well-described mouse model for allergic asthma [17] . Shelters as enrichment also altered motor coordination and some behavioral parameters in mice [18] . Furthermore , several studies revealed that even simple forms of enrichment , like nesting material [19] , shelter [20] , shelter combined with a scaffolding [21] , or labyrinths [22] , affected aggression and stress-related parameters in male mice of certain strains . Others found no effects of nesting material [23] or a shelter [24] on behavior and some physiological parameters . Moreover , there has been much discussion about possible consequences of environmental enrichment on variability in data . Concern has been expressed by some authors that the response to and experience with environmental enrichment might differ between individuals so that environmental enrichment might lead to a higher variability in physiological parameters [25–28] . This might add to the individual variability within groups [29] and thereby increase the number of animals needed to reach statistical power . On the other hand , a multilaboratory study by Wolfer et al . found that environmental enrichment did not increase within-group variability in 19 out of 20 parameters of 4 behavioral tests in female mice [30] . Richter et al . describe a different approach and suggested that a conscious standardized heterogenization of environmental conditions might indeed increase within-experiment variation but then might also lead to lower between-experiment variation and therefore might improve external validity of experiments . An efficient heterogenization strategy is yet to be determined , though [31–33] . But while an environmental heterogenization strategy might give information about generalizability , according to van der Staay et al . , there is the risk that subtle effects might be missed [34] . The choice of study design ( strict standardization versus heterogenization ) is therefore heavily dependent on the scientific questions a study aims to answer [34] . Taken together , despite a diverse body of literature , the assessment of the actual influence of enrichment remains difficult because the existing literature is , in large part , based on ( single-cohort ) studies that examine environmental enrichment effects under very specific conditions in respect to examined strain , sex , enrichment device , and parameters . But direction and size of effects seem to vary depending on the type and combination of enrichment [35] , the mouse strain [36 , 37] , sex [38] , time and duration of enrichment [39] , and which parameters were studied [26]; the applicability across rodent species , strains , sexes , and ages is uncertain [40] . To prevent unclear or spurious results and the need for higher numbers of animals due to increased variability within groups , a systematic evaluation of enrichment strategies is crucial [41 , 42] , and environmental enrichment interventions should be “carefully selected , thoroughly defined , and purposefully used” [4] . This is of special importance in light of the ongoing debate about reproducibility because certain environmental factors might account for irreproducible rodent experiments [43 , 44] and variation or lack of standardization in environmental enrichment strategies might contribute to problems with reproducibility in preclinical research [4] . Kent et al . conclude in the ACLAM position statement on reproducibility that “it is incumbent on laboratory animal veterinarians and the scientific community to define elements of study design that affect experimental reproducibility” [45] . Our study approach was therefore to investigate the effect of 2 simple , commonly used , and easily applicable enrichment items—namely , a shelter and nesting material ( nestlet ) versus nestlet alone or none of the above—on means and variability ( expressed by coefficients of variation [CVs] ) of a wide range of physiological parameters in a systematic , highly standardized study design ( see Fig 1 ) . To this end , we wanted to find out whether those environmental enrichments would change results of future and follow-up studies compared to the former standard of barren housing . For our purposes , we also specifically wished to ascertain whether environmental enrichment alters the measuring system of the German Mouse Clinic [46–48] . We examined male and female wild-type mice of 2 commonly used inbred mouse strains , C57BL/6NTac ( B6 ) and DBA/2NCrl ( D2 ) . The study was conducted in 3 replicates using 3 independent cohorts of mice to give information about variability .
We analyzed the influence of environmental enrichment on the mean of our parameters using linear models with “main factors”: enrichment , sex , and cohort . We used a variable selection using the Bayesian Information Criterion ( BIC ) to determine differences between the experimental groups . The reference group was the unenriched females from cohort 1 . The influence of main factors ( enrichment , sex , cohort ) on the mean of all metric parameters and their double interactions is shown as a heatmap ( Fig 2 ) with strength of color reflecting the size of difference . If the variable selection yielded a variable as nonrelevant , it was not included in the model , and the parameter was marked as grey ( i . e . , no difference ) in the heatmap ( Fig 2 ) . To better illustrate the effects of enrichment compared to the effects of factors sex and cohort , we computed smoothed histograms ( Fig 3 ) of parameters that were influenced by the respective main factors . For an exemplary evaluation of the biological relevance of our findings in the open field test , we prepared boxplots of raw data for the 4 main parameters on which we normally focus . They are “distance traveled total” ( index of locomotor activity ) , “number of rears total” ( index of exploratory activity ) , “percent center distance total , ” and “center permanence time” ( indices of anxiety-related behavior ) . Furthermore , in each plot we included data of more than 200 B6 wild-type animals , which were measured as control mice in phenotyping projects of the German Mouse Clinic ( GMC ) . Because these B6 were the same age and used in the same timespan as the mice of this study , the data can serve as a biological range for B6 mice ( Fig 4 ) . Raw data in form of boxplots ( S1 Fig ) and individual values ( S1 Data ) for every parameter are provided in Supporting information . Some aspects of our analysis are illustrated below by considering the 2 different mouse strains used ( B6 and D2 ) individually . In B6 mice , the means of 69 out of 161 parameters were changed by enrichment; a higher number of parameters was affected by sex ( 118/161 ) and cohort ( 152/161 ) . Overall , percentage differences of the mean of the respective groups and their control were distinctly higher for factor sex and cohort than for factor enrichment ( Fig 3A ) . Considerably fewer parameters were influenced by enrichment than by the other main factors as can be seen by the smaller area under the curve for factor enrichment compared to factors sex and cohort . Both enrichment curves were narrower than the curves of the other main factors . This indicates that the influence of enrichment was considerably smaller than that of the other main factors . A closer look at single research areas in the heatmap in Fig 2 reveals that some were rather robust against housing effects . The measured parameters of the following tests were mainly unchanged by enrichment compared to controls in B6: rotarod ( neurology ) , Scheimpflug imaging ( eye ) , auditory brain stem response ( ABR; neurology ) , indirect calorimetry , and quantitative nuclear magnetic resonance ( qNMR; energy metabolism ) . Other tests were more susceptible to effects of enrichment; in the open field test ( behavior ) , 20 out of 34 parameters were influenced by nest and double enrichment . The percentage difference between mean of nest- and double-enriched groups and mean of controls ranged between 1% and 15% in 17 out of 20 ( double enrichment ) and 18 out of 20 ( nest enrichment ) parameters . Two of the 4 main parameters of the open field test ( “number of rears total” and “center permanence time” ) were affected by enrichment . For those parameters , most values lay within the biological range of B6 ( Fig 4 ) . As expected , there were sex differences for many parameters . Although our tests were performed under strictly standardized conditions , there were differences between the cohort replicates for a wide range of 152 out of 161 parameters . For D2 mice , a difference between enriched and nonenriched mice could be found in 88 out of 160 parameters . For the other main factors , 144 out of 160 ( sex ) and 135 out of 160 ( cohort ) parameters were affected by the respective factors . Overall , as in B6 , fewer parameters were influenced by factor enrichment than by other main factors , which is expressed by the smaller area under the curve for factor enrichment in comparison to the other main factors ( Fig 3B ) . Curves of double and nest enrichment were narrower than those of other main factors , which indicate that the influence of enrichment , on average , was smaller than the influence of factors cohort and sex . Again , Fig 2 reveals that some tests appeared to be less sensitive towards effects of environmental enrichment than others , for example , Scheimpflug imaging and virtual drum ( eye ) , indirect calorimetry ( energy metabolism ) , immunoglobulin E ( IgE; allergy ) , and ECG ( cardiovascular ) . As in B6 , factor sex also influenced a large part of parameters with partially prominent effects in D2 mice . Factor cohort also influenced many parameters regarding mean values; 135 out of 160 parameters were changed by cohort in D2 mice . To evaluate the impact of environmental enrichment on variability , we used bootstrapped samples of the original data . Therefore , we drew a sample from each subgroup 1 , 000 times . As a comparable measure for variability , the CV was used . Bootstrapped CV values were then analyzed with linear models , using enrichment , sex , and cohort as main factors . The influence of the main factors on bootstrapped CVs is shown as a heatmap ( Fig 5 ) . Results of the bootstrap method are summarized by computed confidence intervals for estimators ( β ) , and bootstrapped CVs were then classified into the following 3 categories: β includes 0 , thus no effect is assumed ( grey ) ; confidence interval for β is greater than 0 , i . e . , bootstrapped CVs are increased compared to reference group ( violet ) ; confidence interval for β is below 0 , i . e . , bootstrapped CVs are decreased compared to reference group ( yellow ) . In B6 mice , CVs of 84 out of 161 and 93 out of 161 parameters were affected ( either increased or decreased ) by double enrichment and nest enrichment , respectively , compared to controls . For D2 mice , double enrichment influenced CVs of 101 out of 160 parameters , and nest enrichment affected 91 out of 160 parameters in comparison to controls . Overall , no distinct patterns could be observed that hinted towards a general increase or decrease of CVs of parameters in a certain test due to factor enrichment . Rather , within tests , CVs of individual parameters were increased , decreased , or not changed concomitantly ( Fig 5 ) . For the other main factors , CVs of 107 out of 161 ( sex ) , 114 out of 161 ( cohort 2 ) , and 112 out of 161 ( cohort 3 ) parameters were influenced in B6; in D2 , CVs of 114 out of 160 ( sex ) , 101 out of 160 ( cohort 2 ) , and 114 out of 160 ( cohort 3 ) parameters were changed . Overall , no clear indication could be found that factor enrichment induced higher CVs neither in B6 nor in D2 . However , enrichment ( double and nest ) influenced variability in fewer parameters than sex and cohort in both strains of mice . No effects of different housing conditions were found on categorical and qualitative data relevant for detection of abnormalities ( in Smithkline Beecham , MRC Harwell , Imperial College , the Royal London Hospital Phenotype Assessment [SHIRPA] of the neurology screen , see S1 Table; in morphological examination of the dysmorphology screen , see S1 Text; in histopathological examination of the pathology screen , see S2 Table ) . Data of these tests were not included in the linear model analysis .
The aim of this study was to investigate the effects of commonly used environmental enrichment on a comprehensive range of physiological parameters that cover key experimental procedures of medical research . Three independent cohorts of mice of 2 strains and both sexes with 3 different housing conditions were measured in a highly standardized study design . Mean values of about half of our quantitative parameters were affected by enriched housing in both strains ( B6: 43%; D2: 55% ) . However , the differences found were mostly small , and the biological relevance still has to be interpreted separately for each parameter . For example , in our study , two-thirds of the parameters of the open field test were changed by enrichment in B6 mice . But many of those parameters are correlated with each other , so that if one is changed , the others change concurrently , which might seem to inflate the number of affected parameters . Moreover , the differences of most parameters were rather small ( 1%–15% ) . To further evaluate the biological relevance of our findings in the open field test , we compared results of the 4 main parameters ( “distance traveled total , ” “number of rears total , ” “percent center distance total , ” and “center permanence time” ) , on which we normally focus with the biological range of B6 mice . Two of the 4 mentioned parameters of the open field test ( “number of rears total” and “center permanence time” ) were affected by enrichment . However , these effects could not be observed in all 3 cohorts , and even for these metrics , most of the measured values also lay within the biological range of B6 mice . This suggests that the effects of factor enrichment were within the regular variation that can be seen between different cohorts . It has already been shown that large effects—e . g . , strain differences in behavioral testing—could be reproduced in the environment of different laboratories despite differences in absolute values [49 , 50] . The fact that we did not find biologically relevant effects of simple enrichment on , e . g . , behavior , while others did [16] might indicate that the effects were too small to be found consistently . On the other hand , we observed that some tests and parameters were robust towards the influence of environmental enrichment , as they were not changed . For some parameters , our results provide the same indication as studies in which no effects of enrichment were found in rotarod [16] , body weight [27 , 51] , food intake [51 , 52] , or liver and spleen weight [27] in B6 mice . Other studies observed changes of body weight [23 , 52] and food intake [23] due to certain kinds of environmental enrichment , but—unlike them—our results did not hint towards changes in body weight . The differential findings between the studies can in part be explained by different study designs because factors like type and combination of enrichment [35] , examined strain [36 , 37] , sex [38] , time and duration of enrichment [39] , and studied parameters [26] influence the effects of environmental enrichment . In our study , however , all those factors were standardized , and other environmental factors seemed to influence parameters equally or even more so than factor enrichment . These are represented by factor cohort , which changed 94% ( B6 ) and 84% ( D2 ) of examined parameters . Compared to factor enrichment , influence of cohort was apparent for more parameters , and on average , the observed effect was also stronger . Cohort effects have already been described as temporal variation [53] in phenotyping studies and can be attributed to differing body weights [54] , seasonal variation [55] , uncontrolled noise [56] , sex of the experimenter [57] , differing experimenters [58] , and probably other factors that are yet unknown [4] . Tests in our study were conducted by differing experimenters of both sexes , which might have contributed to variation between cohorts [57 , 58] . Tail handling of mice has been shown to induce anxiety , which might have influenced behavioral results in our study [59 , 60] , and battery testing itself can also induce additional noise [61] and add to the differences between cohorts . Influence of the above-discussed environmental factors attributing to cohort effects could also be accountable for differential study results that examine effects of simple enrichment in a single-cohort design . Furthermore , other ( yet unknown ) environmental factors might interfere with the measurements of the effects of enrichment . In a recent study , scientists failed to reproduce the finding that environmental enrichment decreased tumor growth [62] and also concluded that “other environmental factors are likely acting either in concert with or against environmental enrichment conditions to provide the variable results found” [63] . Altogether , even though we found that enrichment affects the mean of some parameters , its overall influence appeared to be of minor biological relevance in the background of the stronger environmental effects represented by the cohort . However , our study was designed to give a broad overview of possible effects of simple enrichment on a large number of physiological parameters of different research fields . Because we did not test an a priori hypothesis , our statistical analysis did not include a measure of statistical significance . Providing such a broad summary is helpful and can be used by other researchers to focus on single parameters of interest in confirmative studies . Furthermore , for logistical reasons , a blind outcome assessment was not possible in our study . However , most of the conducted tests are considered to be robust to subjective bias because animals are examined with the help of technical devices and parameters are digitally recorded and analyzed . We did not address the question , whether the used enrichment benefits animal welfare or provides a more realistic scenario in terms of resembling a natural environment . It is well known that barren housing conditions can cause impaired brain development and abnormal repetitive behaviors [13 , 64] , which can compromise the validity of animal experiments and add variation [65] . However , the results we present here are , to our knowledge , the first systematic comparison of simple forms of enrichment with the former state-of-the-art—i . e . , barren housing—on a large number of physiological parameters . Apart from analyzing effects of common enrichment items on mean values , our second point of interest was in examining the effect on variability . We found that environmental enrichment influenced the CVs of 52% to 63% of parameters with no clear tendency towards an increase or a decrease . This is in concordance with other studies examining the effect of environmental enrichment on variability of data . Some studies found that variability of some parameters can be increased under enriched housing conditions [25 , 28] or rather decreased [58] . Others found no effects of housing on variability [11 , 66 , 67] or inconsistent results with effects on variability dependent on sex and studied parameters [26] . But the mentioned studies were single-cohort studies , which might account for inconsistency of results between studies . The only other multicohort study studied female mice only and found that within-group variability of several behavioral parameters was not affected by enriched housing [30] . Knowledge of possible influence of factors on variability is crucial to estimate whether reproducibility might be jeopardized . Concerns have been expressed that individual mice might interact differently with enrichment , which might lead to an increased variability of physiological parameters and therefore to higher animal numbers needed to obtain the appropriate statistical power in statistical evaluation [25 , 26] . If indeed enrichment led to higher variability , experimental results achieved with the same number of animals would not be reproducible after changing the housing conditions . This would yield an ethical conflict between reduction and refinement because enrichment is applied to enhance animal welfare ( refinement ) , while higher animal numbers would represent a contrast to the principle of reduction . However , our study gave no clear indication that simple forms of environmental enrichment increase the variability of a broad range of physiological parameters . Moreover , it must be stressed that absolute replicability of results cannot be achieved because the environmental conditions cannot be fully reproduced despite standardization of environmental factors . However , relevant differences for hypothesis-driven comparisons should be reproducible over the small noise induced by differing environmental factors to be of external validity . As our study shows , simple environmental enrichment according to Directive 2010/63/EU adds only little to the noise between cohorts . Broadly and comprehensively speaking , our data argue that simple environmental enrichment does not greatly vary relevant specific parameters of biological and medical enquiry . We conclude that nesting material and shelters can thus be liberally applied to improve laboratory animal welfare without skewing results , and new data from these conditions can be compared to past data that were collected in barren housing .
All animal experiments were performed in compliance with German animal welfare law and were approved by the institutional animal care and use committee ( “Committee for animal experiments and animal facility” of the Helmholtz Zentrum München ) and by the District Government of Upper Bavaria ( approval number: 55 . 2-1-54-2532-199-13 ) . A total number of 360 C57BL/6NTac ( B6; Taconic , Denmark ) and DBA/2NCrl ( D2; Charles River , Germany ) mice of both sexes were used in our study . Sixty mice ( 30 male , 30 female ) of each strain were used in 1 set of examinations ( see Table 1 for a full visual representation of the breakdown of the study design ) . This set of examinations was repeated twice so that 3 independent cohorts of 60 mice per strain were examined on the whole within a total timespan of 13 mo . Upon arrival , at 3 wk of age , animals were weighed , ear tagged , and split into 3 different groups ( n = 10 ) following a stratified randomization scheme so that all groups had a similar body weight distribution at the beginning . All mice were housed in same-sex groups of 5 , in type II polycarbonate cages in individually ventilated caging ( IVC ) systems ( Tecniplast Greenline GM 500 ) with bedding ( wood shavings , Altromin ) and water and food ad libitum ( standardized mouse diet , 1314 , Altromin ) . The enrichment groups additionally had either a nestlet ( PLEXX , Article ref . 14010 ) —which are cotton pads that mice can shred and use as nesting material ( group “nest” ) —or a nestlet plus an orange plastic mouse igloo ( PLEXX , Article ref . 13100 ) as a shelter ( group “double” ) , whereas the “control” group had no enrichment items at all ( pictures of the 3 housing conditions are shown in S1 Fig ) . Nestlets are commonly used in laboratory animal facilities and can additionally be applied to evaluate mouse welfare by nest complexity scoring as needed [68 , 69] . Cages were cleaned , and enrichment items were renewed weekly . On those occasions , mice were also weighed and examined to evaluate their health . The animal room had a controlled 12/12–h light/dark cycle ( lights on at 6:00 AM ) , temperature ( 22 ± 2°C ) , and relative humidity ( 45%–65% ) . At 3 wk of age , mice were imported into the animal facility and randomly assigned to the experimental groups ( “control , ” “nest , ” “double” ) . From wk 9 to 21 , mice were examined following the workflow of the primary screen for phenotypic analysis with minor adaptions ( Fig 1 ) . The phenotyping screens were performed at the German Mouse Clinic , which offers a large-scale standardized and comprehensive phenotypic analysis of mice . In this study , mice were examined in the fields of behavior , dysmorphology , neurology , clinical chemistry and hematology , eye , allergy , energy metabolism , pain perception , cardiovascular health , and pathology ( Fig 1 ) . The phenotyping screens followed standardized examination protocols , as previously described ( www . mouseclinic . de ) [46–48] . In general , n = 10 mice per group ( see Table 1 ) were examined , except for the eye screen ( n = 7 ) , cardiovascular screen ( n = 7 in the first cohort of B6 mice , only for ECHO ) , and pathology screen ( n = 4–5 for macroscopical analysis; n = 1–2 for histological analysis ) . Due to a few cases of unexpected death , animal numbers of groups were in some instances reduced to n = 9 and once to n = 8 ( for details , see S2 Text ) . Our study aimed at answering the following questions: firstly , whether the mean of each parameter is influenced by enrichment and secondly , whether enrichment has an influence on the variability of the measurements . We considered sex and cohort as additional predictors for the possible alteration of mean and variability of the measurements . The influence of enrichment on the mean values of the measured parameters was evaluated with linear models defined by y=βIntercept+βenrichmentnest+βenrichmentdouble+βsexmale+βcohort2+βcohort3+alldoubleinteractions+ε A variable selection using the BIC was performed . The heatmap ( Fig 2 ) shows the color-coded estimators ( β ) of the respective model in percent of the intercept of the model to provide a value which is comparable between the parameters . Nonselected influencing factors are marked in grey . To evaluate the impact of enrichment on the variability , bootstrapped [79] samples of the original data were used . Therefore , 1 , 000 samples were drawn of size nj from each group j ( enrichment × sex × cohort combination ) . As a comparable measure for variability , the CV was used . Linear models using the bootstrapped CV as outcome , and enrichment , sex , and cohort as influencing factors , were fitted . Because the interactions effects did not appear often as relevant in the linear models for the analysis of the mean values , only main effects have been included in the models for CV . To summarize the results of the bootstrap method , empirical 95% confidence intervals for the estimators of all influencing variables of the linear models were computed . The results are summarized in 3 categories and are displayed in Fig 5 , as follows: confidence interval includes 0 ( grey; thus no effect is assumed ) , confidence interval is greater than 0 ( violet ) , or confidence interval is below 0 ( yellow ) . All analyses were performed separately for each measured parameter and mouse strain . The fact that some of the parameters are highly correlated needs to be taken into consideration when interpreting the results . Measures for significance were omitted due to the fact that the main purpose of the study was to get an overview about direction and magnitude of possible enrichment effects on parameters of different research fields . Providing such a broad summary is helpful and can be used by other researchers to focus on single parameters of interest in confirmative studies . The statistic software R ( version 3 . 0 . 2 , R Foundation for Statistical Computing , Vienna , Austria ) was used for all analyses and graphs . Dummy coding was used for all categorical factors in the linear models . Reference categories were as follows: enrichment: none; sex: female; and the cohort: 1 .
|
Adequate housing of laboratory animals is essential to guarantee their well-being . From a scientific perspective , physically and mentally healthy animals also contribute to increased validity and reproducibility of experimental results . The choice of nesting material or shelter type , referred to as environmental enrichment , may influence how laboratory animals perform species-specific behaviors . Consequently , changes in these nesting and shelter materials could influence scientific results by , for example , increasing variability in measured characteristics . Whether studies using different environmental enrichment materials can be compared is currently questioned . Our study shows that simple , species-specific environmental enrichment in the form of nesting material alone or in combination with a shelter did not consistently increase variability of physiological parameters in mice . Differences in parameter average values appeared to be of minor biological relevance when compared to the effects of other environmental factors . These simple environmental enrichment devices may therefore be applied to improve the housing environment of laboratory mice without compromising data validity or comparability .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Material",
"and",
"methods"
] |
[
"animal",
"types",
"body",
"weight",
"medicine",
"and",
"health",
"sciences",
"animal",
"welfare",
"vertebrates",
"mice",
"animals",
"mammals",
"biochemical",
"analysis",
"physiological",
"parameters",
"animal",
"behavior",
"bioassays",
"and",
"physiological",
"analysis",
"animal",
"management",
"eyes",
"zoology",
"research",
"and",
"analysis",
"methods",
"meta-research",
"article",
"behavior",
"laboratory",
"animals",
"head",
"clinical",
"chemistry",
"agriculture",
"rodents",
"eukaryota",
"anatomy",
"physiology",
"biology",
"and",
"life",
"sciences",
"ocular",
"system",
"amniotes",
"organisms"
] |
2018
|
Laboratory mouse housing conditions can be improved using common environmental enrichment without compromising data
|
Telomerase is expressed in early human development and then becomes silenced in most normal tissues . Because ~90% of primary human tumors express telomerase and generally maintain very short telomeres , telomerase is carefully regulated , particularly in large , long-lived mammals . In the current report , we provide substantial evidence for a new regulatory control mechanism of the rate limiting catalytic protein component of telomerase ( hTERT ) that is determined by the length of telomeres . We document that normal , young human cells with long telomeres have a repressed hTERT epigenetic status ( chromatin and DNA methylation ) , but the epigenetic status is altered when telomeres become short . The change in epigenetic status correlates with altered expression of TERT and genes near to TERT , indicating a change in chromatin . Furthermore , we identified a chromosome 5p telomere loop to a region near TERT in human cells with long telomeres that is disengaged with increased cell divisions as telomeres progressively shorten . Finally , we provide support for a role of the TRF2 protein , and possibly TERRA , in the telomere looping maintenance mechanism through interactions with interstitial TTAGGG repeats . This provides new insights into how the changes in genome structure during replicative aging result in an increased susceptibility to age-related diseases and cancer prior to the initiation of a DNA damage signal .
All mammalian telomeres ( the ends of linear chromosomes ) are composed of large tracts of repeated 5ʹ-TTAGGG sequences . Telomeres are well-conserved DNA end structures from yeast to mammals , and it is believed that the primary role of telomeres , in combination with shelterin proteins , is to provide protection of the linear chromosome ends from being recognized as damaged or broken DNA [1] and to facilitate the completion of DNA replication each cell cycle . Telomeres prevent DNA end-joining , DNA recombination , and loss of essential genetic information during DNA replication . Telomeres are maintained by many essential genes , including the six-component shelterin ( TRF1 , TRF2 , POT1 , TIN2 , RAP1 , and TPP1 ) and the CST ( CTC1-STN1-TEN1 ) complexes [1 , 2] . Impairment of these genes is closely associated with age-related clinical pathology and defects in germ cell and stem cell maintenance [3–5] . It is well established that hTERT , the catalytic core reverse transcriptase component , protein levels are rate-limiting for telomerase activity and telomere length homeostasis [6] . Human embryonic stem cells and transit amplifying adult progenitor stem-like cells express hTERT and have active/functional telomerase that can fully or partially maintain telomeres during the substantial number of cell divisions required in fetal development [7] . While telomerase is present from the blastocyst stage in early human development , at approximately 16–18 wk of gestation , telomerase activity is silenced in the vast majority of somatic cells [8] . The molecular mechanisms ( i . e . , transcriptional regulation , alternative splicing changes , epigenetic modifications , or other regulatory processes ) that trigger the silencing of telomerase at specific times during human development remain uncertain . Irrespective , telomerase largely remains silent throughout adult life except for tumor development . In ~90% of human tumors , telomerase is upregulated or reactivated for the maintenance of telomeres during the numerous rounds of cell divisions required for the emergence of malignant and metastatic disease [9] . Thus , tight regulation of telomerase and progressive telomere shortening are thought to be an initial barrier to the early onset of cancer . High resolution mapping of the three-dimensional chromatin interactome addresses many unanswered questions about the cis-regulatory long-range looping interactions important in gene regulation . The human genome is composed of continuous chromosome loops and TADs ( topologically associating domains ) , forming gene territories [10 , 11] . Distal enhancers and/or insulators are believed to be responsible for the regulation of genes along the genome via chromatin folding . Recently , we demonstrated that telomeres also loop to specific loci to regulate gene expression , which we have termed TPE-OLD ( telomere position effect—over long distance ) [12–14] . In the examples characterized so far , genes close to telomeres are silenced in young cells ( with long telomeres ) and become expressed when telomeres are short . Importantly , re-elongation of cells with short telomeres by exogenous expression of the hTERT gene ( active telomerase ) results in expression patterns that mirror the expression of these genes in cells with long telomeres [12–15] . As we have observed genes between the TPE-OLD regulated genes that are not regulated by TPE-OLD , this mechanism is clearly distinct from classic TPE , which regulates genes proportional to the proximity to the telomeric repeats [15] . In the present study , we show that the expression of the hTERT gene itself is also regulated by TPE-OLD . The ability to regulate genes by telomere length without induction of a DNA damage signal from a single or a few critically short telomeres has potential explanatory value for what regulates the maximum length of human telomeres during fetal development and ways to regulate major age-associated transitions as well as to activate or repress genes as part of normal aging without requiring a DNA damage signal .
Long-ranged genomic interactions between telomeres and distal loci may play important roles in the regulation of gene expression , a phenomenon that we previously referred to as TPE-OLD [12 , 13] . Through previous microarray analyses [12] , we identified the human CLPTM1L ( cleft lip and palate-associated transmembrane protein 1-like ) gene that is ~1 . 3 mega bases apart from the chromosome 5p telomere as a putative TPE-OLD candidate gene . CLPTM1L is frequently upregulated in cancer cells [16] and shows preserved colocalization with the TERT locus for a shared synteny in many species ( Fig 1A ) . We analyzed mRNA expression of the genes at this locus , including CLPTM1L and hTERT , in BJ human fibroblast clones with long and short telomeres , to determine if the expression of this locus is regulated by TPE-OLD . CLPTM1L was expressed in normal young passaged cells but showed increased gene expression with progressive telomere shortening ( S1A Fig ) . Historically , it is generally believed that hTERT is not actively transcribed in normal telomerase silent cells; however , expression of hTERT splice variants does occur [17] . The reason for this misconception is that most investigators use primer pairs designed to measure transcripts containing only the RT domain of TERT ( exons 5–10 ) , while exons outside of the RT domain are not measured ( i . e . , exons 1–4 and 11–16 ) . It is now known that hTERT transcripts can be detected in a variety of telomerase-negative cells and tissues , but the mRNA produced is not full-length mRNA capable of producing active telomerase [17] . To test if replicative age or telomere length influenced hTERT expression , we measured hTERT gene expression using a primer pair targeting the 5ʹUTR to exon 1 of hTERT . We observed that hTERT is expressed at higher levels in two human fibroblast strains with short telomeres compared to the same cells with long telomeres ( Fig 1B , S1 Fig ) . As previously described , we did not detect any transcripts that contain the RT domain of hTERT ( Fig 1B ) ; thus , transcripts that could code for active telomerase were not observed . We also analyzed protein expression of CLPTM1L ( S1B Fig ) and observed that the expression of CLPTM1L protein significantly increased during progressive telomere shortening , but the expression was greatly decreased when we re-introduced hTERT in old BJ cells and re-elongated telomeres ( S1B Fig ) . We also examined mRNA expression of genes located between the 5p telomere and the hTERT-CLPTM1L locus ( S1A Fig ) in young and old BJ cells . The expression of the intermediate genes on chromosome 5p showed no significant increase in BJ cells with short telomeres ( S1A Fig ) . We explored if telomere repeat containing RNA , TERRA , was also altered and potentially important in TPE-OLD . Consistent with previous reports [18 , 19] we observed an increase in TERRA expression from three subsets of chromosomes ( 1q-21q , 5p , and 9p-15q-Xq-Yq; Fig 1C ) when telomeres were short compared to long . The TERRA data support our observations that the chromatin environment surrounding chromosome 5p and hTERT change when telomeres are short . Overall , this implies that the hTERT locus may be influenced by the length of telomeres through long-ranged chromatin interactions . Perhaps not surprising , but potentially significant , is that the location of the TERT gene is also evolutionarily conserved ( Fig 1D ) . TERT genes are located at the very end of their chromosomes , near the telomere , in higher primates including humans and most other large long-lived mammals . However , the location of the TERT gene in rodents and many other smaller shorter-lived mammals is non-telomeric . The local genome structure around the TERT locus in rodents is quite different from primates , implying they may have developed different strategies to regulate telomerase expression [20 , 21] . Based on these observations , we decided to test if there is a functional role for TERT being localized at the end of human chromosome 5p . As the distance between the hTERT locus and the telomere is only ~1 . 3 mega bases , we postulated that hTERT might also be regulated in part by a long-ranged telomere looping mechanism in human cells . We designed two specific BAC probes to visualize the hTERT locus and the sub-telomeric 5p region for three-dimensional fluorescence in situ hybridization ( 3D-FISH ) ( Fig 2A ) . We measured the distance between the hTERT locus and the sub-telomeric 5p region , and the pairs of alleles were divided into adjacent to ( A ) or separated ( S ) by the three-dimensional location ( S2A and S2B Fig ) . We first stained the sub-telomeric BAC region , the hTERT locus and telomeres in old BJ cells , with short telomeres ( Fig 2B ) . The telomere staining was detected at the hTERT locus with sub-telomere 5p in the adjacent allele pair . However , we observed at least one hTERT allele that was spatially separated from the sub-telomere 5p probe in old BJ cells without telomere staining . We measured the distance between the hTERT locus and the closest telomere ( Fig 2C ) . The results showed that the hTERT locus colocalized with the telomere when it is adjacent to the sub-telomeric 5p region ( Fig 2B and 2C ) . This implies that the telomere is likely to be adjacent to the hTERT locus for potential long-ranged looping interactions . We next tested if telomere looping close to the hTERT locus changes when telomeres became short . We measured and compared the distance between the hTERT locus and sub-telomeric 5p in young BJ fibroblasts at 20 population doublings ( PDs ) with long telomeres versus old BJ fibroblast at PD90 with short telomeres ( Fig 2D ) . More than 70% of allele pairs were adjacent in BJ cells at PD20 , implying that the telomeric heterochromatin might affect the expression of the hTERT locus in young BJ fibroblasts . BJ cells are telomerase-negative , but non-catalytic alternatively spliced variants are expressed , as shown in Fig 1 and as previously described [17] . This might explain why a small proportion of alleles is separated from the telomere in telomerase-negative young BJ cells with long telomeres , based on the assumption that the looping interactions suppress transcription . In old BJ cells at PD90 , we found that the percentage of adjacent allele pairs was significantly reduced . Almost 60% of alleles were separated in the old cells with short telomeres , indicating that there is at least one hTERT locus spatially separated from the telomere in each cell . Importantly , we confirmed these 5p/TERT looping interactions in a second fibroblast cell strain , IMR90 ( S2C and S2D Fig ) . We measured the number of separated and adjacent alleles in IMR90 cells young ( PD 22 ) and old ( PD 52 ) and show a shift from the majority of alleles being adjacent ( 76% ) in young cells compared to the majority of alleles being separated ( 88% ) in old cells . The looping data and the expression of hTERT are consistent . We suggest that old cells ( with short telomeres ) lose one control mechanism in regulating the hTERT locus ( i . e . , telomere chromatin looping ) that helps repress the expression of hTERT . However , while we observed increased transcription of exon 1 of hTERT , there must be additional mechanisms preventing the inclusion of exons critical to produce active telomerase . There is substantial evidence that alternative splicing of hTERT may also have a major role in suppressing the production of active telomerase in old cells [22–24] . Furthermore , we performed 3D-FISH analysis in transformed SW26 and SW39 cells . SW cells are SV40 antigen expressing clones of IMR90 cells that have spontaneously immortalized using either telomerase ( SW39 ) or an alternative lengthening of telomeres ( ALT; SW26 ) mechanism to maintain telomeres ( S2E Fig ) . In both cell lines , the majority of the alleles were separated ( SW39 = 72%; SW26 = 66% ) , indicating that short telomeres due to replicative aging are likely responsible for the change in chromatin conformation and that a secondary change occurs to cause the production of full-length TERT or engage ALT . It has been suggested that hTERT shows mono-allelic expression in cancer , which is sufficient to preserve constant telomere length [25 , 26] . Our results support this assumption , as we observed that , on average , only one hTERT allele was generally in the open configuration during in vitro aging well before the onset of cancer . As controls for global conformational changes at chromosome 5p , we performed two additional FISH experiments . In the first experiment , we stained intermediate genomic region between the hTERT locus and the 5p telomere ( S3A–S3C Fig ) . In addition , we also stained cells for two loci located 25 . 5 MB and 30 . 6 MB away from hTERT ( S3D–S3F Fig ) . There were no changes in distances between the control loci in young and old cells , demonstrating that the conformation change occurs at the specific genomic region encompassing hTERT during in vitro aging , and this change is not due to classic TPE . To determine if we could artificially shorten telomeres and recapitulate the aging phenotype , we utilized CRISPR/Cas9 ( clustered regularly interspaced short palindromic repeat-associated 9 ) to remove a large portion of the telomere and subtelomere region from chromosome 5p . This experiment allows testing the role of chromosome 5p’s telomere in regulating the looping observed in cells with short and long telomeres . As illustrated in Fig 2D , we also infected young BJ cells with a lentivirus expressing Cas9 protein and single guide-RNA targeting the sub-telomeric region of 5p to specifically disturb telomeres at chromosome 5p for a short period of time [27] . We also added an NHEJ inhibitor , SCR7 , simultaneously during the infection to suppress repair of the double strand breaks induced by the Cas9 protein [28] . The targeted cells showed an unstable end structure of chromosome 5p ( S5 Fig ) , and the specific disturbance of the 5p telomere significantly diminished telomere looping at the end of the chromosome 5p . We further examined if the proposed mechanism was present in BJ cell clones in which both young and old cells were passaged the same amount of time in culture . This approach was necessary to eliminate the possibility that young and old cells that were in culture for vastly differing times could introduce artifacts . To accomplish this , we expressed a floxable hTERT in BJ clones , followed by excision at different time points in order to make isogenic cells with different length of telomeres but passaged similar times in cell culture [12 , 29] . Telomere length of the early-excision clone was 9 kb , and this was extended up to 13 kb in the late-excision clone . The telomere length ( terminal restriction fragment [TRF] ) results are presented in Figure 1B . Population doublings were evenly matched between clones ( to avoid confounding effects of passage of time in culture ) , and we also analyzed telomere looping . Similar to our observations in normally passaged BJ cells , the isogenic clones also showed decreased levels of telomere looping with telomere shortening ( Fig 2E ) . Importantly , there were only background levels of DNA damage signaling during telomere shortening ( Fig 2F ) indicating that the change in genome structure occurred before initiation of DNA damage responses from critically short telomeres . To ensure that our staining protocol was robust , we induced DNA damage ( double strand breaks ) by treating long and short telomere BJ cells with zeocin and assaying for DNA damage ( S2F Fig ) . These data can be interpreted to indicate that our staining protocol is robust and that we are analyzing cells before telomere-DNA damage induced foci are present or significant DNA damage occurs in the cells . We next performed droplet digital 3C ( chromatin conformation capture ) to detect the genomic interactions between the 5p telomere and the hTERT locus in young and old BJ cells ( Fig 2G , left side ) . The results showed that the hTERT locus has specific genomic interactions with the 5p telomere , and the interaction was reduced during in vitro aging and telomere shortening . A proximity control primer which is 10kb away from the fixed primer at the hTERT locus was selected for normalization of 3C results ( Fig 2G , right side ) . Taken together , telomere looping exists between the hTERT locus and the sub-telomeric 5p in normal human cells , and this looping is greatly reduced by gradual telomere shortening . It has been shown that cis-elements upstream of the hTERT locus may play important roles in the tight regulation of human telomerase [30] . Thus , we decided to test if telomere looping could affect the epigenetic status of the hTERT proximal promoter region . We first analyzed DNA methylation of the region from -720bp to +90bp of the hTERT promoter in isogenic BJ cells with different lengths of telomeres but similar times in cell culture ( Fig 3A ) . The relationship between DNA methylation and transcription in the hTERT promoter remains controversial in normal and cancer cells [31 , 32] , but the transcription start site of hTERT retains little or no methylation in telomerase-active cancer cells for active transcription [33] . We found that the level of DNA methylation is significantly higher in BJ cells with long telomeres at several regions associated with hTERT and the hTERT region in comparison to cells with shorter telomeres . The largest differences were observed at -580bp , -250bp , -30bp , and +20bp of the hTERT promoter , including the E-box motif ( a putative Myc binding sequence ) . It has also been reported that the proximal region of the hTERT promoter , including exon 1 and 2 , regulates the activity of the hTERT promoter and that the methylation of this region is responsible for binding of several proteins [34 , 35] . Therefore , our results can be interpreted to indicate that telomere length-associated changes in methylation levels of the hTERT proximal promoter might affect transcriptional regulation of this locus . We next analyzed active and inactive histone marks on the hTERT proximal promoter using chromatin immunoprecipitation combined with droplet digital polymerase chain reaction ( ChIP-ddPCR; [12] ) ( Fig 3B ) . We measured two histone marks associated with active chromatin H3K4 trimethylation ( H3K4me3 ) and H3K9 acetylation ( H3K4ac ) and two histone marks associated with repressed chromatin H3K27 trimethylation ( H3K27me3 ) and H3K9 trimethylation ( H3K9me3 ) , which have key roles in regulating gene expression [36] . We observed an increase in both H3K4me3 and H3K9ac across the TERT promoter in aged cells with short telomeres ( Fig 3B ) . We also observed an increase in the repressive histone mark H3K27me3 , but did not observe any significant differences in young or old BJ cells for the repressive histone mark H3K9me3 . Collectively , this shows that the chromatin status of the hTERT promoter in old BJ cells with short telomeres is different and may be more transcriptionally permissive compared to young BJ cells with long telomeres . These data correlate well with the increased hTERT transcription we observed in cells with short telomeres . Furthermore , we analyzed chromatin at the promoters of three genes surrounding TERT that could also be affected by the altered chromatin environment with aging . We analyzed the proximal promoter regions of CLPTM1L , SCL6A18 , and SCL6A19 for the same histone marks described above in the same cells and preparations used for TERT ChIP . At the CLPTM1L promoter we observed significant increases in histone marks indicating active transcription ( Fig 3B ) . These data correlate well with an increase in CLPTM1L transcripts and protein levels ( S1 Fig ) . We also observed significant changes in the chromatin surrounding the solute/amino acid transporter genes ( SCL6A18 and SCL6A19 ) , even though these genes are not expressed above basal/background levels in old/short telomere BJ cells . Specifically , we observed that both the repressive histone marks were increased in old cells ( short telomeres ) compared to young cells ( long telomere ) . However , there was an increase in the activation marks as well . This indicates an intricate balance between chromatin modifications , methylation status , telomere length , and the expression of tissue-specific transcription and splicing factors that dictates the activation or repression of genes with replicative aging ( telomere shortening—TPE-OLD ) . While we demonstrated that telomere shortening induced conformation changes between the hTERT locus and the sub-telomeric 5p resulting in up regulation of exon 1 , presumably containing spliced hTERT transcripts in normal BJ cells ( see Fig 1B ) , it did not result in full-length telomerase activity competent transcripts . Thus , we suggest that telomere shortening may render the hTERT locus more permissive and under oncogenic stress may lead to the production of full-length hTERT mRNA transcripts that could in turn produce telomerase activity . To test this , we simulated a step in spontaneous cancer transformation by knocking down p21 ( CDKN1A ) and analyzing mRNA expression level of hTERT ( Fig 3C ) . The knockdown of p21 was previously shown to de-repress hTERT expression [37] . Thus , we tested if the knockdown of p21 would increase the expression of hTERT mRNAs and result in the inclusion of exons 7/8 in the short-telomere old BJ cells but not in the young BJ cells with long telomeres . We measured the expression level of hTERT transcripts in young and old BJ cells with and without p21 stable knockdown; mRNA containing exons 7/8 ( exons coding for critical residues in the reverse transcriptase domain of TERT ) and exon 15/16 ( most splice variants of hTERT contain exons 15 and 16 ) , responsible for putative active hTERT and total hTERT variants respectively . Both the active and the total hTERT transcript variants significantly increased with the knockdown of p21 in old BJ but not in young BJ cells; however , we did not detect telomerase activity ( S6 Fig ) . While we observed an increased portion of transcripts that contain exons 7/8 of the TERT RT domain , other critical regions such as exon 2 may be spliced out [38] . Further work into the regulation of hTERT splicing is necessary to more fully understand the complex regulatory network surrounding hTERT and why the majority of transcripts are inactive splice variants as opposed to full length . While this result does not prove a causal role during cancer development , this series of experiments does demonstrate that telomere shortening in cells that bypass replicative senescence leads to the hTERT locus entering into a more permissive state ( e . g . , increased hTERT mRNA expression ) in the presence of oncogenic stresses , consistent with the disengagement of telomere looping . Characterization of cis- or trans-acting factors responsible for telomere looping will be important to understand this novel mechanism for telomerase regulation . A recent report showed that TRF2 ( telomeric repeat-binding factor 2 ) protein is essential for the functional organization of chromosome ends , including human fibroblasts [39 , 40] . There is also mounting evidence for off-telomere functions of the shelterin components [41] . While a recent whole genome sequencing study found 2 , 920 interstitial TTAGGG repeats throughout the human genome [39] , we also found frequent internal ( interstitial ) telomeric sequences ( ITS ) near the TERT locus in higher primates but not in rodent cells ( Fig 4A ) . Thus , we first checked for a putative role of TRF2 in telomere looping in BJ cells as a candidate approach . We knocked down TRF2 by siRNA and performed 3C to directly assess the genomic interactions between the telomere and the hTERT locus ( Fig 4B ) . The knockdown of TRF2 significantly reduced the genomic interactions between the telomere and the hTERT locus in young PD30 BJ cells , implying TRF2 may have a role in telomere looping interaction on hTERT locus . As shown in Fig 4A , a region 100 kb downstream of the hTERT ( Chr5: 1 , 154 , 047–1 , 154 , 347 ) contains a series of internal telomeric sequences that may recruit TRF2 shelterin protein ( hereafter termed hTERT-ITS ) . Thus , we reasoned that this region would be a putative binding site for TRF2 and may be responsible for the telomere looping interaction between the telomere and the hTERT locus in cells with long but not short telomeres . ChIP-qPCR analysis showed that the TRF2 protein associates with the hTERT-ITS region in young and old BJ cells as proposed ( Fig 4C ) . We next performed 3C to further clarify that hTERT-ITS interact with the hTERT promoter by genome folding to affect transcriptional permissiveness as shown in Figs 1 and 3 . Within 200kb , we found more than 20 HindIII restriction enzyme sites were in the hTERT/CLPTM1L locus ( Fig 4D ) . Droplet digital PCR ( ddPCR ) -mediated amplification showed specific interactions between the 5ʹ end of hTERT and the hTERT-ITS ( Fig 4E ) . Moreover , the interaction was weakened in old BJ cells , implying there might be a transition from a more repressive state to a more active state of this TAD location during in vitro aging , consistent with the increased hTERT mRNA , altered methylation , and chromatin . This result also shows that there is an additional genome folding between the hTERT locus and the hTERT-ITS at an intermediate region between the SLC6A18 and SLC6A19 loci . The hTERT promoter is not close to the hTERT-ITS on a linear genome map , but the unique genome folding at this region potentially positions the hTERT promoter close to the ITS , followed by putative TRF2-mediated telomere recruitment to the hTERT promoter only in cells with long telomeres . In Fig 4F , we demonstrate that TRF2 protein is also enriched in the hTERT promoter region using ChIP-qPCR approaches . While TRF2 protein was enriched at proximal regions on the hTERT promoter , the interaction was significantly decreased in old BJ cells at the genomic regions containing -350bp to -50bp of the hTERT promoter . This shows TRF2 protein can occupy the hTERT promoter region , but the interaction is weakened during in vitro aging and telomere shortening . Together , we interpret these experiments to indicate that TRF2 , and perhaps upregulated TERRA , may have at least a partial mechanistic role in telomere looping at the hTERT locus through interaction with the conserved interstitial telomeric repeats . Because we have shown the interaction between the 5p telomere and the hTERT locus , we modeled one possibility for the detailed local genome structure of this locus ( Fig 4G ) . In this model , the hTERT promoter is close to the hTERT-ITS by genome folding in young cells with long telomeres . In addition , this model shows that TRF2 protein is recruited to hTERT locus and hTERT-ITS , which makes this interaction potentially dependent on telomere length . In summary , the hTERT promoter has specific interactions with the hTERT-ITS through gene looping , which may also recruit telomere length-dependent looping ( TPE-OLD ) mechanisms through TRF2 protein . We next performed 3D-FISH to visualize the genomic structure changes between the hTERT locus and the sub-telomeric 5p ( Fig 4H ) . Control PD17 BJ cells showed that 89% of the hTERT and sub-telomeric 5p allele pairs were adjacent , but knockdown of TRF2 reduced this down to 34% . We also knocked down CTCF ( CCCTC-binding factor ) and LDB1 ( LIM domain-binding protein 1 ) , which are proposed to be essential proteins in global gene looping maintenance [42 , 43] . CTCF and LDB1 knockdown also significantly reduced the adjacent allele pairs , implying that the general gene looping mechanisms may also be involved in telomere looping . Western blotting was also performed to show knockdown efficiency ( Fig 4I ) . Taken together , TRF2 , part of the shelterin complex , may be mechanistically involved in the establishment of telomere looping near the hTERT locus through ITS together with general chromosome looping mechanisms . In almost all primary human cancers , telomere length is very short compared to adjacent normal tissues [44] . It is likely that short telomeres , in combination with oncogenic alterations , result in the hTERT gene becoming more permissive for protein expression and enzyme activity . Thus , we next investigated how telomere length affects hTERT expression in telomerase-active cancer cells . We first infected hTERT and hTR ( hTERC ) into the SW39 cell line ( SV40 immortalized human telomerase expressing fibroblasts ) and analyzed mRNA expression of the endogenous hTERT by examining the 3ʹ untranslated region . We observed that the extended telomere length reduced endogenous expression of hTERT mRNA in qPCR analysis ( Fig 5A ) implying TPE-OLD remains engaged at least in this tumor cell line . We further established isogenic HeLa cell clones with different telomere lengths by excising a floxable hTERT cDNA at different time points . We examined expression of splice variants of hTERT mRNA containing total , full-length ( indicative of telomerase activity ) , and minus beta alternative spliced forms through ddPCR analysis ( Fig 5B ) . All three splice variants showed significantly decreased expression in the long-telomere HeLa clone . We also performed 3D-FISH to analyze changes in genomic structure between the hTERT locus and the sub-telomeric 5p after the extension of telomeres in HeLa cells ( Fig 5C ) . The long-telomere HeLa clone showed a higher percentage of adjacent allele pairs compared with the short-telomere HeLa clone . This indicates that the expression of hTERT may also be influenced by the length of telomeres through TPE-OLD in telomerase-positive cancer cells .
The local genome structure around the hTERT locus may be important for the tight regulation of human telomerase . For example , introduction of proximal cis-elements of the hTERT promoter sufficiently inhibits the activity of the TERT promoter [45] . In addition , chemicals perturbing chromatin structure , including trichostatin A and 5-aza-2ʹ-deoxycytidine , induce changes in hTERT expression [46] . Moreover , chromosomal translocation and gene duplication of the hTERT locus can occur as part of the immortalization process in primary cultured cells [47 , 48] . Here , we reasoned that the hTERT locus might recruit telomeric heterochromatin to regulate its own gene expression , especially in large , long-lived mammals where tumor suppression mechanisms are perhaps more important . We showed that telomere looping exists in long-telomere young fibroblasts and that telomere looping was reduced by in vitro aging . This is one possible explanation for why higher primates preserved the location of the TERT gene at the end of one of their chromosomes . We speculate that , in addition to other conserved tumor suppressor mechanisms , higher primates also developed a mechanism to suppress the undesired expression of TERT . For example , it is well established that during human fetal development , full-length telomerase transcription is repressed and correlates with increases in nonfunctional alternative splicing changes in hTERT [8] . Thus , during early human development , when telomerase is active , telomeres elongate . Our current results are consistent with the idea that longer telomeres can fold back on the TERT locus and repress or significantly reduce transcription . Our results also show that replicative senescence , while initially a tumor suppressor mechanism , may paradoxically impinge on the predisposition to cancer through telomerase transcriptional de-repression . While still preliminary , the hTERT locus is arranged in a local chromatin domain that is regulated by telomere length and the interstitial telomere sequences in the vicinity of the hTERT locus . We showed that expression of the CLPTM1L gene ( adjacent to hTERT ) is also regulated by the length of telomeres and predicts transcriptional permissiveness of this locus . However , because hTERT re-activation is an extremely rare event , there may be additional levels of regulation . We propose that , upon telomere shortening , the hTERT region becomes permissive ( as indicated by increased transcription of exon 1 containing RNAs ) , but this first step is not sufficient to support full-length hTERT transcripts at an adequate level to produce telomerase enzyme activity . We further propose that there is another biological role for telomere looping at this locus during development to repress telomerase when telomere length homoeostasis is reached ( i . e . , suggesting that having too-long telomeres may be detrimental ) . Here , we demonstrated a novel epigenetic mechanism regulating hTERT expression during in vitro aging ( Fig 5D ) . Cells with long telomeres at the end of chromosome 5p in young passaged cells form a chromatin loop in the region of the hTERT locus . Importantly , we demonstrated that the chromatin loop is disengaged in cells with short telomeres , leading to partial increased expression of hTERT mRNA during in vitro aging and in response to p21 knockdown; however , telomerase activity was not detected , and , alternatively , spliced variants were likely produced [17 , 22–24 , 38] . Finally , we demonstrated that , in old cells with short telomeres , re-introduction of hTERT and elongation of telomeres results in a re-engagement of TPE-OLD . We found that DNA methylation and histone modifications in the hTERT promoter region showed significant changes as cells developed shorter telomeres , and that TRF2 and , perhaps , TERRA , may have important roles in these age-dependent genomic changes . These observations offer a model and a partial explanation for how age-dependent changes in the genome structure affect the regulation of hTERT without initiating a DNA damage response from a critically shortened telomere .
BJ , SW39 , HeLa , HEK293FT , IMR90 , and Phoenix A cells were maintained in a 4:1 ratio of Dulbecco’s modified Eagle’s medium to Medium 199 containing 10% of fetal bovine serum ( Hyclone , Logan , UT , USA ) under 5% CO2 in a humidified incubator . Retrovirus containing human TERT cDNA was infected into BJ cells and HeLa cells , followed by adenoviral infection for transient expression of Cre recombinase at different time points to produce cells with different lengths of telomeres that had been passaged in vitro for similar times [12 , 29] . Retrovirus was prepared by transfecting viral vectors into Phoenix A cells for 48 h . Medium containing virus was filtered through a 0 . 45 μm pore and provided to cells in the presence of 2 μg/ml polybrene . Lentivirus was prepared by transfecting viral vectors into HEK293FT cells with two packaging vectors ( pMD2 and psPAX2 ) for 48 h . Medium containing virus was filtered through a 0 . 45 μm pore and cells exposed to lentivirus in the presence of 2 μg/ml polybrene . Selection for hygromycin was performed using 100 μg/ml and for puromycin using 1 μg/ml . CRISPR-Cas9 introduction for 5p genomic editing was performed by infecting cells with lentivirus carrying sgRNA target sequence of 5ʹ-GCCTCACTCCTTACGGAGTG-3ʹ . 3D-FISH was performed as described previously [12] . 104 BJ cells were seeded into 4-chambered slides . Cells on slides were fixed with 4% paraformaldehyde , followed by permeabilization with 0 . 1% Triton X-100 in PBS . Repeated liquid nitrogen freezing-thawing cycles were performed for further permeabilization with preservation of intact nuclear structure under 20% glycerol in PBS . After 5 d of incubation of with 50% formamide in 2X SSC , cells were stained with indicated probes at 37°C for overnight . Slides were washed with 0 . 1% SDS in 0 . 5X SSC at 70°C for 5 min , followed by 2 rounds of PBST ( Phosphate-buffered saline with Triton X-100 ) washing for 10 min . Images were acquired using a LSM780 confocal microscope ( Carl Zeiss , Jena , Germany ) , and analyzed by Imaris deconvolution software ( Bitplane , Zurich , Switzerland ) . The proximity of allele pairs was determined visually and quantitated . At least 30 nuclei were counted for the statistical analyses . We used the following criteria for the analyses: adjacent ~0 . 5 μm space or less between probes , separated ~1 . 0 μm between probes or more . The length was determined by calculating the 3D distance between each center of deconvolved fluorescent spots . Probes were prepared using nick translation kits ( Abbott Laboratories , Abbott Park , IL , USA ) from each BAC following manufacturer’s instructions . BAC plasmids were purchased from CHORI ( Children’s Hospital Oakland Research Institute , Oakland , CA , USA ) ; RP11-990A6 for hTERT locus staining and RP11-44H14 for sub-telomeric region 5p staining . Quality of probes was assessed by metaphase spread analyses and PCR . DdPCR and ddTRAP were performed as previously described [12 , 49] . Messenger RNA was prepared from RNeasy plus mini kit ( Qiagen , Valencia , CA , USA ) following the manufacturer’s instructions . 100 ng of RNA was reverse-transcribed from cDNA synthesis kit ( Bio-Rad , Hercules , CA , USA ) by following the manufacturer’s instructions . Ten percent of synthesized cDNA was used for the ddPCR reaction . For ddTRAP , harvested cells were lysed in NP40 lysis buffer ( 1mM Tris-Cl pH8 . 0 , 1mM MgCl2 , 1mM EDTA , 1% NP40 , 0 . 25mM sodium deoxycholate , 10% glycerol , 0 . 15M NaCl , 0 . 05% 2-ME ) for ddTRAP . Lysate was used for TS extension , and the extended products were analyzed with ddTRAP . Endogenous levels of 3ʹUTR were assessed with EvaGreen dye ( Bio-Rad , Hercules , CA , USA ) . Probes were purchased from Roche ( Basel , Switzerland ) , and the primer sequences are described below: 100 ng of gDNA was modified using the EpiTect Bisulfite kit by following the manufacturer’s instructions ( Qiagen , Valencia , CA , USA ) . Modified DNA was PCR-amplified and cloned into the T vector system ( Promega , Madison , WI , USA ) . 7~10 bacterial clones were sequenced for methylation analysis . Primers for the hTERT promoter region amplification were designed as previously described [33] . Chromatin conformation capture ( 3C ) was performed as previously described [12] . Five million cells were washed with PBS and fixed with 25 ml of medium containing 1% formaldehyde for 10 min at room temperatures . To quench the crosslinking reaction , 1 . 5 ml of 2 . 5 M glycine was added and incubated for 10 min at room temperature , followed by an additional 15 min of incubation at 4°C . Cells were washed with PBS and harvested into 1 ml of cold-PBS with protease inhibitor . Cells were next lysed by homogenization , and the nuclear pellet was collected by centrifugation . The nuclear pellet was washed and resuspended in 500 μl of ice-cold NEBuffer 2 ( NEB , Ipswich , MA , USA ) . 15 μl of 10% SDS was added and incubated at 37°C for 1 h , followed by addition of 46 . 35 μl of 20% Triton X-100 for 1 h on a shaking incubator . HindIII ( 400U ) was added and incubated overnight . Enzyme reaction was stopped by adding 88 μl of 10% SDS at 65°C for 20 min . Samples were next transferred to DNA ligation mix containing 50 mM Tris-Cl , pH 7 . 5 , 10 mM MgCl2 , 1 mM ATP , 10 mM DTT , and 50 μg/ml BSA . 372 μl of 20% Triton X-100 was added and incubated at 37°C for 1 h . 2 , 000 U of ligase ( NEB , Ipswich , MA , USA ) was added and incubated for 5 h at 16°C . 40 μl of 20 mg/ml Proteinase K was added to the ligation mix at 65°C overnight . DNA extraction was performed by phenol-chloroform extraction and ethanol precipitation . Quality of the libraries were determined by checking for a single DNA band under agarose gel electrophoresis . Taq-man probe and 5ʹ primers were selected to amplify constant regions at the 5p telomere regardless of genome conformation . 3ʹ primers were selected to amplify the genomic interaction between 5p telomere and subtelomeric genes up to 1 . 3 mega base pairs from 5p containing hTERT . Primer binding regions are 100 base pairs apart from a HindIII recognizing motif . Primer and probe sequences are described below; Chromatin immunoprecipitation was performed as previously described [12] . Antibodies against total histone H3 and a 1:1 mixture of rabbit and mouse IgG isotypes were used as pulldown positive and negative controls of ChIP analyses , respectively . Relative occupancy was determined by first normalizing the target results with amplification signals from total H3 and then dividing by 1% input chromatin extracts . Antibodies against H3K4me3 , H3K27me3 , H3K9me3 , H3K9ac , and LDB1 were purchased from Abcam ( Cambridge , MA , USA ) . Antibody against TRF2 was purchased from Novus biologicals ( Littleton , CO , USA ) . Antibody against CTCF and histone H3 was purchased from Cell signaling ( Cell signaling technology , Danvers , MA , USA ) . Primers for hTERT promoter amplification were described in a previous study [33] . Primers for detection of CLPTML1 , SLC6A18 , CLC6A19 , and the hTERT-ITS are described below; The TIF assay is based on the co-localization detection of DNA damage by an antibody against gamma-H2AX and telomeres using FITC-conjugated telomere sequence ( TTAGGG ) 3-specific peptide nucleic acid ( PNA ) probe . Briefly , BJ cells with long and short telomeres ( 100 , 000 cells ) were seeded to four-well chamber slides , and , after the cells attached to the surface ( next day ) , slides were rinsed twice with 1xPBS and fixed in 4% formaldehyde ( ThermoScientific , IL ) in PBS for 10 min . Then , cells were washed twice with PBS and permeabilized in 0 . 5% Triton X-100 in PBS for 10 min . Following permeabilization , cells were washed three times with PBS . Cells were blocked with 10% goat serum in 0 . 1% PBST ( TritonX-100 ) for 1 h . Gamma-H2AX ( mouse ) ( Millipore , Billerica , MA ) was diluted 1:1 , 000 in blocking solution and incubated on cells for 2 h . Following three washes with PBST ( 1x PBS in 0 . 1% Triton ) and three washes with PBS , cells were incubated with Alexaflour 568 conjugated goat anti mouse ( 1:500 ) ( Invitrogen , Grand Island , NY ) for 40 min , then washed five times with 0 . 1% PBST . Cells were fixed in 4% formaldehyde in PBS for 20 min at room temperature . The slides were sequentially dehydrated with 70% , 90% , and 100% ethanol . Following dehydration , denaturation was conducted with hybridization buffer containing FITC-conjugated telomere sequence ( TTAGGG ) 3-specific peptide nucleic acid ( PNA ) probe ( PNA Bio , Thousand Oaks , CA ) , 70% formamide , 30% 2xSSC , 10% ( w/v ) MgCl2 . 6*H20 ( Fisher Sci ) , 0 . 25% ( w/v ) blocking reagent for nucleic acid hybridization and detection ( Roche ) for 7 min at 80°C on heat block , followed by overnight incubation at room temperature . Slides were washed sequentially with 70% formamide ( Ambion , Life Technologies , Grand Island , NY ) / 0 . 6 x SSC ( Invitrogen ) ( 2 x 1 h ) , 2 x SSC ( 1 x 15 min ) , PBS ( 1 x 5 min ) , and sequentially dehydrated with 70% , 90% , and 100% ethanol , then mounted with Vectashield mounting medium with DAPI ( Vector Laboratories , Burlingame , CA ) . Images were captured with Deltavision wide-field microscope using the 60X objective . TIFs were quantified using Image J and representative pictures were prepared in Imaris software after deconvolution using Autoquant X3 . The average length of telomeres ( terminal restriction fragment lengths ) was measured as described in [50] with the following modifications . DNA was transferred to Hybond-N+ membranes ( GE Healthcare , Piscataway , NJ ) using vacuum transfer . The membrane was air-dried and DNA was fixed by UV-crosslinking . Membranes were then probed for telomeres using a DIG-labeled telomere probe [51] , detected with an HRP-linked anti-DIG antibody ( Roche ) , and exposed with CDP-star ( Roche ) .
|
Telomerase is very tightly regulated in large , long-lived species such as humans . Telomerase is expressed during early human fetal development , turned off in most adult tissues , and then becomes reactivated in most human cancers . However , the exact mechanism ( s ) regulating these switches in expression are not fully known . We recently described a phenomenon in which genes near chromosome ends ( telomeres ) are regulated by telomere length-dependent loops ( telomere position effect—over long distances; TPE-OLD ) . Interestingly , the TERT gene is only a megabase from the human chromosome 5p end . We observed that when telomeres are long , TERT gene expression is repressed and the 5p sub-telomeric region and the TERT locus are spatially co-localized . When telomeres are short , at least one of the TERT alleles is spatially separated from the telomere , developing more active histone marks and changes in DNA methylation in the TERT promoter region . These findings have implications for how cells turn off telomerase when telomeres are long during human fetal development and how cancer cells reactivate telomerase in cells that have short telomeres . These studies add to the growing support for the role of telomeres in regulating gene expression via TPE-OLD . Furthermore , telomere length may be one of the mechanisms of how cells time changes in physiology without initiating a DNA damage response .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"telomere",
"length",
"telomeres",
"cell",
"biology",
"chromosome",
"biology",
"chromosome",
"structure",
"and",
"function",
"molecular",
"biology",
"gene",
"expression",
"genetics",
"gene",
"regulation",
"biology",
"and",
"life",
"sciences",
"epigenetics",
"molecular",
"biology",
"techniques",
"cloning",
"chromatin",
"genetic",
"loci",
"chromosomes",
"research",
"and",
"analysis",
"methods"
] |
2016
|
Regulation of the Human Telomerase Gene TERT by Telomere Position Effect—Over Long Distances (TPE-OLD): Implications for Aging and Cancer
|
Aedes aegypti is one of the most important mosquito vectors of human disease . The development of spatial models for Ae . aegypti provides a promising start toward model-guided vector control and risk assessment , but this will only be possible if models make reliable predictions . The reliability of model predictions is affected by specific sources of uncertainty in the model . This study quantifies uncertainties in the predicted mosquito population dynamics at the community level ( a cluster of 612 houses ) and the individual-house level based on Skeeter Buster , a spatial model of Ae . aegypti , for the city of Iquitos , Peru . The study considers two types of uncertainty: 1 ) uncertainty in the estimates of 67 parameters that describe mosquito biology and life history , and 2 ) uncertainty due to environmental and demographic stochasticity . Our results show that for pupal density and for female adult density at the community level , respectively , the 95% prediction confidence interval ranges from 1000 to 3000 and from 700 to 5 , 000 individuals . The two parameters contributing most to the uncertainties in predicted population densities at both individual-house and community levels are the female adult survival rate and a coefficient determining weight loss due to energy used in metabolism at the larval stage ( i . e . metabolic weight loss ) . Compared to parametric uncertainty , stochastic uncertainty is relatively low for population density predictions at the community level ( less than 5% of the overall uncertainty ) but is substantially higher for predictions at the individual-house level ( larger than 40% of the overall uncertainty ) . Uncertainty in mosquito spatial dispersal has little effect on population density predictions at the community level but is important for the prediction of spatial clustering at the individual-house level . This is the first systematic uncertainty analysis of a detailed Ae . aegypti population dynamics model and provides an approach for identifying those parameters for which more accurate estimates would improve model predictions .
Aedes aegypti is one of the most important mosquito vectors of human viral diseases . It causes approximately 50 million cases of dengue fever per year , 500 , 000 cases of dengue hemorrhagic fever ( DHF ) or dengue shock syndrome ( DSS ) , and approximately 12 , 500 fatalities annually [1] , [2] . Currently , there is no effective vaccine available and the only means for limiting dengue outbreaks is vector control . For a better understanding of mosquito population dynamics and more efficient vector and disease control , researchers have built mathematical models that incorporate fundamental biological and ecological mechanisms affecting mosquito population dynamics . A pioneering model was developed by Gilpin & McClelland [3] to predict how larval development is affected by food density , larval weight and temperature . Although Gilpin & McClelland's model was based on larvae in an artificial laboratory environment and did not simulate the whole life cycle of Ae . aegypti , their model was significant in providing the first biologically realistic approach for predicting larval population dynamics . Based on Gilpin & McClelland's model , Focks et al . [4] developed a life history model ( CIMSiM ) to predict in-field population dynamics for Ae . aegypti . This model incorporated detailed biological processes ( survival , physiological developments , food-regulated body weight growth , and fecundities ) and environmental factors ( temperature and humidity ) for four different life stages: eggs , larvae , pupae and adults . It has been applied to a number of villages and city environments , including locations in Thailand and the US [5] . By coupling CIMSiM with an epidemiological simulation model ( DENSiM ) , it is possible to make predictions about disease dynamics [6] . The model has also been scaled up to global levels to predict the potential effects of climatic change on mosquito population distributions and potential disease risks [7] . The CIMSiM model does not account for spatial heterogeneities in the mosquito population and its environment , and the dispersal of mosquitoes across this environment [8] . Recently , in view of the potential importance of spatial dispersal for mosquito population dynamics and vector control [9] , [10] , new spatial models have been developed [11] , [12] . Based on their spatial model , Otero et al . [11] predicted that dispersal could be a significant factor impacting the seasonal population dynamics of Ae . aegypti in Buenos Aires , Argentina where the environment is marginal for this mosquito species . Magori et al . [12] , using the stochastic and spatially explicit Skeeter Buster model , predicted that dispersal among houses would decrease spatial variations in mosquito densities caused by heterogeneity in the larval habitats among houses in tropical areas . Results from the Skeeter Buster model [12] also indicated that dispersal could impact the efficiency of some transgenic approaches for replacing native mosquito genotypes with engineered genotypes that do not transmit dengue [13] , [14] , [15] . Spatial models of Ae . aegypti could provide an important advance toward model-guided vector control and risk assessment . Attempts to compare the outcomes of different types of control strategies ( e . g . , physical removal of breeding sites , chemical control using adulticidal spraying of houses or larvicidal treatment of water-filled containers , and biological control of releasing transgenic mosquitoes for replacing native mosquito genotypes ) , used either in isolation or in combination , may require the use of models that include detailed descriptions of underlying biological processes . As a result , complex models are being increasingly used in disease and population modeling contexts . However , such models are analytically less tractable than their simple counterparts and can have many different sources of uncertainties , which may affect the reliability of predictions . There are four types of uncertainty in a model [16] , [17]: 1 ) uncertainty in the model structure; 2 ) uncertainty in the parameter estimates; 3 ) uncertainties in data inputs for the model; and 4 ) stochastic uncertainty ( i . e . , the variability that results from environmental and demographic stochasticity ) . The first three types of uncertainty are generally reducible to some extent ( i . e . uncertainty can be reduced given higher quality data and a better understanding of the system being simulated ) , while stochastic uncertainty is generally irreducible [18] . It is possible that the combination of these uncertainties will result in model predictions that are less reliable than acceptable to researchers and practitioners working to suppress dengue . This makes uncertainty analysis indispensible for complex models . To evaluate the reliability of predictions made by Skeeter Buster model , we quantify uncertainties in the predicted Ae . aegypti population dynamics at the community level ( a cluster of 612 houses ) and the individual-house level . We focus on uncertainties in model predictions resulting from parametric uncertainty and stochasticity . In addition to quantifying overall parametric uncertainty , we also quantify proportions of uncertainty in model predictions contributed by specific model parameters using an advanced uncertainty analysis technique , the improved Fourier Amplitude Sensitivity Test ( FAST ) [19] , [20] , [21] . This should enable a better understanding of the factors contributing to uncertainty , and could enable targeting of parameters with high uncertainty contributions for more accurate empirical quantification . Although uncertainties in model structures and data inputs could also be important , it would be difficult to estimate them with currently available information .
In this section , we only provide an overview of Skeeter Buster . For a more detailed description of the model see Magori et al . [12] . Skeeter Buster simulates the biological development of four life stages of Ae . aegypti: eggs , larvae , pupae and adults . The model assumes that larval growth and survival are regulated by the amount of food available in water-filled containers in and around houses . The time from egg hatch to pupation and the period taken for each gonotrophic cycle ( the egg production/laying cycles of female adults ) are mainly determined by temperature-dependent development rates [22] . The pupation time also depends on larval weight , which is calculated using a weight gain model based on the work of Gilpin and McClelland [3] . Fecundity is assumed to be related to female adult weight [4] , [23] ( see Table S1 ) . The survivorship of each life stage is dependent on temperature ( see Figure S1 ) , and survivorship of adults and eggs is also dependent on humidity ( see Figure S2 ) . The daily survival probability within the optimum range of environmental factors is termed the nominal survival rate . Egg hatching is dependent on water level change in the container . Skeeter Buster tracks the water temperature and water level for all containers based on container characteristics ( e . g . , size of opening ) , precipitation and air temperature . In this study , we use environmental and spatial habitat data from the city of Iquitos , Peru ( see Figure S3 for air temperature inputs ) as a follow-up to Legros et al . [24] that uses data from this city to examine predictions of the basic model . Detailed descriptions of the study area have been provided in earlier studies [25] , [26] . A mosquito survey using four-month long sampling circuits within the city , linked to a geographic information system , has been conducted since 1998 . The survey recorded the proportion of water-filled containers holding pupae , the number of pupae , and the number of captured adults [25] . We simulate a district in the city with 612 houses as in Legros et al . [24] . Food inputs for different types of water containers are parameterized so that pupal densities simulated by Skeeter Buster ( using default parameter values in Table S1 , S2 , S3 , S4 , S5 , the assumed most likely values based on data and experiences ) fit pupal data in the mosquito survey conducted in Iquitos [24] ( see Figure S4 for the food input map ) . We initiate the model with 20 eggs for every container and run the model for 3 months to allow mosquito population dynamics to stabilize . The container water temperatures are simulated using a polynomial function obtained from a regression of water temperature on air temperature and sun exposure for 12 containers monitored for 76 days in Gainesville , FL , USA [4] . We rely on these data because similar information for Iquitos is lacking . The first step in our analysis involved assessment of both literature and expert knowledge to gauge the level of uncertainty related to values of each parameter . For the use of expert knowledge , we conducted workshops in 2008 and 2009 that included members of our own lab and two other mosquito ecology labs: Professor Thomas Scott's Lab ( University of California , Davis ) and Professor Laura Harrington's Lab ( Cornell University ) . We selected individuals from these three labs because they have been working on Ae . aegypti for many years and because they are familiar with the modeling framework that we are using . Details of our elicitation process are given in Text S1 . Please see Table 1 for definitions of uncertainty for those parameters that our analyses identify as being most important . A complete list of uncertainties for all parameters considered in our analyses is presented in Tables S1 , S2 , S3 , S4 , S5 . Many parametric uncertainty analysis techniques are now available [27] , [28] . One of the most popular parametric uncertainty analysis techniques is FAST [29] , [30] , [31] , which uses a periodic sampling approach and a Fourier transformation to quantify uncertainties in model predictions as measured by the variances and decomposes the total variance of a model output into partial variances contributed by individual model parameters . Ratios of partial variances to the total variance are used to measure the importance of parameters in their contributions to uncertainties in model predictions . The FAST analysis is a first-order global sensitivity analysis method for linear/nonlinear models that quantifies the separate contribution of each parameter to uncertainty , averaging over the values of all other parameters . These main effects do not consider the combined effects of two or more parameters . The traditional version of FAST assumes independence among parameters , but in this study , we used an improved version of FAST developed by Xu and Gertner [19] , [20] , [21] that can take into account correlations among parameters . The improved FAST analysis is implemented using the UASA ToolBox ( http://xuchongang . googlepages . com/uasatoolbox ) developed by Xu et al . [32] . To statistically compare the importance of different model parameters , standard errors of parametric uncertainty contributions are estimated using a delta method [33] . A sample size of 5000 individual realizations of the model gives us reasonable precision ( i . e . , small standard errors ) for the estimated parametric uncertainty contributions . Uncertainties in the model predictions are measured by variances , which can be greatly affected by any extreme outliers . In order to reduce the effect of those extreme outliers , we exclude simulations where the total number of pupae in the simulated community become larger than 10 , 000 at any day of the simulation ( this occurred in less than 5% of the total number of simulations ) , which is unrealistic given that the mean and standard deviation of the total number of pupae in our simulated community are about 2 , 000 and 1 , 100 , respectively , based on the entomological survey . We also observe that , when the population size is larger than 10 , 000 , the population generally keeps increasing through time and does not stabilize , which is not observed in the survey data and is only found in model runs that have a combination of a low level of dependence on food , slow development rate , and low percent of energy used for metabolic activity . In other words , these parameter combinations are unrealistically sampled by the FAST procedure . Skeeter Buster includes two types of stochasticity: environmental stochasticity and demographic stochasticity . Here , environmental stochasticity mainly refers to stochasticity in food input dynamics , while demographic stochasticity mainly refers to stochasticity in mosquito development , survival and dispersal . In order to understand the importance of stochastic uncertainty , we quantify it by carrying out a second model run for each of the 5000 parameter sets sampled by FAST and examining differences in predicted population densities between pairs of model runs ( see Text S4 for technical details ) . This involves a total of 10 , 000 simulations . In total , using five desktop computers ( Intel Xeon class CPU running at 2 . 8 GHz ) , it takes about two weeks to complete the described FAST analysis for this model .
Our results show that with the inclusion of uncertainties in biological parameters and stochastic uncertainty resulting from environmental and demographic stochasticity , the Skeeter Buster model provides community-level predictions of mosquito population density within a reasonable range ( Figure 1 ) . The 95% confidence interval of the population density at the community level of 612 houses ranges from about 20 , 000 to 100 , 000 for both eggs and larvae ( Figure 1 a , b ) , from 1000 to 3000 for pupae ( Figure 1c ) , from 400 to 1700 for nulliparous female adults ( Figure 1 d ) , from 300 to 3200 for parous female adults ( Figure 1 e ) , and from 500 to 2200 for male adults ( Figure 1f ) . Levels of uncertainty remain roughly constant over time as a result of constrained food inputs . For important parameters contributing to the uncertainty in predicted population density averaged over the second simulation year at each life stage , please see Figure 2 and Tables S6 , S7 , S8 , S9 , S10 , S11 . Generally , uncertainty in model parameters explains about 80% or more of the uncertainty in the model predictions . The uncertainty not explained by the main effects includes two components: 1 ) interactions among parameters; and 2 ) environmental and demographic stochasticity simulated in the model resulting from natural and individual variability . Of all the parameters in the model , four stand out as very important for most life stages . They are the nominal survival rate for female adults and for larvae , the coefficient of metabolic weight loss , and the larval development rate . The nominal survival rate for female adults accounts for about 72% , 70% , 40% , 24% , 18% and 14% of uncertainty in the predicted egg density , parous female adult density , larval density , nulliparous female adult density , male adult density , and pupal density , respectively . There are relatively strong nonlinear effects of nominal female adult survival rate on the predicted population density of parous female adults , egg and larvae ( Figure 3 ) . The strong nonlinear effect of female adult survival rate on parous female adult density results from the fact that this daily survival rate is multiplied repeatedly throughout the life stage of parous female adults . Therefore a large value can have a much stronger effect on parous female adult density than a small value of this survival rate . Given that egg and larval population densities are mainly determined by the density of parous female adults , both of these densities also experience a strong nonlinear dependence on the female adult survival rate ( Figure 2 ) . The coefficient of metabolic weight loss accounts for 21% , 16% , 14% , 8% , and 3% of uncertainty in the predicted pupal density , nulliparous female adult density , male adult density , larval density , and parous female adult density , respectively . The coefficient of metabolic weight loss is important for two reasons . First , when metabolic weight loss is high , less of the energy obtained from consuming food is available for larval growth , which could result in smaller larval body sizes and a smaller number of mosquitoes given the same amount of food ( See Figure S5 for a detailed illustration of the effect of coefficient of metabolic weight loss on predicted population size ) . Second , a large metabolic weight loss can result in a relatively long larval development time as is dependent on larval weight , leading to a lower overall survival rate at the larval stage and a reduced number of mosquitoes . For larvae and parous female adults , because the nominal survival rate of female adults has more dominant effects , the coefficient of metabolic weight loss become less important . The nominal survival rate of larvae accounts for 18% , 17% , 12% , 6% , 3% , and 2% of uncertainty in the prediction of nulliparous female adult density , pupal density , male adult density , larval density , parous female adult density , and egg density , respectively . The nominal survival rate of larvae is an important factor determining the outcome of development from eggs to adults as a result of the relatively long development time of larvae . For parous female adult and egg density , nominal survival rate of larvae becomes less important since they are less dependent on the larval stage . The larval development rate explains about 7% , 6% , 4% and 2% of uncertainty in the prediction of pupal density , nulliparous female adult density , male adult density , and parous female adult density , respectively . The development rate is important because it can affect the duration of larval stage , which can affect the overall larval survival ( a longer larval development time may lead to a lower overall survival rate at the larval stage , given a fixed rate of daily survival probability ) . Our results also show that parameters of predator activities for eggs ( high temperature limit of predator activities and the survival factor of predation at high temperatures ) are very important sources of uncertainty in the predicted population density at the larval stage ( Figure 2 b ) , but are not so important for other life stages . This is because egg survival only affects the early larval stage . For the late larval , pupal and adult life stages , other limiting factors are more important ( e . g . , coefficient of metabolic weight loss , larval and female adult survival rate ) . Our results show that for each life stage , stochastic uncertainty accounts for less than 5% of uncertainty in the predicted community-level population density on each day throughout the two-year simulation period ( Figure 4 ) . This suggests that stochastic uncertainty is relatively low compared to parametric uncertainty for community-level population dynamics . The stochastic uncertainty increases slightly through simulation time due to the accumulation of stochasticity in food input dynamics , dispersal , development and survival . The stochastic uncertainty contribution is relatively higher for pupae and male adults compared to other life stages , largely as a consequence of their smaller population sizes leaving them more prone to stochastic environmental perturbations ( e . g . , low temperatures ) . In this section , we quantify uncertainty in the predicted population densities for each individual house at a time close to the end of simulation period ( simulation day 720 ) . Means , standard deviations and coefficients of variation ( CV ) of population density are calculated for each individual house to measure the spatial uncertainty , based on 5 , 000 simulations using the parameter sets sampled by FAST . Proportions of uncertainty in the predicted population density at each individual house contributed by different parameters are estimated using FAST , and the proportion of uncertainty contributed by stochasticity is estimated using two replicates of the FAST sample ( see Text S4 ) . Our results show that the standard deviation of predicted mosquito population density for each life stage is low for houses where the mean population density is relatively low ( the main text only presents results for the female adult population distribution , see Figure 5 a , b; see Figure S6 , S7 , S8 , S9 for male adult , egg , larval and pupal distributions ) . However , the corresponding coefficient of variation and the proportion of stochastic uncertainty are much higher ( Figure 5 c , d and Figure S6 , S7 , S8 , S9 c , d ) . It is noticeable that stochasticity explains more than 50% of uncertainty in the predicted population density in every house for all life stages except for larvae . For the larval density prediction , the proportion of stochastic uncertainty is high ( >40% ) for most of the houses , except for a few houses with relatively large food inputs ( Figure S8 ) . The proportion of stochastic uncertainty at the individual-house level is substantially higher than that at the community level at the same simulation day ( <5% ) ( see Figure 4 ) . In terms of parametric contributions to uncertainty in the predicted population density , the nominal survival rate for female adults is important for all houses except for a few houses where the proportion of stochastic uncertainty is very high ( Figure 5 e and Figure S6 , S7 , S8 , S9 e ) . The coefficient of metabolic weight loss and larval survival rate are more important where there is a relatively larger amount of food inputs either in the house , or in neighboring houses ( Figure 5 f , g and Figure S6 , S7 , S8 , S9 ) . This is because relatively larger food inputs can lead to a higher population density so that the coefficient of metabolic weight loss and larval survival rate can have more important effects on local larval and pupal population density . Our results show that spatial dispersal is much more important for population densities in those few houses where the food inputs are large ( Figure 5 h and Figure S6 , S7 , S8 , S9 ) compared to other houses with small food inputs . The main reason for this is that a high dispersal rate will result in a large number of mosquitoes spreading out from these houses . For houses with small food inputs , dispersal may still contribute to the population dynamics ( due to the in-flow of dispersing mosquitoes from houses with relatively large food inputs ) but to a lesser extent as a result of stochasticity in dispersal . The effect of short-range dispersal on population density is much weaker for pupae ( See Figure S9 h ) , which depends more on the amount of food held by water containers in and around the house . Our results show that distributions of female and male adults are spatially clustered ( Figure 5a and Figure S6 a ) . The clustering of egg distribution is similar to that of female adults ( Figure 5a and Figure S7 a ) , while larvae and pupae are less clustered ( Figure S8 a and Figure S9 a ) . This is because larvae and pupae are more dependent on the water containers and the amount of food they hold , neither of which is clustered in the model input . Based on a spatial statistic of Moran's I ( see Text S5 ) calculated for each individual simulation ( Figure 6 ) , we show that there is no significant spatial clustering for pupae ( the p-values for Moran's I are not shown but are mostly larger than 0 . 05 ) , while there is some degree of spatial clustering for other life stages . Applying FAST analysis to the level of spatial clustering of female adults as measured by Moran's I , our results show that the most important factor affecting spatial clustering is the coefficient of metabolic weight loss ( Figure 7 a ) . Other important parameters include the nominal survival rate for larvae and for female adults , the short-range and long-range dispersal probabilities for female adults , and the coefficient of food dependence [a coefficient specifying the effect of food inputs in water-containers on larval body weight gain , with a lower value indicating a stronger effect of food on larval growth and a higher level of density dependence ( see Text S2 for more explanations ) ] . If we superimpose the hot spots of houses with large food inputs as identified by a Gi* ( d ) statistic [34] , [35] ( see Text S5 ) onto the female adult population density map ( Figure 7 b ) , we can see that high female adult population densities generally occur at or near houses with large food inputs . This suggests that high local population density ( determined by food inputs , survival rate , coefficient of metabolic weight loss , and coefficient of food dependence ) and spatial dispersal ( determined by mosquito longevity and dispersal probability ) are both important for forming the spatial clustering pattern as measured by the Moran's I statistic . If we calculate the semi-variance of female adult distribution ( a statistic to measure the strength of spatial autocorrelation , see Text S5 for details , using the spatial distribution of mean population densities at each individual house which are based on parameter sets sampled by FAST ) , we can show that the semi-variance stabilizes at a distance of 40–50 meters ( or , equivalently , 4–5 houses ) ( Figure 7 c ) . This suggests that , even though the spatial distribution of food input is not clustered at the level of individual houses , the distribution of adult mosquitoes may have clustering patterns if houses with large amount of food inputs are within a distance of 4–5 houses . This distance is close to that obtained in a previous empirical study indicating that the mosquito data for Iquitos exhibits a weak spatial clustering of Ae . aegypti at a distance of 30 meters [26] . To gain a better understanding of the population dynamics of Ae . aegypti , we also examine factors contributing to the temporal variability at the community and the individual house level . Temporal variability may result from stochastic uncertainty , biological development cycles , environmental factors ( e . g . , temperature ) and temporal dynamics of food in water-filled containers . For the temporal variability of population dynamics at the community level , our results show that important parameters include the temperature limits for survival and predation of eggs , the gonotrophic development rate , and the nominal survival rate for female adults ( See Text S6 ) . Additionally , at the individual-house level , the spatial dispersal of adult mosquitoes and the coefficient of food dependence are also important parameters ( see Text S7 ) .
Our results show that uncertainty in the estimate of nominal survival rate for female adults is the most important source of uncertainty for the prediction of population densities of all life stages by Skeeter Buster at both community and individual-house levels . Thus , it is important that researchers develop more accurate and precise empirical estimates of this parameter . Current estimates of survival are mainly based on mark-release-recapture methods , which may be subject to a number of errors ( e . g . , sampling errors , spatial heterogeneity , and environmental stochasticity ) . Thus , it could be difficult to reduce uncertainty in the estimate of adult survival . Mosquito adult survival can be affected by both intrinsic biological factors ( e . g . , age-related internal physiological deterioration causing senescence ) and extrinsic abiotic and biotic factors ( e . g . , predation , temperature and moisture ) . An important source of uncertainty for the estimation of adult survival rate is due to the uncertainty in predation . Improved model predictions may require a decoupling of the effects of intrinsic and extrinsic factors on mosquito survival . Our study shows that the coefficient of metabolic weight loss , a parameter describing food utilization by larvae , is important for uncertainty in the predicted mosquito population density . In view of the potentially large amount of uncertainty in the estimation of food inputs—an uncertainty which is not explored in our current study—future research on food quantification and food limitation for larval development should provide a better understanding of population dynamics . However , in the field , the effect of food on larval growth and productivity can be very different depending on the leaf species [36] , nutrient content [37] , [38] , algae abundance [39] , and microbial community [40] . Thus , it would be difficult to directly measure the amount of food available for larval growth . The weight gain model used both in Skeeter Buster and CIMSiM is mainly based on the laboratory work of Gilpin and McClelland [3] using liver powder as the food source for larvae . This may not be realistic , but at least provides us a way to estimate the amount of food ( equivalent to liver powder ) available for larval growth by fitting the model to field survey data [24] . However , food inputs for the weight gain model could be a very important source of uncertainty in Skeeter Buster . Currently we are conducting field experiments in Mexico to explore density dependent effects on larval growth and survival [41] , which may improve the weight gain model in the future . Our results show that spatial dispersal importantly affects population density and spatial pattern ( as measured by the Moran's I ) at the individual-house level . However , it does not have an important effect on population density of any life stage at the community level . This is because mosquitoes are present in almost every house of our simulated study area with plentiful availability of containers for mosquito oviposition . Dispersal only balances the population density among individual houses , but does not have much effect on the overall population density at the community level . If severe environmental conditions during the winter in temperate areas or vector control practices lead to a situation in which mosquitoes only survive in a small proportion of containers in refuge sites , then dispersal is likely to be important for the population density during the period of population recovery at the community level [11] . We also notice that dispersal is a particularly important source of uncertainty in the predicted population densities within houses that have the greatest food inputs , due to population outflow by dispersal . This could have important implications for the dynamics of disease spread because dengue infections in houses with high mosquito population density may pose a high risk of disease spread to nearby houses if a large number of infected mosquitoes move to nearby houses . Our results show that , compared to parametric uncertainty , stochastic variation does not produce substantial uncertainty in predicted population density at the community level . However , at the level of individual houses , stochastic uncertainty accounts for more than 50% of uncertainty in the predicted population density for houses with relatively small food inputs . Because stochastic uncertainty is generally irreducible , it could be very difficult to improve the precision of mosquito population density in individual houses even if we could substantially reduce parametric uncertainty in the future . Although stochastic uncertainty is high at the individual-house level , our results indicate that the spatial clustering pattern as measured by Moran's I is jointly determined by the food input , the food utilization by mosquitoes , the spatial dispersal of adult mosquitoes , and their longevity as determined by the survival rate . This suggests that the spatial model can be used to predict the spatial clustering of population density at the individual-house level given the spatial distribution of containers . Uncertainty in the model structure and in model data inputs ( e . g . , container data ) can both be important sources of uncertainty . We did not quantify those uncertainties in this study mainly due to the lack of currently available information . One example of structural uncertainty is in the water temperature calculations . The Skeeter Buster model uses a polynomial regression to calculate water temperature using air temperature and container shading based on data from Florida . An alternative approach has been provided by Kearney et al . [42] who coupled transient-state energy and mass balance equations to calculate daily temperature cycles in containers differing in size , catchment and degree of shading . This type of biophysical model of energy and mass transfer could potentially increase the prediction accuracy of water temperatures , which could be important for larval and pupal development . Uncertainty analysis can be used to characterize the importance of uncertainties that accompany the use of complex models . Quantification of uncertainty provides an indication of the reliability of predictions made by the model , making uncertainty analysis an indispensible step in the deployment of complex models . Our uncertainty analysis has identified parameters whose uncertainties have an important impact on the predictive ability of the model . Future studies should attempt to improve the estimates of these parameters , which will likely require the collection of additional data and reanalysis of existing data . Our reliance on expert knowledge to quantify the uncertainties of individual parameters means that the results of our uncertainty analysis are , to some extent , impacted by the biases to which the process of elicitation of expert opinion are prone [43] . However , Bayesian data analysis techniques [44] can be used to reduce such biases and improve estimates of parameters , by combining prior information ( prior distributions for each parameter , informed by expert opinion ) with information drawn from appropriate experimental and observational data . Although the uncertainty analysis results in this paper are based on the application of Skeeter Buster model to the Peruvian city of Iquitos , many of the results are likely to hold if the model were applied to other tropical areas . The insight gained into the importance of specific model parameters can provide general directions for the future improvement of models for mosquito population dynamics .
|
Dengue is one of the most important insect-vectored human viral diseases . The principal vector is Aedes aegypti , a mosquito that lives in close association with humans . Currently , there is no effective vaccine available and the only means for limiting dengue outbreaks is vector control . To help design vector control strategies , spatial models of Ae . aegypti population dynamics have been developed . However , the usefulness of such models depends on the reliability of their predictions , which can be affected by different sources of uncertainty including uncertainty in the model parameter estimation , uncertainty in the model structure , measurement errors in the data fed into the model , individual variability , and stochasticity in the environment . This study quantifies uncertainties in the mosquito population dynamics predicted by Skeeter Buster , a spatial model of Ae . aegypti , for the city of Iquitos , Peru . The uncertainty quantification should enable us to better understand the reliability of model predictions , improve Skeeter Buster and other similar models by targeting those parameters with high uncertainty contributions for further empirical research , and thereby decrease uncertainty in model predictions .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"public",
"health",
"and",
"epidemiology/infectious",
"diseases",
"public",
"health",
"and",
"epidemiology/global",
"health",
"mathematics/statistics",
"computational",
"biology/ecosystem",
"modeling"
] |
2010
|
Understanding Uncertainties in Model-Based Predictions of Aedes aegypti Population Dynamics
|
The meiotic cell division reduces the chromosome number from diploid to haploid to form gametes for sexual reproduction . Although much progress has been made in understanding meiotic recombination and the two meiotic divisions , the processes leading up to recombination , including the prolonged pre-meiotic S phase ( meiS ) and the assembly of meiotic chromosome axes , remain poorly defined . We have used genome-wide approaches in Saccharomyces cerevisiae to measure the kinetics of pre-meiotic DNA replication and to investigate the interdependencies between replication and axis formation . We found that replication initiation was delayed for a large number of origins in meiS compared to mitosis and that meiotic cells were far more sensitive to replication inhibition , most likely due to the starvation conditions required for meiotic induction . Moreover , replication initiation was delayed even in the absence of chromosome axes , indicating replication timing is independent of the process of axis assembly . Finally , we found that cells were able to install axis components and initiate recombination on unreplicated DNA . Thus , although pre-meiotic DNA replication and meiotic chromosome axis formation occur concurrently , they are not strictly coupled . The functional separation of these processes reveals a modular method of building meiotic chromosomes and predicts that any crosstalk between these modules must occur through superimposed regulatory mechanisms .
The meiotic cell division produces haploid gametes from diploid progenitors by segregating the maternally- and paternally-derived copies of each chromosome . The faithful distribution of homologous chromosomes in meiosis is facilitated in most organisms by the crossovers formed during homologous recombination . Meiotic recombination occurs through the carefully orchestrated repair of programmed DNA double-strand breaks ( DSBs ) and takes place shortly after DNA replication during an extended gap phase referred to as meiotic prophase . Both the formation and faithful repair of meiotic DSBs into crossover recombinants requires the large-scale reorganization of each meiotic chromosome into a series of chromatin loops emanating from a central , condensed axis [1] , [2] . Pre-meiotic S phase ( meiS ) is longer than pre-mitotic S phase ( mitS ) in many organisms [2] , [3] , [4] , and it has been hypothesized that the protracted DNA synthesis either contributes to , or is affected by , the dramatic chromosome reorganization that occurs during meiotic prophase . The kinetics of genome duplication are determined by where and when DNA replication begins . In eukaryotic genomes , DNA replication initiates from many sites along each chromosome , termed origins of replication , whose likelihood of utilization modulates the length of S phase in different developmental situations [5] . In yeast , potential replication origins are selected during G1 phase by the loading of the Mcm2-7 replicative helicase at specific sites along each chromosome 6 , 7 . Upon entry into S phase , the activities of cyclin-dependent kinase ( CDK ) and Dbf4-dependent Cdc7 kinase ( DDK ) trigger the initiation of DNA replication from a subset of these potential origins [8] , [9] . The remaining “inactive” origins are passively replicated by forks derived from nearby origins . Studies of individual DNA molecules revealed that the time at which each origin initiates DNA replication during S phase varies substantially between cells , and there is little correlation between distant loci , suggesting origin activation is not coordinated [10] , [11] . Nevertheless , when the population as a whole is considered , a robust and reproducible replication timing program is seen , regardless of strain background or method used to assess replication timing [8] , [9] , [11] , suggesting chromosomal DNA replication can be accurately described by a probability function . MeiS in budding yeast has been estimated to last between 1 . 5–3 times as long as mitS [3] , [12] . Theoretically , the longer duration of meiS could be due to either reduced efficiency of the initiation of DNA replication ( from all or a subset of origins ) , reduced replication fork rates or a combination of both . Previous studies suggested that the extended length of meiS is not due to changes in origin selection because the majority of the origins on chromosomes III and VI initiate DNA replication during both mitS and meiS in budding yeast [13] , [14] , and genome-wide analyses suggested that origin selection is also similar in both S phases in fission yeast [15] . In budding yeast there is no clear separation of meiS and the start of prophase; DNA synthesis occurs concurrently with the loading of factors required for axis and DSB formation , and both require the same cell-cycle kinase activities . The meiosis-specific cohesin complex containing Rec8 is loaded onto chromosomes as cells enter meiS , and subsequently the axial proteins Hop1 and Red1 associate with the same axial core sites along each chromosome [16] , [17] . As cells progress into prophase , chromosomes condense into a characteristic form , with a shortened axis and intervening DNA loops emanating away from the central core ( reviewed in [2] ) . Association of both axial and DSB factors with core sites is critical for the formation of DSBs on the adjacent loops by the topoisomerase-like enzyme Spo11 [17] , [18] , whose proper association is dependent on Rec8 [16] , [19] . A possible link between axis morphogenesis and S phase length was inferred from FACS analysis of total DNA content in yeast strains lacking Rec8 and Spo11 [12] , and conversely , DNA replication timing has been implicated as a determinant of the time of DSB formation [20] . To better understand how the early meiotic cell division is coordinated , we characterized the kinetics and requirements of meiS and axis formation genome-wide in budding yeast . We found that origin firing was either delayed or less efficient at the majority of origins in meiS . Consistent with a decreased replication capacity , cells were more sensitive to nucleotide depletion during meiS . However , preventing meiotic chromosome reorganization had little effect on origin activation in meiS , suggesting that DNA replication is not strongly regulated by or linked to axis structure . Conversely , full DNA replication was not required for either axis assembly or DSB formation . Together , these data indicate that DNA replication and the initiation of homologous recombination are separable events , which coordinately contribute to the formation of meiotic recombinant chromosomes .
To determine whether the initial selection of potential replication origins could explain the difference in S phase length between the meiS and mitS , we performed genome-wide location analysis for the Mcm2-7 helicase in pre-meiotic and pre-mitotic cells ( Figure 1A and Figure S1 ) . In total from both experiments , we observed Mcm2-7 binding at 393 loci , of which 382 had been identified previously as potential replication origins in mitotic cells in multiple strain backgrounds ( Table S1 ) . Comparison of the pre-meiotic and pre-mitotic Mcm2-7 binding sites revealed that the majority of origins loaded Mcm2-7 in both pre-meiotic and pre-mitotic cells ( 358/393 , Table S1 ) , consistent with the hypothesis that the mechanism of origin selection is the same in both cell cycles . Although origin selection was conserved at most sites , we observed differential Mcm2-7 binding at 35 sites; 22 mitosis-specific and 13 meiosis-specific sites ( Table S1 and Table S2 ) . Sites where Mcm2-7 binding differed between pre-meiotic and pre-mitotic cells were more frequently located in coding regions or promoters than sites with similar Mcm2-7 binding in both cell cycles ( 20/35 versus 87/358 , Chi-squared p = 8 . 1E-5 ) . Origins are generally under-enriched in coding regions of the genome due to the incompatibility between transcription and replication factor binding [21] . Consistent with this incompatibility , mitosis-specific Mcm2-7 binding sites were found in sporulation-induced genes SPO22 and ZIP1 , and meiosis-specific binding sites were associated with mitotic budding-related genes SHE2 and BUD27 ( Figure 1B and Table S2 ) . Moreover , we observed significantly increased gene expression during meiS at mitosis-specific Mcm2-7 binding sites , compared to sites that bind Mcm2-7 in both cell cycles ( Figure 1C compare blue and white boxes , t-test p = 1 . 7E-2 ) , suggesting that differential Mcm2-7 binding at many of these sites was driven by changes in gene expression . Meiosis-specific Mcm2-7 binding sites did not show as clear a change in gene expression , suggesting that other mechanisms may also contribute to Mcm2-7 association . Nevertheless , the small number of changes in Mcm2-7 binding we observed are unlikely to account for the extended length of meiS , as we did not observe larger gaps between Mcm2-7 binding sites in meiotic cells ( Figure 1D ) . Indeed , the meiosis- and mitosis-specific Mcm2-7 binding sites were consistently located close to other origins; the next Mcm2-7 binding site was on average 14 kb away with a maximum distance of 39 kb . In comparison , the average and maximum inter-origin distance for all potential origins was 30 kb and 95 kb , respectively ( Figure 1D ) . These data indicate that the reduced rate of meiS is not due to differential origin selection . Another possible explanation for the extended timing of meiS is that fewer sites with loaded Mcm2-7 complexes are used as origins of replication in meiS . To determine which potential replication origins were “active” during meiS , we measured the average replication time of sites across the genome in sporulating cells . To synchronize the cells as they passed through meiS , we used an ATP-analog-sensitive allele of the Ime2 kinase , ime2-as1 [22] . Ime2 promotes meiotic cell cycle entry and pre-meiotic DNA replication [22] , [23] , so ime2-as1 cells inoculated into sporulation medium containing the ATP-analog inhibitor for 4 hours did not initiate DNA replication ( Figure 2A , 0 minutes ) . When the inhibitor was removed , cells progressed synchronously through meiS , as measured by FACS ( Figure 2A ) . To determine the relative time of DNA replication , we pooled DNA samples that were collected every 7 . 5 minutes from the start to the end of meiS . The resulting samples were applied to a microarray together with a control ( non-replicating ) G1 sample to determine the relative abundance of DNA at 40 , 646 sites across the genome . Because the quantity of the DNA doubles when a site is replicated , sites that replicate earlier in S phase are enriched in the pool compared to sites that replicate later ( Figure 2A ) and the relative abundance of a given site in the S phase pool is inversely proportional to its average relative time of replication during S phase [9] . The results were visualized by plotting the relative enrichment in the S phase sample for all array features along a given chromosome , termed a replication timing profile ( Figure 2B and Figure S2 , red line ) . Peaks in the profile result from regions that replicated before neighboring sequences , and therefore must contain pre-meiotic origins of replication . We next sought to compare the subset of origins that are active during meiS and mitS . We created pre-mitotic replication profiles for cells of the same genetic background ( SK1 ) using alpha-factor synchronized cultures ( Figure 2B and , blue line ) . The mitS replication profiles were very similar to those obtained in W303 , another S . cerevisiae strain background ( Figure S3 ) , indicating that our method works similarly to those previously published and that the replication program is robust across different strains . To measure the level of random noise inherent in the copy number technique , we performed a control co-hybridization of two G1 DNA samples ( Figure 2B and Figure S2 , grey line ) . Because the smoothing algorithm used to create the profiles is unable to accurately predict replication time at the end of chromosomes , we excluded the 25 kb at each chromosome end from our analyses . After this exclusion , the meiS and mitS replication profiles showed a high degree of similarity ( Pearson correlation coefficient = 0 . 64 ) . Importantly , the peaks in both profiles were associated with sites of G1 Mcm2-7 binding ( Figure 2B , inverted triangles ) , indicating that we could identify active origins of replication in both profiles . In general , the same peaks were present in both the pre-meiotic and pre-mitotic replication profiles , extending to all chromosomes the previous observations that the same origins initiate DNA replication during both meiS and mitS [13] , [14] . Although we observed several instances in which meiosis- or mitosis-specific origins initiated replication ( Figure S2 ) , the effect on the overall profile was minimal , suggesting that these differences do not contribute substantially to S-phase progression . Although the majority of origins were active in meiS and mitS , examination of the replication profiles revealed that the relative replication time was different at many sites . The observation that many of the peak heights differed suggested that the timing or efficiency of replication initiation is altered at some origins in the meiotic cell cycle . When the distribution of replication timing for potential origins ( Mcm2-7 binding sites ) was compared to the whole genome in mitS , the majority of origins were replicated before bulk genomic DNA ( Figure 2C , compare blue and black lines on right distribution ) . This finding is consistent with a model of efficient DNA replication initiation from these sites as cells enter mitS . Replication of potential origins was very limited at the end of S phase , consistent with this replication being comprised of fork progression and termination . In contrast , potential origin replication distributed more uniformly throughout meiS ( Figure 2D , compare red and black lines ) , indicating that all origins did not initiate replication as efficiently upon entry into meiS . To further investigate the delay in replication initiation in meiS , we compared the relative time of replication of all Mcm2-7 sites in mitS and meiS ( Figure 2D ) . Given that there is no specific marker for the start and end of S phase in individual cells , or even the population as a whole , we used the FACS analysis to estimate the minimum length of meiS was 45 minutes at 30°C ( Figure 2A ) , approximately twice as long as mitS [24] . If origins initiated replication at a similar time during meiS and mitS , we would expect the distribution of origin timing to resemble the orange dashed line ( Figure 2D ) . If the time of replication were scaled with the length of S phase , but origins still fired in essentially the same order , we would expect the data to cluster around the blue linear-scaling prediction line ( Figure 2D ) . We found that origins fired in a similar order in meiS and mitS , but 71% of potential origins replicated relatively later in meiS than mitS ( Figure 2D , dots above the blue line ) . Consistently , we observed that 74% of origins replicated before the mean of the genome ( mid-S phase ) in mitS , but this number was reduced to 58% in meiS . We created a best fit model using linear regression ( Figure 2D , solid purple line ) [25] , and found that the earlier origins were most delayed and the replication rate seemed to increase at the end of S phase , similar to predictions from other eukaryotes [26] . These data indicate that replication of many potential origins is delayed in meiS , either because of later initiation or passive replication in late S phase . To confirm the apparent differences in replication kinetics that we observed in the meiS and mitS replication profiles , we sought to identify all early replicating origins by delaying cells in early meiS with hydroxyurea ( HU ) , as previously described for mitotic cells [9] . To begin , we tested a titration of HU concentrations to determine the optimal conditions to use with sporulating cells . We found that pre-meiotic cells were more sensitive to replication inhibition than mitotically dividing cells . First , the nature of the replication arrests differed . Pre-meiotic cells treated with 20–200 mM HU exhibited little or no replication progression , indicating that they had largely arrested replication in very early S phase ( Figure 3A , SPO samples ) . In contrast , the mitotic cells inoculated into rich medium ( YPD ) containing 5–200 mM HU did not fully arrest DNA replication . Consistent with previous reports [27] , even in the highest concentration of HU we observed detectible DNA replication after 2 hours ( Figure 3A , YPD+200 mM HU ) . To further test the idea that cells are more sensitive to HU exposure in meiS , we measured the autophosphorylation associated with activation of the intra-S phase checkpoint kinase Rad53 by western blotting . Consistent with the idea that pre-meiotic cells are more sensitive to replication inhibition , Rad53 became hyper-phosphorylated at a much lower concentration of HU in meiS than mitS ( Figure 3B ) . Because it has been reported that cells sporulated in the presence of HU have reduced levels of early meiotic transcripts , including IME2 [28] , we were concerned that addition of HU may generally inhibit meiotic entry independent of DNA replication and S-phase checkpoint activation . To test whether cells had entered meiS in each of our experiments , we measured the CDK-dependent phosphorylation of Orc6 that occurs as cells enter S phase . We were able to detect Orc6 phosphorylation consistent with meiS entry in cells exposed to 5–200 mM HU , although the kinetics of Orc6 phosphorylation were delayed in the presence of high amounts of HU ( Figure 3C ) . Addition of 200 mM urea , a similarly nitrogen-rich compound , also slowed meiS DNA replication and S-phase entry ( Figure 3A , 3C ) . However , because this treatment did not inhibit mitS DNA replication ( Figure 3A ) or elicit a checkpoint response in meiS or mitS ( Figure 3B ) , we conclude that high concentrations of HU or urea inhibit meiotic cell cycle entry independent of S-phase checkpoint activation . When HU- or urea-treated cells were released into sporulation medium without HU , they completed meiosis and formed viable spores , indicating they were reversibly inhibited and remained viable during the treatment ( data not shown ) . Together , these data indicate that high concentrations of HU ( or urea ) can reversibly delay meiS entry . Therefore , we chose to use 20 mM HU for all further meiotic experiments , as this concentration of HU inhibited meiS progression without significant delays in meiotic cell cycle entry . We used HU to determine the number and location of early-replicating origins in meiS and mitS . To create as similar a situation as possible , we synchronized cells in G1 in pre-sporulation medium , and subsequently divided the cultures into either sporulation medium ( to induce meiosis ) containing 20 mM HU or rich medium ( to induce mitosis ) containing 200 mM HU . After four hours , total DNA was collected and relative copy number was measured genome-wide . We detected replication initiation at a subset of sites in both pre-meiotic and pre-mitotic HU-arrested cells ( Figure 3D , Figure S4 and Figure S5 ) . The extent of replication in HU for each origin was similar to the time of replication of that site in the corresponding S-phase replication profile . The highest peaks in the HU profiles almost always coincided with the highest peaks in the corresponding replication timing curve ( Figure S5 ) . Thus , both the S phase and HU profiles detected the locations of early replicating origins . We compared the identity of origins replicated in meiotic and mitotic cells exposed to HU . We considered all origins that showed copy number enrichment greater than half the maximum enrichment of the genome to be replicated in each HU experiment ( Figure 3D and Figure S5 , inverted triangles ) . Although the majority of these origins were associated with a clear peak in the HU profiles , indicative of active initiation , some of these origins also could have been passively replicated by the fork from a nearby origin . Consistent with previous results from mitotically dividing cells , we observed that all chromosomes contained multiple early-replicating origins in mitS . Most chromosomes contained early-replicating origins during meiS , although the sites on chromosomes VIII and XVI were just below the 50% cutoff in the meiS HU profile . Comparing the number of origins replicated in the meiS and mitS HU profiles revealed that many fewer origins initiated replication in HU in pre-meiotic cells ( 47 versus 121 , Figure 3E and Table S1 ) . All origins that were replicated in HU in pre-meiotic cells were also replicated in HU in pre-mitotic cells ( Figure 3E ) , indicating that a subset of early mitotic origins also function efficiently in meiS , but that others become inhibited by HU during the sporulation program . Given that meiotic cells were far more sensitive to inhibition of DNA replication by HU treatment ( Figure 3A ) , we asked whether low nucleotide levels could explain the delayed replication initiation in meiS . We increased nucleotide levels by removing the ribonucleotide reductase ( RNR ) inhibitor SML1 [29] . When we measured DNA replication in sml1Δ cells treated with HU , we found that increasing nucleotide levels increased the number of early origins to levels intermediate between meiS and mitS conditions ( total of 71 , Figure 3E and Figure S4 ) . SML1 deletion did not result in defects in meiotic S phase entry , sporulation efficiency or spore viability ( data not shown ) . Given the sensitivity of meiotic cells to HU treatment , and the increases in DNA replication observed when nucleotide levels are increased , we propose that the starvation conditions required to initiate meiotic entry lead to low intra-cellular nucleotide levels that delay DNA replication . In an attempt to explain the changes in replication initiation timing that occurred between meiS and mitS , we looked at the relationship between chromosomal features and replication timing . Because meiotic entry is associated with large changes in the gene expression program , we first explored the connection between replication timing and gene expression . Using published datasets , we determined the expression of all genes within 500 bp of meiS and mitS origins [30] , [31] . We found no relationship between meiotic gene expression level and replication time in meiS ( Figure 4A ) . We also examined expression of genes surrounding the 47 meiS early origins and the 74 mitS-only early origins that do not initiate replication in HU in meiS . We found there was no significant difference between the expression levels of genes adjacent to these two classes of origins ( Figure 4B , compare red and blue boxes ) , again suggesting that the delay in meiS replication initiation is not due to transcriptional changes proximal to these origins . Similarly , we tested for a correlation between changes in time of replication and changes in gene expression between meiotic and mitotic cells , but found no relationship ( data not shown ) , indicating that the large-scale changes in replication timing in meiS are independent of the meiotic gene expression program . Finally , we explored the locations of meiotic unannotated transcripts ( MUTs ) [32] and found no relationship between their presence and Mcm2-7 binding and origin activation ( Table S2 ) . For example , ECM23/MUT1498 is predicted to cover ARS1621 , yet we observed Mcm2-7 binding and a peak in the replication profiles indicating origin activation at this site in both meiS and mitS ( Figure S2 ) . We next asked whether early replication of centromeres was conserved in meiS , because centromere proximal regions of chromosomes are replicated early during mitS in multiple yeasts [33] , [34] . Indeed , we found that all centromeres replicated in the first half of S phase in both mitS and meiS , with an average replication time of 22% and 28% of S phase , respectively ( Figure 4C ) . Additionally , centromere-proximal origins were highly enriched in the meiS HU profiles for every chromosome ( Figure S4 ) . Plotting the replication time of all origins during meiS as a function of distance from the centromere revealed that origins close to centromeres were consistently replicated earlier in S phase than origins farther from centromeres . Strikingly , meiS early origins were on average 70 kb from a centromere , and the majority ( 32 of 47 ) was within 50 kb of a centromere ( Figure 4D red dots , Figure 4E red distribution ) . Conversely , the set of origins that are replicated early during mitS extended significantly further ( average of 176 kb ) from centromeres ( Figure 4D , blue dots , Figure 4E , blue distribution , t-test p = 1 . 2E-4 ) . The effect of centromere proximity on replication time extended 50–100 kb along the chromosomes , as the origins in this range replicated significantly earlier than those farther away ( Figure 4C , 4D ) . The overall size of this 100–200 kb domain on each chromosome could , at least in part , explain why the smallest chromosome have a relatively high density of early origins and , on average , replicate early ( Table S1 and Figure S2 ) . These data reveal that , as in mitS , centromeres are a strong determinant of early meiS replication initiation , and the effect is more apparent during meiS due to compromised DNA replication capacity . Given that meiotic chromosomes undergo large structural changes in preparation for recombination , and factors involved in these processes have been implicated in the control of meiotic replication , we investigated the relationship between pre-meiotic DNA replication and DSB formation . To understand whether axis or DSB formation delay meiS replication initiation , we measured early DNA replication ( in the presence of HU ) in cells unable to form meiotic axes ( rec8Δ ) or defective in DSB formation ( spo11Δ ) . We observed similar HU replication profiles in sporulating wild-type , rec8Δ and spo11Δ cells: the vast majority of early meiS origins were replicated in all three strains ( 44 of 47 in wild-type cells , Figure 5A , 5B and Figure S4 ) . These data indicate that Rec8 and Spo11 are not primarily responsible for the changes in meiotic replication origin timing that we observed . We next determined the replication time of several chromosomal features during meiS , including DSB hotspots ( HSs ) and axis-associated core regions . Analysis of 3434 HSs mapped by Spo11-oligo accumulation [35] revealed that DSB sites were replicated throughout S phase ( Figure 5C , grey line ) . When the HSs were ordered by rank , there was a slight trend that the stronger HSs were replicated earlier in S phase than the weaker sites , although the difference was not statistically significant ( Figure S6A ) . We also measured the replication time of the strong DSB HSs mapped by either ssDNA enrichment in dmc1Δ cells or Spo11 genome-wide location analysis in rad50S cells [36] and found both were replicated with timing mirroring the entire genome ( Figure 5C , brown and green lines , respectively , t-test p = 0 . 25 for dmc1Δ and p = 0 . 90 for Spo11 DSBs ) , indicating neither set of HSs are preferentially enriched in early or late replicating regions . Since many DSB factors associate with axis sites [17] , we also measured the replication time of these regions . We defined axis association sites by overlapping localization of the axial proteins Rec8 , Hop1 and Red1 , which occurred at 565 sites in the genome ( Figure S7 , Table S3 ) . As with HSs , axial sites were replicated throughout S phase , with a distribution similar to the whole genome ( Figure 5D , t-test p = 0 . 97 ) . Moreover , the change in timing of DSB and axis sites showed no trend toward earlier or later DNA replication ( Figure S6B ) . The lack of detectable relationships between replication timing and the presence of axis and DSB sites suggests that meiotic chromosome structures do not strongly influence the timing of meiotic replication . Since axis formation was not a critical determinant of meiS replication timing , we wondered whether replication timing might instead contribute to axis formation . Therefore , we monitored axis formation by indirect immunofluorescence of the Hop1 and Red1 proteins on spread nuclei from cells lacking complete DNA replication . We inhibited DNA replication in 3 ways; by arresting cells in early S phase with HU , by depleting the Mcm2-7 loading factor Cdc6 ( cdc6-mn ) , which severely decreases DNA replication , and by removing the cyclins Clb5 and Clb6 , which prevents all pre-meiotic DNA replication [37] . In each case we observed Hop1 and Red1 distributed along chromosomes ( Figure 6A for Red1 , Hop1 data not shown ) , demonstrating that replication is not required for meiotic axis association . We noted that the chromosomes failed to condense and individualize in the clb5Δ clb6Δ nuclei , indicating that CDK activity and/or DNA replication are likely important for the full assembly of normal meiotic chromosome structures . However , previous analysis of Rec8 staining in cdc6-mn cells indicated that full DNA replication is not required to form full axes [38] , [39] . To confirm that axis formation occurs on the same sites in the presence and absence of DNA replication , we localized Rec8 , Hop1 and Red1 by whole-genome location analysis . As previously described , Hop1 ( Figure 6B and Figure S7 ) and Red1 ( Figure S7 ) localized to cohesin-associated regions ( CARs ) [17] , [40] , similar to both Scc1 in mitotic cells and Rec8 in meiotic cells [41] . Although the overall levels of binding varied , we found consistent patterns of Hop1 , Red1 and Rec8 at CARs in all situations lacking DNA replication examined , indicating that axis formation occurs independently of DNA replication ( Figure S7 ) . To determine whether the axes formed in these situations were functional , we measured genome-wide DSB formation by ssDNA enrichment in a cdc6-mn strain ( a dmc1Δ mutation was used to prevent repair of DSBs ) . We were able to detect DSBs across all chromosomes after 5 hours in sporulation medium ( Figure 6C and Figure S8 ) , despite the fact that the genome remained largely unreplicated at this time ( Figure 6D ) . These DSB HSs occurred at the same sites in both dmc1Δ and cdc6-mn dmc1Δ cells , although the intensity of DSB formation differed at many sites . Because the FACS analysis indicated that there is some DNA replication occurring in the cdc6-mn strains ( Figure 6D , see tailing towards 4C at 5 hours ) , we were concerned that the ssDNA at DNA replication forks might interfere with the quantitative measurement of DSBs in the cdc6-mn cells . Therefore , we measured DSB formation by pulsed-field gel electrophoresis , revealing high levels of DSBs in the cdc6-mn strains ( Figure 6E , note that the total signal is lower in the cdc6-mn samples because we normalized for cell number and the chromosomes do not replicate ) . We conclude that the formation of DSB-competent meiotic chromosomes does not require bulk meiotic DNA replication . Together , our results indicate that pre-meiotic DNA replication and meiotic chromosome axis assembly are functionally separable processes , and that the formation of a fully DSB-competent chromosome configuration can occur in a chromosome-autonomous fashion without the need for a sister chromatid .
Although the Mcm2-7 binding sites were largely the same in both the mitotic and meiotic cell cycles , approximately 9% of sites showed differential Mcm2-7 loading . These sites were much more frequently located within promoters or coding regions of genes , and Mcm2-7 loading appeared to be prevented by gene expression . Previous reports indicated that transcription through an origin is deleterious to replication complex assembly and replication initiation [21] , [42] . Similar to the situation described here , it has been reported that ARS605 is inactivated by meiosis-specific transcription of the overlapping gene MSH4 , which caused the loss of ORC-DNA association [14] . We did not identify ARS605 as a mitosis-specific origin in this study ( Figure S1 ) , possibly because we collected samples for Mcm2-7 analysis relatively early in the meiotic cell cycle , when MSH4 transcription was not yet fully activated and residual amounts of Mcm2-7 were still bound to the DNA . Alternatively , the low levels of Mcm2-7 we detected at ARS605 are insufficient for initiation . However , we identified additional origins , at which Mcm2-7 association was similarly regulated by transcription of the locus . We note that none of the meiosis-specific origins identified in this study were novel; either ARS activity or Mcm2-7 binding was detected in previous studies using mitotically dividing cells ( http://www . oridb . org ) . However , none of them were shown to initiate DNA replication in genome-wide mitotic studies , suggesting they do not function in their chromosomal context . Because these transcriptionally-regulated origins were located close to other origins , their inactivation is unlikely to have a substantial effect on the completion of DNA replication . Given that origin selection and activation were highly similar in meiS and mitS , the reduced rate of meiS must be due to delayed replication initiation or slow fork progression rates . The presence of a greater amount of noise in the meiS replication profiles made it impossible to measure relative fork rates in meiS and mitS , as we could not create an algorithm to specifically locate and measure all fork progression regions . Despite this difficulty , we noted that in some regions of the genome the scaled meiS and mitS profiles had similar slopes ( Figure S2 ) . Because the time of meiS is approximately twice the length of mitS and the profiles are scaled to S phase length , a similar slope indicates that the meiotic fork rates are approximately half the rate of the mitotic forks . On the other hand , we found strong evidence for a delay in replication initiation , as the majority of origins replicated later in meiS than mitS . This replication delay could be due to later or reduced efficiency of initiation , which the CGH method does not distinguish . In support of delayed initiation , a much smaller number of meiS origins initiated replication in HU . Although previous studies observed a similar efficiency of origin usage in meiS and mitS [13] , [14] , we found that the small chromosomes monitored previously showed smaller delays in meiS replication than larger chromosomes ( Figure S2 ) , leaving open the possibility that many origins exhibit a reduced efficiency of initiation in meiS . Recent studies suggest that timing and efficiency are linked [43] , [44] , so it is possible that both contribute to the delayed replication in meiS . We postulate that the reduced replication initiation in meiS is caused by a limiting initiation factor . One candidate is the level of CDK activity , which is required for replication initiation . Removal of the cyclin Clb5 in mitotic cells causes a reduction in late origin activation , but the presence of Clb6/CDK substitutes to drive mitS [45] , [46] . In meiotic cells , CLB5 deletion has an even more severe phenotype , with very delayed and inefficient replication [37] , suggesting residual Clb6/CDK activity is lower in meiotic cells . It seems less likely that DDK activity is limiting in meiS , as the use of an analog-sensitive allele of Cdc7 revealed that pre-meiotic DNA replication is virtually unaffected in the presence of the inhibitor [47] . It has been proposed that DDK must act at each individual origin at the time of initiation of DNA replication [48] , [49] , and it is possible that because replication initiation is spread out over a much longer time period in meiS , less DDK activity is required to support these lower initiation rates . A second and non-exclusive model is that slow pre-meiotic DNA replication is caused by the reduced dNTP levels in meiS [50] , which presumably occur because of the starvation conditions used to induce sporulation . Lowered nucleotide levels could account for a decrease in both initiation and fork progression rates . This hypothesis is reminiscent of studies of mitotic growth in the presence of HU , which also causes both a delay in origin activation and slower fork rates , resulting in a protracted S phase [27] . The observation that meiotic cells arrest more tightly in response to HU is also consistent with a model of reduced dNTP levels . Why is replication initiation delayed in meiS ? The generalized delay in replication initiation observed in meiS is very similar to the scaling of S phase observed in other mutants that slow DNA replication [25] , suggesting that cells respond to S phase challenges by decreasing the number of active forks . Although a slow S phase would be detrimental in competitive mitotic cultures because it would decrease growth rate , the meiotic program is a form of terminal differentiation and cells are not prepared to divide again immediately following meiotic exit . In sporulating cells , it may be advantageous to proceed slowly but accurately through the cell cycle . It has recently been shown that excessive replication initiation leads to genome instability [43] , and meiotic errors would be propagated by the progeny . In higher eukaryotes , meiosis takes place only in germ cells , which differentiate within special organs in response to specific developmental cues . Although these germ cells are not limited by nutrient availability , they may also be optimized for fidelity . It is interesting to note that not all origins were equally delayed during meiS; centromere-proximal origins initiated replication efficiently during both meiS ( This study and [13] ) . The conservation of early replication timing of centromeres in meiS and mitS ( reviewed in [33] , as well as in distantly related yeast species [34] , suggests that these sites play a critical role in determining the replication timing program . Consistent with this idea , it has been observed that moving a centromere was sufficient to change replication timing of adjacent origin sequences [51] . One hypothesis for early centromere replication is that it is important for kinetochore function , because mutants that change replication timing were shown to interfere with chromosome segregation [52] . Given that every chromosome has a centromere , it is also possible that linking early replication to centromeres helps to guarantee that every chromosome initiates replication in S phase , even when replication is compromised . Although it was previously observed that Rec8 and Spo11 regulate the length of meiS [12] , our findings indicated that the activation of the earliest replicating origins is not directly regulated by these proteins . Deletion of either Rec8 or Spo11 did not significantly alter the profile of early pre-meiotic replication in HU . Similarly , DSB sites and chromosome core sites were distributed at random with respect to replication time in meiS , indicating no direct link between replication delays and either axis assembly or DSB formation . Therefore , we suggest that meiosis-specific cohesion and the Spo11 protein are not responsible for the altered replication timing program that we observed in meiS . Similarly , full DNA replication is not required for the formation of break-competent meiotic chromosomes . The association of the axial proteins Hop1 and Red1 can be detected in HU-treated , cdc6-mn and clb5Δclb6Δ cells , all of which fail to duplicate their genomes , indicating that the formation of chromosome axes does not require either DNA replication or the presence of a connected sister chromatid . Association of Hop1 and Red1 occurs at cohesin-associated regions on chromosomes and is regulated by Rec8 . It has been shown that mitotic and meiotic cohesin complexes load onto chromosomes independent of DNA replication [19] , [38] , [39] , [53] , and we propose that axial proteins are similarly able to load onto unreplicated chromosomes . We have also shown that DNA replication is not required for DSB formation , as full levels of DSBs form in cdc6-mn cells , which complete very little DNA replication ( Figure 6 ) , extending our previous finding that cdc6-mn cells form DSBs at the engineered his4-LEU2 hotspot [54] . It has been observed that Spo11 is first loaded onto centromeres in meiS , before it becomes redistributed to sites along chromosome arms [19] , and it is possible that the early replication of centromeres drives Spo11 association . However , we were unable to detect the specific replication of centromeres in cdc6-mn cells by CGH analysis ( data not shown ) , yet they were able to form full levels of DSBs , indicating that Spo11 loading does not require early centromere replication . Although the wild-type kinetics of DSB formation in cdc6-mn cells indicates that chromosome axis assembly and DSB formation proceed on a timer that does not require DNA replication , it is clear that locally delaying DNA replication by eliminating origins on one chromosome arm retards proximal DSB formation [20] , [55] . The data presented here indicate that DSB formation is not intrinsically dependent on replication fork passage . The apparent discrepancy of these results could be explained if the single , severely delayed replication fork on the origin-less chromosome arm were to locally disrupt the loading or phosphorylation of DSB factors , delaying the initiation of DSB formation . In this case , the depletion of replication forks in the cdc6-mn cells would allow DSB formation . Alternatively , the processes could be coupled through a checkpoint mechanism triggered by the single delayed replication fork . In mitotic cells , the intra-S phase checkpoint down-regulates the activity of DDK [56] , [57] . As it was demonstrated that DSB formation requires higher levels of DDK activity than DNA replication [47] , the intra-S phase checkpoint could prevent DSB formation in wild-type meiotic cells , but may be lacking in cdc6-mn cells due to the severe decrease in DNA replication , similar to results obtained in S . pombe [58] , [59] . In either model , DNA replication is not a prerequisite for DSB formation , but rather the processes would be coordinated by superimposed regulatory mechanisms . Whereas much effort has been made to understand the events of meiotic prophase , relatively little is known about the regulation of meiS and the assembly of specialized chromosome structures necessary for meiotic recombination . In many organisms , the signals that initiate meiosis are unclear , and meiotic cell cycle entry cannot be determined by molecular or cytological markers until after the initiation of recombination . Studies in S . pombe revealed that pre-meiotic DNA replication initiates from the same sites as mitotic DNA replication , but replication is delayed or less efficient for a significant number of origins [15] . Our results indicate that this delay is due to limiting replication capacity , and reveal that centromeres are a strong determinant of early replication timing . Additionally , in S . pombe DNA replication is also not required for DSB formation , as multiple mutants that decrease DNA replication form DSBs across all chromosomes [58] . Therefore , the modular regulation of DNA replication and meiotic chromosome formation is conserved across distantly related yeast species , and could extend to other organisms as well .
Strains used in this study are isogenic to SK1 and are listed in Table S4 . Gene disruptions were carried out using a PCR-based protocol [60] . FLO8 was deleted in SB1505 to reduce flocculation . Cells lacking CLN3 were used for Mcm2-7 Genome-wide location analysis experiments to increase efficiency of meiotic entry . To induce synchronous meiosis , strains were pre-inoculated at OD600 = 0 . 2 in YPA ( 1% yeast extract , 2% bactopeptone , 1% potassium acetate , Figure 1 and Figure 2 ) , or BYTA medium ( 1% yeast extract , 2% tryptone , 1% potassium acetate , 50 mM potassium phthalate , Figure 3 , Figure 4 , Figure 5 , Figure 6 ) , grown for 16 hours at 30°C , washed twice with water , and resuspended at OD600 = 1 . 9 in SPO medium ( 0 . 3% potassium acetate , pH 7 . 0 ) at 30°C . For G1 control DNA , mitotic Mcm2-7 chromatin immunoprecipitation and mitS phase profiles , cells were inoculated into fresh YPD medium containing 5 µg/ml alpha-factor for 3 hours . For mitS profiles , cells were released into S phase by washing with 2 volumes of sterile water and resuspended in YPD at 30°C . MeiS cells containing the ime2-as1 allele were synchronized by incubation in SPO+20 µM 1-NA-PP1 ( Toronto Research Chemicals ) for 4 hours , the cells were washed with 2 volumes of sterile water and resuspended in SPO medium . Samples of 1 . 5 mls were removed every 5 minutes for mitS profiles and every 7 . 5 minutes for meiS profiles . All DNA samples inclusive of S phase ( those which showed cells in S phase in the FACS profiles , as well as two time points before and after ) were pooled for processing . For hydroxyurea ( HU ) experiments , cells were inoculated into YPD containing 200 mM HU or SPO containing 20 mM HU for 4 hours at 30°C . 25 mls of cells were harvested after 1 hour ( Mcm2-7 ) or 3 hours ( Rec8 , Hop1 , Red1 ) in SPO . For pre-mitotic Mcm2-7 analysis , 50 mls of culture at OD600 = 0 . 8 were collected from alpha-factor arrested cultures . Chromatin immunoprecipitation ( ChIP ) was performed as described [61] . One tenth of the lysate was removed as an input sample . Samples were immunoprecipitated for 16 hours at 4 degrees with UM185 ( Rabbit polyclonal anti-Mcm2-7 , 2 µl serum used per immunoprecipitation ) , 3F10 ( Rec8-3HA , Roche , used 2 µg per immunoprecipitation ) , anti-Hop1 or anti-Red1 ( N . Hollingsworth , 2 µl each serum used per immunoprecipitation ) . Cell pellets from 100 µl of sporulation culture were fixed in 70% ethanol overnight at 4°C . Ethanol was removed and cells were resuspended in 500 µl of 50 mM sodium citrate ( pH 7 . 0 ) containing 20 µg RNaseA for 16 hours at 50°C . Subsequently , 100 µg of Proteinase K were added and samples were incubated an additional 24 hours . 500 µl of 50 mM sodium citrate ( pH 7 . 0 ) containing 2 µM Sytox green ( Invitrogen ) were added . Cells were sonicated briefly on lowest power and scanned using a FACSCalibur ( BD Biosciences ) . Cells were lysed by bead beating in 500 µl phenol/chloroform and 500 µl of breakage buffer ( 10 mM TRIS , pH 8 . 0 , 1 mM EDTA , 100 mM NaCl , 2% Triton X-100 , 1% SDS ) . After centrifugation , the aqueous phase was precipitated with ethanol and resuspended in 500 µl TE7 . 6 ( 10 mM TRIS , pH 7 . 6 , 1 mM EDTA ) with 30 µg RNase . DNA was resuspended and samples were incubated at 50°C for 3 hours . DNA was sheared by sonicating at 100% output and lowest power for 10 seconds using a Branson sonicator . DNA was extracted with 500 µl phenol/chloroform , precipitated with ethanol and resuspended in 100 µl of TE7 . 6 For ChIP experiments , one half of the immunoprecipitated DNA and one tenth of the input DNA were labeled . For pooled S-phase and HU replication profiles , ∼5 µg of DNA from replicating or G1-arrested cells were labeled . Samples were labeled with Cy3-dUTP and Cy5-dUTP by random priming using 4 µg random nonamer oligo ( IDT ) and 10 units of Klenow ( New England Biolabs , Beverly , MA ) . Unincorporated dye was removed using microcon columns ( 30-kDa MW cutoff , Millipore , Bedford , MA ) , and samples were co-hybridized to custom Agilent arrays ( Wilmington , DE ) using a standard protocol . For each co-hybridization , Cy3 and Cy5 levels were calculated using Agilent Feature Extractor CGH software . Background normalization , log2 ratios for each experiment and scale normalizations across each set of triplicate experiments were calculated using the sma package [62] in R , a computer language and environment for statistical computing ( v2 . 1 . 0 , http://www . r-project . org ) . The raw data and log ratios analyzed in this study are available from the NCBI Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) , accession number GSE35667 . Mcm2-7 binding sites were defined as sites that were significantly enriched ( P<0 . 05 ) in 3 independent experiments . Array features within 500 bp of each other on the chromosome were merged into a single binding site . Mcm2-7 binding sites were assigned to a previously characterized origin if they overlapped the defined region ( http://www . oridb . org ) . Clear Mcm2-7 peaks were detected at some sites that did not make the statistical cutoff . They were manually included in the list of binding sites if they corresponded to a known origin and an Mcm2-7 binding site was called in the other data set ( meiotic or mitotic ) . For analysis of replication timing , Mcm2-7 sites were defined as the ACS , when one was predicted [63] or previously defined ( http://www . oridb . org ) , or else as the midpoint of the minimally defined origin region . The replication time of each Mcm2-7 binding site was determined for each experiment by assigning it to the time of the closest point on the smoothed and predicted replication timing curve . Points <25 kb from chromosome ends were excluded from timing analysis due to the inability to accurately predict timing at chromosome ends . For pooled S-phase and HU DNA samples , DNA replication profiles were smoothed and predicted every 50 bp using the loess smoothing spline with a span = 0 . 025 and a spar = 0 . 45 ( Table S5 ) . Mcm2-7 binding sites were considered replicated in HU if their value was greater than half of the maximum value in the genome ( excluding points <25 kb from chromosome ends ) . Axis association sites were defined as those with overlapping Rec8 , Hop1 and Red1 binding at more that one adjacent chromosomal feature , defined similarly to Mcm2-7 binding sites , except with P<0 . 15 . The positions of axis association sites were taken to be the midpoint of the intersection of the binding peaks of all three proteins . Analysis of the replication time for axis association sites , Spo11 binding sites and ssDNA-enriched sites was performed as for the Mcm2-7 binding sites . To measure gene expression , we analyzed the average of expression values at 15 and 20 minutes post alpha-factor from the mitotic data set of Granovskaia at al . [30] and the average of the 2- and 3-hour expression data for wild-type cells from Borde et al . [31] . The expression data sets were scale-normalized to a mean log value of 0 and a standard deviation of 1 over the 4987 genes for which data were available in both sets . Origin-proximal transcripts are those within 500 base pairs of the Mcm2-7 binding site . We repeated all analyses using the dataset of Primig et al . [64] and Friedlander , et al . [65] , and obtained highly similar results ( data not shown ) . Meiotic nuclear spreads were performed as described [66] . In brief , the nuclei of spheroplasted cells were spread on a glass slide in the presence of paraformaldehyde fixative and 1% lipsol . After drying , the slides were blocked in blocking buffer ( 0 . 2% gelatin , 0 . 5% BSA in PBS ) and stained with anti-Red1 ( N . Hollingsworth , 1∶250 dilution ) . The genome-wide analysis of DSBs in the cdc6-mn strain using ssDNA enrichment was conducted as described [36] . Clamped-homogeneous electric field ( CHEF ) gel electrophoresis and Southern blotting were performed as described [36] .
|
Sexually reproducing organisms rely on a specialized cell division called meiosis to produce genetically distinct gametes with half the chromosome number of the parent . The first stage of the meiotic cell division is the duplication of chromosomes , followed by the exchange of DNA between homologous chromosomes inherited from both parents . It has long been known that DNA replication occurs more slowly in pre-meiotic cells than in mitotically dividing cells , and it was postulated that this delay is due to the chromosome structures or proteins required for homologous DNA exchange . We show here that the delay of DNA replication in yeast is regulated separately from the formation of recombinant chromosomes; preventing recombination structures from forming does not alleviate the delays in pre-meiotic DNA replication , and cells lacking DNA replication are able to initiate recombination . We propose that these two processes are functionally separable and that the delay in pre-meiotic DNA replication in yeast may be a result of the starvation conditions required for the induction of meiosis in this organism .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"meiosis",
"chromosome",
"structure",
"and",
"function",
"centromeres",
"cell",
"division",
"dna",
"replication",
"dna",
"dna",
"synthesis",
"chromosome",
"biology",
"biology",
"molecular",
"biology",
"cell",
"biology",
"nucleic",
"acids",
"dna",
"recombination",
"molecular",
"cell",
"biology"
] |
2012
|
Separation of DNA Replication from the Assembly of Break-Competent Meiotic Chromosomes
|
Herpes simplex virus type 1 causes mucocutaneous lesions , and is the leading cause of infectious blindness in the United States . Animal studies have shown that the severity of HSV-1 ocular disease is influenced by three main factors; innate immunity , host immune response and viral strain . We previously showed that mixed infection with two avirulent HSV-1 strains ( OD4 and CJ994 ) resulted in recombinants that exhibit a range of disease phenotypes from severe to avirulent , suggesting epistatic interactions were involved . The goal of this study was to develop a quantitative trait locus ( QTL ) analysis of HSV-1 ocular virulence determinants and to identify virulence associated SNPs . Blepharitis and stromal keratitis quantitative scores were characterized for 40 OD4:CJ994 recombinants . Viral titers in the eye were also measured . Virulence quantitative trait locus mapping ( vQTLmap ) was performed using the Lasso , Random Forest , and Ridge regression methods to identify significant phenotypically meaningful regions for each ocular disease parameter . The most predictive Ridge regression model identified several phenotypically meaningful SNPs for blepharitis and stromal keratitis . Notably , phenotypically meaningful nonsynonymous variations were detected in the UL24 , UL29 ( ICP8 ) , UL41 ( VHS ) , UL53 ( gK ) , UL54 ( ICP27 ) , UL56 , ICP4 , US1 ( ICP22 ) , US3 and gG genes . Network analysis revealed that many of these variations were in HSV-1 regulatory networks and viral genes that affect innate immunity . Several genes previously implicated in virulence were identified , validating this approach , while other genes were novel . Several novel polymorphisms were also identified in these genes . This approach provides a framework that will be useful for identifying virulence genes in other pathogenic viruses , as well as epistatic effects that affect HSV-1 ocular virulence .
Herpes simplex virus type 1 ( HSV-1 ) causes recurrent mucocutaneous lesions , is an increasing cause of genital herpes , and is the primary source of infectious blindness and sporadic encephalitis in the United States [1–4] . HSV-1 ocular infection in humans usually presents as conjunctivitis , which can then advance to epithelial keratitis or deeper corneal infection ( stromal keratitis ) [4] . HSV-1 viral replication in the corneal epithelium triggers cell death , and infiltration of CD4+ T-cells resulting in corneal damage [5] . Research using animal models has found that the severity of HSV-1 infections depends on three factors; innate immunity , host immune response , and viral strain [6–21] . Several groups have used gene mapping methods to identify host genes influencing the severity of HSV-1 ocular disease . Mapping studies in mice have identified loci on chromosomes 4 , 5 , 12 , 13 , and 14 associated with general clinical disease [22] , as well as a locus near the TNF p55 receptor on the murine chromosome 6 associated with resistance to HSV-1 infection and reactivation [11] . Other studies have also discovered loci on mouse chromosome 16 associated with mortality [15] , mouse chromosome 12 which was associated with weight loss [15] , CD45 tyrosine phosphatase ( protective immunity against encephalitis ) [23] , and the calcitonin receptor which was related to susceptibility to encephalitis [24] . Recently , the NK complex on the distal arm of murine chromosome 6 was found to restrict viral spread in the brains of C57BL/6 mice [25] . The severity of ocular disease has been shown to be influenced by the genetic makeup of viral strains [19 , 26 , 27] and conventional studies on the genetics of viral virulence have depended on isolating and characterizing a naturally occurring viral strain with altered virulence characteristics , genetically engineering either deletions or point mutations , or using marker transfer methods to exchange genes between strains . It is highly likely that the virulence phenotype of a given strain of HSV is due to the effects of multiple genes and epistatic interactions between these genes . Early evidence for potential epistatic interactions was provided by Peter Wildy [28] . He carried out mixed infections with HSV strains using chorio-allantois membranes and isolated several recombinants that displayed altered plaque and virulence phenotypes . In 1986 Javier et al [29] showed that mixed infections with two avirulent HSV-1 strains generated lethal recombinant viruses . Subsequently , we [30] showed that mixed ocular infection with low virulence parental viruses generated recombinants with varying virulence phenotypes . More recently , the same phenomenon has been shown to occur in mixed genital infections [31] . In a previous study we used marker transfer of genomic segments from a moderately virulent strain , CJ394 , into the avirulent strain OD4 , to map genes associated with ocular and neurovirulence [32] . This study identified several virulence determinants , including UL41 ( VHS ) , UL42 and US1 ( ICP22 ) , and suggested there was a complex interplay between viral genes since we obtained different disease phenotypes depending on which combinations of genes were transferred into the avirulent OD4 strain [6] . We also showed that two sequencing changes , S34A and Y116C in the ICP22 protein affected ocular virulence only when co-inherited [32 , 33] . Our work was the first to actually identify genes involved in these epistatic interactions . We have developed a novel approach incorporating QTL based analysis of the genomes and phenotypes of 40 HSV-1 viral recombinants generated by mixed infection with two avirulent parental strains; OD4 and CJ994 to identify genes affecting virulence . The blepharitis and stromal keratitis ocular disease phenotypes of each viral recombinant were quantified and combined with genomic sequence data for QTL based phenotypic association analysis . The QTL based analysis , which we term vQTLmap , used a Ridge regression model to identify several phenotypically meaningful features for blepharitis and stromal keratitis . Notably , amino-acid encoding nonsynonymous SNPs in UL24 , ICP8 , VHS , gK , UL56 , ICP4 , US1 , US3 , and gG were predicted to influence the severity of blepharitis . Nonsynonymous SNPs in VHS , ICP4 , ICP22 , US3 and gK were predicted to affect the severity of stromal keratitis . We also present evidence that the ability of the virus to replicate in the mouse is an important driver of virulence . The present study provides a methodology that will be useful for identifying additional virulence genes in HSV and other pathogenic viruses , examining epistatic interactions , and identifying protein-protein interaction networks that affect virulence .
The recombinant viruses used in this study were generated by mixed infections with two avirulent parental strains; OD4 and CJ994 . The OD4 and CJ994 strains were low passage clinically derived plaque purified isolates from Seattle , WA , USA , and the ocular disease phenotypes of the OD4 and CJ994 parental strains ( blepharitis and stromal keratitis ) were characterized previously [30] . The OD4-CJ994 recombinants were generated using both in vivo and in vitro methods [30 , 34] . Briefly , the seventeen in vivo derived recombinants ( Table 1 ) were derived as follows . Three to 4-week-old BALB/c female mice were infected by corneal scarification with 1 × 105 PFU each of strain OD4 and CJ994 . The corneas were removed at day 3 post-infection . homogenized , and freeze-thawed . The cleared lysates were serially diluted and titered on Vero ( CCL-81 , ATCC , Manassas , VA , USA ) cells for plaque selection . The selected plaques were subjected to two additional rounds of plaque purification . Individual plaques ( one per mouse to avoid isolating siblings ) were picked and high-titer stocks were prepared in Vero cells as we have described previously [34] . The 23 in vitro derived recombinants ( Table 1 ) were generated by infecting a 10cm plate of confluent Vero cells with 2 × 108 PFU ( multiplicity of infection , MOI , 10 ) of the OD4 and CJ994 ( 1:1 ratio ) viruses . When the cells reached a 100% CPE , they were harvested and subjected to three freeze-thaw cycles . Clarified supernatants ( 400 xg , 10 minutes ) were then serially diluted and plaqued onto Vero cells in six-well plates . Individual plaques were randomly picked , further plaque purified an additional two times , and high-titer stocks were prepared as described previously [34] . We deliberately chose to use two low virulence parents which were likely to generate recombinants with increases in virulence . This initial genetically restricted set of parents also increased the probability of finding significant associations with fewer recombinants . The ocular mouse model for HSV-1 disease used in this study has been described previously [26 , 30 , 35] . Briefly , for each OD4-CJ994 recombinant strain , the corneas of ten 4–6 week old Balb/C female mice were scarified using a 30 gauge hypodermic needle , and 5μL of medium ( DMEM , 2% serum ) containing 1 x 105 pfu/ml of each recombinant virus was placed on the cornea . The mice were scored for blepharitis and stromal keratitis on days 1 , 3 , 5 , 7 , 9 , 11 , 13 , and 15 post-infection . The scoring system was as follows . Blepharitis: 1 + , mild swelling of eyelids; 2+ , moderate swelling with some crusting; 3 + , eye swollen 50% shut with severe crusting; 4 + , eye crusted shut . Stromal keratitis: 1 + , some haziness; iris detail visible; 2+ , moderate clouding , iris detail obscured; 3+ , cornea totally opaque; 4+ , perforated cornea . Tear film samples were also taken on days 1 , 3 , 5 , and 7 days post-infection , serially diluted , and then titered on Vero cell monolayers . The mean peak disease score ( MPDS ) , which is the average of the most severe disease score for each mouse , per viral recombinant strain for the 15 day duration of the study was calculated for blepharitis and stromal keratitis . Mortality due to encephalitis was also recorded , but there weren’t enough neurovirulent strains to determine significant mortality associations . We also scored the severity of corneal neovascularization , but significant associations were not identified . This will require the analysis of additional recombinants . Eighteen hour growth experiments were performed using both Vero cells and mouse embryonic fibroblasts ( MEF; M-FB-481 , Lonza , Walkersville , MD , USA ) . The Vero cells were cultured using Dulbecco’s Modified Eagle’s Medium ( DMEM ) plus 5% serum ( 1:1 mixture of fetal bovine serum and defined supplemented calf serum ) , and the MEF cells were cultured with DMEM containing 10% fetal bovine serum . The Vero and MEF cells were grown to confluency in 24-well plates in duplicate and infected with seven high pathogenic and nine low pathogenic OD4-CJ994 recombinants at a multiplicity of infection ( MOI ) of 1 , with DMEM containing 2% serum . The cells were harvested 18 hours post-infection , centrifuged at 400 xg and subjected to three freeze-thaw cycles . The resulting cleared lysates ( 400 xg , 10 minutes ) were then serially diluted and titered on Vero cells . The genomic sequencing and assembly of the 40 OD4-CJ994 HSV-1 recombinants has been previously described [34] . Briefly , twelve of the in vitro-derived recombinants were sequenced using an Illumina HiSeq 2000 sequencing system . One microgram of high-quality genomic DNA was submitted to the University of Wisconsin—Madison DNA Sequencing Facility for paired-end library preparation . Each library was generated using an Illumina TruSeq LT sample preparation kit ( Illumina Inc . , San Diego , CA , USA ) per the manufacturer's specifications , with 300-bp fragments being targeted . Paired-end , 100-bp sequencing was performed in a single lane on the Illumina HiSeq 2000 sequencing system using SBS ( version 3 ) kits , and an average of 5 million unique reads ( 1 Gb ) was returned per library . FASTQ reports were created using the CASAVA ( version 1 . 8 . 2 ) program . The remaining recombinants were sequenced using the Illumina MiSeq platform , which produces longer reads . Five hundred nanograms of high-quality genomic DNA was submitted to the University of Wisconsin—Madison DNA Sequencing Facility for paired-end library preparation . Each library was generated using an Illumina TruSeq Nano LT sample preparation kit per the manufacturer's specifications , with 550-bp fragments being targeted . Paired-end , 250-bp sequencing was performed on the Illumina MiSeq platform using version 2 kits , and an average of 250 , 000 unique reads ( 125 Mb ) was returned per library . FASTQ reports were created using the CASAVA ( version 1 . 8 . 2 ) program . The paired-end sequencing reads from the 40 recombinants and strain CJ994 were generated using a reference assembly . Between sequencing runs , an updated annotation was made available through GenBank; however , for consistency we decided to use the annotation with GenBank accession number NC_001806 . The sequencing reads were aligned to the sequence of HSV-1 strain 17 using a local alignment method , with a consensus sequence subsequently being generated and extracted in a manner similar to that described previously [36] . Resulting gaps in the reference assembly were filled in with N′s ( any nucleotide ) without a proxy sequence , as has been done previously [37 , 38] . The reason for not filling the sequencing gaps with proxy sequence is that these regions may not be phenotypically silent . Filling these regions with proxy sequence could produce false negatives in the QTL analysis . The genomes of the 40 OD4-CJ994 HSV-1 recombinants were aligned with the OD4 and CJ994 parental genomes using the MAFFT aligner from the SATé software package [39 , 40] . The multiple sequence alignment is available for download at http://sites . ophth . wisc . edu/brandt/ . From the multiple sequence alignment ( MSA ) , we first identified the alignment coordinates at which there were polymorphisms . We then filtered this set of MSA coordinates in order to limit our attention to those for which ( i ) the parental strains have different alleles , ( ii ) all recombinants have one of the two parental alleles , and ( iii ) the two parental alleles each occur in at least five of the recombinants . In order to reduce the effect of artifacts , such as large alignment gaps , we also filtered MSA coordinates that were in the neighborhood of at least 15 consecutive gaps . The motivation for filtering was to focus our analysis on the polymorphisms that occur frequently enough in our recombinant population that it would be possible to detect meaningful associations with the phenotypes . The potential downside of the filtering is that we might be excluding some functionally significant polymorphisms . From the set of filtered MSA coordinates , we next aggregated neighboring coordinates into haplotype blocks . We defined a haplotype block as a contiguous region of the genome in which each recombinant has an identical pattern of inheritance across the SNPs . That is , for a given recombinant , all of the alleles within a haplotype block are either identical to the corresponding allele for one parent or the other . This process resulted in 491 haplotype blocks . To form the representations for machine-learning algorithms , we defined a feature vector for each recombinant and parental strain such that there are two binary features per haplotype block and the values of the feature indicate whether that block was inherited from either the OD4 or CJ994 strain . The motivation for choosing a two-bit encoding per haplotype was to be able to represent other polymorphisms that are not inherited from either parental strain which will be included in future studies . We applied three different machine-learning methods to learn models mapping the haplotype feature vectors described above to the three phenotypes of interest . We learned separate models for each phenotype where the phenotype for a given strain was the mean peak disease score for the animals infected with the strain . The learning methods we investigated were Random Forest regression [41] , Lasso regression [42] and Ridge regression [43] . We selected these specific methods because they are all well suited to tasks with many irrelevant features , and because they represent two broad classes of models: whereas Lasso and Ridge learn linear functions , the Random-Forest approach learns a set of tree-based functions . We used the R randomForest package ( https://cran . r-project . org/web/packages/randomForest/ ) to learn Random-Forest models . The parameter specifying the number of trees in each forest was set to 1 , 000 . All the other parameters of the algorithm were set to their default values . This decision was made in order to minimize the likelihood that the models would overfit the data set , given the small number of recombinants available . The random seed was set to the value 123 to ensure reproducibility in the random selection of bootstrap samples and the random selection of candidate features at each internal node in a tree . To learn Lasso and Ridge regression models we used the R glmnet package ( http://cran . r-project . org/web/packages/glmnet/ ) . The Lasso or Ridge regression method was selected by setting the ‘alpha’ parameter value to 0 or 1 respectively . All other parameters were set to their default values . For each learned model , the λ parameter for both Lasso and Ridge was set to the value that minimized cross-validated error within each training set . 100 candidate values of λ considered during this process were determined by the glmnet package using its default procedure . In order to measure the extent to which the learned models were able to capture general relationships between viral genotypes and disease phenotypes , we used a leave-one-out cross-validation methodology . Specifically , on each iteration of the cross validation , we held aside one instance ( consisting of a haplotype feature vector and the associated phenotype ) , learned a model using the remaining instances , and then applied the learned model to predict the phenotype of the held aside instance . We measured the accuracy of our predictions using both mean squared error ( MSE ) and R2 measures . To assess the whether these measures showed statistically significant levels of predictive value , we employed a Monte Carlo methodology . For each phenotype , we repeated the cross-validation procedure 1 , 000 times with the measured phenotypes randomly assigned to the 42 haplotype feature vectors ( i . e . the response variables in each data set were shuffled ) . For each randomized cross-validation , we measured the resulting R2 and MSE values as we did with the actual data . We constructed box plots to display the distribution of R2 and MSE values for the randomized data and to compare them to their counterpart values for the actual data . Since the Ridge regression models resulted in the best predictive accuracy among the three learning approaches , we focused on these models to identify the strongest genotype-phenotype associations . To do this , we used a Monte Carlo methodology that systematically considered each feature ( i . e . haplotype block ) in isolation and measured its impact on the MSE of the learned models . For each feature , we repeatedly created new test-set instances that were identical to the actual instances except that the values of the feature were permuted . That is , we retained the distribution of values for the given feature , but broke the dependence between the feature values and the phenotypes . We then measured the change in MSE when using the same cross-validation methodology as described above , but with the permuted feature . We did this 100 times for each feature , and then constructed Manhattan plots showing the average change in MSE as a function of genome coordinates ( relative to HSV-1 strain 17 ) . To determine thresholds for significance , we identified the largest decrease in MSE that occurred with the permuted data for each phenotype and negated this value . This approach was based on the assumption that decreases in MSE resulting from permuted data indicated variance due to noise and small sample sizes , and therefore meaningful associations were likely to show increases in MSE that had magnitudes at least as large as the largest decrease . A protein-protein interaction network based on vQTLmap identified proteins containing nonsynonymous variations was assembled using literature searches in conjunction with GADGET ( http://gadget . biostat . wisc . edu/ ) , a tool that finds and ranks genes that are associated with a concept of interest in the biomedical literature . The network was generated using Cytoscape 3 . 2 . 0 [44] . A full list of the protein-protein interactions assembled through literature searches is located in S3 Table . Linear regression scatter plots of the mean peak titers versus mean peak disease scores for blepharitis and stromal keratitis were constructed using SigmaPlot 12 . 0 ( Systat , San Jose , CA , USA ) . To determine statistical differences between the MPDS scores of in vivo and in vitro derived recombinants , non-parametric Mann-Whitney rank sum tests were performed using SigmaPlot 12 . 0 . Mann-Whitney rank sum tests were also performed to establish if the mean peak tear film titers were statistically different between the in vivo and in vitro derived strains . To ascertain if trends in ocular disease associated with vQTLmap identified features were statistically significant , the mean peak disease scores for blepharitis and stromal keratitis for each of the 40 recombinants were first combined . For each notable vQTLmap feature , Mann-Whitney rank sum test was performed by placing the combined MPDS scores associated with SNPs derived from the OD4 parent in one array , and from the CJ994 parent in the other array . This research was approved by the University of Wisconsin-Madison School of Medicine and Public Health Institutional Animal Care and Use Committee ( Animal Welfare Assurance Number A3368-01 ) as protocol # M00267 , expiration date 5/20/2018 . Our IACUC adheres to the guidelines mandated by the Animal Welfare act , administered by the United States Department of Agriculture ( USDA ) , and the Public Health Service Policy on the Humane Care and Use of Laboratory Animals , overseen by the NIH Office of Laboratory Animal Welfare ( OLAW ) .
We previously published the sequences and recombination maps of 40 OD4-CJ994 recombinants [34] . To obtain quantitative disease scores , 10 mice per group were infected by corneal scarification with each recombinant strain , and the severity of blepharitis and stromal keratitis was determined . Although we had previously identified virulence phenotypes for the in vivo recombinants [30] we re-determined them for the current study to insure consistency across the dataset . The mean peak disease scores ( MPDS ) for each recombinant are shown in Fig 1 . A range of MPDS scores was observed , ranging from the low pathogenic recombinant 10-14-1 ( blepharitis 1; stromal keratitis 0 ) to high pathogenic recombinants like 10-2-2 ( blepharitis 3 . 4; stromal keratitis 3 ) . Notably , the in vivo derived recombinant strains exhibited higher MPDS scores than the in vitro derived recombinants . The mean blepharitis MPDS score of the in vivo derived strains was 2 . 81 versus 1 . 54 for the in vitro derived strains , which was significantly different ( p = <0 . 001 ) . The mean stromal keratitis MPDS scores were 2 . 2 for the in vivo derived recombinant strains , compared to 1 . 11 for the in vitro strains . These differences were also statistically significant ( p = <0 . 001 ) . We also observed mortality with the 2-4-2 , 2-5-3 , 10-1-2 , 10-2-3 , 10-5-1 , 10-6-2 , 10-6-3 , 10-11-2 , 11M , 31XL , 36L , and 82S recombinants . We do not have enough power with the current data set to be able to identify mortality determinants using the vQTLmap analysis . To assess the ability of each OD4-CJ994 recombinant to replicate in vivo , corneal tear samples were taken on days 1–7 post-infection , and the mean peak titers for each recombinant are shown in Fig 1C . There was at least a 3-log difference in the mean peak titers , which ranged from 1 . 48 x 102 pfu/mL for recombinant 81L to 4 . 5 x 105 pfu/mL for the 76M recombinant . The average mean peak titer for the in vivo strains was 1 x 105 pfu/mL versus 5 . 5 x 104 pfu/mL for in vitro derived recombinants and was statistically significant ( p = 0 . 023 ) . Linear regression analysis of MPDS scores versus mean peak tear film titers suggest that there may be two separate populations for the blepharitis and stromal keratitis phenotypes ( Fig 2A and 2B ) . The results also suggest that ocular disease severity and ability to replicate in vivo may be linked , with the majority of low pathogenic or high pathogenic recombinants associating together . There were however , several low pathogenic recombinants such as 4M , 16S , and 65M that replicated to levels similar to that of the high pathogenic strains ( Figs 1 and 2A ) . Based on these results , we reasoned that replication of the low and high pathogenic recombinant strains would be similar in the highly permissive Vero cells , but that the low pathogenic recombinants would replicate less well in the presumably less permissive mouse embryonic fibroblast ( MEF ) cells . We selected 14 high pathogenic and 14 low pathogenic recombinants for testing and determined titers at 18 hours post-infection at an MOI of 1 . The results show that the 14 high pathogenic and 14 low pathogenic strains burst sizes were similar in Vero cells ( Fig 2C and 2D ) , but there were several outliers . However in MEF cells , most of the low pathogenic strain had burst sizes close to zero ( Fig 2B and 2C ) . It should be noted that the high pathogenic strains titers were also reduced in MEF cells compared to Vero cells ( Fig 2B ) , however the burst sizes were generally higher . To further examine the differences of one step growth curves in Vero versus MEF cells , we generated scatterplots of mean peak disease scores versus burst size for blepharitis and stromal keratitis . Fig 2E shows a weak correlation between blepharitis MPDS and MEF burst size ( R2 = 0 . 25 ) , while in Vero cells there was no correlation ( R2 = 0 . 00; Fig 2F ) . There was also a weak correlation between stromal keratitis MPDS versus MEF burst size ( R2 = 0 . 30; Fig 2G ) , while no correlation was observed in Vero cells ( R2 = 0 . 01; Fig 2H ) . These results are similar to the in vivo titer results and suggest that the ability to replicate in the host is an important driver of virulence , although it is not the only factor since the correlative R2 values were relatively weak . Three machine learning methods , Random Forest , Lasso , and Ridge regression , were evaluated to determine which provided the highest predictive accuracy when mapping OD4-CJ994 recombinant genotypes to ocular phenotypes . The recombinant genotypes were represented using 491 haplotype blocks that were derived from a multiple sequence alignment of the parental and recombinant genomes . We used leave-one-out cross validation to assess the predictive accuracy of the three methods for the three phenotypes . The accuracies of the cross-validated predictions for blepharitis and stromal keratitis using the three learning methods are shown as red points in Fig 3A . To determine whether these R2 values represent statistically significant predictability , we used a Monte Carlo methodology in which the cross-validation procedure was repeated 1 , 000 times with the measured phenotypes randomly shuffled and then reassigned to the haplotype feature vectors . The box plots in Fig 3A show the resulting R2 values for models learned from the randomized genotype-phenotype data sets . These results indicate that the learned models have statistically significant predictive power for the blepharitis and stromal keratitis phenotypes . Since the R2 values for ocular disease phenotypes were highest using Ridge regression , we use these models for the subsequent QTL based virulence association analysis ( vQTLmap ) . Fig 3B shows Manhattan plots depicting the association between the 491 loci ( haplotype blocks; S1 Table ) and the two phenotypes as determined by the Ridge regression models . The horizontal axis represents coordinates in the HSV-1 strain 17 reference genome , and the vertical axis represents the change in the mean squared error ( MSE ) of predicted phenotypes when the values for a given locus are permuted . The horizontal blue lines indicate the thresholds used for the associations to be considered significant . Following the vQTLmap analysis , phenotypically important features from the learned models were extracted , with a full list found in S2 Table . The ocular phenotype with the highest number of considered associations was blepharitis followed by stromal keratitis ( S2 Table ) . A few of the detected associations may be false positives as they occur in poor quality sequence regions ( e . g . 126 , 825 IRS , 6 , 456 TRL , ICP0 S305G ) . Because of the unreliability of the sequence in the indicated regions , these features were not considered further . A collection of highly scoring , notable associations are listed in Table 2 . A few notable intergenic and promoter regions were detected , including intergenic regions between UL21 and UL22 ( blepharitis and stromal keratitis ) , and UL3 and UL4 ( blepharitis ) . Several features mapped to either 5’ or 3’ UTR regions of genes , including UL3 , US1 , UL30 , and US3 . Highly scoring features encoding synonymous variations were found in the UL25 ( blepharitis ) , UL40 ( blepharitis and stromal keratitis ) , and US2 ( blepharitis , stromal keratitis ) genes . Notable associations encoding amino acid variations were found ( where the OD4 SNP:amino acid postion:CJ994 SNP ) in the ICP4 ( M454L; blepharitis and stromal keratitis ) , US3 ( T52P; blepharitis and stromal keratitis ) , gG ( K96E , V113F , G117E , V119D , P131S , G133D , S152I , Q163R; blepharitis and stromal keratitis ) , and VHS ( L374R , N384S , fs*475P; stromal keratitis ) proteins . We next mapped the highly scoring vQTLmap identified nonsynonymous SNPs to their corresponding proteins to determine if any of the detected variations occur in known functional sites or motifs . First , the vQTLmap identified genes were mapped to the HSV-1 genome ( Fig 4A ) . Fig 4B shows the mapped vQTLmap features . Several associations mapped to known functional motifs , such as the VHS ( UL41 ) identified SNPs L374R and N384S , which map to the tristetraprolin binding region . In ICP4 ( RS1 ) , the M454L feature maps to the DNA binding II domain , and the I325T association in ICP27 ( UL54 ) maps to the RNA binding KH1 domain . There were several detected features which are consistent with possible serine/threonine phosphorylation sites in known phosphorylated proteins; ICP27 ( I325T ) , ICP22 ( A102T , S103A and A215T ) , US3 ( T52P and A153T ) . Phenotypically meaningful variations in the gK ( S305L ) and UL56 ( G213W ) proteins mapped to transmembrane domains . The UL24 and ICP8 detected associations did not map to any known functional domains . Ocular disease trends of the identified vQTLmap associations were determined by setting the OD4 variation as the baseline . In Fig 4B the ocular disease phenotype trends for nine of the proteins identified in vQTLmap are shown . The average of total MPDS scores associated with the OD4 and CJ994 parental SNPs , along with Mann-Whitney rank sum test p-values are also shown ( Fig 4B; S4 Table ) . Decreasing disease trends associated with CJ994 SNPs compared to the OD4 baseline SNPs were observed in UL24 , ICP4 , ICP22 , US3 , and gG . All of the associations that correlated with a downward trend in virulence were statistically significant , with the exception of UL24 which was not considered for further analysis . The vQTLmap identified features in ICP8 , VHS , gK , ICP27 , and UL56 were associated with an increase in virulence compared to the strain OD4 baseline SNPs , and all were statistically significant . To aid the interpretation of the vQTLmap data , a protein-protein interaction network was constructed ( Fig 5; S3 Table ) . All of the identified major virulence proteins had multiple protein-protein interactions . Several of the major virulence proteins detected in this study have been shown to interact with each other; including ICP4 and ICP8 , ICP8 and ICP27 , ICP27 and VHS , ICP22 and US3 . Also , with the exception of gG , the remaining virulence genes were connected through secondary or tertiary interactions , e . g . US3-VP13/14-ICP27 , ICP4-ICP8-ICP27 , and ICP4-CLOCK-ICP22 . Importantly the ICP27 , US3 , and gG proteins directly interact with host immune system proteins . Glycoprotein G directly interacts with several chemokines , ICP27 binds IκBα ( NFKBIA ) , and US3 hyperphosphorylates both IR3 and p65/RELA . The significant virulence determinants were further categorized into three functions groups; transcription , virion assembly/egress , and immunomodulation ( Table 3 ) . Several of the proteins reside in overlapping functional groups , for example ICP22 plays a function in both transcription and virion assembly/egress , and ICP27 plays a role in transcription as well immunomodulation . Additionally , ICP8 was the only β class gene that was identified in the virulence determinant network .
We have previously shown that 17 HSV-1 OD4-CJ994 recombinants exhibit a wide range of ocular disease phenotypes in mice [30] . It is also notable that we were able to generate virulent recombinants from the two low virulence parental strains , suggesting that different combinations of parental genes are involved in determining virulence . Following ocular virulence characterization in our mouse ocular model , the in vivo derived strains were statistically more virulent and had significantly higher mean peak tear film titers than the in vitro derived strains . We hypothesize that selective pressure in the mouse cornea results in recombinants that are better adapted for replication in vivo , unlike the in vitro derived recombinants which were subjected to different selection pressures . The in vitro recombinants were generated in Vero cells which are highly permissive , do not synthesize interferon , and may have other innate defects that contribute to their permissiveness ( Fig 2C and 2D ) . If we had generated recombinants in MEF cells , we might have selected for different traits . Likewise , the linear regression scatter plots and growth studies of high pathogenic and low pathogenic recombinants in mouse embryonic fibroblast ( MEF ) cells ( Fig 2 ) suggest that virulence is a function of ability to replicate and that replication may be an important driver of virulence . It should be noted that the R2 values for the linear regression analyses of mean peak titer versus phenotypic disease were low , with several low pathogenic strains replicating to high titers ( Figs 1 and 2 ) , suggesting that additional factors beyond replication efficiency contribute to virulence . Finding a correlation between virulence and replication in HSV-1 is not unexpected , as similar phenomena have been observed in poliovirus 1 [46] , vesicular stomatitis virus [47] , and Marek’s disease virus , another alphaherpesvirus [48] . Based on this finding , determining the viral replication potential of HSV-1 strains in MEF cells or another restrictive cell line may be a rapid method of estimating HSV-1 virulence . Traditionally , studies on the genetics of virulence have relied on isolating and characterizing a naturally occurring viral strain with altered virulence properties , genetically engineering either deletions or point mutations , or using marker transfer methods to exchange genes between strains . A previous study of ours used marker transfer/infection to exchange different combinations of genes from a moderately virulent strain ( CJ394 ) into the attenuated HSV-1 strain OD4 , and found that virulence phenotypes in mice was dependent on the combination of genes that were transferred [32] , suggesting epistatic interactions play a role in virulence . We found that two mutations in the ICP22 protein ( US1 ) needed to be co-inherited for the virulence phenotype supporting a role for epistasis in determining virulence [32] . Additionally , the study identified several virulence determinants including UL9 , UL33 , UL37 , UL41 ( VHS ) , UL42 and US1 ( ICP22 ) ( Fig 6a ) . When the current vQTLmap study which is based on OD4:CJ994 recombinants and the previous study ( OD4:CJ394 ) are compared , only the UL41 and US1 genes overlapped as virulence determinants ( Fig 6 ) . This lack of virulence gene overlap between the two HSV-1 strain combinations suggests that complex epistatic interactions are involved in determining ocular virulence phenotypes . While the majority of downstream analysis of the vQTLmap features focused on amino acid encoding SNPs , intergenic , 5’ and 3’ gene UTR , and promoter virulence associations were also identified . The only intergenic feature identified was an INDEL located between the UL21 and UL22 genes . There are no annotated regulatory elements identified in this region , and we are uncertain if the phenotypic importance of the INDEL is due to an uncharacterized regulatory element or the influence of SNPs in the surrounding genes . Features in the 5’ and 3’ UTR regions of UL3 , UL30 , US1 , US2 , and US3 were also detected by vQTLmap , and as with the intergenic region described above , we are not certain if the features contain unknown regulatory sequences or are influenced by SNPs in the surrounding genes . Features mapping to the UL56 , ICP4 , and IE 4/5 promoters were also detected . Examination of these promoter regions did not reveal a gain or loss of any notable transcription factor binding sites , so the importance of these regions as virulence determinants remains unclear . The vQTLmap analysis identified several novel amino acid encoding feature SNPs , including ICP8 , VHS , gK , ICP27 , UL56 , ICP4 , US1 , US3 , and gG ( Table 2 , Fig 4 ) . When these genes were examined in the protein: protein interaction network ( Fig 5 ) , we were able to classify the genes into three functional clusters ( Table 3 ) ; transcription , virion assembly-egress , and immunomodulation . The ICP8 , VHS , ICP27 , ICP4 , and ICP22 proteins are associated with various components of viral transcription [49–51] . While we are uncertain as to exactly how the detected virulence associated SNPs in each of these proteins could be affecting transcription , there are several SNPs warranting closer inspection . In UL41-VHS , Two of the variations ( L374R/N384S ) map to the tristetraprolin ( TPP ) binding domain of VHS . Tristetraprolin has been shown to recruit VHS to AU rich elements in stress mRNAs for subsequent cleavage [52] , and it is possible that the vQTLmap variations may negatively affect the recruitment of VHS by TPP . Additionally , a frameshift at position 475 associated with a reduction in virulence extends the VHS protein by 47 amino acids and may adversely alter VHS functionality . The ICP27 protein contained one SNP ( I325T ) . ICP27 appears to mediate VHS degradation of mRNA [53 , 54] and is a component of the HSV-1 transcriptome complex [51] . The vQTLmap feature ( I325T ) mapped to the KH1 RNA binding domain of ICP27 . ELM motif prediction found that the T325 residue is part a putative GSK3 phosphorylation motif , and it should be noted that the loss of the threonine is associated with reduction in virulence . Regulation of KH domain binding to mRNA has been shown to be regulated by phosphorylation [55] , and it is possible that phosphorylation of T325 could be playing a similar function . In ICP4 , the M454L variation maps to a methionine residue in the DNA binding domain 2 of ICP4 which is highly conserved across alphaherpesvirinae [56] . We hypothesize that the leucine at position 454 is negatively affecting DNA binding , and thus reducing expression of viral late genes , as well regulatory binding to target promoters . Support for this hypothesis comes from mutational studies of the ICP4 DNA binding region residues 442–485 showing that several mutations in DNA binding domain II resulted in reduced DNA binding phenotypes [57] . Glycoprotein K ( gK ) , UL56 , US1 and US3 have been implicated in virion egress [58–63] . Notably , UL56 contains three SNPs , with one G213W occurring near the N-terminal putative transmembrane domain . Transmembrane domain analysis of the UL56 protein , predicts a reduction of transmembrane potential with a glycine at position 213 , as compared to the hydrophobic tryptophan residue , and may therefore affect membrane anchoring stability or the ability to interact with other membrane bound proteins . Similarly , the S305L SNP in gK maps to the C-terminal transmembrane domain , and may affect membrane anchoring . The immunomodulatory proteins VHS , ICP27 , US3 and gG appear to be converging on adaptive immunity . The US3 serine/threonine kinase contained five separate vQTLmap features for the blepharitis and stromal keratitis phenotypes , but only two , T52P and A153T , encoded a nonsynonymous variation ( Table 2; S2 Table ) . US3 is a multifunctional kinase and neurovirulence determinant [64 , 65] that has immunomodulatory activity by hyperphosphorylating IRF3 and p65/RELA [66 , 67] , inhibiting T cell signaling through confining the host T-cell activator component LAT [68] , as well as interacting with PDCD4 to block apoptosis [69] . The function of the vQTLmap identified T52P and A153T variations is unclear as they occur outside of the US3 kinase domain . The T52P and A153T variations instead map to a putative disordered region , and may affect the ability of US3 to bind to interaction partners . The vQTLmap analysis identified a 202 bp feature containing the K96E/V113F/G117E/V119D/P131S/G133D/S152I/Q163R variations which mapped to gG’s extracellular domain ( Fig 4 ) . A second lower scoring 575 bp feature also mapped to gG and included the P165T/V209G/P237S variations . The V209G variation mapped to gG’s transmembrane region and the P237S variation mapped to the cytoplasmic tail . Recently , glycoprotein G has been shown to bind the glycosaminoglycan-binding domain of several chemokines including CCL18 , CCL28 , CXCL9 , and CXCL14 [70] . The significance of how the vQTLmap amino acid variations in gG may affect virulence is uncertain , however , it is not unreasonable to hypothesize that at least one of detected variations may affect chemokine binding efficiency and affect innate or adaptive immune responses . While the significance of the SNPs in VHS , ICP27 , and US3 are not yet clear , these three proteins affect the interferon response . VHS inhibits Stat-1 phosphorylation and prevents formation of the Stat-1/2-p48 complex [71 , 72] , reducing interferon levels . ICP27 inhibits IRF-3 activation , blocking interferon expression [73] . NF-κβ activity is reduced by both ICP27 and US3 . The ICP27 protein physically interacts and stabilizes IκBα , lowering NF-κβ activity , and US3 hyperphosphorylates p65/RELA reducing NF-κβ activation [66 , 74] . US3 also hyperphosphorylates IRF3 , which in turn blocks IRF3 nuclear translocation and IFN-β activation . In summary this is the first report using QTL based analysis of HSV-1 for virulence gene discovery . The analysis successfully detected previous and unidentified virulence genes and novel associated SNPs . This data lays the groundwork for future virulence studies and methods that may also be applied to other viruses .
|
In addition to causing recurrent labial lesions , herpes simplex virus type 1 ( HSV-1 ) is also the primary source of infectious blindness in the United States . Animal studies have shown that the severity of infection is influenced by several factors , including viral strain . Conventional studies investigating the genetics of viral virulence have focused on characterizing a naturally occurring strain , and engineering mutations into viruses . The purpose of this study was to develop a quantitative trait locus ( QTL ) computational analysis of HSV-1 genome to identify ocular virulence determinants and associated viral SNPs . Notably , phenotypically meaningful variations were detected in the UL24 , UL29 ( ICP8 ) , UL41 ( VHS ) , UL53 ( gK ) , UL54 ( ICP27 ) , UL56 , ICP4 , US1 ( ICP22 ) , US3 and gG genes . Several genes previously implicated in virulence were identified , validating this approach , while other genes were novel . This is the first time a QTL based approach has been applied to a herpesvirus and it will also be valuable in future virulence , epistasis , and protein-protein interaction studies .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"sequencing",
"techniques",
"herpes",
"simplex",
"virus",
"vero",
"cells",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"keratitis",
"pathogens",
"split-decomposition",
"method",
"biological",
"cultures",
"population",
"genetics",
"microbiology",
"ocular",
"anatomy",
"viruses",
"multiple",
"alignment",
"calculation",
"dna",
"viruses",
"molecular",
"biology",
"techniques",
"population",
"biology",
"herpesviruses",
"herpes",
"simplex",
"virus-1",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"sequence",
"alignment",
"medical",
"microbiology",
"microbial",
"pathogens",
"cell",
"lines",
"molecular",
"biology",
"eye",
"infections",
"haplotypes",
"anatomy",
"computational",
"techniques",
"virulence",
"factors",
"cornea",
"viral",
"pathogens",
"ophthalmology",
"genetics",
"biology",
"and",
"life",
"sciences",
"ocular",
"system",
"evolutionary",
"biology",
"organisms"
] |
2016
|
Quantitative Trait Locus Based Virulence Determinant Mapping of the HSV-1 Genome in Murine Ocular Infection: Genes Involved in Viral Regulatory and Innate Immune Networks Contribute to Virulence
|
Bacteria were thought to be devoid of tyrosine-phosphorylating enzymes . However , several tyrosine kinases without similarity to their eukaryotic counterparts have recently been identified in bacteria . They are involved in many physiological processes , but their accurate functions remain poorly understood due to slow progress in their structural characterization . They have been best characterized as copolymerases involved in the synthesis and export of extracellular polysaccharides . These compounds play critical roles in the virulence of pathogenic bacteria , and bacterial tyrosine kinases can thus be considered as potential therapeutic targets . Here , we present the crystal structures of the phosphorylated and unphosphorylated states of the tyrosine kinase CapB from the human pathogen Staphylococcus aureus together with the activator domain of its cognate transmembrane modulator CapA . This first high-resolution structure of a bacterial tyrosine kinase reveals a 230-kDa ring-shaped octamer that dissociates upon intermolecular autophosphorylation . These observations provide a molecular basis for the regulation mechanism of the bacterial tyrosine kinases and give insights into their copolymerase function .
Protein phosphorylation–dephosphorylation represents one of the most powerful and versatile mechanisms of molecular regulation in living organisms . For many years , however , protein phosphorylation–dephosphorylation was considered to be exclusive to eukaryotes . It was only after a long period of controversy that the existence of this modification was documented in bacteria ( for a review , see [1] ) . Early studies essentially focused on the characterization of the “two-component system” [2] and “phosphotransferase PTS system” [3] , the well-known hallmarks of bacterial signalling and regulation in which proteins are phosphorylated on histidines and aspartic acids . Then , thanks in large part to genomics , the widespread presence of genes encoding eukaryotic-like serine/threonine kinases [4] and phosphatases has also turned out to be indisputable in bacteria [5] . In addition , high-accuracy mass spectrometry experiments have recently allowed the characterization of more than 100 serine , threonine , and tyrosine phosphorylation sites in two model bacteria [6 , 7] . Besides , some bacterial members of the large family of P-loop containing proteins [8 , 9] characterized by the Walker A nucleotide binding motif [10] were found to carry a protein kinase activity [11] . The first structurally [12] and functionally [13] characterized member of this new family of P-loop containing protein kinases was a serine kinase , the bifunctional HPr kinase/phosphorylase involved in a signalling pathway regulating the use of carbon sources by bacteria [14] . Progress on tyrosine phosphorylation in bacteria was slower , and it was only in 1997 that the first gene encoding a bacterial tyrosine kinase was characterized [15] . This enzyme is structurally and functionally unrelated to its eukaryotic counterparts . Like the HPr kinase/phosphorylase , it belongs to the family of P-loop containing protein kinases . This particular type of tyrosine kinase has been identified in numerous bacteria [16] , thus defining a bacterial idiosyncratic family of bacterial tyrosine kinases ( BY-kinases ) [17] . In proteobacteria and actinobacteria , BY-kinases are encoded as a single polypeptide , whereas in Firmicutes , they are found in the form of two interacting proteins . The periplasmic N-terminal and the cytoplasmic C-terminal domains of BY-kinases from proteobacteria and actinobacteria are homologous to the membrane adaptor and the cytoplasmic BY-kinase from Firmicutes , respectively ( Figure 1A ) . All BY-kinases that have been examined undergo autophosphorylation on a C-terminal tyrosine cluster , but also phosphorylate other proteins . Among the first identified endogenous protein substrates of BY-kinases were proteins involved in polysaccharide production [18–20] , but also RNA polymerase sigma factors [21] and single-stranded DNA binding proteins [22] . Therefore , BY-kinases are implicated in many other important physiological processes , including stress response , DNA metabolism , antibiotic resistance , control of the bacterial cell cycle , and pathogenicity [17 , 23] . The mechanism by which BY-kinases control extracellular polysaccharide biosynthesis is the best documented . Since 2000 , an increasing number of publications have analyzed this process , and tyrosine phosphorylation has turned out to be a key feature of capsule formation [24] . BY-kinases have been characterized as polysaccharide copolymerases ( PCP ) belonging to multiprotein transmembrane machineries involved in synthesis and/or export of a large number of extracellular polysaccharides [25] . However , the accurate function of their phosphorylation remains unclear even though it has been shown to influence both the length and the amount of the produced polymer [26–28] , thus modifying the physicochemical properties of the capsule [29] . In bacterial human pathogens such as Staphylococcus aureus , capsule promotes virulence in animal models of infection [30 , 31] . The S . aureus capsule has been shown to be involved in protection against phagocytosis [32] and in modulation of the host immune response [33] . Therefore , structural analysis of this new type of enzyme would not only contribute to depict their function in extracellular polysaccharide synthesis , but could also be used as a basis for a structure-based drug design project targeting microbial pathogens . In this work , we focused on S . aureus serotype 5 , a Gram-positive pathogen responsible for a diverse spectrum of animal and human diseases , and predominating in clinical isolates [31 , 34] . S . aureus whole-genome analysis [35] revealed two couples of cytoplasmic BY-kinase and associated transmembrane adaptor: Cap5A1/Cap5B1 , encoded by genes located in the cap operon controlling capsule biosynthesis , and the highly similar Cap5A2/Cap5B2 couple , the genes of which are located elsewhere on the genome [36] . Surprisingly , it has been demonstrated that the Cap5B2 tyrosine kinase activity is more efficiently activated by the transmembrane protein Cap5A1 than by the cognate Cap5A2 activator [36] . More precisely , the last 29 C-terminal and cytoplasmic residues of Cap5A1 ( or Cap5A2 ) are sufficient for stimulation of the kinase activity . Once activated , Cap5B2 trans-phosphorylates on its tyrosine cluster , but also phosphorylates Cap5O , an UDP-acetyl-mannosamine dehydrogenase involved in the production of a polysaccharidic capsule precursor [20] . Despite the 57% overall sequence identity with Cap5B2 and the high conservation of the tyrosine cluster , no kinase activity could be detected for Cap5B1 , either in the presence of Cap5A1 or of Cap5A2 [36] . Reproducing the Gram-negative organization of BY-kinases by direct linkage of the Cap5A1Ct fragment ( herein called CapACt ) to the N-terminal extremity of Cap5B2 ( herein called CapB ) allowed the production of a fully active soluble protein called CapAB ( Figure 1B ) . We performed a high-resolution structural analysis of this chimeric protein and of its inactive P-loop mutant CapAB ( K55M ) . The respective 1 . 8 Å and 2 . 6 Å resolution structures provide the first atomic view of a tyrosine kinase from bacterial origin . The regulatory autophosphorylation mechanism suggested by this structural analysis was further investigated by mutational and biochemical approaches . We finally propose a molecular model for the regulation of extracellular polysaccharide synthesis .
The structure of the S . aureus CapAB chimeric protein was determined at 1 . 8 Å resolution ( Table 1 ) . Evolutionary classification of the P-loop proteins suggested that the BY-kinase family is closely related to the Mrp-MinD subfamily P-loop ATPases [37] . A CapA/CapB mutational analysis based on the structure of the MinD cell division regulator confirmed this similarity [36] . Thus , despite the low sequence identity ( 17% ) between S . aureus Cap5B2 and the Pyrococcus horikoshii MinD protein [38] , the later was successfully used as the starting model in the molecular replacement procedure that allowed us to solve the first BY-kinase structure . The refined structure of the CapAB chimeric protein includes a continuous polypeptide corresponding to residues 197a to 222a of Cap5A1 linked to residues 1b to 215b of Cap5B2 . The N-terminal extremity ( 6His-tag and Cap5A1 residues 194a–196a ) and the C-terminal tyrosine cluster ( Cap5B2 residues 215b–230b ) are disordered . The asymmetric unit contains two molecules with a small contact surface area of about 600 Å2 , characteristic of packing interactions [39] . The crystal form of the truncated cytoplasmic domain of CapAB is thus a monomer , as observed in solution by size-exclusion chromatography ( unpublished data ) . The CapB kinase core possesses a P-loop type α/β mononucleotide binding fold ( Figure 2A ) . A central seven-stranded β-sheet with the strand order 3425167 is flanked on one side by four ( α1–α4 ) and on the other by six ( α5–α10 ) α-helices . The distal strand β3 ( residues 111b–113b ) of the β-sheet is antiparallel to the others . The loop connecting strand β1 to helix α3 is the phosphate-binding loop ( P-loop ) corresponding to a divergent Walker A motif ( E49APGAGKS56 ) . The CapACt fragment ( residues 194a–222a ) provides an additional strand called βA ( residues 214a–219a ) interacting with strand β7 of CapB and thus completing the central β-sheet of the protein . CapACt also contains an additional α-helix called αA ( residues 202a–211a ) interacting with helix α10 ( residues 187b–200b ) of CapB . The total surface contact area between CapACt and CapB covers about 3 , 000 Å2 and is highly hydrophobic ( Figure 2B ) , explaining why CapB is poorly soluble in the absence of CapACt ( unpublished data ) . Structural comparison with the Protein Data Bank using the SSM service at the European Bioinformatics Institute [40] confirmed that the closest structural relative of the chimerical CapAB is the bacterial cell division regulator MinD . A Z-score of 9 . 2 with a root mean square deviation of 1 . 94 Å over 160 aligned Cα atoms was obtained with the P . horikoshii MinD structure [38] used in the molecular replacement procedure . Comparison of the two structures is presented in Figure S1 . The active sites of both proteins are highly similar , and the nucleotide-binding mode is conserved . In particular , the base is in sandwich interactions between the conserved arginine and a hydrophobic residue from MinD helix α9 replacing CapACt F221a . However , whereas MinD displays an ATPase activity [41] , we verified that the protein does not autophosphorylate and is unable to phosphorylate UgD , the substrate of the Escherichia coli BY-kinase , Wzc ( unpublished data ) . The active site of the protein contains ADP-Mg , most probably resulting from the hydrolysis of the 10 mM ATP-Mg contained in the crystallization solution . Typical interactions are observed between the phosphate groups of ADP and the P-loop . The associated magnesium ion is fully chelated by the side chain of S56b , the β-phosphate , and four water molecules . The latter are stabilized by an interaction network involving three conserved aspartate residues , i . e . , D157b from the Walker B motif and D77b , D79b from the conserved DxD motif located 20 residues downstream from the Walker A motif . The O4 oxygen atom of the ribose interacts with CapB residue R212b , whereas the N6 and N7 nitrogen atoms of the adenine ring specifically interact with the side chain carboxyamide of residue N211b . The adenine ring is also involved in a classical hydrophobic sandwich interaction with the side chains of CapB R212b and CapA F221a ( Figure 2C ) . The stimulatory effect of CapACt on the kinase activity of CapB has been shown to be correlated with an increased affinity for ATP [36] . The ( F221A ) mutation was introduced in the CapACt segment of the chimeric CapAB protein in order to verify the essential role of residue F221a suggested by the structure . A strongly decreased autokinase activity was observed with the CapAB ( F221A ) mutant compared to the wild-type CapAB protein ( Figure S2 ) . Preliminary fluorescence experiments using labelled nucleotide analogs further confirmed that this loss of activity is correlated with a reduced affinity of the CapAB ( F221A ) mutant for the nucleotide ( unpublished data ) . The absence of electron density for the CapB tyrosine cluster raised the question of its phosphorylation state . Analysis of the CapAB protein sample from the crystallisation experiments using nondenaturing gel electrophoresis revealed four bands of about equivalent intensities ( Figure 3A ) . These four bands were converted in a single , slowly migrating band when the CapAB sample was treated with the cognate S . aureus tyrosine phosphatase CapC2 . The inactive CapAB ( K55M ) mutant , affected at the catalytic K55b residue from the conserved Walker A motif [36] , also displays a single band ( Figure 3A ) . These results strongly suggest that the crystallized CapAB sample is heterogeneously phosphorylated . This hypothesis was further investigated by analyzing each band of the gel using mass spectrometry . This analysis confirmed that the upper band observed with the inactive mutant or after dephosphorylation of CapAB by CapC indeed corresponds to the unphosphorylated protein . The four other bands correspond to one , two , three , and four phosphorylations from top to bottom , respectively ( Figure 3B ) . Tandem mass spectrometry analysis and sequencing of each phosphopeptide allowed us to calculate the percentage of phosphorylation for each tyrosine ( unpublished data ) . Any combination of phosphorylated tyrosines was observed in each band . For example , the distribution of population for the monophosphorylated peptide was evaluated as 12% Y225 , 28% Y224 , 19% Y222 , 35% Y221 , and 6% nonphosphorylated . In parallel , 14 proteins containing various combinations of Tyr to Phe or Tyr to Glu exchanges ( Glu was expected to mimic a phosphorylation ) have been engineered to further assess the influence of each tyrosine on the autokinase activity of CapAB . This mutational analysis revealed that each of the four tyrosines is phosphorylated independently of the F or E mutation applied to the three other tyrosines ( Figure 3C ) . These results confirm the heterogeneous autophosphorylation process of CapAB , and indicate that phosphorylation occurs without any preferred order . Thus , the crystallized protein was heterogeneously phosphorylated , and the absence of electron density corresponding to the C-terminal extremity suggests that the phosphorylated tyrosine cluster is highly flexible . The structure of the inactive P-loop CapAB ( K55M ) mutant was determined to 2 . 6Å resolution ( Table 1 ) . It presents a subunit fold highly similar to that of the CapAB wild-type protein with an rmsd of 0 . 67 Å over 241 aligned residues . The major difference concerns the quaternary structure of this unphosphorylated form of the protein that associates to a ring-shaped octamer ( Figures 4A ) . The total surface contact area of about 2 , 000 Å between two neighbouring subunits is characteristic of biological interactions [39] . Residues 216b–228b of the tyrosine cluster that were disordered in the phosphorylated wild-type structure form a long loop with Y225b side chain fitting in the active site of the neighbouring CapB molecule ( Figure 4B ) . Despite the absence of a nucleotide in the crystallization solution , ADP-Mg is observed in the P-loop of the CapAB ( K55M ) mutant protein . This is in agreement with a previous study showing that in P-loop proteins , this mutation inhibits the phosphate transfer but increases the affinity of the protein for the nucleotide [42] . The bound ADP molecule thus originates from the E . coli cell extract and remains bound to the protein during the purification process . The C-terminal cluster and helix α2 of one subunit form 44% and 50% , respectively , of the contact area facing the surface loops β2-α4 , β4-α7 , and β5-α9 , as well as helix α10 and the P-loop of the neighbour subunit . With the exception of a specific interaction between the αA residue E203a and the helix α10 residue K193b from an adjacent subunit , CapACt is not directly involved in octamer contacts ( Figure 4B ) . The side chain of Y225b is bound in the active site of the neighbour subunit via hydrophobic sandwich interactions with the side chain of K82b and the two consecutive proline residues P159b–P160b forming an extended hhhhDTPP Walker B motif characteristic of the BY-kinase subfamily of P-loop ATPases ( Figure S3 ) . The hydroxyl group of Y225b is pointing toward the 4 . 8 Å distant β-phosphate of the bound ADP molecule ( Figure 4B ) . Superimposition with the Pyrococcus furiosus MinD/AMP-PCP complex [41] showed that this Y225b hydroxyl group is 2 . 84 Å from the γ-phosphate to be transferred ( unpublished data ) . The catalytic residue D79b from the conserved DxD motif is positioned to deprotonate the Y225b hydroxyl , a prerequisite for its phosphorylation ( Figure 4B ) .
The intermolecular autophosphorylation process suggested by the CapAB ( K55bM ) octameric structure is in agreement with all BY-kinases phosphorylation data published so far , even those originally thought to reflect an intramolecular mechanism [19] . However , the exact autophosphorylation process remains unclear . Although the structure suggests that Y225b is preferentially phosphorylated , our mass spectrometry and site-directed mutagenesis experiments revealed a heterogeneous phosphorylation pattern of the four tyrosines without any preferred order . The tyrosine cluster forms a long surface loop with a putative high intrinsic flexibility , suggesting that it could adopt different conformations . After intermolecular autophosphorylation , the cluster most probably exits the neighbouring active site , inducing dissociation of the kinase domains , as observed in the monomeric structure of the phosphorylated CapAB protein . The heterogeneous phosphorylation pattern however suggests that the affinity between subunits with partially phosphorylated clusters is sufficient to allow reassociation and further phosphorylation of the cluster . Heterogeneous phosphorylation has also been observed in vivo with Wzc of E . coli [43] and CpsD of S . pneumoniae [44] . Whereas the core of the kinase domain is highly conserved among BY-kinases , the sequence and the length of the tyrosine cluster , as well as the number and the relative positions of the phosphorylatable tyrosines , are variable ( Figure S3 ) . This variability further supports the hypothesis of a biological nonspecific phosphorylation pattern . BY-kinases sequence comparison ( Figure S3 ) demonstrated that the CapB helix α2 residues E23b , R26b , and R29b , as well as residues E133 of helixα7 and R81b of loop β2-α4 , specifically involved in the octamer contacts are highly conserved among the whole family , except in CpsD from Streptococcus pneumoniae . The conservation of this interface ( Figure 4C ) suggests that the octamer is functionally important . However , simultaneous replacement of the four conserved interface residues of CapAB helix α2 with alanines did not significantly reduce the autokinase activity of the protein ( unpublished data ) , suggesting that these four residues are not essential for the intermolecular phosphorylation process . As confirmed by size-exclusion chromatography analysis of the CapAB ( K55M ) mutant ( unpublished data ) , only the monomeric form of the protein is observed in solution . This result suggests that the octamer is not stable in the absence of the transmembrane domain , except in the high protein concentrations used in crystallization . In solution , autophosphorylation probably occurs via nonspecific transient interactions between subunits . Thus , in our opinion , in vitro experiments performed with truncated soluble proteins poorly represent the in vivo 2-D situation occurring at the membrane surface , where the cytoplasmic kinase domains are maintained close together via specific interactions with the octameric transmembrane activator ( Figure 4D ) . Whereas the kinase and transmembrane activator form two distinct proteins in Firmicutes like S . aureus , they are associated in a single protein in proteobacteria as in the E . coli Wzc protein ( Figure 1 ) . We can thus speculate that in vivo , the octameric ring extends to the transmembrane regulatory domain . This hypothesis is supported by the electron microscopy ( EM ) low-resolution structures of Wzc solved in the absence [45] and presence [46] of the associated translocon Wza of the extracellular polysaccharide synthesis machinery of E . coli [47] . In both cases , Wzc displays a transmembrane ring-shaped structure with dimensions ( ≈50-Å inner diameter , ≈120-Å outer diameter ) similar to those observed in CapAB ( Figure 4A ) . The cytoplasmic Wzc kinase domains formed four spikes extruding from the transmembrane ring . The Wzc samples used in this EM experiments were phosphorylated . This EM structure is thus in agreement with our results , suggesting that only the nonphosphorylated cytoplasmic kinase domains associate into a ring-shaped octamer favouring intermolecular autophosphorylation . The tetrametric symmetry used in the EM analysis extends to the ring-shaped Wza component of the Wzc-Wza complex . However , a high-resolution crystal structure of Wza clearly demonstrated that the translocon is an octamer [48] . It is thus possible that Wzc , like CapAB , also forms an octameric ring allowing intermolecular autophosphorylation of the subunits before dissociation of the cytoplasmic kinase domains . The association–dissociation process of the cytoplasmic region of the ring is most probably cooperative . Both the phosphorylated and dephosphorylated forms of Wzc have been shown to influence the synthesis of polysaccharides [16] . However , a positive regulation of the polysaccharide synthesis by PCPs phosphorylation has been observed in certain bacterial strains [49 , 50] , whereas the opposite situation has been found in other strains in which the nonphosphorylated form of PCPs allows polysaccharide production [27 , 28 , 44] . These contradictory data support the hypothesis that polysaccharide synthesis requires both the phosphorylated and unphosphorylated forms of PCPs . Bacterial-encoded phosphotyrosine phosphatases catalyze the dephosphorylation of PCPs [51 , 52] . Thus , cycling between both forms of PCPs represents an attractive model [28 , 53] . Our data further suggest a structural-mechanical cycling process according to which phosphorylation/dephosphorylation of PCPs would induce cyclic dissociation–association of the cytoplasmic ring-shaped octamer ( Figure 5 ) . This conformational switch would most probably be transmitted to the transmembrane domain of PCPs that would be affected in its interaction with the other protein components of the polysaccharide assembly complex , such as the polysaccharide unit polymerase , the lipid-linked repeat unit flippase , or the lipid-sugar transferase [24] . However , one cannot exclude that the affinity of the machinery for the nascent polysaccharide [54] would also be affected . Cycling phosphorylation/dephosphorylation of PCPs would thus adjust continuously the polymerization and export steps of the polysaccharidic polymer . Given the strong conservation between PCPs , this may be a general model for the regulation of extracellular polysaccharide synthesis . Our model suggests that the juxtamembrane fragments preceding αA-βA in the CapA structure are acting as flexible linkers allowing the phosphorylated kinase domains to dissociate from each other while remaining associated with the octameric transmembrane modulator . This phosphorylated open conformation would be the active form for phosphorylation of the endogenous protein substrate . This hypothesis is supported by CapO phosphorylation experiments using the Glu substituted form of the CapAB tyrosine cluster mimicking the phosphorylated state of the protein . On the other hand , a deleted form of the protein missing the terminal tyrosine cluster is still able to phosphorylate CapO , thus demonstrating that the phosphorylated tyrosine cluster is not directly implicated in the interaction with CapO ( Figure S4 ) . The involvement of the BY kinases , not only in capsule production , but also in other important cellular processes implicated in the virulence of bacterial pathogens [17] , designates them as potential therapeutic targets . Controlling the development and the adaptation ability of bacteria , and more specifically of pathogens , is a major scientific challenge . Blocking these bacterial idiosyncratic tyrosine kinases represents , therefore , an original and attractive strategy with expected limited side effects on the host cells and potentially important biomedical applications .
The previously described plasmids pQE30-A1CtB2 and pQE30-A1CtB2K [36] were used to produce the His-tagged chimeric wild-type protein CapAB and the inactive mutant CapAB ( K55M ) , respectively . Wild-type or mutated chimeric CapAB proteins contain the last 29 C-terminal and cytoplasmic residues 194a–222a of Cap5A1 His-tagged at the N-terminus , whereas the C-terminus was fused to full-length wild-type or mutant Cap5B2 ( residues 1b–230b ) . Site-directed mutagenesis of CapAB was carried out by PCR amplification using specific primers ( Table S1 ) . The same strategy was applied to create CapAB mutants deleted of the C-terminal tyrosine cluster ( residues Y221b–S230b ) . The plasmid pQE30-CapO described in [20] was used to produce the S . aureus protein substrate CapO . The S . aureus phosphosphotyrosine phosphatase CapC2 was PCR-amplified using specific primers ( Table S1 ) and inserted into vector pET15b . Proteins were overproduced in E . coli , purified by IMAC and size-exclusion chromatography ( Superdex S75 ) , concentrated by centrifugal ultrafiltration , and stored at −20 °C . Prior loading on a nondenaturing 12% polyacrylamide gel , 45 μM CapAB samples were respectively incubated for 3 h at 37 °C alone , with 1 mM ATP/MgCl2 or with 8 μM recombinant His-tagged S . aureus CapC2 phosphatase and 1 mM MnCl2 [55] . After gel migration , the proteins were stained with Coomassie Blue . Stained protein bands from the native gel were excised and washed with 25 mM NH4CO3 . In-gel tryptic digestion was performed following the classical protocol [56] . The phosphopeptides were purified by nanoscale Fe ( III ) –Immobilized Metal Ion Affinity Chromatography ( IMAC ) according to the manufacturer's ( Millipore ) instructions . The tryptic peptides were loaded onto the column , and after extensive washing , phosphopeptides were eluted in 5 μl of 2% NH4OH . Mass spectra were recorded in positive reflectron mode with a matrix-assisted laser desorption/ionization time-of-flight MALDI-TOF/TOF 4800 mass spectrometer ( Applied Biosystem ) using a-cyano-4-hydroxycinnamic acid ( Sigma ) as a matrix . Close calibration was performed using angiotensin I ( [M+H+] , 1296 . 68 ) and adrenocorticotropic hormone 18–39 ( M+H+ , 2 , 465 . 20 m/z ) . Mass tolerance was set to 15 ppm . In vitro phosphorylation of 1 μg of different purified proteins was carried out in a reaction mixture containing 25 mM Tris-HCl ( pH 7 . 0 ) , 1 mM DTT , 5 mM MgCl2 , 1 mM EDTA , and 10 μM ATP with 200 μCi/ml [γ-32P]ATP . After 10 min incubation at 37 °C , the samples were analyzed by SDS-PAGE electrophoresis . After migration the gels were soaked in 16% TCA for 10 min at 90 °C and stained with Coomassie Blue . The radioactive proteins were visualized by autoradiography using direct film exposure . Crystallization conditions of the CapAB ( K55M ) mutant protein were determined at 18 °C by screening commercial crystallization kits using a nanodrop crystallization robot ( Cartesian ) . The first crystals were obtained in the Nextal PEG condition 17 . The crystals were improved using an additive screen ( Hampton Research ) . The crystal used for diffraction data measurements was obtained at 8 . 5 mg/ml of CapAB ( K55M ) in the presence of 10 mM MgCl2 after equilibration with 20% ( v/v ) PEG 1000 , 200 mM glycine , and 0 . 1 M Na-Hepes ( pH 7 . 5 ) . Crystals of CapAB were obtained by manual screening using the hanging drop method . They grew at 35 mg/ml CapAB in presence of 10 mM ATP-Mg after equilibration against a crystallization solution containing 23% ( v/v ) PEG 1000 and 0 . 1 M Tris-HCl ( pH 8 . 8 ) . Crystals were frozen in liquid nitrogen , after soaking in a cryoprotectant solution consisting in reservoir solution supplemented with increasing glycerol concentration up to 25% ( w/v ) . Diffraction data were collected at the European Synchrotron Radiation Facility ( ESRF ) in Grenoble , France , on the microfocus beamline ID23–2 and on beamline ID29 for CapAB and CapAB ( K55M ) , respectively . The CapAB crystal system is monoclinic , space group P1 , with two molecules per asymmetric unit . Data from two crystals were merged and scaled with the XDS package [57] . The structure was solved by molecular replacement with PHASER [58] using the P . horikoshii cell division regulator MinD [38] as the search model . The initial solution of CapAB was then rebuilt with ARP/wARP [59] . The CapAB ( K55M ) crystal system is I4 , with two molecules per asymmetric unit . Data were processed and scaled with the MOSFLM package [60] . The structure was solved by molecular replacement with PHASER [58] using the wild-type CapAB as the search model . Models were visualised and built using COOT [61] . The refinements were done using CNS [62] and REFMAC [63] , and monitored using the free R factor . The final models were evaluated using COOT validation tools and PROCHECK . A summary of the refinement and data statistics is given in Table 1 .
Coordinates and data of the CapAB and CapAB ( K55M ) structures have been deposited into the Protein Data Bank ( PDB; http://www . rcsb . org/pdb ) with ID codes 3BFV and 2VED , respectively . The PDB assession number for the MinD protein is 1ION , and for the MinD/AMP-PCP complex is 1G3R . Accession numbers from the National Center for Biotechnology Information ( NCBI; http://www . ncbi . nlm . nih . gov ) for proteins mentioned in this paper are Bacillus subtilis YveK ( CAB15442 ) , YveL ( CAB15441 ) , YwqC ( CAB15643 ) , and YwqD ( CAB15642 ) .
|
An idiosyncratic new class of bacterial enzymes , bacterial tyrosine-kinases ( BY-kinases ) , has been characterized . These enzymes , which are involved in an increasing number of physiological processes ranging from stress resistance to pathogenicity , share no sequence similarities with eukaryotic kinases , and their function remains largely unknown . They have nevertheless been described to undergo autophosphorylation on a C-terminal tyrosine cluster and to phosphorylate endogenous protein substrates . We describe here the first crystal structure of a bacterial tyrosine kinase , namely CapB from the pathogen Staphylococcus aureus , in complex with the cytoplasmic domain of the transmembrane stimulatory protein CapA . Our data explain the activation mechanism of CapB by CapA and allow us to propose a regulatory mechanism based on intermolecular autophosphorylation . These results also give new insights onto the phosphorylation of the endogenous substrate CapO , an enzyme involved in the synthesis of polysaccharide precursors . CapA and CapB , among others , are involved as copolymerases in the synthesis of extracellular polysaccharides that are thought to be potent virulence factors . Thus , these structural data provide the basis for designing specific inhibitors for these enzymes , which constitute an original and attractive target for the development of new drugs to treat infectious diseases .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"biochemistry",
"infectious",
"diseases",
"microbiology",
"biophysics"
] |
2008
|
Structural Basis for the Regulation Mechanism of the Tyrosine Kinase CapB from Staphylococcus aureus
|
Faithful transcription of DNA is constantly threatened by different endogenous and environmental genotoxic effects . Transcription coupled repair ( TCR ) has been described to stop transcription and quickly remove DNA lesions from the transcribed strand of active genes , permitting rapid resumption of blocked transcription . This repair mechanism has been well characterized in the past using individual target genes . Moreover , numerous efforts investigated the fate of blocked RNA polymerase II ( Pol II ) during DNA repair mechanisms and suggested that stopped Pol II complexes can either backtrack , be removed and degraded or bypass the lesions to allow TCR . We investigated the effect of a non-lethal dose of UVB on global DNA-bound Pol II distribution in human cells . We found that the used UVB dose did not induce Pol II degradation however surprisingly at about 93% of the promoters of all expressed genes Pol II occupancy was seriously reduced 2–4 hours following UVB irradiation . The presence of Pol II at these cleared promoters was restored 5–6 hours after irradiation , indicating that the negative regulation is very dynamic . We also identified a small set of genes ( including several p53 regulated genes ) , where the UVB-induced Pol II clearing did not operate . Interestingly , at promoters , where Pol II promoter clearance occurs , TFIIH , but not TBP , follows the behavior of Pol II , suggesting that at these genes upon UVB treatment TFIIH is sequestered for DNA repair by the TCR machinery . In agreement , in cells where the TCR factor , the Cockayne Syndrome B protein , was depleted UVB did not induce Pol II and TFIIH clearance at promoters . Thus , our study reveals a UVB induced negative regulatory mechanism that targets Pol II transcription initiation on the large majority of transcribed gene promoters , and a small subset of genes , where Pol II escapes this negative regulation .
Proper cell homeostasis and function requires expression of the DNA encoded information . Maintenance of genome integrity and accurate replication is crucial for correctly regulated gene expression . Transcription of thousands of coding and non-coding RNAs by the RNA polymerase II ( Pol II ) is a regulated multistep process that can be divided into five stages: pre-initiation , initiation , promoter clearance , elongation and termination . Based on numerous genome-wide studies analyzing Pol II transcription in several metazoan organisms using chromatin immunoprecipitation followed by deep sequencing ( ChIP-seq ) it is now clear that on different regions of an expressed gene , distinct types of Pol II occupancy signals can be detected . The “canonical” Pol II occupancy ChIP-seq profile on an average expressed gene displays Pol II molecules engaged in the major phases of transcription [1] , [2] , [3] , [4] , [5] , [6] , [7] and can be divided in three major regions: i ) the sharp and usually high peak centered about +50 bp downstream of the transcription start site ( TSS ) , representing Pol II molecules that have entered the pre-initiation complex ( PIC ) during transcription initiation/clearance and stopped at promoter proximal pausing position . Analyses of short transcribed RNA molecules showed that these arrested polymerases are predominantly in a transcriptionally engaged state [4] , [8] , [9]; ii ) the background-like low signals in the gene body ( GB ) , representing quickly elongating Pol II molecules; and iii ) the broad signal downstream from the 3′ end of the annotated genes ( EAGs ) representing Pol IIs that have finished transcribing the pre-mRNA and are slowly transcribing and approaching the termination site often 4–6 kb away from the 3′end of the gene [10] , [11] , [12] , [13] ( see also below ) . Damage or alterations of the DNA structure can threaten the progression of transcription . Indeed , Pol II driven transcription has been reported to be disturbed by “roadblocks” on the DNA template , which arises from both environmental and endogenous sources , such as special DNA sequences , non-canonical DNA structures , topological constrains and DNA lesions [14] . UV light is one of the most genotoxic environmental sources of transcription-blocking DNA damages . Different wavelengths of the UV light can generate a wide range of lesions in the DNA template . Based on its wavelength , UV light can be divided into UVA ( 315–400 nm ) , UVB ( 280–315 nm ) and UVC ( <280 nm ) . UVC has higher energy level than UVA and UVB due to its shorter wavelength; however , UVC radiation is not relevant from a public health standpoint as it is absorbed by the ozone layer . UV-related lesions in living organisms are induced mostly by UVA and UVB . The ionizing energy of UVB and UVC radiation is directly absorbed by the DNA and can cause cyclobutane pyrimidine dimers ( CPDs ) , pyrimidine 6-4 pyrimidone photoproducts ( 6-4PPs ) , which are the most persistent and predominant lesions [15] . Nucleotide excision repair ( NER ) is a mechanism that removes UV-induced lesions efficiently using two distinct pathways [16] , [17]: The first , called transcription coupled repair ( TCR ) , is mainly linked to Pol II transcription and is highly specific and efficient . TCR preferentially removes DNA lesions from the transcribed strand of active genes , allowing blocked transcription to resume . In transcribed regions UV-induced DNA lesions are known to block the elongating Pol II complex causing persistent transcriptional arrest . CPDs arrest transcription as they occupy the active site of Pol II . Moreover , DNA crosslinked proteins and interstrand crosslinks block transcription by steric hindrance before the lesion reaches the active site of Pol II . When the elongating polymerases arrest at a damage site , TCR is triggered and the corresponding lesions are repaired . One of the first steps of the TCR consist of the recognition of the blocked Pol II elongation complex by CSB ( Cockayne syndrome b protein , also called ERCC6 ) , which will trigger the further recruitment of NER factors essential to carry out the repair process . Amongst those factors is the general transcription factor TFIIH that plays a role both in repair and in Pol II transcription initiation [18] , [19] , [20] . Global genome repair ( GGR ) is the second pathway of NER that mainly acts on intergenic or non-coding regions of the genome and recognizes DNA lesions based on their base-pairing and helix-disrupting properties . GGR for some types of lesions ( such as UV-induced CPDs ) is less efficient than the repair carried out by the TCR machinery on the transcribed strand of active genes [21] , [22] . In vitro the half-life of an arrested Pol II at a CPD can be ∼20 hours , and it covers 10 nt upstream and 25 nt downstream of the CPD [23] , [24] . Therefore the arrested Pol II seems to create a roadblock for all the transcription on the given open reading frame , and may also block the access of the lesion by repair factors [25] , [26] . Such persistent Pol II blocks and subsequent transcriptional arrest can initiate checkpoint signaling , which can lead to cellular apoptosis [27] . Moreover , the stalled Pol II at a helix-distorting DNA damage can block the access of the nucleotide excision repair factors to the lesions [28] . It seems that cells have evolved several solutions to deal with the persistently stopped Pol II elongation complexes: i ) Pol II can bypass the lesions , but this process is slow and extremely inefficient [29] , ii ) CSB removes Pol II from the lesions through its Swi/Snf-like activity [19] , iii ) Pol II is backtracking allowing repair [30] . The restart of transcription depends on the cleavage and reposition the 3′ end of the RNA to the active center of Pol II , which can be mediated by the TFIIS elongation factor [31] . Persistent DNA damage can also result in the poly-ubiquitination and degradation of the largest subunit of Pol II [26] . This would make the lesion accessible for other repair processes and allow a new round of Pol II transcription . It has been suggested that the Pol II degradation pathway is activated only when the transcription activity of the blocked Pol II cannot be restored , and this pathway is an alternative to TC-NER . Our knowledge about Pol II transcription inhibition after UV irradiation is based on studies carried out on a few model genes and in experiments often using lethal UVC doses . Moreover , many studies have investigated the fate of Pol II elongation complexes during TCR , but very little information has been obtained on how TCR influences the whole Pol II transcription cycle during TCR . Therefore , the mechanism by which Pol II transcription is affected genome-wide upon sublethal doses of UV irradiation is not yet well understood . To investigate the fate of Pol II during TCR processes , we have investigated Pol II occupancy at a genome wide level following UVB treatment over time in human MCF7 cells . Our results show that on about 93% of the promoters of expressed genes Pol II occupancy is seriously reduced 2–4 hours following UVB irradiation , and that the presence of Pol II is restored to “normal” , or even sometimes higher , levels 5–6 hours after irradiation . We also identified a smaller set of genes , where the presence of Pol II at the promoter regions does not decrease , but rather increases at the promoters and also throughout the entire transcription units of these genes after UVB irradiation . Thus , our study reveals a global negative regulatory mechanism that targets RNA polymerase II transcription initiation on the large majority of transcribed genes following sublethal UV irradiation and a small subset of key regulatory genes , where Pol II escapes the negative regulation .
To investigate the general effect of UVB irradiation on transcription in human cells , we have set up to find irradiation conditions that do not induce apoptosis and under which cells can repair UV-lesions . To define a sublethal irradiation dose , we carried out a survival assay during which we tested the effect of 55 , 100 and 200 J/m2 of UVB irradiation on the DNA damage response proficient MCF7 human breast cancer cell line , containing wild type p53 ( Figure S1 , and see below ) . Upon 55 , 100 and 200 J/m2 irradiation 95% , 50% and 30% of the plated cells survived the treatment , respectively ( Figure S1A ) . Thus , for our further study we have chosen the 55 J/m2 dose of UVB . Importantly , 55 J/m2 UVB induces the main UV-DNA lesions as we detected the presence of CPDs with an anti-CPD antibody up to 24 hours after 55 J/m2 UVB irradiation ( Figure S1B ) . Moreover , by testing the induction of DNA-damage response markers , such as phospho-Chk1 and phospho-p53 , our experiments show that the 55 J/m2 UVB dose is enough to trigger the UV/DNA damage response of MCF7 cells ( Figure S1C ) . Thus , throughout the study we used this sublethal UVB dose to study transcription in MCF7 cells . It has been shown that UVC irradiation temporarily arrests Pol II transcription in human cells ( [32] , [33] and references therein ) . We investigated whether the above-defined 55 J/m2 UVB dose has the same effect on the global transcription program of MCF7 cells . To this end we assessed 5 fluorouridine ( 5FU ) incorporation in the cells by immunofluorescence as a marker of newly synthesized RNA and ongoing transcription by all three RNA polymerases . To this end 5FU was added to each sample 20 min before harvesting the cells ( Figure 1 ) . This assay revealed a reduction in the levels of nascent transcripts 1 hour following irradiation and from three hours to six hours a constant increase in the global transcription levels ( Fig . 1A and B ) . Surprisingly , at six hours following UVB irradiation nascent transcript levels increased about three times over the non-irradiated levels ( Fig . 1A and B ) . Such unexpectedly strong nascent RNA production overshoots have already been described in MCF7 cells after estradiol stimulation and in other systems , and when combined with time dependent RNA degradation analyses , was suggested to shape transient physiological responses with precise mRNA timing and amplitude [34] , [35] . Note however , that the used method labels all transcripts at a single cell level produced by the three RNA polymerases , including many non-coding transcripts , abortive transcripts produced during promoter clearance , and also short upstream antisense transcription start site associated RNAs ( TSSa-RNAs ) and others [36] . Nevertheless , our UVB irradiation experiment indicates that global nascent transcription is first inhibited by the used sublethal dose and then restarts again , suggesting that arrested polymerases may resume global transcription quickly as transcription-coupled repair is completed on the genome . As TCR has been mainly linked to Pol II transcription [18] we investigated the effect of UVB irradiation on genome-wide Pol II behavior . The great advantage of mapping Pol II occupancy across the genome is that it may directly reflect transcriptional activity , unlike the measurement of mRNA levels at steady state , which are the cumulative result of numerous co-transcriptional and post-transcriptional processes . To map Pol II occupancy changes genome-wide following UVB irradiation , we carried out chromatin immunoprecipitation ( ChIP ) coupled to high throughput sequencing ( seq ) analyses using an antibody that recognizes the N-terminus of the largest subunit of Pol II ( Rpb1 ) ( N-20 ) . MCF7 cells were either not irradiated , or treated with 55 J/m2 UVB and harvested 1 , 2 , 3 , 4 , 5 and 6 hours following irradiation . Cells were crosslinked with formaldehyde , ChIP was carried out and the recovered DNA fragments were deep sequenced . Specific Pol II bound sequence-reads were mapped to the human genome , and unique reads were considered for further analyses . For the comparative ChIP-seq analyses , all the seven datasets were normalized based on background tag densities calculated on intergenic regions ( see Materials and Methods ) . Note that our control non-irradiated data set was very comparable to that obtained in MCF7 cells by [13] . Next , Pol II density profiles on the coding regions of all refseq genes were calculated for all datasets by using seqMINER tool [37] . To this end , average Pol II tag density values on each ORF , starting −1 kb upstream and ending +4 kb downstream from every refseq gene were calculated and compared . The non-irradiated sample resulted in the canonical Pol II occupancy profile showing a high , sharp peak centered around +50 bp relative to the TSS , a low density profile on the gene body ( GB ) and a higher broad peak profile downstream from the EAG ( Figure 2A , [11] . Surprisingly , when we compared the six UVB treated samples to the non-treated control sample , by aligning the calculated mean Pol II profiles together on the same scale , we observed an unexpected genome-wide loss of Pol II signal around the TSS region of the refseq genes in the samples that were UVB treated and harvested 2 , 3 or 4 hours following the treatment ( Figure 2A and B ) . This observation suggests that there is a general signaling pathway that i ) stimulates paused Pol IIs to leave their promoter paused position , and/or ii ) inhibits the formation of new initiation complexes and/or iii ) removes Pol II from its promoter proximal pausing position somewhere between 2 to 4 hours after UVB irradiation . Interestingly , in the UVB-treated samples that were left for 5 and 6 hours to recover before ChIP , Pol II occupancy at the TSSs of all refseq genes increased to the initial levels , suggesting that Pol II transcription has been restarted after TCR has been completed ( Figure 2A and B ) . As in the above Pol II binding analyses , when analyzing all refseq genes at gene bodies , we did not observe an obvious GW increase of Pol II occupancy , we next re-analyzed global Pol II tag density changes in the GB regions of all transcribed genes . For this first we selected 4500 expressed genes , from a recently published RNA-seq dataset for MCF-7 cell line [38] ( for complete gene list see Table S2 ) . These analyses clearly indicated i ) a significant quick increase of Pol II tag density at all transcribed genes 1 hour following UVB irradiation; ii ) followed by a gradual decrease of Pol II binding in GBs that sink under control levels at 3–4 hours following UVB , and iii ) a novel global increase of Pol II signal that rises again above control levels at 5–6 hours following IVB irradiation ( Figure 3 panels A–F ) . Next , we calculated the total Pol II reads on the gene body of the 4500 highly expressed genes in the 6 time point samples following UVB irradiation ( Figure S2 ) . In agreement with our genome wide analyses ( Figure 3 panels A–F ) , we have found a statistically significant increase of Pol II global signal in the gene body regions of all the 4500 expressed genes in the 1-hour sample , a decrease at 3–4 hours and an novel increase at 5–6 hours following UVB irradiation . The increased Pol II occupancy values observed genome-wide at GBs 1 hour after UVB irradiation may represent the blocked Pol II complexes that are located at different lesions in the analyzed cells population . The decrease of Pol II tag density below control levels at 3–4 hours seems to reflect reduced transcription initiation ( see below ) and/or removal of Pol II from the transcribed genome . The novel increase in the GB regions at 5–6 following UVB irradiation may be responsible of the restarting of transcription ( see Discussion ) . In order to carry out a more detailed investigation of the effect of UVB irradiation on the different phases of Pol II transcription , we calculated Pol II tag densities around TSSs ( −/+300 bp ) , along the GBs of the genes ( from TSS +100 bp to EAG ) and downstream from EAG ( from EAG to EAG +4 kb ) regions of the 4500 expressed genes from the control data set and the six UVB irradiated samples ( Figure 4 ) . In addition , to identify genes with different Pol II behavior patterns we sorted the 4500 genes into clusters by using k-means clustering ( Figure 4 ) . With this method , by using the calculated Pol II reads , we sorted the genes into distinct groups based on Pol II occupancy pattern and density . During cluster and heat map generation to visualize Pol II density changes , values from all three regions ( TSS , GB and downstream from EAG ) were considered for the calculations including the 4500 expressed genes under control ( c ) conditions and at each of the 6 time points upon UVB irradiation ( Figure 4 ) . From the heat maps it is visible that the generated clusters represent genes with distinct , unique Pol II transcription responses following UVB treatment , as we can observe well-defined differences in the changes of Pol II distribution at the different regions of the annotated genes . We found that the 4500 expressed genes can be sorted into two main groups , hereafter called A and B . Group A contains about 93% of the examined genes ( Table S2 ) and shows in contrast to group B dramatic Pol II signal loss from the promoters between 2 and 4 hours post UV irradiation ( Figure 4 and Figure S3 ) . While on the gene promoters of group A an almost uniform Pol II signal loss can be observed between 2 and 4 hours after UVB irradiation , this group can be further subdivided into additional subgroups , depending on different Pol II behavior patterns observed mainly in the GB and/or the EAG+4000 regions ( see Aa-Ag in Figure 4 and Figure S3 ) . Moreover , to analyze and find potential differential gene function categories between the detected distinct Pol II behavior patterns on genes belonging to the different groups and subgroups , we carried out Gene Ontology ( GO ) analyses on the identified categories of genes ( Table 1 , carried out with D . A . V . I . D . ; and Table S1 , carried out with MANTEIA ) . Interestingly , in many sub-clusters Pol II occupancy increased at 1 hour and then again at 5 and 6 hours following UVB treatment at distinct regions of the transcription units ( Figure 4 and Figure S3 ) . Compared to the other patterns , genes in subgroup Aa have a strong increase of Pol II signal at 6 h on TSS , GB and EAG+4000 regions , while they have a somewhat weaker decrease of Pol II signal at their TSS regions between 2 and 4 hours than subgroups Ac-Ag ( Figure 4 and Figure S3 ) ( for gene lists see Table S2 ) . Genes in the Aa subgroup belong predominantly to ‘RNA splicing’ and ‘mRNA processing’ GO categories ( Table 1 , as defined by DAVID; and Table S1 as defined by MANTEIA; [39] , [40] , see Materials and Methods ) . Genes in subgroup Ab have also a somewhat weaker decrease of Pol II signal at their TSS regions between 2 and 4 hours when compared to the Ac-Ag subgroups , but have a strong decrease of Pol II signal in the EAG+4000 region between 1 and 4 hours , suggesting that on these genes Pol II is rapidly terminating and/or removed from these 3′ regions . Interestingly , this subgroup contains a number of genes that belong to the ‘negative regulation of macromolecule metabolic process’ and ‘negative regulation of gene expression’ GO categories ( Table 1 ) . In genes belonging to subgroup Ac , in addition to the strong Pol II disappearance at the TSS region , Pol II signal decreases very strongly in the GB region between 2 and 4 hours , while this decrease is not apparent in the EAG+4000 region . Importantly , this subgroup contains mainly genes involved in ‘ribonucleoprotein complex formation’ , ‘regulation of translation elongation and termination’ GO categories ( Table 1 ) . Genes belonging to the subgroup Ad amongst other functions play a role in ‘mRNA metabolic process’ and have a very strong Pol II increase in the GB one hour after UVB irradiation suggesting that the gene products are very quickly required after UVB irradiation . Genes in subgroup Ae have a very strong Pol II decrease at their promoters , but relatively modest changes in their GBs and EAG+4000 regions . These genes , amongst other functions , fall in the ‘nucleotide and ATP-binding’ GO categories . Genes belonging to the subgroup Af have a very strong increase of Pol II density following irradiation at 1 hour in the GB , and at 1–2 and 5–6 hour at the AEG+4000 region , suggesting that these genes may be stimulated during the first hour after UV irradiation and after that Pol II accumulates downstream from the genes . Genes belonging in the ‘structural constituent of ribosome’ and ‘translation elongation’ GO categories are overrepresented in this subgroup . The subgroup Ag consists of genes , which show Pol II signal loss from their promoters , but show a quick and almost constant increase of Pol II enrichment on GB and EAG+4000 regions . Interestingly , amongst other transcription units , genes in the ‘response to radiation’ or ‘response to UV’ GO categories ( Table 1 and Table S1 ) are overrepresented in this subgroup suggesting that these genes are heavily transcribed , but without having a paused Pol II at their promoters ( Figure 4 and Figure S3 ) . Note that in the above clusters we did not observe any correlation between gene length and Pol II behavior following UVB irradiation . In contrast to group A , the relatively small set of genes in group B ( containing 322 genes , Table S2 ) is characterized by no general loss of Pol II signal from their promoter regions ( Figure 4 and Figure S3 ) . In addition 1 and 5–6 hour after irradiation a strong increase of Pol II occupancy can be observed at the promoters of these genes . Moreover , in general in these genes a significant increase of Pol II signal through the entire transcription unit can be observed after irradiation . Interestingly , genes belonging to group B are overrepresented ( p-values 6E-07-4E-06 ) in the ‘DNA damage response’ and ‘DNA damage response , signal transduction by p53 class mediator’ GO categories , further validating the relevance of our Pol II ChIP assays and bioinformatics classifications . These results together suggest that a general negative regulation of Pol II transcription exist in response to UVB irradiation . Moreover , on distinct regions of the transcription units the presence of Pol II is differentially regulated following UVB irradiation , probably also depending on the function of the genes . Nevertheless , the response to UVB irradiation can mainly be broken down in two categories of genes: those where Pol II presence at the promoters is down regulated after irradiation ( group A , about 93% of the genes ) and genes , out of which many regulate DNA damage response , signal transduction by p53 and apoptosis , where Pol II presence is increased in the TSS , GB and slightly at EAG+4000 regions ( group B , less than 10% of the expressed genes ) . Note however that most of the NER factors are abundant in the nucleus [41] explaining why certain NER genes can be found in group Ag instead of group B . In the above detailed global analysis of Pol II behavior on expressed genes upon UVB treatment we have observed that many genes in group B , belonging to the GO categories ‘response to UV’ and ‘DNA damage response’ , have increased Pol II occupancy throughout their whole transcription unit . Thus , we analyzed Pol II distribution at annotated repair and UV-responsive genes existing in the KEGG database [42] , which may have been missed in the above analyses because they are not expressed under ‘normal’ conditions . We clustered the 164 characterized and annotated repair genes according to their Pol II occupancy and created heat maps as above ( Figure 5 ) ( for gene lists see Table S2 ) . These analyses indicate that in about half of the annotated repair genes Pol II signals increase in all of the three regions or in only part of them . We observe the following categories: a ) Pol II tag density increases everywhere in the transcription unit with a either a strong increase at the TSS or with a strong increase only in the GB and EAG+4000 regions at almost all the analyzed time points , b ) Pol II occupancy slightly increases at all three regions of the transcription units following UVB treatment , c ) while Pol II occupancy decreases at the TSS regions , its increase is more restricted to the GB and EAG+4000 regions , d ) Pol II is increasing only at the EAG+4000 region , e ) Pol II occupancy does not increase , but rather decreases at all three analyzed regions ( Figure 5 ) . Interestingly , in a ) and b ) categories there are several genes , such as DNA ligase IV ( ATP-dependent ) , cyclin D2 , p21 ( also called cyclin-dependent kinase inhibitor 1A ) , GADD45A and GADD45B , and TP53AIP1 , SESN2 , FAS , BBC3 , which are regulators of repair , cell growth or survival pathways further validating the biological significance of the present Pol II occupancy study . To evaluate whether the above observed massive Pol II promoter clearance at 2–4 hour time points in Group A ( Figure 4 ) is due to degradation of Pol II or other PIC subunits , we prepared cell extracts from non-irradiated cells and cells 1–6 hours following UVB irradiation and tested the presence of the indicated PIC subunits by western blot assay ( Figure 6 ) . The N-20 antibody recognizes Pol IIA and Pol IIO forms of Rpb1 , which have been suggested to correspond to hypo- ( IIA ) and hyperphosphorylated ( IIO ) carboxy-terminal repeat domains ( CTDs ) , respectively [43] , [44] . Note , however , that these two very discrete forms of Pol II may be due to other more complex modifications as well . Importantly , our immunoblot assays indicated no detectable degradation of Rpb1 in several independent experiments ( Figure 6A and B , and data not shown ) . Moreover , examination of the distributions of the differentially migrating forms of Pol II revealed that between 1 and 3 hours following UVB irradiation the normal balance between Pol IIA and Pol IIO forms ( 70/30% , respectively ) is shifted towards the IIO form ( 50/50% ) , and that by 6 hours after UVB irradiation the Pol IIA and Pol IIO balance is again close to the normal non-irradiated ratio ( 65/35% ) . Thus , our results seem to be in good agreement with previous studies showing that upon strong doses of UVC caused DNA damage Pol II is hyperphosphorylated and/or the Pol IIO forms becomes dominant [45] , [46] . This could also explain the observed promoter clearance , as Pol II needs to be hypophosphorylated to form the PIC . Additionally we tested the level of the phosphorylation of the CTD of Rpb1 using antibodies that recognize different and specifically phosphorylated forms of the CTD heptapeptide repeats ( Figure 6C ) . In this assay Ser2-P of Pol II CTD does not show any significant alterations upon UVB irradiation . In contrast , Ser5-P signal of Pol II CTD decreased immediately 1 h after UVB irradiation and this lower level seemed to be maintained during 6 hours following irradiation with a hint of recovery at the last time point . In addition , we detected a decrease in the level of Ser7-P signal upon UVB treatment between 2–4 hours; and a progressive reappearance of the Ser7-P from the 5 h time point following irradiation . This signal seems to follow the behavior of Pol II occupancy on the majority of the genes in Group A and is in good agreement with the finding that Ser7-P CTD may be a marker of transcription from expressed genes [44] , [47] . Importantly , none of the tested Pol II signals indicate the degradation a Pol II Rpb1 and/or its CTD following the 55 J/m2 dose of UVB irradiation . To test whether the degradation of additional PIC subunits would be responsible for the important Pol II clearance from the promoters upon UVB irradiation , we tested the global protein levels of TBP , TFIIB and the kinase subunit of TFIIH , CDK7 , which is known to phosphorylate the CTD of Pol II [48] [44] . Our analyses do not show any significant changes in the levels of the tested proteins ( Figure 6D ) . These results suggest that the loss of Pol II signal from promoters after UVB irradiation is not due to a general degradation of PIC components is the nucleus . As the general disappearance of Pol II signal from the promoters of Group A genes following UVB irradiation does not seem to be due to Pol II or other PIC component degradation , next we set out to validate the bioinformatically detected different Pol II behavior categories at the promoters ( Pol II clearance at group A and stable or increasing Pol II signal at group B ) . To this end we used anti-Pol II ChIP coupled qPCR detection on non-treated samples and on samples incubated for 3 h and 6 h after 55 J/m2 UVB irradiation . Pol II signals were quantified on the promoters of two randomly selected genes from group A ( rplp1 and ubc ) and B ( p21 and wdr24 ) . Negative/mock control ChIP was carried out with Sepharose G beads alone ( NoAb ) , and for an additional control , oligonucleotides were designed to target an intergenic region , where no Pol II binding is expected ( Figure 7A ) . The ChIP-qPCR experiment confirmed the different Pol II behavior patterns at the promoters of the selected genes . At the promoters of genes from group A we observed a decreased Pol II occupancy in the sample that was harvested 3 hours following UVB irradiation when compared to the control ( Figure 7A ) . As expected from the ChIP-Seq and bioinformatics results ( Figure 4 ) , both genes from group A show an increased Pol II occupancy on their promoter region in the sample that was harvested 6 hours following UVB irradiation ( Figure 7A ) . Genes from group B show either no decrease ( p21 ) or increased ( wdr24 ) Pol II enrichment at the promoters at 3 hours after UVB treatment compared to the control . In the case of wdr24 gene Pol II enrichment increases up to 6 hours post UVB treatment . These ChIP-qPCR validations are in good agreement with our ChIP-seq , bioinformatics and IF results . Next , to better understand the mechanisms that may regulate the opposite Pol II behavior on gene promoters belonging to either group A or B , we investigated whether certain PIC subunit enrichments would also be affected upon UVB irradiation . To this end we carried out ChIP-qPCR detection using antibodies against subunits of two GTFs , the TATA-box binding protein ( TBP ) a subunit of TFIID , and p62 , a subunit of the TFIIH ( Figure 7B and C ) . Surprisingly , TBP showed relatively stable or even increasing occupancy patterns at every tested gene from group A and B and its binding seemed to be resistant to the events that cause Pol II dissociation from the promoter ( Figure 7B ) . In contrast , the p62 subunit of TFIIH followed the same behavior as Pol II . The detectability of p62 by ChIP decreased on the promoters of genes belonging to group A , but it was stable on genes from group B 3 hours following UVB irradiation ( Figure 7C ) . At 6 hours following UVB irradiation , p62 presence at promoters recovered to the non-irradiated control levels or even higher . Thus , it seems that while TBP-containing partial PICs , or reinitiation complexes stay at the group A promoters at 3 hours following UVB irradiation , TFIIH disappears from promoters together with Pol II . These results suggest that on group A genes upon UVB irradiation transcription might be blocked to prevent PIC formation that in return would provide “free” TFIIH and time for TCR ( see Discussion ) . CSB is known to trigger the recruitment of NER factors , including TFIIH , to UV-induced DNA lesions to carry out the repair process ( see Introduction ) . Thus , to test our above hypothesis concerning the sequestration of TFIIH by the TC-NER pathway away from PIC formation , we have knocked down CSB expression by using siRNA transfection in MCF7 cells ( Figure S4 ) , and have tested whether under the CSB knock-down condition Pol II and TFIIH recruitment would still be inhibited to group A promoters by UVB ( Figure 8A and B ) . In good agreement with our hypothesis , when cells were treated with siRNA against CSB , UVB did not reduce either Pol II or p62/TFIIH recruitment to the promoters of the tested group A genes , whereas at group B gene promoters siCSB had no significant effect on either Pol II or TFIIH recruitment induced by UVB ( Figure 8A and B ) . These experiments further suggest that CSB and the NER pathway participate in employing the pool of TFIIH that in turn would not be available for participating in PIC formation ( see also Discussion ) .
In the past decades a lot of efforts have been devoted to understand how Pol II transcription is recovered after genotoxic stress , such as UV irradiation . However , our knowledge about Pol II transcription inhibition during TCR and the subsequent recovery of RNA synthesis is based only on a handful of model genes . Note that most of the previous studies that investigated the link between repair and transcription used much higher , often lethal , UVC doses [49] . To analyze Pol II behavior following UV irradiation , we carried out seven parallel ChIP-seq experiments following sublethal UVB treatment of human MCF7 cells to track DNA-bound RNA Pol II complexes genome-wide over time . Importantly , the sublethal 55 J/m2 dose of UVB irradiation used had a wide effect on the genome of MCF7 cells , as it induced CPD lesions genome-wide , which persisted up to , or even longer than 24 hours ( Figure S1 ) . Despite the presence of these lesions ( and probably other type of lesions ) in the genome , the transcription and initiation capability of Pol II got restored , and/or even stimulated , 5–6 hours post UVB irradiation in the cells ( Figure 1–4 ) suggesting that CPDs have been repaired in the transcribed genome , but not yet in the intergenic regions . Thus , our observations are in good agreement with previous studies [21] , [22] , and reflect the differences in speed and efficiencies between TCR and GGR , and show that the genome wide UV-induced negative regulation is very dynamically relieved after TCR ( see also below ) . Our results show that on about 93% of the promoters of expressed genes Pol II accumulates at the TSSs during the first hour after irradiation , Pol II occupancy is seriously reduced 2–4 hours following UVB irradiation , and that the presence of Pol II is restored to “normal” , or even sometimes “overshoot” levels 5–6 hours after irradiation ( Figure 4 and Figure S3 ) . These results seem to be in apparent contradiction with the observed decrease of nascent transcripts ( as measured by incorporation of 5-fluorouridine ) in the first hour post irradiation , followed by a constant increase between 3 and 6 hour after UVB ( Figure 1 ) . Note however , that incorporation of nucleotides labels all transcripts at a single cell level produced by the three RNA polymerases , including many non-coding transcripts , abortive transcripts produced during promoter clearance , and also short upstream antisense transcription start site associated RNAs ( TSSa-RNAs ) and many others [36] , whereas Pol II ChIP-seq visualizes crosslinkable Pol II molecules on the genome in a large cell population . Thus , the two methods are complementary and together suggest that following UVB stress in MCF7 cells there is a very rapid global reduction in transcript production in general that is reassumed from 3 hours onwards after UVB irradiation , while the ChIP-able genome-wide binding of Pol II reaches a minimal level between 2 and 4 hours and is returning to normal or even higher levels 5–6 hours after irradiation . The reduction of the Pol II signal at promoters can be the result of several molecular events acting either independently or in combination: i ) Pol II assembled in a PIC and pausing at or close to the TSSs runs in the gene body , ii ) new PIC formation does not occur , or iii ) existing PICs containing paused Pol II are actively removed from TSSs . Nevertheless , our observations strongly suggest the existence of a rapid negative regulatory mechanism , which seems to act on almost all expressed gene promoters during TCR to either remove existing PICs , containing paused Pol IIs , and/or prevent Pol II to enter in initiation , or re-initiation , complexes at promoters , when transcription-blocking lesions may still be present on the ORFs . The fact that promoter-proximal pausing of Pol II at group A genes 2–4 h after UVB irradiation decreases everywhere ( Figure S3 and Figure 4 ) , independently of the heights of the Pol II peaks ( or Pol II residency time ) , suggests that the negative regulation causing the genome-wide Pol II clearance on promoters influences “strong” or “weak” promoter-proximal pausing of Pol II the same way . In agreement , an active global transcriptional repression process , rather than a physical blocking of transcription , has already been suggested [32]; and refs therein ) . Such a negative regulation would operate at several levels on most of the transcribed genes . Pol II molecules , which have been loaded on the promoter and/or the gene body at the moment of the UVB irradiation would quickly run into the DNA lesions , stop and signal the road blocks ( Figure 3 ) . This signalization would in response have dual effects: i ) induce the recruitment of the TCR-NER to the lesions and ii ) trigger the inhibition of transcription at most transcribed genes . In agreement , it has been suggested that transcription arrest and DNA repair can be separated [50] . Along these lines , it has also been shown that ATF3 expression is induced following UVC irradiation , ATF3 is recruited to its binding site located in the vicinity of a subset of promoters where it represses transcription of its target genes [50] . Nevertheless , this mechanism would only partially explain the genome-wide observed Pol II clearance at TSSs described in the present study . It is crucial for the cell that DNA lesions are repaired in the different transcription units with equal efficiencies , in order to avoid that short genes with low damage probability are repaired and transcribed quicker than long genes with a high likelihood of carrying many UV-induced CPD lesions . We do not know whether this negative “preventive” transcription regulatory mechanism can operate at several levels separately ( i . e . remove existing PICs containing paused Pol II and/or block Pol II incorporation in new PICs ) or whether it would inhibit both mechanisms by blocking the function of the same factor for example . Interestingly , it has been observed that the loss of de novo RNA synthesis occurs only at the UV-irradiated area of the nucleus [51] , suggesting that the transcription inhibition does not spread to long distances in the nucleus . The transcription factor TFIIH was shown to play an essential role in both transcription initiation and DNA repair [20] , [52] . As on TSSs of genes of group A , Pol II and TFIIH are reduced comparatively 3 hours following irradiation ( Figure 7 ) , it is conceivable that after UVB irradiation TFIIH is sequestered away by the TC-NER machinery ( including CSB ) from both existing and newly forming PICs by the repair machinery . This in return would help to open the DNA around the lesion and thereby allow the excision of the damaged oligonucleotide and its replacement by a new DNA fragment genome-wide [20] . Our results showing that following the depletion of CSB , one of the first factors of the TC-NER machinery that recognizes the DNA lesions , neither Pol II nor TFIIH binding is reduced to the promoter of group A genes after UVB irradiation ( Figure 8 ) , further corroborates this model . Note however , that CSB was reported to play a role in the UVC-dependent degradation of the large subunit of Pol II [46] , making it possible that the depletion of CSB could also increase Pol II stability in our assay . In line with the sequestration model by the TC-NER machinery , earlier work showed that TFIIH engagement in transcription initiation takes only a few seconds , whereas when it engages in NER it takes minutes for every NER event , which may explain why the pool of TFIIH is quickly depleted and shifted towards repair [53] , [54] . In theory , as TFIIH is present in the PICs or re-initiation complexes of the transcribed genes , the promoter-bound TFIIH molecules would be easier/quicker to recruit to the neighboring DNA lesions occurring in the same transcribed units than “freely” diffusing TFIIH molecules present in the nucleoplasm , in agreement with the observation of [51] . Moreover , it has been demonstrated that very quickly after UV irradiation TFIIH changes its subunit composition , by loosing its kinase sub-module ( called CAK ) needed for transcription initiation , and the core TFIIH ( that does not contain CAK ) subsequently associates with DNA repair factors and gets recruited to the sites of NER [55] . Such an UV-induced TFIIH “promoter deprivation” and dissociation mechanism ( possibly from both existing and newly forming PICs ) would explain why the presence of Pol II would decrease at transcribed promoters and why the repair machinery would repair the transcribed regions quicker than other genomic regions . Such a regulatory step inhibiting PIC formation and the consequent Pol II molecules running in the gene bodies would be very important to avoid the accumulation of Pol II complexes around the DNA lesion sites . Our model would also predict that transcription units , which are silent , or intergenic regions without Pol II transcription , would be repaired slower . The detected synchronized Pol II reappearance on the TSSs of most of the transcribed genes 5–6 hours after UVB irradiation suggests that transcription-coupled repair is largely completed by this time in MCF7 cells; TFIIH complexes are released from the repair sites and again available for new PIC formation on the transcribed genes . Moreover , our results investigating the presence of TBP , a DNA-binding component of TFIID , showed that the presence of TBP at the TSSs of genes is not changing dramatically over time after UVB irradiation . This observation suggests that on the transcribed genes during UVB irradiation , and following the potential TFIIH sequestration by the repair machinery , a minimal TFIID/TBP-containing re-initiation complex may stay bookmarking the TSSs where transcription has to be resumed once TCR is completed . While the Pol II clearance and recovery seems to be synchronized at the promoters of group A genes , we found very diverse patterns of Pol II behavior on the GB and on the EAG+4000 regions of the expressed genes during recovery after UVB irradiation ( Figure 4 ) . Based on our GO analyses we speculate that the main reason for these characteristic Pol II occupancy differences amongst the distinct gene clusters may be due to their function in diverse cellular process . Alternatively or in addition , the structure or the function of a given gene product may also play a role in the differential Pol II presence in the transcription units . For example the comparison of Pol II patterns and the GO results of group Ac ( GO terms: translational elongation and termination ) and group Ag ( GO terms: response to UV ) clearly show that the genes in group Ag must be repaired and restored very fast as they might have important role in the recovery of normal homeostasis after UV stress . Another common characteristic exists on the GBs of group A transcription units , namely that in most of the cases there is an increase of Pol II occupancy at 1 hour after irradiation on the GBs of these genes , which show Pol II clearance from their promoters ( Figure 2 and 3 ) . The increased Pol II signal in the GBs ( Figure 3 ) may represent a synchronized “last” round of transcription that may be required to detect and signal the DNA lesions to start TCR . Moreover , Pol II changes on the GBs and EAG+4000 regions did not always parallel the homogenous decrease in Pol II binding at the promoters of group A genes following UVB irradiation . This suggests that the UVB-induced global negative regulatory mechanisms affecting Pol II transcription initiation , elongation and termination may be distinct and are not always interconnected . We also detected a set of genes , which show no decreased Pol II presence at their promoter regions , but rather a general increase of Pol II density throughout their three analyzed gene regions after UVB irradiation ( Figure 4 ) . Genes belonging in this group ( B ) fall often in the GO categories annotated as DNA damage response , signal transduction and apoptotic processes . A separate search in repair-associated genes in the KEGG database also showed that a portion of genes in this category behave as genes in our group B . Many of these genes seem to be key genes regulating repair , cell cycle , apoptosis and stress responses . Thus , these genes with increase Pol II signals at their TSSs and other regions should have a particularity that differentiates them from the majority of the expressed genes in group A , and it is tempting to speculate that group B are somehow protected from the above described transcription inhibition mechanism . To overcome the negative regulation at the promoters of group B genes , several scenarios are possible: i ) these genes may get repaired much faster than the genes in group A and at the 1 hour time point they are transcribing again; or ii ) TFIIH is present , but indispensable for transcription initiation on these genes , and thus , the TFIIH sequestration mechanism does not influence the transcription of these genes; or iii ) these promoters would have specific requirements for transcription initiation , involving slightly different , non-canonical initiation machinery that could for instance involve specific stress-related transcription factors and a special form of TFIIH . As TFIIH independent transcription initiation has already been reported [56] , [57] , [58] , [59] it is conceivable that even if TFIIH was present in the PICs of the group B promoters , its sequestration by CSB and the repair machinery would not block transcription initiation on these genes ( see also Figure 8 ) . The above possibilities alone or in combination may ensure rapid clearance of the transcribed strand from damage and subsequent rapid transcription because of the need of the cell to use the encoded proteins . It is known that p53 can regulate a subset of genes under compromised physiological conditions , when for example DNA is damaged . It is has been suggested using the p21/cdkn1a model gene that p53 uses unorthodox mechanisms to activate p21 when Pol II CTD phosphorylating kinases are inhibited , the recruitment of specific elongation factors are defective and mRNA synthesis from certain individual genes is inhibited [60] . From this study testing a handful of genes , a so-called “paradoxical scenario” was suggested , where the transcription of specific stress-response genes through p53 action would escape the global inhibition of mRNA synthesis . Our genome-wide study identifying the group B genes , containing many p53-responsive genes , defines all those genes where the cells seem to use alternative processes to react to UV stress that otherwise would compromise mRNA synthesis in general . Furthermore , the fact that group B genes are not influenced by the depletion of CSB ( Figure 8 ) is in good agreement with previous observations showing that p53-responsive genes do not require functional CSB , while housekeeping genes do [61] . Studies investigating the effect of genotoxic stresses on transcription reported two possible pathways by which Pol II protein levels may be affected: either the hyperphosphorylation of the CTD or the degradation of the largest subunit of Pol II [26] . We did not detect any change in the global level of Pol II ( Figure 6 ) therefore it seems that the sublethal UVB irradiation condition used does not induce degradation of the Pol II complex , but rather an active negative regulation of the activity of Pol II . Between 1–4 hours following UVB irradiation , when there is a massive Pol II clearance from the majority of the promoters , the proportion of the Pol IIO form increases , and decreases again to at 6 hours after UVB irradiation , when Pol II presence on the genes is re-established . Thus , our observations seem to be in line with previous studies [62] , [63] , suggesting that the Pol IIO form is less competent for PIC formation . Nevertheless , at this stage it is not possible to decide whether the increase of the Pol IIO form 1–4 hours following UVB is a cause or a consequence of the above-discussed negative regulatory mechanism . Surprisingly , none of the antibodies raised against different phosphorylated forms of the CTD hepta-peptide repeat ( anti-Ser2 , anti-Ser5 or anti-Ser7 ) revealed increased levels of phosphorylation of the Rpb1 CTD upon UVB stress that would explain the shift from the Pol IIA to the Pol IIO form ( Figure 6C ) . These results suggest a more complex regulation in the CTD modification mechanism ( s ) that would result in the well detectable and discrete shift from the Pol IIA to the Pol IIO form in western blot assays . Moreover , we detected a quick drop and recovery at 6 hours in Ser7 CTD phosphorylation in parallel with the promoter clearance and recovery of Pol II at the TSSs of the majority of genes . The reduction of the CTD Ser7-P mark between 2 and 4 hours might reflect the above-described negative regulation of Pol II transcription during this time window , and further supports the idea , that Ser7-P is required for gene expression [47] . Taken together all our observations it seems that the massive Pol II clearance on group A genes upon UVB irradiation is not due to Pol II degradation , but due to the incapability of the Pol II complex to initiate transcription . It seems that during TCR the general transcription factor TFIIH is sequestered away from the TSSs by the repair machinery and this in turn would either dismantle genome-wide existing PICs and/or block the formation of new PICs on the majority of the transcribed genes . In contrast , on a small subset of key regulatory genes this negative mechanism does not work either because transcription initiation on these genes is not dependent on the repair-competent form of TFIIH or these genes are repaired much faster than the inhibited genes . Further experiments , will be needed to distinguish amongst all these different exciting possibilities . In conclusion , our study for the first time gives a genome-wide view about the mechanistic details of UVB induced Pol II transcription changes during TCR .
The MCF7 human cell line ( obtained from American Type Culture Collection; reference number HTB-22 ) was grown in Dulbecco's Modified Eagle Medium ( DMEM , Invitrogen ) supplemented with 10% foetal calf serum ( FCS ) . The medium contained insulin ( 0 . 6 µg/ml ) and gentamicin ( 40 µg/ml ) . For assessing global and ongoing transcription cells were incubated with 1 mM 5-fluorouridine ( Sigma-Aldrich ) for 20 minutes . Incorporation of the modified nucleotide was monitored by indirect immunofluorescence using an anti 5-FU antibody from Sigma-Aldrich . For the ChIP and ChIP-seq experiments exponentially growing cells were irradiated with 55 Joules/m2 UVB dose at 312 nm wavelength ( Vilber T-15M lamp ) or with with 55 , 100 and 200 Joules/m2 ( see Figure S1 ) . siRNAs targeting CSB ( ERCC6 ) , GAPD and non-targeting control ( L-004888-00-0050 , D-001830-10-05 , D-001810-10-05 , Dharmacon , Thermo Scientific ) were transfected to MCF7 cells using Dharmafect Transfection Reagent 1 ( T-2001-03 , Dharmacon , Thermo Scientific ) according to the manufacturers protocol . Cells were harvested for western blot analysis or ChIP 72 hours after the transfection . MCF7 cells were plate into a 6 well plate ( 300 cells/well ) one day prior to UV treatment . In the following days , the survived cells will form colonies . 7 days after UV irradiation , the cells were washed with PBS then stained with Crystal violet solution ( 0 . 2% crystal violet , 2% ethanol ) . The staining was removed from the cells with 1% sodium dodecyl sulphate ( SDS ) containing MQ water . The crystal violet amount in both UV treated and in control samples were measured with spectrophotometer at 595 nm . Results were calculated from biological triplicates Cells were plated in 6 cm plates and UV-treated at 80–90% confluence . After incubation for 1 , 2 , 4 , 6 , 8 , 16 , 24 hours DNA was extracted from samples as well as from non-treated control with SIGMA GenElute Mammalian Genomic DNA Miniprep Kit . DNA content was quantified with Nanodrop . 250 ng of DNA was diluted in 2× SSC ( 0 . 3 M NaCl , 0 . 03M Sodium citrate , pH: 7 ) buffer from each sample and was transferred to Amersham Hybond-N+ membrane with Slot-blot vacuum chamber . The membrane was treated with Denaturizing buffer ( 0 . 5M NaOH , 1 . 5M NaCl ) then Neutralizing buffer ( 0 . 5 M Tris-HCl , 1 . 5 M NaCl ) . The membrane was then treated according to Western blot protocol: blocked with PBS +2% milk , and then incubated with mouse IgG monoclonal anti-CPD ( TDM2 ) ( MBL international corp . ) primary antibody overnight in 4°C . MCF7 cells were plated in 6 cm plates prior treatment . At 80–90% confluence , cells were treated with 55 J/m2 UVB . The irradiated and control cells 1 , 2 , 3 , 4 , 5 , 6 , hours later after incubation were washed twice with ice-cold PBS containing complete protease inhibitor cocktail ( 1× ) , phenylmethylsulfonyl fluoride ( PMFS ) ( 0 . 5 mM ) , β-glycerophosphate ( 10 mM ) , sodium orthovanadate ( 1 mM ) , sodium fluoride ( 20 mM ) inhibitors . Cells were scraped in PBS containing protease inhibitor cocktail and frozen-thawed three times . Samples were sonicated for 10 cycles ( 30 second on , and 30 seconds off ) ( Bioruptor ) then boiled for 5 min in loading solution . Protein samples were separated by a 6–10% SDS-PAGE , transferred and western blot assays were carried out by using standard methods . The following antibodies were used: RNA polymerase II N-terminal H-224× ( Santa Cruz ) , Pol II Ser2 , AB: Covance , ( MMS-129R ) , Pol II Ser5 AB: Abcam , ( ab5131 ) Pol II Ser 7 AB: [64] , TBP: 3G3 [65] , TFIIH subunit ( p62 ) : 3C9MAB [66] , TFIIB: [67] , CDK7: ( C-19 ) , sc-529 ( Santa Cruz ) , Tubulin-α: ( D-10 ) : sc-135659 ( Santa Cruz ) , GAPD: 6C5 ( MAB374 , Millipore ) , CSB: 1CSB- 1A11 [68] . In Figure S1 Phospho-p53 ( Ser15 ) antibody #9284 ( Cell Signaling Technology ) ; Phospho-Chk1 ( Ser345 ) ( 133D3 ) antibody #2348 ( Cell Signaling Technology ) ; Tubulin-α: ( D-10 ) antibody: sc-135659 ( Santa Cruz ) were used . MCF7 cells were plated in 15 cm dishes . At 80–90% confluence cells were UVB treated as described above . After 1 , 2 , 3 , 4 , 5 , or 6 hours of incubation cells were quickly washed with PBS , and cross-linked with 1% formaldehyde for 20 minutes at room temperature . ChIP experiments were carried out as described earlier [11] . Validation of the ChIP was performed by quantitative PCR ( qPCR ) analysis using a Roche LightCycler 480 with Sybr green ( Roche ) master mix . Oligonucleotides were designed to amplify the promoter regions of the human Ubc/NM_021009 , Rplp1/NM_001003 , p21/cdkn1a/NM_000389 and WDR24/NM_032259 genes . Intergenic region was selected as a negative control region . The ChIP experiments were repeated at least twice , and all the qPCR reactions were done in triplicates . The sample preparation for ChIP-seq was the same as described [11] . To have enough material for sequencing , 5 ChIP samples were pooled together for each time point . Library preparation for sequencing was performed as described by the manufacturer . The generated sequencing data was deposited in the Gene Expression Omnibus ( GEO , http://www . ncbi . nlm . nih . gov/gds ) database . The 32 base pair tags generated from Hi-seq 2000 were mapped to the human genome ( UCSC hg19 ) using the eland program allowing two mismatches . Only sequences that mapped uniquely to the genome with maximum of two mismatches were used for further analysis . To eliminate non-specific binding sites , we used our control ChIP-seq dataset , which was generated using an antibody that does not recognize any human proteins ( GSE34001 ) . Genome annotations were downloaded from the UCSC Genome Browser ( https://genome . ucsc . edu/ ) , human genome Build 37 ( hg19 assembly ) . Gene definitions were given by the refseq genes track [69] . Intergenic regions ( around 8000 regions ) were selected that are far away from genes about 20 kb and tag numbers were counted on 2 kb interval in the middle of them for all the 7 samples . These values were used as an input for DESeq Bioconductor package , which normalizes the samples based on their median values . ( http://www . bioconductor . org/packages/2 . 9/bioc/vignettes/DESeq/inst/doc/DESeq . pdf ) . We carried out analyses on all genes found in the refseq database and on 4500 expressed genes , based on the published RNA-seq dataset for MCF-7 cell line [38] . The sequenced ChIP-seq reads represented 36 base pair fragments . To illustrate the entire DNA fragments bound by Pol II , basically before analysis , 3′ end of each ChIP-seq read was extended to 200 bp in the direction of the reads . To generate an average gene profile from ChIP-seq results , Pol II tags were counted on the selected genes with seqMINER software [37] from −1000 bp relative to the TSS of a given gene until the end of EAG +4000 bp regions by dividing these regions into 120 bins ( the same number for long as well as for short genes ) . The ChIP-seq reads were counted in each bin and used to generate the profile . The promoter regions of all refseq genes were divided into 5 bins , while the GB+EAG+4000 regions together were covered by 115 bins . While doing this analysis , the strand orientation is taken in account in order to orientate all analyzed features in the same direction . For heat map generation , Pol II read numbers for the 4500 expressed genes were counted from the seven datasets around the promoter ( +/−300 bp around TSS ) , on the annotated gene body ( TSS+100 until the EAG ) and downstream of EAG ( EAG+4000 bp ) . During heat map generation , Pol II tag densities were subjected to k-means clustering in order to organize or cluster genes in a same group based upon similar tag enrichment within a defined region . In k-means clustering , number of clusters is fixed and hence the samples are sorted in the clusters based upon the tag enrichment and patterns of Pol II . Cluster and heat map generation was carried out with Cluster 3 and TREEview software . Cluster:http://bonsai . hgc . jp/~mdehoon/software/cluster/manual/index . html#Top Treeview: http://sourceforge . net/projects/jtreeview/ The Database for Annotation , Visualization and Integrated Discovery ( D . A . V . I . D . ) ( http://david . abcc . ncifcrf . gov/home . jsp ) was used for GO analyses and gene ID conversion . Further GO enrichment analyses were also performed in Manteia using its statistical module ( http://manteia . igbmc . fr/ ) . During the analyses only GO categories with lower than 0 . 01 p-values ( p-value<0 . 01 ) were considered as positive results .
|
Our genome is continuously exposed to genotoxic attacks that generate aberrant DNA structures . These can block the transcribing DNA-dependent RNA polymerase II ( Pol II ) enzyme and can lead to deleterious cellular processes . Cells have developed several mechanisms to stop Pol II , repair the roadblocks and to restore normal polymerase traffic . Numerous efforts investigated the fate of blocked Pol II during DNA repair mechanisms and suggested that stopped Pol II complexes can either backtrack , be removed or bypass the lesions to allow repair . We carried out a genome-wide analysis of Pol II behavior upon a DNA damaging stress , UVB , which is relevant from the public health standpoint . Thus , we could follow UVB-induced Pol II behavior changes on every human gene over time . We uncovered a novel UV induced negative regulatory mechanism , which inhibits the recruitment of Pol II to the promoters of about 93% of all transcribed genes , and a small subset of gene ( including regulators of repair , cell growth and survival ) that escapes this negative regulation , probably because their gene products are required during/after UVB irradiation . Thus , we uncover how a cell induces a global negative regulation at the level of transcription initiation in response to a genotoxic stress .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"cellular",
"stress",
"responses",
"genomics",
"cell",
"biology",
"gene",
"expression",
"genetics",
"biology",
"and",
"life",
"sciences",
"dna",
"repair",
"dna",
"cell",
"processes",
"molecular",
"cell",
"biology",
"dna",
"transcription"
] |
2014
|
UVB Induces a Genome-Wide Acting Negative Regulatory Mechanism That Operates at the Level of Transcription Initiation in Human Cells
|
Protein homeostasis is critical for cell survival and functions during stress and is regulated at both RNA and protein levels . However , how the cell integrates RNA-processing programs with post-translational protein quality control systems is unknown . Transactive response DNA-binding protein ( TARDBP/TDP-43 ) is an RNA-processing protein that is involved in the pathogenesis of major neurodegenerative diseases , including amyotrophic lateral sclerosis ( ALS ) and frontotemporal dementia ( FTD ) . Here , we report a conserved role for TDP-43 , from C . elegans to mammals , in the regulation of protein clearance via activation of FOXO transcription factors . In response to proteotoxic insults , TDP-43 redistributes from the nucleus to the cytoplasm , promoting nuclear translocation of FOXOs and relieving an inhibition of FOXO activity in the nucleus . The interaction between TDP-43 and the FOXO pathway in mammalian cells is mediated by their competitive binding to 14-3-3 proteins . Consistent with FOXO-dependent protein quality control , TDP-43 regulates the levels of misfolded proteins . Therefore , TDP-43 mediates stress responses and couples the regulation of RNA metabolism and protein quality control in a FOXO-dependent manner . The results suggest that compromising the function of TDP-43 in regulating protein homeostasis may contribute to the pathogenesis of related neurodegenerative diseases .
A defining feature of all living cells is the ability to adapt to stress stimuli . This adaptive response is particularly important for maintaining protein homeostasis , which is critical for cellular functions . The cell employs a variety of protein quality control mechanisms in an effort to maintain the integrity of the proteome , including those regulating protein synthesis and degradation . The regulation of protein synthesis occurs at multiple levels , including transcription [1] , RNA processing [2] , and translation initiation [3] . Global attenuation of protein synthesis is often part of stress responses , and RNAs and RNA-processing proteins are central players in this adaptation [4] . Meanwhile , coordinated protein quality control systems are activated to enhance the degradation of damaged proteins . For instance , endoplasmic reticulum ( ER ) stress activates the signal transduction pathway known as the unfolded protein response ( UPR ) , which coordinates a general translational attenuation and a specific induction of quality control proteins , including molecular chaperones , in order to improve protein folding in the ER lumen [5] . However , the coordination between these distinct stress responses is not completely understood and may involve connected regulation at both RNA and protein levels . TAR-DNA binding protein ( TDP-43 ) is an RNA-binding protein that has been suggested to play a major role in the pathogenesis of amyotrophic lateral sclerosis ( ALS ) and frontotemporal dementia ( FTD ) [6]–[34] . Bearing features of a heterogeneous nuclear ribonucleoprotein ( hnRNP ) , TDP-43 has well-characterized RNA-processing functions [35]–[37] . TDP-43 has been shown to regulate transcription [38] , [39] , RNA splicing [40] , [41] , mRNA stability [42] , [43] , and microRNA processing [44] . An increasing number of RNA-binding proteins have been implicated in ALS/FTD and related neurodegenerative diseases [45] , including FUS ( fused in sarcoma ) [46] , [47] , hnRNPA2B1 , and hnRNPA1 [48] . As is true for TDP-43 , a pathological feature of these RNA-binding proteins is the formation of proteinaceous inclusions in patients' tissues . Another feature shared by these RNA-binding proteins is their redistribution during stress . Although primarily nuclear , they can be found in stress granules after diverse stimuli [48]–[54] . Although the role of TDP-43 in RNA processing is well established , the full range of TDP-43 function has yet to be understood . Recently , the ortholog of TDP-43 in C . elegans , TDP-1 , was shown to negatively regulate proteotoxicity associated with protein misfolding , suggesting that the nematode protein plays a role in the regulation of protein homeostasis [55] , [56] . This observation raises a question as to whether the RNA-processing function of TDP-43 is directly coupled to its ability to regulate protein homeostasis . Despite extensive study of the complex pathways responsible for cellular stress responses , how the cell coordinates these different adaptive programs is not yet completely understood . In particular , the exact mechanisms by which RNA processing coordinates with other aspects of stress responses to maintain protein homeostasis remain unclear . Here , we present a mechanistic pathway through which TDP-43 couples RNA processing with active protein quality control during stress . Our results show that TDP-43 regulates the activities of FOXO transcription factors , which are orthologous to C . elegans DAF-16 and mediate expression of genes involved in longevity , stress resistance , and protein quality control [57] . The activation of FOXOs is switched on when TDP-43 responds to differential stress signals , undergoes nucleocytoplasmic translocation , and reconfigures its interacting partners . We propose that the regulation of FOXO by TDP-43 represents an important scheme for the cell to efficiently maintain protein homeostasis by exerting control at both the RNA and protein levels; compromising the function of this pathway may contribute to the pathogenesis of TDP-43-related diseases .
C . elegans lacking its sole TDP-43 ortholog , TDP-1 , lives longer than wild-type ( WT ) controls ( Figure 1A ) [55] , [56] , and the underlying mechanism is not understood . The insulin and insulin-like growth factor ( IGF ) pathway is an evolutionarily conserved regulator of longevity from C . elegans to humans [58] . Reduced function of the insulin/IGF-1 receptor , DAF-2 , significantly extends the lifespan by activating DAF-16 , a transcription factor that controls the expression of aging-related and stress-resistance genes [59] . To determine whether TDP-1 functions in the DAF-2–DAF-16 pathway , we utilized hypomorphic or null alleles of these genes to perform an epistasis analysis . A double mutant , tdp-1 ( ok803lf ) ;daf-2 ( e1370lf ) , exhibited a longer lifespan than did daf-2 ( e1370lf ) alone ( Figure 1B ) . There are further genetic interactions between the two genes on other phenotypes; the tdp-1;daf-2 double mutant had improved egg-laying and locomotion compared with the daf-2 mutant alone ( Figure S1 ) . These data suggest that TDP-1 acts in a pathway parallel to that of DAF-2 to influence longevity , although a crosstalk between TDP-1 and DAF-2 may still be possible . However , another double mutant , tdp-1 ( ok803lf ) ;daf-16 ( mu86lf ) , completely abolished the longevity effect of tdp-1 ( ok803lf ) alone ( Figure 1A ) [55] , indicating that there is a genetic link between TDP-1 and DAF-16 , in which DAF-16 lies downstream of TDP-1 in the regulation of lifespan ( Figure 1C ) . Correlating with increased lifespan in C . elegans lacking TDP-1 , the mutant also shows enhanced clearance of misfolded proteins [55] , [56] . Consistently , we found that the tdp-1 ( ok803lf ) mutant reduced the aggregation of TDP-C25-YFP , a misfolded protein reporter expressed in C . elegans neurons ( Figure 1D ) . To test whether DAF-16 is downstream of TDP-1 , we generated a strain expressing TDP-C25-YFP and harboring the double mutant , tdp-1 ( ok803lf ) ;daf-16 ( mu86lf ) . The daf-16 mutant reversed the reduction of protein aggregation conferred by the tdp-1 mutant ( Figure 1D ) . This data suggests that TDP-1 regulates proteotoxicity via DAF-16 . Since DAF-16 is a transcription factor , we asked whether TDP-1 influences the expression of DAF-16's transcriptional targets . We performed quantitative RT-PCR to measure the mRNA levels of a panel of known DAF-16 target genes in tdp-1 ( ok803lf ) mutants and WT controls . These DAF-16-regulated genes included stress-resistance genes such as the metallothioneins mtl-1 and mtl-2 as well as uncharacterized genes dao-4 , dct-8 , and dct-17 . The results indicated that most of the tested DAF-16 target genes are significantly up-regulated in tdp-1 ( ok803lf ) mutant C . elegans ( Figure 1E ) . Next we asked whether this up-regulation upon loss of TDP-1 is specific to DAF-16 target genes . Although the transcriptional profiles of tdp-1 ( ok803lf ) mutants and WT controls indicates that there are more genes down-regulated than up-regulated in tdp-1 ( ok803lf ) mutants ( Figure S2A ) [55] , quantitative RT-PCR analysis shows that DAF-16 targets are specifically up-regulated ( Figure S2B ) . Taken together , these data demonstrate that loss of tdp-1 produces a specific up-regulation of DAF-16 transcription factor activity . Since DAF-16 is a major transcription factor of stress-resistance genes [59] , and mammalian TDP-43 undergoes stress-induced localization changes [49]–[51] , we hypothesized that C . elegans TDP-1 is involved in stress signaling . To determine whether TDP-1 undergoes stress-induced changes in neurons , we generated transgenic strains that expressed YFP-tagged TDP-1 under the control of the pan-neuronal snb-1 promoter . These animals exhibited severe locomotor defects similar to those that we have previously noted in transgenic C . elegans expressing human TDP-43 driven by the same neuronal promoter [60] . Since protein quality control is involved in the regulation of both lifespan and neurodegeneration , we investigated whether TDP-1 responds to proteotoxic stress . First , we observed that neuronal TDP-1 responds to heat shock stress , which is known to increase misfolded proteins . When the transgenic TDP-1-YFP strain was grown on solid or liquid medium at 20°C , the TDP-1-YFP protein was localized to neuronal nuclei ( Figure 2A ) . However , when the strain was subjected to heat shock stress at 28°C for 16 hours , TDP-1-YFP migrated to the cytoplasm , and in a subset of neurons , the protein formed granular structures ( Figure 2B ) . Next , we tested the effects of hypertonic stress , which has been shown to induce molecular crowding and protein damage [61]–[64] . When the strain was treated with 0 . 4 M NaCl in liquid medium , we again observed the nucleocytoplasmic translocation of TDP-1 and formation of granular structures ( Figure 2C ) . To test the response of TDP-1 in a setting directly relevant to proteotoxicity-related neurodegeneration , we crossed the stable transgenic TDP-1-YFP C . elegans strain into a C . elegans model of ALS expressing human SOD1 with the G85R mutation . The SOD1-G85R mutant has a high propensity to misfold and aggregate in this model system [65] . In the double-transgenic strain expressing both TDP-1-YFP and SOD1-G85R , but not the single-transgenic strain , we observed a switch in localization of TDP-1-YFP from the nucleus to the cytoplasm , where it was localized to punctate granules similar to those observed under heat shock and hypertonic stress ( Figure 2D ) . These TDP-1 puncta could be distinct RNA granules; alternatively , the presence of misfolded proteins , such as SOD1-G85R , may seed the aggregation of TDP-1 . Taken together , these results demonstrate that TDP-1 responds to different types of proteotoxic stresses , suggesting that the regulation of lifespan by TDP-1 involves its function in stress signaling . Next , we asked whether the observed regulation of DAF-16 by TDP-1 is conserved from C . elegans to humans . DAF-16 is the sole C . elegans ortholog of four mammalian FOXO members ( FOXO1 , FOXO3a , FOXO4 , and FOXO6 ) , with the first three showing a high degree of structural and regulatory similarity [66] . To determine whether TDP-43 regulates the transcriptional activity of FOXOs , we used a luciferase reporter under the control of forkhead responsive elements ( FHRE-Luc ) to measure the FOXO transcriptional activity in HEK293T human embryonic kidney cells . Co-expression of the FHRE-Luc reporter with a FOXO family member significantly boosted the luciferase signal , enhancing the sensitivity for measuring the activity of a particular FOXO transcription factor . Consistent with the up-regulation of C . elegans DAF-16 activity by loss of TDP-1 , shRNA-mediated knockdown of endogenous TDP-43 in HEK293T cells significantly increased the FOXO transcriptional activity , as indicated by the increase in luciferase activity ( Figure 3A–B ) . Conversely , ectopic expression of TDP-43 markedly decreased the transcriptional activity of all three FOXO family members ( Figure 3C–D ) . Moreover , the effects of TDP-43 on FOXO transcriptional activity were dose-dependent , with increasing levels of TDP-43 causing further suppression of the FHRE-Luc reporter signal . This suppression of FOXO transcriptional activity was not due to a decrease in FOXO protein levels caused by the overexpression of TDP-43 ( Figure 3E–F ) . Overexpression of TDP-43 alone did not significantly change the luciferase activity of the FHRE-Luc reporter , reflecting the fact that the low endogenous level of FOXOs is not sufficient for the assay ( Figure S3 ) [67] . Given the primarily nuclear localization of TDP-43 , these results suggest an inhibition of FOXO transcriptional activity by TDP-43 in the nucleus . Taken together , these results establish a regulation of FOXO by TDP-43 that is conserved from C . elegans to humans . Since NaCl treatment induced the nucleocytoplasmic translocation and granule formation of C . elegans TDP-1 , we asked whether this response to hypertonic stress is evolutionarily conserved , by examining the effect of NaCl treatment on human TDP-43 in HEK293T cells through immunofluorescent staining . Treatment of HEK293T cells with 0 . 2 M NaCl induced the translocation of TDP-43 from the nucleus to the cytoplasm , where it co-localized with the stress granule marker Ras GTPase-activating protein-binding protein 1 ( G3BP ) ( Pearson's correlation coefficient>0 . 9 ) ( Figure 4A ) . The redistribution of TDP-43 to cytoplasmic G3BP-positive structures with treatment of 0 . 2 M NaCl was similar to that observed after treatment with sorbitol , a known osmotic stressor and well-established inducer of stress granule formation [68] . To examine the dynamic redistribution of TDP-43 during hypertonic stress , we stained for TDP-43 after incubating HEK293T cells with 0 . 2M NaCl for various lengths of time ( Figure S4 ) . Changes in TDP-43 were observed within 15 min of NaCl treatment , with TDP-43 forming punctate structures in the nucleus . By 2 h , TDP-43 was observed in the cytoplasm in large stress granules co-localizing with G3BP . Interestingly , we found that NaCl-stress-induced patterns of TDP-43 translocation and sequestration varied in a concentration-dependent manner . When HEK293T cells were treated with 0 . 3 M NaCl , TDP-43 underwent cytoplasmic translocation but was recruited to a previously undescribed , smaller type of granules that did not co-localize with G3BP ( Pearson's correlation coefficient <0 . 4 ) ( Figure 4A ) . We also examined the dynamic redistribution of TDP-43 with 0 . 3 M NaCl treatment ( Figure S5 ) . TDP-43 formed punctate granules in nucleus within 15 minutes , and by 30 minutes TDP-43 redistributed to the cytoplasm forming this type of small granules . Next we explored whether the translocation of TDP-43 is a reversible process . After a 3-h treatment with sorbitol or NaCl , the stressors were washed off , and the cells were kept in normal medium . After 24 h , TDP-43 was completely translocated back to the nucleus , although G3BP-positive stress granules remained in the cytoplasm ( Figure S6 ) . These results indicate that TDP-43 responds to various stresses in a dynamic and reversible manner that is not always associated with stress granules . Since redistribution of proteins in the cell is often associated with post-translational modifications , we examined how the phosphorylation of TDP-43 correlates with the changes in its localization induced by hypertonic stress . We used a phospo-TDP-43 Ser409/410-specific antibody to detect the phosphorylated TDP-43 in HEK293T cells by immunofluorescence microscopy ( Figure 4B ) . In untreated HEK293T cells , unlike the unmodified TDP-43 , the phosphorylated protein appeared in both the nucleus and cytoplasm . As has previously been observed for sorbitol [49] , low hypertonic stress ( 0 . 2M NaCl ) treatment resulted in the majority of the phosphorylated TDP-43 co-localizing with G3BP-positive stress granules in the cytoplasm ( Pearson's correlation coefficient>0 . 9 ) . In contrast , when cells were exposed to high hypertonic stress ( 0 . 3M NaCl ) , the phosphorylated TDP-43 was localized differently and produced an appearance similar to that of untreated cells: The phosphorylated TDP-43 was distributed throughout both the nucleus and cytoplasm and did not colocalize with the G3BP-positive stress granules ( Pearson's correlation coefficient <0 . 4 ) . These results indicate that although cytoplasmic translocation is a consistent feature of TDP-43 during stress responses , its localization patterns are determined by the type and strength of the stress signals . To understand how TDP-43 could regulate the activity of FOXOs during stress responses , we investigated the protein interactions that link these two proteins . We co-transfected HEK293T cells with tagged versions of the TDP-43 and FOXO3a proteins and performed co-immunoprecipitation assays . Immunoprecipitation assays using TDP-43 as bait failed to pull down FOXO3a ( Figure S7 ) , indicating that there is no physical interaction between TDP-43 and FOXO3a . Next we investigated whether TDP-43 and FOXOs are linked in their localization changes during stress responses . To easily visualize the localizations of FOXO proteins , we utilized two U2OS cell lines that stably expressed GFP-FOXO1 or GFP-FOXO3a . Interestingly , we observed a strong mutual exclusion in the nucleocytoplasmic compartmentalization of TDP-43 and FOXO proteins ( Figure 5A–B ) . Under normal culture conditions , endogenous TDP-43 was primarily localized in the nucleus , and only less than 5% of cells had a significant fraction of the TDP-43 in the cytoplasm , with the percentage increasing with stress . When TDP-43 was in the nucleus , the GFP-tagged FOXOs were almost invariably in the cytoplasm . When TDP-43 was cytoplasmic , the majority of the cells showed translocation of the FOXO proteins to the nucleus . Under oxidative stress induced by H2O2 treatment , cytoplasmic translocation of TDP-43 and nuclear translocation of FOXOs both increased , and their exclusive spatial correlation was maintained . We then asked whether the cytoplasmic translocation of TDP-43 specifically drives the nuclear translocation of FOXO proteins as a stress response . To address this question , we performed cellular fractionation assays using HEK293T cells co-transfected with tagged versions of the TDP-43 and FOXO3a proteins and treated with hydrogen peroxide , which consistently induces TDP-43 cytoplasmic translocation . Western blotting against a cytoplasmic marker ( caspase-3 ) and a nuclear marker ( PARP1 ) confirmed a clean separation of cytoplasmic and nuclear fractions . The expression of TDP-43 alone , without stress , did not induce any detectable change in the fractionation of FOXO3a . However , with 1 mM H2O2 treatment , which increases the cytoplasmic fraction of TDP-43 , the expression of TDP-43 led to a pronounced shift in FOXO3a from the cytoplasm to the nucleus ( Figure 5C–D ) . These results suggest that the redistribution of TDP-43 from the nucleus to the cytoplasm under stress drives FOXO proteins translocating from the cytoplasm to the nucleus , consistent with the observation of a strong mutual exclusion in the nucleocytoplasmic compartmentalization of TDP-43 and FOXO proteins . To test whether TDP-43 also regulates the function of FOXOs in a stress-dependent manner , we used the FHRE-Luc reporter to measure FOXO transcriptional activity in the absence or presence of TDP-43 . In contrast to the unstressed condition in which the expression of TDP-43 significantly suppressed FOXO activities , the TDP-43 expression dramatically increased FOXO3a transcriptional activity under the H2O2 stress ( Figure 5E ) . Thus TDP-43 plays a pronounced role in stress to promote the nuclear translocation and transcriptional activity of FOXO proteins . To understand how TDP-43 regulates FOXO localization and activity without a physical interaction between the proteins , we asked whether there is another player that might mediate an indirect association between them . The 14-3-3 family of proteins emerges as a possible candidate because these proteins have been shown to be involved in a multitude of signaling pathways and have a diverse set of binding partners . FOXO1 , FOXO3a , and FOXO4 all interact with 14-3-3 proteins [69]–[71] , and TDP-43 has been shown to interact with 14-3-3 proteins in an RNA-dependent manner [43] . To determine whether 14-3-3 relays signals from TDP-43 to FOXO , we performed competitive co-immunoprecipitation assays to address whether 14-3-3 partners with TPD-43 and FOXO in mutually exclusive protein complexes ( Figure 5F–H ) . For this purpose , we transfected HEK293T cells with different combinations of Myc-tagged TDP-43 , Flag-tagged FOXO3a , and HA-tagged 14-3-3σ . With 1 mM H2O2 treatment , 14-3-3σ was able to pull down either TDP-43 or FOXO3a when 14-3-3σ was co-transfected with either of the two proteins ( Figure 5F ) . However , when all three proteins were expressed , the level of FOXO3a was greatly reduced in the 14-3-3σ co-immunoprecipitates ( Figure 5F ) . Similar competitive binding to 14-3-3σ was also observed between WT TDP-43 and FOXO1 ( Figure 5G ) . These results demonstrate that TDP-43 and FOXOs compete for binding to 14-3-3 . To further examine the relationships among these three proteins , we studied the effect of mutant TDP-43 proteins lacking the nuclear localization signal ( ΔNLS ) or the nuclear export signal ( ΔNES ) on the interaction between14-3-3 and FOXO proteins using the same competitive co-immunoprecipitation assays described above . The ΔNLS and ΔNES mutations enhanced the relative enrichment of cytoplasmic and nuclear TDP-43 , respectively ( Figure S8 ) . The compartmentalization of the mutants was not exclusive , since residuals of the ΔNLS and ΔNES mutants could be found in the nuclear and cytoplasmic fractions . Nevertheless , the ΔNLS and ΔNES mutants allowed us to address how localization of TDP-43 affects the competitive binding of FOXOs to 14-3-3 proteins . We transfected HEK293T cells with tagged versions of FOXO3a , 14-3-3σ , and ΔNLS or ΔNES TDP-43 , and then performed co-immunoprecipitation experiments using 14-3-3 as the bait . The ΔNLS TDP-43 was more effective than ΔNES in interfering with the interaction between 14-3-3σ and FOXO3a , indicating that the cytoplasmic fraction of TDP-43 is capable of dissociating FOXO3a from its binding to 14-3-3 . This result suggests that the competitive binding of TDP-43 to 14-3-3 occurs at least in part in the cytoplasm ( Figure 5H ) . FOXOs have been reported to positively regulate protein quality control systems , including proteasomes and autophagy [72]–[74] . The regulation of FOXOs by TDP-43 suggests that TDP-43 may be a regulator of protein quality control . To explore this possibility , we studied the effects of loss or gain of TDP-43 on protein aggregation using a previously established SOD1 solubility assay [75] . The assay relies on differential detergent extraction to separate insoluble protein aggregates from soluble low-molecular weight monomers and oligomers . The G85R mutant , but not WT SOD1 , was found in the insoluble pellet , providing a sensitive reporter for protein aggregation . When TDP-43 was ectopically expressed in HEK293T cells , there was a significant increase in the level of insoluble G85R SOD1 aggregates , with no difference in the soluble level ( Figure 6A ) . However , when TDP-43 was knocked down in HEK293T cells , there was a marked reduction in the insoluble aggregates of G85R SOD1 , together with a decrease in the level of soluble mutant SOD1 ( Figure 6B ) . The WT SOD1 protein level was not changed when TDP-43 was knocked down or overexpressed , suggesting that TDP-43 negatively regulates the turnover of misfolded proteins .
In the present study , we have described a conserved signaling pathway in which TDP-43 senses stress and regulates protein quality control . This pathway is mediated , at least in part , by the ability of TDP-43 to regulate FOXO transcription factors . Therefore , TDP-43 , a known RNA binding protein , represents a link between protein quality control and RNA metabolism , indicating a novel layer of regulation of protein homeostasis imparted by RNA-processing proteins . We propose that TDP-43 mediates stress responses designed to maintain protein homeostasis by coordinating the attenuation of protein synthesis and the selective enhancement of protein quality control systems . First , the loss of TDP-43 from the nucleus and its localization to stress granules in response to cellular stress constitute an adaptive response to keep target mRNAs from active translation [76] . Second , the cytoplasmic translocation of TDP-43 promotes protein quality control , increasing the removal of misfolded proteins through the regulation of FOXOs described here . Thus , the connection between the two metabolic processes , RNA processing and protein quality control , represents a high-level regulation of protein homeostasis , accomplished through TDP-43 coordination . The regulation of FOXO transcription factor activity by TDP-43 has not been previously described . In this regulation , TDP-43 acts as a stress response switch to control FOXO activities . When the cell is in the resting state , TDP-43 is predominantly nuclear and exerts negative control over the FOXO transcription factors ( Figure 7A ) . Evidence for this model includes TDP-1's negative regulation of DAF-16 transcriptional activity in C . elegans ( Figure 1 ) and TDP-43's negative regulation of FOXO transcription activity in mammalian cells ( Figure 3 ) . When the cells are exposed to stress , TDP-43 temporarily leaves the nucleus and relaxes its negative control of the FOXO transcription factors . TDP-43 does not appear to influence the levels of FOXO proteins , which are governed by other complex regulations . Instead the increased fraction of cytoplasmic TDP-43 competes with FOXOs for binding to 14-3-3 proteins and drives the nuclear translocation of the FOXOs , further enhancing their transcription activity ( Figure 7B ) . The regulation of FOXOs by TDP-43 is consistent with the changes we observed in the cell's protein quality control systems . DAF-16 , the only ortholog of the FOXO transcription factors in C . elegans , promotes longevity by activating the transcription of stress-resistant genes , including molecular chaperones . Accordingly , the loss-of-function TDP-1 mutant has an increased lifespan that is DAF-16-dependent , and it also has reduced levels of misfolded proteins ( Figure 1 ) [55] , [56] . In mammalian cells , the activation of FOXO transcription factors , including FOXO1 and FOXO3a , induces autophagy [72]–[74] , [77]; the activation of FOXO3a also promotes proteasome activity [73] . In accordance with the negative regulation of FOXOs by nuclear TDP-43 , acute reduction of TDP-43 decreases the levels of misfolded and aggregated proteins ( Figure 6 ) , suggesting enhanced protein quality control . The coupling of RNA regulation to protein quality control by TDP-43 may represent a general coordination feature among stress-adaptive programs . There are other RNA-processing proteins that exhibit similar switching behaviors during stress responses . For example , a number of hnRNP proteins translocate to the cytoplasm from the nucleus in response to stress and are sequestered in punctate structures such as stress granules . We propose that , like TDP-43 , these RNA-processing proteins function as stress response switchers to maintain cellular homeostasis . The nucleocytoplasmic translocation and sequestration of these RNA-processing proteins into stress granules represent an adaptive loss of function that serves to temporarily curtail protein synthesis . TDP-43's role in controlling stress response and protein homeostasis may have important implications for neurodegenerative diseases . Rather than a simple gain- or loss-of-function scenario , we propose that a mechanism involving the compromised function of TDP-43 acting as a stress response switch underlies the etiology and pathology of TDP-43-related degenerative diseases . The TDP-43 proteinopathy is characterized by the cytoplasmic accumulation and concomitant nuclear clearance of the non-mutated form of the TDP-43 protein [6] . This common pathology in related neurodegenerative diseases is likely a result of the response to chronic stress . Moreover , the present study suggests that there is a duality in the cellular effects of TDP-43 cytoplasmic translocation and nuclear clearance . As a stress response , this acute reduction in TDP-43 function is protective , defending the cell against proteotoxicity through the pathway delineated above . However , if chronic stress persists , the resulting long-term reduction in TDP-43 function is deleterious . Without a resetting of the switch , the capacity of TDP-43 to buffer further stress would be lost . Also , over-activation of FOXOs promotes senescence or cell death [78] , suggesting that the activation of FOXOs by the TDP-43 switch may initiate a built-in program to eliminate over-stressed cells . This duality is analogous to that in ER stress , in which the UPR program has both a protective and a deleterious effect [5] . In conclusion , TDP-43 acts as a stress response switch to regulate RNA and protein metabolism in order to maintain protein homeostasis . The role of TDP-43 in the feedback regulation of the proteotoxic stress response and quality control provides a new perspective for TDP-43-related pathogenesis . Compromise of the stress response by proteins like TDP-43 may be a general mechanism underlying neurodegenerative diseases .
All C . elegans strains are on the N2 Bristol background and cultured under standard conditions at 20°C unless otherwise indicated . To generate the Psnb-1::TDP-1-YFP ( iwIs53 ) strain , a transgene DNA construct was generated by subcloning TDP-1 cDNA with a C-terminal YFP tag into a modified plasmid , pPD30_38 ( Fire Lab Vector , Addgene ) , with the promoter replaced with that of the snb-1 gene , as previous described [60] . The transgene DNA solution containing 20 ng/µl of the expression construct was injected into hermaphrodite gonads [79] , and multiple extrachromosomal lines were established based upon the fluorescent markers . These lines were further treated with 30 µg/ml trimethylpsoralen ( Sigma-aldrich ) and 300 µJ of 365 nm UV light to screen for integrated lines that stably expressed the transgenes . Each integrated line was backcrossed with the N2 strain at least four times . The Psnb-1::TDP-C25-YFP ( iwIs22 ) strain was reported previously [60] . Some strains were provided by the Caenorhabditis Genetics Center , which is funded by the NIH Office of Research Infrastructure Programs ( P40 OD010440 ) . The WT N2 C . elegans and mutant strains RB929 [tdp-1 ( ok803 ) ] , CF1038 [daf-16 ( mu86 ) ] , CB1370 [daf-2 ( e1370 ) ] , IW417 [tdp-1 ( ok803 ) ; daf-16 ( mu86 ) ] , and IW177 [tdp-1 ( ok803 ) ;daf-2 ( e1370 ) ] were cultured under standard conditions at 20°C . Newly laid embryos were synchronized within 2 h and transferred to fresh NGM plates , with 50 embryos per plate . These animals were transferred to new plates every day until they reached the post-reproductive stage and were allowed to age under normal culture conditions . Animals were checked daily and considered dead if they showed no response to probing with a platinum pick . The animals that crawled out of the plate , had vulval burst , or died with internally hatched larvae or “bags of worms” were censored . The day when embryos were synchronized was defined as the first day for lifespan analysis . The lifespan data were analyzed using Prism 5 software . C . elegans were cultured at 20°C until they grow to L4 larval stage . L4 larvae were individually transferred to new plates and cultured at 25°C . Every 24 hours , these animals were transferred to new plates at 25°C until they stopped producing eggs . After transferring , the eggs laid on the plates were counted . For locomotion measurement , L4 larvae grown at 20°C were subject to a thrashing assay . The animals were transferred into M9 buffer ( 3 mg/ml KH2PO4 , 6 mg/ml Na2HPO4 , 5 mg/ml NaCl , and 1 mM MgSO4 ) and allowed to adapt to the buffer for 1 min . Then the rate of body bending or thrashes for the animals was measured , with a thrash being counted when both the head and the tail bend over 45 degrees . To quantify the expression of specific genes in C . elegans , animals were harvested and total RNA was isolated using a phenol-chloroform extraction with TRIzol reagent ( Life Technologies ) , followed by purification with an RNeasy mini kit ( Qiagen ) . A two-step RT-PCR was employed to assess relative changes in transgenic transcripts using an iScript cDNA Synthesis Kit and an IQ SYBR Green kit ( Bio-Rad ) . Fluorescence was measured on a real-time PCR cycler ( Bio-Rad ) , and CT values were analyzed based on standard curves . The worm gdh-1 gene was used as a control . The sequences of all the primers used are listed in the Table S1 . HEK293T cells were grown in Dulbecco's modified Eagle's medium supplemented with antibiotics and 10% fetal bovine serum . Transient transfection of HEK293T was carried out with Lipofectamine 2000 according to the manufacturer's instructions ( Life Technologies ) . The primers for subcloning TDP-43 cDNA into pRK5-myc vector at Sal site and Gateway vector ( pDonor-221 ) are listed in the Table S1 . To knock down the expression of TDP-43 , we generated shRNA constructs targeting different regions of the TDP-43 transcript and containing a puromycin resistance gene . The TDP-43 shRNA constructs were cloned by inserting small hairpin oligonucleotides matching TDP-43 mRNA sequences into the pRFP-C-RS plasmid ( Origene ) using BamHI/HindIII restriction sites . The sequence of shRNA oligonucleotides ( i ) , ( ii ) , and ( iii ) as well as a control shRNA-RFP-C-RS are listed in the Table S1 . HEK293T cells were plated in 60-mm dishes at a density of 3 . 5×105 per well , then transfected with the shRNA constructs after 24 h . After 24 h , puromycin was applied at 3 µg/ml to select for positively transfected cells , and cells were harvested at 72 h post-transfection . A reporter construct , pGL3-FHRE-Luc was originally from M . Greenberg ( Addgene Plasmid 1789 ) , which expresses the firefly luciferase driven by a promoter containing three copies of forkhead responsive elements , was employed to measure FOXO transcription activity [80] . A control reporter construct , pSV40-Renilla ( Promega ) , which provides constitutive expression of Renilla luciferase , was used as an internal control . Cells were plated in 24-well plates at a density of 1×105 cells per well , and after 24 h , cells were transfected with expression plasmids of FOXOs , pSV40-Renilla , pGL3-FHRE-luciferase , or TDP-43 . At 48 h , luciferase activities were measured by using the Dual-Luciferase Reporter Assay System ( Promega ) on a Synergy H1 luminometer ( Bio-Tek ) . The experimental firefly luciferase activity was normalized to the control Renilla luciferase activity to reflect the FOXO activities . In addition to HEK293T cells , two U2OS stable cells lines expressing FOXO1 or FOXO3a were used ( Thermofisher ) . Cells were plated on coverslips pre-treated with polyethylenimine ( Sigma-aldrich ) , in 6-well plates . Cells were stressed with 0 . 4 M sorbitol ( Sigma-aldrich ) for 1 h or 0 . 2 M ( or 0 . 3 M ) NaCl for 3 h . Coverslips were washed twice with 1× PBS and then fixed with 4% paraformaldehyde ( PFA ) for 10 min at RT . After the PFA was washed , the cells were permeabilized with 0 . 1% Triton X-100 in 1× PBS for 10 min . After treatment with blocking buffer containing 2% BSA in PBS with 0 . 1% Triton X-100 for 30 min , the coverslips were incubated with primary antibody at 4°C overnight . The primary antibodies were diluted in blocking buffer; they were: polyclonal anti-TDP-43 , 1∶200 ( 10782-2-AP , ProteinTech ) ; monoclonal anti-G3BP , 1∶200 ( 611126 , BD Transduction Laboratories ) ; and monoclonal anti-phospho TDP-43 ( Ser409/410 ) , 1∶200 ( MABN14 , Millipore ) . The coverslips were then incubated with secondary antibody for 1 h at RT: goat anti-rabbit Alexa Fluor 488 , 1∶1000 ( A11008 , Life Technologies ) ; goat anti-mouse Alexa Fluor 555 , 1∶1000 ( A21422 , Life Technologies ) ; or goat anti-mouse Alexa Fluor 555 , 1∶1000 ( A11006 , Life Technologies ) . The coverslips were mounted in buffer with 2 . 5% DABCO , 100 mM Tris-HCl ( pH 8 . 8 ) , 50% glycerol , and 0 . 2 µg/ml DAPI . Images were collected with a Zeiss AxioObserver Z1 with an Apotome imaging system . Cells were lysed in buffer containing 50 mM Tris-HCl ( pH 8 . 0 ) , 150 mM NaCl , 0 . 4 mM EDTA ( pH 8 . 0 ) , 1% NP-40 , 0 . 05% sodium deoxycholate , and complete protease inhibitor cocktail ( 11836153001 ) . Cell lysates were incubated with anti-HA antibody ( H6908 , Sigma-aldrich ) overnight at 4°C before being centrifuged at 10 , 000× g for 10 min . Supernatant was transferred to clean tubes and incubated with protein G-Sepharose beads ( 17061801 , GE Healthcare life sciences ) for 1 h . After five washes with lysis buffer , the beads were resuspended in SDS sample buffer and boiled for 5 min before the eluted materials were subjected to standard western blot analysis: Protein samples were separated by SDS-PAGE and transferred to nitrocellulose membranes ( Bio-Rad ) . The membranes were blocked with 5% milk in 1× phosphate-buffered saline with 0 . 1% Tween 20 ( PBST ) and incubated with the following primary antibodies: anti-c-myc- horseradish peroxidase , 1∶5000 ( 11814150001 , Roche ) ; monoclonal anti-c-myc , clone 9E10 , 1∶3000 ( M5546 , Sigma-aldrich ) ; monoclonal anti-Flag M2 , clone M2 , 1∶5000 ( F3165 , Sigma-aldrich ) ; polyclonal anti-GAPDH , 1∶30 , 000 ( PA1-27448 , Thermofisher ) ; monoclonal anti-V5 , 1∶3000 ( 460705 , Life Technologies ) ; polyclonal anti-TARDBP , 1∶3000 ( 10782-2-AP , ProteinTech ) , polyclonal anti-PARP , 1∶1000 ( 9542 , Cell Signaling ) , polyclonal anti-Caspase 3 , 1∶1000 ( 9662 , Cell Signaling ) , and polyclonal anti-Cu/Zn SOD , 1∶3000 ( ADI-SOD-100 , Enzo life sciences ) . The following secondary antibodies were used: goat anti-rabbit IgG ( H+L ) -HRP conjugate , 1∶3000 ( 170–6515 , Bio-Rad ) ; goat anti-mouse IgG ( H+L ) -HRP conjugate , 1∶3000 ( 170–6516 , Bio-Rad ) ; goat anti-rabbit IgG IRDye , 1∶40 , 000 ( 680 LT , 926–68021 or 800 CW , 926–32211 , LI-COR ) ; and donkey anti-mouse IgG , 1∶40 , 000 ( 680 LT , 926–68022; or 800 CW , 926–32212 , LI-COR ) . After incubating with secondary antibodies , the membranes were developed on films or the Odyssey image system ( Li-COR ) . To isolate cytoplasmic and nuclear fractions , cultured mammalian cells were harvested in 1× PBS , centrifuged at 200× g for 1 min , and washed twice with 1× PBS . The cell pellets were resuspended in a cytoplasmic extraction buffer containing 10 mM HEPES ( pH 7 . 9 ) , 10 mM KCl , 1 . 5 mM MgCl2 , 0 . 1 mM EDTA , 0 . 5 mM DTT , 0 . 4% NP-40 , 0 . 5 mM PMSF , and complete protease inhibitor cocktail , then incubated on ice for 5 min . Cell lysates were then centrifuged at 600× g at 4°C for 3 min . Supernatants were transferred to clean tubes and saved as the “cytoplasmic fraction . ” The pellets were washed twice with cytoplasmic extraction buffer and centrifuged at 600× g at 4°C for 3 min . After washing , the pellets were resuspended in a nuclear extraction buffer containing 20 mM HEPES ( pH 7 . 9 ) , 420 mM NaCl , 1 . 5 mM MgCl2 , 25% glycerol , 0 . 5 mM PMSF , 0 . 2 mM EDTA , 0 . 5 mM DTT , and complete protease inhibitor cocktail and vortexed at room temperature for 1 min . The resuspended samples were incubated on ice for 10 min , then vortexed for 1 min and centrifuged at 16 , 000× g for 10 min . The supernatants were transferred to clean tubes and saved as the “nuclear fraction . ” A biochemical assay was used to detect insoluble aggregated proteins according to a previously described protocol , with some modifications [60] . Mammalian cells or C . elegans were extracted in 200 µl of buffer containing 10 mM Tris-HCl ( pH 8 . 0 ) , 100 mM NaCl , 1 mM EDTA ( pH 8 . 0 ) , 0 . 5% NP-40 , 50 µM iodoacetamine , and protease inhibitor ( P8340 , Sigma-aldrich ) by using a Bioruptor ultrasonicator at 4°C for 5 min . The lysates were then transferred to an Airfuge ultracentrifuge ( Beckman Coulter ) and centrifuged at 25 psi ( ∼130 , 000 g ) for 5 min . The supernatant was transferred to clean tubes and saved as the “soluble” fraction . The remaining pellet was again resuspended in extraction buffer , then sonicated for 5 min . This resuspended pellet was applied to the Airfuge and centrifuged at 25 psi for 5 min . The remaining pellet was transferred to 100 µl of resuspension buffer containing 10 mM Tris-HCl ( pH 8 . 0 ) , 100 mM NaCl , 1 mM EDTA ( pH 8 . 0 ) , 0 . 5% NP-40 , 0 . 5% deoxycholic acid , and 2% SDS , and sonicated for 5 min . This fraction was considered the “insoluble” protein aggregate fraction . Image J software was used to analyze the colocalization between TDP-43/pTDP-43 and G3BP , and the colocalization was measured by Pearson's correlative coefficient . p values for comparing Kaplan-Merier survival curves between groups were calculated by the Log-rank test . p values of qPCR , egg-laying , locomotion and Luciferase assay data were calculated with the Student's t-test .
|
TDP-43 is linked to pathogenesis of major neurodegenerative diseases , including amyotrophic lateral sclerosis ( ALS ) and frontotemporal dementia ( FTD ) . How TDP-43 contributes to the development of these degenerative diseases remains unsolved , and the full range of TDP-43 functions has yet to be established . In the present study , we explored a conversed function of TDP-43 in regulating protein homeostasis from C . elegans to mammals . Under conditions of stress , TDP-43 translocates from the nucleus to the cytoplasm , competes with FOXO transcription factors for binding to 14-3-3 proteins , and releases FOXO for nuclear translocation and activation . These data are consistent with the ability of TDP-43 to regulate protein aggregation . Together the results provide important insight into the role of TDP-43 in stress responses and disease mechanisms . Since chronic stress is associated with neurodegenerative diseases , the TDP-43 switch could be kept in overdrive mode in these disorders , with its capacity to buffer further stress and maintain protein homeostasis being compromised . This mechanism also suggests that other RNA-processing proteins that exhibit similar stress-induced behavior may be coupled to other cellular pathways to provide coordinated reprogramming in stress responses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"molecular",
"cell",
"biology",
"cell",
"biology",
"biology",
"and",
"life",
"sciences",
"molecular",
"biology"
] |
2014
|
RNA-Processing Protein TDP-43 Regulates FOXO-Dependent Protein Quality Control in Stress Response
|
Suppressor of cytokine signaling ( SOCS ) proteins are inducible feedback inhibitors of cytokine signaling . SOCS1−/− mice die within three weeks postnatally due to IFN-γ-induced hyperinflammation . Since it is well established that IFN-γ is dispensable for protection against influenza infection , we generated SOCS1−/−IFN-γ−/− mice to determine whether SOCS1 regulates antiviral immunity in vivo . Here we show that SOCS1−/−IFN-γ−/− mice exhibited significantly enhanced resistance to influenza infection , as evidenced by improved viral clearance , attenuated acute lung damage , and consequently increased survival rates compared to either IFN-γ−/− or WT animals . Enhanced viral clearance in SOCS1−/−IFN-γ−/− mice coincided with a rapid onset of adaptive immune responses during acute infection , while their reduced lung injury was associated with decreased inflammatory cell infiltration at the resolution phase of infection . We further determined the contribution of SOCS1-deficient T cells to antiviral immunity . Anti-CD4 antibody treatment of SOCS1−/−IFN-γ−/− mice had no significant effect on their enhanced resistance to influenza infection , while CD8+ splenocytes from SOCS1−/−IFN-γ−/− mice were sufficient to rescue RAG1−/− animals from an otherwise lethal infection . Surprisingly , despite their markedly reduced viral burdens , RAG1−/− mice reconstituted with SOCS1−/−IFN-γ−/− adaptive immune cells failed to ameliorate influenza-induced lung injury . In conclusion , in the absence of IFN-γ , the cytoplasmic protein SOCS1 not only inhibits adaptive antiviral immune responses but also exacerbates inflammatory lung damage . Importantly , these detrimental effects of SOCS1 are conveyed through discrete cell populations . Specifically , while SOCS1 expression in adaptive immune cells is sufficient to inhibit antiviral immunity , SOCS1 in innate/stromal cells is responsible for aggravated lung injury .
Influenza virus causes highly contagious acute respiratory disease . Despite vaccine availability , the virus remains a major worldwide health problem . Proper host immunity is essential for virus clearance and recovery , with T cells playing a major role [1] . Cytokines have pivotal effects in the initiation and regulation of immune responses . In recent years , SOCS proteins have been identified as a negative feedback loop to attenuate cytokine signaling [2]–[4] . The induction of SOCS proteins by influenza virus has been recently reported; however , the role of these cytoplasmic proteins in immune defense against influenza infection remains unclear [5]–[7] . SOCS1 is a critical feedback inhibitor of both IFN-γ/STAT1 [8] , [9] and IL-4/STAT6 signaling pathways [10] , [11] . Due to its mutual suppression of both Th1 and Th2 responses , i . e . , high IFN-γ levels inhibit IL-4/STAT6 signaling , whereas high levels of IL-4 suppress the IFN-γ/STAT1 pathway [12] , IFN-γ-induced SOCS1 production could increase the threshold of T cell responsiveness to IL-4 [4] , thereby facilitating the establishment of a Th1/IFN-γ-biased immune environment during influenza infection [13] . SOCS1−/− mice die by postnatal week three due to IFN-γ-induced hyperinflammation [14] , [15] . Although influenza infection induces strong T cell-dependent IFN-γ production , IFN-γ is dispensable for protective antiviral immunity [16] , [17] . Therefore , we developed SOCS1−/−IFN-γ−/− mice to evaluate the role of SOCS1 during influenza infection ( S1 Figure ) . We found that SOCS1 deficiency not only enhanced viral clearance but also improved the resolution of acute inflammation . These findings were in stark contrast to observations in other infectious disease models where SOCS1-deficient mice , including SOCS1−/−IFN-γ−/− and SOCS1+/− , demonstrated both enhanced IFN antimicrobial and detrimental pro-inflammatory activities [8] , [18] , [19] . Furthermore , here we demonstrate that these non-competing detrimental effects on host resistance to influenza infection are mediated by SOCS1 expression in different cell types . While SOCS1 in adaptive immune cells inhibits antiviral immunity , its presence in innate/stromal cells is responsible for aggravated lung damage .
C57BL/6 WT , IFN-γ−/− and SOCS1−/−IFN-γ−/− mice were intranasally infected with A/PR/8 influenza virus to determine the regulatory effect of SOCS1 on host defense . Similar viral clearance kinetics were detected in WT and IFN-γ−/− mice after a sublethal dose ( 50 PFU ) of PR8 infection ( Fig . 1A ) . This observation is consistent with other reports , which showed that IFN-γ is dispensable for immune defense against influenza infection [16] , [17] . Although viral burdens at the early stage of infection ( 4 dpi ) were comparable in WT and gene-deficient mice , SOCS1−/−IFN-γ−/− mice exhibited improved viral clearance at 7 dpi compared to both IFN-γ−/− and WT mice , as revealed by a10-fold decrease in viral burdens ( Fig . 1A ) . We also assessed influenza-induced lung vascular injury by quantitating albumin efflux into the airway . In both WT and IFN-γ−/− mice , albumin levels increased at 7 dpi and remained elevated at 11 dpi . In contrast , albumin concentrations in SOCS1−/−IFN-γ−/− airways were significantly decreased at 11 dpi ( Fig . 1B ) , indicating that SOCS1 deficiency is associated with attenuated lung vascular damage at the resolution phase of infection . Accordingly , SOCS1−/−IFN-γ−/− mice exhibited improved survival rates after an otherwise lethal dose ( 1000 PFU ) of PR8 infection ( Fig . 1C ) . We next sought to determine how SOCS1 may inhibit viral clearance by investigating protective antiviral immune responses in SOCS1−/−IFN-γ−/− mice . Alveolar macrophages ( CD11c+MHC−F4/80+ ) are the resident immune population in normal airways ( Fig . 2A&B ) . In response to infection , DCs are recruited to initiate adaptive immunity which is essential for elimination of influenza virus [1] , [20] . Consistent with their improved viral clearance , we detected increased numbers of DCs ( CD11c+MHChiF4/80low ) in influenza-infected SOCS1−/−IFN-γ−/− airways at 7 dpi ( Fig . 2A&B ) . Despite a lack of effect of IFN-γ on viral clearance , IFN-γ−/− mice showed reduced airway T cell numbers compared with WT animals at 11 dpi ( Fig . 3A&B ) , which is in agreement with the regulatory effect of IFN-γ on T cells themselves during influenza infection [21] . Importantly , SOCS1−/−IFN-γ−/− mice exhibited significantly increased levels of airway CD4+ ( Fig . 3A ) and CD8+ T cells ( Fig . 3B ) , as well as influenza-specific IgM and IgG production at 7 dpi ( Fig . 3C ) . In contrast , peak recruitment of T cells in WT mice was delayed to 11 dpi . Therefore , SOCS1-inhibited viral clearance is associated with delayed adaptive immune responses in IFN-γ−/− and WT mice . To determine how SOCS1 may exacerbate lung injury , we investigated its regulatory effect on influenza-induced inflammatory responses . SOCS1−/−IFN-γ−/− mice exhibited significantly decreased production of IL-6 and IL-10 at 7 dpi but increased IL-4 , IL-5 and IL-13 levels in airways during influenza infection ( Fig . 4 ) . Surprisingly , TNF-α , IL-1β and IL-17 levels were significantly increased in SOCS1−/−IFN-γ−/− mice as compared to IFN-γ−/− and WT animals at 11 dpi ( S2 Figure ) , indicating a disassociation between pro-inflammatory cytokine production and SOCS1-enhanced lung injury at this time point . We next analyzed influenza-induced inflammatory cell infiltration by flow cytometry . Inflammatory cells , including neutrophils and inflammatory monocytes , are recruited into the alveolar space following influenza infection [22]–[24] . Although it remains debatable whether these myeloid cells are essential for immune protection [25] , their prolonged presence exacerbates lung damage [26]–[28] . In WT and gene-deficient mice , inflammatory cell infiltrates increased at 7 dpi ( Fig . 5A ) . Interestingly , BALF cell analysis revealed a decrease in the accumulation of CD11b+Ly6B+ but an increase in CD11b+Ly6B− myeloid cells in SOCS1−/−IFN-γ−/− mice at 11 dpi ( Fig . 5A&B ) . Since both CD11b+Ly6G+ neutrophils [29] and CD11b+Ly6C+ inflammatory monocytes/macrophages [30] comprise the Ly6B-positive subpopulation ( Fig . 5B ) , the reduction in CD11b+Ly6B+ cells indicates that airway inflammatory cell infiltrates are decreased in SOCS1−/−IFN-γ−/− mice . Indeed , SOCS1−/−IFN-γ−/− mice exhibited significantly decreased neutrophil numbers at 11 dpi ( Fig . 5C ) . Therefore , SOCS1-enhanced lung injury is consistent with prolonged recruitment of neutrophils in IFN-γ−/− and WT mice during the resolution phase of infection . It is well established that CD4+ T cells play an important role in the elimination of influenza virus , mainly through promoting virus-specific antibody production [31] . We sought to determine the contribution of CD4+ T cells to enhanced antiviral immunity in SOCS1−/−IFN-γ−/− mice . Anti-CD4 antibody treatment delayed viral clearance in IFN-γ−/− mice but had no significant effect in SOCS1−/−IFN-γ−/− animals ( Fig . 6A ) . Conversely , anti-CD4 antibody treatment did not affect the severity of influenza-induced lung injury in either IFN-γ−/− or SOCS1−/−IFN-γ−/− mice ( Fig . 6B ) . Importantly , SOCS1−/−IFN-γ−/− mice demonstrated significantly improved antiviral immunity compared with IFN-γ−/− mice ( Fig . 6A&B ) , independent of CD4+ T cells and influenza-specific IgG production ( Fig . 6C ) . Therefore , although SOCS1−/−IFN-γ−/− mice exhibited increased CD4+ T cell and influenza-specific antibody responses , these animals were competent in CD4+ T cell-independent resolution of influenza infection . We next investigated whether CD8+ T cells in SOCS1−/−IFN-γ−/− mice were the effector cells responsible for enhanced viral clearance . Anti-CD8 antibody-treatment depleted CD8+ T cells in IFN-γ−/− mice; however , even with an increased dosage , it failed to adequately deplete CD8+ T cells in influenza-infected SOCS1−/−IFN-γ−/− mice ( S3 Figure ) . Therefore , as an alternative approach , we demonstrated that adoptive transfer of CD8+ T cells isolated from naïve SOCS1−/−IFN-γ−/− mice rescued RAG1−/− animals from lethal influenza infection ( Fig . 7A ) . This observation was consistent with significantly reduced viral burdens in these animals compared with unreconstituted RAG1−/− controls or RAG1−/− mice reconstituted with WT or IFN-γ−/− T cells ( Fig . 7B ) . Of note , there were limited numbers of virus-specific CD8+ T cells in naïve mouse spleens ( S4 Figure ) . We thus conclude that CD8+ T cells in SOCS1−/−IFN-γ−/− mice are sufficient for improved viral clearance . From the evidence presented above , it appeared that the immunopathological effects of SOCS1 might originate from inadequate viral clearance . However , adoptive transfer of CD8+ cells from SOCS1−/−IFN-γ−/− mice reduced viral burdens ( Fig . 7B ) but failed to alleviate lung injury in RAG1−/− mice ( Fig . 7C ) . To determine whether SOCS1 deficiency in other adaptive immune cells is required for optimal viral clearance and thereby amelioration of lung injury , we assessed antiviral immune responses and the severity of influenza-induced lung injury in RAG1−/− mice reconstituted with SOCS1−/−IFN-γ−/− adaptive immune cells . SOCS1−/−IFN-γ−/− splenocyte recipients demonstrated significantly reduced viral burdens at 11 dpi compared to IFN-γ−/− splenocyte recipients ( Fig . 8A ) , which coincided with increased numbers of CD8+ T cells in the airways of the former ( Fig . 8B ) . Conversely , CD4+ T cell recruitment ( Fig . 8B ) , antibody production ( Fig . 8C ) , and cytokine responses ( Fig . 8D ) did not differ significantly between SOCS1−/−IFN-γ−/− splenocyte recipients and their corresponding IFN-γ−/− splenocyte recipients . These results indicate that SOCS1 deficiency in adaptive immune cells alone is not sufficient for enhanced CD4+ T cell and influenza-specific IgG responses . Importantly , the attenuated lung injury observed in SOCS1−/−IFN-γ−/− mice could not be recapitulated by adoptive transfer of their splenocytes ( Fig . 8E ) . This result indicates that SOCS1 expression in innate/stromal cells is involved in enhanced lung injury . Collectively , these data establish a discrete contribution of SOCS1 to lung injury in addition to its inhibitory effect on viral clearance .
Here we demonstrate that mice with a targeted mutation in both SOCS1 and IFN-γ displayed increased adaptive immune responses at the early stage and reduced inflammatory cell infiltration at the resolution stage of influenza infection . These traits led to decreased viral loads and lung injury , and accordingly increased survival rates of SOCS1−/−IFN-γ−/− mice following influenza infection . Therefore , in the absence of IFN-γ the cytoplasmic protein SOCS1 not only inhibits viral clearance but also exacerbates inflammatory lung damage . The identification of these non-competing detrimental roles of SOCS1 could have important therapeutic implications for treating influenza infection . The published evidence demonstrates a role of IFN-γ in regulation of virus-specific CD8+ T cell homeostasis following a high dose of ( 6 . 8 log10 egg ID50 ) of A/HKx31 ( H3N2 ) influenza infection [21] . Likewise , we show that IFN-γ−/− mice had reduced airway T cell numbers compared with WT animals at the resolution phase of infection ( 11 dpi ) ( Fig . 3A&B ) . However , we did not detect a significant impact of IFN-γ or SOCS1 on virus-specific CD8+ T cell numbers in spleens following 50 PFU of PR8 infection ( S5A Figure ) . Moreover , the percentages of airway CD8+ T cells binding to DbNP366 or DbPA224 tetramers were comparable among WT , IFN-γ−/− and SOCS1−/−IFN-γ−/− mice at 7 dpi ( S5B Figure ) . Of note , these frequencies were significantly increased in all influenza-infected mice at 11 dpi , particularly DbNP366-specific T cells in SOCS1−/−IFN-γ−/− animals ( S5B Figure ) . Interestingly , when only CD8+ T cells were available for adaptive antiviral immunity ( Fig . 7& S6A Figure ) , in addition to a small but insignificant ( P = 0 . 18 ) increase in total T cell numbers ( S6B Figure ) , airway virus-specific T cells were significantly increased in RAG1−/− mice that had received SOCS1−/−IFN-γ−/− T cells ( S6C Figure ) as compared to RAG1−/− mice that had received IFN-γ−/− T cells . Together , these results suggest a greater antiviral potential of CD8+ T cells from SOCS1−/−IFN-γ−/− mice . Given that SOCS1 is an intracellular protein , these immune suppressive effects of SOCS1 are likely T cell-intrinsic . However , we cannot exclude the possibility that SOCS1 expression in other cell types inhibits the effector and expansion potential of naïve CD8+ T cells during T cell development . In addition to enhanced T cell responses , early virus-specific antibody production was also significantly increased in SOCS1−/−IFN-γ−/− mice ( Fig . 3C ) . Although in both IFN-γ−/− and SOCS1−/−IFN-γ−/− mice , virus-specific IgG production was dependent upon CD4+ T cells ( Fig . 6C ) , we detected temporarily increased virus-specific IgM production in SOCS1−/−IFN-γ−/− airways independent of CD4+ T cells ( S7 Figure ) . This observation is consistent with a previous report showing that early B cell responses to influenza virus is a T cell independent B-1 cell IgM responses [32] . Therefore , we propose that B-1 cell activity is increased in influenza–infected SOCS1−/−IFN-γ−/− mice , possibly due to enhanced type I IFN signaling [33] . Likely due to low percentages of B-1 cells in spleens , virus-specific antibody production did not differ significantly between RAG1−/− mice that had received SOCS1−/−IFN-γ−/− splenocytes and the corresponding IFN-γ−/− splenocyte recipients ( Fig . 8C ) . Importantly , these data suggest that B-2 cells from SOCS1−/−IFN-γ−/− mice are not sufficient for enhanced viral clearance . In addition to its critical feedback inhibition of IFN-γ signaling , it is noteworthy that SOCS1 is involved in negatively regulating the type I IFN and IFN-lambda signaling pathway [7] , [18] . We have previously shown that type I IFN production is induced at the early phase of influenza infection [13] . These findings raise the possibility that the reduced viral burden observed in SOCS1−/−IFN-γ−/− mice was due to enhanced IFN antiviral function . In addition , it has also been reported that SOCS1 regulation of type I IFN is responsible for resistance to Semliki Forest virus infection independent of IFN-γ [18] . Moreover , SOCS1-knockdown transgenic mice showed less viral load compared with BALB/c WT mice on day 3 after A/WSN/33 influenza virus infection [7] . However , in the current study , viral burdens at the early phase of infection ( 4 dpi ) were similar among WT , IFN-γ−/− and SOCS1−/−IFN-γ−/− mice , suggesting an insignificant effect of SOCS1 on direct innate control of viral replication in epithelial cells . Probably due to the antagonistic effect of influenza virus NS1 protein on type I IFN activity and the redundant role of IFN-lambda in viral clearance [7] , [34] , BALB/c IFNAR1−/− mice have been shown to be as resistant to influenza infection as WT controls [35] . Conversely , increased susceptibility of C57BL/6 IFNAR1−/− mice to influenza infection results from severe lung inflammation rather than defective viral clearance [24] . Furthermore , using an adoptive transfer system , we showed that CD8+ T cells in SOCS1−/−IFN-γ−/− mice were sufficient to reduce viral burdens , which is consistent with the reported negative role of SOCS1 during T cell priming and effector functions [36] . Therefore , although a direct antiviral function of type I IFN and IFN-lambda has been demonstrated in other infectious disease models [7] , [18] , [37] , we propose that SOCS1 inhibition of antiviral activities of these IFNs in stromal and innate immune cells is not essential for enhanced viral clearance in SOCS1−/− IFN-γ−/− mice . Considerable information is now available regarding immune mechanisms essential for elimination of influenza virus [16] , [38] . Conversely , little is known about the resolution of inflammation after viral clearance , despite the fact that lung immunopathology is often the main cause of influenza-related morbidity and mortality [17] , [39] . Studies in humans and mice suggested that immunological factors critical for efficient viral clearance are also involved in mediating tissue damage [17] . Alternatively , severe immunopathology could be secondary and the consequence of inability to resolve lethal infection [40] . We did not observe a significant correlation between viral loads and lung vascular injury in our non-lethal influenza infection model . Importantly , we found that the detrimental effects of SOCS1 on both viral clearance and lung injury are conveyed through distinct and non-competing cellular pathways as such that , SOCS1 deficiency in adaptive immune cells was sufficient for enhanced viral clearance , while SOCS1 deficiency in innate/stromal cells was required for resolution of pathological damage . Strong evidence to support this possibility came from observations that amelioration of lung injury occurred in SOCS1−/−IFN-γ−/− mice after CD4+ T cell depletion ( Fig . 6B ) , but not in RAG1−/− animals reconstituted with SOCS1−/−IFN-γ−/− adaptive immune cells ( Fig . 8E ) , despite the fact that viral burdens were barely detectable in both groups ( Figs . 6A & 8A ) . Therefore , reduced virus burden alone does not account for the ameliorated immunopathology in influenza-infected SOCS1−/−IFN-γ−/− mice . Of note , RAG1−/− mice reconstituted with IFN-γ−/− adaptive immune cells demonstrated increased lung injury following influenza infection . This is consistent with a previous report where CD8+ T cell IFN-γ production ameliorated the severity of influenza-induced inflammation and lung damage in an adoptive cell transfer model [41] . SOCS1 is also a critical feedback inhibitor of the IL-4 signaling pathway responsible for anti-inflammatory action and tissue repair [10] . However , it has been shown that CD4+ T cell expression of Th2-type cytokines including IL-4 and IL-5 does not promote recovery from viral infection , but rather increases lung viral burdens [42] . Although the role of IL-4 during influenza infection remains debatable , SOCS1−/−IFN-γ−/− mice showed increased IL-4 production following influenza infection . Moreover , a positive correlation was observed with IL-4 levels and the severity of lung injury , in that IL-4 production remained elevated in SOCS1−/−IFN-γ−/− mice even after CD4+ T cell depletion ( S8 Figure ) but not in RAG1−/− mice reconstituted with SOCS1−/−IFN-γ−/− adaptive immune cells ( Fig . 8D ) . Therefore , it is possible that T helper cell-independent IL-4 production is beneficial to the resolution of pathological changes resulting from influenza infection . As a major anti-inflammatory cytokine , IL-10 has been shown to be crucial in regulating the magnitude of inflammation during influenza infection [43] . Similar to IL-6 , peak IL-10 production was significantly decreased in SOCS1−/−IFN-γ−/− airways , which correlated with their reduced viral burdens at 7 dpi . In contrast , at the resolution phase of infection , IL-10 level was slightly increased in SOCS1−/−IFN-γ−/− mice relative to the low levels in WT and IFN-γ−/− mice , which may contribute to the attenuation of lung inflammation after viral clearance . Moreover , multiple studies have shown that Type I IFN can suppress immune responses by driving production of anti-inflammatory cytokines [44] . Therefore , although we propose that enhanced viral clearance in SOCS1−/−IFN-γ−/− mice is not due to increased IFN/STAT1 activation at the acute phase of infection , these SOCS1-regulated pathways may contribute to the resolution of inflammation after viral clearance . We show that SOCS1 in innate/stromal cells is involved in aggravated lung injury , consistent with influenza-induced SOCS1 expression in both cell types ( S9 Figure ) . However , both innate and stromal cells are known to produce as well as respond to anti-inflammatory cytokines . Furthermore , both cell types are directly involved in acute lung injury . Therefore , it would be intriguing albeit challenging , to determine the cellular/molecular pathways responsible for amelioration of lung damage after influenza infection . The immune suppressive role of SOCS1 had been previously demonstrated in SOCS+/− mice [40] , [45] . However , we found these SOCS1-haplodeficient mice were susceptible to influenza infection similar to WT animals ( S10 Figure ) . Although IFN-γ is dispensable for protection against influenza infection , SOCS1-deficient CD8+ T cells from SOCS1−/− IFN-γ−/− mice were sufficient to improve antiviral immunity and , furthermore , SOCS1-enhanced lung injury occurred after IFN-γ production was diminished in WT mice , we cannot exclude the possibility that these detrimental effects of SOCS1 were significant only in the absence of T cell IFN-γ production . Nonetheless , to our knowledge , there is no report showing the regulatory role of SOCS1 during the course of influenza infection , and importantly , no evidence directly linking SOCS1 with excessive inflammation in other infectious disease models . The distinct and non-competing detrimental roles of SOCS1 , as revealed in this study , make it an appealing target in the design of effective immunotherapies for combating influenza infection .
All animal experiments were approved by Albany Medical College Animal Care and Use Committee ( Protocol number 11-04004 ) and University of Nebraska Medical Center ( Protocol number 13-057-09-FC ) , and all experiments were carried out in accordance with Albany Medical College and University of Nebraska Medical Center Assurance of Compliance with PHS Policy on human Care and Use of Laboratory Animals , which is on file with the Office of Protection from Research Risks , NIH . Specific pathogen-free , 8–10 week old C57BL/6 WT , RAG1−/− and IFN-γ−/− mice were purchased from the Jackson Laboratory ( Bar Harbor , ME ) and bred locally under pathogen-free conditions . C57BL/6 SOCS1+/− mice were obtained from Dr . Warren Alexander ( Walter and Eliza Hall Institute ) [2] , [46] and then mated with C57BL/6 IFN-γ−/− mice from the Jackson Laboratory . Mice were genotyped for deficiency in both SOCS1 and IFN-γ alleles by PCR analysis of genomic DNA isolated from tail tips , using the SOCS3 gene as a positive control ( S1A Figure ) . Primers used for SOCS1: gcatccctcttaacccggtac and aaatgaagccagagaccctcc; for IFN-γ: agaagtaagtggaagggcccagaag and agggaaactgggagaggagaaata; and for SOCS3: gagttttctctgggcgtcctcctag and tggtactcgcttttggagctgaa . Mice deficient in both SOCS1 and IFN-γ alleles were selected and bred locally for the studies . SOCS1−/−IFN-γ−/− mice appeared to have normal CD11b+ myeloid cell subsets in blood ( S1B Figure ) and reached to adulthood without any overt signs of pathology [46] . Viral challenge was performed with A/PR8/34 influenza virus ( Charles River Laboratories ) administered i . n . to anesthetized , sex and age-matched adult mice in 50 µl of sterile PBS . Titers of virus stocks and viral levels in the bronchoalveolar lavage fluids ( BALF ) and lungs of infected mice were determined by plaque assays on MDCK cell monolayers as previously described [47] . BALF samples were collected by making an incision in the trachea and lavaging the lung twice with 0 . 8 ml PBS , pH 7 . 4 . Total leukocyte counts were determined using a hemacytometer . For flow cytometric analysis , BALF cells were incubated with 2 . 4G2 mAb against FcγRII/III , and stained with PE-Cy7-conjugated anti-CD11c ( BD Biosciences ) , APC-Cy7-conjugated anti-CD11b ( BD Biosciences ) , PE-conjugated Ly6B ( Abcom ) , PCP-Cy5-conjugated anti-Ly6C ( eBiosciences ) and PE-Cy7 conjugated anti-Ly6G mAb ( BD Biosciences ) for myeloid cell analysis . APC-conjugated anti-CD11c , APC-Cy7-conjugated anti-CD11b ( BD Biosciences ) , PE-conjugated anti-MHC II ( BD Biosciences ) and PCP-Cy5-conjugated anti-F4/80 ( eBiosciences ) were used for DC analysis . PCP-Cy5-conjugated anti-CD3 ( Biolegend ) , APC-conjugated anti-CD4 ( BD Biosciences ) and APC-Cy7-conjugated anti-CD8 mAb ( BD Biosciences ) were used for T cell analysis . Splenocytes and BALF cells were stained with Tetramer Alexa 647-Labeled H-2D ( b ) /PA224 ( SSLENFRAYV ) and BV421-Labeled H-2D ( b ) /NP366 ( ASNENMETM ) , using FITC-conjugated anti-CD3 ( BD Biosciences ) , APC-Cy7-conjugated anti-CD4 ( BD Biosciences ) and PE-conjugated anti-CD8 mAb ( BD Biosciences ) for cell surface markers . The stained cells were analyzed on a BD FACSCanto or BD LSRII-green using FlowJo and BD FACSDiva software analysis . BALF samples were harvested and assayed for TNF-α , IL-1β , IL-6 , IL-17 , IL-10 , IL-4 , IL-5 , IL-13 and IFN-γ by ELISA using commercially available kits from BD Biosciences and eBioscience ( San Diego , CA ) . Concentrations of virus-specific antibodies in BALF samples were measured by ELISA . Briefly , Maxisorp ELISA plates ( Nalge Nunc International ) were coated overnight at 4°C in PBS containing 2 µg/ml Fluvirin ( Chiron Vaccines , Liverpool , UK ) . After washing , 2-fold dilutions of BALF samples were incubated in the plates at 37°C for 2 hr . Detection was performed using biotin-labeled goat anti-mouse IgM or IgG antibodies ( Southern Biotechnology Associates , Birmingham , AL ) . Finally , an avidin-HRP complex ( BD Biosciences ) was added and OptEIA substrate solution ( BD Biosciences ) was used for signal development . BALF samples were harvested and assayed for albumin by ELISA using a commercially available kit from Bethyl Laboratories ( Montgomery , TX ) . Anti-CD4 and anti-CD8 mAbs were purified from culture supernatants of the GK1 . 5 and 53-6-72 hybridomas , respectively [13] . C57BL/6 mice were injected i . p . with 500 µg of mAb daily for three days before influenza infection , followed by every three days after infection ( 18 ) . The efficiency of pulmonary CD4+ and CD8+ T cell depletion after influenza infection was determined by flow cytometric analysis of isolated BALF cells and splenocytes [13] . C57BL/6 RAG1−/− mice were injected i . p . with splenocytes ( 2×107 cells/mouse ) isolated from naïve IFN-γ−/− or SOCS1−/−IFN-γ−/− mice and infected with 50 PFU PR8 10 weeks after cell transfer [48] . In a separate experiment , total CD8+ cells were isolated from the spleens of naïve IFN-γ−/− or SOCS1−/−IFN-γ−/− mice through negative magnetic selection using a Mouse CD8+ T Cell Isolation Kit ( STEMCELL Technologies ) . The purity of CD8+ T Cells was determined to be >90% by flow cytometry . RAG1−/− mice were injected i . p with 107 CD8+ cells and infected with PR8 10 days after cell transfer [49] , [50] . Influenza-induced airway recruitment of adoptively transferred CD8+ T cells was confirmed by flow cytometric analysis . Alveolar macrophages and BALF dendritic cells were purified using a Mouse CD11c Positive Selection Kit ( STEMCELL Technologies ) . After preparation of single cell suspensions , lung epithelial cells were enriched by negative selection using a Mouse Epithelial Cell Enrichment Kit ( STEMCELL Technologies ) . Total RNA derived from naïve and post-influenza-virus-infected cells was characterized by using iScript Reverse Transcription and iTaqUniversal SYBR Green Supermix ( Bio-Rad ) on a Bio-Rad CFXConnet Real-Time system . The primer sequences were as following: Fwd 5′- ACAAGCTGCTACAACCAGGG-3′ and Rev 5′-ACTTCTGGCTGGAGACCTCA-3′ for SOCS1; and Fwd 5′-CATAACCTGGTTCATCATCGC-3′ and Rev 5′- GGAGCGGTAGCACCTCCT-3′ for HPRT . Results are expressed as the mean ± s . d . Significant differences between experimental groups were determined using a Student t-test ( to compare two samples ) , or an ANOVA analysis followed by Tukey's multiple comparisons test ( to compare multiple samples ) in GraphPad Prism 6 ( La Jolla , CA ) . Survival analyses were performed using the Kaplan-Meier log rank test . For all analyses , a P value<0 . 05 was considered to be significant .
|
Cytokines are critical in regulating the balance between protective immunity and detrimental inflammation during influenza infection . Suppressor of cytokine signaling ( SOCS ) proteins are inducible feedback inhibitors of cytokine signaling . Using gene-deficient and infectious animal models , we determined how SOCS1 regulates immune defense against influenza infection . We show that the intracellular protein SOCS1 not only inhibits adaptive antiviral immune responses but also exacerbates inflammatory lung damage . These detrimental effects of SOCS1 are conveyed through discrete cell populations . Specifically , while SOCS1 expression in adaptive immune cells is sufficient to inhibit antiviral immunity , SOCS1 in innate/stromal cells is responsible for aggravated lung injury . To our knowledge , there is no report showing the regulatory role of SOCS1 during the course of influenza infection , and importantly , no evidence directly linking SOCS1 with excessive inflammation in other infectious disease models . The distinct and non-competing detrimental roles of SOCS1 , as revealed in this study , make it an appealing target in the design of effective immunotherapies for combating influenza infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology",
"and",
"life",
"sciences",
"immunology"
] |
2014
|
Expression of Suppressor of Cytokine Signaling 1 (SOCS1) Impairs Viral Clearance and Exacerbates Lung Injury during Influenza Infection
|
There are economic and physical limitations when applying prevention and control strategies for urban vector borne diseases . Consequently , there are increasing concerns and interest in designing efficient strategies and regulations that health agencies can follow in order to reduce the imminent impact of viruses like Dengue , Zika and Chikungunya . That includes fumigation , abatization , reducing the hatcheries , picking up trash , information campaigns . A basic question that arise when designing control strategies is about which and where these ones should focus . In other words , one would like to know whether preventing the contagion or decrease vector population , and in which area of the city , is more efficient . In this work , we propose risk indexes based on the idea of secondary cases from patch to patch . Thus , they take into account human mobility and indicate which patch has more chance to be a corridor for the spread of the disease and which is more vulnerable , i . e . more likely to have cases ? . They can also indicate the neighborhood where hatchery control will reduce more the number of potential cases . In order to illustrate the usefulness of these indexes , we run a set of numerical simulations in a mathematical model that takes into account the urban mobility and the differences in population density among the areas of a city . If we label by i a particular neighborhood , the transmission risk index ( TRi ) measures the potential secondary cases caused by a host in that neighborhood . The vector transmission risk index ( VTRi ) measures the potential secondary cases caused by a vector . Finally , the vulnerability risk index ( VRi ) measures the potential secondary cases in the neighborhood . Transmission indexes can be used to give geographical priority to some neighborhoods when applying prevention and control measures . On the other hand , the vulnerability index can be useful to implement monitoring campaigns or public health investment .
Dengue , Zika and Chikungunya are deseases of major concern in many countries [1 , 2] . In particular , Dengue is of major importance due to its epidemiological magnitude [3 , 4] . On the other hand , in many countries Zika and Chikungunya can be considered as new diseases for which a great portion of the population is susceptible . This feature make them a major epidemiological threat . These three deseases are vector borne , transmitted by the bite of Aedes aegypti mosquito [1 , 5] . Thus the greatest efforts in prevention and control are in reducing the mosquito population . This can be done by spying or by reducing the hatcheries . The A . aegypti is a domestic species in the sense that it oviposit its eggs in human made containers with clean water , so it is principally found around houses [4 , 6] . The containers used by the mosquitoes for reproducing can be trash in yards or streets filled with water from rain , drums that some people use to accumulate water in case it goes scarce , or even pools and swimming pools [7] . In addition to fumigation , other strategies has been implemented to control vector reproduction capacity , like picking up unprocessed trash and abatization . The implementation of information campaigns like promoting to cap water recipients , the use of repellents and mosquito nets , or even visit the physician at first symptoms have been also important . Implementing this measures cost money , so in big to medium cities is not normally possible to apply them in all the urban area , and a lot less in a whole country . Thus , local governments are forced to take a decision about which measures to implement with the resources at hand and where they are going to be implemented [8] . Thus , in the process to better manage the resources they always face the following questions: Where should control measures be implemented ? Which kind of measures should be implemented in order to get the best impact in controlling the dispersion of the disease ? Nowadays , the traditional control and preventive measures are based on population indexes [5 , 9 , 10] . That means that if the larvae density is higher than a certain empirically pre-established threshold , alert is raised , and in case there are enough resources , hatchery control is carried out . These traditional indexes used by entomologists have the following disadvantages . First , they are reactive and not preventive , because of the measures are taken once a high density of mosquitoes population is detected and nothing is done to prevent its growth before that . Second , even if vector density is one of the main factors promoting the disease transmission , this kind of indexes overlook other important factors like human density and mobility [11 , 12] . Human mobility and density play an important role not only in outbreaks but also in the maintenance of endemic states [12–16] . Thus , either an strategy to reduce the impact of an outbreak or an strategy to eliminate an endemic situation should take into account these human factors [17 , 18] ( See [19] to look some current methods to prevent malaria disease importation in countries by classifying human movement in: people in the eliminating region , during transit , in the endemic region , and upon return to the eliminating country . ) . This is also true because of these kind of indexes do not take into account the dynamics of the disease that is determined by the transmission mechanisms [20–23] . In this work , we derive risk indexes based in the idea of secondary cases . Then , we obtain explicit expressions for them in the frame of a dynamical mathematical model for the spread of Aedes aegypti borne diseases . We propose a model within a meta-population framework with a Lagrangian approach in order to take into account human intra-urban mobility . The proposed indexes arise in a natural way from the dynamical model using the theory of dynamical systems and networks [14 , 24–28] . We focus our attention in two types of indexes . One of them , is a measure of the potential transmission and spread of the disease caused by human behavior . The other kind of index is a measure of the transmission caused by the particular spatial distribution of mosquitoes . Specifically , information campaigns targeted at promoting some convenient behaviors like going to hospitals at first symptoms , use of repellents , mosquito nets and large cloths can be guided by the human transmission risk index ( TRi ) . This is so , because this transmission risk index is a measure of the potential secondary infections the inhabitants of a particular neighborhood cause in the whole system . On the other hand , abatization , fumigation and hatchery elimination targeting at reducing vector population can be guided by the vector transmission risk index ( VTRi ) . This index is a measure of the potential secondary cases that the mosquitoes of a certain neighborhood cause in the system . Thus , this set of indexes can be used to guide a complex strategy in which the resources focused in changing vector population or human habits do not necessarily are applied in the same place . In addition to this , we also find useful the vulnerability risk index ( VRi ) to guide monitoring actions of early warning protocols as this index measures the potential secondary cases in a particular neighborhood caused by the whole system . Even if this indexes can be used to guide control measures they are build to guide prevention measures , thus they are independent of an outbreak state . This is a main difference between the proposed risk indexes and optimal control strategies where the state of the epidemics needs to be known thus being reactive and not preventive . While the proposed indexes consider population densities , they also take into account human mobility , so they can be used to propose a global control strategy . That means that the risk indexes take into account that a neighborhood with important human inward flux and outward flux has more chance to be a corridor for the spread of the disease . Thus , the kind of questions that can be answered using these indexes are: Which area is more likely to act as a corridor and which is more vulnerable , i . e . more likely to have cases ? In which neighborhood the hatchery control will reduce more the number of potential cases ? In which neighborhood will the resource allocation be more effective in surveillance of cases and immediate attention ?
We look for to define summary measures that capture important information of how a virus transmitted by a vector ( like the A . aegypty mosquito ) is spread in a region . Let Ω be the spatial region where the vector-borne disease transmission will be analyzed . Such region could be a city or a village which can be divided into N disjoint subregions Ωi , such as neighborhoods , which we call patches . Thus , Ω = ∪ i = 1 N Ω i . Hosts and vectors coexist , but each patch has its particular social and ecological features , i . e . human population , transportation and mobility habits of the inhabitants , and mosquitoes density can differ from one neighborhood to other . Because of the A . aegypty has a very limited range of flight , the virus is mainly spread among patches just by human mobility . In general , the spread process caused by human mobility is as follows . An individual that normally is in patch i ( a resident ) travels to patch k , where they becomes infected by a mosquito . Then they travels again to an other patch j , where a mosquito there is infected by them . The result is that the virus was spread from patch k to patch j by a resident from patch i . We can illustrate the generality of this with two particular cases . When i = j , it corresponds to an individual introducing the disease in their own patch because they got infected in a different patch . On the other hand , i = k represents a case when an already infected individual travel to a different patch and spread the virus in that particular patch . The secondary cases caused by a single infected individual at a completely susceptible population , normally called the basic reproduction number R0 , is one of the most important summary measures that describe the severity of an epidemic outbreak . In what follows we extend this idea to include geographical information of where the secondary cases where produced and which is the origin of the infected hosts . First we denote R k j ( v ) as the secondary human infections of residents from patch j produced by an infected vector in patch k in the disease-free state . In a similar way , we define R i k ( h ) as the number of vector secondary cases in patch k caused by a single infected resident in patch i . These quantities can be hard or even impossible to be measured directly , but they may be inferred once a mathematical model for the disease is proposed . A natural way of deriving useful risk measures from these quantities is to obtain the secondary infections R i ( h ) generated by a single individual of patch i in the total susceptible population of the system: R i ( h ) = ∑ j = 1 N ∑ k = 1 N R i k ( h ) R k j ( v ) . ( 1 ) Here R i k ( h ) R k j ( v ) is the number of human-human secondary infections that a resident of patch i generated in residents of patch j that were produced in patch k . Summation in k is to take into account all the possible places where the contagion could take place . Summation in j is to account for all the secondary human infections that a single resident of i produces in all the system . Thus R i ( h ) is a measure of the contagion capacity of residents from the patch i . On the other hand , the classic definition of risk is the probability of occurrence of an unwanted event multiplied by the consequence of the event [29] . Following this definition , the transmission risk index TRi is the probability Pi that a resident of patch i gets infected , multiplied by the secondary cases it generates ( See Fig ( 1 ) ) . Thus , it is given by T R i = P i R i ( h ) ( 2 ) and indicates the risk of the neighborhood i to become the main disperser of the disease at the beginning of an epidemic . On the other hand , the number of secondary cases of patch j residents caused by a single infected resident of patch i is given by ∑ k = 1 N R i k ( h ) R k j ( v ) . ( 3 ) The summation in the previous expression accounts for the vector contagions in all patches . We can now define a Vulnerabiliy Risk index VRj for patch j as ( See Fig ( 1 ) ) V R j = ∑ i = 1 N ∑ k = 1 N P i R i k ( h ) R k j ( v ) . ( 4 ) Finally , we define the Vector Transmission Risk index VTRi as the secondary human infections R i ( v ) caused by an infected vector in patch i multiplied by the probability of a vector of patch i becomes infected at the beginning of an epidemic . Then the VTRi is expressed as VTRi=P˜i ( 1− ( 1−1wi ) Nvi ) Ri ( v ) , ( 5 ) where P ˜ i is the probability of the original infected host is in patch i , irrespective of where they came from . Also , ( 1− ( 1−1wi ) Nvi ) is the probability of it gets bitten by a mosquito in patch i , and R i ( v ) is calculated as R i ( v ) = ∑ j = 1 N R i j ( v ) . ( 6 ) In this case R i ( v ) represents the system-wide secondary human infections caused by a single infected vector in patch i . This index will be important just in the cases when the number of mosquitoes is large , so we can approximate it by V T R i ≃ P ˜ i ( 1 - e - N v i / w i ) R i ( v ) for N v i ≫ 1 . ( 7 ) Our model aims to capture the dynamics of a virus transmitted by vectors ( like the Aedes aegypty mosquito ) . Important viruses transmitted by this species are Dengue , Zika and Chikungunya . In order to take into account human mobility and density population within the city , we divided it into different areas or neighborhoods that we will call patches . In each patch hosts and vectors coexist , and every one has its particular social and ecological features , i . e . human population , transportation and mobility habits of the inhabitants , and mosquitoes density can differ from one neighborhood to other . In addition , hosts travel among patches . In this sense , patches are said to be connected . The model is thus built in two steps . First we build a general model for a single patch , that describes the dynamics of a vector-borne disease in a single patch . After that , we extend the local model for multiple patches , representing the whole city and mobility effects .
In order to find an explicit expression for the secondary human cases R k j ( v ) caused by a single infected mosquito in patch k , we have to multiply the rate of infections generated from mosquitoes of patch k to visitors from patch j , i . e . β S h j p j k I v k w k times the characteristic duration time that a mosquito remains infected , 1/μk . Then we evaluate this quantity with a single infected vector in the disease-free equilibrium . That is Rkj ( v ) =βShjpjkIvkμkwk|Shj=Nhj , Ivk=1=βNhjpjkμkwk . ( 20 ) In a similar way , from the proposed model an explicit expression for secondary vector infections in patch k that were caused by travelers from patch i at the beginning of an epidemic is R i k ( h ) = β ′ p i k N v k γ w k . ( 21 ) Thus , R i ( h ) is given by R i ( h ) = ∑ j = 1 N ∑ k = 1 N R i k ( h ) R k j ( v ) = β β ′ γ ∑ k = 1 N p i k N v k μ k w k . ( 22 ) If we assume that each person in the system has equal chance of starting the outbreak , then we have a particular case where Pi = Ni/Nh , and the transmission risk index becomes T R i = N h i N h R i ( h ) = β β ′ N h i γ N h ∑ k = 1 N p i k N v k μ k w k . ( 23 ) In a similar way , the vulnerability index takes the form V R j = ∑ i = 1 N ∑ k = 1 N N h i N h R i k ( h ) R k j ( v ) = β β ′ N h j γ N h ∑ k = 1 N p j k N v k μ k w k , ( 24 ) and finally the vector transmission risk is V T R i ≃ w i N h ( 1 - e - N v i / w i ) R i ( v ) , ( 25 ) where R i ( v ) = ∑ j = 1 N R i j ( v ) = β μ i , ( 26 ) and we have taken the particular case where P ˜ i = w i N h . For the sake of simplicity , we consider this simple case . However , other probability distributions which take into account well known factors of introduction of vector-borne diseases into a population , as importation by travellers or some trading businesses , could be considered at this point . In order to show how the risk indexes can be used to guide control strategies we simulate an ensemble of Dengue outbreaks using the model ( 14 ) – ( 18 ) . First we perform an ensemble of 200 simulations with parameter values shown in Table 1 . For each simulation , we choose randomly the initial infected host individual . We used 5 patches and the number of humans and carrying capacity in each patch was taken randomly in the range 4000-10000 and 1000-2800 respectively . See Table 2 for the particular values . We used two types of mobility matrix: the first is an unrestricted mobility , where any average fraction of people from patch i can go to any other patch j; the second type of tested mobility matrix resembles a network constructed with the Barabasi-Albert algorithm [34] , in which there exist patches that are more visited than others . The particular mobility matrices used in the first and second type of mobility are labeled with P1 and P2 , respectively , and its corresponding values are showed in the S1 Appendix . According to the definition , the vulnerability index VRi stands for the expected number of secondary human cases in patch i produced in a totally susceptible population by an initial sick host , assuming we do not know where they comes from . Consequently , this index gives an idea of the severity of the epidemic in the corresponding patch at the very beginning of it: the more large this index is , the more great the number of infected hosts will be in this patch . Concretely , the patch with greatest vulnerability index VRi corresponds to the patch with more infections at the first stages of the outbreak , as can be seen in Fig 4 for the above types of mobility . Note that this picture could change as long as the epidemic evolves to a different state from the initial totally susceptible one . We then compare the effect of applying an specific control measure in any other patch ( randomly selected , for instance ) with the effect of applying the same control measure but in the patch indicated by an adequate index ( in relation to the control measure ) . Following the risk indexes definition , the transmission risk index TRi measures the transmission power of a given patch; that is , the secondary cases an initial sick host in patch i produces in a complete totally susceptible population , weighted by the probability of patch i being the initial focus of the epidemics . Then , the patch with highest transmission risk index TRi is the candidate to become the main disperser of the disease at the fist stage of the epidemics . This index can be linked with control measures on human populations . Therefore , the first tested control measure was the fast isolation of infected people by hospitalizing them as soon as an infection is detected . We simulate this by increasing the recovery rate γ of a single patch . Fig 5 shows , as expected , that this measure is more effective when applied in the patch with greatest transmission index TRi than in any other patch , on average . One can see in Fig 5 that the amount of total infected hosts Ih is the lowest one for t ≤ 50 when the disease control measure is applied to the patch with largest transmission index TRi . Finally , analogously to the previous one , the vector transmission risk index VTRi measures the transmission power of a given patch taken into account its vector population; that is , the secondary human cases an initial infectious vector in patch i produces in a complete totally susceptible population , weighted by the probability of patch i being the initial focus of the epidemics , wherever the initial carrier host come from . Hence , the patch with largest vector transmission risk index VTRi is the candidate to become initially the main disperser of the disease at the beginning of the epidemics , regarding to the vector dynamics . This index can be linked with control measures on vector populations . Accordingly , we consider here the reduction of the local vector population as the control measure ( resulting from abatization , fumigation , hatchery elimination… ) . We simulate this by reducying the carrying capacity Ci ( or directly by removing the local vector population ) of a single patch . As expected , the vector transmission risk index VTRi was able to indicate the patch where this strategy proved to be more effective to reduce the initial growth of the epidemic , on average ( see Fig 6 ) . That is , the amount of total infected hosts Ih is the lowest one for t ≤ 50 when the control is applied to the patch with highest vector transmission risk index VTRi , compared to the other patches located control strategy , and to the unchecked situation .
We propose three risk indexes for the transmission of vector-borne diseases . Two of them are related with the transmission risk of patches and the other one gives a measure of the vulnerability of each patch . It is worth to notice their ability to localize epidemiological risk at different nodes of a net . The transmission indexes of a patch quantify the potential secondary cases that a first infected individual or vector in this patch may generate system-wide . On the other hand , the vulnerability index of a patch quantify the potential secondary cases that a first infected individual in the system cause in the relevant patch . Specifically , the transmission risk index TRi is the probability of a host in patch i became the first infected host , times secondary human infections they would potentially cause . The second index VTRi , called vector transmission risk index , is defined as the probability of a vector gets first infected in patch i , times secondary human infections it would potentially cause . The vulnerability index VRi is secondary host infections in patch i averaged over a randomly distributed initial infected human in the system . These risk indexes can be used in different ways . First , they indicate optimal places to apply prevention measures . They are also useful to guide the monitoring campaigns for an early detection of epidemics . And finally , they can guide control and mitigating strategies at the beginning of an outbreak . For example , the transmission risk index TRi indicate that the patch with the greatest value of it , is the best place to distribute repellents as a prevention strategy . Another control strategy is to isolate by hospitalization infected individuals of such a neighborhood . The vector transmission risk VTRi indicates the most suitable places where abatization and fumigation campaigns will be more effective . Thus , when there are limited resources , the best strategy is to give priority to the patches with higher values of the index . On the other hand , the vulnerability risk index VRi can guide investments in health clinics . This would increase the public health capacity in particular areas where many cases will likely arise . In addition to this , as it is expected to find more cases in the neighborhood with highest VRi , this is a good place for incidence monitoring . That will help in detecting increased anomalous endemic states or an outbreak . In order to illustrate these control measures , we compared a set of simulations in the frame of a proposed particular model for vector-borne diseases spread in a multi-patch system for a Dengue epidemics . In addition to vector and host densities , this model takes into account human mobility . We have observed that an immediate medical attention gives benefits to the whole population if the neighborhood with highest transmission risk TRi is prioritized . In contrast , reducing the hatcheries for example by abatization brings more benefits if the neighborhood with highest vector transmission risk VTRi is prioritized . We observed in the simulations that the risk indexes can also be used to design control strategies but just at the beginning of the epidemic . The time these indexes give the best strategy during an epidemic depends on the network structure . A complete study of the relationship among all possible network configurations , the corresponding risk indexes values , and the most efficient strategies is out of the scope of the current work . In order to apply these indexes in practical situations , it is necessary to have estimations of the model parameters . With respect to this , entomological parameters can be estimated using reported values in the literature at different temperatures [35 , 36] . On the other hand , the now ubiquitous tracking technologies based on mobile devices such as google maps , twitter of even traffic cams , have opened the possibility to estimate with high resolution human mobility patterns . Finally , even if the carrying capacity of each patch is difficult to measure , to stratify a region it is not necessarily to know its absolute value . It is just enough to know the relative importance of it among the patches . This can be obtained by the usual field work carried by the entomologist .
|
A disease is called vector-borne when it is not transmitted directly among humans , but in a human-vector-human way . Examples of major importance , due to its epidemiological magnitude , are Dengue , Chikungunya and Zika tropical diseases , for which the main vector is the Aedes aegypti mosquito . Usually , some indexes are used to measure the potential damage that such a disease could cause , which concern infectivity and entomological issues , human mobility and geographical density , etc . We consider a mathematical epidemiological model which takes specifically into account these spatial factors ( mobility , density ) , and propose a set of new risk indexes which give information about how the epidemic spread could occur , and where the outbreaks could take place . These indexes come from a preventive perspective , and they also pay attention to the epidemic dynamics . Consequently , they potentially allow to proceed in the correct places , and before troubles have arisen . We think these new tools could eventually help health agencies in the design of efficient and effective strategies on prevention and control of vector-borne diseases epidemics .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"death",
"rates",
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"infectious",
"disease",
"epidemiology",
"neighborhoods",
"vector-borne",
"diseases",
"social",
"sciences",
"human",
"mobility",
"animals",
"population",
"biology",
"infectious",
"disease",
"control",
"insect",
"vectors",
"human",
"geography",
"infectious",
"diseases",
"geography",
"epidemiology",
"disease",
"vectors",
"insects",
"arthropoda",
"population",
"metrics",
"mosquitoes",
"eukaryota",
"earth",
"sciences",
"biology",
"and",
"life",
"sciences",
"species",
"interactions",
"organisms"
] |
2018
|
Vector-borne disease risk indexes in spatially structured populations
|
Due to their remarkable parasitocidal activity , artemisinins represent the key components of first-line therapies against Plasmodium falciparum malaria . However , the decline in efficacy of artemisinin-based drugs jeopardizes global efforts to control and ultimately eradicate the disease . To better understand the resistance phenotype , artemisinin-resistant parasite lines were derived from two clones of the 3D7 strain of P . falciparum using a selection regimen that mimics how parasites interact with the drug within patients . This long term in vitro selection induced profound stage-specific resistance to artemisinin and its relative compounds . Chemosensitivity and transcriptional profiling of artemisinin-resistant parasites indicate that enhanced adaptive responses against oxidative stress and protein damage are associated with decreased artemisinin susceptibility . This corroborates our previous findings implicating these cellular functions in artemisinin resistance in natural infections . Genomic characterization of the two derived parasite lines revealed a spectrum of sequence and copy number polymorphisms that could play a role in regulating artemisinin response , but did not include mutations in pfk13 , the main marker of artemisinin resistance in Southeast Asia . Taken together , here we present a functional in vitro model of artemisinin resistance that is underlined by a new set of genetic polymorphisms as potential genetic markers .
Malaria remains the most prevalent and deadly vector-borne disease in the world , with an estimated two hundred million cases and over four hundred thousand deaths recorded in 2015[1] . Currently , the cornerstone of global malaria control programs is artemisinin combination therapy ( ACT ) . ACT combines the highly potent , rapidly acting artemisinin-based compounds with long-lasting partner drugs[2] . Artemisinin-based compounds have an excellent safety profile , exert a very rapid parasitocidal effect , and are active against gametocytes and all stages of the intraerythrocytic developmental cycle ( IDC ) , from the early rings to the mature schizonts[3 , 4] . In particular , artemisinin compounds are typified by their short plasma elimination half-life , ranging from <1 to 3 hours for the water-soluble artesunate ( ATS ) and dihydroartemisinin ( DHA ) , and from 3 to 11 hours for the oil-soluble artemether[3] . This is in sharp contrast to other antimalarial drugs that have considerably slower elimination times , persisting over several days to several weeks[5] . Hence , artemisinin-based drugs are the frontline therapies used by most , if not all , malaria control programs around the world . In spite of its wide use , understanding of the artemisinin mode of action remains limited . Artemisinin belongs to the class of sesquiterpene lactones with an endoperoxide bridge that is essential for its antimalarial activity[6 , 7] . It is widely accepted that artemisinin-mediated parasite killing requires bioactivation of the peroxide structure that leads to generation of reactive oxygen species ( ROS ) and subsequent damage of biomolecules such as proteins , lipids and nucleic acids[6 , 7 , 8] . Some notable protein targets of artemisinin include: PfTCTP , a translationally controlled tumor protein homolog[9] which is located in both the cytoplasm and the food vacuole[10]; Pfatp6[11] , an ER-resident , parasite ortholog of sarco/endoplasmic reticulum membrane calcium ATPase; and Pfpi3k[12] , which is thought to be an early ring stage target of dihydroartemisinin . Artemisinin-derived radicals have been also shown to alkylate heme[13] , which could lead to the disruption of hemozoin synthesis[14] which is essential to parasite survival . Additionally , this class of drugs have also been found to induce the ROS-mediated depolarization of both the mitochondrial[15 , 16] and plasma membranes[16] , representing a different mechanism of parasite killing . It could very well be that the potency of endoperoxide-based drugs against the asexual blood stage is due to their ability to interact with a wide range of targets , across multiple cellular compartments[17 , 18] . However , the true impact of these interactions on parasite killing remains to be fully understood and requires further investigation . Indeed , the use of artemisinin combination therapy has led to major progress in malaria control throughout the world in the last two decades , paving the way for better cure rates and reduced transmissibility in the field . From the late 2000s , however , pockets of decreased drug sensitivity to artemisinin-based drugs have been found in Southeast Asia . First detected in western Cambodia[19 , 20 , 21] , resistance has been now reported from multiple locations across Asia including Thailand[22 , 23] , Myanmar[23 , 24] , Vietnam[23 , 25] , and even Southern China[26] . It is believed that artemisinin resistance is continuously emerging de novo[27 , 28 , 29] , but a few fit lineages are now spreading regionally[30] . What was originally characterized by delayed parasite clearance among patients treated with ACTs has now escalated to an alarming surge in treatment failures[31] . Interestingly , standard ex vivo 72-hour drug assays that are typically used to measure drug sensitivity are not able to differentiate between the slow-clearing ( artemisinin-resistant ) and fast-clearing ( artemisinin-sensitive ) parasites[32] . Instead , the Southeast Asian field isolates exhibit decreased susceptibility to artemisinins only in the very early ring stage of the IDC[32] . Transcriptional and cellular characterization of the resistant isolates demonstrated a delayed progression of the first half of the IDC , particularly the ring stage that is also the least susceptible to artemisinin[33 , 34 , 35] . These parasites are also characterized by upregulation of several cellular stress response pathways related to antioxidant defense and the unfolded protein response ( UPR ) [34] . Crucially , Ariey et a . l 2014 identified a biomarker of clinical artemisinin resistance that can be found in both in vitro and in vivo P . falciparum isolates[36] . After sequencing over 150 Cambodian isolates , they found several nonsynonymous single nucleotide polymorphisms ( SNPs ) in pfk13 located at chromosome 13 that was similarly mutated in an artemisinin-resistant parasite derived in vitro by artemisinin exposure for over five years[36 , 37] . Interestingly , the chromosome 13 region around pfk13 was identified independently as one of the genetic regions with a strong signature of selection among Thai and Cambodian parasites with slow clearance rates[38 , 39] . Subsequent surveillance of Southeast Asian isolates with different genetic backgrounds further corroborated pfk13 as a strong genetic correlate of delayed parasite clearance[23 , 27 , 28] . Finally , functional studies validated that specific amino acid changes within the Pfk13 propeller domain significantly increases the rate of parasite survival after early ring-stage treatment with DHA[40] . Although pfk13 is currently the best-characterized molecular marker , many questions remain about the mechanistic links between the amino acid changes in Pfk13 ( a putative factor of intracellular protein-protein interactions ) and the parasite’s resilience to artemisinin . It is particularly important to uncover all molecular components of the artemisinin resistance mechanism that can act in either a pfk13-dependent or -independent manner . Here we identified several putative factors that can facilitate artemisinin resistance by deriving and characterizing two artemisinin-resistant parasite lines from the P . falciparum 3D7 strain . Through the genomic , transcriptional and chemosensitivity profiling of these in vitro artemisinin-resistant parasites , our findings corroborate the central role of the parasite’s stress responses in mediating artemisinin resistance in Plasmodium , as well as demonstrate the possibility of a robust resistance phenotype that is potentially clinically relevant and is driven by different genomic alterations beyond pfk13 .
The overall goal of this research was to identify and characterize molecular factors that contribute to resistance of the malaria parasite P . falciparum , to artemisinin . For this purpose , we derived two parasite lines from two isogenic clones of the 3D7 strain termed 6A and 11C[41] . This was done by repeated exposures of synchronized parasite cultures to 900 nM of artemisinin for 4 hours at the ring stage ( 10–14 hours post invasion , HPI ) ( Fig 1A ) . At the initial earlier stages of the selection process , these pulse treatments were applied every other round of the IDC ( see materials and methods ) . The main rationale of this selection regimen was to approximate clinical conditions in the peripheral blood of infected patients where artemisinin peaks at ~900nM[42] and decays below clinical levels within 2 to 5 hours[3] , and where the P . falciparum populations consists predominantly of ring-stage parasites ( ~10 HPI ) [33 , 43] . The ring stage that is otherwise the least sensitive to artemisinin[44] , is believed to be driving the currently occurring artemisinin resistance phenotypes observed in natural infections[32 , 45] . Initially , during the first 13 treatment cycles , the rate of parasite survival after each artemisinin exposure fluctuated between 30–90% ( Fig 1C ) . These surviving parasites were typically arrested in the ring/trophozoite stages for up to 24 hours post treatment instead of progressing to the expected schizont stages ( Fig 1A and 1C , S1 Fig ) . However , from 18 cycles onwards , 70–100% of parasites were consistently surviving the treatment , progressing normally through the IDC ( Fig 1C ) . We observed a marked decrease in artemisinin susceptibility in both clones as early as 6 rounds of treatment ( 26 days ) for 6A-R , and 8 rounds of treatment for 11C-R ( 33 days ) . At that stage the 6A-R and 11C-R exhibited a 3- and 17-fold increase of artemisinin resistance , respectively , as measured by a survival assay establishing the 50% inhibition concentration for parasites exposed to the drug for 4 hours at 10 HPI ( IC5010hpi/4hr ) ( Fig 1B , S1 Table ) . This drug pulse assay was designed to match the window of the drug selection , resembling the previously utilized shorter exposure drug assays that were shown to capture the stage-dependent artemisinin activities[44 , 46] . Using this assay , we were observed marked differences in the dynamics of the progression of artemisinin resistance between the two clones throughout the drug selection regimen ( Fig 1B , S1 Table ) . 6A-R showed a gradual increase of IC5010hpi/4hr , starting at 55 . 49 nM at 6 cycles of artemisinin exposures , progressing to 3 , 880 nM after 11 months and peaking at 33 , 726 nM after approximately 1 . 5 years of continuous treatments . On the other hand , 11C-R exhibited a rapid increase of resistance between 6 and 37 cycles ( first 5 months of drug selection ) to IC5010hpi/4hr = 3 , 052 nM . Subsequently , this level of resistance plateaued for the next 19 months of continuous cultivation under drug selection ( Fig 1B ) . Hence , compared to their corresponding parental lines , the resulting artemisinin resistant lines 6A-R and 11C-R exhibited up to a 398- and 69-fold increase in IC5010hpi/4hr , respectively . The drug resistance phenotypes of both lines remained fully intact in parasites that were cryopreserved and reintroduced to culture . Moreover , a significantly elevated IC5010hpi/4hr was maintained after three months of cultivation in the complete absence of drug pressure . In summary , here we derived two artemisinin resistant lines of P . falciparum that could be actively maintained in an in vitro culture and thus serve as a tool for mechanistic studies of artemisinin resistance . The differences in the resistance levels and selection dynamics suggest that the two resistant parasite lines employ ( to at least some degree ) distinct molecular factors to withstand artemisinin . Interestingly , the derived resistance phenotype ( s ) of both 6A-R and 11C-R are predominant in the rings ( 10 HPI ) and do not affect the later stages of IDC development ( Fig 2A , S2A Fig , S2 Table ) . However , for 11C-R , the window of resistance extends until the early trophozoite stage ( ~20 HPI ) , where a moderate level of resistance can still be observed . The robustness of the ring-specific artemisinin resistance is likely the main reason for the observed resistance demonstrated by both parasite lines in the standard 72-hour drug assay that measures parasite survival after artemisinin exposure across all stages of the IDC ( Fig 2B , S2B Fig , S2 Table ) . Crucially , both parasite lines also showed decreased drug susceptibility in the ring survival assay ( RSA ) [32 , 45] carried out with parasites at 0–3 HPI ( Fig 2C ) . Both 6A-R and 11C-R passed the 1% RSA survival cutoff employed in the field to denote resistance[45 , 47 , 48] . This contrasts the current phenotype observed in natural infections that exhibit high levels of ring-stage specific resistance ( in the RSA ) , but show no changes in the standard 72-hour drug assay[32] . Both 6A-R and 11C-R also have significantly elevated IC5010hpi/4hr to other semisynthetic artemisinin derivatives . 6A-R exhibited 5- and 8-fold higher IC5010hpi/4hr to dihydroartemisinin ( DHA ) and artesunate ( ATS ) , and 11C-R showed 2- and 3-fold higher IC5010hpi/4hr to DHA and ATS , respectively . Both , 6A-R and 11C-R , however , showed no changes in sensitivities to other antimalarial drugs including two quinolines ( quinine and chloroquine ) and pyrimethamine ( Fig 2D , S3A and S3B Fig , S3 Table ) . Taken together these results suggest that the derived resistance phenotypes are specific to artemisinin and its endoperoxide-carrying derivatives , and can give rise to full resistance phenotypes of the P . falciparum parasites . Given its relevance in the RSA , these mechanisms may correspond to the current artemisinin resistance in natural infections albeit being independent from pfK13 polymorphisms[32 , 36] ( see below ) . Interestingly , both parasite lines exhibited increased susceptibility to mefloquine , whose mode of action is presumably related to other quinolines[49] . In future studies , it will be interesting to investigate the relationship between the altered sensitivities of P . falciparum to artemisinins and mefloquine . However , here it is important to note that the connection between these two chemosensitivity phenotypes is not absolute as observed in another artemisinin-resistant line derived from a polyclonal population of the T996 P . falciparum strain ( S3D Fig ) . Stress responses to an oxidative damage and the unfolded protein response ( UPR ) have been implicated in the mechanisms of artemisinin resistance of P . falciparum in in vitro cultures [50 , 51] and natural infections[34] . To investigate the role of these two biological processes in the derived resistant parasite lines , we challenged our in vitro-derived resistant parasites with H2O2 , dithiothreitol ( DTT ) and epoxomicin ( EPX ) . While H2O2 causes oxidative damage , DTT and EPX are inducers of ER stress , causing an accumulation of damaged/misfolded proteins inside the cell . Intriguingly , 6A-R , but not 11C-R , exhibited a significant resistance to all three inhibitors ( Fig 2E , S3C Fig , S3 Table ) . This is consistent with our previous suggestion of inherent mechanistic differences in the artemisinin resistance mechanisms between 6A-R and 11C-R and shows that oxidative damage repair and unfolded protein responses play a central role in artemisinin resistance as observed in vivo [33 , 34 , 51] . To assess whether the in vitro-derived artemisinin resistant phenotypes reflect the similar physiological state observed in vivo , we characterized the transcriptomes of 6A-R and 11C-R . First we reconstruct the IDC transcriptomes of both resistant clones grown under normal conditions ( S4A Fig ) . The “best fit” parasite aging analysis[33] showed that starting from the mid ring stage ( time point 2 ) , both lines progressed identically and completed their IDC in approximately 48 hours . However , both resistant parasite lines appeared to accelerate their early ring stage progression being older ( 10 HPI ) than their sensitive counterparts ( 4 HPI ) at the first sampling interval ( S4A Fig ) . This observation is consistent with the ring-specific resistance in both clones and their resistance in the RSA that appear to be involved in the pfk13-dependent artemisinin resistance observed in vivo . Examining the transcriptomes of 6A-R and 11C-R between 10–20 HPI , we detected broad alterations in mRNA levels of >300 P . falciparum genes ( corrected p-value < 0 . 05 , FDR < 0 . 25 ) , as well as changes in key processes that might be linked to modulating artemisinin response in the parasite ( Fig 3A ) . In 6A-R , pathways related to the redox stress responses and protein turnover were predominant amongst the upregulated genes . Notably , we observed an upregulation of genes that may be related to the parasite’s thioredoxin-based redox system such PF3D7_1457200 ( thioredoxin 1 ) , PF3D7_1438900 ( thioredoxin peroxidase 1 ) , and PF3D7_1352500 ( thioredoxin-related protein ) . We also observed an enrichment of targets of glutathionylation , as well as targets of the thioredoxin enzyme superfamily . The upregulated protein turnover-associated genes included heat shock and chaperone proteins , and a number of enzymes involved in proteolysis . We also observed an upregulation of genes involved in translational elongation , electron transport , and protein transport , particularly vesicular trafficking between the ER and Golgi complex . On the other hand , the significantly downregulated genes were enriched for pathways related to host-parasite interactions , control of gene expression , and translational initiation ( Fig 3A , Table A in S4 Table and S1A File ) . Interestingly , gene sets involved in cell cycle regulation were also found to be differentially expressed between 6A-R and 6A—which could be related to the slight shift in temporal progression during the early stages of parasite development . In the case of 11C-R , we likewise observed a significant upregulation of genes involved in oxidative stress defense , although to a lesser extent compared to 6A-R . These include genes that encode S-glutathionylated proteins , PF3D7_0306300 ( glutaredoxin 1 ) and PF3D7_0709200 ( glutaredoxin-like protein ) . Pathways involved in protein damage repair , including chaperones and components of proteasome-mediated degradation are also overexpressed . In addition , 11C-R exhibited an upregulation of processes related to early translation events , and transcriptional and post-transcriptional mechanisms of gene regulation such as chromatin modification , stress helicase activity , and the formation of P-bodies . Induction of P-bodies has been observed under stress or conditions that repress translation initiation[52 , 53 , 54] , and their role in drug resistance may not be ruled out . As for the significantly downregulated functionalities in 11C-R , we identified factors of host-parasite interactions , components of the transcriptional machinery , cellular transport , hemoglobin digestion , several translational elongation factors and ATP synthesis ( Fig 3A , Table B in S4 Table and S1B File ) . Evaluating the transcriptional correspondence of 6A-R and 11C-R with slow clearing isolates in Southeast Asia from the TRAC I[34] , we found a great degree of overlap between significantly upregulated pathways in the in vitro and in vivo datasets ( Fig 3B ) . Strikingly , several of these pathways have also been associated with longer parasite clearance half-lives in the field such as coping mechanisms against ER stress ( ER trafficking , proteasome-mediated degradation , translation ) and oxidative stress ( targets of glutathionylation ) , as well as mRNA processing[34] . Not only does this observation reinforce the involvement of these cellular processes in modulating artemisinin resistance in Plasmodium , it also demonstrates that 6A-R and 11C-R are each able to recapitulate key aspects of in vivo artemisinin resistance at the transcriptional level . Next we analyzed global transcriptional responses of 6A-R and 11C-R to artemisinin drug exposure that is identical to the selection conditions ( synchronized parasites were treated with 900nM artemisinin from 10 to 14 HPI ) ( S4B Fig ) . Here we observed many similarities between how 6A-R and 11C-R respond to a ring-stage artemisinin challenge in relation to their sensitive counterparts . Notably , both lines exhibit a downregulation of processes pertaining to pathogenesis , transcriptional control , translation , cellular transport and cell cycle regulation ( S4B Fig , Tables A and B in S5 Table ) . That both in vitro-derived lines demonstrate a marked dysregulation of genes involved in cell cycle regulation could be related to their ability to overcome the drug induced quiescence caused by artemisinin . Interestingly , GSEA identified transport across the ER-Golgi and digestive vacuole ( DV ) membranes as significantly upregulated in 11C-R ( S4B Fig , Table B in S5 Table and S2B File ) . Likewise , 6A-R also displayed an upregulation in transmembrane transport components—a number of which have been linked to drug resistance in Plasmodium . A notable example is the DV-resident chloroquine resistance transporter , pfcrt , which is significantly upregulated in both resistant lines and has been associated with chloroquine resistance [55 , 56 , 57 , 58] . Pfcrt also plays a role in glutathione transport and antioxidant defense within the DV[59] . Pfexp1 , a glutathione transferase located on the parasitophorous vacuole and is associated with artesunate sensitivity and metabolism[60] is also found to be upregulated in 6A-R ( S2A File ) . On the other hand , we also observed transcriptional features that are distinct to only one parasite line , such as the downregulation of autophagy-related pathways in 6A-R vs . 6A , and the observed downregulation of heat shock proteins in 11C-R compared the 11C . It is probable that the differences we observed in global transcriptional profiles between 6A-R and 11C-R could account for some of the phenotypic variations between these two parasite lines such as resistance to H2O2/DTT/EPX . In the future it will be interesting to study these variations as they could represent genuine differences in drug resistance phenotypes in vivo . The whole genome sequencing of the two resistant parasite lines identified several intragenic SNPs compared to their parental lines . These included 3 and 5 missense mutations in 6A-R and 11C-R , respectively; one nonsense mutation in each parasite line and an additional intronic SNP in 6A-R ( Table 1 ) . As a result , there are mutation alleles for five genes in 6A-R and six genes in 11C-R . Cross-referencing our SNP data with the Pf3k[61] and MalariaGEN[62] databases , the nonsynonymous mutations detected in PF3D7_1427100 , PF3D7_0810600 and PF3D7_1115700 were found to also occur in natural infections of African origin . Crucially , there was no overlap between the mutated genes in the two parasite lines , both of which also carried the wild-type allele of the K13 gene ( validated by PCR-based genotyping of pfk13[36 , 63] ) . No polymorphisms were also detected in previously identified drug resistance markers , such as pfcrt[56 , 64] , pfmrp1[65 , 66] , pfmdr1[67] , pfnhe-1[68] , pfdhps[69] , pfdhfr[70 , 71] , pfatp6[72] , pfubp1[73] , pfap2mu[74] PF3D7_101700[39] , and PF3D7_1343400[39] . Moreover , none of the SNP-containing genes in 6A-R and 11C-R match the previously reported putative targets and interacting partners of artemisinin , such as pfatp6[11] , pfpi3k[12] , pftctcp[9] and other proteins [17 , 18] . The only exception is the nonsense mutation in pffp2a ( PF3D7_1115700 ) that encodes falcipain 2a , the main factor of hemoglobin digestion , whose nonsense polymorphism was previously linked with artemisinin resistance in vitro[36 , 37] . On the other hand , both 6A-R and 11C-R harbor mutations in genes that might play a role in gene expression regulation such as AP2-like transcription factors , a PHD finger protein and an RNA helicase . Such genes could be implicated in the regulation of the Plasmodium IDC transcriptional cascade and subsequently contribute to the resistance phenotypes of both parasite lines . Next , we characterized the genome-wide patterns of copy number variations ( CNVs ) using microarray-based comparative genomic hybridization ( CGH ) as previously described[41] . In both 6A-R and 11C-R , we detected two gDNA segments whose amplifications could be directly related to their artemisinin resistance status ( Fig 4 , S6 Table ) . Namely , there is a segment on chromosome 14 spanning 40 genes ( PF3D7_1454000-PF3D7_1458000 ) amplified in 6A-R , and a segment on chromosome 12 spanning 9 genes ( PF3D7_1228000—PF3D7_1228800 ) amplified in 11C-R . Moreover , both 6A-R and 11C-R also carry a common amplification on chromosome 10 spanning 17 genes ( PF3D7_1028700—PF3D7_1030300 ) . This selfsame amplification has also been identified previously in an artemisinin sensitive P . falciparum 3D7[75] strain . The three CNVs on chromosomes 10 , 12 and 14 were detected during the later stages of drug selection and subsequent culturing , and were consistently detected over a period of five months ( 89 generations ) ( S5 Fig ) . Comparing our CNVs with a dataset collated from 122 clinical isolates from Africa , South East Asia and South America[76] , we found that none of the isolates contained the chromosome 10 , chromosome 12 and chromosome 14 amplification clusters in their entirety . However , one isolate collected from Peru harbored a copy gain for the putative gamma-adaptin encoding PF3D7_1455500 . Given the scope of the detected transcriptional changes in 6A-R and 11C-R , we wished to investigate the possibility that CNV-driven variations in expression can mediate artemisinin resistance . Evaluating the individual expression levels of each gene in the three CNV clusters identified , we found that not all transcripts appear to be significantly overexpressed across the IDC between resistant parasites and their sensitive counterparts ( Fig 5A and S6 Table ) . However , comparing the collective expression among the amplified genes on chromosomes 10 , 12 and 14 , we were able to detect a significant enrichment of upregulation in the genes located in these regions ( Fig 5A ) . This observation is particularly striking in the case of the chromosome 14 amplification in 6A-R , where 30 out of the 40 genes were significantly overexpressed across the IDC ( S6 Table ) . Here we focused on three genes on the 6A-R chromosome 14 amplification that are likely to be involved in adaptive responses against cellular damage within the parasite . These include 6-phosphogluconate dehydrogenase ( PF3D7_1454700 , pf6pgd ) and thioredoxin 1 ( PF3D7_1457200 , pftrx1 ) —both of which are involved in antioxidant defense[77 , 78 , 79] , and an ER-resident signal peptide peptidase ( PF3D7_1457000 , pfspp ) [80] that is a component of ER associated degradation ( ERAD ) [81] . All three candidate genes were found to be significantly overexpressed in 6A-R compared throughout the IDC ( Fig 5A and S6 Table ) . In order to assess their potential to confer artemisinin resistance , we generated transgenic P . falciparum lines in which each candidate gene was overexpressed episomally . Briefly , each gene was fused with the HA-antibody epitope at the C-terminus and cloned into the pBcamR_3xHA transfection vector ( see materials and methods ) that allows adjustable expression via increased copy number driven by blasticidin ( BSD ) . Quantitative RT-PCR demonstrated increased transcription of the transgenic contracts by 7-fold for pf6pgd and 2-3-fold for pftrx1 and pfspp ( Fig 5B ) . Western blot analysis confirmed the production of the HA-tagged transgene protein products at their expected molecular weights in the transgenic cell lines grown in the presence of 2 . 5 ug/mL BSD ( Fig 5C ) . Crucially , overexpression of pftrx1 , and pfspp resulted in a subtle but significant decrease in artemisinin sensitivity , with IC5010hpi/4hr 1 . 7-fold , and 2 . 9-fold higher than the “empty vector” control , respectively ( Fig 5D , S6 Fig and S7 Table ) . On the other hand , no significant difference in artemisinin sensitivity could be observed in the parasites overexpressing pf6pgd . These results indicate that the specific upregulation , possibly as a result of gene amplification , of pftrx1 and pfspp contributed to the decreased sensitivity of 6A-R to artemisinin .
It has been previously shown that resistance can be induced in culture-adapted P . falciparum parasites through long-term exposures to artemisinin and/or its derivatives[37 , 50 , 82 , 83] . That includes the studies that discovered the current principal marker of artemisinin resistance in Southeast Asia , pfk13 [36 , 37] . The identification of the pfk13 gene highlights the value of such in vitro models to systematically investigate the mechanisms that drive artemisinin response and resistance in the clinical setting . Here , we developed two artemisinin resistant cell lines from isogenic clones of the 3D7 P . falciparum strain . For this study , we chose two isogenic clones of the 3D7 reference strain that has been previously extensively characterized , and thus will lead to efficient identification of all derived genetic variation . The 3D7 strains also represent a fully artemisin-susceptible background which provides a “naïve” baseline genome that potentially allows for the identification of causative factors of artemisinin resistance that are independent of any potential genetic background with a propensity for drug resistance[27 , 84] . This yielded a resistance phenotype ( s ) that is ( are ) distinct from the previous reports . Essentially all previously derived P . falciparum parasites involved an artemisinin-induced growth arrest and recovery as a major component of the resistance phenotype[37] , [50] , [85] , [83] . In contrast , 6A-R and 11C-R are both characterized by an increased survival in the presence of artemisinin with no detectable levels of growth retardation or arrest . This marked difference is likely due to the pulse-based regimen that contrasts the previous studies in which the parasite lines were treated for considerably longer time periods , ranging from 24–48 hour drug exposure intervals[36 , 37] to continuous drug pressure[50 , 82 , 83] . Moreover , 6A-R and 11C-R displayed significant decreases of artemisinin sensitivity ( IC5010hpi/4hr ) within as early as 1 . 5 months of selection . This is also in stark contrast with previous reports by Witkowski et al . that showed that the chemosensitivity of the P . falciparum F32 strain remained unaltered for up to 3 years and/or 100 cycles of drug pressure when the parasites were treated with artemisinin for 24 hours at a time[37] . Similarly , Cui et al . were unable to raise drug resistance in the 3D7 strain at all and could only generate resistant parasites using other culture adapted P . falciparum strains including 7G8 , Dd2 , HB3 and D10 after at least one to two months of continuous exposure to DHA[50] . This collectively indicates that artemisinin resistance of P . falciparum could be derived by multiple ways , each of which may induce a distinct mechanism . Unsurprisingly , the artemisinin resistance in both parasite lines extends to its cognate drugs ATS and DHA . But while 6A-R and 11C-R showed up to almost 400- and 70-fold increases in IC5010hpi/4hr values for artemisinin ( Fig 1B , S1 Table ) , respectively , both lines exhibited increases in IC5010hpi/4hr for ATS and DHA by less than 10-fold ( Fig 2D , S3 Table ) . This is likely a reflection of key differences in pharmacodynamic profiles between artemisinin and its two synthetic derivatives . Compared to the plant-derived artemisinin , both ATS and DHA are more potent antimalarials with DHA being the primary cytopathic metabolite responsible for the parasite killing[6 , 86] . In contrast , artemisinin is not metabolized to DHA but instead acts as the primary antimalarial agent itself and is subsequently transformed into inactive deoxyartemisinin and dihydrodeoxyartemisinin[4 , 87 , 88] . The variance in the resistance level of the two derived clones could be attributed to differences in the overall levels of the cytopathic activities , the mode of activation , and/or the protein targets that each compound is specifically engaging . Moreover , while 6A-R and 11C-R did not exhibit cross-resistance to other types of antimalarials , both clones are more susceptible to mefloquine ( Fig 2D ) . Interestingly , DHA-resistant parasites previously derived by Cui et al . from a Dd2 parent , displayed decreased sensitivity to other artemisinin-based drugs albeit to a lesser extent compared to DHA , but also to quinine , chloroquine and mefloquine[50] . Furthermore , parasites derived using long term exposure to artelinic acid from the D6 and W2 backgrounds showed cross-resistance to mefloquine but increased susceptibility to chloroquine[82 , 83] . These findings allude to the possibility that resistance to artemisinin-based drugs could also affect the clinical efficacy of its partner drugs used in the currently deployed ACTs . These results highlight the importance of testing for cross-resistance as an integral part of drug development , and also demonstrate a key use for in vitro drug resistance models that can be utilized as a platform with which to perform such extensive and rigorous studies . The P . falciparum parasites causing the current state of slow clearing infections in the Southeast Asian patients show are marked by higher RSA values[45] but show no differential sensitivities in standard in vitro drug assays[20 , 32 , 89] . These in vivo parasites are characterized by transcriptional induction of oxidative and ( other types of ) protein damage responses , and at the same time , a deceleration of the early stages the IDC [33 , 34] . Both of these transcriptional phenotypes are strongly linked with mutations in the pfk13 gene as the main marker of artemisinin resistance [27 , 28 , 36] . Here we observed several main similarities between in vivo artemisinin resistance and the in vitro-derived phenotypes of 6A-R and 11C-R . First , like the slow-clearing isolates in Southeast Asia , the resistance of 6A-R and 11C-R is tied to the earlier stages of the IDC , and fades as the parasites progress into the later stages . This is reflected by an elevation in the RSA index ( >1% ) for both 6A-R and 11C-R that is comparable to the in vivo isolates ( Fig 2C ) . Second , both resistant lines demonstrated a steady state upregulation of genes and pathways that are involved in antioxidant defense , as well as the UPR ( Fig 3A and 3B ) [34] . Crucially , the induced artemisinin resistance in the 6A-R clone also gave rise to cross-resistance against oxidative agents ( e . g . H2O2 ) , protein-folding disruptors ( e . g . DTT ) , and stressors of protein processing in the ER ( EPX ) ( Fig 2E ) . This indicates that that its derived resilience to artemisinin is tied to an increased capacity to mediate oxidative stress and protein damage . These findings suggest that one possible mechanism for artemisinin resistance is an enhanced ability of the P . falciparum parasites to cope with the oxidative stress and protein damage presumably caused by artemisinin directly . On the other hand , the in vitro-derived lines were unable to recapitulate certain features of the resistant isolates . Neither 6A-R nor 11C-R experienced a dramatic shift in the temporal progression of the IDC , nor did they develop artemisinin-resistance associated genotypes that have been previously observed in vivo—most notably , mutations in pfk13 . In spite of these genotypic and phenotypic discrepancies , these derived parasite lines nonetheless provide a unique opportunity for future analyses of artemisinin resistance in the context of multiple genetic backgrounds[27 , 28] . The apparent lack of pfk13 polymorphisms in 6A-R and 11C-R suggests that these parasites may serve as a model to study the relevant mechanisms driving the PfK13-independent artemisinin resistance phenotype newly emerging in Southeast Asia[48] and Africa[90] . The prerequisite of a genetic background and the possibility of “PfK13-independence” suggest that other genetic polymorphisms will contribute to the overall phenotype of artemisinin resistance that is currently in existence or will emerge in the future . Genomic profiling of 6A-R and 11C-R revealed unique sets of SNPs and CNVs that could represent such polymorphisms . Surprisingly , these polymorphisms did not involve genes with associations to any drug sensitivity phenotypes of malaria parasites reported in the past . The two exceptions include pffp2a and pfprp22 . Pffp2a is a cysteine protease involved in hemoglobin digestion that is believed to mediate the activation of artemisinin presumably via the release of haemoglobin-derived iron[91] . Indeed Pffp2a can modulate artemisinin sensitivity in the ring stages[92] , and a nonsense mutation in pffp2a has been previously found in an in vitro-derived artemisinin-resistant parasite line[36 , 37] . Hence the presence of the nonsense mutation the pffp2a likely contributes to artemisinin resistance in 6A-R . The amplification of pfprp22 in both 6A-R and 11C-R on the common segment of chromosome 10 coincides with its duplication in another resistant parasite line derived from a D6 strain using artelinic acid[83 , 93] . However , this amplification at chromosome 10 had already been reported in naturally occurring infections including artemisinin sensitive parasites[75] . Hence its role in artemisinin resistance remains unclear . Here , we were able to substantiate the potential of the chromosome 14 CNV to influence the parasite’s sensitivity to artemisinin by the specific overexpression of two key genes in this region: pftrx1 and pfspp . Both PfTrx1 and PfSpp play a role in the parasite’s antioxidant defense system and/or protein damage stress response . Thioredoxin 1 is a key enzyme in the Plasmodium NADPH-dependent thioredoxin system which is involved in the detoxification of reactive oxygen metabolites , redox regulation of transcription factors , and control of protein folding[77 , 78 , 94] , while Signal Peptide Peptidase is a transmembrane protease component of the ER-associated degradation pathway , which is utilized by the parasite to cope with damaged or misfolded proteins[81] . Hence , the upregulation of pftrx1 and pfspp likely supports the increased capacity of the UPR which , in eukaryotic cells , subsequently employs trafficking across cellular compartments , enzymatic processing of proteins to mediate their folding and degradation , and attenuation of translation to mitigate the ER workload[95 , 96 , 97] . Consistent with this model , 6A-R and 11C-R both demonstrated differential expression of genes related to translational control and the regulation of gene expression , including early translational events ( initiation ) , binding and processing of messenger RNA , as well as transcriptional regulation via transcription factors and chromatin modification ( see Fig 3A , Tables A and B in S4 Table ) . It has been previously shown that that Plasmodium is also able to cope with cellular stresses via translational repression involving the eif2α-mediated attenuation of global protein synthesis[97 , 98 , 99] , and the association of mRNA with RNA-binding proteins that facilitate their stability ( stress granules ) or degradation ( P-bodies ) [98 , 99 , 100] . Transcriptional changes in many of these pathways were also observed in the in vivo isolates[34] . Taken together , this data represents a spectrum of SNPs and CNVs that may represent multiple , alternative genetic events that are yet to be observed or validated in the field but could emerge and spread in the ( near ) future . These could either deepen the existing pfk13-dependent artemisinin resistance phenotypes , or could give rise to new mechanisms compounding alternative genetic backgrounds of P . falciparum populations ( e . g . Indian or African ) [27 , 48 , 90] .
Two clonal parasite lines , named 6A and 11C , were previously derived from the P . falciparum 3D7 strain using limiting dilution[41] and subsequently used for in vitro drug selection . Continuous cultivation of parasites was performed as previously described[101] . Cultures were maintained in purified human red blood cells at 1–2% hematocrit , in RPMI 1640 medium ( Gibco ) supplemented with 0 . 25% Albumax I ( Gibco ) , 2 g/L Sodium bicarbonate ( Sigma ) , 0 . 1 mM hypoxanthine ( Sigma ) , and 50 μg/L gentamicin ( Gibco ) . Parasite cultures were kept at 37 o C with 5% CO2 , 3% O2 , and 92% N2 and treated twice with 5% ( v/v ) sorbitol ( Sigma ) every cycle to maintain stage synchronicity . Culture medium was replenished every 12–24 hours , and freshly washed uninfected red blood cells ( RBC ) was added to the culture as needed . Monitoring of parasitemia and parasite morphology was performed using microscopic evaluation of thin blood smears that were first fixed with methanol ( Merck ) , and then stained with Giemsa ( Sigma ) . Ethical approval for the use of blood in this study was granted by the Institutional Review Board of the Nanyang Technological University . All of the blood utilized for the in vitro cultivation of parasites was derived from healthy adult volunteers , and extracted by trained personnel at the National University Hospital Blood Donation Center , Singapore . All donors provided their written informed consent . 6A and 11C parents were each divided into two parasite lines: one selection line ( 6A-R , 11C-R ) , which would be subjected to artemisinin selection , and one control line ( 6A and 11C ) , which would undergo mock treatment with dimethyl sulfoxide ( DMSO ) ( Sigma ) . All parasite lines were synchronized at 4 HPI and diluted to a parasitemia ( percentage of parasitized erythrocytes ) of 2–5% prior to drug treatment . Each selection line was then pulse treated with a 900 nM artemisinin ( Sigma ) diluted in DMSO for four hours from 10–14 HPI; Control lines were also pulse treated in parallel with pure DMSO , for four hours at 10–14 HPI . During treatment , all parasites were kept at 2% hematocrit with 1 mL of parasitized blood . After treatment , the media containing artemisinin and DMSO were removed , and the parasite pellets washed twice with fresh media . Parasites were then resuspended in fresh media . Blood smears fixed with methanol and then stained with Giemsa were prepared for each parasite line 20–24 hours after washing to obtain post-treatment parasitemia as well as observe any morphological effects of drug treatment . During the initial phase of drug selection , artemisinin-treated parasites were allowed to recover to a viable parasitemia of at least 2% before artemisinin treatment . Once the parasite lines were able to consistently survive artemisinin pressure , they were maintained as synchronized cultures and subjected to pulse treatment with 900nM artemsinin from 10–14 HPI every other asexual cycle . Cultures were not kept away from artemisinin/DMSO treatment for more than three consecutive generations . Both sets of parasite lines were subjected to the same number of artemisinin and DMSO treatments throughout the course of drug selection , and at the same generations .
|
The emergence of artemisinin resistance within and beyond Southeast Asia is a looming threat that needs to be promptly addressed . With this in mind , we derived several artemisinin-resistant parasite lines in vitro in order to fully characterize the resistance phenotype at the cellular and molecular levels . In addition to reinforcing the role of stress responses in mediating artemisinin resistance , we also identified novel genetic alterations that could also be responsible for causing artemisinin resistance . Collectively , this work provides additional insight in relation to , and beyond the paradigm of pfk13-driven artemisinin resistance and artemisinin response in P . falciparum . Understanding the processes that govern the acquisition of artemisinin resistance could aid in the development of strategies to prevent and contain it .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"parasite",
"groups",
"medicine",
"and",
"health",
"sciences",
"plasmodium",
"gene",
"regulation",
"regulatory",
"proteins",
"microbiology",
"dna-binding",
"proteins",
"parasitic",
"diseases",
"parasitic",
"protozoans",
"parasitology",
"apicomplexa",
"protozoans",
"genome",
"analysis",
"transcription",
"factors",
"pharmacology",
"antimicrobial",
"resistance",
"malarial",
"parasites",
"proteins",
"gene",
"expression",
"biochemistry",
"eukaryota",
"transcriptome",
"analysis",
"microbial",
"control",
"biology",
"and",
"life",
"sciences",
"genetics",
"genomics",
"computational",
"biology",
"organisms"
] |
2018
|
Oxidative stress and protein damage responses mediate artemisinin resistance in malaria parasites
|
The insulin/IGF signaling pathway is a highly conserved regulator of metabolism in flies and mammals , regulating multiple physiological functions including lipid metabolism . Although insulin signaling is known to regulate the activity of a number of enzymes in metabolic pathways , a comprehensive understanding of how the insulin signaling pathway regulates metabolic pathways is still lacking . Accepted knowledge suggests the key regulated step in triglyceride ( TAG ) catabolism is the release of fatty acids from TAG via the action of lipases . We show here that an additional , important regulated step is the activation of fatty acids for beta-oxidation via Acyl Co-A synthetases ( ACS ) . We identify pudgy as an ACS that is transcriptionally regulated by direct FOXO action in Drosophila . Increasing or reducing pudgy expression in vivo causes a decrease or increase in organismal TAG levels respectively , indicating that pudgy expression levels are important for proper lipid homeostasis . We show that multiple ACSs are also transcriptionally regulated by insulin signaling in mammalian cells . In sum , we identify fatty acid activation onto CoA as an important , regulated step in triglyceride catabolism , and we identify a mechanistic link through which insulin regulates lipid homeostasis .
The insulin/IGF signaling ( IIS ) pathway is a highly conserved and critical regulator of metabolism in mammals and in flies , where it senses organismal nutrient levels to regulate multiple physiological functions including carbohydrate metabolism , tissue growth and longevity [1]–[3] . Insulin regulates carbohydrate metabolism by controlling expression and activity of a number of metabolic enzymes such as phosphofructokinase-2 , PEPCK , Glycogen synthase and Glycogen phosphorylase [4] . Conditions of altered insulin signaling are associated not only with changes in carbohydrate metabolism , but also with abnormal lipid metabolism , as in the cases of Type 2 Diabetes-associated obesity and Non-Alcoholic Hepatic Steatosis [5] , [6] . A large body of evidence suggests that insulin resistance plays a central , causal role in the development of the lipid imbalances observed in both of these conditions [5] , [6] , however the molecular mechanisms leading to these lipid imbalances are not completely understood . This raises the need to better understand the molecular connections between insulin signaling and lipid metabolism . The molecular relationship between insulin signaling and lipid homeostasis is complex , as dyslipidemia is considered to be both a cause and a consequence of insulin resistance [6] . That said , IIS clearly plays a causative role in regulating the balance of lipid production versus breakdown in animals , since mice and flies in which IIS has been specifically manipulated have altered lipid metabolism ( [7] , [8] and reviewed in [9]–[11] ) . The molecular mechanisms by which IIS regulates lipid metabolism are only partially understood . On the one hand , IIS promotes fatty acid biosynthesis [12] , [13] . On the other , IIS regulates fatty acid catabolism [13] , [14] . Fatty acid catabolism is a multi-step process ( Figure 1A ) . First , fatty acids are mobilized from stored triacylglycerols ( TAG ) via the activity of lipases to yield free fatty acids . Second , the free fatty acids are activated by coupling to Coenzyme A ( CoA ) . This step is catalyzed by the acyl-CoA synthetase ( ACS ) family of enzymes . Third , the free fatty acids are imported into mitochondria . Finally , in mitochondria , the fatty acids are oxidized , yielding energy . Some of the steps in this catabolic pathway are known to be regulated by IIS . For instance , IIS inhibits expression and activity of lipases such as adipose triglyceride lipase and hormones sensitive lipase [15] , [16] . IIS also decreases the rate of fatty acid entry into mitochondria [17] in part via a FoxO-dependent process [18] . A complete molecular understanding of how IIS regulates fatty acid catabolism , however , is currently lacking . The upstream signaling events of the IIS pathway are fairly well characterized . Activation of insulin/IGF receptor ( s ) leads to a relay of phosphorylation events activating a number of kinases including PI3K , Akt/PKB , TOR-C1 and S6K , thereby inhibiting a key transcription factor FOXO ( for review [19] ) . A challenge in the field remains , however , to obtain a complete understanding of how these upstream ‘signaling’ components of the IIS pathway link to , and regulate , the metabolic biochemical pathways controlling cellular metabolism . Discovering the connections between the signaling components of the insulin pathway and the metabolic enzymes controlling cellular biochemical pathways remains an important step in understanding how IIS controls metabolism generally , and lipid metabolism in particular . We identify here an ACS which we term pudgy , as a gene that is strongly upregulated upon fasting in Drosophila . We find that pudgy is a target of the insulin signaling pathway , as its expression is suppressed by insulin signaling , as a consequence of direct regulation by FOXO . We find that animals with reduced levels of pudgy expression are hyper-triglyceridemic and have defects in their lipid usage upon fasting . This suggests that in order to effectively channel fatty acids towards beta-oxidation upon fasting conditions , organisms need to induce both the lipolysis of fatty acids from TAG , as well as the activation of fatty acids at mitochondria for beta-oxidation . Finally , we show that expression of multiple mammalian ACSs are also regulated by insulin signaling in mouse muscle , liver and adipose cells . In sum , this work uncovers fatty acid activation by ACSs as a novel and important insulin-regulated step in TAG catabolism .
We previously studied the transcriptional output of insulin signaling in Drosophila by performing microarray analyses on fasted versus fed animals [20] . By comparing wildtype versus FOXO mutant animals , we pinpointed genes that are regulated in a FOXO-dependent manner [20] . In this and similar studies by other groups [21]–[24] , a number of acyl-CoA synthetases ( ACSs ) were found to be regulated by nutrient status . In particular , the ACS gene CG9009 emerged in our analysis as a strongly regulated gene , which we characterize further here . Quantitative RT-PCR analysis on wildtype larvae shows that expression of CG9009 , which we term here pudgy ( pdgy ) , is very strongly up-regulated in the fat body upon 18 hours of fasting , increasing 110-fold ( Figure 1B ) . ( The Drosophila fat body performs the functions of mammalian adipose tissue and liver combined . ) In contrast , in FOXO21/25 null mutant larvae , expression of pudgy only increases 3 . 4-fold in the fat body upon fasting , indicating that the up-regulation of pudgy is strongly FOXO dependent ( Figure 1C , note different scale compared to Figure 1B ) . Pudgy expression behaved similarly in muscle ( Figures 1B and 1C ) . Pudgy expression could either be regulated directly or indirectly by FOXO . To distinguish these possibilities , we performed a bioinformatic scan of the promoter region of the pudgy gene , as we previously showed that functional FOXO binding sites in Drosophila are usually clustered within a few kilobases of the transcription start site of regulated genes [20] . The pudgy promoter region had a significant number of consensus FOXO binding sites – 3 perfect ( GTAAACAA ) and 3 imperfect ( 1 mismatch in the 1st or 2nd position ) ( indicated by asterisks in Figure 1D ) . We first tested whether this region is able to serve as a FOXO-responsive cis-regulatory enhancer element . Test genomic regions were linked to a basal promoter directing luciferase expression in S2 cells . As a positive control , a genomic region of the 4E-BP gene , an established direct target of FOXO [25] , [26] , was able to induce luciferase activity in response to FOXO expression ( Figure 1E ) . Likewise , an 800 bp fragment of the pudgy region , containing 3 of the 6 FOXO binding sites , induced luciferase activity in response to FOXO expression ( Figure 1E ) , suggesting it is a bona fide FOXO response element . Next , to test whether endogenous FOXO binds these sites in vivo , we performed chromatin immunoprecipitations ( ChIP ) of endogenous FOXO from 3rd instar larvae . We performed two negative controls: a mock ChIP using pre-immune serum on wildtype larval lysates , as well as a ChIP using anti-FOXO antibody [26] on lysates of FOXO21/25 null mutant larvae ( Figure 1F ) [23] . Quantitative PCR on the immunoprecipitated material revealed that the promoter region of 4E-BP was strongly enriched in the FOXO ChIP from wildtype larvae compared to the negative control ChIPs ( ttest<0 . 001 , Figure 1F , black bars versus grey bars ) . Likewise , two test regions in the first intron of pudgy , P1 and P2 ( Figure 1D ) , were also significantly enriched in the FOXO ChIP compared to the negative control ChIPs ( ttest<0 . 05 for P1 and ttest<0 . 01 for P2 , Figure 1F ) . As negative controls , the genomic regions of mir-278 and sty were not enriched in the FOXO ChIP compared to control ChIPs ( Figure 1F ) . Together , these data indicate that FOXO binds the pudgy promoter region in vivo . In sum , this identifies pudgy is a bona fide direct FOXO target . Since FOXO activity is repressed by insulin signaling , pudgy expression should also be repressed by insulin . Indeed , pudgy expression was reduced in explants of both fat body tissue and muscle tissue when they were treated with insulin ( ttest<0 . 001 , Figure 1G ) . Moreover , in vivo , insulin signaling drops when larvae have terminated feeding and start wandering out of the food . Consistent with this , pudgy expression was 4-fold higher in wandering 3rd instar larvae ( wL3 ) compared to feeding 3rd instar larvae ( fL3 ) ( Figure 1H ) . Previous computational analyses identified CG9009/pudgy as a gene encoding an acyl-CoA synthetase ( ACS ) [27] . ACSs are a family of enzymes which activate free fatty acids for subsequent anabolic or catabolic reactions by loading them onto CoA . Each member of this family has distinct substrate specificity , loading fatty acid molecules of different lengths or saturation onto CoA [27] . In addition , each member of the ACS family has a distinct intracellular localization . This is particularly relevant in lieu of that fact that subsequent reactions involving activated acyl-CoA molecules take place in distinct subcellular compartments . Fatty acid oxidation occurs either in mitochondria in the form of beta-oxidation , or in peroxisomes . In contrast , anabolic reactions take place predominantly in the cytoplasm or endoplasmic reticulum . Thus the subcellular localization of each member of the ACS family may influence the fate of the acyl-CoA molecules that it generates [28] . By channeling fatty acids towards downstream anabolic or catabolic processes , ACSs such as Pudgy have the potential to influence the fate of the fatty acids and the overall balance of organismal lipid homeostasis [29] , a hypothesis which we test here . To confirm that the protein encoded by pudgy is indeed an ACS , we recombinantly expressed and purified His-tagged pudgy from E . coli and found that it has acyl-CoA synthetase activity in vitro ( Figure 2A ) . Pudgy is expressed in all tissues of the larva that we tested ( Figure 2B ) . Since the localization of ACSs influences their function , we investigated the subcellular localization of pudgy . Expression of a C-terminal epitope-tagged version of pudgy in S2 cells revealed that it co-localizes with a GFP construct marking mitochondria ( mitoGFP ) ( Figure 2C ) , suggesting pudgy may load fatty acids onto CoA for mitochondrial beta-oxidation ( see below ) . To study the physiological role of pudgy , we obtained flies containing a transposon insertion in the 5′ UTR of pudgy ( P{GT1}BG02662 , “pdgy[BG]” , Figure 1D ) . The pdgy[BG] mutation was back-crossed into the w1118 background for five generations ( via females ) in order to obtain two stocks with similar genetic backgrounds , differing by presence or absence of the pdgy[BG] mutation . The resulting stock carrying the pdgy[BG] mutation in the w1118 background was used for all subsequent experiments described here , and will be referred to as pdgy[BG] mutant flies , whereas the w1118 flies will be referred to as controls . pdgy[BG] homozygous larvae and adults have strongly reduced expression of pudgy , measured by quantitative RT-PCR ( Figure 2D and 2D′ respectively ) . We believe this animal model may not represent a complete pudgy null situation , but is a good model for studying the physiological effects of strongly reduced pudgy function . To test whether pudgy is involved in fatty acid oxidation , we measured oxygen consumption in control and pdgy[BG] mutant larvae using a Clark electrode . In the absence of drugs , oxygen consumption in pdgy[BG] mutant larvae was significantly reduced compared to controls ( Figure 2E ) . Subsequent addition of etomoxir , a specific inhibitor of Carnitine palmitoyltransferase I ( CPTI ) [30] , required for the transport of fatty acids into mitochondria where beta-oxidation takes place , causes this difference in oxygen consumption to be abrogated ( 300 µM etomoxir , Figure 2E ) . This indicates that the difference in oxygen consumption between pdgy[BG] mutants and controls is due to differential mitochondrial lipid oxidation . Subtraction of the basal rate of oxygen consumption in the presence of 300 µM etomoxir from the oxygen consumption in the absence of etomoxir , yields the rate of CPTI-dependent oxygen consumption , revealing that pdgy[BG] mutants have significantly reduced ß-oxidation levels compared to controls ( Figure 2E′ ) . Conversely , overexpression of pudgy in larvae was sufficient to increase the rate of fatty acid beta-oxidation ( Figure S1 ) . The above-mentioned data indicate that insulin/IGF signaling modulates pudgy expression in vivo . Therefore , we asked whether modulation of pudgy expression has an impact on organismal lipid homeostasis . We first tested the effect of increasing pudgy expression . Ubiquitous over-expression of pudgy from a transgene using the GAL4/UAS system [31] was sufficient to cause a significant reduction in organismal triglyceride levels both in larvae and in adults ( Figure 3A and 3A′ respectively ) . pdgy[BG] homozygous mutants are viable , fertile , and normally patterned ( Figure S2A ) . Conversely to pudgy gain-of-function , pdgy[BG] mutant larvae and adults have significantly elevated triglyceride levels compared to controls ( Figure 3B and 3B′ respectively ) . This phenotype was fully rescued in larvae and partially rescued in adults by introducing UAS-pudgy into the pdgy[BG] mutants , since the pdgy[BG] insertion is a GAL4 gene trap resulting in both pudgy loss-of-function as well as GAL4 expression ( Figure 3B and 3B′ ) . A comprehensive lipidomic analysis using Ultra Performance Liquid Chromatography coupled to mass spectrometry ( UPLC-MS ) of molecular lipid species in pdgy[BG] mutant versus control flies revealed that many , but not all , triglyceride species were significantly elevated in pdgy[BG] mutant adults ( Table S1 ) . The results for the 20 most abundant TAGs are shown in Figure 3C . In addition , levels of some other complex lipids , such as cholesteryl ester ( 19∶0 ) , were also elevated in pdgy[BG] mutants ( Table S1 ) . The increased adiposity of pdgy[BG] mutants is consistent with the reduced levels of fatty acid oxidation observed in these animals ( Figure 2E and 2E′ ) . Furthermore , Pudgy mutants do not ingest more than control animals ( Figure S3A and S3A′ ) and have reduced expression of key lipogenic genes such as Acetyl-CoA Carboxylase ( ACC ) and Fatty Acid Synthase ( FAS ) ( Figure S3B and S3B′ ) , suggesting that mutant animals may be trying to compensate for their increased adiposity . These results are analogous to those observed in ACSL1 knockout mice , which have elevated fat mass [32] . Together , they indicate that the level of expression of ACSs is important for setting steady-state lipid levels both in flies and in mammals . We next studied the physiological consequences of impaired pudgy expression in flies upon fasting . Upon complete food withdrawal , pdgy[BG] mutants survived significantly longer compared to controls ( Figure 4A and Figure S3C ) . This is likely due in part to the increased adiposity of pdgy[BG] mutants , as starvation survival is known to correlate with lipid levels in the fly [25] , [33]–[35] . Additionally , this could also be due in part to a reduced rate of lipid catabolism which is nonetheless sufficient to support viability . We therefore tested whether lipid catabolism might also be impaired in pdgy[BG] mutants , as they have reduced fatty acid oxidation . Upon food removal , control flies progressively catabolized their triglyceride stores . After 6 hours of fasting , both control larvae and control adult flies significantly reduced their triglyceride stores ( Figure 4B and 4B′ , grey curves ) . Control larvae reproducibly displayed an unexpected transient increase in stored triglycerides after 2 hours of fasting before starting to deplete them ( Figure 4B ) . In contrast , pdgy[BG] mutants did not show any reduction in triglyceride levels the first 6 hours of starvation ( Figure 4B and 4B′ , black curves ) . Only as of 8 hours of starvation did pdgy[BG] mutants start depleting their triglycerides stores , completely depleting them by 36 hours of fasting ( Figure 4B , 4B′ and Figure S3D ) , indicating that after an initial period , they were nonetheless able to catabolize lipids . Similar defects could also be observed by staining fat bodies of control and pdgy[BG] mutants with Nile Red ( Figure 4C ) . Interestingly , both the extended survival upon food withdrawal as well as the delay in triglyceride consumption the first 6 hours of fasting are also observed in mutants for another gene involved in lipid catabolism - the fly homolog of adipocyte triglyceride lipase , brummer [24] , [36] . To study lipid catabolism in pdgy[BG] mutants in more detail , we performed quantitative lipidomic profiling of fed versus fasting flies . Since the direct substrates of ACS action are free fatty acids , we first quantified free fatty acids in pdgy[BG] mutant and control animals ( Figure 4D ) . Upon starvation , levels of free C14:0 , C16:0 and C16:1 drop in control animals ( Figure 4D ) . Since levels of free fatty acids reflect the balance between fatty acid lipolysis and fatty acid ligation to CoA ( Figure 1A ) , this indicates that upon starvation ACSs become activated in order to handle the increased production of free fatty acids coming from triglyceride lipolysis . In contrast , in pdgy[BG] mutants , levels of free C14:0 and C16:0 remained aberrantly high ( Figure 4D ) , as expected from impaired ACS activity in the pudgy mutants . Defects were only apparent in a subset of free fatty acids ( Figure 4D ) suggesting that the metabolism of all fatty acids might not be affected equally by loss of pudgy in vivo . We next performed quantitative lipidomic profiling to detect all TAG species in fed versus fasting control and pdgy[BG] flies . Although many TAG species are normally catabolized in pdgy[BG] mutants ( Table S2 ) , some species are not . For instance , levels of TAG ( 39∶1 ) dropped in control animals upon fasting but remained elevated in pdgy[BG] mutants ( Figure 4E ) , whereas TAG ( 53∶3 ) remained constant in control animals but dropped in pdgy[BG] mutants ( Figure 4E′ ) . Therefore , pudgy mutants display an altered profile in the catabolism of lipid species . Consistent with this , pdgy[BG] mutants have aberrant expression of a large number of putative lipases , elongases and ACSs ( Figure S4 ) suggesting that lipid catabolic pathways may be readjusting in response to loss of pudgy . In sum , our data indicate that pudgy mutants are initially defective in the catabolism of fatty acids , but after an initial period are able to catabolize all triglycerides , albeit with a different pattern compared to controls . Interestingly , although Pudgy is an enzyme involved in lipid metabolism , we found that pudgy mutants also have a number of other non-lipid phenotypes . Pudgy mutants had significantly reduced expression of insulin-like peptides ( Figure 5A and 5A′ ) . Correspondingly , they had elevated expression of 4E-BP , a direct FOXO target , consistent with reduced insulin signaling in these animals ( Figure 5A and 5A′ ) . Pudgy mutants also have two phenotypes associated with reduced insulin signaling: they are mildly , but significantly reduced in size compared to controls ( Figure 5B and 5B′ ) and they are long-lived ( Figure 5E ) . In addition , pudgy mutants also have reduced glycogen stores ( Figure 5C and 5C′ ) and increased circulating sugars ( Figure 5D and 5D′ ) suggesting elevated mobilization of carbohydrates . Conversely , pudgy overexpression leads to reduced circulating sugars ( Figure 5F ) . Although these phenotypes are not the focus of this story , and we do not know their underlying molecular mechanisms , they are worth noting as they probably represent crosstalk mechanisms in pdgy[BG] animals caused by their elevated lipid stores and reduced lipid oxidation , of interest for future studies . We next asked whether our two central observations from Drosophila—that insulin signaling regulates ACS expression and that ACS expression levels are important for lipid homeostasis—can also be observed in a mammalian context . To this end , we treated three different cell types , 3T3-L1 adipocytes , Hepa1 . 6 hepatocytes and C2C12 myotubes , representing three different tissues of metabolic importance , in the presence or absence of insulin , and measured by quantitative RT-PCR the expression of all medium-chain , long-chain and very-long-chain ACSs . Reported in Figure 6 are the ACSs who's transcription was regulated in a manner similar to that of pudgy , i . e . repressed by insulin . In addition , other ACSs were either not transcriptionally regulated by insulin , or were induced by insulin ( Table S3A and S3B ) . In 3T3-L1 adipocytes , expression of six different ACSs was up-regulated upon removal of serum ( Figure 6A ) . This up-regulation was suppressed if insulin was supplied upon serum removal , indicating that the up-regulation was specific for insulin signaling ( Figure 6A ) . In particular , expression of ACSL4 increased very strongly , 12-fold , within the short 1-hour time window of serum removal ( Figure 6A ) . Likewise , expression of 6 different ACSs increased in an insulin-dependent manner in Hepa1 . 6 hepatocytes upon serum removal , with ACSVL5 increasing 13-fold ( Figure 6B ) . Although some ACSs are similarly regulated by insulin in both cell types , such as ACSL1 , other ACSs are specifically regulated in one cell type or the other , probably reflecting the specific function of each tissue . Finally , a number of ACSs were also regulated by insulin in C2–C12 myotubes ( Figure 6C ) . ( Since C2–C12 myoblasts are differentiated into myotubes by culturing in low-serum conditions , the ‘control’ and ‘serum-deprived’ conditions are similar in gene expression . ) To test whether the level of expression of ACSs in 3T3-L1 adipocytes affects lipid homeostasis , we knocked down expression of three different ACSs – ACSL1 , ACSL3 and ACSL4 . Knockdown of ACSL1 and ACSL3 using siRNAs caused reduced triglyceride storage in differentiated 3T3-L1s ( Figure 6D ) in a manner that correlated with relative knock-down efficiency ( Figure S5A , S5B ) . This is consistent with previous reports that ACSL1 promotes fatty acid uptake and incorporation into TAG in 3T3-L1s [37] , [38] . Using a different approach , 3T3-L1s expressing an shRNA targeting ACSL4 also had reduced triglyceride storage ( Figure 6E and Figure S5C ) .
Fatty acid ( FA ) catabolism represents an important energy yielding mechanism for cells and organisms , contributing up to 50–60% of a person's energy expenditure under aerobic exercise conditions [39] . Fatty acid catabolism can be envisioned in two steps ( Figure 6F ) . First , fatty acids are mobilized from stored triacylglycerols ( TAG ) via the activity of lipases to yield free fatty acids . Second , the free fatty acids are oxidized , yielding energy . Traditionally , textbook knowledge considers the first step – mobilization via lipases – to be the important regulated step . However , several lines of reasoning suggest that lipolysis cannot be the only important regulated event in the fatty acid catabolic pathway . Firstly , liberation of free fatty acids from TAG does not necessarily channel them towards beta-oxidation . Free fatty acids can have several fates , including not only beta-oxidation but also fatty acid elongation ( yielding very long chain fatty acids ) and re-esterification to generate complex lipids including TAG [40] , [41] . In fact , a large fraction of FAs liberated from TAG participate in a ‘futile’ cycle , being re-esterified to generate new TAG [42] . Quantitative estimates of the triglyceride/fatty acid cycle in humans and in animals show that only a small fraction of the FFA released as a result of lipolysis in adipose tissue are oxidized , and the majority are re-esterified to triglycerides in various tissues [43] . Secondly , elevated levels of free FA are believed to be deleterious to animals , causing lipotoxicity and contributing towards insulin resistance [40] . Therefore , increased FA levels due to increased lipolysis without concurrent upregulation of downstream biochemical pathways might actually be noxious to the animal . We identify here the subsequent step in fatty acid catabolism - coupling of fatty acids to CoA via ACSs - as an additional , important regulated step in lipid catabolism . A priori , it was possible that the level of expression of pudgy in vivo was not limiting for lipid oxidation , and that lipid catabolism in Drosophila is only regulated by availability of free fatty acids via lipolysis . However , our data suggest this is not the case . Both a reduction and an increase in pudgy levels effects total lipid levels in the fly ( Figures 3A , 3A′ , 3B , 3B′ ) , indicating that regulation of pudgy levels contributes significantly to total body lipid homeostasis . This makes sense in light of the fact that free fatty acids can have multiple different fates once released from triglycerides , such as beta-oxidation or re-esterification to form triglycerides . Therefore the relative activities of biochemical reactions downstream of lipolysis are important for determining the fate of the released fatty acids . In particular , the balance in expression and activity of ACSs that activate fatty acids for beta-oxidation versus lipid biosynthesis may be of particular importance . In Drosophila , upon starvation , FOXO upregulates expression of the fly adipocyte triglyceride lipase homolog , brummer [24] . By upregulating expression of both brummer and pudgy , FOXO mounts a concerted effort towards channeling fatty acids from their stored form towards beta-oxidation . It may appear surprising that blocking fatty acid ß-oxidation via mutation of pudgy leads to increased TAG levels in the animal , since lipolysis is often considered to be the key step in regulating TAG levels . Indeed , via the actions of lipases and acyl-transferases , fatty acids cycle between a free form and a stored TAG form ( Figure 6F ) , however neither of these enzymatic activities either creates or destroys fatty acids . The steady-state level of fatty acids in an organism depends only on the relative balance of fatty acid synthesis/uptake versus fatty acid oxidation . Therefore , reducing ß-oxidation increases total organismal fatty acids . Since free fatty acids are in equilibrium with the stored TAG form , this entails an increase in TAG levels ( Figure 6F ) . An alternate interpretation of our data is that the observed delay in TAG consumption reflects a reduced global metabolic rate caused indirectly by lack of pudgy activity . We believe this interpretation is unlikely , because a global redution in metabolic rate would be expected to lead to a concomitant increase in the levels of both stored lipids and stored carbohydrates ( ie glycogen ) . Pudgy mutants , however , have elevated lipids levels but reduced glycogen levels , suggesting a lipid-specific defect in accordance with pudgy's ACS function . Insulin/IGF signaling is known to control lipid biosynthesis in part via SREBP1 , and lipid catabolism via regulation of lipases such as hormone sensitive lipase and via decreasing the rate of fatty acid entry into mitochondria [15] , [44] , [45] . We identify here the ACS CG9009/pudgy as one molecular link between the insulin signaling pathway and lipid catabolism in Drosophila . We find that pudgy is a transcriptional target gene of the insulin pathway which is directly regulated by FOXO . By repressing pudgy expression , insulin blocks the channeling of fatty acids towards the beta-oxidative pathway . Insulin has been reported to induce expression of two ACSs in mammals - ACSL5 via a mechanism involving SREBP1c [46] , and ACSL6 via an unknown mechanism [47] – however to our knowledge pudgy is the first example of an ACS which is repressed by insulin . Likewise , although pudgy belongs to a clade of ACSs that does not also include human paralogs , we identify a number of human ACSs that are transcriptionally repressed by insulin in mammalian cells , analogously to pudgy . We find that pudgy mutants have a significant number of metabolic alterations . For instance , in addition to the changes in lipid metabolism , we find that pudgy mutants have reduced glycogen stores and increased circulating sugars . Although the underlying mechanism is unclear , one plausible explanation is that pudgy mutants need to rely more on glucose mobilization to maintain cellular energy levels , to compensate for reduced fatty acid beta-oxidation , which is normally a significant energy source . We also find that pudgy mutants have a different profile of lipid homeostasis and starvation-induced catabolism compared to controls . Under fed conditions , some lipid species in pudgy mutants are highly elevated , such as TAG ( 50∶1 ) which is almost 3-fold the normal levels , whereas others such as TAG ( 42∶0 ) are unperturbed ( Figure 3C ) . Likewise , during starvation , the catabolism of lipid species is altered , with some TAGs being catabolized more readily and some less readily compared to controls ( Figure 4E and 4E′ ) . Fatty acid species are linked to each other via a complex network of biochemical pathways involving saturases , desaturases , elongases , ACSs , lipases , etc . This ‘landscape’ of lipid species is clearly perturbed by removal of pudgy . This perturbation might be partly a direct consequence of loss of pudgy , and partly an attempt of the system to compensate . Indeed , at the gene expression level , a very large proportion of genes with putative functions in fatty acid metabolism are altered in pudgy mutants , suggestive of compensatory mechanisms ( Figure S4 ) . For instance , the elongase eloF is more than 2-fold up-regulated in the pudgy mutant , and the ACS CG6432 is dramatically down-regulated . In sum , we identify here the ACS pudgy as a transcriptional target of insulin signaling , and show that modulation of pudgy expression levels causes changes in steady-state lipid levels in the fly . Mammalian tissue culture experiments suggest similar mechanism may be at work in mammalian cells .
A list of oligos used for clonings and quantitative PCRs can be found in Supplemental Materials & Methods ( Text S1 ) . Additional oligos sequences are available upon request . UAS-pudgy was generated by cloning the CG9009 coding sequence , obtained by RT-PCR as an XhoI-XbaI fragment , into the XhoI-XbaI sites of pUAST . The mito-GFP ORF , encoding the 31 amino acid mitochondrial import sequence from human cytochrome C oxidase subunit VIII fused to the N terminus of GFP , was amplified from flies carrying mito-GFP ( Bloomington Stock Center , [48] ) and cloned into pCasper4 carrying a tubulin promoter . For luciferase assays , the FOXO enhancer region of pudgy intron 1 was amplified as a KpnI-KpnI fragment and cloned into the KpnI site of a luciferase plasmid containing the Adh basal promoter , described in [20] . Remaining constructs for the FOXO luciferase assay were described previously [20] . FOXO21 and FOXO25 flies [23]; P{GT1}BG02662 flies and actin-GAL4 flies ( Bloomington Stock Center ) . For all metabolic , respiratory , and longevity analyses , animals were reared under strictly controlled growth conditions . Eggs were collected on apple plates , and newly hatched L1 larvae were seeded in vials at a density of 60/vial and grown at 25°C without yeast supplementation . Adult flies were then aged 3 days for analysis . All assays were done in triplicate . Our fly food recipe is as previously reported [49] . Metabolic , starvation and longevity assays were performed as in [40] and as detailed in Text S1 ( Supplemental Materials and Methods ) . Growth controlled w1118 and pdgy[BG] mutant males were aged 3 days , and then fed normal food or starved on 0 . 8% agarose/PBS overnight ( 16 hours ) . The flies were frozen in liquid nitrogen and cryo-dried . The samples were then analyzed by UPLC-QTof-MS using an Acquity BEH C18 ( 1 . 7 µm 2 . 1×100 mm ) column and electrospray ionization in positive ion mode . Details are provided in the Supplemental Materials & Methods ( Text S1 ) . His-tagged pudgy protein was obtained by cloning the coding sequence into pET23d , expressing it in BL21 E . coli , and purifying it using Ni-NTA Agarose beads ( Qiagen ) . 4 . 2 µg of recombinant pudgy-His , or an equivalent amount of eluate from a parallel purification using bacteria not expressing pudgy-His ( circa 4 . 3 mg ) , were added into reaction buffer ( 50 mM Tris–HCl pH 7 . 8 , 10 mM sodium acetate , 4 mM ATP , 0 . 15 mM CoA , 1 mM magnesium chloride , 10 mM DTT ) with 10 nmol free fatty acid . After incubated at 37C for 30 min , the synthesized acyl-CoA was detected using the Free Fatty Acids Quantification Kit ( Biovision ) , omitting the ACS incubation step . As a positive control , 4 . 2 µg of ACS supplied with the kit was used . Growth-controlled , wandering third instar larvae were cleaned in cold PBS , dried on filter paper and weighed . Larvae were then dissected into ice-cold BIOS buffer ( 2 . 77 mM CaK2EGTA , 7 . 23 mM K2EGTA , 5 . 77 mM Na2ATP , 6 . 56 mM MgCl2·6H2O , 20 mM Taurine , 15 mM Na2Phospho-creatine , 20 mM Imidazole , 0 . 5 mM DTT , 50 mM MES ) and subsequently permeabilized with 4 mM digitonin in BIOS buffer for 15 min at 4°C in a shaker . Tissues were then resuspended in ice-cold FAO medium ( 110 mM NaCl , 4 . 7 mM KCl , 2 mM MgSO4 , 1 . 2 mM Na2HPO4 , 2 . 5 mM glucose adjusted to pH 7 . 4 , supplemented with 0 . 5 mM carnitine ) . Oxygen consumption was measured using a Clark electrode and normalized to animal body weight . Etomoxir was added ( 50 µM or 300 µM ) to block acyl-CoA transport via CPTI . Detailed procedures of methods used are included in the Supplemental Materials & Methods ( Text S1 ) .
|
Type 2 diabetes , which is reaching epidemic proportions worldwide , is often associated with obesity and an imbalance in organismal lipid homeostasis . Therefore , understanding how insulin regulates lipid biosynthesis and breakdown is necessary . Surprisingly , the molecular mechanisms by which insulin regulates fatty acid catabolism are not entirely understood . We show here that insulin signaling regulates expression of acyl-CoA Synthetases ( ACS ) . ACSs couple fatty acids to Coenzyme A , thereby activating them for subsequent biochemical reactions . In Drosophila , we find that insulin signaling modulates expression of one ACS called Pudgy , which activates fatty acids for beta-oxidation . Modulation of pudgy expression leads to changes in overall organismal lipid homeostasis . Likewise , we show that in mammalian cells insulin signaling regulates expression of a number of ACSs and that ACS expression modulates steady-state lipid levels .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"animal",
"models",
"developmental",
"biology",
"model",
"organisms",
"molecular",
"development",
"biology"
] |
2012
|
Insulin Signaling Regulates Fatty Acid Catabolism at the Level of CoA Activation
|
Understanding the role of humans in the dispersal of predominately animal pathogens is essential for their control . We used newly developed Bayesian phylogeographic methods to unravel the dynamics and determinants of the spread of dog rabies virus ( RABV ) in North Africa . Each of the countries studied exhibited largely disconnected spatial dynamics with major geo-political boundaries acting as barriers to gene flow . Road distances proved to be better predictors of the movement of dog RABV than accessibility or raw geographical distance , with occasional long distance and rapid spread within each of these countries . Using simulations that bridge phylodynamics and spatial epidemiology , we demonstrate that the contemporary viral distribution extends beyond that expected for RABV transmission in African dog populations . These results are strongly supportive of human-mediated dispersal , and demonstrate how an integrated phylogeographic approach will turn viral genetic data into a powerful asset for characterizing , predicting , and potentially controlling the spatial spread of pathogens .
Every year approximately 55 , 000 people die from rabies [1] . Over 99% of these deaths occur in developing countries where rabies virus ( RABV; negative-sense RNA virus , family Rhabdoviridae ) is endemic in the domestic dog [2] . Rabies has been neglected across much of Asia and Africa , despite becoming an increasing problem in the recent decades [1] , [3] , [4] . Although the history of rabies in Africa prior to the 20th century is uncertain [5] , the currently circulating dog rabies virus is thought to have emerged during the 19th and 20th centuries [6] , [7] . Despite the importance of dogs as vectors for human rabies , little is known about the spatial and temporal dynamics of rabies in this major reservoir species , or the processes responsible for its maintenance in specific geographic localities . In particular , the role of human activities in mediating the spread of dog RABV is unclear , nor is it known how landscape characteristics , including human infrastructures such as roads , affect RABV dispersal within dog populations . However , such information is critical to revealing the determinants of RABV transmission and hence for its control in the domestic dog . We used a recently developed probabilistic approach [8] to determine the spatial and temporal dynamics of dog RABV transmission from a large-scale gene sequence study . We encode different phylogeographic scenarios of viral spread , as well as different landscape features , in a model-based approach , and choose among these models in a quantitatively rigorous fashion . Our focus was on dog populations in North Africa where RABV has been endemic for more than a century , and our key aim was to determine how ecological , anthropogenic and evolutionary dynamics shape the spatial distribution and spread of this important zoonotic pathogen [9] , [10] , [11] , [12] .
We first inferred the evolutionary history of 287 RABV sequences ( 3080 nt; encompassing the whole N , P and intergenic G-L region ) sampled from Algeria , Morocco , Tunisia and the Spanish territories from North Africa ( Ceuta and Melilla ) between 1986 and 2008 . All these viruses are assigned to the Africa 1 genotype ( relevant epidemiological information for all RABV isolates analysed in this study is presented in Table S1 in Supporting Information S1 ) . We estimated the timescale of this evolutionary history using a Bayesian Markov chain Monte Carlo ( MCMC ) approach [13] . The most recent common ancestor of all the North African RABV sampled here was estimated to have existed between 1878–1945 , supporting previous suggestions that dog RABV was periodically responsible for local sporadic epidemics in the middle of the 19th century [14] , and that rabies became enzootic in this entire region during the 20th century . More generally , this timescale is consistent with the expanding European colonial influence in North Africa [7] . This analysis also revealed distinct phylogenetic lineages in Algeria , Morocco and Tunisia , indicating that viruses generally grouped according to their country of origin ( Figure 1 ) . This result is unexpected if the virus is only dispersed through the local movement of animals as observed in wildlife rabies [9] , [10] as these would not respect geo-political boundaries . Indeed , we found only a few exceptions to the country-specific clustering , such as two Algerian sequences within the Moroccan clade and four Moroccan sequences in the Algerian clade . The Africa 1 clade is therefore consistent with the general phylogeographic pattern observed for dog RABV at reasonably large geographic scales; a series of spatially distinct clusters that experience relatively little contact among them [6] , [7] . To analyze intra-country patterns of viral transmission in more detail , we considered a stochastic diffusion process among the 20 ( Algeria ) and 28 ( Morocco ) sampling localities for which most data were available ( Figure 2 and Figure S1 in Supporting Information S1 ) . We quantified the degree of spatial admixture using a modified Association Index ( AI , [8] , [15] ) , and by summarizing the number of inferred transitions to each location within Algeria and Morocco ( Table 1 ) based on an analysis in which rates of diffusion between each pair of locations were estimated . Although these analyses reveal that there is still significant spatial structure within each country ( p<0 . 001 ) , the AIs are considerably higher ( 0 . 67 [0 . 62–0 . 73] and 0 . 55 [0 . 51–0 . 63] for Algeria and Morocco , respectively ) than those found for rabies at a larger spatial scale ( e . g . , 0 . 087 [0 . 043–0 . 132] for the Africa 2 lineage in Central and West Africa ) [8] , indicating weaker spatial structure at the within-country level . The summaries of transitions to each location generally identify multiple independent introductions of viruses in each location from which several samples were obtained ( Table 1 ) . Overall , the number of independent transitions to densely sampled locations is lower in Morocco than Algeria , in agreement with the lower AI for Morocco . Taken together with the strong spatial structure across countries , these results suggest that a relatively fluid RABV diffusion process within countries is restricted by geopolitical boundaries at larger scales . To identify the factors that may explain RABV spread , we incorporated several potential predictors as relative diffusion rates among each pair of locations , and tested these against equal rates of diffusion . Specifically , we considered geographical distances ( great-circle distances ) , human population size , road distances and spatial accessibility measures . Road distances were derived from transport network data ( Figure 2 ) and demonstrated a strong correlation with great-circle distances ( r = 0 . 96 ) . More detailed landscape features , which may imply multiple , direct and indirect pathways connecting the different localities sampled in this study , were represented by accessibility data . These data reflect the travel time to the nearest major city using road/track-based travel [16] and were less correlated with geographical distances ( r = 0 . 61 ) . We employed circuit theory to translate the accessibility landscape into an origin-destination distance matrix ( the so-called ‘isolation by resistance model’ ) [17] . We also tested a simple gravity model of viral spread that , in the absence of real dog population sizes for the locations involved , was based on human population sizes for the discrete as a proxy . Finally , we also used population sizes in a landscape approach , similar to accessibility measures , to construct a population surface matrix [18] . Marginal likelihood estimates of the model fit of these different predictors suggested that RABV spatial dynamics are best described by road distances ( Table 2 ) . This was consistent across both countries and again supports human-assisted dispersal of rabies-infected dogs . As expected by their high correlation , geographical distances provided only a marginally lower fit compared to road distances . Only the population surface provided inconsistent results between both countries; whereas this model competes with road distances in Algeria , the population surface did not provide a good fit to the Moroccan data ( Figure S2 in Supporting Information S1 ) . Although accessibility did not seem to explain RABV diffusion as well , we note that all samples were obtained from relatively accessible parts of Morocco and Algeria . To quantify and compare the dissemination process with previous results , we estimated the rate of RABV gene flow among the sampled isolates using ‘Markov jump’ counts [19] of location state transitions and their reward-associated distances between locations across each branch . The posterior average rate of viral gene flow among localities estimated for Algeria was 26 km/yr ( 95% highest probability density interval: 18–34 ) and 33 ( 23–43 ) km/yr based on great circle distances and road distances , respectively . Somewhat higher viral gene flow rate estimates were obtained for Morocco with 42 ( 26–58 ) km/yr and 51 ( 34–72 ) km/yr for great circle distances and road distances , respectively . We note that the rates of viral gene flow estimated here are highly dependent of the scale of sampling such that comparison may only prove useful at the same geographic scale . However , these estimates were 2 . 7 to 4 . 4 times higher than those recorded in established enzootic situations in wildlife animals [9] , again suggestive of human-mediated transmission . Although it is theoretically possible that these relatively high rates reflect epidemic waves periodically moving through this geographical region [20] , particularly since similar rates have been observed in wild carnivores during epidemic spread [9] , [10] , such waves were not observed in the geographical areas studied here and where the virus appears to be largely enzootic . The occasional mixing of sequences from different locations at the tips of the inferred tree ( Figure 1 ) is suggestive of long distance spread in relatively little time ( 6 months to one year ) . To quantify such rapid and long distance spread , we summarized the posterior distribution of distances covered along individual branches ( Figure 3 ) . We focused on branches along which inferred location state changes occurred in a time period of less than 1 year , and between 1 and 2 years . As a control , we analysed the branches without inferred state changes; as expected these all had negligible Markov jump count distances ( not shown ) . Across the posterior distribution of trees , we observed between 5 and 13 branches per tree that have a time length less than 2 years and cover a distance of more than 200 km , and 12 to 13 branches that cover a distance of about 100 km ( Figure 3 ) . Importantly , our ability to clearly detect long-distance movement is limited to branches representing short evolutionary times; longer branches could also harbour such events , providing an explanation for the relatively high average rates of viral gene flow . The rates of viral gene flow we estimate among the sampled isolates from Algeria and Morocco contrast with those of spatial RABV movement in an African dog population that should experience very limited human-mediated dissemination of rabid dogs [21] . In this case , the spatial dispersal of single RABV infections was estimated to be predominantly less than 2 km ( and always smaller than 20 km ) . Considering that the average incubation period of RABV is between 22 to 29 days [20] , [21] , [22] , [23] , [24] , it is clear that such long distances as those recorded in our study could only be achieved with at least some human intervention . To investigate more formally how the RABV distribution we observe in Algeria and Morocco contrasts with the patterns of spread we would expect from transmission dynamics in African dogs alone ( i . e . without human intervention ) , we simulated a phylogeodynamic process based on epidemiological parameters obtained from detailed analyses of rabies transmission biology [20] , [21] . In particular , we considered epidemiologically informed virus movement over all evolutionary histories in the posterior distribution resulting from our phylodynamic inference ( see Supplementary Information ) . In our spatial simulation we analyze cases in which ( i ) each new infection takes a random direction in continuous space , or ( ii ) subsequent infections consistently take the same direction ( Figure 4 ) . Although the latter may not be very realistic , it should resemble virus movement along roads . For both Algeria and Morocco , spatial diffusion is initiated at the centre of the sampling locations , such that the process has the largest probability to cover these locations a priori . When assuming up to one year of movement these simulations clearly show that RABV could not have spread to the same extent as shown by the current sampling in Algeria and Morocco if the virus was simply being transmitted by dog dispersal alone . Even if we enforce a year of successive RABV transmissions in the same direction , which is highly implausible given the observed dynamics of dog RABV in a local setting [21] , the simulations still do not attain the observed spatial RABV spread . In addition , the distances realized by dispersal in random directions along branches less than 2 years were all less than 60 km , which is far more restricted than estimated for the real data ( Figure 3 ) . Rabies is a prime example of an infectious disease in which dispersal can be exacerbated by animal movement mediated by humans . This is illustrated by raccoon rabies in Virginia , USA [25] , dog rabies in Indonesia in Flores Island [26] , in Bali ( F . X . Meslin , Personal communication ) and in parts of Europe [27] . Each epidemic resulted in enormous expenditure on rabies post exposure prophylaxis in humans and animal vaccination programs [28] , [29] , [30] , [31] . Importantly , our study allows us to quantify rates of viral gene flow among sampled dog isolates ( between 18 and 72 km/yr ) in a mixed geographic and socio-economic landscape , such as those characterized by Algeria and Morocco where there is currently little dog vaccination . In addition , our analysis suggests that the human-mediated dispersal of infected dogs is likely to continue to play a major role in the transmission of RABV in geographical areas where it has been present for many years . Indeed , our observations of administrative borders that restrict a relatively fluid pattern of spread , the occasional long-distance movement of viruses to particular countries , and the fit between spatial dynamics and road distances , all point to the displacement of rabies-infected dogs by humans . Understanding the frequency and distance of movements of potentially infected animals is of paramount importance in predicting the spread of viral infections [32] , [33] . In addition , such information has important implications for disease control; understanding the conditions under which the containment of wildlife [34] and dog rabies can reliably be achieved will assist in the long term goal of eliminating animal RABV . In particular , that humans mediate the transmission of RABV among dogs in North Africa requires that intervention procedures are implemented more rapidly than in situations in which humans play little or no role in viral transmission . The high cost associated with surveillance underscores the importance of sampling design and the development of cost-effective monitoring and testing approaches [9] , [12] , [35] . In addition , this study illustrates the power of phylogeographic approaches [8] to identify the factors responsible for the spread of major animal and zoonotic pathogens . By integrating spatial dynamics with temporal inferences , the Bayesian analysis utilized here constitutes a powerful new tool that may complement traditional epidemiological methods in studying the effects of human behaviour on the evolution of zoonotic viruses .
The Office of Veterinary Public Health Services of the different countries coordinates follow-up per animal bites . The respective state health departments ( in conjunction with qualified laboratories that they designate ) conduct all collection , observations , and euthanization ( if necessary ) of animals suspected of rabies , according to established national standardized protocols . A total of 287 isolates sampled from Morocco , Algeria , Tunisia and Spain ( Ceuta and Melilla ) were collected by the authors within the framework of these qualified laboratories , and sequenced . These samples were collected from dead animals suspected of rabies so that submission for laboratory rabies diagnosis is mandatory . Spatial co-ordinates and time of sampling , covering a period of 22 years ( 1986–2007 ) , were available for the majority of these isolates . Relevant epidemiological information and GenBank accession numbers for all RABV isolates analysed in this study are presented in Table S1 in Supporting Information S1 . All the locations sampled in this study experienced cases every year . As such , our sampling does not focus on areas that have been free of rabies in the recent past . To perform a reliable evolutionary analysis of dog RABV circulating in North Africa , we aimed at selecting a genetic region with sufficient phylogenetic information . To this end , we sequenced a total of 3080 nt encompassing the N , P and intergenic G-L region . Total RNA from the original brain samples was extracted using Trizol reagent ( Invitrogen ) according to the manufacturer's instructions . RT-PCRs and sequencing reactions were performed as described previously [6] , [36] . All sequences obtained have been deposited in GenBank ( accession numbers GU798102–GU798962 ) . Additional primers used in this study were N1280 ( 5′- AGTCAGTTCTAATCATCAAGC-3′ ) , M138 ( 5′-AAGTTCCTYATGTTYTTCTTGC-3′ ) , G ( 5′GACTTGGGTCTCCCGAACTGGGG-3′ ) and L ( 5′-CAA AGG AGA GTT GAG ATT GTA GTC-3′ ) , at positions 1348–1368 , 2632–2653 , 4666–4688 and 5512–5535 , respectively , of the lyssavirus genome [37] . Multiple sequence alignment was performed using MUSCLE available through the Muscle web interface ( http://www . ebi . ac . uk/Tools/muscle/index . html ) [38] . All alignments are available from the authors on request . To investigate the evolutionary relationships and time to common ancestry among RABV lineages circulating in north Africa , we reconstructed the phylogenetic history for the entire data set using Bayesian Markov chain Monte Carlo ( MCMC ) analysis implemented in the BEAST package [13] . BEAST incorporates sampling time information to estimate evolutionary rates and a posterior distribution of time-scaled trees . We employed a GTR model of nucleotide substitution with gamma-distributed rate variation among sites and a relaxed ( uncorrelated log-normal ) molecular clock model [39] . We specified a Bayesian skyline plot model as flexible tree prior [40] . All chains were run for a sufficient length and convergence was diagnosed using Tracer ( http://tree . bio . ed . ac . uk/software/tracer/ ) ignoring 10% of the chain as burn-in . Evolutionary history was summarized using an annotated Maximum Clade Credibility ( MCC ) phylogenetic tree . Posterior probability values provide an assessment of the degree of support for each node on the tree . To reconstruct the spatial dynamics of dog-associated RABV spread and investigate the role of different diffusion predictors in shaping the epidemic in both Morocco and Algeria , we extracted two data sets with their specific spatial and temporal co-ordinates: ( i ) A total of 117 Algerian sequences ( 3080 nt ) collected from dogs in 20 cities over 7 years ( from 2001 to 2008 ) , and ( ii ) a total of 133 Moroccan sequences ( 3080 nt ) sampled from dogs in 28 cities between 2004 and 2008 . For all these isolates precise dates ( month ) of sampling and geographical localities ( city ) are available ( Table S2 in Supporting Information S1 ) . As an additional component in the fully probabilitistic Bayesian inference framework , we consider a discretized diffusion process among the sampling locations in both countries , formalized as a continuous time Markov chain ( CTMC ) model [8] . A CTMC is fully characterized using a matrix that describes the rate of movement from location state i to j for every pair of locations . To efficiently estimate the diffusion process from a single observation ( a single location realization for each sequence ) , we restrict the parameterization to a sparse set of rates that adequately explains the phylogeographic dispersal process using Bayesian Stochastic search variable selection ( BSSVS ) . This BSSVS procedure also allows us to employ Bayes factor testing in the identification of the most parsimonious description of the diffusion process [8] . We used a modified Association Index ( AI ) to assess the degree of spatial structure in the phylogeographic data [8] , [15] . This reports the posterior distribution of association values relative to those obtained by randomizing the tip locations . In addition , we summarize the number of transitions to each sampling location in the posterior tree distribution based on the location realizations at the nodes . The latter provide a conservative estimate of the number of independent introductions in each location . To quantify the dissemination process , we estimated the rate of rabies spread among the sampled isolates using ‘Markov jump’ counts [19] of location state transitions for all possible states along the phylogeny . Markov jump counts measure the expected number of transitions along each branch conditional on the observed data . By multiplying the expected number of transitions between each pair of locations by the geographical distance between these two locations , we arrive at the expected distance travelled within the time elapsed on each branch . This approach , implemented in BEAGLE [41] a library that can be used in conjunction with BEAST ) , integrates over all uncertainty in the evolutionary tree and offers a degree of robustness to model misspecification [42] . To test different scenarios of phylogeographic diffusion , we fix the CTMC relative rate parameters to the normalized pairwise location measures that represent different diffusion predictors and perform Bayesian model selection using marginal likelihood approximations [43] . We consider; ( i ) geographical distances , specifically great-circle distances that represent the shortest path on the surface of the Earth between two points , ( ii ) human population size , obtained from http://en . wikipedia . org/ and http://www . mongabay . com ( Table S3 in Supporting Information S1 , rates between each pair of locations were fixed to the normalized products of the population sizes ) , ( iii ) road distances , ( iv ) a gravity model , ( v ) spatial accessibility , and ( vi ) ‘population conductivity’ measures . The accessibility estimates are derived from a range of spatial data sets , road type and network data [44] , satellite derived and cover information , settlement database locations and sizes , and satellite derived topography . They are combined to create a ‘friction surface’ where each 1×1 km square represents the difficulty ( or travel time ) in crossing it . These estimates provide a representation of the difficulty in travel between all the locations . Using a circuit theory approach , an origin-destination distance matrix was estimated from this accessibility landscape [17] . A simple gravity model was constructed by fixing the rates to the normalized product of the population sizes divided by the great circle distance between the locations involved . As an alternative , population sizes were also mapped in a landscape ( Figure S2 in Supporting Information S1 ) [18] and again translated to an origin-destination distance matrix using circuit theory . To assess model fit , marginal likelihood approximations are obtained using an importance sampling estimator [43] , [45] , which employs a mixture of model prior and posterior samples [46] . To contrast the spatial distribution of our rabies samples in Algeria and Morocco with the patterns of spread we would expect from local transmission dynamics in African dogs as the sole maintenance population , we performed a simulation analysis that integrates phylodynamic and epidemiological parameters . Specifically , we consider a spatial process based on epidemiological parameters obtained from a detailed analysis of rabies transmission biology in African dogs [20] , and simulate virus movement accordingly over all evolutionary histories in the posterior distribution resulting from our phylodynamic inference . The latter characterizes the successful ancestral transmission history of the viruses we sampled and provides a time-scale for the spatial process we would like to simulate . For each tree in the posterior distribution , we consider the ancestral virus at the root to start spreading from the mid-point of our available samples ( average of longitudes and latitudes ) . We recursively visit all branches from root to tip , each time simulating a number of successive infections , which jointly encompass the entire time length for each branch . Each time interval t ( in days ) between successive infections follows: ( 1 ) where a is a random incubation time , b is the random period of infectiousness , and f is a random fraction drawn from a uniform[0 , 1] distribution . Following the results of the comprehensive study by Hampson et al . [21] , we consider ( 2 ) and ( 3 ) Each new infection is moved a random distance d ( in m ) away from its source case; the distribution for d follows a previously described spatial infection kernel [21]: ( 4 ) In the spatial simulation process , we assume that each new distance takes a random direction in continuous space , but we also explore subsequent infections consistently taking the same direction . To achieve a realistic distribution in the relevant geographic area , we prohibit new infections to invade water areas . The tree heights used for simulation for Algeria and Morocco were 33 ( 23–46 ) years and 28 ( 18–39 ) years respectively ( as estimated from the country-specific data ) , whereas the tree lengths encompassed 623 ( 490–789 ) years and 532 ( 367–706 ) years respectively . This simulation procedure yields location realizations in continuous space for all tips and all trees in the posterior distribution . We summarize this spatial distribution using two-dimensional contours . Because the spatial simulation for each tree in the posterior distribution may cover a different area , it is important to note that the contour representing the process over all trees depicts the maximum area that can be covered for the set of epidemiological parameters we consider .
|
At least 15 million doses of anti-rabies post-exposure prophylaxis are administered annually worldwide , and an estimated 55 , 000 people die of rabies every year . Over 99% of these deaths occur in developing countries , predominantly in Asia and in Africa where rabies is endemic in domestic dogs . Despite the global health burden due to rabies , little is known about the patterns of the spread of dog rabies in these endemic regions . We used recently developed Bayesian analytical methods to unravel the dynamics and determinants of the spatial diffusion of dog rabies viruses in North Africa based on viral genetic data . Our analysis reveals a combination of restricted spread across administrative borders , the occasional long-distance movement of rabies viruses , and a strong fit between spatial spread of the virus and road distances between localities . Together , these data indicate that by transporting dogs , humans have played a key role in the dispersal of a major animal pathogen . Our studies therefore provide essential new information on the transmission dynamics of rabies in Africa , and in doing so will greatly assist in future intervention strategies .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/infectious",
"diseases",
"of",
"the",
"nervous",
"system",
"evolutionary",
"biology/microbial",
"evolution",
"and",
"genomics",
"computational",
"biology/evolutionary",
"modeling",
"infectious",
"diseases/viral",
"infections",
"public",
"health",
"and",
"epidemiology/epidemiology",
"public",
"health",
"and",
"epidemiology/infectious",
"diseases",
"computational",
"biology/ecosystem",
"modeling",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases"
] |
2010
|
Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus
|
Amino acid substitutions in protein structures often require subtle backbone adjustments that are difficult to model in atomic detail . An improved ability to predict realistic backbone changes in response to engineered mutations would be of great utility for the blossoming field of rational protein design . One model that has recently grown in acceptance is the backrub motion , a low-energy dipeptide rotation with single-peptide counter-rotations , that is coupled to dynamic two-state sidechain rotamer jumps , as evidenced by alternate conformations in very high-resolution crystal structures . It has been speculated that backrubs may facilitate sequence changes equally well as rotamer changes . However , backrub-induced shifts and experimental uncertainty are of similar magnitude for backbone atoms in even high-resolution structures , so comparison of wildtype-vs . -mutant crystal structure pairs is not sufficient to directly link backrubs to mutations . In this study , we use two alternative approaches that bypass this limitation . First , we use a quality-filtered structure database to aggregate many examples for precisely defined motifs with single amino acid differences , and find that the effectively amplified backbone differences closely resemble backrubs . Second , we directly apply a provably-accurate , backrub-enabled protein design algorithm to idealized versions of these motifs , and discover that the lowest-energy computed models match the average-coordinate experimental structures . These results support the hypothesis that backrubs participate in natural protein evolution and validate their continued use for design of synthetic proteins .
Proteins routinely incorporate amino acid changes over evolutionary time by adapting their conformation to the new sidechain . However , it remains a difficult task to predict such a conformational response , especially when subtle backbone adjustments are involved . This issue is of central importance to the burgeoning field of computational protein design , which has recently enjoyed a string of exciting developments [1]–[4] . A number of descriptions of backbone motion have been implemented for the purposes of protein design in the past , each with its own set of advantages and disadvantages . Anticorrelated “crankshaft” adjustments of the ψ ( i−1 ) and φ ( i ) torsions [5] are evident from order parameters derived from molecular dynamics ( MD ) simulations , but unrealistically distort the ends of the peptide if employed in isolation . Helical parameters [6] and normal mode analysis [7] enable efficient exploration of conformational space near the starting model , but are only useful for a small subset of protein architectures: respectively , coiled-coils and structures for which a small number of motional modes dominates conformational diversity . Peptide fragments [8] implicitly reflect local protein energetics because they are extracted from experimental structures , but can be computationally inefficient because most random fragment insertion attempts are incompatible with a given local structural context and will therefore be rejected . This being the case , it may be prudent to let nature inform our notion of backbone motion by using a move set based on empirical observations , which may encode aspects of protein energetics and sidechain/backbone coupling that are difficult to handle explicitly . One such model is the backrub ( Figure 1 ) , a highly localized backbone motion tightly coupled to sidechain rotamer jumps , initially characterized by examining alternate conformations in ultra-high-resolution crystal structures [9] . A simple geometrical model of the backrub consists of a small ( <15° ) rotation of a dipeptide about the axis between the first and third Cα atoms . Resulting strain in the N-Cα-C bond angle τ of all three residues may be partially alleviated and backbone H-bonding maintained with small counter-rotations of the two individual peptides . Note that this Cα formulation is a simplified but very close approximation of the real molecular mechanism , which probably involves a computationally unwieldy set of small shifts in 6–10 backbone torsion angles , as discussed in [9] . Backrubs were seen for 3% of the total residues in that previous study , and for 2/3 of the alternate conformations with a change in Cβ position – far exceeding the next most common shifts , which are either peptide flips or local shear in a turn of helix . Several studies have successfully used the backrub approach to expand the search space of protein design efforts and improve agreement between computed sidechain dynamics and nuclear magnetic resonance ( NMR ) measurements [10]–[14] . Recent work has shown that computational design of backbone structures generated by backrub sampling can recapitulate much of the sequence diversity found in the natural ubiquitin protein subfamily [15] and by phage display experiments [16] . However , the backrub has only been empirically demonstrated to accompany dynamic rotamer changes , not actual changes in amino acid identity . Importantly , no direct experimental evidence has been presented to support the assumption implicit in these studies that a dynamic , low-energy motion on the pico-to-nanosecond timescale is relevant on an evolutionary timescale . The contribution of this current study is to address in atomic detail the specific mechanisms by which backrubs accommodate amino acid changes during processes like subfamily evolution . We use a data set of 5200 high-resolution , high-quality crystal structures to examine differences in local backbone conformation between well-defined motif populations related by a single amino acid difference , and find that the backrub motion explains the majority of the mainchain movement . Furthermore , we demonstrate that a provably-accurate flexible-backbone design algorithm allowing backrubs at those positions , in conjunction with a common molecular mechanics force field , accurately recapitulates such mutation-coupled backbone changes . These findings validate inclusion of the empirically observed backrub motion as part of the repertoire of “moves” for protein design and other modeling efforts .
The N-cap or C-cap position of a helix is defined as the residue half-in and half-out of the helix: the peptide on one side of the cap makes standard helical backbone interactions , while the peptide on the other side has quite non-helical position and interactions [17] . α-helix N-cap residues can make several types of interactions that stabilize or specify the structural transition from loop into α-helix , the most common and dominant of which is a sidechain-mainchain hydrogen-bond to the i+3 amide [17]–[19] . The N-cap H-bond enhances protein stability by compensating for the loss of a mainchain H-bond at the helix start relative to the middle of a helix . Note that the sidechain cannot reach this H-bonding position if the residue has helical φ , ψ , so this interaction also specifies the exact helix start position and the direction from which the backbone can enter [20] . Asn , Asp , Ser , and Thr are especially favored at N-caps because their sidechains have the proper chemical character and shape to mimic the helical backbone interactions ( which Gln and Glu are too long to do ) . Notably , Asn/Asp sidechains are longer than Ser/Thr sidechains by one covalent bond , yet their H-bond distances ( N-cap sidechain O to i+3 amide H ) are only slightly shorter ( 2 . 01±0 . 18 vs . 2 . 17±0 . 18 Å ) based on a survey of all N-caps with i+3 H-bonds in the Top5200 database ( described below and in Methods ) . This means the backbone must slightly adjust to maintain similar H-bond geometry in both cases . With this motivation , we wished to confirm the appropriateness of the backrub model for this case of mutational rather than rotamer change . However , backbone coordinate shifts due to backrubs are very small – on the order of the coordinate differences between crystal structures of the same protein [21] , [22] , thus obscuring differences between genuine shifts and experimental noise . The initial description of the backrub bypassed this problem by comparing alternate conformations within single structures [9] . Our approach here , in contrast , was to use the collective weight of many examples to ensure that observed local conformational differences were in fact genuine . Aromatic residues often pair with glycine in antiparallel β-sheet by adopting rotamers with χ1≈+60° , which places the aromatic ring directly over a Gly on the adjacent strand across a narrow pair of backbone H-bonds [29] . Aromatic-glycine pairings in antiparallel β-sheet have been demonstrated to yield a synergistic thermodynamic benefit [30] . If the opposite residue is changed to anything other than Gly , a sidechain including at least a Cβ atom is now present , which would sterically clash with the aromatic in its original conformation . However , the “plus χ1” aromatic rotamer will still be compatible with some rotamers of the opposite sidechain , provided that the aromatic may shift slightly to re-optimize packing of its ring against the opposite residue's Cβ hydrogens . Here we investigate whether backrubs enable this relaxation by excursions in both directions from a “neutral” β-sheet conformation . The leverage provided by such backbone motions could lean the aromatic residue forward/backward to maintain close inter-strand contact when the identity of the opposite residue is changed to/from Gly .
It is known that backrubs relate conformations that interchange dynamically [9] . In this study we further show that , at least for certain specific motifs , backrubs relate conformations that “interchange” based on point mutations . For the β aromatic motif , local restraints on steric packing influence the aromatic residue's backbone indirectly via the other altered sidechain . This is in contrast to helix N-caps where the sequence change and the backrub occur at the same residue , as seen previously for rotamer changes [9] . Taken together , these findings support the intriguing idea that backrubs may “foster” mutations , easing them into the structure and promoting their survival into future generations . In this paradigm , backrubs enable individual mutations that provide the raw material for natural selection . The two specific motifs analyzed here represent only about 0 . 5% of the protein residues in our Top5200 data set , and thus in one sense the scope of this study is relatively narrow . However , a tight focus was necessary to substantiate the idea of mutation-coupled backrubs with sufficient certainty , due to the coordinate error problem in the alternative approach of comparing individual wildtype and mutant crystal structures directly . These two cases were chosen as common , well-defined motifs where the primary interaction environment of the changing sidechain is provided by local secondary structure and is therefore consistent across hundreds of examples . For the general case of an individual mutation , the potential interaction environment is also the same before and after; however , it is seldom simple enough to be closely repeated in numerous proteins . Furthermore , as shown in previous work at ultra-high resolution [9] , 2/3 of alternate conformations that move Cβ demonstrate backrubs between rotamers of the same amino acid . All in all , therefore , it is reasonable to assume that the general prevalence of backrub accommodation at sites of mutation is significantly higher than the “lower bound” provided in this study . The backbone shift considered on its own is continuous and low-energy , without a barrier , while the two-state behavior is contributed by the sidechain switch between rotamers , between H-bond partners , or between amino acids . In the dynamics case of jumps between distinct sidechain rotamers or H-bonds [9] , both conformations are quite favorable , but backbone and sidechain must change together . In the evolutionary case , such as the single amino acid changes between stable motifs illustrated in this paper , the two amino acid types cannot coexist in the same molecule . The sidechain-backbone coupling shifts the energy landscape for the backbone [31] , stabilizing a different choice within a shallow energy well . From a modeling perspective , examination of existing fast-timescale structural dynamism may illuminate other possibilities for mutations on an evolutionary timescale [32] . Mutation-coupled backrubs are small local changes , which presumably mediate neutral drift much more often than they aid large-scale structural rearrangements or changes in function . However , the accumulation of changes via neutral drift over time may in fact enable future large-scale changes by subtly altering the native state energy landscape such that eventually a tipping point is reached . Recent analysis of the evolution of an ancient protein confirms that some function-altering mutations required structural pre-stabilization by earlier “permissive” mutations [33]; backrubs may facilitate such preemptive sequence changes by shifting the backbone such that the functionally neutral amino acids can fit . Backrub-related sequence changes could also sometimes enable functional change based on a purely local adaptation when they occur in active sites , either directly or by first enhancing functional promiscuity . Note that we do not directly address true evolutionary relationships between proteins in this study . Rather , we substantiate the idea that backrubs enable single amino acid changes at specific motifs , which could aid actual evolution within a protein family [15] . It is only natural to segue from the role of backrubs in protein evolution to their utility for protein design – essentially a computational analog of molecular evolution . Our results indicate that , despite the relative simplicity of their functional form , molecular-mechanics-based force fields like Amber plus EEF1 that are commonly used for protein design can in fact accurately recapitulate empirically-observed backbone conformation for multiple specific structural motifs , given the chance to access them via a backrub . ( Note that the cases presented here were dominated by single interactions such as H-bonds or steric packing; a higher-cost energy function might be needed to maintain similar accuracy if different interactions are competing and need to be compared quantitatively . ) Thus , predicting the conformational consequences of a sequence change in computational protein design is in large part a search problem: if the appropriate regions of protein conformational space are searched efficiently , in many cases low-cost energy functions can do the rest . Unfortunately , that space is vast indeed even for a single sequence , as we know from Levinthal's famous thought experiment [34] . The additional consideration of combinatorial mutations ( even when conformational changes are restricted to simple sidechain rotamer alternatives ) creates a space that is even more difficult to search , as shown by the proof that protein design is NP-hard [35] . Of course , backbone flexibility further enlarges the search space . However , flexible-backbone design algorithms like BRDEE are excellent candidates for this task in many cases because ( 1 ) they are based on empirically demonstrated types of flexibility and ( 2 ) they come with mathematical guarantees of their accuracy with respect to the input parameters . Other algorithms that search over amino acid and rotamer identities , then minimize over backrub degrees of freedom post facto are not guaranteed to identify the global minimum energy conformation ( GMEC ) given the input model ( starting structure , rotamer library , energy function ) . An advantage of BRDEE is that it incorporates backrub minimization awareness directly into the amino acid and rotamer comparison stages of dead-end elimination , and thus is guaranteed to identify the GMEC given the input model . Because BRDEE avoids becoming trapped in local minima , it effectively decouples the often intertwined issues of conformational search and scoring . Therefore , as a result of using BRDEE , this paper gives the limit of how well any algorithm can perform given our input model . In the future we plan to implement additional empirically-validated small backbone motions , such as peptide flips and tripeptide shears [9] , [14] , to improve coverage of conformational space . Overall , we have demonstrated that the backrub , a model of local backbone motion previously only documented for dynamic rotamer changes , also applies to local sequence changes . This finding is an important direct validation for the application of the backrub to the study of natural protein evolution and to continuing efforts in computational protein design .
To identify numerous examples of the desired motifs , we used a “Top5200” database of high-quality protein structures . The rapid growth of the Protein Data Bank ( PDB ) [36] in recent years enabled the creation of a high-quality database with an order of magnitude increase in size relative to the previously described Top500 [23] while maintaining similar standards of resolution and structure quality . However , due to sheer logistics it also necessitated a more automated selection protocol . We included at most one protein chain per PDB 70% sequence-similarity cluster as of April 5 , 2007 . We chose the representative for each such cluster as the chain with the best average of resolution and MolProbity score [37] where resolution is <2 Å . MolProbity score is an estimate of the resolution at which a structure's steric clashes , rotamer quality , and Ramachandran quality would be average; thus the average of resolution and MolProbity score is a combined experimental and statistical indicator of structural quality [37] . The homology filter prevents redundancy and thus over-representation of certain motifs or substructures . To calculate the MolProbity score for each chain , first hydrogens were added with the program Reduce [38] . The -flip flag was used in order to allow Asn/Gln/His flips throughout the structure , including at interfaces where multimer partners may participate in hydrogen-bonding networks . All protein chains with at least 37 residues were then extracted , along with any “het” atoms or waters with the same chain identifier , and MolProbity score was calculated for each chain . Two “post-processing” steps were required . First , we removed four chains whose PDB structures had been obsoleted and replaced them with updated structures where possible ( 1sheA→2pk8A , 1wt4A→2v1tA , 2eubA→2pl1A , 2f4dA→no replacement ) . Finally , we removed two chains with incomplete or unclear PDB files ( 1c53A had only Cα atoms , 3ctsA had only “UNK” unknown residue types ) . The resulting 5199 protein chains make up about a million residues . For all BRDEE calculations , we used the same input parameters as described previously [10] for energy function , rotamer library , τ filter , etc . Briefly , the energy function consists of the Amber electrostatic and van der Waals terms [24] plus the EEF1 pairwise solvation energy term [25] . The τ filter prevents large strain at the only bond angle allowed to change in the calculations [10] . The KiNG graphics program [39] was used both to study the superposition results and to produce the figures . Dataset S3 provides raw PDB coordinate files for N-cap and aromatic crystal structure examples , average crystal structures , and BRDEE lowest-energy models .
|
Protein design has the potential to generate useful molecules for medicine and chemistry , including sensors , drugs , and catalysts for arbitrary reactions . When protein design is carried out starting from an experimentally determined structure , as is often the case , one important aspect to consider is backbone flexibility , because in response to a mutation the backbone often must shift slightly to reconcile the new sidechain with its environment . In principle , one may model the backbone in many ways , but not all are physically realistic or experimentally validated . Here we study the "backrub" motion , which has been previously documented in atomic detail , but only for sidechain movements within single structures . By a twopronged approach involving both structural bioinformatics and computation with a principled design algorithm , we demonstrate that backrubs are sufficient to explain the backbone differences between mutation-related sets of very precisely defined motifs from the protein structure database . Our findings illustrate that backrubs are useful for describing evolutionary sequence change and , by extension , suggest that they are also appropriate for rational protein design calculations .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"protein",
"structure",
"biology",
"computational",
"biology",
"macromolecular",
"structure",
"analysis"
] |
2012
|
The Role of Local Backrub Motions in Evolved and Designed Mutations
|
Phlebotomine sand flies are blood-sucking insects transmitting Leishmania parasites . In bitten hosts , sand fly saliva elicits specific immune response and the humoral immunity was shown to reflect the intensity of sand fly exposure . Thus , anti-saliva antibodies were suggested as the potential risk marker of Leishmania transmission . In this study , we examined the long-term kinetics and persistence of anti-Phlebotomus papatasi saliva antibody response in BALB/c and C57BL/6 mice . We also tested the reactivity of mice sera with P . papatasi salivary antigens and with the recombinant proteins . Sera of BALB/c and C57BL/6 mice experimentally bitten by Phlebotomus papatasi were tested by ELISA for the presence of anti-saliva IgE , IgG and its subclasses . We detected a significant increase of specific IgG and IgG1 in both mice strains and IgG2b in BALB/c mice that positively correlated with the number of blood-fed P . papatasi females . Using western blot and mass spectrometry we identified the major P . papatasi antigens as Yellow-related proteins , D7-related proteins , antigen 5-related proteins and SP-15-like proteins . We therefore tested the reactivity of mice sera with four P . papatasi recombinant proteins coding for most of these potential antigens ( PpSP44 , PpSP42 , PpSP30 , and PpSP28 ) . Each mouse serum reacted with at least one of the recombinant protein tested , although none of the recombinant proteins were recognized by all sera . Our data confirmed the concept of using anti-sand fly saliva antibodies as a marker of sand fly exposure in Phlebotomus papatasi–mice model . As screening of specific antibodies is limited by the availability of salivary gland homogenate , utilization of recombinant proteins in such studies would be beneficial . Our present work demonstrates the feasibility of this implementation . A combination of recombinant salivary proteins is recommended for evaluation of intensity of sand fly exposure in endemic areas and for estimation of risk of Leishmania transmission .
Sand flies ( Diptera: Phlebotominae ) serve as vectors of leishmaniasis , a neglected disease with symptoms ranging from non-lethal cutaneous to life-threatening visceral form . The causative agents of the disease are protozoan parasites of the genus Leishmania which are transmitted to the hosts by the bites of infected sand fly females . The percentage of infected flies in foci of leishmaniasis fluctuates and humans and animals are more frequently exposed to the bites of uninfected sand flies . Repeated exposure to sand fly saliva elicits anti-saliva antibodies that could be used as a marker of exposure to sand fly bites [1]–[5] . Moreover , the antibodies are sand fly species-specific . Therefore they can be utilized to differentiate between exposure to vector and non-vector species [1] , [4] , [6]–[9] . In several epidemiological studies , anti-sand fly saliva antibodies were already employed as a reliable tool to monitor exposure to sand fly bites , to evaluate the effectiveness of vector control programs , and in some instances to estimate the risk of Leishmania transmission [1] , [4] , [5] , [10]–[14] . In endemic areas sand fly population fluctuate seasonally [15] , which may influence host anti-saliva antibody response . However , very little is known about the kinetics and persistence of anti-saliva antibodies in sera of hosts bitten by blood-feeding insects . Few data on antibody kinetics are available from mice , chicken and guinea pigs experimentally exposed to bites of Triatoma infestans [16]–[18] , from humans bitten by mosquitoes [19]–[22] as well as from humans [4] , [23] and dogs [3] , [5] , [24] bitten by sand flies . Screening for antibodies is , however , unsuitable for broader use in epidemiological studies until recombinant proteins could be employed instead of the crude salivary gland homogenate , which requires maintenance of sand fly colonies and laboratory dissections of insects . So far , only recombinant salivary proteins from Lutzomyia longipalpis have been tested for reactivity with sera of naturally bitten humans , dogs , and foxes [8] , [9] . We studied mice antibody response to P . papatasi , the main vector of Leishmania major , and compared long-term kinetics and persistence of anti-saliva antibodies in BALB/c and C57BL/6 mice that are widely used as model organisms sensitive or resistant to L . major infection , respectively . Furthermore , we characterized and compared main P . papatasi salivary antigens recognized by sera of experimentally bitten BALB/c and C57BL/6 mice . The reactivity of mice sera was also tested with the four P . papatasi recombinant proteins; two Yellow-related proteins ( PpSP44/AF335492 and PpSP42/AF335491 ) and two D7-related proteins ( PpSP30/AF335489 and PpSP28/AF335488 ) .
BALB/c and C57BL/6 mice were maintained and handled in the animal facility of Charles University in Prague in accordance with institutional guidelines and Czech legislation ( Act No . 246/1992 coll . on Protection of Animals against Cruelty in present statutes at large ) , which complies with all relevant European Union and international guidelines for experimental animals . The experiments were approved by the Committee on the Ethics of Animal Experiments of the Charles University in Prague ( Permit Number: 24773/2008-10001 ) and were performed under the Certificate of Competency ( Registration Number: CZU 934/05; CZU 307/09 ) in accordance with the Examination Order approved by Central Commission for Animal Welfare of the Czech Republic . A colony of Phlebotomus papatasi ( originating from Turkey ) was reared under standard conditions as described in [25] . Salivary glands were dissected from 4–6-day-old female sand flies , placed into 20 mM Tris buffer with 150 mM NaCl and stored at −20°C . Twelve mice of BALB/c or C57BL/6 strains ( 6 weeks old ) were divided into experimental and control groups of six mice each . Mice in the experimentally bitten groups were exposed individually to 30 Phlebotomus papatasi females ( 22±0 . 6 ( standard error ) blood-fed females per mouse per exposure on BALB/C mice; 26±0 . 7 ( standard error ) blood-fed females per mouse per exposure on C57BL/6 mice ) , once a week in a total of 5 exposures ( weeks 1–5 ) . Mice in the control groups remained without any exposure to sand flies . Animals in both groups were anaesthetized ( ketamin 150 mg/kg and xylazin 15 mg/kg body weight , intraperitoneally ) . Blood samples were taken weekly from the tail vein of each mouse one day before exposure to sand flies from week 0 ( pre-immune serum ) to week 12 and than every other week till the end of the experiment ( week 28 for BALB/c mice; week 27 for C57BL/6 mice ) . In total , mice were followed for 29 and 28 weeks , respectively . Two independent experiments were done for each mice strain . To test the presence of memory cells , BALB/c mice were additionally exposed to P . papatasi bites ( 21±0 . 5 ( standard error ) blood-fed females per mouse ) in the week 27 . Genes coding for P . papatasi salivary gland secreted proteins PpSP28 ( AF335488 ) , PpSP30 ( AF335489 ) , PpSP42 ( AF335491 ) and PpSP44 ( AF335492 ) were amplified from VR2001-TOPO vector [26] by PCR . Two specific restriction sites ( Nde I and Bam HI ) were incorporated into the PCR primers: PpSP28Fw ( CATATGAAGTACCCTAGGAATGCCGAT ) , PpSP28Rev ( GGATCCGTACGTTCTTGCGGATTGGTCATC ) , PpSP30Fw ( CATATGCGATTTCCTAGGAATGGAGAC ) , PpSP30Rev ( GGATCCGTATTTCCAAGATTCAATATCAAG ) , PpSP42Fw ( CATATGAAAAGAGATGATGTTGGA ) , PpSP42Rev ( GGATCCCCCTTGACACTTTTCTCC ) , PpSP44Fw ( CATATGAAAAGAGACGATGTTGAA ) , and PpSP44Rev ( GGATCCTTTAGGTTTTCTCACTTC ) . Afterwards , PCR products were ligated into E . coli pGEM-T Easy Vector ( Promega ) using TA cloning and the ligation products were transformed into E . coli competent cells TOP10 ( Invitrogen ) . Vectors were replicated in bacteria and after that , genes restricted by Nde I and Bam HI enzymes and restricted E . coli pET-42 Expression Vectors ( Novagen ) were ligated . Ligation products were transformed into E . coli competent cells TOP10 ( Invitrogen ) again . Plasmids were isolated from the bacteria , and transformed into E . coli BL21 ( DE3 ) gold ( Agilent ) for expression . E . coli lysates were prepared under denaturing conditions and His-tagged proteins were purified by FLPC on a Ni-NTA Superflow column with The QUIaxpressionist kit ( Quiagen ) according to manufacturers manual . Anti-P . papatasi saliva IgG antibodies and IgG subclasses were measured in sera of BALB/c and C57BL/6 mice using indirect ELISA . Microtiter plate wells were coated with P . papatasi salivary gland homogenate ( SGH ) made by three freeze-thaw cycles ( about 60 ng of protein per well ) . To block free binding sites , washed wells were incubated with 6% low fat dry milk diluted in 20 mM phosphate-buffered saline with 0 . 05% Tween 20 . Mice sera were diluted 1∶200 in 2% low fat dry milk and incubated for 90 min at 37°C for specific IgG or overnight at 4°C for IgG subclasses . Secondary antibodies ( goat anti-mouse IgG , IgG1 , IgG2a , IgG2b , IgG2c , and IgG3; Serotec ) conjugated with horseradish peroxidase ( HRP ) were diluted and incubated at 37°C as described in Table S1 . Orthophenylendiamine and H2O2 in McIlwein phosphate-citrate buffer ( pH 5 . 5 ) were used as substrate solution . Absorbance was measured at 492 nm using an Infinite M200 microplate reader ( Tecan ) . The cut-off value was determined as two standard errors of the mean of the absorbance of pre-immune serum . The intensity of booster effect was measured by increased levels of specific antibodies in sera of bitten mice after the last sand fly exposure ( comparing week 24 and 28 ) . Anti-P . papatasi IgE were measured in sera of BALB/c mice as described above with the following modifications . Microtiter plate wells were coated with P . papatasi SGH ( about 300 ng of protein per well ) . To block the free binding sites , washed wells were incubated with 6% fetal calf serum . Mouse sera were diluted 1∶100 in 2% fetal calf serum . Secondary antibody ( rat anti-mouse IgE; BD PharMingen ) was diluted and incubated as listed in Table S1 . Phlebotomus papatasi SGH ( about 10 µg of protein per well ) was separated on 10% SDS-PAGE gel under non-reducing conditions using the Mini-Protean III apparatus ( BioRad ) . Salivary proteins were blotted onto a nitrocellulose membrane by Semi-Phor equipment ( Hoefer Scientific Instruments ) and cut into strips . The strips were then blocked with 5% low fat dry milk in Tris-buffered saline with 0 . 05% Tween 20 ( TBS-Tw ) and subsequently incubated with mice sera ( week 28 for BALB/c mice; week 5 for C57BL/6 mice ) diluted 1∶200 for 1 hour . In the next step the strips were incubated for 1 hour with peroxidase-conjugated goat anti-mouse IgG , IgG1 , or IgG2b ( Serotec ) diluted in TBS-Tw as follows: IgG and IgG1 1∶5000; IgG2b 1∶2000 for BALB/c mice sera and IgG , IgG1 1∶2000 for C57BL/6 mice sera . The chromogenic reaction was developed using a solution containing diaminobenzidine and H2O2 . Similar protocol was used for western blot analysis with P . papatasi recombinant proteins PpSP28 , PpSP30 , PpSP42 , and PpSP44 . Briefly , recombinant proteins were loaded on the 10% SDS-PAGE gel ( 3 µg protein per well ) and separated under reducing conditions . BALB/c mice sera ( week 28 ) were diluted 1∶50 and secondary antibody ( goat anti-mouse IgG from Serotec ) was diluted 1∶1000 in TBS-Tw . The proteins from the P . papatasi salivary glands used for mass spectrometric analysis were run on the same gel as salivary glands used for western blot analysis . Proteins were visualized by Coomassie Blue G-250 staining ( Bio-Rad ) . The individual bands were cut and incubated with 10 mM dithiothreitol ( DTT ) and then treated with 55 mM iodoacetamid . Washed and dried bands were digested with trypsin ( 5 ng , Promega ) . Alpha-cyano-4-hydroxycinnamic acid was used as a matrix . Samples were measured using a 4800 Plus MALDI TOF/TOF analyzer ( AB SCIEX ) . A peak list from MS spectra was generated by 4000 Series Explorer V 3 . 5 . 3 ( AB SCIEX ) without smoothing . Peaks with local signal to noise ratio greater than 5 were picked and searched by local Mascot v . 2 . 1 ( Matrix Science ) against a database of putative salivary protein sequences derived from GenBank . Database search criteria were as follows – enzyme: trypsin , taxonomy: Phlebotomus , fixed modification: carbamidomethylation , variable modification: methionine oxidation , peptide mass tolerance: 80 ppm , one missed cleavage allowed . Only hits that scored as significant ( p<0 . 05 ) are included . The data obtained by ELISA were subjected to GLM ANOVA and Tukey-Kramer Multiple Comparison procedure to analyze differences in kinetics of anti-P . papatasi saliva antibody response between experimentally bitten and control mice at all sampling points . The non-parametric Wilcoxon rank sum test for differences in medians was used for evaluation of booster effect , the comparison of antibody level between week 24 and 28 . For correlation tests we used the non-parametric Spearman rank correlation matrix . For all tests statistical significance was regarded as a p-value less than 0 . 05 . All statistical analyses were performed using NCSS 6 . 0 . 21 software .
To investigate the kinetics and persistence of anti-P . papatasi saliva antibody response , experimentally bitten and control mice were followed for 29 weeks . Mice exposed five times to bites of sand flies at one-week interval had significantly increased levels of specific IgG , IgG1 , and IgG2b as compared to control group ( Figure 1A , C , E ) . In contrast , specific IgG2a , IgG3 , and IgE levels in sera of bitten mice were comparable to non-exposed controls with some differences only at the last data points ( Figure S1 ) . No anti-saliva antibodies were detected in any pre-immune sera tested . In bitten mice , anti-P . papatasi saliva IgG and IgG1 levels increased significantly ( p<0 . 05 ) after the fourth exposure ( Figure 1A , C ) . IgG2b levels differed between experimental and control group from week 9 onward , with the exception of weeks 10 and 11 ( Figure 1E ) . Anti-saliva IgG increased steadily till the end of the study , while specific IgG2b increased slowly until week 22 followed by a slight decrease at week 24 . Anti-saliva IgG1 increased steadily and peaked at week 7 and persisted on this level until the end of the study . To test the presence of putative memory cells to P . papatasi salivary proteins , BALB/c mice were additionally exposed to sand flies 22 weeks after the last exposure ( week 27 ) . One week after the booster ( at week 28 ) anti-P . papatasi saliva antibodies increased significantly in IgG by 43% , in IgG1 by 80% and in IgG2b by 79% ( Figure 1A , C , E ) . Positive correlation was found between the number of blood-fed sand fly females during the individual immunization weeks ( sum of the blood-fed females from the relevant week and the weeks before ) and the corresponding levels of anti-P . papatasi IgG ( r = 0 . 62 , p<0 . 0001 ) , IgG1 ( r = 0 . 74 , p<0 . 0001 ) , and IgG2b ( r = 0 . 29 , p<0 . 05 ) ( Figure 2A , C , E ) . Furthermore , positive correlation was detected between the total amount of blood-fed females and the levels of specific IgG ( r = 0 . 72 , p<0 . 0001 ) and IgG1 ( r = 0 . 8 , p<0 . 0001 ) after the fifth sand fly exposure ( week 5 ) . Experimentally bitten and control mice of C57BL/6 strain were followed in experiments lasting 28 weeks . Five exposures at one-week interval significantly increased levels of specific IgG and IgG1 in bitten mice ( Figure 1B , D ) . In contrast , specific IgG2b , IgG2c , and IgG3 levels of bitten mice were comparable to controls . No anti-saliva antibodies were detected in any pre-immune sera tested . Similarly to BALB/c mice , anti-P . papatasi IgG and IgG1 levels differed significantly between experimentally bitten and control C57BL/6 mice from week 4 onward ( Figure 1B , D ) . Anti-saliva IgG gradually increased until week 8 and then with a slight fluctuation of antibody levels decreased until the end of the study . Specific IgG1 developed with similar kinetics to IgG , however , it peaked earlier ( at week 6 ) and then slowly decreased till the end of the study . Anti-saliva IgG2b , IgG2c , and IgG3 antibodies did not differ between the exposed and control group throughout the study ( Figure 1F; Figure S1B , D ) with the exception of week 21 for IgG3 subclass ( Figure S1D ) . We also detected a positive correlation between the number of blood-fed sand fly females during the individual immunization weeks ( sum of the blood-fed females from the relevant week and the weeks before ) and the corresponding levels of anti-P . papatasi IgG ( r = 0 . 80 , p<0 . 0001 ) and IgG1 ( r = 0 . 86 , p<0 . 0001 ) ( Figure 2B , D ) . Moreover , positive correlation was detected between the total amount of blood-fed females and the levels of specific IgG ( r = 0 . 85 , p<0 . 0001 ) , IgG1 ( r = 0 . 86 , p<0 . 0001 ) , and IgG2c ( r = 0 . 5 , p<0 . 05 ) after the fifth sand fly exposure ( week 5 ) . Phlebotomus papatasi salivary antigens were studied using sera of experimentally bitten BALB/c and C57BL/6 mice . Only the antibody classes and subclasses shown to be produced in high titers by ELISA were tested in a western blot; specific anti-P . papatasi IgG and IgG1 in both mice strains and additionally specific IgG2b in BALB/c mice . BALB/c mice sera recognized up to 10 protein bands with approximate molecular weights of 70 , 65 , 51 , 49 , 47 , 35 , 31 , 30 , 23 , and 15 kDa , the last three being the most intensively recognized by all BALB/c sera in all IgG subclasses tested . Sera of C57BL/6 mice reacted additionally with the 53 kDa protein but did not recognize the 49 and 47 kDa protein bands . The most intensive reaction in all C57BL/6 mice was detected with the 65 , 53 , and 30 kDa protein bands in IgG as well as in IgG1 ( Figure 3 ) . Comparison of two mice strains therefore revealed an interesting difference in recognition of four protein bands of 53 , 51 , 49 , and 47 kDa . No reaction was detected with any pre-immune mice sera tested ( Figure 3 ) . In BALB/c mice , the 51 kDa protein was recognized only by one out of 5 sera tested in IgG and IgG1 , while in C57BL/6 mice , this protein band was recognized by all mice sera tested in IgG1 and by two out of five sera tested in IgG . Anti-P . papatasi IgG2b antibodies reacted consistently with the 65 , 35 , 31 , 30 , 23 , and 15 kDa proteins ( Figure 3 ) . In C57BL/6 mice , 70 , 65 , 53 , 31 , and 30 kDa proteins were recognized by all mice sera tested ( IgG as well as IgG1 ) , while the 51 , 35 , 23 , and 15 kDa antigens were recognized by some sera only ( Figure 3 ) . Specific IgG1 of C57BL/6 mice predominantly recognized the 65 , 53 , 51 , 31 , and 30 kDa antigens ( Figure 3 ) . Mass spectrometry analysis identified the salivary proteins with the same mobility in the SDS-PAGE as the proteins recognized by the sera of experimentally bitten mice as the Yellow-related proteins ( GenBank acc . no . AF335492 and AF335491 ) , apyrase ( AF261768 ) , D7-related proteins ( AF335489; AF335488 ) , antigen-5 protein ( DQ205724 ) , and proteins of the SP15 protein family ( AY628879 , AY628880; AF335486; AF335485 ) ( Table 1 ) . The reactivity of PpSP44 ( yellow related protein ) , PpSP42 ( yellow related protein ) , PpSP30 ( D7 related protein ) , and PpSP28 ( D7 related protein ) recombinant proteins was studied using sera from BALB/c mice exposed to P . papatasi bites and positive for anti-P . papatasi IgG antibodies . Sera of control mice did not recognize any of the recombinant proteins tested . The most intensive reaction was detected with the PpSP30 , although , this protein was not recognized by all sera tested ( 4 out of 5 ) . Three out of five mice sera reacted with the PpSP42 and PpSP44 recombinant proteins and very weak reaction was detected with the PpSP28 recombinant protein in two out of five mice sera ( Figure 4 ) .
This study describes in detail long-term kinetics and persistence of anti-P . papatasi saliva antibodies in sand fly-exposed BALB/c and C57BL/6 mice strains that are widely used as model organisms sensitive or resistant to Leishmania infection , respectively ( e . g . [27] , [28] ) . Four IgG subtypes have been described in mice: IgG1 , IgG2a , IgG2b , and IgG3 . Additionally , certain strains such as C57BL/6 produce the IgG2c subclass instead of IgG2a [29] . The nomenclature of murine IgG subtypes does not correlate with the subtypes of human or canine IgG . The most abundant subclass is IgG1; it binds to Fc-receptors of mast cells and basophils , and it mediates the immediate hypersensitivity reactions . Both IgG1 and IgG2a activate the complement cascade via the alternative pathway , whereas IgG2b employs the classical pathway of complement activation [30] . Moreover , production of IgG1 is the marker of Th2 profile of immune response in mice , while IgG2a predicts Th1 type of immune response in these animals [31] . We showed that repeated exposure to sand fly bites elicits increased levels of anti-saliva IgG and IgG1 in both BALB/c and C57BL/6 strains , and additionally IgG2b in BALB/c mice . In comparison , higher levels of specific IgG were detected in BALB/c mice . This finding complies well with the fact that BALB/c mice mostly respond to repeating antigens by Th2 humoral immune response while C57BL/6 mice produce mainly Th1 cellular response [30] . It seems that P . papatasi saliva elicits mainly production of specific IgG1 subclass , which suggests the polarization to the Th2 type of immune response in bitten mice regardless of the strain . The production of anti-sand fly saliva IgG1 was previously described in BALB/c mice repeatedly bitten by Lutzomyia longipalpis , but they did not observe any production of neither IgG2a nor IgG2b [32] . As the composition of sand fly saliva varies in different sand fly species [33] and the sand fly saliva compounds elicit different profile of specific antibody response [34] , this could be the feasible explanation for the production of different antibody subclasses in mice bitten by different sand fly species . To our knowledge , there are no data available about the anti-sand fly saliva antibody subclasses elicited by sand fly feeding in the C57BL/6 mice . In Swiss Webster mice immunization by P . ariasi saliva produced also predominantly IgG1 antibodies [34] . Production of specific IgG2b in BALB/c mice compared to the absence of this antibody subclass in C57BL/6 mice may be the result of different cytokine responses in both mice strains against sand fly saliva . The switch to IgG2b subclass is initialized by production of TGF-β [35] , a suppressive cytokine that blocks the activation of lymphocytes and monocytes derived phagocytes . This could positively contribute to the susceptibility of BALB/c mice to Leishmania parasites . Importantly , positive correlation was found in both mice strains between the intensity of sand fly exposure and the levels of specific antibodies in aforementioned subclasses . Our results correspond well to previously published data showing that the antibody response in dogs [3] , [5] as well as in humans [4] reflected the intensity and the time-course of sand fly exposure . We found that sand fly exposure did not affect the production of IgG2a and IgG3 in BALB/c mice , and IgG2b , IgG2c , and IgG3 in C57BL/6 mice . Neither did the levels of specific IgE differ significantly between non-exposed and exposed groups of mice , and the IgE kinetics showed high variation during the study . Similarly , high fluctuation in specific IgE response was detected in humans [11] , [23] and dogs [3] bitten by Lutzomyia longipalpis in the field as well as under laboratory conditions . While some of the individuals and animals presented high levels of specific IgE , others did not mount specific IgE response at all [3] , [11] , [23] . To mimic the situation commonly occurring in endemic foci of leishmaniases , where sand fly-free periods last up to 6 months [15] , BALB/c mice were exposed to P . papatasi bites again 23 weeks after the last sand fly exposure . This single sand fly exposure elicited statistically significant increase of anti-P . papatasi IgG , IgG1 , IgG2b which suggests the persistence of memory cells generated during the previous round of exposures . This could be related to the “previous sand fly season” in the field . Furthermore , in both mice strains , the differences between non-exposed and exposed groups of mice in production of specific IgG1 and IgG2b were detectable from week four or nine , respectively , until the end of the study . Similarly , the levels of specific IgG , IgG1 , and IgG2 in sera of dogs exposed to L . longipalpis or P . perniciosus bites differed significantly from pre-immune sera for more than 14 weeks after the last sand fly exposure [3] , [5] . In individuals repeatedly bitten by P . argentipes , elevated levels of specific antibodies persisted after the 30-day sand fly-free period , although anti-saliva antibodies significantly decreased throughout this time [4] . Thus , regardless the host-sand fly combination , anti-sand fly saliva antibodies can persist in sera of repeatedly bitten hosts until the next sand fly season . We also characterized the reactivity of mice sera with P . papatasi salivary proteins as well as with selected recombinant proteins . Mice sera of BALB/c and C57BL/6 strains reacted with up to eleven P . papatasi antigenic protein bands . The 30 kDa protein band recognized by both mice strains was identified by mass spectrometry as a mixture of a D7-related ( AF335489 ) and an antigen 5-related ( DQ205724 ) protein . The other proteins which were intensively recognized either by BALB/c ( 47 , 23 , and 15 kDa proteins ) or by C57BL/6 mice ( 65 , 53 , and 51 kDa proteins ) were determined as members of the Yellow-related protein family ( 51 kDa - AF335492 , 47 kDa - AF335491 ) , D7-related protein family ( 23 kDa – AF335488 ) , and SP-15 protein family ( 15 kDa – AY628879 , AY628880 , AF335486 , AF335485 ) . The 70 , 65 , 53 , and 49 kDa bands were not identified by mass spectrometry . Our results correspond to previously published data , where the human and BALB/c mice IgG antibodies recognized preferentially the P . papatasi 30 kDa protein band [1] , [14] . To our knowledge , the only study describing the reactivity of specific IgG subclasses with P . papatasi antigens was performed on humans [14] . In accordance with our results , the 30 kDa D7-related protein was also found to be the most immunogenic antigen in all human antibody subclasses tested [14] . Taken together , our data complies well with previously published studies , where Yellow-related proteins , D7-related proteins , as well as SP-15 proteins from P . papatasi saliva were identified as potent antigens for mice and humans [1] , [14] . Sera of BALB/c mice experimentally bitten by P . papatasi were tested also with four bacterially expressed recombinant proteins belonging to two salivary protein families: Yellow-related proteins ( PpSP44/AF335492 and PpSP42/AF335491 ) and D7-related proteins ( PpSP30/AF335489 and PpSP28/AF335488 ) . Within the salivary gland homogenate , sera reacted with proteins identified as PpSP42 , PpSP30 , and PpSP28 proteins , but no reaction was detected with PpSP44 . In contrast , PpSP30 and PpSP44 recombinant proteins were strongly recognized and PpSP42 gave a weak reaction . Reaction of anti-saliva IgG with recombinant proteins may , however , differ between mouse strains . For example , the C57BL/6 mice reacted predominantly with PpSP42 and PpSP28 recombinant proteins ( data not shown ) . Although none of the recombinant proteins were recognized by all sera . Each mouse serum tested reacted with at least one of the recombinant proteins . Our data suggest that recombinant proteins could be used as markers of sand fly exposure instead of crude salivary gland homogenates , ideally as a mixture of several different proteins to cope with various host species and individual reactivity of each serum sample . In sand flies this concept has been demonstrated using Lutzomyia longipalpis recombinant proteins; the reactivity of anti-L . longipalpis seropositive human sera with the salivary gland sonicate was comparable to the reaction with the combination of the two L . longipalpis recombinant Yellow-related proteins ( LJM11/AY445935 and LJM17/AF132518 ) [8] . In conclusion , we detected a significant increase of specific IgG and IgG1 in exposed mice of both strains , and of IgG2b in exposed BALB/c mice . The other IgG subclasses were comparable to controls . Specific IgG response was shown to reflect the intensity of sand fly exposure and furthermore , anti-P . papatasi saliva antibody response persisted in mice for more than 5 months . Thus , in endemic areas the antibodies could persist till the following sand fly season . The 30 kDa band recognized by sera of experimentally bitten BALB/c as well as C57BL/6 mice was identified as a mixture of D7-related and antigen 5-related proteins . Moreover , the reactivity of mice sera with PpSP44 , PpSP42 , PpSP30 , and PpSP28 recombinant proteins suggested that their combination could substitute the salivary gland homogenate . Taken together , the kinetics , persistence and the individual variability of anti-sand fly saliva antibody response are important aspects to consider in further experiments , where anti-saliva antibodies are used as the markers of sand fly exposure .
|
Leishmania major is the causative agent of zoonotic cutaneous leishmaniasis and Phlebotomus papatasi serve as the major vector . In endemic foci , rodents are the natural reservoirs of this disease . Thus , we studied anti-P . papatasi saliva antibody response in BALB/c and C57BL/6 mice that are commonly used as model organisms sensitive and resistant to cutaneous leishmaniasis , respectively . We followed the kinetics and persistence of specific antibody response in both mice strains and we characterized the main P . papatasi salivary antigens . We demonstrated that sand fly bites elicit production of specific IgG that reflect the intensity of sand fly exposure . In endemic areas , this could provide useful information about the effectiveness of anti-vector control programs . We also examined the reaction of mice sera with four P . papatasi recombinant proteins . Our data indicate that a combination of these proteins could be used instead of crude salivary gland homogenate for the monitoring of anti-sand fly saliva antibodies in natural hosts in endemic foci .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"animal",
"models",
"model",
"organisms",
"parasitology",
"immunology",
"biology",
"zoology",
"mouse",
"immune",
"response"
] |
2012
|
Kinetics of Antibody Response in BALB/c and C57BL/6 Mice Bitten by Phlebotomus papatasi
|
Stimulus properties , attention , and behavioral context influence correlations between the spike times produced by a pair of neurons . However , the biophysical mechanisms that modulate these correlations are poorly understood . With a combined theoretical and experimental approach , we show that the rate of balanced excitatory and inhibitory synaptic input modulates the magnitude and timescale of pairwise spike train correlation . High rate synaptic inputs promote spike time synchrony rather than long timescale spike rate correlations , while low rate synaptic inputs produce opposite results . This correlation shaping is due to a combination of enhanced high frequency input transfer and reduced firing rate gain in the high input rate state compared to the low state . Our study extends neural modulation from single neuron responses to population activity , a necessary step in understanding how the dynamics and processing of neural activity change across distinct brain states .
Correlations between the spike trains of neuron pairs are observed throughout the central nervous system [1] . The correlation between a pair of neurons' spike trains can change depending on the state of their neural circuit . For instance , correlated neural activity is altered by stimulus properties [2] , [3] , anesthetics [4] , [5] , stimulus adaptation [6] , focus of spatial attention [7] , [8] , and the behavioral context of a task [9] . The level of spike train correlation between neuron pairs has implications for the accuracy of population codes [10] , the formation of neural assemblies [11] , and the propagation of neural activity [12] , [13] . Nonetheless , only recently has attention been given to the mechanisms by which correlated activity is modulated [14] , [15] , [16] , . Cortical neurons receive a mixture of excitatory and inhibitory synaptic inputs , resulting in spiking activity that is driven by input uctuations rather than the input mean [21] , [22] . This state is often described as balanced , to denote that the mean excitatory and inhibitory inputs that neurons receive are approximately equal [23] , [24] . Balanced activity is inuenced by stimulus properties and history [25] , [21] , as well as internal brain state [26] . These changes can modulate the integration properties of single neurons , strongly inuencing neuronal activity [22] . For example , increases in the firing rate of balanced pre-synaptic activity afferent to a neuron can reduce single neuron firing rate gain [27] , [28] , [29] , [30] , [31] , [32] . Further , an increase in the temporal correlation between the arrival times of excitatory pre-synaptic inputs increases the firing rate of a post-synaptic target neuron [33] , [34] , [35] , while correlations between excitatory and inhibitory inputs can reduce output activity [34] , [36] . The impact of such shifts in the temporal structure of synaptic input is amplified when the post-synaptic cell has a small integration timescale , as expected for neurons in the high input rate , balanced state [22] . These examples deal with synaptic activity convergent to a single target cell . However , what is less studied is the role that the balanced state plays in modulating the responses of a pair of neurons subject to a common synaptic input . In this study , we consider this latter scenario and show that shifts in balanced pre-synaptic population activity modulate the magnitude and timescale of the correlations of spike trains from pairs of post-synaptic neurons . We first explore a model system and show that output spike train correlations from a pair of neurons are modulated by varying the rate of uctuating , balanced excitatory and inhibitory inputs . Specifically , we demonstrate that an increase synaptic input rate leads to an increase of short-timescale output correlation ( i . e . precise spike synchrony ) while correlation at long timescales ( i . e firing rate co-variation ) remains unaffected , or even decreases . Due to the differential affects of our mechanism on short and long timescale spiking activity we label the combined modulation correlation shaping . Correlation shaping has been observed in various sensory systems [2] , [3] , [37] , [38] , yet the core mechanisms underlying the modulation remain unknown . We present linear response analysis showing that the enhancement of output synchrony through an increase of input rate results from a shift in single neuron integration properties that favors the transfer of high frequency inputs . Dynamic clamp recordings from cortical neurons verify our theoretical predictions . Finally , in a feedforward network model , we show how correlation shaping supports a selective propagation of network responses , so that activity can be gated by correlations in complex neuronal networks . In total , our work extends mechanisms of single neuron firing rate control include the control of pairwise correlations , thereby providing a bridge between single neuron and network state modulation .
We modeled neurons as leaky integrate-and-fire units receiving conductance input [39] . Each neuron had an intrinsic timescale ms and leak reversal potential mV . Excitatory and inhibitory synaptic input caused conductance changes and with reversal potentials mV and mV so that the membrane potential dynamics followed:When reached a threshold voltage mV , the neuron spiked and the voltage was reset to mV . We modeled the excitatory and inhibitory synaptic conductances as Poisson processes with rates and consisting of series of -functions with heights and . This framework was used for all of the simulations presented and provides a minimal model that captures our main results ( for simulations of other models , see Supplementary Figures ) . These inputs consisted of independent processes private to each neuron as well as a shared component presynaptic to all neurons , yielding where superscripts and denote independent and shared components , respectively . For large rates , this input was approximated as a diffusion process [39] , [40] , [41] , [42] ( Figure S1 ) :where was a Gaussian white noise process with unit intensity . This allowed us to write our voltage equation in the form ( 1 ) where , , and . Note that as the rates of excitation and inhibition and increase in a balanced manner , decreases , increases , and does not change substantially because of the excitation and inhibition balance . For our simulations and calculations , we set . This approximation ignored the multiplicative nature of the noise , which in our simulations did not substantially change the results ( Figure S1 ) , since the change in and were sufficient to modulate neuronal responses . To simulate pairs of neurons receiving correlated input , we set the fluctuating input to each neuron to be ( 2 ) where was shared across both neurons while was independent for each neuron . We note that , although the correlation in output spike trains depended on the degree of pre-synaptic overlap , Eq . ( 2 ) shows that , and hence the firing rate of neurons in our model , was independent of . The rate of excitatory input in the low state was 1 . 50 kHz and 6 . 16 kHz in the high state , with the inhibitory rate chosen to elicit a firing rate of 15 Hz in both cases . Simulations were performed using an Euler-Maruyama numerical integration scheme with a simulation timestep of 0 . 005 ms . We next developed a theoretical framework to study the behavior of the above system and compared our theory against simulations of the stochastic system . For completeness , we write the governing equations used to calculate the single neuron power spectrum and transfer function ; these techniques are fully presented in [42] and we refer the reader there for further details . Letting , the voltage distribution associated with the stochastic differential equation ( 1 ) obeys the Fokker-Planck equation:where is the probability flux [43] . The boundary conditions for the probability distribution and flux at threshold are and , where is the firing rate . Furthermore , the flux obeys for and is 0 otherwise . For time independent and the steady state distribution obeys:Using the normalization condition , we can solve for the steady state firing rate . In order to study the system's response to a correlated , fluctuating input , it is necessary to study the system's response to time-dependent inputs . This is done most effectively by writing a time-dependent Fokker-Planck equation in the Fourier domain:where ( ) denotes the Fourier transform of and is computed with initial condition . Solving this equation yields the Fourier transform of the first passage time density [42] . The power spectrum , where is calculated from the well known renewal relation [44] . Finally , we compute the transfer function . Suppose that we add a time-varying periodic current to the right hand side of Eq ( 1 ) . If we let be sufficiently small , we can compute the spike train response to these time-dependent modulations . Decomposing the probability density , flux , and firing rate into steady state and modulated components:and then solving the Fokker-Planck equation for the time-dependent terms , we obtain a new set of equations:with boundary conditionsThese equations were solved numerically [42] obtaining a solution for the transfer function . Surgery: Somatosensory ( S1 ) cortical slices were prepared from CBJ/Bl6 mice age P19-26 . All surgical procedures followed the guidelines approved by the Carnegie Mellon Animal Welfare Committee . The mice were anesthetized with isoflourane and decapitated . The brain was exposed , removed from the skull and immersed , in ice cold oxygenated ( ) ACSF ( in mM: 125 NaCl , 2 . 5 KCl , 25 , 1 . 25 , 1 . 0 , 25 Dextrose , 2 ) ( all chemicals from Sigma , USA ) . Coronal slices ( 300 m ) of barrel cortex made using a vibratome ( Leica , Place ) . The slices were maintained in ACSF at for 30 min then rested at room temperature ( ) for 1 hr prior to recording ( ) . Electrophysiology: L2/3 pyramidal neurons were visualized using infrared-differential interference contrast microscopy ( Olympus , Center Valley , PA ) . Whole cell , dynamic clamp recordings were performed using a MultiClamp 700B amplifier ( Molecular Devices , Union City , CA ) . Data were low pass filtered ( 4 kHz ) and digitized at 50 kHz using an ITC-18 ( Instrutech , Mineola , NY ) controlled by custom dynamic clamp software ( R . Gerkin; http://rick . gerk . in/software/recording-artist/ ) written in IgorPro ( Wavemetrics , Lake Oswego , OR ) . Pipettes were pulled from borosilicate glass ( 2 . 0 mm , outer diameter ) on a Flaming/Brown micropipette puller ( Sutter Instruments , Novato , CA ) to a resistance of 6–10 M . The intracellular solution consisted of ( in mM ) 130 K-gluconate , 5 KCl , 2 , 4 ATP-Mg , 0 . 3 GTP , 10 HEPES , and 10 phosphocreatine . Stimulation: Pyramidal cells ( n = 8 ) were directly stimulated by a series ( 50–100 trials ) of simulated noisy synaptic currents in dynamic clamp . Each trial was 4 s in duration with a 5 s inter-trial interval; the period of rest was used to ensure that stability of the recordings . For each trial , excitatory ( : 0 mV ) or inhibitory ( : −60 mV ) synaptic conductance inputs were simulated as Poisson distributed spike times convolved with alpha function . ( nS , nS , ms , 8 ms ) . The Poisson rates for excitatory and inhibitory inputs were equal to one another ( ) , and were set to 3 kHz in the low state and 7 . 5 kHz in the high state . These rates were higher than in the simulations to ensure high spike time variability , since the input variability is attenuated by the finite temporal extent of the synaptic timescales . For each state , half of these inputs were common to all neurons stimulated and half were newly generated on each trial for every neuron . This produced an input correlation , , of 0 . 5 between any given pair of neurons . This setup permitted pairwise comparisons . Since the synaptic drive was subthreshold , a bias current ( 0 . 3–0 . 7 nA ) was added such that the balanced conductance fluctuations produced a mean cortical firing rate of ( 4–6 Hz ) in both the low and high states . We studied a layered network in which a population of 100 leaky integrate-and-fire neurons ( Layer 2 ) received balanced input from a pre-synaptic layer ( Layer 1 ) with and provided excitatory input to two distinct downstream targets . Neurons in Layer 1 were assumed to be Poisson as in previous sections , and the total input to a Layer 2 neuron was therefore approximated by a diffusion process . In particular , the voltage dynamics of each Layer 2 neuron followed Eqs . 1 and 2 . The downstream target was also modeled as leaky integrate-and-fire neuron . Because we wished to fix the timescale of the downstream target , we assumed delta-function , current-based synapses so that the voltage of the downstream neuron followed:where indexes the neurons in Layer 2 and indexes the spikes in each Layer 2 neurons' spike train . We compared ms and ms . For ms , we set mV and for ms , mV so that the neurons fired at comparable rates given identical input . Other parameters , including leak , threshold , and reset voltages were identical to the model previously studied .
In general , it is difficult to determine the specific changes in a neural system's dynamics that cause changes in spike train correlations . We studied a framework in which common inputs drive the correlations between the spike trains of a pair of neurons [45] , [46] , [47] . If the degree of input correlation , , is small , a linear approximation relating to the output spike correlation , , is written as:Here the quantity , termed the correlation susceptibility , determines the extent to which two neurons' spike trains will be correlated given a fixed level of correlation between the inputs they receive [17] . Throughout this study , we focused on a pair of neurons that shift their output correlation ( ) due to a change in their pre-synaptic drive ( Figure 1A ) . Under our linear model , two simple explanations for the shift in output correlation are possible . First , the shift may simply reflect a change in the correlation of the inputs that the neuron pair receives ( ; Figure 1B ) . While this answer appears straightforward , understanding shifts in input correlation requires detailed anatomical knowledge of the network architecture , in the absence of which simplifying assumptions are required [48] . A second explanation for the shift in output correlation is a shift in correlation susceptibility ( ) , even when the input correlation remains fixed ( Figure 1C ) . Because relates the correlations in the spiking output of neurons to their common input , we expect to be sensitive to how each neuron integrates its input . Indeed , single neuron response properties such as firing rate and neural excitability determine the extent to which neurons become synchronized by shared input [49] , [17] , [18] , [19] , [20] . There has been substantial work on how single neuron properties , such as firing rates , are modulated [27] , [28] , [29] , [30] , [31] , [32] , [50] , [51] , [52] , [53] , [54] , suggesting that should also be open to modulation . We focused on this second mechanism and established how modulations of single neuron responses also modulated pairwise correlations in cortical populations . We first investigated the transfer of input correlations to output spike train correlations in a simplified two-neuron network . Each neuron received conductance-based , pre-synaptic inputs from a mixed population of excitatory and inhibitory neurons ( Figure 2A ) . To model the stochastic nature of cortical activity , the arrival times of both excitation and inhibition were modeled as Poisson processes . We set the relative strengths and rates of excitation and inhibition so that the mean input was balanced [23] , [24] , and the average membrane potential was below spiking threshold . Balanced pre-synaptic activity results in large membrane fluctuations that trigger spikes in a random , aperiodic pattern , consistent with in vivo recordings from cortical neurons [21] , [22] . Shifts in the activity level of a recurrent cortical population are observed in many neural systems and have been shown to affect the response properties of neurons in vitro and in vitro [22] , [55] , [31] . To explore the modulatory effects of balanced synaptic input , we considered the neuron model in two states: a low state , in which pre-synaptic input arrived at a low rate , and a high state , in which pre-synaptic input arrived at a high rate ( Figure 2A ) . While the level of balanced fluctuations may lie on a continuum , we compared two representative points , analogous to high and low activity states in a cortical network [56] , [26] . A clear consequence of the shift from low to high states was an increase in the variability of both the input current and membrane potential response , due to greater fluctuating input ( Figure 2B ) . This increase of input variability was reflected in an increase in spiking variability , with the coefficient of variation of the inter-spike intervals increasing from 0 . 73 in the low state to 0 . 91 in the high state . A second consequence of an increase in pre-synaptic rate was the reduction of the membrane time constant ( Figure 2B ) . This was expected , since the membrane time constant , with the membrane capacitance and the total membrane conductance [57] . As is roughly proportional to the pre-synaptic rates , an increase in the rate of synaptic input lead to a decrease in . Taken together , the shift from the low to high state evoked a more stochastic and faster membrane potential response . We first examined the effect of balanced synaptic input on firing rate gain , the slope of the firing rate curve when plotted as a function of excitatory input strength . When the rate of balanced excitatory and inhibitory synaptic input changed from low to high , the neuron's firing rate gain was substantially reduced ( Figure 2C ) . This gain decrease in the high background state has been studied extensively in theoretical and in vitro work [27] , [28] , [29] , [30] , [31] , [32] as well in vivo under specific stimuli conditiona [31] . In the high state , larger membrane potential fluctuations increased firing rates for weak inputs . However , there was also a decrease of the net membrane input resistance , causing an increase in the rheobase current ( minimum steady current required to recruit spiking ) . The combination of these two effects lead to an overall reduction in firing rate gain [29] . We next explored the consequences of gain modulation via balanced activity for correlation transfer by pairs of neurons . To study the effects of balanced excitatory and inhibitory inputs on pairwise spike train correlations , we extended our model to include a pair of post-synaptic neurons receiving overlapping pre-synaptic inputs ( Figure 3A ) . Previous work has shown that the output firing rate affects correlation susceptibility [17] . To preclude any firing rate-induced effects , the synaptic input was adjusted so that the average output firing rate of each neuron remained at 15 Hz in low and high states ( Figure 2C ) . Furthermore , there was a fixed overlap in the input populations , so that the input correlation also remained constant in both network states ( Figure 3A ) . Thus , any change in the output spike train correlation induced by changing synaptic input will be due exclusively to a shift in correlation susceptibility ( Figure 1C ) . We found that the timescale over which the two spike trains were correlated was dependent on the level of balanced synaptic activity ( Figure 3A , Right ) . When the synaptic rate increased from the low to high state , the magnitude of the peak of the cross-correlation function near zero lag increased , reflecting greater spike time synchrony between the neurons . However , this increase was not present for longer lags , and the spike train cross-correlation function was unchanged or reduced for sufficiently long lags ( ms ) . To quantify this change in output correlation over a range of timescales , we first counted the number of spikes and that the two neurons emitted in intervals of milliseconds . We next computed the spike count correlation as a function of window size: ( 3 ) where Cov and Var denote covariance and variance , respectively . In the framework of our simple circuit ( Figure 3A ) , correlation in output spike trains was a consequence of a shared input correlation . For small , linear response theory [17] takes the output correlation to be a linear function of the input correlation ( Figures 1B , C; 3B ) : ( 4 ) In our model , this linear relationship held for a range of , in both low and high states and at both short and long ( Figure 3B ) . Further , the values produced were , in magnitude , consistent with in vivo recordings from a variety of systems [58] , [3] , [2] , [6] . When comparing for the low and high states at fixed , a differential change of correlation at different timescales was evident . Specifically , for small ( Figure 3B , = 3 ms ) , while for large ( Figure 3B , = 50 ms ) . This differential modulation of correlation occured over a broad range of timescales , with and intersecting only once ( Figure 3C ) , and we label the modulation a shaping of correlation [38] . This substantial change in both the magnitude and timescale of correlation must involve a nontrivial change in how the neurons process their inputs , since the input correlation and firing rate were the same in both low and high states . We note that the qualitative results of our study are also valid for larger ( Figure S2 ) and different synaptic strengths ( Figure S3 ) . Since as [59] , changes in at small are necessarily smaller in magnitude . However , synchrony at short timescales can have large effects on downstream targets sensitive to coincident pre-synaptic spikes [12] and indeed the peak of the cross-correlation function increased substantially in the high state ( Figure 3A , Right ) . To properly compare correlation shaping at small and large we considered the ratio , providing a relative measure across the low and high states . The ratio was a decreasing function of , with substantial changes in correlation at both short and long timescales ( Figure 3D ) . The negative slope of the curve indicates that increases in the rate of balanced synaptic activity favor spike synchronization rather than long timescale correlation . Finally , the spectral measure of spike train coherence between the two spike trains in both states exhibited a decrease for low frequencies but a significant increase for high frequencies in the high state ( Figure 3E ) . Here , the increase for high frequencies , which occurs over a broad range of frequency space , is related to the increase in short timescale synchrony , consistent with the spike count correlation shaping . Correlation shaping is an unexpected feature of balanced synaptic activity . For subthreshold membrane potential dynamics ( or any other linear system ) the ratio is equal to 1 for all assuming a fixed input correlation ( Figure 3D , gray line ) . The mechanism that shapes correlation transfer so to promote spike train synchronization over long timescale correlation in the high state ( Figure 3D ) is the focus of the next section . Correlation shaping is a property of the joint statistics of a pair of neurons . However , since the input correlation was the same in the low and high states of our model , then the mechanism underlying the shaping is hypothesized to be related to changes in single neuron input integration and spike emission across the two synaptic states ( Figure 1C rather than 1B ) . In this section , we show that correlation shaping is a consequence of a shift in the single neurons' frequency response across the low to the high input state . The spike train auto-correlation and cross-correlation functions are written as: ( 5 ) where , with labeling the spike time from neuron . Here is the mean firing rate of neuron . We are interested in the joint spike count correlation for the neuron pair , where the spike count for neuron over a window of length is ( we take the neuron's stochastic dynamics to be in statistical equilibrium ) . The spike count variance and covariance are related to integrals of auto- and cross-correlation functions [44] , yielding an alternate expresion for : ( 6 ) In the second equality we have , for simplicity , assumed that ( or equivalently ) . These integrals can be transformed to the frequency domain , using the Wiener-Khinchin theorem [44] to relate correlation functions to their spectral analogues , yielding ( 7 ) Here is the Fourier transform of the triangular weighting term in Eq . ( 6 ) . Our strategy was to relate the cross spectrum between the spike trains , , to single neuron integration properties . Single neuron input-output transfer is typically expressed through its spectral transfer function . The transfer function measures the ratio of the amplitudes of a neuron's firing rate response and a small amplitude sinusoidal signal of frequency ( Figure 4A ) . For very slow inputs , the transfer function equals the firing rate gain , since this measures the sensitivity of firing responses to static ( ) inputs . For , is the susceptibility for a neuron's trial averaged response to be locked to a time varying signal . The transfer function is experimentally measurable [60] , and is related to the more commonly reported spike triggered average [61] . In general , for neurons in the fluctuation-driven regime , is a decaying function of ( Figure 4B ) . If each neuron receives a small shared signal , then we can write the expectation of the Fourier transform of the spike train from neuron as: ( 8 ) where the brackets denote an average over repeated frozen presentations of the shared signal with different realizations of the independent noise driving the neurons [62] . Here , is the linear response of the system to the perturbation . Finally , averaging the quantity over different realizations of the process yields the cross-spectrum between neurons 1 and [17] , [62] , [63] , [64]: ( 9 ) For the case of white noise input , we have that . With Eqs . ( 7 ) and ( 9 ) we calculated the spike count correlation coefficient between the two neurons receiving shared white noise input as ( 10 ) Our theory then relates single neuron transfer and power spectrum to the joint pairwise response . The theoretical predictions given in Eq . ( 10 ) gave a very good quantitative match to simulations of the leaky integrate-and-fire neuron pair ( Figures 3B–E , compare solid curves to points ) , capturing the correlation shaping between the two states . Eq . ( 10 ) has been previously derived [17] , [18] , however , the model neurons considered in those studies were current driven model neurons . We considered conductance driven model neurons , meaning that the calculation of and must account for the linked shifts of the membrane time constant and membrane potential fluctuations from the low to the high state ( Figure 2B ) . For our conductance based integrate-and-fire model neurons , the quantities and were calculated by numerically integrating the Fokker-Planck equation associated with the stochastic differential equation expressed in Eq . ( 1 ) ( see [42] and Methods ) . The distinction between current and conductance based neural integration will be shown to be critical for correlation shaping . Before correlation shaping is related to the shifts in between the low and high states , we first discuss the dependence of susceptibility on the window size ( Figure 3B ) . This dependence enters equation ( Eq . ( 10 ) ) through the weighting term , which determines the contribution of across frequency to . For long timescales ( large ) , is low-pass , so that only the neurons' response to low frequencies contributes to correlation susceptibility . In contrast , for short timescales ( small ) , weighs the transfer function approximately equally across all frequencies . Hence , the neurons' high frequency response determines precise spike synchrony . Indeed , for we have that , while limits to a constant function on . Therefore , for large , only the zero-frequency components of contribute to the integral , while for small , all frequencies contribute . A mechanistic understanding of correlation shaping ( Figure 3D ) requires knowledge of how the rate of balanced synaptic activity affects the transfer function . As discussed previously , the increase in synaptic input from the low to the high state decreased the effective membrane time constant of the neuron while it increased the input variability ( Figure 2B ) . The decrease in corresponded to a decrease in the timescale over which a neuron integrates inputs and hence an attenuation of the neuron's transfer function . For low frequency inputs , this reduction was precisely the firing rate gain control known to occur with increased synaptic input ( Figure 2C ) . Increased variability and shunting due to heightened conductance reduced the neuron's ability to respond to slow depolarizing inputs . However , the reduction in the transfer function from the low to high state was not uniform across all frequencies ( Figure 4C , Left ) . This was because the smaller value of in the high state enhanced the tracking of fast inputs , mitigating the attenuation of the transfer function for high frequencies . The combination of the non-uniform attenuation of the transfer function and increase in from the low to high state determined the shaping of the correlation susceptibility ( see Eq . ( 10 ) ) . To illustrate the shift in single neuron response between the low and high states , we considered the quantity , the strength of the input fluctuations multiplied by the input transfer function . The ratio was an increasing function of frequency ( Figure 4C , Center ) , indicating that high frequency transfer is favored in the high state . In general , a favoring of high frequencies corresponds to a favoring of synchrony , measured over only small ( since is nearly flat across for small ) . Thus , the high state is expected to favor small correlation transfer compared to the low state ( Figure 4C , Right ) . In contrast , for large which corresponds to low frequencies , correlation transfer was disfavored in the high state ( since only weights low for large ) . This ratio allowed us to intuitively link correlation shaping over different timescales to the shaping of the transfer function over different frequencies . We argue above that a change in the effective membrane time constant is central to the correlation shaping we discuss . To demonstrate this fact , we computed the transfer function and correlations for a current-based model in which remained unchanged in the low and high state , although increased by the same amount . If firing rates were again fixed at 15 Hz , the transfer function was again reduced in the high state , but the ratio remained close to unity ( Figure 4D , Left and Center ) . As a result , no substantial correlation shaping was observed ( Figure 4D , Right ) . The above comparison shows that this shaping requires the modulation of cellular properties that is allowed by a conductance-based model . Finally , we note that , although our analysis has focused on the numerator of Eq . ( 7 ) , the denominator also affects the correlation for large time windows ( Figure S4 ) . For these values of , the denominator was increased in the high state , reflecting the higher variability of firing due to stronger input fluctuations . This further attenuated the value of for large in the high state . To avoid changes in correlation owing to firing rate [17] , we chose the balance between excitation and inhibition in previous sections so that firing rate was fixed across both the low and high states ( Figure 2C ) . However , it is unlikely that firing rates will remain fixed as a network shifts from a low conductance to a high conductance state . Thus , it is important to understand how correlation shaping via balanced excitatory and inhibitory inputs interacts with the correlation changes expected due to firing rate changes . In this section we show how the modulations of correlation due to balanced excitatory and inhibitory inputs and those due to firing rate changes from imbalanced inputs are distinct . The firing rates of our output neurons were determined by the input rate of both the excitatory ( ) and inhibitory ( ) inputs . In fact , for any desired output rate , there was a curve in ( ) space that achieved that rate ( Figure 5A ) . For moderate input rates , a balanced shift in input ( approximately linear in and ) preserved output firing rate . A change in output firing rate ( switching from one curve to another in Figure 5A ) , can occur from a shift in , a shift in , or some combination of the two . When we fixed to its value in the low state and increase so that the output rate increased , increased over all timescales ( Figure 5B , top ) , as expected [17] . A similar effect occured if we repeat this in the high state ( Figure 5B , bottom ) . Thus , the modulation of by a rate change due to an imbalanced shift of simply scales for all ( collapsed blue and orange curves in Figure 5C ) . Nevertheless , after correcting for the rate scaling of , the shaping of correlation between the low and high states remained clear ( Figure 5C ) , demonstrating that correlation shaping due to a change from low to high states is distinct from correlation shifts due to arbitrary output firing rate changes . To illustrate this , we considered a shift from 8 Hz in the low state to 35 Hz in the high state . In the shift from the low to high state , the effective membrane timescale shifted from 10 . 8 to 2 . 9 ms and the amplitude of the input fluctuations from 0 . 16 to 0 . 37 nA . These shifts changed significantly ( as discussed in the previous section ) , and changed the timescales over which the neuron pair was correlated . This was contrasted by a shift from 8 Hz to 35 Hz in the low state: a change in firing rate without a change between low and high states . Here , shifted from 10 . 8 to 10 . 2 ms and the input fluctuations from . 16 to . 18 nA , having little influence on other than a uniform scaling due to the output rate change . In total , by changing both and , it was possible to not only change the output firing rate so as to amplify or attenuate , but also to shape the timescales over which a neuron pair was correlated . Our two-neuron framework for studying correlation transfer ( Figure 1A ) permited an experimental verification of correlation shaping with balanced , fluctuating conductance inputs . We performed in vitro patch clamp recordings from cortical pyramidal neurons receiving simulated excitatory and inhibitory inputs . Unlike past experimental studies of correlation transfer [16] , [17] , our model involved conductance-based , rather than current-based synapses . Therefore , we simulated synaptic input using dynamic clamp [65] ( see Methods ) , which affected the membrane integration timescale as well as membrane potential variability . We chose maximal excitatory and inhibitory conductances of 1 nS and synaptic timescales of 6 and 8 ms , respectively , producing a synaptic input that was more biophysically realistic than the diffusion process used in previous sections ( Figure 6A ) . The shift from low to high state caused a near two-fold reduction in firing rate gain ( Figure 6B ) , in qualitative agreement with our model simulations ( Figure 2C ) and past dynamic clamp studies [29] . Further , as was done in the model , we set the synaptic balance in the low and high states to produce approximately the same firing rate ( Hz in the low state and Hz in the high state ) . The correlated input for a given neuron pair was a mixture of shared and independent excitatory and inhibitory inputs , mimicking the input provided to the model ( Figure 3A ) . The partial overlap in the synaptic input produced correlated membrane potential and spike dynamics for every neuron pair in both the low and high states . Our recorded spike trains showed a dependence of spike count correlation on that was qualitatively similar to that of the model , apparent in the ratio of in the high and low states ( Figure 6C ) . The ratio was a decreasing function of , indicating a bias toward synchrony in the high state compared to the low state . This shape was consistent with our model results ( Figure 3D ) , although the ratio did not fall substantially below unity in the limit of large . This suggested that the decrease in gain and the increase in variability from the low to high state were of similar magnitudes , since in the limit of large correlation susceptibility is proportional to ( Methods ) . A conductance-based simulation using the same synaptic parameters used for dynamic clamp stimulation produced results in agreement with the experiment ( Figure S5 ) . The favoring of synchrony ( = 2 ms ) over long timescale correlation ( = 200 ms ) in the high state was statistically significant in a pairwise analysis across the dataset ( Figure 6C , inset; , paired t-test ) . The experiments demonstrated that an increase in the rate of balanced conductance input shapes pairwise correlation so as to favor synchronization over long timescale correlation , thereby verifying the main theoretical predictions of our study . Our theoretical treatment has ignored the timescale of synaptic input , and has associated all filtering to the membrane and spike properties of the model ( Figure 4 ) . Correlation transfer with realistic synaptic timescales did quantitatively differ from the case with instantaneous synaptic input ( Figure S5B ) . Nevertheless , our theoretical work captured the main effects of correlation shaping when synaptic timescales were realistic ( Figures 6 and S5 ) . This is because only the effective membrane time constant was sensitive to a shift in input firing rate , which our theory accounts for , while synaptic filtering did not change between low and high states . We remark that , for synapses with very long timescales , correlation shaping should only be present for large , since correlations at small will be negligible . The spike train correlations between neuron pairs substantially influence the propagation of neural activity in feedforward architectures [13] . For example , while our study has so far focused on the transfer of correlation for neuron pairs receiving common input , the firing rate of a single downstream neuron also depends on the correlation between neurons in its pre-synaptic pool [12] . If the integration timescale of the downstream target is small , only precise spike synchrony will effectively drive the neuron . In contrast , neurons that slowly integrate inputs will be sensitive to long timescale correlations . In our study , we demonstrated that an increase in the rate of synaptic input increases spike count correlation at small while simultaneously decreasing the correlation at large ( Figure 3D ) . We therefore expected that this correlation shaping would influence the extent to which activity can be propagated to a downstream layer . Further , that the magnitude of this effect would depend on the integration timescales of the downstream targets . As an illustration of this effect in a simplified system , we studied the firing rate of a downstream neuron receiving input from an upstream population of correlated neurons ( Figure 7A; Methods ) . The level of synaptic drive from layer 1 shaped the correlation of pairs of layer 2 neurons ( Figure 7A , insets ) . The network was constructed so that the activity of any given pair of neurons in Layer 2 was equivalent to that of the neuron pairs studied in previous sections . As the correlation of layer 2 spike outputs was shaped , so too was the magnitude and timescale of the synaptic drive to the downstream target neuron ( Figure 7B ) . For comparison , we show that downstream target's synaptic input when the layer 2 neurons were uncorrelated ( Figure 7B , bottom ) , showing significantly reduced variability [12] . In the uncorrelated case , the firing rate of the downstream target was much less than 1 Hz , indicating that correlated input was necessary for its recruitment . We study how correlation shaping of the layer 2 projections affected the recruitment of the downstream target neuron . In particular , we focused on how the changing timescale of correlation recruited downstream targets differentially , depending on their own integration properties . We varied the rate of balanced synaptic input from layer 1 to layer 2 in a smooth manner ( following the and path for 15 Hz output in Figure 5A ) , gradually shaping the correlation function between any given layer 2 neuron pair . The shaping included the low and high states described earlier as near endpoints on a continuum ( Figure 7C ) . When the downstream target had a smaller time constant ( 3 ms ) , its firing rate was increased when the pre-synaptic population was in the high state ( Figure 7C , dashed line ) . This contrasted with the decreased firing rate in the high state when the downstream target had a longer time constant ( 20 ms ) ( Figure 7C , solid line ) . This differential effect was due to matching between the correlation timescale of layer 2 and the integration timescale of the downstream target . In the high state , synchrony drove the neuron with the short integration timescale , while , in the low state , long timescale correlations drove the slower neuron . Note that the firing rate of layer 2 neurons was unchanged in all cases studied . This simple example demonstrates that the structure of correlations between pre-synaptic neuron pairs can differentially drive downstream targets depending on their integration properties .
Correlated neural activity continues to receive increasing attention [1] , prompting investigations of the mechanisms that determine the transfer of correlation . Correlations are typically measured only at one timescale , but as we have shown , the magnitude of correlation depends on the timescale being considered , as does the likely significance of this correlation for activation of downstream neurons . Past studies have highlighted the dependence of spike train correlations on the magnitude of input correlation [15] , [16] , the form of spike excitability [19] , [66] , or the firing rate of the neuron pair [17] , [18] . However , how the timescale of correlations are modulated through plausible mechanisms had not been addressed . Changes in membrane conductance have been widely studied and strongly influence the dynamics of single neuron activity [22] . In our study , we found that timescale-specific changes in neural correlations are a necessary consequence of conductance based modulation schemes . Previous work that has examined how correlated activity is transferred has used linear response methods to examine the response of neurons to current fluctuations , thereby leaving membrane integration invariant [17] , [18] . As a result , cellular properties such as timescale were not modulated ( see Figure 4D ) . We showed that when synaptic conductance is considered , it is possible to shape both the magnitude and timescale of output spike train correlations . This is a novel result that is nevertheless consistent with , and complementary to , the observation that firing rate also modulates correlations ( see Figure 5 ) . The widespread use of multi-unit recording techniques to study population activity has produced an increasingly clear picture of how neuronal spike trains are correlated in a variety of neural states . Recently , there has been particular interest in noise correlations , which are specific to within trial comparisons and cannot be directly attributed to a common signal [10] . Several groups have reported noise correlation measurements , ranging from small positive values [58] , [2] , [3] , [6] , [7] , [8] to values that are , on average , zero , with positive and negative values equally represented [4] , [67] , [48] . Furthermore , in cases where significant noise correlation is measured , it can be modulated on distinct timescales . In the visual system , for example , noise correlation measured on timescales less than 100 ms is largest for cells with similar preferred stimulus orientations being driven at that orientation , observed in both spike responses [2] and synaptic input [37] . Further , while increasing stimulus contrast enhances short timescale correlation , it reduces long timescale ( ms ) correlation [2] . In primate area V4 , stimulus attention reduces noise correlation when measured on timescales that are larger than 100 ms , yet has little influence on short timescale correlation [7] , [8] . In contrast , other groups have shown that stimulus attention enhances spike synchrony measured at the gamma frequency timescale ( 20–40 ms ) [68] . In the electrosensory system , long timescale noise correlation is reduced by recruitment of a non-classical receptive field , while synchrony is increased under the same conditions [3] . Thus , spike train noise correlations provide an excellent framework to study how the magnitude and timescale of correlations are shaped by neural state changes . While a shaping of output correlation observed in these systems may be inherited from a state-dependence of input correlation ( Figure 1B ) , single neuron response properties are often also modulated by network state . This suggests that a shift in correlation susceptibility may underlie a shift in pairwise correlation ( as in Figure 1C ) . Indeed , firing rate gain is modulated by attention [69] , stimulus contrast [21] , and the recruitment of a non-classical receptive field [70] . In many cases , intracellular recordings have established that gain control is mediated by an increase in the rate of excitatory and inhibitory synaptic inputs [21] , [31] , in a fashion similar to the case presented in our study . Dual intracellular experiments that measure both input and output correlation across distinct neural states [45] , [46] , [37] are required to parcel the contribution of correlation inheritance and correlation transfer to the full shift in noise correlations . A central result of our paper is that changes in synaptic input rate shape the correlation between the output spike trains from a pair of neurons . This is a consequence of how synaptic input modulates the timescale of membrane integration and response sensitivity of the two neurons . Our theoretical analysis formalizes this concept by explicitly relating the spike train correlation coefficient to the single neuron transfer function . Though we focused on modulation by balanced synaptic inputs , the relationship between transfer function and correlation is general , requiring only that the input correlation be sufficiently small . Thus , we predict that any synaptic or cellular mechanism that modulates single neuron transfer will necessarily affect spike train correlations . Modulation of single neuron transfer with the level of synaptic input rate is well studied [27] , [28] , [29] , [30] , [31] , [32] . However , how other cellular processes affect neuronal transfer is equally well studied . For example , increases in the spike after-hyperpolarization [50] or decreases in the spike after-depolarization [51] reduce the gain of the firing rate response to static driving inputs . Sustained firing often recruits slowly activating adaptation currents that also reduce gain [52] , [53] . We predict that these modulations will reduce long timescale spike rate correlations . In contrast , the presence of low threshold potassium currents in the auditory brainstem [71] promotes high frequency single neuron transfer and thus may also promote pairwise synchronization . In total , our result gives a general theory that links the modulation of single neuron and network responses , thereby expanding the applicability of studies of single neuron modulation . How the brain selectively propagates signals is a basic question in systems neuroscience . One control mechanism is through an ‘unbalancing’ of feedforward excitation to inhibition , with disinhibited populations propagating activity and excessive inhibition silencing propagation [72] . Modulation of correlation is an alternative mechanism to control signal propagation . The correlation between spike trains from neurons in a population enhances the ability of that population's activity to drive downstream targets [12] , [13] . We have shown that modulating the timescale of correlation in the upstream population to match the integration timescale of the downstream population improves signal propagation ( Figure 7 ) . Matching the integration dynamics of distinct neuronal populations to one another is a common theme in the binding of distributed activity [73] . In previous studies , the phase relationship between distinct neuronal populations both oscillating at some frequency gated the interaction between distinct brain regions . Our study did not assume rhythmic population dynamics , but rather only matched integration timescales . The nonlinearity of spike generation allows for the transfer of shared input to multiple neurons to be controlled in complex ways . We have shown that well-studied mechanisms of single neuron response modulation , such as firing rate gain control , have direct relations to changes in correlation for neuron pairs . Thus , state dependent shifts in single neuron transfer also influence how populations of neurons coordinate their activity . Our results are a step in understanding how the collective behavior of neuronal networks can be controlled in different brain states .
|
Neurons in sensory , motor , and cognitive regions of the nervous system integrate synaptic input and output trains of action potentials ( spikes ) . A critical feature of neural computation is the ability for neurons to modulate their spike train response to a given input , allowing task context or past history to affect the flow of information in the brain . The mechanisms that modulate the input-output transfer of single neurons have received significant attention . However , neural computation involves the coordinated activity of populations of neurons , and the mechanisms that modulate the correlation between spike trains from pairs of neurons are relatively unexplored . We show that the level of excitatory and inhibitory input that a neuron receives modulates not only the sensitivity of a single neuron's response to input , but also the magnitude and timescale of correlated spiking activity of pairs of neurons receiving a common synaptic drive . Thus , while modulatory synaptic activity has been traditionally studied from a single neuron perspective , it can also shape the coordinated activity of a population of neurons .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"physics",
"statistical",
"mechanics",
"computational",
"neuroscience",
"single",
"neuron",
"function",
"biology",
"sensory",
"systems",
"neuroscience",
"coding",
"mechanisms"
] |
2011
|
Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains
|
Although it is generally believed that CD4+ T cells play important roles in anti-Leishmania immunity , some studies suggest that they may be dispensable , and that MHC II-restricted CD3+CD4−CD8− ( double negative , DN ) T cells may be more important in regulating primary anti-Leishmania immunity . In addition , while there are reports of increased numbers of DN T cells in Leishmania-infected patients , dogs and mice , concrete evidence implicating these cells in secondary anti-Leishmania immunity has not yet been documented . Here , we report that DN T cells extensively proliferate and produce effector cytokines ( IFN-γ , TNF and IL-17 ) and granzyme B ( GrzB ) in the draining lymph nodes and spleens of mice following primary and secondary L . major infections . DN T cells from healed mice display functional characteristics of protective anti-Leishmania memory-like cells: rapid and extensive proliferation and effector cytokines production following L . major challenge in vitro and in vivo . DN T cells express predominantly ( > 95% ) alpha-beta T cell receptor ( αβ TCR ) , are Leishmania-specific , restricted mostly by MHC class II molecules and display transcriptional profile of innate-like genes . Using in vivo depletion and adoptive transfer studies , we show that DN T cells contribute to optimal primary and secondary anti-Leishmania immunity in mice . These results directly identify DN T cells as important players in effective and protective primary and secondary anti-L . major immunity in experimental cutaneous leishmaniasis .
The spectrum of disease collectively called Leishmaniasis is caused by several species of protozoan parasites belonging to the genus Leishmania . The disease is currently endemic in 88 countries , affecting an estimated 12 million people with over 1 . 5–2 million new cases and 70 , 000 deaths each year [1] . Because Leishmania parasites reside mainly within macrophages , a strong cell-mediated immunity is required to control intracellular parasite replication and disease progression [2] , [3] , [4] , [5] , [6] . Experimental L . major infection in mice closely mimics the human cutaneous disease and is an excellent model for understanding the factors that regulate cell-mediated immunity . Resistance to cutaneous leishmaniasis is associated with strong IFN-γ response , which activates infected macrophages leading to nitric oxide and reactive oxygen species production and destruction of the intracellular parasites [4] , [7] , [8] , [9] . Although it is generally believed that CD4+ T cells play a primary role in mediating anti-Leishmania immunity , a study suggests that they may be dispensable and that MHC II-restricted CD3+CD4−CD8− ( double negative , DN ) T cells are critical for regulating primary anti-Leishmania immunity [10] . In addition , several studies have reported increased numbers of DN T cells in blood of Leishmania-infected patients [11] , [12] , dogs [13] , and in spleens of Leishmania-infected mice [14] . These cells have been proposed to contribute to primary and vaccine-induced immunity against Leishmania . However , direct evidence implicating DN T cells in anti-Leishmania immunity has not yet been clearly documented . Here , we report for the first time , that infection with L . major leads to activation and proliferation of DN T cells in the draining lymph nodes ( dLNs ) and spleens of infected mice . These cells produce effector cytokines ( IFN-γ and TNF ) , display functional characteristics of memory-like cells and contribute to optimal primary and secondary protection against L . major infection .
Recovery from natural or experimental L . major infection is associated with strong T cell proliferation and IFN-γ production in spleens and dLNs . To investigate the contribution of CD4+ T cells in this process , we co-cultured CD8+ T cell-depleted splenocytes from healed mice with L . major-infected BMDCs in vitro . Surprisingly , we found in addition to CD4+ T cells , strong proliferative and IFN-γ responses by CD3+CD4−CD8− ( DN ) T cells ( Fig . 1A and Fig . S1A and B ) . Proliferating DN T cells also produced TNF ( Fig 1B ) , IL-17 ( Fig . S2A ) and little IL-2 ( Fig . 1D ) , suggesting they are polyfunctional in cytokine production . Indeed , most of the IFN-γ-producing DN cells also co-produced TNF ( Fig . 1C ) . Interestingly , although DN T cells proliferate significantly more than CD4+ T cells , their quantitative ability to produce IFN-γ and TNF was significantly lower than those of CD4+ T cells ( Fig . S2B–D ) . In addition , DN T cells also produced GrzB ( Fig . 1E ) , suggesting they may perform effector functions in L . major-infected mice . DN T cells from L . major-infected mice did not proliferate or produce IFN-γ following stimulation with OVA-loaded DCs ( Fig . 1F ) , but were activated by DCs pulsed with SLA or freeze-thawed L . major ( Fig . 1F ) . Collectively , these results suggest that the proliferation and cytokine production by DN T cells from healed mice are L . major specific . Our co-culture system showed that Leishmania-specific DN T cells are activated following in vitro recall response . To determine whether DN T cells are activated in vivo , we adoptively transferred CFSE-labeled T cells from healed Thy1 . 2 mice into naive Thy1 . 1 mice that were then challenged with L . major the next day . Both CD4+ and DN T cells from healed donor mice showed extensive proliferation and IFN-γ production compared to those from naive mice ( Fig . 2A–D ) . The in vivo relevance of DN T cell response was further confirmed by BrdU incorporation ( Fig . 2E and F ) . Interestingly and similar to CD4+ T cells , the percentage of proliferating and IFN-γ-producing DN T cells in healed mice were significantly higher than those in naïve mice following L . major challenge , suggesting that DN T cells display functional characteristics of memory T cells ( rapid proliferation and cytokine production ) . Indeed , we found that the percentage of DN T cells in lymph nodes ( Fig 3A ) of healed mice that express CD62LhiCD44hi ( central memory-like ) was significantly higher ( p<0 . 05 ) than those in naive mice ( Fig . 3B ) . Following adoptive transfer of whole T cells from healed mice and subsequent L . major challenge , almost all the proliferating donor CD4+ T cells downregulated their CD62L expression ( i . e . were CD62Llo ) . In contrast , the proliferating DN T cells contained an almost equal proportion of CD62Llo and CD62Lhi populations ( Fig . 3C ) . In addition , more DN T cells were CD62LhiCD44hi compared to CD4+ T cells ( Fig . 3D ) . In addition to αβ T cells , NKT and γδ T cells also do not express CD4 and CD8 molecules . To determine whether Leishmania-reactive DN T cells are NKT and γδ T cells , we assessed the expression of αβ , γδ and NK1 . 1 molecules on DN T cells by flow cytometry . As shown in Fig . 4A , DN T cells predominately ( > 90% ) expressed αβ TCR and not NK1 . 1 and γδ molecules , indicating that they are not NKT or γδ T cells . To further determine whether DN T cells are CD4+ or CD8+ T cells that have down-regulated their surface molecules following activation , we assessed highly enriched ( > 99% purity , Fig . S3 ) DN , CD4+ and CD8+ T cells for CD4 and CD8 transcripts by RT-PCR . DN T cells did not express CD4 and CD8 mRNA ( Fig . 2B ) , suggesting they are not CD4+ or CD8+ T cells that have down-regulated their surface molecules . In addition , highly purified CD4+ , CD8+ and DN T cells maintained their respective phenotypes following in vitro restimulation for 5 days with L . major-infected BMDCs ( Fig . 4C ) . To determine whether Leishmania-reactive DN T cells display regulatory properties as previously reported in other systems [12] , [15] , [16] , we co-cultured CD4+ and DN T cells with L . major-infected BMDCs and assessed CD4+ T cell proliferation and IFN-γ production by flow cytometry . DN T cells did not affect CD4+ cell proliferation and IFN-γ production ( Fig . 4D ) , suggesting that they do not exhibit regulatory/suppressive properties . To determine whether Leishmania-reactive DN T cells are restricted by MHC II molecule , we co-cultured highly enriched T cells from healed mice with infected BMDCs in the presence or absence of anti-MHC II antibodies . Anti-MHC II antibodies blocked proliferation and IFN-γ production by both CD4+ and DN T cells in a dose-dependent manner ( Fig . 5A ) . In addition , L . major-infected BMDCs from MHC II KO mice failed to induce proliferation and IFN-γ production by DN and CD4+ T cells ( Fig . 5B ) . In contrast , proliferation and IFN-γ production by DN T cells were minimally affected following co-culture with infected BMDCs from CD1d KO mice ( Fig . 5C ) , confirming that DN T cells are mostly restricted by MHC II molecules . We found that Leishmania-reactive DN T cells are recalled in healed mice following L . major challenge in vitro and in vivo suggesting that they may be induced following primary infection . To determine this , we assessed CD4+ and DN T cells response in the dLNs and spleens of infected mice C57BL/6 mice at different times after infection corresponding to early , peak and resolution of lesion progression ( Fig . 6A ) . As expected , there was strong CD4+ T cell response ( proliferation and IFN-γ production , Fig . 6B ) at all times ( 3 , 6 and 12 weeks ) post-infection . Similarly , DN T cells from infected mice also strongly proliferated and produced IFN-γ following restimulation with infected BMDCs ( Fig . 6C ) . In contrast , CD4+ and DN T cells from naïve mice did not proliferate or produce IFN-γ upon stimulation with L . major-infected BMDCs ( Fig . 6B and C ) . Collectively , these results show that Leishmania-reactive DN T cells are induced during primary L . major infection and could contribute to anti-Leishmania immunity . To determine if DN T cells contribute to primary immunity against L . major , we selectively depleted CD4+ and CD8+ or all T cells by treatment with anti-CD4/CD8 or anti-Thy1 . 2 mAbs , respectively , during the course of primary L . major infection ( Fig . S4 ) . Mice depleted of both CD4+ and CD8+ T cells still had some IFN-γ-producing CD3+ DN T cells ( Fig . 7A and 7B ) and harbor significantly ( p<0 . 01 ) lower parasite burden ( Fig . 7C ) compared to those depleted of all T cells ( by anti-Thy1 . 2 mAb treatment ) , indicating that DN T cells contribute to optimal control of parasite proliferation during primary L . major infection . Next , we used both in vitro and in vivo approaches to investigate whether DN T cells contribute to secondary anti-Leishmania immunity . Highly purified DN T cells from healed ( but not naïve ) mice significantly ( p<0 . 05 ) inhibited parasite proliferation in infected BMDMs and this effect was comparable to those of CD4+ T cells ( Fig . S5A and B ) . These results provide direct in vitro evidence that DN T cells could control parasite growth in L . major-infected BMDMs . Next , we used two different experimental approaches to determine whether DN T cells contribute to secondary anti-Leishmania immunity in vivo . First , we selectively depleted CD4+ and CD8+ or all CD3+ T cells ( as in Fig . 7A above ) in healed mice and after 24 hr , rechallenged them with L . major . As shown in Fig . 7D , CD4+ and CD8+ T cells-depleted mice , which still had DN T cells , retained some level of infection-induced resistance as evidenced by significantly ( p<0 . 01 ) lower parasite burden compared to naïve mice ( primary infection ) . In contrast , depletion of all CD3+ T cells completely abrogated secondary immunity ( Fig . 7D ) . Second , we assessed the ability of highly enriched ( purity > 96% , Fig . S6 ) DN T cells from healed mice to protect naïve animals against virulent L . major challenge . Adoptively transferred DN T cells from healed mice protected naïve mice against virulent L . major challenge as evidenced by significantly lower parasite burden ( Fig . 7E ) . Collectively , these in vitro and in vivo observations strongly implicate Leishmania-reactive DN T cells in contributing to optimal anti-Leishmania immunity in mice . Apart from lacking CD4 molecules , DN T cells display functional characteristics similar to CD4+ T cells ( MHC-II restriction , proliferation , IFN-γ production and parasite control ) . To further investigate how Leishmania-reactive DN T cells differ from CD4+ T cells , we compared the transcriptional profile of proliferating DN and CD4+ T cells following restimulation with L . major-infected BMDCs . Although most of the 84 mouse innate and adaptive immune genes showed similar pattern and level of expression in both cell types , some genes were preferentially upregulated or downregulated in DN T cells compared to CD4+ T cells ( Fig . 8A ) . The gene transcripts showing ≥ 2 folds difference in DN T cells were further analyzed and validated by quantitatively real-time PCR ( Fig 8B and C ) . Interestingly , most of the upregulated transcripts in DN T cells were genes associated with innate immune responses , including C3 , Mac-1 ( CD11b ) , myeloperoxidase ( Mpo ) , lysozyme , etc . In contrast , the downregulated transcripts ( relative to CD4+ T cells ) included genes associated with adaptive immunity , including CCR4 , Foxp3 , Gata-3 , etc . Collectively , these results suggest that despite mediating anti-Leishmania immunity ( akin to CD4+ T cells ) , Leishmania-reactive DN T cells are phenotypically distinct from conventional CD4+ T cells .
We show here that DN T cells proliferate and produce effector cytokines in secondary lymphoid organs of mice following primary and secondary L . major challenges . DN T cells from healed mice display functional characteristics of anti-Leishmania memory-like cells: they rapidly proliferate and produce effector cytokines ( TNF and IFN-γ ) in response to L . major challenge in vitro and in vivo and mediate infection-induced immunity ( rapid protection ) following adoptive transfer in vivo . Leishmania-reactive DN T cells express predominantly αβ TCR , are restricted by MHC class II molecules , lack immunoregulatory properties and display transcriptional profile distinct from conventional CD4+ T cells . To the best of our knowledge , this is the first extensive characterization and demonstration of the protective ability of Leishmania-reactive DN T cells in vitro and in vivo . It is generally believed that CD4+ T cells play a dominant role in anti-Leishmania immunity . However , the finding that CD4 deficient mice were resistant while MHC class II deficient mice were highly susceptible to L . major challenged this dogma [10] and suggests that MHC II-restricted CD4−CD8− T cells may be more important in regulating primary anti-Leishmania immunity . Indeed , several studies have reported the expansion of CD3+CD4−CD8− ( DN ) T cells in the blood of Leishmania-infected patients and dogs , and in spleens of Leishmania-infected mice [11] , [12] , [13] , [14] . These cells have been proposed to contribute to primary and vaccine-induced immunity although a concrete evidence implicating them in immunity has not yet been demonstrated . Our studies directly show the importance of Leishmania-reactive DN T cells in mediating optimal primary and secondary anti-Leishmania immunity in mice . The precise origin and development of peripheral DN T cells is not clearly understood and is controversial . Some reports suggest that DN T cells originate in the thymus by escaping negative selection [17] , [18] , [19] . In contrast , several reports suggest that DN T cells are generated in the periphery rather than in the thymus [19] , [20] , [21] , [22] . These cells comprise about 1–5% of total T cells in non-transgenic mice and in humans [11] , [23] making them difficult to isolate and subsequently study . TCR transgenic [24] or lpr ( Fas mutation ) mice [19] , [25] , which present increasing accumulation of DN T cells are widely used to investigate the function and developmental origin of DN T cells . DN T cells have been shown to influence long-term allograft survival [24] , [26] , [27] , prevent the development of autoimmune disease [28] , [29] , [30] , and contribute to control of intracellular pathogens [31] , [32] . In addition , DN T cells have been shown to possess immunoregulatory and alloreactive properties , inhibit autoreactive CD4+ T cells and mediate MHC I-restricted killing of allogenic target cells [20] , [24] , [25] . Our studies show that Leishmania-reactive DN T cells are restricted by MHC class II and may not have immunoregulatory properties because they failed to suppress CD4+ T cell proliferation in vitro ( Fig . 4D ) . Rather , a large percentage of proliferating DN T cells produced IFN-γ , TNF , IL-17 and GrzB , which is consistent with their effector functions as seen in other studies [11] , [12] , [29] . Previous studies that have reported the expansion and possible protective role of DN T cells in leishmaniasis focused mainly on primary Leishmania infection [11] , [12] , [13] , [14] . We extend these studies during secondary immunity by showing rapid expansion and effector functions ( cytokine production and parasite control ) by DN T cells following challenge infection . Healed mice had more proliferating and IFN-γ-producing DN T cells compared with naive mice following L . major challenge ( Fig . 2 ) , and adoptive transfer of DN T cells from healed ( but not naïve mice ) rapidly protected naïve mice against virulent L . major change . Moreover , DN T cells from healed mice expressed high levels of CD44 and majority of them were CD62LhiCD44hi , which are characteristics markers expressed by central memory-like cells . Collectively , these results suggest that DN T cells display functional characteristics of memory cells and contribute to optimal secondary immunity against L . major . How do DN T cells mediate their anti-Leishmania immunity ? We speculate that this may be related in part to their ability to produce IFN-γ and TNF , key cytokines that activate infected macrophages leading to intracellular parasite killing . Indeed , we found that Leishmania-reactive DN T cells in the spleens and lymph nodes are highly proliferative and produce IFN-γ , TNF and granzyme B . Importantly , we also found that DN T cells from immune mice were recruited to and proliferate at the infected footpads ( Fig . S7 ) . In addition , our in vitro co-culture experiments with infected BMDMs and highly enriched DN T cells show that suppression of parasite proliferation was associated with increased nitric oxide production , a key effector molecule that mediate destruction of parasites in infected cells . The findings that DN T cells mediate comparable ( or even superior ) protection against L . major in vitro and in vivo may challenge the dogma that CD4+ T cells are the major T cell subset that mediates anti-Leishmania immunity . Indeed , the proliferation of DN T cells was either comparable or sometimes higher than those of CD4+ T cells following in vitro or in vivo L . major challenge ( see Figs . 1–3 ) . Interestingly , although the percentage of IFN-γ-producing DN T cells was sometimes higher than those of CD4+ T cells , their MFI was significantly lower ( Fig . 1C ) , an observation that explain the relatively lower IFN-γ transcripts in DN compared to CD4+ T cells ( Fig . 8 ) . In addition , the numbers of Leishmania-reactive CD4+ T cells were quantitatively ( ∼ 3–4 fold ) higher than those of DN T cells . Thus , despite their superior proliferative response , DN T cells may still play a subordinate role to CD4+ T cells in vivo . Furthermore , it is conceivable that CD4+ T cells may be required for proper activation and effector functions of DN T cells . In line with this , we have observed that proliferation and IFN-γ production by highly enriched DN T cells is impaired in cultures devoid of immune CD4+ T cells in vitro and in vivo ( Fig . S8 ) . It is conceivable that DN T cells may assume increased roles in the absence of CD4+ T cells . For example , SIV infection in nonhuman primates does not result in immune dysfunction and progression to simian AIDS because DN T cells partially compensate for defective CD4+ T cell functions upon SIV-induced CD4+ T cell depletion in these animals [33] , [34] . Similarly , a strong DN T cell-mediated HIV Gag-specific response has been associated with seronegativity in HIV-exposed individuals [35] . It is interesting that the expression of genes associated with innate immune responses including C3 , were significantly higher in Leishmania-reactive DN T cells than in CD4+ T cells . While commonly associated with initiation of inflammation and critical molecule involved in first line of defense against pathogens , the complement proteins , particularly C3 and its degradation fragments are also known to prominently influence the adaptive immunity [36] , [37] . Recent studies have been shown that some subset of T cells express C3 and that its intracellular activation is not only required for homeostatic T cell survival [38] , but also in optimal Th1 induction and differentiation into effector cytokine ( particularly IFN-γ ) production [38] , [39] . It is conceivable that C3-expressing DN T cells in L . major-infected mice might be involved in IFN-γ production leading to effective macrophage activation , nitric oxide production and parasite killing . Collectively , our studies provide direct evidence for DN T cells in mediating anti-Leishmania immunity akin to CD4+ T cells . We propose that DN T cells complement CD4+ T cells to mediate efficient primary and secondary anti-Leishmania immunity in mice . In the absence of DN T cells , the induction of effective anti-Leishmania immunity may be either delayed or impaired . In a recent preliminary study , we observed impaired induction of DN T cells in spleens and draining lymph nodes of L . major-infected highly susceptible BALB/c mice . It would be interesting to determine whether the susceptibility of BALB/c mice to L . major infection is related in part to this impaired expansion of DN T cells . Collectively , our studies clearly identify DN T cells as important subset of T cells that contribute to optimal anti-Leishmania immunity .
All mice were kept at the University of Manitoba Central Animal Care Services ( CACS ) facility in accordance to the Canadian Council for Animal Care guidelines . The University of Manitoba Animal Use Ethics Committee approved all studies involving animals , including infection , humane endpoints , euthanasia and collection of samples . Six to 8 wk-old female C57BL/6 ( Thy1 . 2 ) mice were obtained from Charles River , St Constante PQ , Canada . Thy1 . 1 and MHC class II deficient ( MHC II KO ) C57BL/6 mice were purchased from The Jackson Laboratory ( Bar Harbor , ME ) . Female CD1d deficient C57BL/6 mice were kindly supplied by Dr . Xi Yang from a breeding colony maintained at the University of Manitoba Central Animal Care Services ( CACS ) Facility . Leishmania major parasites ( MHOM/80/Fredlin ) were grown in M199 culture medium ( Sigma , St . Louis , MO ) supplemented with 20% heat inactivated FBS ( HyClone , Logan , UT ) , 2 mM glutamine , 100 U/ml penicillin , and 100 µg/ml streptomycin . For infection , mice were injected with 2×106 ( primary infection ) or 5×106 ( secondary infection ) stationary-phase promastigotes in 50 µl PBS suspension into the right ( primary ) or left ( secondary ) hind footpad . Lesion sizes were monitored weekly by measuring footpad swelling with calipers . Parasite burden in the infected footpads was determined by limiting dilution assay . Parasite titers were determined from the highest dilution at which growth was visible . Bone marrow cells were isolated from the femur and tibia of naïve C57BL/c mice and differentiated into macrophages using complete medium supplemented with 30% L929 cell culture supernatant as previously described [40] . BMDCs were differentiated in petri dishes in the presence of rmGM-CSF ( 20 ng/ml; Peprotech , Rocky Hill , NJ ) . BMDMs and BMDCs were infected at a cell-to-parasite ratio of 1∶5 and after 6 hr , free parasites were washed away and infected BMDCs were used to stimulate purified CD3+ , CD4+ or DN T cells from naïve or healed mice in vitro . To assess the ability of CD4+ or DN T cells to control parasite proliferation , infected BMDMs were co-cultured with CD4+ or DN T cells and parasite proliferation in infected BMDMs was determined at different times by counting Giemsa-stained cytospin preparations under light microscope at ×100 ( oil immersion ) objective . Infected mice were sacrificed and spleens and dLNs were collected and made into single-cell suspensions . Cells were labeled with CFSE dye ( 1 . 5 mM; Molecular Probes , Eugene , OR ) and resuspended at a concentration of 2×106 cells per milliliter in RPMI 1640 supplemented with 10% heat-inactivated FBS , 100 U/ml penicillin , 100 µg/ml streptomycin , and 5×10−5 M 2-mercaptoethanol ( complete medium ) , plated with 100 µl per well in 96-well tissue culture plates , and stimulated with infected BMDCs ( BMDC: T cell = 1∶100 ) or soluble anti-CD3/CD28 mAb ( 1 µg/ml; BioLegend , San Diego , CA ) . After 5 days , proliferation and cytokine production were determined by flow cytometry . In some experiments , CFSE-labeled T cells from spleens and dLNs of infected mice were co-cultured with L . major-infected WT , MHC II KO , or CD1d KO BMDCs for 5 days , stimulated with PMA , BFA and ionomycin for 4–6 hr and proliferation , IFN-γ , TNF , IL-2 , IL-17 and GrzB expression by different T cell subsets were analyzed by flow cytometry . In some experiments , anti-MHC II antibodies were used to block MHC II-TCR interaction in vitro . Healed ( > 12 weeks post-infection ) Thy1 . 2 C57BL/6 mice were sacrificed and single-cell suspensions from the dLNs and spleens were made . T cells ( Thy1 . 2+ ) were enriched by positive selection using mouse CD90 . 2 ( Thy1 . 2 ) selection kit according to the manufacturer's protocols ( StemCell Technologies , Vancouver , BC ) . Enriched T cells ( > 98% purity ) were labeled with CFSE dye , and 107 cells were adoptively transferred into naive congenic ( Thy1 . 1 ) mice by tail vein injection . After 24 hr , the recipient mice were challenged with 5×106 L . major , sacrificed after 7 days and cell proliferation and IFN-γ expression by donor ( Thy1 . 2 ) cells in the dLNs and spleens were determined directly ex vivo . For in vitro co-culture experiments , DN ( CD3+CD4−CD8− ) and CD4+ T cells were purified from pooled spleens and dLNs of healed or naïve mice by cell sorting ( FACSAria III , BD Biosciences ) . For in vivo adoptive transfer studies , DN T cells were enriched using a combination of in vivo depletion and positive selection . Briefly , L . major-infected and healed mice ( > 12 weeks post-infection ) were first injected with 200 µl GK1 . 5 and TIB210 ascites ( i . p ) to deplete CD4+ and CD8+ cells . After 48 hr , DN T cells were purified using mouse CD90 . 2 selection kit ( StemCell Technologies , Vancouver , BC ) . Enriched DN T cells were > 99% negative for CD4 and CD8 expression and > 95% positive for CD3 by flow cytometry . To assess the numbers ( percentages ) and proliferation of DN T cells at the site of infection , CFSE-labeled whole T cells from L . major-infected Thy1 . 2 mice were adoptively transferred into naïve Thy1 . 1 mice that were then challenged with L . major . After 7 days , recipient mice were sacrificed and donor cells were recovered from the footpads as we previously described [41] . Briefly , the footpads were disinfected in 70% ethanol , the skins were peeled off and homogenized gently in PBS with tissue grinders . The crude homogenates were resuspended in 7 ml of cold PBS , carefully layered on top of 5 ml Ficoll and the infiltrating cells were separated by centrifugation according to the manufacturer's suggested protocols . The cells were collected , resuspended in 5 ml complete medium , counted , stained directly for expression of various cell surface markers and analyzed by flow cytometer by gating on Thy1 . 2+ donor cells . For reverse transcription-PCR ( RT-PCR ) , cells from spleens of healed mice were stained with fluorescent-conjugated anti-CD3 , anti-CD4 and anti-CD8 antibodies . CD4 , CD8 and DN T cells were sorted to high purity by gating on CD3+ cells . CD4 , CD8 and GAPDH gene expression in sorted cells were analyzed by RT-PCR . For PCR array , CFSE-labeled whole spleen cells from healed mice were stimulated with L . major-infected BMDCs for 5 days and proliferating ( CFSElo ) CD4+ and DN T cells were purified by cell sorting . Eighty-four innate and adaptive immune genes in CD4+ and DN T cells were analyzed with Mouse Innate & Adaptive Immune Responses PCR Array kit ( Qiagen , Frederick , MD ) . PCR array was performed by a real-time cycler ( Bio-Rad CFX96 ) and analyzed with web-based PCR Array Data Analysis Software ( Qiagen , Frederick , MD ) . To quantify gene expression levels , equal amounts of cDNA were mixed with SYBR Green PCR master mix ( Toyobo , Osaka , Japan ) and primers specific for the gene of interest ( Table S1 ) . 18S rRNA was amplified as an internal control . Naïve and healed mice were injected with 2 mg of BrdU i . p . per mouse and then challenged with 5×106 L . major in the next day . BrdU solution was prepared in sterile water , protected from light exposure , and changed daily . The night before the assay , mice were injected i . p . with 0 . 8 mg of BrdU in PBS . The next day , mice were sacrificed , spleens were harvested and BrdU staining was performed using BrdU Staining Kit according to the manufacturer's suggested protocol ( BD PharMingen ) . Healed mice were depleted of CD4 and/or CD8 T cells by injecting i . p . 200 µl ascites containing anti-CD4 ( GK1 . 5 ) or anti-CD8 ( TIB 210 ) mAb ( or both ) per mouse or depleted of total T cells by injecting i . p . 100 µg anti-Thy1 . 2 mAb ( TIB 107 ) per mouse , once a week , and then challenged with 5×106 L . major . Data are presented as means and standard error of mean ( SEM ) . Two-tailed Student's t-test or ANOVA were used to compare means and SEM between groups using GraphPad Prism software . Differences were considered significant at p<0 . 05 .
|
Although it is generally believed that CD4+ T cells mediate anti-Leishmania immunity , some studies suggest that CD3+CD4−CD8− ( double negative , DN ) T cells may play a more important role in regulating primary anti-Leishmania immunity . Here , we report that DN T cells extensively proliferate and produce effector cytokines in mice following primary and secondary L . major infections . Leishmania-reactive DN T cells utilize αβ T cell receptor ( TCR ) and are restricted by MHC class II molecules . Strikingly , DN T cells from healed mice display functional characteristics of protective anti-Leishmania memory-like cells: rapid and extensive proliferation , effector cytokine production in vitro and in vivo , and accelerated parasite control following secondary L . major challenge . These results directly identify DN T cells as important players in protective primary and secondary anti-L . major immunity in experimental cutaneous leishmaniasis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"and",
"health",
"sciences",
"biology",
"and",
"life",
"sciences",
"immunology",
"microbiology",
"parasitology"
] |
2014
|
MHC Class II Restricted Innate-Like Double Negative T Cells Contribute to Optimal Primary and Secondary Immunity to Leishmania major
|
The 2009 H1N1 pandemic ( H1N1pdm ) viruses have evolved to contain an E47K substitution in the HA2 subunit of the stalk region of the hemagglutinin ( HA ) protein . The biological significance of this single amino acid change was investigated by comparing A/California/7/2009 ( HA2-E47 ) with a later strain , A/Brisbane/10/2010 ( HA2-K47 ) . The E47K change was found to reduce the threshold pH for membrane fusion from 5 . 4 to 5 . 0 . An inter-monomer salt bridge between K47 in HA2 and E21 in HA1 , a neighboring highly conserved residue , which stabilized the trimer structure , was found to be responsible for the reduced threshold pH for fusion . The higher structural and acid stability of the HA trimer caused by the E47K change also conferred higher viral thermal stability and infectivity in ferrets , suggesting a fitness advantage for the E47K evolutionary change in humans . Our study indicated that the pH of HA fusion activation is an important factor for influenza virus replication and host adaptation . The identification of this genetic signature in the HA stalk region that influences vaccine virus thermal stability also has significant implications for influenza vaccine production .
The swine-origin H1N1 2009 influenza virus ( H1N1pdm ) caused an estimated 151 , 700 to 575 , 400 deaths worldwide during the first 12 months of the 2009 pandemic [1] , [2] , [3] . Children and young adults were most vulnerable to infection because they lacked pre-existing immunity to the H1N1pdm virus [4] . This virus continues to be the predominant circulating H1N1 virus in the human population and has been a component of the annual seasonal influenza vaccine since the 2010 season . Vaccination remains the most effective approach to prevent influenza virus infection . In response to the 2009 pandemic , a monovalent live attenuated influenza vaccine ( LAIV ) was produced and administered to millions of people . The LAIV is a 6∶2 reassortant virus that contains the six internal protein gene segments from the cold-adapted A/Ann Arbor/6/60 that confer the attenuation phenotype and the hemagglutinin ( HA ) and neuraminidase ( NA ) antigenic glycoprotein gene segments from A/California/7/2009 ( Cal/09 ) H1N1pdm virus . However , the development of the H1N1pdm LAIV presented significant challenges . First , Cal/09-like viruses grew poorly in embryonated chicken eggs , the substrate used for vaccine manufacturing . The vaccine yield was improved by the E119K and G186D ( H1 numbering ) changes in the HA1 head region of the HA [5] . Second , the HA protein of Cal/09 could not be cleaved by bromelain for HA protein preparation . The insensitivity to bromelain cleavage is due to the HA 373 and 374 residues ( HA2 position 46 and 47 ) in the HA stalk region [6] . Third , the Cal/09 LAIV has a shorter shelf-life at 4°C compared to the previous seasonal H1N1 vaccines , and the reason for this has yet to be determined . The HA protein is a trimeric , class I membrane protein with a membrane-proximal stalk region and a membrane-distal receptor binding head region . It initiates viral entry by binding to sialic acid-containing receptors on the host cell surface . The receptor binding specificity of the HA protein has been known to be the major determinant of viral host tropism , pathogenicity and human to human transmission [7] . The cleavage of the HA precursor HA0 to the disulfide bond-linked HA1 and HA2 subunits by proteases in the host is required for viral fusion and infectivity . After viral internalization by endocytosis , the low pH in the endosome triggers an irreversible structural change in the HA protein , allowing the viral envelope to fuse with the endosomal membrane to release the ribonucleoprotein core of the virion into the cytosol [8] . The threshold pH for fusion activation and acid stability differs among different subtypes and strains and has been recognized as an important factor in viral host restriction , stability , transmissibility and pathogenesis [3] , [9] , [10] , [11] , [12] , [13] . Recent surveillance data has revealed the emergence of a prominent mutation , E47K ( HA2 numbering ) in the HA2 stalk region of H1N1pdm isolates [14] , [15] , [16] , [17] . In this study , we compared two H1N1pdm viruses that differ at the HA2 position 47 of their HA proteins . We demonstrated that the HA2-47 residue determined the threshold pH of fusion . The inter-monomer interaction between HA2-47 and the residue at HA1 position 21 in the stalk region of the HA protein was identified as the structural basis for the different pH for fusion activation and thermal stability of H1N1pdm viruses . Furthermore , H1N1pdm viruses with HA2-K47 are more infectious in ferrets , underscoring the importance of the fusion activation pH of the HA protein for viral host adaptation and fitness .
The HA proteins of the original H1N1pdm strain A/California/7/2009 ( Cal/09 ) and a later strain A/Brisbane/10/2010 ( Bris/10 ) were evaluated for their membrane fusion activity by a transient expression assay . 293T cells were transfected with a dual-promoter expression plasmid expressing both GFP and HA . After 24 hours of transfection , the cells were treated with trypsin to allow HA cleavage , followed by incubation in various pH buffers ranging from pH 5 . 6 to 5 . 0 to trigger membrane fusion . In contrast to the cells expressing only GFP , the cells expressing both GFP and HA proteins underwent membrane fusion at pH 5 . 0 ( Figure 1A ) , which was apparent by the diffusion of the GFP signal . Cells transfected with the HA from Cal/09 and Bris/10 exhibited a 0 . 4 pH unit difference in the threshold pH at which fusion occurred . The fusion of the Cal/09 HA was triggered at pH 5 . 4 , while that of Bris/10 required pH 5 . 0 . The levels of HA expression ( 100% vs . 104% ) and the ratio of the cleaved HA1/HA2 proteins ( 39% vs . 46% ) after trypsin treatment were comparable between the Cal/09 and Bris/10 HA-transfected cells ( Figure 1B ) . The difference in the pH required for fusion between the HA proteins of the two H1N1pdm viruses was further confirmed using a viral fusion assay ( Figure 1C ) . Vero cells were infected with wild type ( wt ) Cal/09 or Bris/10 followed by a low pH treatment to trigger membrane fusion as measured by syncytia formation . Consistent with the transient expression assay , the Cal/09 virus exhibited a higher threshold pH for fusion ( pH 5 . 4 ) than the Bris/10 virus ( pH 5 . 0 ) . There are 6 amino acid differences between the HA proteins of Cal/09 and Bris/10 in the HA head and stalk region ( Figure 2A ) . Each of the Bris/10-specific residues were introduced into the corresponding position of the Cal/09 HA gene , and the threshold pH for fusion was determined by the HA/GFP co-expression fusion assay ( Table 1 ) . Only the substitution of the glutamic acid at HA2 position 47 to lysine ( Cal/09 HA2-E47K ) effectively lowered the threshold pH of the Cal/09 HA from 5 . 4 to 5 . 0 . Conversely , the HA2-K47E substitution in the HA of Bris/10 raised the threshold pH for fusion from 5 . 0 to 5 . 4 . These results indicate that HA2 residue 47 regulates the threshold pH for fusion in the H1N1pdm strains . Recombinant wt Cal/09 and Bris/10 that differed at the HA2-47 residue were generated and tested for their susceptibility to acid inactivation ( Figure 1D ) . Viral infectivity was kept at the starting titers ( approximately 6 . 0 log10 TCID50/mL ) in the pH range of 7 . 2 to 5 . 6 . In contrast , at pH 5 . 4 , the infectious viral titers of Cal/09 HA2-K47 mutant and wt Bris/10 with HA2-K47 were more than 3 . 0 logs higher than their counterparts containing HA2-E47 . By pH 5 . 0 , the infectivity of all viruses dropped to only 2 . 0 log10 TCID50/mL . The data demonstrated that the HA2-47 residue affected the threshold pH for fusion and the acid stability of the viruses . HA2 residue 47 is in the subunit interface of the HA trimer , which undergoes conformational changes during membrane fusion . It has been predicted that the HA2-E47K change introduces an inter-monomer salt bridge between the glutamic acid residue at HA1 position 21 ( E21 ) from one monomer to the HA2-K47 in another ( Figure 2 ) [17] , [18] , [19] . The HA1-E21 residue is highly conserved among the H1 subtype viruses , including Cal/09 and Bris/10 . We hypothesized that the inter-monomer interaction between HA1-E21 and HA2-K47 in the Bris/10 HA trimer , which is not found in the Cal/09 trimer due to the presence of HA2-E47 , results in a more acid-stable structure than that found in the Cal/09 trimer , such that a lower pH is required for the Bris/10 HA to undergo the conformational change required for viral infection compared to the Cal/09 HA . To confirm that the HA1-E21 and HA2-K47 inter-monomer interaction was critical for the threshold pH of fusion , an HA1-E21K change was introduced into the HA of Cal/09 ( Cal/09 HA1-E21K ) and Bris/10 ( Bris/10 HA1-E21K ) , and the threshold pH for fusion was determined by the HA/GFP co-expression fusion assay . As predicted , the HA1-E21K change in Cal/09 lowered the threshold pH for fusion from 5 . 4 to 5 . 0 , which can be explained by the introduction of the stabilizing salt bridge between HA1-K21 and HA2-E47 . Conversely , Bris/10 HA1-E21K , which eliminated the interaction between residues HA1-21 and HA2-47 in the Bris/10 HA , raised the threshold pH for fusion from 5 . 0 to 5 . 4 ( Figure 2 ) . These data provide direct evidence that the interaction between HA residues HA1-21 and HA2-47 stabilize the HA trimer structure , resulting in a lower pH for fusion . Cell lines that differ in their endosomal pH may support the replication of viruses with different pH thresholds for fusion differently . Vero cells have been reported to have a higher endosomal pH than MDCK cells [20] . To test the effect of viral fusion pH on virus growth , the growth kinetics of wt Bris/10 and wt Cal/09 viruses that differed at the HA2-47 residue were compared in Vero and MDCK cells ( Figure 3 ) . All viruses tested grew efficiently with similar kinetics in MDCK cells and reached similar peak titers ( Figure 3A and B ) . In contrast , the two viruses with the high threshold pH of fusion ( wt Cal/09 HA2-E47 and the Bris/10 HA2-E47 mutant virus ) achieved peak titer with faster kinetics in Vero cells than the corresponding viruses containing HA2-K47 ( Figure 3C and D ) . Remarkably , the Cal/09 virus with the single HA2-E47K mutation exhibited a greater defect in replication . No viral titers were detected until as late as 186 hpi . Thus , a higher endosomal pH in Vero cells may not be able to support the replication of viruses with a fusion pH threshold of 5 . 0 as efficiently as the one with a fusion pH threshold of 5 . 4 . Both low pH and high temperature treatment can induce an irreversible conformational change in the HA protein , resulting in the formation of an inactivated fusogenic structure [21] , [22] , [23] . To determine if the high threshold pH for fusion ( low acid stability ) correlates with the low thermal stability of the Cal/09 vaccine virus , aliquots of Cal/09 HA2-E47 and Cal/09 HA2-K47 were incubated at high temperatures , and the integrity of the HA protein was assessed by a hemagglutination assay . Following a 20-minute incubation at 47 . 5–65°C , both viruses retained HA titer after incubation at temperatures of up to 52 . 5°C ( Figure 4A ) . The Cal/09 HA2-E47 virus showed a precipitous drop in HA titer following the incubation at 55°C . In contrast , the Cal/09 HA2-K47 virus retained HA titer at 55°C , not showing a similar drop until 60°C , a temperature of 5°C higher than its HA2-E47 counterpart . Virus stability was then examined by holding the Cal/09 virus pair at 57 . 5°C over a time period of 240 min ( Figure 4B ) . Cal/09 HA2-K47 had a more gradual decline in HA titer over time compared to Cal/09 HA2-E47 , demonstrating that the Cal/09 HA2-E47 virus with lower acid stability also displayed lower thermal stability compared to the HA2-K47 counterpart . To investigate whether the HA2-47 residue affects the shelf-life of the Cal/09 vaccine in vaccine formulation , Cal/09 HA2-E47 and Cal/09 HA2-K47 vaccine viruses were purified and prepared in the vaccine buffer formulation with 1× SP-cGAG . The viruses were incubated at 26°C ( Figure 4C ) and 4°C ( Figure 4D ) , and the virus infectivity was measured at 3-day and 2-week intervals , respectively . The Cal/09 HA2-K47 vaccine virus maintained a higher titer over time than the Cal/09 HA2-E47 virus under both temperature conditions . The HA2-K47-containing virus was 130-fold more infectious when held at ambient temperature ( Figure 4C ) and 50-fold more infectious after more than 3 months at 4°C than the HA2-E47-containing virus ( Figure 4D ) . Taken together , these data show that the HA2-E47K mutation in Cal/09 conferred greater temperature stability across temperatures from 4°C to 57 . 5°C . The global emergence and increased prevalence of the HA2-E47K change in human H1N1pdm isolates have been reported [15] , [16] , [17] , [24] . To evaluate whether increased stability due to HA2-E47K conferred a fitness advantage to the H1N1pdm virus , ferret studies were carried out to compare the infectivity of the two pairs of H1N1pdm viruses: wt Cal/09 HA2-E47 and the Cal/09 HA2-K47 mutant; and wt Bris/10 HA2-K47 and the Bris/10 HA2-E47 mutant . Ferrets were inoculated with three doses of 10 , 100 or 1000 PFU of each virus . As shown in Table 2 , with high virus inputs ( 100 and 1000 PFU ) , nearly every animal became infected . All of the viruses were detected in the respiratory tissues , and the ferrets exhibited weight loss and fever ( data not shown ) . The GMT titers of the shed viruses were not significantly different between K47 and E47 viruses . In addition , the antibody titers induced by the viruses that differed at position HA2-47 were also comparable ( data not shown ) . Interestingly , animals infected with the Bris/10 pair shed virus at higher titers than animals infected with the Cal/09 pair , indicating that other HA residues different between Bris/10 and Cal/09 affected viral shedding . At the low dose of infection ( 10 PFU ) , both viruses with HA2-K47 were highly infectious in ferrets ( Cal/09 HA2-K47 mutant , 4/4 infected and wt the Bris/10 HA2-K47 , 6/7 infected ) . In contrast , the wt Cal/09 HA2-E47 virus infected only one of four ferrets at the 10 PFU dose . The Bris/10 HA2-E47 mutant virus did not infect any ferrets in study 1 ( N = 3 ) and infected two out of four ferrets in study 2 ( N = 4 ) . The FID50 of the wt Cal/09 HA2-E47 virus was calculated to be 17 . 8 PFU , approximately 5 times higher than the mutant Cal/09 HA2-K47 ( 3 . 2 PFU FID50 ) . Similarly , the FID50 of the wt Bris/10 HA2-K47 virus was calculated to be 4 . 4 PFU , 5 times lower than that of Bris/10 HA2-E47 ( 23 PFU FID50 ) . The differences among the FID50 data was significant based on the 95% confidence intervals using the Spearman-Karber method . Thus , the HA2-E47K change in recently circulating H1N1pdm viruses increased viral infectivity in ferrets .
The original A/California/7/09 ( Cal/09 ) -like H1N1pdm strains contained E47 in the HA2 stalk region . Since July 2009 , an E47K mutation emerged and rapidly became predominant worldwide . Our studies have demonstrated the importance of this residue for viral membrane fusion activity , acid and thermal stability and infectivity in vivo . The pH for fusion activation has been shown to regulate the virulence and transmission of influenza H5N1 viruses in ferrets and mice [11] , [13] . Our study on H1N1pdm supports the model that the pH of fusion activation is an important factor in determining viral fitness in humans . The HA2-47 residue is located in the helix region near the fusion peptide which undergoes a dramatic conformational change to form a coiled-coil structure during the low pH triggered membrane fusion . It mediates an electrostatic interaction to other residues in the HA trimer interface to maintain a structure required for membrane fusion [8] , [19] , [25] . The HA2 Q47R and Q47K changes in the H3 and H7 viruses , respectively , have been previously reported to affect virus fusion pH [26] . Structure modeling has suggested that a salt bridge between a highly conserved acidic residue HA1-E21 and the basic residue HA2-K47 , which is absent between HA1-E21 and HA2-E47 , would require higher protonation ( a lower pH ) for fusion to occur . We experimentally confirmed that the interaction between the residues HA1-21 and HA2-47 in the HA monomer interface regulates the pH of fusion activation for H1N1pdm viruses . High temperature at neutral pH can also induce a conformational change in the HA that was indistinguishable from the low pH-induced conformational change , in which the metastable prefusion HA changes to a fusogenic form leading to protein inactivation [21] , [22] , [23] . Thus , a higher threshold pH for fusion normally reflects a lower viral thermal stability . We showed that the viruses containing HA2-K47 exhibited higher stability after heat treatment or prolonged incubation at 26°C and 4°C compared to their HA2-E47 counterparts . It is noteworthy that each subtype of influenza viruses contains specific and highly conserved amino acids at positions HA1-21 and HA2-47 of the HA . It would be interesting to further explore the role of positions HA1-21 and HA2-47 in viral fusion activity in other influenza virus subtypes . The inter-monomer interaction between residue 21 in the HA1 region and residue 47 in the HA2 region identified in this study provides a structural explanation for the decreased thermal stability of the H1N1pdm vaccine viruses at 4°C , a challenge encountered during the 2009 H1N1 pandemic response . The H1N1pdm vaccine strain with the HA2-K47 residue is preferred as a vaccine candidate because of its prolonged shelf-life at 4°C . It has also been confirmed at MedImmune that the Bris/10 ( HA2-K47 ) monovalent LAIV has an improved shelf-life at 4°C compared to Cal/09 ( HA2-E47 ) ( data not shown ) . The HA2 residue 47 was also responsible for the poor cleavage of the Cal/09 HA by bromelain , an enzyme used to release the HA ectodomain from the viral envelope . Bris/10 with HA2-K47 can be efficiently cleaved by bromelain , while Cal/09 with HA2-E47 cannot [6] . Virus adaptation to different cell lines , host species or under the pressure of higher endosomal pH induced by the antiviral drug amantadine often lead to mutations in the HA that result in a change in the fusion pH [26] , [27] , [28] . Consistent with a previous report that a PR8 HA2 mutant with a higher HA fusion pH threshold of 5 . 4 grew better in Vero cells than the wt PR8 with a lower fusion pH threshold of 5 . 2 [20] , we observed a growth advantage forH1N1pdm viruses with HA2 E47 , which have a fusion pH threshold of 5 . 4 , in Vero cells . A more recent H1N1pdm isolate from 2012 containing K47 was also tested and found to have a similar growth defect in Vero cells ( data not shown ) . The engineering of HA with an optimal pH for fusion activation resulting in higher viral replication could be leveraged to improve virus yield for cell culture-based vaccine production . An optimal fusion pH is required for balancing viral acidic stability in the mildly acidic nasal tissue environment and fusion activation in the acidic endosome . Human influenza viruses have a lower fusion pH than their avian counterparts , indicating that the pH of fusion activation may influence viral transmission and establishment in new species [10] . Studies on H5N1 have highlighted the importance of the pH of fusion activation to host-specific replication and pathogenicity . Only a narrow pH range of 5 . 5–6 . 2 supports efficient and sustainable infection of H5N1 virus in ducks [29] , [30] . The pathogenicity of highly pathogenic avian influenza virus ( HPAI ) H5N1 in chickens was associated with a higher fusion pH compared to moderately pathogenic avian influenza ( MPAI ) H5N1 [9] . A K58I mutation in the HA2 of H5N1 that decreased the activation pH for fusion reduced viral pathogenicity in ducks , but increased the virulence and the infectivity and immunogenicity of an intranasal H5N1 vaccine virus in mice , showing the species specific impact of the fusion activation pH [13] , [29] , [31] , [32] . For avian H5N1 viruses to transmit among ferrets , sequence changes are required in both the HA head region to alter receptor binding specificity and the stalk region , in which a single residue change ( T318I ) near the fusion peptide lowers the pH for fusion and increases virus stability [11] . Therefore , in addition to the receptor binding preference conferred by the HA protein and viral replication capability attributed by the internal protein genes [33] , the pH of HA fusion activation is another important factor for influenza virus host tropism and transmission . A mouse-adapted H1N1 virus that acquires an HA2-W47G change was reported to lower both the fusion pH and lethal dose in mice [34] , [35] . The E47K change at the same HA2 position in the H1N1pdm viruses resulted in a similar biological phenotype for fusion activation pH and infectivity in ferrets . The H1N1pdm with K47 in HA2 is consistently both more acid stable in vitro and more infectious than viruses with E47 in ferrets , indicating that a highly acid stable virus is more fit in the acidic environment of the human respiratory tract . The FID50 value of H1N1pdm obtained herein is consistent with our previous study , in which we also showed that the H1N1pdm virus is more infectious than the previously circulating seasonal H1N1 virus [36] . A recent 2012 H1N1pdm strain was reported to have a lower fusion pH compared to Cal/09 [10] . These studies indicate that a lower fusion pH is often associated with adaptation to humans . The various challenges and lessons learned from the 2009 H1N1pdm will enable us to better understand cross-species virus adaptation from animal hosts to humans and rapidly respond to future pandemics .
The ferret studies were conducted in an AAALAC accredited facility under a specified protocol ( ACF-12-004 ) as approved by MedImmune's Institutional Animal Care and Use Committee ( IACUC ) . MedImmune is registered with the United States Department of Agriculture ( USDA ) and applies the standards for the institutional animal care and use program as outlined in the Guide for the Care and Use of Laboratory Animals ( Guide ) , Eighth Edition , National Research Council ( NRC ) , 2011 . Madin-Darby Canine Kidney ( MDCK ) cells , Vero cells and 293T cells were grown in Dulbecco modified Eagle medium ( DMEM ) containing 10% fetal bovine serum ( FBS ) . The recombinant influenza viruses used in this study were generated by plasmid rescue as previously described and propagated in 10- to 11-day-old embryonated chicken eggs [37] . The QuikChange® Site-directed Mutagenesis kit ( Agilent Technologies , Santa Clara , CA ) was used to introduce changes in the HA plasmids . Recombinant wild type ( wt ) A/California/7/2009 ( Cal/09 ) and wt A/Brisbane/10/2010 ( Bris/10 ) reassortants containing the Bris/10 HA and NA and the 6 internal protein gene segments of Cal/09 were made by reverse genetics . The 6∶2 reassortant vaccine viruses contain the corresponding wt HA and NA protein genes and the 6 internal protein genes from the A/AnnArbor/6/60 ( AA ca , H2N2 ) [5] , [37] . HA protein-mediated membrane fusion was assessed by transient expression in 293T cells . The Green Florescent Protein ( GFP ) and HA genes were cloned into each cloning site of a dual expression vector pVitro2-neo-mcs ( Invivogen , San Diego , CA ) . Point mutations were introduced into the HA by site-directed mutagenesis and confirmed by sequencing . The 293T cells were transfected with 1 µg of the HA/GFP plasmid using Lipofectamine 2000 ( Invitrogen , Grand Island , NY ) . Twenty-four hours post transfection , cells were carefully washed one time with PBS , followed by 10 min of treatment with a trypsin-like enzyme , TrypLE ( 1∶5 ) ( Gibco , Grand Island , NY ) , at 37°C to cleave the HA0 protein . The TrypLE was then inactivated by the addition of 10% FBS in PBS , and the transfected cells were incubated with different pH buffers ranging from 5 . 0 to 7 . 2 for 5 minutes and neutralized by the addition of DMEM/10% FBS . After incubating for 2 hours , the fused cells were monitored by GFP fluorescence using the Nikon Eclipse Ti microscope . The expression of the HA protein in transfected 293T cells was examined by Western Blot using influenza-specific antibodies . Band density was quantitated using the ImageQuant LAS 4000 Luminescent Image Analyzer ( GE Healthcare ) . The formation of syncytia after viral infection was evaluated by infecting monolayers of Vero cells with a multiplicity of infection ( MOI ) of 4 . 0 at 37°C for 14 hours . The infected cells were treated with PBS/TrypLE and exposed to buffers of different pH as described above . The cells were stained with the Hema-3-Stat kit ( Fisher , Pittsburg , PA ) , and syncytia formation was examined by a light microscope . The acid stability of the viruses was measured by determining viral infectivity after acid treatment . Viruses were initially diluted 10-fold in PBS . The pH of the diluted viruses was lowered by careful , dropwise addition with 0 . 1M Citric Acid until the desired pH was reached . The viruses were then incubated at 37°C for 1 hour . The titers of acid treated viruses were determined by TCID50 assay in MDCK cells . Cells were infected with each virus at an MOI of 0 . 004 for 1 hour , washed twice with PBS and then incubated at 37°C for 4 days in minimum essential medium ( MEM ) containing 1∶40 TrypLE . The culture supernatants were collected daily , and the virus was titrated by 50% tissue culture infectious dose ( TCID50 ) in MDCK cells . The heat stability of the HA protein was measured by determining the loss of the hemagglutination ( HA ) titer after incubating the viruses at temperatures between 50°C and 65°C for 0 to 240 min . The HA titer was measured pre- and post-incubation . The evaluation of viral stability at room temperature ( 26°C for 35 days ) and 4°C ( 14 weeks ) was conducted with the sucrose purified virus in the vaccine virus formulation buffer , 1× SP-cGAG ( Sucrose-Phosphate+1% concentrated Gelatin-Arginine-Glutamate ) . Duplicate aliquots were removed at various time-points and stored at −80°C prior to viral titration by TCID50 assay in MDCK cells . The infectivity of the H1N1pdm wt virus was determined using 9- to 12-week-old male and female ferrets from Simonsen Laboratories ( Gilroy , CA ) . The ferrets were individually housed and inoculated with PBS or 10 , 100 , or 1000 plaque forming units ( PFU ) of the indicated viruses intranasally . The body weight and temperature of the ferrets were monitored and nasal washes were collected daily . On day 3 after infection , the ferrets were euthanized and the nasal turbinates ( NT ) and lungs were harvested . The virus titer in the nasal washes , lungs and NT was determined by the TCID50 assay in MDCK cells and expressed as log10TCID50/gram of tissue . The ferret 50 percent infectious dose ( FID50 ) was calculated by the Spearman-Karber method .
|
Influenza viruses cause seasonal epidemics and occasional pandemics , representing a threat to public health . The trimeric hemagglutinin ( HA ) surface glycoprotein mediates viral entry and plays important roles in viral host restriction , transmission and pathogenesis . The HA protein binds to the receptor on the cell via the head region , and mediates the low pH-triggered viral and cellular membrane fusion via the stalk region . The 2009 H1N1 pandemic ( H1N1pm ) viruses have been circulating in humans since 2009 . A single amino acid change was found in the stalk region of recent H1N1pdm strains . In this study , we revealed that this amino acid change , by stabilizing the trimer structure , lowered the pH for fusion and exhibited a higher acid stability . Accordingly , the H1N1pdm with this change showed higher thermal stability after high temperature treatment . Furthermore , the H1N1pdm with this change had higher infectivity in ferrets , suggesting that recent H1N1pdm viruses have evolved to be more adapted in humans . Our data not only indicate the importance of the fusion activation pH to viral replication and host adaptation , but also provide solutions to improve the shelf-life of live vaccines in vaccine manufacture .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2014
|
A Single Amino Acid in the Stalk Region of the H1N1pdm Influenza Virus HA Protein Affects Viral Fusion, Stability and Infectivity
|
Chromosomal translocations between loci encoding MALT1 and c-IAP2 are common in MALT lymphomas . The resulting fusion proteins lack the c-IAP2 RING domain , the region responsible for its ubiquitin protein ligase ( E3 ) activity . Ectopic expression of the fusion protein activates the canonical NF-κB signaling cascade , but how it does so is controversial and how it promotes MALT lymphoma is unknown . Considering recent reports implicating c-IAP1 and c-IAP2 E3 activity in repression of non-canonical NF-κB signaling , we asked if the c-IAP2/MALT fusion protein can initiate non-canonical NF-κB activation . Here we show that in addition to canonical activation , the fusion protein stabilizes NIK and activates non-canonical NF-κB . Canonical but not non-canonical activation depended on MALT1 paracaspase activity , and expression of E3-inactive c-IAP2 activated non-canonical NF-κB . Mice in which endogenous c-IAP2 was replaced with an E3-inactive mutant accumulated abnormal B cells with elevated non-canonical NF-κB and had increased numbers of B cells with a marginal zone phenotype , gut-associated lymphoid hyperplasia , and other features of MALT lymphoma . Thus , the c-IAP2/MALT1 fusion protein activates NF-κB by two distinct mechanisms , and loss of c-IAP2 E3 activity in vivo is sufficient to induce abnormalities common to MALT lymphoma .
The defining characteristic of the IAP ( Inhibitor of Apoptosis ) gene family is the presence of one or more baculovirus IAP repeats ( BIRs ) ( reviewed in [1] ) . These ∼70 amino acid regions mediate protein-protein interactions , and in the context of adjacent sequences are responsible for the association of certain IAP family members with caspases . There are eight mammalian IAPs . Some IAPs also contain a RING motif that confers ubiquitin protein ligase ( E3 ) activity . c-IAP1 and c-IAP2 are such RING-containing proteins that bind caspase-7 or -9 but , unlike XIAP , do not inhibit their enzymatic activities [2] . c-IAP1 and c-IAP2 also bind the adaptor protein TNF Receptor Associated Factor 2 ( TRAF2 ) and are components of the Tumor Necrosis Factor Receptor 1 ( TNF-R1 ) and 2 signaling complexes [3] . Upon TNF-R2 occupancy , c-IAP1 , but not c-IAP2 , ubiquitinates TRAF2 and the mitogen activated protein ( MAP ) kinase kinase kinase ASK1 , resulting in the proteasomal degradation of all three proteins , cessation of MAPK signaling , and an increased susceptibility to cell death [4]–[6] . An emerging body of evidence has implicated the c-IAPs in regulating the activation of the transcription factor NF-κB . NF-κB can be activated by two distinct signaling mechanisms ( reviewed in [7] , [8] ) . The most common ( the canonical pathway ) depends on IκB kinase ( IKK ) β-mediated phosphorylation of inhibitory IκB proteins , leading to their ubiquitination and degradation . This frees cytosolic NF-κB heterodimers to translocate to the nucleus and regulate gene transcription . The second activating mechanism ( the non-canonical pathway ) is downstream of a limited number of receptors , including CD40 , lymphotoxin β receptor , and BAFF receptors , and involves the proteolytic removal of carboxy-terminal ankyrin motifs in the NF-κB protein p100 to yield p52 [9] , [10] . p52/Rel B-dimers translocate to the nucleus and regulate gene transcription [11] . Processing of p100 to p52 is dependent on the sequential activation of the upstream kinases NIK ( NF-κB-inducing kinase ) and IKKα [12]–[14] . Transient overexpression of c-IAP2 in cells has been shown to induce the ubiquitination and degradation of IκB , the essential antigen receptor NF-κB signaling intermediate Bcl-10 , and NIK [15]–[18] . Overexpression of c-IAP1 induced the ubiquitination and degradation of TRAF2 and NIK , and its knockdown with silencing RNA impaired TNFα-induced NF-κB activation [4] , [18]–[20] . Despite the ( mostly in vitro ) evidence for c-IAP regulation of NF-κB , primary cells from c-IAP1 and c-IAP2 knockout mice showed no obvious abnormalities in NF-κB activation [21] , [22] . However , studies using synthetic “Smac mimetics” that induce the proteasomal degradation of c-IAP1 and c-IAP2 , or siRNA to knock down the remaining c-IAP molecule expressed in cells from c-IAP1- and c-IAP2-deficient mice , have suggested that these two proteins may work redundantly to promote TNF-α-induced NF-κB activation and inhibit spontaneous non-canonical NF-κB activation [18] , [20] , [23]–[25] . Binding of c-IAPs to TRAF2 brings them into proximity with TRAF3-associated NIK . The result is a repressive complex that causes ubiquitination and degradation of NIK and maintains non-canonical NF-κB signaling in a basal state [3] , [26] , [27] . Consistent with this , tandem deletions of the c-IAPs have been associated with increased non-canonical NF-κB signaling and the development of multiple myeloma [28] , [29] , and conditional deletion of TRAF2 and TRAF3 results in stabilization of NIK , increased non-canonical signaling , and B cell hyperplasia [30]–[33] . MALT ( mucosal associated lymphoid tissue ) lymphomas are indolent neoplasms that have cytological features and bear cell surface markers of marginal zone B cells , and typically invade epithelial organs such as the gut and lung [34]–[36] . The molecular events that contribute to MALT lymphomagenesis are not well understood , but it is thought to involve the constitutive activation of NF-κB [37] . A variety of chromosomal abnormalities are associated with this disease; the most prevalent is a translocation , t ( 11;18 ) ( q21;q21 ) , that results in the production of a fusion protein containing the NH2-terminal ( BIR-containing ) fragment of c-IAP2 and the COOH-terminal portion of MALT1 , a paracaspase involved in antigen receptor signaling [38]–[40] . Ectopic expression of this fusion protein in cell lines activates NF-κB [41] , and transgenic overexpression in mice results in an increase in marginal zone B cells [42] . It is thought that the fusion protein activates NF-κB via the canonical signaling pathway [43]–[46] . The relevance of the different domains in the c-IAP2/MALT1 fusion protein to the development of MALT lymphoma has not been addressed . Here we investigate the mechanism by which the c-IAP2/MALT1 fusion protein contributes to the development of MALT lymphoma . Ectopic expression of the fusion protein in cell lines activated both the canonical and non-canonical NF-κB signaling pathways , the former but not the latter being dependent on the MALT1 paracaspase activity . Expression of a mutant c-IAP2 that , like the c-IAP2 portion of the fusion protein , lacks E3 activity activated non-canonical but not canonical NF-κB . Knockin mice expressing this same c-IAP2 mutant in lieu of the wild type gene accumulated abnormal B-cells that had elevated non-canonical but not canonical NF-κB signaling , a cell-autonomous survival advantage in vivo , and other features of MALT lymphomas . The many points of similarity between mice expressing a c-IAP2 E3-inactive mutant and patients expressing a c-IAP2 E3-inactive MALT1 fusion protein suggests that the loss of this activity activates non-canonical NF-κB and predisposes to malignancy .
Ectopic expression of the c-IAP2/MALT1 fusion protein causes p65 to translocate to the nucleus , evidence of canonical NF-κB activation [43] . We assessed the mechanism of NF-κB induction in 293T cells transfected with the fusion protein ( Figure 1A and 1B ) . Expression of the c-IAP2/MALT1 fusion protein induced IκB phosphorylation , as did a constitutively active form of IKKβ ( IKKβ-CA ) . Unlike IKKβ-CA , however , c-IAP2/MALT1 resulted in little if any IκB degradation , suggesting that it is a much less potent activator of canonical signaling . Notably , the c-IAP2/MALT1 fusion protein , but not IKKβ-CA , also increased the levels of NIK and p52 , hallmarks of non-canonical signaling . Expression of MALT1 did not induce IκB phosphorylation or degradation , or increase NIK or p52 . Therefore , the fusion protein can trigger both arms of the NF-κB signaling cascade . The MALT1 portion of the c-IAP2/MALT1 fusion protein has paracaspase activity , and it has been shown that expression of an inactivating mutation resulted in approximately 2-fold less NF-κB reporter activity than the paracaspase-active form [47] . We compared NF-κB activation in 293T cells transfected with the native sequence or paracaspase-inactive ( c-IAP2/MALT1C464A ) c-IAP2/MALT1 cDNA ( Figure 1C ) . The canonical pathway , as judged by IκB phosphorylation , was markedly reduced by the mutation , but increases in the non-canonical pathway components NIK and p52 were unaffected . The fusion protein lacks the c-IAP2 RING domain and therefore its E3 activity , and c-IAPs have been shown to ubiquitinate NIK and repress non-canonical NF-κB signaling [18] , [26] , [27] . In fact , expression of c-IAP2 lacking its c-terminal half , as occurs in c-IAP2/MALT1 fusion proteins , increased both NIK and p52 levels ( Figure S1 ) . To ask if this was due specifically to the loss of E3 activity , we expressed c-IAP2 in which a RING histidine that is critical for E3 activity was replaced by alanine ( c-IAP2H574A ) , but the protein was otherwise intact ( Figure 1A ) [48] , [49] . Expression of c-IAP2H574A induced little if any IκB phosphorylation but increased NIK and p52 levels ( Figures 1D and S1 ) . These results show that the c-IAP2/MALT1 fusion protein activates both the canonical and non-canonical NF-κB signaling cascades and that there are two distinct mechanisms . The finding that expression of E3-defective c-IAP2 ( Figure 1D ) but not MALT1 ( Figure 1B ) activated non-canonical NF-κB raised the possibility that a similar mechanism might account for non-canonical NF-κB activation by the c-IAP2/MALT1 fusion protein . To investigate the consequences of expressing c-IAP2 lacking E3 activity in vivo , we generated gene-targeted knockin mice that express an E3-inactive mutant of c-IAP2 ( c-IAP2H570A ) under the control of the native regulatory regions ( Figure 2A ) . ES cells that had integrated the targeting vector were used to generate chimeric mice that were crossed to the C57BL/6 background . The presence of the H570A substitution in F1 offspring and subsequent generations was assessed by long-template PCR followed by Spe 1 restriction endonuclease digestion . The expected fragment sizes generated from the wild type allele are 4 . 9 and 0 . 7 kb , and those from the c-IAP2H570A allele are 4 . 3 and 0 . 6 kb ( Figure S2 and Figure 2B ) . Acquisition of the mutant allele in c-IAP2+/H570A and c-IAP2H570A/H570A mice caused the appearance of shorter fragments in a gene dose-dependent manner . Mutation of the Zn2+-coordinating histidine in the c-IAP1 , c-IAP2 , and XIAP RING domains [48] , [49] prevents autoubiquitination and results in increased protein levels in cells transiently expressing the corresponding cDNAs . Furthermore , under physiologic conditions c-IAP1 downregulates c-IAP2 protein levels by trans-ubiquitination and proteasomal degradation [21]; there does not seem to be a reciprocal regulation of c-IAP1 by c-IAP2 [22] . To determine how c-IAP2 E3 activity might affect c-IAP levels , splenocyte lysates were immunoblotted with an antiserum that recognizes both c-IAP2 and c-IAP1 ( Figure 2C ) [50] . The antibody detected a doublet in wild type cells , the upper and fainter band being c-IAP2 and the lower and more prominent being c-IAP1 [21] . There was a marked increase in c-IAP2 expression in c-IAP2+/H570A cells and an even greater increase in c-IAP2H570A/H570A cells . In contrast , there was only a small increase in the level of c-IAP1 . We compared the susceptibility of wild type c-IAP2 and the RING-less c-IAP2/MALT1 fusion protein to ubiquitination-dependent degradation . Consistent with a previous report [51] , only levels of c-IAP2 increased in response to proteasome inhibition , indicating that the lack of E3 activity also stabilizes the fusion protein ( Figure S3 ) . Given that c-IAP2 expression is also regulated by c-IAP1-mediated ubiquitination [21] , these results indicate that the combined activity of the c-IAPs is required to maintain c-IAP2 at physiologic levels . Homozygous c-IAP2 knockin mice were viable , fertile , and displayed no obvious phenotypic abnormalities . Analysis of peripheral lymphoid organs in 6–7-month-old c-IAP2H570A/H570A mice , however , revealed a number of abnormalities . Unlike the spleen , cell numbers of pooled peripheral lymph nodes ( axial , brachial , superficial cervical , and inguinal ) as well as mesenteric lymph nodes were markedly increased ( Figure 3G , A , and D ) . There was a reduction in the percentage of T cells with a corresponding increase in the percentage of B ( B220+ ) cells ( Figure 3B , E , and H ) . The result was approximately a 5-fold and 4-fold increase in the absolute number of pooled and mesenteric lymph node B cells , respectively , and a smaller ( 2-fold ) increase in T cell number ( Figure 3C and F ) . The CD4+∶CD8+ T cell ratio in c-IAP2H570A/H570A mice was normal ( unpublished data ) . c-IAP2H570A/H570A lymphocytes had an unactivated phenotype , with normal levels of B7 . 1 and I-Ab ( B cells ) and CD25 and CD69 ( T cells ) ( unpublished data ) . Two- to three-month-old c-IAP2H570A/H570A mice also had increases in lymph node B cells , although to a lesser extent than older animals ( Figure S4 ) . Analysis of B and T cell precursors in bone marrow and thymus , respectively , revealed no abnormalities . Among splenic B cells there was reproducibly an approximately 3-fold increase in the percentage of cells with a marginal zone phenotype ( CD21hiCD23− ) , with a compensatory decrease in the percentage of follicular ( CD21intCD23hi ) and immature ( CD21−CD23− ) B cells ( Figure 3J ) . Although lymph nodes normally have few B cells with a marginal zone phenotype [52] , there was a small increase in these cells in c-IAP2H570A/H570A lymph nodes . Circulating IgA was increased approximately 3-fold in c-IAP2H570A/H570A mice , and there were highly statistically significant increases in IgM and IgG3 , and a reduction in IgG1 as well ( Figure 4 ) . No statistically significant changes were found in IgG2b and IgE levels . B cell hyperplasia , particularly of marginal zone B cells , in gut-associated lymphoid tissue ( GALT ) and lung is a feature of MALT lymphomas [34] , [36] . Gross examination revealed that c-IAP2H570A/H570A mice had enlarged GALT and mesenteric lymph nodes , which was confirmed by histological evaluation ( Figure 5A ) . There were also mild to moderate lymphocytic infiltrates in the lung ( Figure 5B ) , with no evidence of neoplasia in either organ . Despite the increased size of the GALT in c-IAP2H570A/H570A mice , immunohistochemistry and flow cytometric analysis of both wild type and c-IAP2H570A/H570A GALT revealed primarily B cells with a follicular phenotype ( Figure 5C and 5D ) , organized T-cell-enriched areas ( compare Figure 5C with Figure S5 ) , and no evidence of cellular activation ( unpublished data ) . The lymphocytic infiltrates in the lungs of the c-IAP2 knockin mice also consisted of B cells and T cells ( unpublished data ) . Taken together , these results demonstrate that mice with catalytically inactive c-IAP2 acquire a lymphoid phenotype that shares many features with MALT lymphomas . The increase in B cell numbers in vivo could be due to decreased death , increased expansion , or a combination . Susceptibility to cell death was determined by culturing splenocytes in the absence of growth or survival factors and quantifying cell viability of B220+ and TCRβ+ cells by measuring 7-AAD incorporation ( Figure 6A ) . c-IAP2 knockin B cells died more slowly than wild type cells , with 10%–15% still viable even after 64 h , compared to 3% for wild type cells . Addition of BAFF or agonistic anti-CD40 partially rescued the survival of B cells of both genotypes with similar dose-response curves ( Figure 6B and unpublished data ) . There was no difference between the genotypes with regard to T cell survival ( Figure 6A ) . Proliferative ability was addressed by stimulating purified B cells with anti-μ F ( ab′ ) 2 or lipopolysaccharide ( LPS ) and measuring 3H-thymidine incorporation ( Figure 6C ) . c-IAP2H570A/H570A B cells had enhanced responses to both stimuli , with approximately a 3-fold shift in the dose response curve toward lesser concentrations of stimulus compared to wild type cells . During the course of the proliferation assays there were no differences between the two genotypes with regard to cell death ( unpublished data ) . To determine if these in vitro observations correspond to B cell behavior in vivo , experiments were performed in which a mixture of wild type and c-IAP2 knockin splenic B cells was adoptively transferred into RAG2-deficient mice ( Figure 6D ) . Although equal numbers of cells of each genotype were injected , after 45 d a 3-fold ( lymph node ) to 5-fold ( spleen ) preponderance of c-IAP2 knockin B cells was observed . These results show that the absence of c-IAP2 E3 activity in B cells results in a cell-intrinsic abnormality that increases their capacity to survive and/or proliferate in vitro and in vivo . Ectopic expression of a c-IAP2/MALT1 fusion protein spontaneously activates NF-κB , as does depletion of c-IAPs with Smac mimetics or silencing siRNAs [18] , [25] , [26] , [38] , [41] , [53] , [54] . We therefore asked if selective loss of c-IAP2 E3 activity , in an otherwise physiological setting , affects NF-κB . Quantitative RT-PCR found that transcripts for NF-κB-responsive genes encoding GADD45β , IκB , c-IAP2 , and ferritin heavy chain were elevated in c-IAP2H570A/H570A B cells ( Figure 7A ) [15] , [55]–[57] . There was no increase , however , in the expression of Bcl-2 , a gene product that has been reported to increase in response to canonical but not non-canonical NF-κB activation [58] , [59] , raising the possibility that NF-κB activation in c-IAP2H570A/H570A B cells was pathway-specific . Activation of the canonical pathway was assessed by measuring IκB levels and its state of phosphorylation . IκB levels were similar to or perhaps slightly increased in c-IAP2H570A/H570A B cells ( Figure 7B ) and murine embryonic fibroblasts ( MEFs ) ( Figure 7C ) compared to wild type cells . More importantly , there was no increase in spontaneously phosphorylated IκB in c-IAP2H570A/H570 cells , arguing against spontaneous canonical NF-κB activation . In contrast , the levels of both NIK and p52 were elevated in knockin B cells ( Figure 7D ) and MEFs ( Figure 7E ) . The levels of TRAF2 and TRAF3 , two components of a c-IAP-containing inhibitory complex thought to degrade NIK [26] , [27] , were unaffected by the loss of c-IAP2 E3 activity ( unpublished data ) . In T cells , the amount of NIK was lower in wild type T than wild type B cells , and there was little increase in T cells expressing E3-inactive c-IAP2 ( Figure 7D ) . There was correspondingly little increase in p52 , although a small amount was detected in c-IAP2H570A/H570A T cells . Together , these results indicate the E3 activity of c-IAP2 is required to inhibit constitutive non-canonical NF-κB activation in B cells , MEFs , and to a much lesser degree , T cells . Although the E3 activity of c-IAP2 is absent in both c-IAP2−/− and c-IAP2H570A/H570A cells , only the latter has increased spontaneous NF-κB activation . Because c-IAP1 also binds TRAF2 , which is essential for c-IAP-mediated repression of the non-canonical signaling cascade [26] , the results are consistent with the possibility that the E3-defective c-IAP2 competes with endogenous c-IAP1 . In fact , c-IAP2H570A/H570A is able to bind TRAF2 at least as well as the wild type protein ( Figure S6 ) . To ask if the c-IAP2 RING mutant interfered with endogenous c-IAP1 , c-IAP2-specific siRNA was used to knock down c-IAP2 in wild type and c-IAP2 knockin MEFs ( Figure 7F ) . As seen in splenocytes ( Figure 2C ) , there was a large increase in c-IAP2 and a small increase in c-IAP1 levels in c-IAP2 knockin MEFs ( Lanes 1 and 3 ) . Transfection of wild type MEFs with c-IAP2 siRNA specifically reduced c-IAP2 but had little if any effect on the levels of p52 . In contrast , knockdown of c-IAP2 in c-IAP2H570A/H570A MEFs resulted in a substantial reduction of p52 levels . To determine if c-IAP2H570A interferes with c-IAP1-mediated ubiquitination/degradation of NIK , 293T cells were co-transfected with NIK and c-IAP1 , with or without c-IAP2H570A ( Figure 7G ) . Consistent with previous reports [18] , [26] , expression of c-IAP1 reduced NIK to undetectable levels; this was prevented by co-expression of E3-inactive c-IAP2 . Thus , the E3-defective c-IAP2H570A can inhibit constitutive c-IAP1-mediated ubiquitination/degradation of NIK and de-repress the non-canonical signaling cascade .
Unmanipulated mice deficient for c-IAP1 and c-IAP2 have no obvious phenotypic abnormalities [21] , [22] , which has made it difficult to ascribe a physiologic role to these proteins in vivo . Recent studies have suggested that redundancy among the c-IAPs , at least with regard to NF-κB activation , could account for the lack of apparent abnormalities [18] , [25] , [26] . If so , this could be an even bigger factor in c-IAP1 knockout mice , in which c-IAP2 levels are elevated because it is no longer ubiquitinated by c-IAP1 and targeted for degradation [21] . c-IAP1 is not elevated in cells from c-IAP2-deficient mice [22] , suggesting that even normal c-IAP1 levels are sufficient to compensate for the loss of c-IAP2 . In contrast to the c-IAP2 knockout animals , we have found that substitution of wild type c-IAP2 with an E3-defective point mutation does result in constitutive NF-κB activation and abnormal B cell accumulation . This is likely because the endogenous c-IAP1 is unable to compensate for the lack of c-IAP2 E3 activity . The N-terminal BIR-containing region of both proteins binds to TRAF2 , a prerequisite for c-IAP-mediated NIK ubiquitination [18] , [26] . Furthermore , only one c-IAP molecule can bind one TRAF2 trimer at a time [60] . We found that overexpressed c-IAP2H570A/H570A interferes with c-IAP1-mediated degradation of NIK and that knockdown of the c-IAP2 mutant restored repression of non-canonical NF-κB . These data argue that the mutant c-IAP2 prevented c-IAP1 from associating with the repressive complex . The c-IAP2H570A/H570A mice therefore represent an example in which replacement of the endogenous gene with an inactive form , but not a complete knockout , can reveal normal function . Abnormal B cell expansion has been observed in a number of animal models in which NF-κB activity is chronically elevated . For example , overexpression of B cell activating factor ( BAFF ) or NIK , both of which lead to non-canonical NF-κB activation , results in B cell hyperplasia with increased numbers of CD23loCD21hi B cells [59] , [61] . Similarly , mice lacking either TRAF2 or TRAF3 in B cells have elevated non-canonical NF-κB , an expanded B cell compartment , increased numbers of cells with a marginal zone phenotype , and elevated serum immunoglobulins [31]–[33] . TRAF2 and TRAF3 are adaptor molecules downstream of BAFF receptors that constitutively form a complex with c-IAP1 , c-IAP2 , and NIK [26] , [27] . These associations result in c-IAP-dependent ubiquitination of NIK and its proteasomal degradation , which is thought to maintain the non-canonical NF-κB activation pathway in a basal state . Although we found no alterations in expression of TRAF2 and TRAF3 in c-IAP2H570A/H570A mice , NIK levels and NF-κB activity were increased , and the mice developed age-dependent B cell hyperplasia in a manner similar to BAFF and NIK transgenic mice , or TRAF2 and TRAF3 knockout mice [31]–[33] , [59] , [61] . The data are all consistent with the notion that basal ubiquitination of NIK by c-IAP2 is an important mechanism for regulating constitutive NF-κB activity and B cell homeostasis . It is widely believed that the c-IAP2/MALT1 protein is pathogenic because it activates the canonical NF-κB signaling pathway [37] . A variety of mechanisms have been suggested , including proteolytic cleavage of A20 , a negative regulator of NF-κB activation , ubiquitination of NEMO , binding of the fusion protein to lysine 63-linked polyubiquitinated NEMO , and the failure of the fusion protein to degrade Bcl-10 [37] . However , a potential role for non-canonical NF-κB activation has not been explored . We have found that the c-IAP2/MALT1 fusion protein activates both canonical and non-canonical signaling pathways , and activation of the latter in mice is sufficient to promote the development of features common to MALT lymphoma . Our results are in agreement with a report that overexpression of the fusion protein in 3T3 cells resulted in an NF-κB complex that was supershifted with antibodies to RelB [62] . Interestingly , introduction of a Bcl-10 transgene , which mimics the MALT lymphoma-associated t ( 1;12 ) ( p22;q32 ) chromosomal translocation that deregulates Bcl-10 , results in marginal zone B cell hyperplasia and elevated non-canonical as well as canonical NF-κB signaling [63] . It is noteworthy that mice lacking the COOH-terminal ankyrin domain of p100 , which results in constitutive activation of p52 , develop B cell hyperplasia and enlarged GALT . Thus , activation of the non-canonical pathway may be a major contributor to the development of MALT lymphoma . The development of MALT lymphoma-like abnormalities in the c-IAP2 E3-defective mice raises a cautionary note that drugs that reduce c-IAP levels , such as SMAC mimetics , may have unintended side effects due to activation of non-canonical NF-κB signaling , especially if administered chronically .
RAG2-deficient and CD45 . 1 congenic mice were obtained from the Jackson Laboratory . All restriction endonucleases were obtained from New England Biolabs . pCMV9 containing carboxy-terminal myc-tagged human NIK cDNA was obtained from Nobuhiko Kayagaki and Vishva Dixit ( Genentech ) and pRK5 containing Flag-tagged human c-IAP2 and c-IAP2/MALT1 was obtained from Xiaolu Yang ( University of Pennsylvania ) . pRK5-Flag-tagged human c-IAP2H574A and pRK5-Flag-tagged human c-IAP2/MALT1C464A were generated by site directed mutagenesis using the primers 5′-GTCCATAGTGTTTATTCCTTGTGGTCATCTAGTAGTATGCAAAGATTGTGC-3′ , 5′-GCACAATCTTTGCATACTACTAGATGACCACAAGGAATAAACACTATGGAC-3′ , 5′-GACTTAATGTGTTCTTATTGGATATGGCTAGGAAAAGAAATGACTACGATGATAC-3′ , 5′-GTATCATCGTAGTCATTTCTTTTCCTAGCCATATCCAATAAGAACACATTAAGTC-3′ , respectively , and the QuickChange mutagenesis system from Stratagene . pRK5-Flag-tagged human c-IAP2ΔCARD-RING was generated by cloning a PCR product amplified from human c-IAP2 cDNA into pRK5 that already contained cDNA encoding the Flag-tag using the primers 5′-GCTCGTGAATGCGGGATCCTCTAGAAACATAGTAGAAAACAGC-3′ and 5-GCTGCAACGTAAGCTTTCATTCATTTGATTCTTTTTCCTCAGTTGC-3′ , BamH1 and HindIII . Presence of the mutations was confirmed by direct sequencing . pCMV-Tag2 murine c-IAP2 has been described [21] . GST-tagged murine c-IAP2 was obtained by subcloning into pGEX-6P-1 ( Amersham ) . GST-tagged murine c-IAP2H570A was generated by site directed mutagenesis using primers that have been described [21] . Myc-tagged murine c-IAP1 was obtained by subcloning into pCMV-Tag5 ( Clontech ) . IKKβ-CA has been described [64] . pCMV4 containing Flag-tagged IκB cDNA was obtained from Dean Ballard ( Vanderbilt University ) . The anti-c-IAP antibody was obtained from Herman Chung and Bob Korneluk ( Apoptosis Research Center , Children's Hospital of Eastern Ontario ) , anti-NIK and anti-p52 from Cell Signaling Technologies , anti-phospho-IκB and anti-IκB from Santa Cruz , and anti-FLAG and anti-β-actin from Sigma . Anti-CD40 ( HM40-3 ) was obtained from BD Biosciences . BAFF was obtained from Peprotech . The fluorescently labeled antibodies used for analysis of lymphoid populations in the thymus , bone marrow , lymph node , and spleen by flow cytometry were obtained from BD Biosciences . The Mouse Immunoglobulin Isotype Panel ( Southern Biotech ) was used to quantify the serum immunoglobulin titers for IgM , IgG1 , IgG2b , IgG3 , and IgA . The OptEIA Set Mouse IgE ( BD Biosciences ) was used to quantify the amount of serum IgE . The anti-B220/CD45R and anti-CD3 used from B and T cell immunohistochemistry were purchased from BD Biosciences and Serotec , respectively . The B cell and T cell enrichment kits were obtained from Stemcell Technologies . For some experiments B cells were purified using the Mouse B cell Recovery Column Kit from Cedarlane Laboratories Ltd . The primer sequences used in the quantitative PCR are as follows , GADD45β 5′ ( 5′-CTGCCTCCTGGTCACGAA-3′ ) , GADD45β 3′ ( 5′-TTGCCTCTGCTCTCTTCACA-3′ ) , IκB 5′ ( 5′-TCACGGAGGACGGAGACTCG-3′ ) , IκB 3′ ( TGGAGATGCTGGGGTGTGC ) , ferritin heavy chain 5′ ( 5′-GGAGTTGTATGCCTCCTACGTCT-3′ ) , ferritin heavy chain 3′ ( 5′-TGGAGAAAGTATTTGGCAAAGTT-3′ ) , c-IAP2 5′ ( 5′-TATTTGTGCAACAGGACATTAGGAGT-3′ ) , c-IAP2 3′ ( TCTTTCCTCCTGGAGTTTCCG ) , Bcl-2 5′ ( 5′-GTACCTGAACCGGCATCTG-3′ ) , and Bcl-2 3′ ( 5′-GGGGCCATATAGTTCCACAA-3′ ) . The HPRT primers have been described [65] . c-IAP2 siRNA has been described [26] and was modified to Stealth RNAi siRNA . The sequences of the oligonucleotides are 5′-AAGUGGUAGGGACUUGUGCUCAAAG-3′ and 5′-CUUUGAGCACAAGUCCCUACCACUU-3′ . The BamH1-EcoR1 and EcoR1-EcoR1 recombination arms used to generate the c-IAP2H570A targeting construct were obtained from BAC-DNA ( clone 239-13P; Research Genetics ) using the respective endonucleases and subcloned into shuttle vectors . To insert the silent mutation in the neighboring leucine codon introducing a novel Spe1 restriction endonuclease site and then replace the histidine codon with an alanine codon , the BamH1-Ecor1 arm was sequentially mutagenized using mutagenic primers 5′-CATCGTGTTCATTCCCTGTGGCGCACTAGTCGTGTGCAAAGACTGCG-3′ and 5′-CGCAGTCTTTGCACACGACTAGTGCGCCACAGGGAATGAACACGATG-3′ , and then 5′-CATTCCCTGTGGCCATCTAGTCGTGTGCAAAGACTGC-3′ and 5′-GCAGTCTTTGCACACGACTAGATGGCCACAGGGAATG-3′ using the QuickChange mutagenesis system from Stratagene . The presence of H570A in exon 9 and absence of other spontaneous mutations in the other exons were confirmed by direct sequencing . After subcloning both recombination arms into a vector containing a neomycin cassette flanked by two loxP recombination sites , the resultant targeting vector was linearized with Not1 and transfected into ES cells . Stable transfectants were screened by southern blotting and long-range polymerase chain reaction ( LR-PCR ) coupled with Spe1 restriction endonuclease digestion . The primers used to screen the c-IAP2H570A/H570A mice were obtained from Invitrogen and their sequence was 5′ CGAAAAAGATGCCCATCTACTCAG-3′ and 5′-TATCCCTAAAATGTCATCCAATAAATAACAG-3′ . The clone that had correctly integrated the targeting construct at the c-IAP2 locus was injected into blastocytes to generate chimeric mice . F1 offspring of the chimeric mice were backcrossed 6 additional times to the C57BL/6 ( B6 ) background and then c-IAP2+/H570A were interbred to obtain c-IAP2H570A/H570A mice . B6 mice bred in the CRC Vivarium ( NIH ) were used as controls for all experiments . All animal experimental procedures were approved by the Animal Care and Use Committee of the National Cancer Institute . The fragment spanning the recombination arm containing c-IAP2H570A was amplified from tail DNA using buffer 3 from the Expand Long Template PCR System ( Roche ) and the c-IAP2 locus 5′ and c-IAP2 locus 3′ primers , digested with Spe1 , and resolved by agarose gel electrophoresis . Total RNA was isolated from purified B cells using the Utraspec RNA isolation reagent ( Biotecx laboratory ) and reverse transcribed using Superscript II Reverse Transcriptase kit ( Invitrogen ) following the manufacturers' protocol . The amount of ferritin heavy chain , IκB , c-IAP2 , GADD45β , Bcl-2 , and hypoxanthine phosphoribosyltransferase ( HPRT ) mRNA was quantified using the respective primers , SYBR Green PCR Master Mix ( Applied Biosystems ) , and the 7500 Real Time PCR System ( Applied Biosystems ) . The values were normalized to HPRT and the percent increase relative to wild type was calculated by dividing the c-IAP2 knockin values by the wild type values . Bone marrow , thymus , spleen , lymph nodes ( superficial cervical , axillary , brachial , inguinal , and mesenteric ) and GALT were harvested from wild type and c-IAP2H570A/H570A mice , disrupted by teasing , and total cell suspensions made by gently mashing the debris through 40 µM nylon mesh ( BD Biosciences ) . The cells were counted and the distribution of lymphoid populations in each organ was determined by cell surface staining and flow cytometry . B and T cells were purified from spleen and lymph nodes from wild type and c-IAP2H570A/H570A mice using B and T cell enrichment kits following the manufacturer's protocol . The purity was determined by cell surface staining and flow cytometry , and for all experiments , greater than 90% . In some experiments B cells and splenocytes were cultured in RPMI supplemented with 10% fetal calf serum , 100 U/ml penicillin , 100 µg/ml streptomycin , 2 mM L-glutamine , and 50 µM-β-mercaptoethanol . MEFs were prepared from day 13 . 5 embryos as described [66] and maintained in Dulbecco's Modified Eagle's medium supplemented with 10% fetal calf serum , 100 U/ml penicillin , 100 µg/ml streptomycin , 2 mM L-glutamine , and 50 µM-β-mercaptoethanol . For quantifying cell death , splenocytes ( 7 . 5×105 cells/ml ) were incubated in vitro , stained with fluorescently labeled anti-B220/CD45R and anti-TCRβ , and incubated with 7-amino-actinomycin D ( 7AAD; 1 µg/ml ) . Uptake of 7AAD by dying B ( B220+ ) and T ( TCRβ+ ) cells was quantified by flow cytometry . The percentage of viable cells was calculated by dividing B220+7AAD− or TCRβ+7AAD− by the total B220+ or TCRβ+ cells at each time point . For BAFF- and anti-CD40-induced survival , purified B cells were incubated at ( 7 . 5×105 cells/ml ) with the indicated concentrations of BAFF or agonistic anti-CD40 ( 100 ng/ml ) for 66 h , stained with fluorescently labeled anti-B220 and 7AAD , and analyzed by flow cytometry . To assess proliferation , purified B cells ( 2 . 5×105 cells/ml ) were stimulated with anti-μ F ( ab′ ) 2 ( Jackson ImmunoResearch Laboratories , Inc . ) or LPS ( Sigma ) , and during the final 18 h of the 66 h period , DNA synthesis was measured by adding 1 µCi 3H-thymidine to the culture . The cells were then harvested and lysed , and the DNA was transferred to a filtermat . The amount of incorporated 3H-thymidine was quantified using a scintillation counter . B cells , T cells , and MEFs were lysed in a buffer containing 20 mM Tris pH 7 . 5 , 150 mM NaCl , 1% Triton X-100 , 1 mM EDTA , 30 mM NaF , 2 mM sodium pyrophosphate supplemented with Complete ( Roche ) protease inhibitor cocktail , and the detergent-soluble lysate was collected after centrifugation . Lysates were normalized to protein concentration , denatured in sample buffer ( 50 mM Tris pH 6 . 8 , 10% glycerol , 2% SDS , 2% β-mercaptoethanol , and 0 . 04% bromophenol blue ) , resolved by SDS-PAGE , and immunoblotted with the appropriate antibodies . For knockdown studies , 3 . 0×105 MEFs were plated in 60 mm cell culture dishes and 16 h later transfected with 30 nM of Universal Lo GC content non-targeting or c-IAP2 Stealth iRNA siRNA using Lipofectamine RNAiMAX ( Invitrogen ) following the manufacturer's protocol . After 24 h the cells were washed twice with phosphate-buffered saline ( PBS ) and lysed . For ectopic expression studies , 293T cells were transfected with the indicated plasmids using Lipofectamine 2000 ( Invitrogen ) following the manufacturer's protocol . Twenty-four hours later the cells were harvested , washed with PBS , counted , and lysed in sample buffer . Glutathione S-transferase ( GST ) -tagged proteins were expressed in DH5α cells with 0 . 05 mM isopropyl-β-thiogalactopyranoside at 16°C for 20 h and lysed in 20 mM HEPES pH 7 . 5 , 100 mM NaCl , 1 . 5 mM MgCl2 , 1% Triton X-100 . The recombinant proteins were purified from clarified lysates using glutathione Sepharose 4B beads ( Amersham Biosciences ) . The beads were washed extensively and incubated with 35S-labeled TRAF2 that had been translated in vitro using the TNT Quick Coupled Transcription/Translation System ( Promega ) for 3 h at 4°C in binding buffer containing 120 mM NaCl , 10% glycerol , 1% Triton X-100 , and 50 mM Tris pH 7 . 5 . The bead-bound complexes were washed with the binding buffer , eluted with sample buffer , and resolved by SDS-PAGE . Equal number of splenic B cells purified from wild type ( CD45 . 1+ ) and c-IAP2H570A/H570A ( CD45 . 2+ ) knockin mice were mixed and 107 cells were injected into the tail veins of RAG2-deficient ( CD45 . 2+ ) mice . Forty-five days later the percentage of wild type and c-IAP2H570A/H570A B cells in the spleens and lymph nodes was determined by staining cell suspensions with B220 , CD45 . 1 , and CD45 . 2 and analyzed by flow cytometry . The ratio was generated by dividing the percentage of c-IAP2H570A/H570A B cells by the percentage of wild type B cells . Mice were euthanized using CO2 inhalation and necropsies were performed . A comprehensive set of organs and tissues were collected and fixed in 10% neutral buffered formalin . Tissues were paraffin-embedded , sectioned at 5 µm , and stained with hematoxylin and eosin . For lymphocytes , slides were stained with biotin-conjugated anti-B220/CD45R or anti-CD3 . The antigens were retrieved by microwaving in EDTA ( B220 ) or citrate buffer ( CD3 ) . Detection of B220 was performed using the avidin-biotinylated enzyme complex ( Vector Laboratories ) with 3 , 3′-diaminobenzidine ( Sigma ) as chromagen . Detection of CD3 was accomplished using the Rabbit Elite kit ( Vector Laboratories ) using 3 , 3′-diaminobenzidine as chromagen . Slides were counterstained with hematoxylin . Stained sections were evaluated by a boarded veterinary pathologist . Serum immunoglobulin isotypes were quantified by ELISA following the manufacturer's protocol . p values were calculated using GraphPad Prism and a two-tailed t test .
|
MALT ( mucosal associated lymphoid tissue ) lymphomas commonly express a mutant protein that contains a portion of the ubiquitin protein ligase cellular Inhibitor of Apoptosis 2 ( c-IAP2 ) and a portion of the paracaspase MALT1 . Expression of this fusion protein activates the anti-apoptotic transcription factor NF-κB , but how it does so and whether or not this activity contributes to lymphomagenesis is not known . Here we identify the mechanisms by which the fusion protein activates NF-κB and show that absence of c-IAP2 ubiquitin protein ligase activity in mice , as is the case in patients that express the fusion protein , results in spontaneous activation of NF-κB and many of the phenotypic cellular features of MALT lymphoma . Our findings demonstrate that c-IAP2 ubiquitin protein ligase activity dampens constitutive NF-κB activity and maintains B cell homeostasis , and provide genetic evidence that the loss of this enzymatic activity in the fusion protein has a major contributing role in MALT lymphomagenesis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunology/leukocyte",
"signaling",
"and",
"gene",
"expression",
"oncology/gastrointestinal",
"cancers",
"cell",
"biology/cell",
"signaling"
] |
2010
|
Non-Canonical NF-κB Activation and Abnormal B Cell Accumulation in Mice Expressing Ubiquitin Protein Ligase-Inactive c-IAP2
|
The epidemic tendency of hemorrhagic fever with renal syndrome ( HFRS ) is on the rise in recent years in Guangzhou . This study aimed to explore the associations between meteorological factors and HFRS epidemic risk in Guangzhou for the period from 2006–2015 . We obtained data of HFRS cases in Guangzhou from the National Notifiable Disease Report System ( NNDRS ) during the period of 2006–2015 . Meteorological data were obtained from the Guangzhou Meteorological Bureau . A negative binomial multivariable regression was used to explore the relationship between meteorological variables and HFRS . The annual average incidence was 0 . 92 per 100000 , with the annual incidence ranging from 0 . 64/100000 in 2009 to 1 . 05/100000 in 2012 . The monthly number of HFRS cases decreased by 5 . 543% ( 95%CI -5 . 564% to -5 . 523% ) each time the temperature was increased by 1°C and the number of cases decreased by 0 . 075% ( 95%CI -0 . 076% to -0 . 074% ) each time the aggregate rainfall was increased by 1 mm . We found that average temperature with a one-month lag was significantly associated with HFRS transmission . Meteorological factors had significant association with occurrence of HFRS in Guangzhou , Southern China . This study provides preliminary information for further studies on epidemiological prediction of HFRS and for developing an early warning system .
Hemorrhagic fever with renal syndrome ( HFRS ) is a rodent-borne zoonosis caused by different species of hantaviruses , characterized by varying degrees of bleeding diathesis , hypertension , and renal failure [1] . In Asia the majority of reported cases of HFRS have occurred in China and the annual incidence of HFRS of China has ranked the highest in the world since 2000 [2] . The prevalence of HFRS peaked in 1986 , declined in the 1990s , but it was on the rise in recent years , especially in the large and medium-sized cities [3] . Guangzhou , as a political , economic and cultural center , has over 7 . 94 million registered inhabitants and 4 . 76 million floating population ( from 2010 census data ) . Elucidating the dynamic tendencies and influencing factors in Guangzhou will be critical and urgent for developing an appropriate plan for the prevention and control of HFRS . The epidemiological characteristics of HFRS are affected by various factors , including meteorological factors [4 , 5] , rodent density [4] and vaccination [6] . Meteorological factors may influence the incidence of HFRS via affecting infection rates and population dynamics of hosts , the regeneration of mites , and the contact rate between rodents and human beings . Infection rates and population dynamics of hosts are thought to be influenced by climatic factors [7–10] . For example , a longitudinal study in Qingdao , China found that precipitation and relative humidity were positively correlated to the densities of hosts and/or hantavirus-positive hosts and the densities of hosts or hantavirus positive hosts were positively correlated to the incidence of HFRS [11] . The data were quite consistent with other reports [12–14] . In China , HFRS is caused mainly by two types of hantavirus , Hantaan virus ( HTNV ) and Seoul virus ( SEOV ) , previous studies showed that HTNV could be isolated from gamasid and trombiculid mites collected from the nests of field hosts and from laboratory-reared offspring of these mites and that both trombiculid and gamasid mites could transmit HTNV by biting susceptible mammals [15–16] . Hantavirus transmission among hosts is speculated to be likely maintained through biting during aggressive interaction [17] . Previous studies indicated that the densities of hosts’ mites could be influenced by humidity , humid environment facilitates the survival or breeding of mites , might be important in mediating host-to-host and possibly host-to-human transmission of hantaviruses [11] . Besides , meteorological factors can influence human behaviors , and thus influence the chance of people having contact with rodent excrement . Although several studies have explored the associations between meteorological factors and HFRS epidemic risk [18–21] , there has been inconsistency between the results due to different models and regions . The most appropriate model for HFRS still remains unclear . One of the critical reasons may be that the variability in meteorological factors in different degrees can produce different effects . The climate of Guangzhou is humid subtropical , where the summer is wet with high temperatures and a high humidity index . Therefore , there is an urgent need to explore the associations between meteorological factors and HFRS epidemic risk in Guangzhou which can help to establish an early warning system for HFRS .
This study was approved by the Ethics Committee of Guangzhou center for disease control and prevention ( GZCDC ) . Guangzhou ( Fig 1 ) , the capital city of Guangdong province of China , is located between longitudes 112°57'E and 114°3'E , latitudes 22°26'N and 23°56'N . The city population in 2015 was 13 . 50 million . It is situated in the northern hemisphere with an annual average relative humidity of 78% , temperature of 22 . 3°C and rainfall 2471 . 9 mm . The climate is humid subtropical , with a wet summer is wet of high temperatures and a high humidity index . We obtained data of HFRS cases in Guangzhou from the National Notifiable Disease Report System ( NNDRS ) during the period of 2006–2015 in this study . All cases of HFRS were diagnosed according to the unified diagnosed criteria issued by Chinese Ministry of Health . The diagnostic principles include epidemiological exposure histories , clinical manifestations and laboratory test . The criteria for probable cases of HFRS include epidemiological exposure histories ( traveled to an endemic area or contact with rodents or the urine , droppings , or saliva of infected rodents within 2 months before onset of the disease ) , clinical manifestations ( such as fever , chills , nausea , flushing of the face , inflammation or redness of the eyes , or a rash , low blood pressure and acute kidney failure ) and serologic test results positive for hantavirus infection , evidence of hantavirus antigen in tissue by immunohistochemically staining and microscope examination , or evidence of hantavirus RNA sequences in blood or tissue . All the laboratory tests were completed by GZCDC using the same method and same kits . All hospitals and clinics in Guangzhou city are obliged to report HFRS cases through NNDRS within 24 hours . Meteorological data , including daily average temperature ( in degrees Centigrade ) , maximum temperature , minimum temperature , relative humidity ( as a percentage ) , atmospheric pressure ( in hPa ) , wind velocity ( in meters per second ) , sunshine ( in hours of daylight ) and rainfall ( in millimeter ) were obtained from the Guangzhou Meteorological Bureau . Monthly meteorological data , including average temperature , cumulative rainfall , average atmospheric pressure , average relative humidity , average wind velocity and cumulative sunshine were calculated . The Pearson's correlation coefficients were calculated to examine the degree of multi-collinearity among the meteorological variables . Multi-collinearity was identified when the Pearson's correlation coefficient was greater than 0 . 9 . Given the data were over-dispersed , a negative binomial multivariable regression was used to explore the relationship between meteorological variables and HFRS . The monthly incidence of HFRS was presented as cases per 100000 inhabitants . Meteorological variables for the months preceding the HFRS outbreaks have been shown to be critical . Considering the lagged effect of the meteorological variables on the number of HFRS cases , we incorporated meteorological variables over a range of lags into the regression model . The basic expressions for the model are as follows: logμ=intercept+b1X1+b2X2+…+bmXm , μ=exp ( intercept+b1X1+b2X2+…+bmXm ) We calculated the percent increase , which indicated the influences of meteorological variables . All estimates of percent increase were complemented by a 95% confidence interval ( CI ) and p-value . The year variable was forced into the model to eliminate the effects of the long-term trends . All of these analyses were performed using R Project 3 . 0 . 2 ( R Development Core Team , 2012 ) . The geographic location of Guangzhou was created by ArcGIS 10 . 1 ( Environmental Systems Research Institute , Inc ) .
There were 1098 HFRS cases reported in Guangzhou between 2006 and 2015 . The annual average incidence was 0 . 92 per 100000 , with the annual incidence ranging from 0 . 64/100000 in 2009 to 1 . 05/100000 in 2012 . A seasonality phenomenon became apparent , with epidemic peaks occurring in February to May . The peak accounted for 46 . 45% of all HFRS cases . The monthly average temperature , average atmospheric pressure , average relative humidity , average wind velocity , aggregate rainfall and aggregate sunshine ranged from9 . 83°C to 30 . 18°C , from 998 . 87 hPa to 1020 . 99 hPa , from 1 . 77% to 87 . 65% , from 1 . 50 m/s to 2 . 92 m/s , from 0 . 28 mm to 888 . 95 mm , respectively ( Table 1 ) . The time series of case and meteorological data are shown in Fig 2 . The Pearson's correlation coefficients revealed a strong correlation ( r = -0 . 937 , P<0 . 01 ) between average temperature and average atmospheric pressure ( Table 2 ) . The result indicated that collinearity of the preliminary variables can be observed in our study . In this study , lags of meteorological variables from one to four months were included to build different models , and to avoid the collinearity of average temperature and average atmospheric pressure , we put them into two different models when exploring the relationship between meteorological variables and HFRS . There were significant lag effects between meteorological variables and monthly cases of HFRS ( Table 3 ) . Average temperature and aggregate rainfall in the same month , lags of average temperature from one to three months , aggregate rainfall of two months and average relative humidity of four months all have significant association with the incidence of HFRS . The final negative binomial regression model ( Table 4 ) suggests that the monthly number of HFRS cases decreased by 5 . 543% ( 95%CI -5 . 564% to -5 . 523% ) each time the temperature was increased by 1°C , and the number of cases decreased by 0 . 075% ( 95%CI -0 . 076% to -0 . 074% ) each time the aggregate rainfall was increased by 1 mm . The comparison of fitted and cases in the final model is shown in Fig 3 .
HFRS is epidemic in many provinces in mainland China , and it is worth noting that the prevalence is on the rise in the large and medium-sized cities , such as Guangzhou . Transmission of hantaviruses from rodents to humans is believed to occur through inhalation of aerosols contaminated by virus shed in excreta , saliva , and urine of infected animals [22–24] . The number of HFRS cases is influenced by the density and hantavirus infection rate of host rodents , as well as the contact rate between rodents and human beings [7 , 25] . Meteorological factors may influence the incidence of HFRS via affecting infection rates and population dynamics of hosts , the regeneration of mites , and the contact rate between rodents and human beings . Vector-borne viral diseases including HFRS are amongst the most sensitive of all diseases to climate change [26] . Climate change would directly affect disease transmission by shifting the reservoir's geographical range and increasing reproductive rates and by shortening the pathogen's incubation period [10] . The results of this study show that average temperature was negatively associated with the incidence of HFRS , which is in agreement with the results at Shandong [27] . However , inconsistent findings have also been reported in other studies . The results of a study in Junan County showed that extremes of weather ( too cold or too hot ) do not favor HFRS prevalence , and the most appropriate mean temperature was between 10°C and 25°C [13] Lin et al . applied a generalized additive model to examine the effect of meteorological factors on the occurrence of HFRS in Jiaonan county , China [28] . They found that a daily mean temperature at about 17°C was associated with highest HFRS occurrence , a positive association between temperature and HFRS occurrence was observed when the daily mean temperature was below 17°C , while when the daily mean temperature was higher than 17°C , an inverse association was observed . Temperature could affect the breeding and survival of rodents as well as infectivity of hantavirus; it could also affect the activities of both rodents and the human population . In cooler climates , warmer temperatures may allow reservoirs to survive more easily in winters that normally would have limited their populations and to cause rodents to reach maturity much faster than lower temperatures [21] . The discrepancy might be due to the difference in the characteristics of climate of the study regions and different models applied in the studies . In Guangzhou , the mean temperature is 22 . 11°C , which is close to the highest suitable temperature for outside activities of both rats and human ( 25°C ) , so in this area , when the temperature increases further , there is less interaction between rodents and humans , leading to the decrease of the disease . The results of this study show that there is a 1 month lagged effect of average temperature to the incidence of HFRS . The lag would capture the period of rodents growth , virus development time within the rodents and the virus incubation period within the human body [10] . This lead time is of practical importance in predicting epidemics of HFRS and giving health authorities sufficient time to formulate plans , disseminate warnings , and implement public health interventions , such as vaccinating high-risk populations , killing the rodent hosts , and managing environments for the prevention and control of the disease ( Ministry of Health 1998 ) [21] . While the lag effects for associations of the climatic variables were inconsistent , for example the study of Elunchun and Molidawahaner showed that land surface temperature , rainfall and relative humidity were significantly correlated with the monthly reports of HFRS with lags of 3–5 months [21] , and the study in Heilongjiang Province showed an important seasonal signal in monthly maximum temperature , relative humidity with a lag of 1–3 months in the association with reported HFRS cases [18] . The difference may due to geographical difference , where the meteorological characteristics and biological characteristics of viral transmission may be different . The results of this study suggest that aggregate rainfall have significant association with the incidence of HFRS , which is consistent with the findings of previous studies . Fang et al . found that there was a negative association between monthly cumulative precipitation and HFRS , in a study carried out in Shandong Province [27] , and similar results were also reported in Yingshang County [10] , Jiangsu Province and Jiaonan County [28] , China . Although heavy precipitation followed by increased grass seed production was associated with higher deer mouse densities that caused an outbreak of hantavirus pulmonary syndrome in the Four Corners region of the USA [29–32] , excessive rainfall could have a negative impact on rodents by destroying their habitats [10 , 33] . In addition , frequent rain may decrease the likelihood of rodent-to-rodent contact , rodent-to-human contact , and virus transmission due to decreased rodent activity and reduced human exposure [10] . The present study is first to investigate the effect of meteorological factors on HFRS incidence in southern China , to the best of our knowledge . However , some limitations should be noted when interpreting findings from this study . Firstly , the study design was an ecological study; it did not allow us to explore individual-based association and limited the capacity for causal inference . Secondly , the occurrence of HFRS cases in each region may not be caused by climate alone . Other factors such as human activities and movement , socioeconomics status , land use and population immunity may contribute to the transmission of HFRS . However , data are limited on many of these variables . Thus we could not exclude these potential confounding factors . Therefore , further studies of the associations between meteorological factors and occurrence of HFRS are warranted . In conclusion , this study demonstrated that meteorological factors had significant association with occurrence of HFRS in Guangzhou , Southern China . A rise in temperature and rainfall may reduce the risk of HFRS infection . This study provides preliminary information for further studies on epidemiological prediction of HFRS and for developing an early warning system .
|
The prevalence of HFRS was on the rise in recent years , especially in the large and medium-sized cities in China . We obtained data of HFRS cases in Guangzhou from the National Notifiable Disease Report System ( NNDRS ) during the period of 2006–2015 . Meteorological data were obtained from the Guangzhou Meteorological Bureau . A negative binomial multivariable regression was used to explore the relationship between meteorological variables and HFRS . Meteorological factors had significant association with occurrence of HFRS in Guangzhou , Southern China . This study provides preliminary information for further studies on epidemiological prediction of HFRS and for developing an early warning system .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"china",
"atmospheric",
"science",
"pathogens",
"geographical",
"locations",
"microbiology",
"vertebrates",
"animals",
"mammals",
"viruses",
"hemorrhagic",
"fever",
"with",
"renal",
"syndrome",
"hantavirus",
"rna",
"viruses",
"humidity",
"bunyaviruses",
"infectious",
"diseases",
"medical",
"microbiology",
"epidemiology",
"microbial",
"pathogens",
"mites",
"arthropoda",
"people",
"and",
"places",
"rain",
"rodents",
"eukaryota",
"asia",
"meteorology",
"earth",
"sciences",
"viral",
"pathogens",
"biology",
"and",
"life",
"sciences",
"viral",
"diseases",
"amniotes",
"organisms"
] |
2018
|
Meteorological factors and risk of hemorrhagic fever with renal syndrome in Guangzhou, southern China, 2006–2015
|
Infection with the human gastric pathogen Helicobacter pylori is associated with a spectrum of diseases including gastritis , peptic ulcers , gastric adenocarcinoma , and gastric mucosa–associated lymphoid tissue lymphoma . The cytotoxin-associated gene A ( CagA ) protein of H . pylori , which is translocated into host cells via a type IV secretion system , is a major risk factor for disease development . Experiments in gastric tissue culture cells have shown that once translocated , CagA activates the phosphatase SHP-2 , which is a component of receptor tyrosine kinase ( RTK ) pathways whose over-activation is associated with cancer formation . Based on CagA's ability to activate SHP-2 , it has been proposed that CagA functions as a prokaryotic mimic of the eukaryotic Grb2-associated binder ( Gab ) adaptor protein , which normally activates SHP-2 . We have developed a transgenic Drosophila model to test this hypothesis by investigating whether CagA can function in a well-characterized Gab-dependent process: the specification of photoreceptors cells in the Drosophila eye . We demonstrate that CagA expression is sufficient to rescue photoreceptor development in the absence of the Drosophila Gab homologue , Daughter of Sevenless ( DOS ) . Furthermore , CagA's ability to promote photoreceptor development requires the SHP-2 phosphatase Corkscrew ( CSW ) . These results provide the first demonstration that CagA functions as a Gab protein within the tissue of an organism and provide insight into CagA's oncogenic potential . Since many translocated bacterial proteins target highly conserved eukaryotic cellular processes , such as the RTK signaling pathway , the transgenic Drosophila model should be of general use for testing the in vivo function of bacterial effector proteins and for identifying the host genes through which they function .
The human pathogen , Helicobacter pylori , infects the stomachs of at least half the world's population and chronic infection is associated with the development of diseases such as gastritis , peptic ulcers and gastric cancer [1] . A major virulence determinant of H . pylori is the cytotoxin associated gene A ( CagA ) which is translocated into host cells via a type four secretion system ( reviewed in [2] ) . Inside host cells , CagA is phosphorylated by Src family kinases on tyrosines contained in repeated five-amino acid motifs ( EPIYA ) in CagA's carboxyl terminus . Phosphorylated CagA disrupts receptor tyrosine kinase ( RTK ) signaling pathways by directly activating Src homology 2 ( SH2 ) domain containing tyrosine phosphatase ( SHP-2 ) ( reviewed in [3] ) . Normally SHP-2 is activated by the scaffolding adaptor Grb2-associated binder ( Gab ) proteins , thereby amplifying RTK signaling pathways to control cell growth , differentiation and survival ( reviewed in [4] ) . The Gab proteins occupy a pivotal position in RTK signaling pathways by interacting directly with RTKs such as the c-Met receptor of the Hepatocyte growth factor/Scatter factor ( HGF/SF ) as well as downstream cytoplasmic proteins including SHP-2 , v-crk sarcoma virus CT10 oncogene homolog ( avian ) -like ( Crk ( L ) ) , and Growth factor receptor-bound protein 2 ( Grb2 ) ( reviewed in [5] , [6] , [7] ) . Although CagA shares no sequence similarity with Gab proteins , CagA has been shown to activate SHP-2 in tissue culture cells , resulting in cell elongation [8] , [9] . Similarly , in tissue culture cells CagA has been found to associate with c-Met , Crk ( L ) and Grb2 [10] , [11] , [12] . Based on these interactions , CagA has been hypothesized to mimic Gab proteins and to function as an oncogene by over-activating RTK signaling [13] . The significance of CagA's interactions with RTK signaling pathway proteins , however , has only been explored in tissue culture cells . We have developed transgenic Drosophila with inducible CagA expression as a model to understand CagA's mechanisms of action in complex epithelial tissues . In order to test the hypothesis that CagA can function as a Gab substitute , we investigated CagA activity in a well-characterized Gab-dependent process , the specification of photoreceptors in the Drosophila eye [14] , [15] , [16] . The Drosophila compound eye , whose crystalline array of facets or ommatidia are exquisitely sensitive to perturbations in cell specification , has been used as a powerful system for the discovery and genetic analysis of RTK signaling components [17] , [18] . Drosophila RTK signaling proteins are highly conserved with their mammalian orthologues and oncogenic mutations in these proteins , such as those that constitutively activate RTK receptors or their downstream effectors , function similarly in both Drosophila and mammalian cells [19] . The Drosophila model also offers elegant tools for genetic manipulations including the UAS/GAL4 system [20] for expression of transgenes in a tissue specific manner , the FLP/FRT system for the generation of somatic mutant clones [21] , and null mutations in most RTK signaling pathway members , which allow us to probe the in vivo requirements for CagA's activation of RTK signaling pathways . Finally , Drosophila are amenable to forward genetic approaches that will facilitate the discovery of host factors required for CagA function in eukaryotic cells [22] . RTK signaling is required for multiple steps of Drosophila photoreceptor development . The Drosophila epidermal growth factor receptor ( EGFR ) is necessary for cell proliferation in the early eye imaginal disc , cell survival in the differentiating region of the disc behind the morphogenetic furrow , and recruitment of all photoreceptors except R8 [23] . A second RTK , Sevenless ( SEV ) is required exclusively for the R7 photoreceptor to adopt the appropriate fate , as opposed to becoming a nonneuronal cone cell [24] ( reviewed in [25] ) . The Drosophila Gab adaptor , Daughter of Sevenless ( DOS ) is required for full signaling through both the EGFR and SEV pathways [16] . Clones of eye imaginal cells lacking DOS activity fail to proliferate and produce few photoreceptors , similar to clones lacking EGFR [16] , [26] , [27] . The EGFR pathway is required additionally for multiple aspects of Drosophila development [28] . Here we show that CagA can substitute for the Drosophila Gab adaptor , DOS , and rescue phenotypes associated with loss of dos , including larval lethality and photoreceptor differentiation . We further demonstrate that CagA functions through the Drosophila SHP-2 homologue , Corkscrew ( CSW ) similar to Gab . Our work demonstrates the power of using a genetically tractable system like Drosophila to dissect the mechanism of action of a prokaryotic protein that modulates a conserved eukaryotic signaling pathway .
To determine if the Drosophila system would be useful for dissecting the molecular mechanism of CagA-induced activation of RTK signaling , we examined whether CagA exhibited similar properties when expressed in Drosophila tissue to those previously observed in mammalian tissue culture cells . We used P-element mediated transgenesis to generate Drosophila with a transgene encoding an N-terminal hemagglutinin ( HA ) tagged CagA under control of the yeast GAL4 upstream activating sequence ( UAS-CagA ) . Additionally , we generated transgenic flies with a mutated version of CagA lacking the EPIYA tyrosine phosphorylation motifs ( UAS-CagAEPISA ) . These transgenic flies were crossed to flies that expressed the GAL4 transcription factor under tissue-specific or inducible promoters to express CagA in specific cells and at specific times during development . In the experiments described here , the GMR-GAL4 line was used to express CagA in all cells of the developing imaginal eye disc after the morphogenetic furrow . Western analysis of anti-HA affinity purified proteins from heads of adult UAS-CagA/GMR-GAL4 flies showed that CagA was expressed ( α-HA ) and phosphorylated ( α-P-Tyr , Figure 1A ) . Similar to CagA's distribution in tissue culture cells [8] , [29] , we showed in the Drosophila eye disc CagA was localized predominantly to the cell cortex ( Figure 1C ) . Examination of the cellular morphology of the pupal retina revealed that CagA expression caused disorganization of the epithelium . The wild type retinal epithelium is organized into regular cell clusters , each containing a single R7 and R8 photoreceptor ( Figure 1D ) . In retina expressing CagA , the normal cell shapes and neighbor relationships were perturbed ( Figure 1E ) , similar to CagA-dependent epithelial disorganization observed in mammalian tissue culture monolayers [29] , [30] . When we examined the eyes of adult flies expressing a single copy of CagA with GMR-GAL4 , we observed a perturbation of the normal crystalline array of the ommatidia ( compare wild type , Figure 1F , with CagA expression , Figure 1G ) . Expression of two copies of the UAS-CagA transgene dramatically enhanced the eye phenotype , indicating that the developmental pathways disrupted were sensitive to the amount of CagA expressed ( Figure 1H ) . Expressing one copy of the CagA mutant lacking the tyrosine phosphorylation sites ( CagAEPISA ) did not perturb the crystalline array of the adult eye to the extent caused by wild type CagA ( Figure 1I ) even though the CagAEPISA protein was expressed at similar levels as CagA ( Figure 1B ) . Dose dependent perturbations of Drosophila eye patterning , as observed with CagA expression , have been used as the basis for genetic screens for modifiers of the rough eye phenotype to elucidate several signaling pathways , including RTK pathways . [17] , [31] To test the hypothesis that CagA functions as a prokaryotic mimic of eukaryotic Gab proteins , we asked whether CagA expression could rescue phenotypes caused by the loss of the Drosophila Gab , DOS . DOS functions downstream of multiple RTKs during development , and homozygous dos loss-of-function mutants rarely develop into pupae and never survive to adulthood [16] . Rescue of dos mutants' lethality has been used as an in vivo assay to determine the function of specific domains of DOS [26] . We therefore determined the percentage of dos homozygous mutants that survived to the pupal stage of development with or without CagA expressed ubiquitously with temporal precision using the heat shock inducible Hsp-GAL4 . The frequency of dos homozygous mutants was scored as a percentage of expected pupae that should develop if the dos mutants showed no lethality defect . As expected , a low percentage ( 33% ) of homozygous dos mutant pupae expressing only Hsp-GAL4 were observed ( Figure 2A ) . When CagA was expressed , we observed a significant increase to 89% of the pupae developing that lacked dos ( Figure 2A ) . These results indicate that CagA can substitute for essential functions of DOS during Drosophila development . To specifically test whether CagA could substitute for Gab in photoreceptor development , we generated mitotic dos/dos clones within the eye using the FLP/FRT recombinase system [27] , [32] . In these experiments the dos mutation was recombined onto a chromosome arm containing a centromere proximal FRT recombination site and maintained in trans to a chromosome containing the same FRT site as well as a GFP transgene . By expressing FLP recombinase in the developing eye we induced mitotic recombination between FRT sites , which generated clones of homozygous cells ( +/+ and dos/dos ) in an otherwise heterozygous background ( dos/+ ) . The dos/dos mutant cells were distinguished by their lack of GFP , and the photoreceptors were visualized by staining for the photoreceptor-specific protein ELAV . As previously reported [16] , [26] the dos/dos clones rarely contained photoreceptors and were composed of very few cells ( Figure 2B–E ) , due to the dual requirements for EGFR signaling in cell survival and photoreceptor specification [23] . As expected , expression of DOS with GMR-GAL4 in dos/dos cells resulted in much larger clones with increased numbers of photoreceptors ( Figure 2B , F–H ) . Expression of CagA in dos/dos cells was able to rescue clone size and photoreceptor development similarly to expression of DOS with the same driver ( Figure 2B , I–K ) . Two independent dos mutants gave similar results ( Figure 2 and data not shown ) . These data demonstrate that CagA can substitute for DOS during the development of photoreceptors . We predicted that if CagA functions similarly to Gab , then CagA would require the downstream signaling molecule SHP-2/CSW to promote photoreceptor development . As a downstream component of RTK pathways , CSW is required for photoreceptor development [17] . In contrast to wild type larval eye discs , in which thousands of photoreceptors are specified ( Figure 3A ) , in larval eye discs of csw null mutants only a few photoreceptors develop along the morphogenetic furrow ( Figure 3B , E ) as described previously [33] . The residual photoreceptors in the csw eye discs were mostly R8 cells ( data not shown ) , the only photoreceptor class that does not require RTK signaling for its specification [23] . A significant increase in photoreceptor number could be achieved in the csw mutant eye discs by expression of UAS-CSW with GMR-GAL4 ( Figure 3C ) or Hsp-GAL4 ( data not shown ) . However , expression of CagA from multiple different transgenic lines using either GMR-GAL4 or Hsp-GAL4 failed to increase the number of photoreceptors in two different csw null mutants ( Figure 3D , E , data not shown ) . These results argue that CagA , like DOS , requires SHP-2/CSW to promote photoreceptor development .
We used a transgenic Drosophila system to test the hypothesis that H . pylori's virulence factor CagA can substitute for the Gab adaptor in RTK signaling pathways . This system is ideal for these studies because RTK signaling pathway components can be genetically manipulated , resulting in interpretable phenotypic consequences for tissue development . First , we have demonstrated that CagA in Drosophila tissue is phosphorylated , that it associates with the cell cortex , and that its expression causes epithelial disorganization as in mammalian tissue culture cells . Second , we have provided genetic evidence that CagA can substitute for Gab by demonstrating that CagA expression restores larval viability and photoreceptor development in mutants lacking the Drosophila Gab , DOS . Our inability to rescue dos mutants to adulthood with CagA expression may be due to differences in RTK activation or to non-overlapping functions of Gab and CagA . Indeed too much CagA expression ( using an actin-GAL4 driver ) is lethal to flies ( unpublished results ) , which is not the case for ubiquitous expression of DOS [26] . Third , our genetic epistasis analysis with mutants lacking csw has shown that CagA functions through the Drosophila SHP-2 homologue , similar to results from tissue culture experiments [8] , [9] . RTK signaling is essential for several fundamental biological processes and erroneous signaling can promote tumor formation [19] . Gain-of-function mutations of SHP-2 have been established as oncogenic in numerous leukemia types as well as other diseases like Noonan's Syndrome [4] , [34] , [35] . Over-expression of the Gab scaffolding adaptor proteins is associated with the development of several types of cancers , including breast cancer [6] , [7] and gastric cancer [36] . The specific cancers that develop as a result of these mutations reflect tissue sensitivities to increased Gab and SHP-2 . In the case of H . pylori infection , CagA provides a tissue specific activation of RTK signaling that can precipitate events leading to gastric carcinogenesis [37] , as suggested by a recent report of CagA-expressing transgenic mice [38] . Our approach of examining the cellular effects of CagA expression in Drosophila tissue takes advantage of the fact that bacterial proteins frequently target essential , highly conserved cell-signaling pathways . Drosophila has been employed traditionally as a model organism for dissecting signaling pathways in development , but in recent years it has also proven useful in understanding host-pathogen interactions ( reviewed in [39] , [40] ) , and in one instance has been used as a heterologous system for expression of the bacterial toxins , anthrax lethal and edema factors [41] . Here we have exploited Drosophila eye development to demonstrate CagA's capacity to function as a RTK adaptor . Future studies using this transgenic Drosophila model will allow us to better understand the cellular and tissue-wide consequences of CagA's disruption of eukaryotic signaling pathways and to identify candidate host factors through which CagA functions .
CagA cDNA was amplified from genomic DNA from H . pylori G27 . The CagAEPISA ( lacking EPIYA tyrosine phosphorylation motifs ) cDNA was amplified from a plasmid provided by Manuel Amieva ( originally from Markus Stein [42] ) . CagAEPISA lacks the tyrosines in the four 5-amino acid motifs , EPIYA , which are phosphorylated by host kinases ( point mutations at nucleotide 2684 [A→C] and 2740 [A→C] and a deletion at nucleotide 2878 to 3082 ) . CagA and CagAEPISA were cloned into a modified pUAST vector with an N-terminal hemagglutinin ( HA ) tag ( provided by Chris Q . Doe ) . Transgenic lines were generated by injecting Qiagen-purified plasmid DNA into y , w1118 embryos . Several independent transformant lines were established for each construct . Genetic null alleles of csw ( cswC114 and csw13-87 ) and dos ( dos1 . 46 and dos2 . 46 ) were obtained from Michael Simon . The UAS-DOS strain was from Thomas Raabe and the UAS-CSW strain ( UAS-flgcsw[WTCIM] ) from Lizabeth Perkins . UAS-CagA and UAS-CagAEPISA ( lacking EPIYA tyrosine phosphorylation motifs ) transgenes were expressed in the eye using P{w[+mC] = GAL4-ninaE . GMR}12 ( GMR-GAL4 , Bloomington Stock Center ( BSC ) # 1104 ) . P{GAL4-Hsp70 . PB}2 ( Hsp-GAL4 , BSC # 2077 ) was used for heat-shock inducible expression of transgenes . Fly heads were fixed overnight at 4°C in 2% gluteraldehyde in 0 . 1 M sodium cacodylate buffer ( pH 7 . 2 ) and dehydrated through an ethanol series ( 30% , 50% , 70% , 80% , 90% 95% , three times in absolute ethanol ) at room temperature for 10 minutes in each solution . Samples were critically point dried , sputter coated with gold and viewed using a JEOL 6400 SEM . Eye imaginal discs were dissected from third instar wandering larvae , fixed for 30 minutes ( 4% formaldehyde , 0 . 1 M PIPES ( pH 6 . 9 ) , 0 . 3% Triton X-100 , 2 mM EGTA , 1 mM MgSO4 ) . Discs were washed ( 0 . 3% Triton X-100 in phosphate buffered saline , PBS ) and blocked for one hour ( 1% BSA , 0 . 3% Triton X-100 in PBS ) . Primary antibodies included rat anti-ELAV 1∶10 ( 05HB 7E8A10 , from Chris Q . Doe ) , rat anti-HA 1∶100 ( Roche ) and chicken anti-GFP 1∶2 , 000 ( Chemicon ) . Secondary antibodies included anti- rat conjugated Rhodamine Red 1∶200 ( Jackson ImmunoResearch ) , anti-rat conjugated AlexaFluor 488 1∶200 ( Molecular Probes ) , anti-mouse conjugated Cy3 1∶200 ( Jackson ImmunoResearch ) and anti-chicken conjugated Cy2 1∶100 ( Jackson ImmunoResearch ) . Phalloidin conjugated to Tetramethyl Rhodamine Iso-Thiocyanate ( TRITC , Sigma Aldrich , 1∶500 ) was used to stain F-actin . Imaginal discs were visualized using a Nikon TE2000 U with C1 Digital Eclipse confocal microscope . Wandering third instar larvae were placed at 25°C and approximately 50 hours later the pupal retinas were dissected ( 50% pupal stage ) . Retinas were dissected in PBS , fixed for 20 minutes ( 4% paraformaldehyde in PBS ) and washed three times in PBT ( 0 . 5% Triton X-100 in PBS ) . Retinas were blocked at least 15 minutes in 10% normal goat serum in PBT . Antibodies were diluted in the blocking solution . Primary antibodies included mouse MAb 24B10 which stains all photoreceptors and their axons [43] ( Developmental Studies Hybridoma Bank , 1∶200 ) , rabbit anti-SAL , which stains R7 and R8 nuclei ( also called SPALT , provide by Reinhard Schuh [44] , 1∶100 ) , guinea pig anti-SENSELESS , which stains R8 nuclei ( proved by Hugo Bellen [45] , 1∶1000 ) . Secondary antibodies from Molecular Probes included AlexaFluor 555 conjugated anti-mouse , AlexaFluor 488 conjugated anti-rabbit and AlexaFluor 633 conjugated anti-guinea pig , which were all used at 1∶250 . Pupal retinas were visualized using a Leica TCS SP5 confocal microscope . Fly heads were collected by flash freezing adult flies in liquid nitrogen , shaking the flies in a conical tube , and then separating the heads from the bodies using a mesh sieve . Heads ( ∼1 . 5 mL ) were homogenized in ice cold lysis buffer ( 50 mM Hepes , 150 mM NaCl , 1 mM EDTA , 1 mM Na3VO4 , 0 . 5% Triton X-100 and Complete protease inhibitors [Roche] ) and then centrifuged at 16 , 000 G for 5 minutes . Supernatant from the lysate solution ( 1 . 5 mL ) was added to 50 µL anti-HA Affinity Matrix ( Roche ) which was incubated overnight at 4°C with gentle agitation . The anti-HA affinity matrix was washed 4 times with ice-cold lysis buffer . CagA was eluted from the matrix by boiling in 100 uL sample loading buffer and separated using manufactures protocols for 7% NuPAGE® Novex Tris-Acetate gels , transferred to polyvinylidene difluoride membranes , blocked overnight at 4°C ( 200 mM Tris pH 7 . 5 , 100 mM NaCl , 0 . 1% Tween-20 and 3% BSA ( Fisher ) ) , probed using appropriate antibodies and detected using enhanced chemiluminescene ( ECL plus , Amersham Biosciences ) . Mouse anti-HA was used at 1∶1 , 000 ( Babco ) . Mouse anti-phospho tyrosine was used at 1∶2 , 000 ( Cell Signal Technologies ) . Horseradish peroxidase-conjugated sheep anti-mouse ( Amersham Biosciences ) was used at 1∶5 , 000 . Hsp70-GAL4 balanced over CyO , P{Ubi-GFP} with dos2 . 42 over TM3 , P{Act-GFP} , Ser were crossed to dos1 . 46/TM3 , P{Act-GFP} , Ser ( negative control ) or UAS-CagA; dos1 . 46/TM3 , P{Act-GFP} , Ser . Progeny were raised at 30°C and pupae were examined for GFP florescence using a Stemi SV 11 Apo Zeiss microscope . The number of non-GFP expressing progeny was scored as a percentage of the total number of pupae that developed per bottle and averaged across bottles of the same genotype . At least 12 bottles were scored per cross with between 150–450 pupae examined per bottle . The FLP/FRT recombinase system was used to induce somatic clones in the eye [27] . Males y w , ey-FLP 3 . 5/Y; GMR-GAL4; FRT2 , dos1 . 46/CyO-TM6B were crossed to P{ey-FLP . N}6 , ry506 ( BSC #5577 ) ; P{Ubi-GFP . nls}3L1 P{Ubi-GFP . nls}3L2 P{FRT ( whs ) }2A ( BSC #5825 ) ( negative control ) or UAS-DOS; P{Ubi-GFP . nls}3L1 P{Ubi-GFP . nls}3L2 P{FRT ( whs ) }2A ( positive control ) . Male GMR-GAL4 , UAS-CagA; FRT2 , dos1 . 46/CyO-TM6B were crossed to P{ey-FLP . N}6 , ry506; P{Ubi-GFP . nls}3L1 P{Ubi-GFP . nls}3L2 P{FRT ( whs ) }2A . Imaginal eye discs were stained with anti-ELAV and anti-GFP antibodies . Two genetic null alleles of csw were used to examine if CagA could rescue loss of csw . The cswC114 or csw13-87 alleles were balanced over FM7 , P{Act-GFP} with GMR-GAL4 balanced over CyO , P{Ubi-GFP} on the second chromosome . These females were then crossed to males y1w1118 , P{Ubi-GFP . nls}X1 P{FRT ( whs ) }9-2 ( BSC # 5832 ) /Y ( negative control ) , y1w1118 , P{Ubi-GFP . nls}X1 P{FRT ( whs ) }9-2/Y; UAS-CSW ( positive control ) or y1w1118 , P{Ubi-GFP . nls}X1 P{FRT ( whs ) }9-2/Y; UAS-CagA . Eye imaginal discs were dissected from male larvae .
|
Like many pathogens , the human gastric bacterium Helicobacter pylori orchestrates infection through the activity of proteins that it translocates into host cells . The H . pylori translocated protein , CagA , which shares no homology to any other proteins , is a significant risk factor for H . pylori–associated diseases including gastric cancer . Experiments in tissue culture cells have shown that CagA can activate SHP-2 phosphatase , a component of the receptor tyrosine kinase signaling pathway . Based on this activity , CagA has been proposed to function as a mimic of Gab proteins that serve as adaptors in this signaling pathway . We have developed a transgenic Drosophila model to test this hypothesis in the tissues of an organism . We demonstrate that CagA can substitute for Gab and restore developmental defects caused by the loss of the Drosophila Gab , including promoting photoreceptor specification in the developing eye . Furthermore , we show that CagA functions similarly to Gab because it requires the Drosophila SHP-2 to exert its effect on photoreceptor development . Our transgenic Drosophila model provides new insight into CagA's activity in tissues and will allow us to identify host factors through which CagA functions to manipulate cellular signaling pathways and promote disease .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/bacterial",
"infections",
"genetics",
"and",
"genomics/gene",
"function"
] |
2008
|
A Transgenic Drosophila Model Demonstrates That the Helicobacter pylori CagA Protein Functions as a Eukaryotic Gab Adaptor
|
The archaeal RNA polymerase ( RNAP ) shares structural similarities with eukaryotic RNAP II but requires a reduced subset of general transcription factors for promoter-dependent initiation . To deepen our knowledge of cellular transcription , we have determined the structure of the 13-subunit DNA-directed RNAP from Sulfolobus shibatae at 3 . 35 Å resolution . The structure contains the full complement of subunits , including RpoG/Rpb8 and the equivalent of the clamp-head and jaw domains of the eukaryotic Rpb1 . Furthermore , we have identified subunit Rpo13 , an RNAP component in the order Sulfolobales , which contains a helix-turn-helix motif that interacts with the RpoH/Rpb5 and RpoA′/Rpb1 subunits . Its location and topology suggest a role in the formation of the transcription bubble .
Gene expression in cellular organisms across the three kingdoms of life is carried out by multisubunit RNA polymerase ( RNAP ) enzymes . Eukaryotes have three different multisubunit nuclear RNAPs ( Pol I , II , and III ) , whereas Archaea and Bacteria have single enzymes [1] . A wealth of structural information has been gathered in the past decade allowing the visualization of RNAP II in isolation , in the act of transcription , and in complex with transcription factors transcription factor II S ( TFIIS ) or transcription factor II B ( TFIIB ) [2–5] . The archaeal transcription machinery is orthologous to that of eukaryotes , but initiation only requires two accessory factors: transcription factor B ( TFB ) ( an ortholog of TFIIB ) and TATA-box binding protein ( TBP ) [6–8] , and thus provides a simplified model system for studying transcription initiation . In eukaryotes , the additional basal factors are needed , in part to facilitate DNA melting at the initiation site , a functional complexity that Archaea must overcome by other means [6 , 7] . Recent structural studies on archaeal polymerases [9 , 10] have shed light on the basic architecture , but the information gathered thus far remains incomplete . We have therefore determined the crystal structure of the complete DNA-directed RNA polymerase from the archaeon Sulfolobus shibatae ( SshRNAP ) at 3 . 35 Å resolution ( see Materials and Methods and Table 1 ) revealing the complete 13 subunit set of the functional enzyme including two subunits so far undetected: RpoG/Rpb8 and Rpo13 ( Figure 1 ) . The highly positively charged C-terminus of Rpo13 extends into the DNA entry channel , suggesting its involvement in binding to nucleic acids . Our intact RNAP structure allows us to propose a model for the archaeal preinitiation complex formation .
The structure determination in two distinct crystal forms , to 3 . 35 Å resolution is described in Materials and Methods; 3 , 334 residues in 13 subunits are seen , but the resolution achieved limits the accuracy of the position of the side chains . For the most flexible subunits , Rpo4 and Rpo7 , accounting for some 265 residues , the register of the sequence is , in places , uncertain ( ±1 ) . The model quality is good , it lies in the top 15th percentile of structures solved at between 3 . 1–3 . 6 Å as judged by MolProbity [11] , 78% of the residues are in the most favoured region of the Ramachandran plot ( see Table 1 ) . This compares favourably with the equivalent value of 61% for the structure of RNAP from S . solfataricus [9] . The overall architecture , subunit arrangement , composition , and topology closely follow those of the eukaryotic counterpart RNAP II [2]; for this reason , we propose a new subunit nomenclature applicable to all archaeal RNAPs and based on the eukaryotic terminology ( Figures 1 and 2 ) . The basic assembly resembles ( root mean square deviation [rmsd] 1 . 1 Å , for 2 , 938 residues aligned , 97% of the residues in common between the two structures ) the recently published archaeal RNAP structure [9] , but our structure adds considerable new information . More specifically , we have located the clamp-head domain in Rpo1N ( Figure 2A ) , the jaw domain in subunit Rpo1C ( Figure 2B ) , and the entire Rpo8 subunit ( Figure 2C ) . Furthermore , we observe density corresponding to a helix-turn-helix ( HTH ) motif in a groove created by Rpo5 and the clamp-head domain of Rpo1N ( Figures 2D and 3 ) . Mass spectrometry analysis ( see Materials and Methods ) confirmed the presence of a previously reported RNAP subunit , named “component F” [12] , comprising 104 residues of which the 45-residue HTH motif constitutes an ordered fragment . Fitting of the electron density yielded to a satisfactory alignment ( Figures 2D and S1 ) . We rename this subunit Rpo13 , as RpoF has been used to refer to the distinct archaeal Rpb4 homolog . Uniquely in the archaeal RNAP , the Rpo13 subunit does not have an ortholog in the eukaryotic RNAP II . Of the approximately 370-kDa archaeal RNAP , subunits Rpo1 ( split into two subunits Rpo1N and Rpo1C ) and Rpo2 represent more than two-thirds of the mass and are equivalent to bacterial β′ and β and to the eukaryotic Rpb1 and Rpb2 [9 , 13] . These subunits are composed of different domains that perform specific roles during RNA polymerisation in the active site of the Rpo1N subunit ( catalytic residues D456 , D458 , and D460 are conserved across cellular RNAPs [2 , 8] ) . The second largest subunit , Rpo2 , contains three Zn2+ atoms ( two coordinated with His570 and with His696/His997 , respectively; the third located in the clamp ) . Its polypeptide chain is largely ordered , and it provides , with Rpo1 , the catalytic activity of the RNAP . Both subunits in the cellular RNAPs contain a double-Ψ β-barrel domain involved in the polymerization process , whose heterodimeric structure has been suggested as the ancestral core enzyme [13] . Subunits Rpo3 ( containing a 4Fe-FS cluster [9] ) , Rpo6 and Rpo11 constitute , along with Rpo1 and Rpo2 , the core RNAP , conserved across the three domains of life [8 , 9 , 13] . Structure-based phylogenetic analysis between the homologous components illustrates this evolutionary relationship ( Figure S2 ) and strengthens the idea of a transcription apparatus that has increased cellular specificity associated with the addition of new functional modules . The remaining known archaeal subunits Rpo4/7 , Rpo5 , Rpo10 , and Rpo12 , with homologs only in Eukarya ( class II subunits ) , decorate the core enzyme as shown in Figure 1 ( Rpo10 and Rpo12 each bind a Zn2+ ) . Of all the subunits common to Archaea/Eukarya , Rpo5/Rpb5 differs the most in size . Rpb5 is composed of a jaw and assembly domain [2] , of which only the latter is present in the archaeal Rpo5 ( which lacks the first ∼130 residues of Rpb5 ) . The absence of the jaw domain allows access to a positively charged groove between the assembly domain and helices 3 and 4 of the clamp-head domain ( see below and Figure 3A and 3B ) . The Rpo4/7 heterodimer , which is conditionally required for initiation [14] , protrudes from the main structure interacting mostly through Rpo6 and the C-terminus of Rpo1C ( Figure 1 ) . The Rpo4/7 stalk is highly mobile as judged by the electron density and normal mode analysis ( Figure 4 ) . Some weak density attributable to the C-terminus of subunit Rpo4 is visible and reminiscent of the position of the C-terminal helix 6 ( H6 ) observed in the isolated Rpo4/7 crystal structure from Methanococcus jannaschii [15] . This suggests that H6 can move from its location , possibly contributing to the interaction with accessory cofactors such as transcription factor E ( TFE ) [7 , 8] . The electron density maps reveal the clamp head domain ( residues 97–173 ) in the Rpo1N subunit to be mostly ordered ( residues 97–156 ) . This domain , absent from the recent archaeal X-ray structure [9] is located at the DNA-binding cleft ( Figure 2A ) , as is its eukaryotic counterpart . It adopts a fold similar to its eukaryotic ortholog and contains a Zn2+ ion chelated by C98 , C101 , and C146 ( Figure 2A ) . It also shows some differences including a longer HTH motif ( residues 107–140 ) that flexes by approximately 34° . This motif , together with the Rpo5 subunit , forms a cavity into which Rpo13 docks ( Figure 3B and 3C ) . The remaining portion of the Rpo1N structure is well ordered , showing a Zn2+ ion in the clamp core domain and a single Mg2+ ion in the active site [2] . Electron density corresponding to the jaw domain of the Rpo1C subunit is also visible . This domain is implicated in binding DNA downstream of the transcription start site [4] , and residues 147–236 have been modelled initially by reference to the eukaryotic polymerase ( see Materials and Methods and Figure 2B ) . The bridge helix in Rpo1N and the trigger loop in Rpo1C , which have been proposed to play critical roles in DNA translocation [3] , are respectively in a straight conformation ( albeit with some differences from that observed by Hirata and co-workers [9] [rmsd 0 . 8 Å , for 40 aligned Cα] ) and disordered . The location and the topology of the clamp-head and jaw domain in the Rpo1 subunit reinforce the structural similarity with Rpb1 of naked RNAP II . Until recently , it was believed that archaeal RNAPs from both the Crenarchaea and Euryarchaea kingdoms , the two main groups of Archaea , did not possess orthologs of Rpb8 [8 , 16] , but recent work has identified divergent homologs of Rpb8 in the Crenarchaea [1 , 17] . This subunit , Rpo8 ( 15 . 1 kDa; 132 residues ) , is seen for the first time in our current study and is a constitutive structural element of the RNAP complex ( Figures 1 and 2C ) . Rpo8 adopts an eight-stranded antiparallel β oligo-binding ( OB ) fold ( Figure 2C ) with the first three and last 15 residues disordered . It is located at a peripheral position ( Figure 1 ) , similar to eukaryotic Rpb8 , with which it shares 112 Cα equivalences ( out of 114 ) with 2 . 9 Å rmsd ( Figure S3 ) and 14% sequence identity ( the lowest sequence identity of all archaeal and eukaryotic subunits ) . Rpo8 interacts with subunit Rpo1N , sitting in the external crevice formed by residues 507–596 and burying a surface area of 1 , 470 Å2 , equivalent to the interaction of Rpb8 with Rpb1 ( Figure 2 ) . The shorter Ω-loop motif ( residues 63–69 ) is ordered , and the isosurface of electrostatic potential shows marked segregation of charges with a line of basic residues R20 , K24 , K52 , K54 , and K56 decorating the top of the molecule ( Figure S4 ) . Predictions from the amino acid sequence [18 , 19] indicate an ordered HTH core motif ( α1 and α2 ) with flexible N- and C-termini , respectively , predicted as mainly coil and α-helix ( α3 ) , suggesting a simple three-helix bundle protein prototypical of DNA binding proteins [20] with an N-terminal extension ( Figure 5A ) . The HTH motif of Rpo13 ( absent from the recent model of the RNAP from S . solfataricus [9] ) , fits between Rpo5 and the clamp-head domain of Rpo1N ( Figures 1 and 3 ) in the position equivalent to that occupied by residues 1377–1420 , in the β′ large subunit of the crystal structures of the RNAP from the bacteria Thermus aquaticus and T . thermophilus RNAP [21 , 22] ( Figure 3C ) . The corresponding sequence of this bacterial insertion is highly conserved within the Thermus-Deinococcus phylum , but there is also some detectable sequence similarity in other bacterial β′ sequences mainly of the Proteobacteria phylum . In T . aquaticus and T . thermophilus , this structure ( whose function has not yet been characterized ) folds into two antiparallel β strands followed by an α-helix; an organisation quite different from our Rpo13 ( Figure 3C ) . In eukaryotes , the equivalent locus is partially occupied by the eukaryote-specific Rpb5 jaw domain ( Figure 3B ) . Significantly , this domain is involved in downstream DNA binding [23] , and the entire subunit has also been implicated in contacting transcription factor II B [24] . We have used a normal-mode–based protocol [25] for structure refinement ( see Material and Methods ) . Although it is difficult to recognize biologically relevant modes per se , the principal modes present a simple dynamic picture of the RNAP , which might have relevance in vivo . The low-order modes include a pincer movement of the jaw-lobe module and clamp , in agreement with the structural variability found in static eukaryotic RNAP structures [2 , 26 , 27] , and a contraction of the same structural elements generating a “ratchet” of the HTH motif and rudder ( residues 278–297 ) in the clamp-core of Rpo1N; movements that can be detected by observing , for example , modes 2 , 28 , and 29 given in Protocols S1 and S2 . This conformational plasticity would facilitate the transition of the RNAP from the apo- to the DNA-bound form for transcription initiation [2] . The Rpo4/7 subunits also swing along the side of the polymerase , a flexibility underlining the multiple roles played by these subunits [8] . This analysis defines the catalytic site as a rigid ensemble relative to the rest of the structure ( Figure 4 ) , providing enzymatic precision at the heart of a flexible machine [28] . To gain insights into the assembly of the archaeal preinitiation complex , we have docked our intact RNAP onto the DNA–RNA hybrid visualized in the RNAP II transcribing complex [29] , the eukaryotic RNAP-TFIIB complex [5] , and the TFBc-TBP-DNA complex from Pyrococcus woesei [30] ( TFB and TBP , respectively , share 51% and 46% sequence identity with their S . shibatae orthologs ) ( see Figures 5B and 5C and Text S2 ) . The overall architecture of the archaeal preinitiation complex resembles the minimal initiating eukaryotic complex RNAP-TFIIB-TBP-DNA [5 , 31] , but differs by not requiring homolog basal factors TFIIH and TFIIF and by the influence of TFE [6 , 8] . Our structure and the preinitiation complex model provide a rationale for this minimal set of cofactors ( see Discussion below ) .
Our results clarify the evolutionary relationships of Archaea with Eukarya and Bacteria . The finding that Rpo8 is an integral component of the Sulfolobus enzyme , together with the ordered clamp-head and jaw domains in Rpo1 , underscores the fact that the crenarchaeal and eukaryotic RNAPs have conserved the same basic enzymatic platform even when the sequence identity is lower than 15% . This implies a closer structural ancestry between RNAPs from Crenarchaea and Eukaryotes . A major structural difference however is the presence of the carboxyl-terminal-domain ( CTD ) in eukaryotic Rpb1 . This feature presumably represents a later evolutionary acquisition , acting as a bolt-on module that facilitates coordination of eukaryote-specific cotranscriptional processing events such as capping , splicing , and polyadenylation . On the other hand , whereas archaeal RNAP structurally anticipates the enzymatic machinery of the eukaryotic systems , RNAPs from the order Sulfolobales ( and others from the Crenarchaea kingdom ) have acquired Rpo13 , a subunit that is not present in Eukarya and that corresponds architecturally to an insertion into the bacterial β′ subunit of T . aquaticus and T . thermophilus . Sequence analysis [32] shows that the Rpo13 gene has orthologs in the orders Sulfolobales and Desulfurococcales of the Crenarchaeota phylum , but not in Euryarchaea ( Figure S5 ) . We have detected Rpo13 as part of the RNAP in three Sulfolobus species: first in our structure from S . shibatae ( in both crystal forms , see Materials and Methods and Figure S6 ) , then in S . acidocaldarius [12] and finally in S . solfataricus where we have reanalyzed the electron density ( Figure S7 ) . These results indicate that Rpo13 constitutes a stable structural component of the enzyme . Furthermore , the topology and location of the ordered fragment of Rpo13 suggests a mechanism of action in the context of the preinitiation complex assembly model ( see below ) . Although the function of Rpo13 is still unknown , its location leads us to hypothesize roles at initiation and elongation . Rpo13 could facilitate transcription bubble formation once the archaeal preinitiation complex is formed ( modelled as in Figure 5B and 5C ) and the N-terminal domain of TFB has driven the DNA towards the RNAP active centre [5 , 33] . The visible C-terminus of Rpo13 is at about 7 Å distance from the phosphate group of the nucleotide at position +8 from the start site of the modelled non–template DNA strand ( Figure 5C ) . This close juxtaposition combined with the prediction of Rpo13 being a basic trihelical bundle protein , reminiscent of DNA recognition proteins , suggests that the third predicted helix of Rpo13 may interact with DNA . Additionally , the fact that Rpo13 has ten lysines in the last 20 residues supports an interaction of the predicted C-terminal α3 helix with negatively charged DNA rather than with the positively charged DNA binding cleft of Rpo1 ( Figures 3A , 5A , 5C , and 5D ) . At initiation , the α3 helix of Rpo13 could provide a lock point , against which the main body of the polymerase cleft can push or twist the DNA; during elongation these locking interactions would be overcome by the translocation forces but may still interfere with DNA duplex stability . In this manner , Rpo13 may perform some of the roles attributed to eukaryote-specific general transcription factors . In this view , the α1 and α2 helices of Rpo13 act as constitutive anchors onto the RNAP , whereas α3 confers additional functionality , prefiguring some of the capabilities of removable cofactors needed for eukaryotic initiation . Moreover , the presence of Rpo13 illustrates how the ancestral core enzyme was modulated by incorporation of novel subunits , a process that in eukaryotes has led to the emergence of three distinct classes of nuclear RNAPs .
Production and purification of archaeal RNAP are described elsewhere [34] . Briefly , S . shibatae cells were grown in three steps of 4 d each to a final optical density at 600 nm ( OD600 ) ≈ 3 . 0 . This growth served as inoculum for the final large-scale cell growth , carried on for additional 4 d and to an OD600 ≈ 4 . 0 . The RNA polymerase was purified from the cell pellet by dialysis , Q Sepharose chromatography , and Hi-Trap heparin column . Archaeal RNAP crystals were initially obtained with a microbatch under oil technique ( Hampton ) using purified RNAP at approximately 7 . 0 mg/ml in 150 mM KCl , 100 mM SrCl2 , 100 mM Na-Cacodylate ( pH 6 . 5 ) , and 12% PEG MME 5K . This initial condition was expanded using a hanging-drop vapour diffusion technique and several attempts were made to optimize the original fragile crystals by adding 1 mM Zn2+ to exploring different gradient concentration of PEG 20K . Different datasets were collected either from native or heavy-atom–soaked crystals . Useful data that contributed to the initial phasing came from two crystals , a native close to 3 . 5 Å and a W11 tungsten cluster soak close to 4 . 0 Å ( unpublished data ) , belonging to P212121 space group ( Crystal_1 ) with two RNAP complexes per asymmetric unit ( AU ) . A second native dataset was later collected from a crystal in P21212 space group ( Crystal_2 ) with one RNAP molecule in the AU . This was obtained by adding 5% glycerol to the above crystallization conditions and diffracted to a resolution of about 3 . 35 Å . All crystals were flash-frozen and the collected datasets indexed , integrated , and scaled using HKL [35] . A summary of the native data collection statistics is shown in Table 1 . Initially , the Crystal_1 structure was solved to a resolution of 6 Å by first finding a molecular replacement locked-rotation function solutions for two RNAP molecules in the asymmetric unit ( GLRF program [36] ) , and subsequently by finding a phase translation function solution ( MOLREP [37] ) utilizing low-resolution phases obtained experimentally from crystals soaked in W11 tungsten clusters ( SIRAS technique , SOLVE program [38] ) . Yeast RNAP polyalanine coordinates ( Protein Data Bank [PDB] entry 1EN0 ) were used as a search model . The phases to approximately 4 Å were then 2-fold averaged and solvent flattened using DM [37] allowing the initial manual rebuilding of the different subunits as alanine models . When the data from the crystal in P21212 space group ( Crystal_2 ) were obtained , cross-crystal averaging between the two crystal forms was performed in GAP ( unpublished program , D . I . Stuart and J . Grimes ) . Prior to this , rigid-body refinement of the initial polyalanine model was carried out in both crystal forms using REFMAC [37] and the correspondent 2Fo-Fc and Fo-Fc maps inspected for integrity of RNAP . The cross-averaged electron density map at 3 . 52 Å confirmed the presence of all subunits , including the Rpo8 and the additional density resembling a HTH motif close to Rpo1N ( residues 97–151 ) . The sequence for each archaeal subunit was determined by PCR-mediated cloning and sequencing ( see below ) and docked onto the RNAP polyalanine model . The model was then improved by iterative manual building and refinement as described in detail in Text S1 . When the coordinates of the RNAP structure from S . solfataricus ( PDB entry 2PMZ ) [9] became available , the refinement process accelerated , and we turned our attention to the higher resolution data ( 3 . 35 Å; Crystal_2 ) encouraged by its higher signal-to-noise ratio at 3 . 52 Å ( 2 . 5 vs . 2 . 0 of Crystal_1 ) and confident of the correct but incomplete new starting model ( PDB entry 2PMZ ) . We finalized the refinement of our RNAP structure against the data collected from the P21212 crystal by iterative manual adjustment of the model , normal-mode [25] and positional with B overall refinement in REFMAC [37] . A summary of the final statistics for Crystal_2 is shown in Table 1 . As a validation tool , we extended the refinement of the Crystal_1 RNAP model whose current statistics are also included in Table 1 . All major findings for the RNAP structure in the P21212 space group are observed in the P212121 structure including the presence of the Rpo13 subunit bound to the two RNAP molecules in the asymmetric unit ( Figure S6 ) . Coordinates and structure factors for both crystal forms have been deposited in the Protein Data Bank under ID codes 2WB1 ( Crystal_1 ) and 2WAQ ( Crystal_2 ) . Open reading frames for the S . shibatae RNAP subunits were amplified by PCR from genomic DNA using Pfu DNA polymerase prior to cloning in PCR script ( Stratagene ) and sequencing ( Geneservice ) . Primers were designed based on the conservation of flanking genes in S . solfataricus and S . tokodaii and are listed in Table S1 . Table S2 shows the sequence identity with S . solfataricus . Inspection of the electron density of neighbouring subunits and superimposition with known RNAP components excluded the 2Fo-Fc electron density map correspondent to the unknown HTH motif of being an ordered or cleaved fragment of an already identified RNAP subunit . This structural element is reminiscent of the HTH domain of basal and specific transcription factors including the archaeal TFE [39] and DNA-binding proteins [20 , 40] . However , biochemical data rule out the possibility that this represents a fragment of TFE ( unpublished data ) and its binding locus is inconsistent with it belonging to transcription factor S ( TFS ) [4] or TFB [5] . To identify the novel archaeal subunit , we carried out liquid chromatography-mass spectroscopy with peptide fingerprinting [LC MS/MS; ( HCTplus; Bruker Daltonics ) coupled to a HPLC system ( Ultimate; Dionex/LC-Packings ) ] of the sample used for crystallization at the Central Proteomics Facility Headington ( CPF , University of Oxford ) . Using the sequenced genome of S . solfataricus [41] through an in-house Mascot server [42] ( Matrixscience ) , we were able to fingerprint a protein component rich in lysine residues ( Uniprot: SSO0396 ) corresponding to a previously detected RNAP component of the 13-subunit RNAP from S . acidocaldarius [12] . This gene is cotranscribed with pcna3 ( a DNA replication accessory factor ) , a situation reminiscent of the clustering of genes of other Rpos and information processing components [43] . The peptide mapping was carried out on the trypsin-digested fractions corresponding to molecular weight bands between 5 and 25 kDa extracted from a SDS-polyacrylamide gradient gel electrophoresis of the RNAP used for crystallization . The 2Fo-Fc electron density supported a protein binding to the RNAP in a 1:1 ratio and the packing restraints suggested a molecule no larger than approximately 250 residues . The gene for the homologous protein in S . shibatae was then sequenced and used for secondary and disorder structure predictions and model building ( Figure 5A ) . The data search was rerun against our S . shibatae sequence database , and Figure S8 shows the Rpo13 peptides identified and the sequence coverage .
|
Transcription , the process of converting DNA into RNA ( which in turn is translated into proteins by ribosomes ) is carried out by the multisubunit RNA polymerase ( RNAP ) enzyme . Transcription is fundamental to all organisms across the three kingdoms of life—Eukarya , Bacteria , and Archaea—and can be divided into three major steps: initiation , transcription/elongation , and termination . Eukaryotes have three different nuclear RNAPs , whereas Archaea and Bacteria have one . Archaeal transcription is similar to that of eukaryotes , but initiation requires only two accessory proteins bound to DNA: transcription factor B ( TFB ) and TATA-box binding protein ( TBP ) . It is believed that studies of the archaeal enzyme may shed light on the more complex eukaryotic RNAP . Our complete structure of the archaeal RNAP from Sulfolobus shibatae has fully elucidated its architecture , confirming its close evolutionary relationship with the eukaryotic RNAP II and at the same time revealed a new subunit , Rpo13 , with no ortholog in the eukaryotic enzyme . The location and topology of Rpo13 allow us to suggest a mechanism by which Archaea bypass the additional eukaryotic cofactors required for transcription initiation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biophysics",
"biochemistry"
] |
2009
|
Evolution of Complex RNA Polymerases: The Complete Archaeal RNA Polymerase Structure
|
The suppression of protective Type 2 immunity is a principal factor driving the chronicity of helminth infections , and has been attributed to a range of Th2 cell-extrinsic immune-regulators . However , the intrinsic fate of parasite-specific Th2 cells within a chronic immune down-regulatory environment , and the resultant impact such fate changes may have on host resistance is unknown . We used IL-4gfp reporter mice to demonstrate that during chronic helminth infection with the filarial nematode Litomosoides sigmodontis , CD4+ Th2 cells are conditioned towards an intrinsically hypo-responsive phenotype , characterised by a loss of functional ability to proliferate and produce the cytokines IL-4 , IL-5 and IL-2 . Th2 cell hypo-responsiveness was a key element determining susceptibility to L . sigmodontis infection , and could be reversed in vivo by blockade of PD-1 resulting in long-term recovery of Th2 cell functional quality and enhanced resistance . Contrasting with T cell dysfunction in Type 1 settings , the control of Th2 cell hypo-responsiveness by PD-1 was mediated through PD-L2 , and not PD-L1 . Thus , intrinsic changes in Th2 cell quality leading to a functionally hypo-responsive phenotype play a key role in determining susceptibility to filarial infection , and the therapeutic manipulation of Th2 cell-intrinsic quality provides a potential avenue for promoting resistance to helminths .
Protective immunity to helminth parasites takes decades to acquire , if it develops at all , with over 1 billion people harbouring chronic infections [1] . Protection is mediated by the Th2 arm of immunity [2] , which is also responsible for causing allergic diseases such as asthma , atopic dermatitis , and allergic rhinitis , and types of fibrosis . A major reason for the failure in anti-helminth Th2 immunity is that the parasites immunosuppress their host , exemplified by host PBMC losing the ability to proliferate and produce Th2 cytokines , such as IL-4 and IL-5 , in response to parasite antigen [3] , [4] , [5] . Interestingly , this Th2 down-modulation has parallels with the modified Th2 response originally described in association with tolerance to allergens , and characterised by a switch from an inflammatory IgE response to an anti-inflammatory IgG4 and IL-10 response [6] , [7] . Thus , the regulatory pathways invoked by helminths can cross-regulate and protect against allergic diseases in humans and animal models [8] , [9] . As such , defining the mechanisms of immune down-regulation during helminth infections is of importance for the development of therapeutic strategies or vaccines to induce long-term protective anti-helminth immunity , and novel approaches for the treatment of allergies and fibrosis . Following the observations that neutralisation of IL-10 or TGF-β can restore the immune-responsiveness of PBMC from helminth-infected individuals [10] , [11] , studies have focussed on determining the extrinsic regulators that control Th2 cell function . From these , a variety of cell types have been shown to inhibit immunity to helminths and allergens [12] , including Foxp3+ regulatory T cells ( Tregs ) [13] , [14] , alternatively activated macrophages ( AAM ) [15] , [16] , DC [17] , [18] , and B cells [19] , [20] . However , the intrinsic fate of parasite-specific CD4+ Th2 cells within a chronic down-regulatory environment is largely unknown , even though the idea that helminth-elicited T cells become anergised during infection was postulated 20 years ago [21] . It is known that CD8+ T cells develop a functionally hypo-responsive phenotype in chronic Th1 infections , termed exhaustion [22] , and human helminth studies provide some evidence for the development of a form of Th2 cell-intrinsic dysfunction . PBMC from filariasis patients display a gene expression profile characteristic of anergic T cells [3] , and T cells from individuals with chronic nematode infections show defects in TCR signalling [23] . Recently , a murine study on the down-modulation of pathogenic Th2 responses during Schistosoma mansoni infection provided the first formal demonstration that CD4+ Th2 effector cells can develop an intrinsically hypo-responsive phenotype [24] . Thus , there is a question of whether individuals fail to acquire protective immunity to helminths because their Th2 cells become intrinsically dysfunctional . We previously used a murine model of filariasis , Litomosoides sigmodontis infection of permissive BALB/c mice , to define the immune regulatory mechanisms that prevent helminth killing . We demonstrated that purified CD4+ T cells lose the ability to proliferate and produce Th2 cytokines to parasite antigen as infection progresses [25] . This loss of function within the CD4+ T cell compartment was independent of Foxp3+ Tregs and IL-10 indicating that , alongside extrinsic regulation by Foxp3+ Tregs [24] , [25] , [26] , susceptibility to filarial infection is associated with an intrinsic functional change within the CD4+ Th2 cells . Thus , in this study we employed IL-4gfp 4get reporter mice [27] to track and determine the fate of Th2 cells during L . sigmodontis infection . We found that , whilst increasing in number , the IL-4gfp+CD4+ Th2 cells became conditioned towards a functionally hypo-responsive phenotype as infection progressed denoted by a progressive loss in their intrinsic ability to produce the cytokines IL-4 , IL-5 and IL-2 . The onset of hypo-responsiveness was accompanied by increased expression of PD-1 by IL-4gfp+ Th2 cells , and in vivo PD-1 blockade led to increased resistance to infection and a long-term increase in Th2 cell functional quality . In contrast to viral and protozoan infections [28] , [29] , [30] , the control of T cell quality by PD-1 was driven through its interactions with PD-L2 , and not PD-L1 . Thus , intrinsic changes in Th2 cell functional quality play an important role in defining resistance and susceptibility to filarial nematodes , and it is possible to enhance resistance to infection by therapeutically manipulating Th2 cell quality .
Susceptibility to L . sigmodontis infection is associated with a loss of responsiveness by CD4+ T cells at the infection site , the pleural cavity ( PC ) , such that as infection progresses purified PC CD4+ T cells show reduced L . sigmodontis antigen ( LsAg ) -specific proliferative and cytokine responses in vitro [25] , [26] . This down-modulation within the CD4+ T cell population was independent of extrinsic regulation by CD4+CD25+Foxp3+ Tregs or IL-10 , suggesting that it represented either a contraction in the number of Th2 cells , or a qualitative change in the intrinsic function of the responding Th2 cells . Identifying parasite-specific T cells during helminth infection is challenging due to the polyclonal nature of the response and a lack of knowledge of the specific antigens recognised . Thus , to determine whether changes in Th2 cell quantity or intrinsic functional quality explain the observed CD4+ T cell down-modulation during L . sigmodontis infection we employed BALB/c IL-4gfp 4get reporter mice [27] . IL-4gfp+ T cells elicited during acute infection with the nematode Nippostrongylus brasiliensis are parasite specific [31] , and so IL-4gfp expression by CD4+ T cells was used as a tool for tracking L . sigmodontis-specific Th2 cells , with a caveat that IL-4gfp is a surrogate marker and a small proportion of IL-4gfp+ T cells may not be L . sigmodontis specific . Importantly , once committed to the Th2 lineage , T cells store IL-4 mRNA and the production of IL-4 protein is controlled post-transcriptionally [32] . IL-4gfp 4get mice report the presence of IL-4 mRNA independently of IL-4 protein [32] , [33] , meaning that the number of committed IL-4 mRNA+ Th2 cells can be quantified by GFP expression , whilst further assays can be used to independently assess their functional quality . BALB/c IL-4gfp mice were infected s . c . with L . sigmodontis larvae . From the skin the larvae migrate via the lymphatics to the PC by d 4 post-infection ( pi ) where they undergo a series of moults reaching the adult stage around d 25 pi , and become sexually mature with the females releasing transmission stage microfilaria ( Mf ) approximately 55 d pi . A patent infection is defined as having mature adult parasites within the PC , and Mf circulating within the blood stream [34] . At the infection site there was a gradual increase in the proportion of IL-4gfp+ Th2 cells as infection progressed , culminating in 35% of CD4+ T cells expressing GFP by day 60 ( Figure 1A and B ) . This translated to a significant elevation of total numbers of IL-4gfp+ Th2 cells by d 20 pi , which was maintained until d 60 pi ( Fig . 1C ) . Increases in the proportions of IL-4gfp+ Th2 cells were also seen in the thoracic LN ( tLN ) and spleen ( Figure 1D and F ) , albeit to a lesser extent , and only resulted in significantly increased total numbers of IL-4gfp+ Th2 cell in the tLN ( Figure 1E and G ) . Thus , the down-modulation of CD4+ T cell responsiveness within the PC was not caused by a loss of Th2 cells . To determine whether Th2 cell functional quality declined during infection , intra-cellular staining was used to define the proportion of IL-4gfp+ Th2 cells actively producing IL-4 protein ( Figure 2A ) , as well as IL-5 and IL-2 ( Figure S1 ) , in response to PMA and ionomycin stimulation . Contrasting with the increase in numbers of IL-4gfp+ Th2 cells within the PC , there was a 69% reduction in the proportion of IL-4gfp+ Th2 cells making IL-4 protein between d 20 and d 40 , which was still apparent at d 60 ( Figure 2B ) . The proportion of IL-4gfp+ Th2 cells producing IL-5 protein also declined by 70% , although with delayed kinetics as the reduction did not occur until d 60 , indicating a staggered loss of cytokine production ( Figure 2C ) . Similarly , there was a 79% decrease in the proportion making IL-2 between d 20 and d 60 ( Figure 2D ) . Distal to the PC , the proportion of IL-4gfp+ Th2 cells capable of producing IL-4 protein within the tLN remained unaffected ( Figure 2E ) , and despite a transient decrease at d 40 in the spleen the proportion of IL-4+ IL-4gfp+ Th2 cells at d 60 pi was equivalent to d 20 ( Figure 2H ) . In contrast , the production of IL-5 and IL-2 proteins by IL-4gfp+ Th2 cells was impaired at d 60 in both the tLN and spleen ( Figure 2 F , G , I and J ) . Thus , the decline in CD4+ T cell responsiveness observed during chronic L . sigmodontis infection represents a step-wise intrinsic loss of functional ability of IL-4gfp+ Th2 cells to produce cytokines , rather than a decrease in the total number or proportion of Th2 cells . This hypo-responsive Th2 cell phenotype is most prominent at the infection site , but to a lesser extent radiates out to the draining LN and spleen . Co-inhibition through the PD-1 pathway leads to the functional exhaustion of CD8+ T cells during chronic immune challenge [22] , [28] , and is involved in the inhibition of Th2 responses during helminth infections [35] , [36] , [37] , [38] . To investigate whether L . sigmodontis-induced Th2 cell hypo-responsiveness was associated with PD-1 co-inhibition , the expression of PD-1 by IL-4gfp+ Th2 cells was assessed . At d 20 pi , when the IL-4gfp+ Th2 cells were still functionally active , there was no change in the proportion of PC IL-4gfp+ Th2 cells expressing PD-1 ( Figure 3A ) . However , concomitant with the onset of hypo-responsiveness , there was a two-fold increase in the proportion of IL-4gfp+ Th2 cells expressing PD-1 at d 40 pi . PD-1 expression remained elevated until d 60 ( Figure 3A ) , and the mean fluorescence intensity of PD-1 expression on IL-4gfp+ Th2 cells increased with similar kinetics ( Figure 3B ) . When PD-1 expression by IL-4gfp+ Th2 cells was compared to production of IL-4 protein , the majority of IL-4 producing Th2 cells at d 20 were PD-1 negative , and the enhanced PD-1 expression at d 40 and 60 associated with the loss of IL-4 protein ( Figure 3C ) . T follicular helper ( Tfh ) cells are IL-4gfp+ and express PD-1 during helminth infection [39] , [40] , [41] , and as expected the increases in tLN IL-4gfp+ T cells observed during L . sigmodontis infection represented an expansion of both IL-4gfp+CXCR5− Th2 cells and IL-4gfphighCXCR5+ Tfh cells ( Figure 3D ) . IL-4gfphighCXCR5+ Tfh cells from naïve mice constitutively expressed high levels of PD-1 and there was no change upon infection ( data not shown ) . In contrast , infection with L . sigmodontis significantly increased the percentage of IL-4gfp+CXCR5− Th2 cells expressing PD-1 from d 40 onwards ( Figure 3E ) . To test the hypothesis that blocking PD-1 signalling on the hypo-responsive Th2 cells in vitro could re-activate their functional responsiveness , IL-4gfp+ Th2 cells were purified from the PC 60 d post-L . sigmodontis infection and restimulated with LsAg in the presence of an anti-PD-1 blocking mAb [42] using irradiated naïve splenocytes as APC . Due to the low number of IL-4gfp+ T cells present within the PC it was necessary to pool cells from 10–15 mice to obtain sufficient cell numbers . Significantly increased LsAg-specific proliferation and elevated IL-5 production was seen upon addition of the anti-PD-1 mAb ( Figure 3F and G ) , indicating that PD-1 blockade can restore the function of committed Th2 cells . Thus , Th2 cell hypo-responsiveness is associated with increased expression of PD-1 by IL-4gfp+ Th2 cells in both the PC and tLN , and blocking PD-1 in vitro increases the antigen-specific capacity of PC IL-4gfp+ Th2 cells to proliferate and produce IL-5 . To directly test whether co-inhibition through the PD-1 pathway inhibits protective immunity , L . sigmodontis infection was allowed to establish within susceptible BALB/c mice and PD-1 activity blocked from d 28–43 pi using a neutralising anti-PD-1 mAb ( Figure 4A ) . PD-1 blockade impaired the ability of L . sigmodontis to develop a fully patent infection as the incidence and levels of blood Mf were significantly reduced in anti-PD-1 treated mice compared to control mice at d 68 pi ( Figure 4B and Table 1 ) . As there was no effect of treatment on the number of adult parasites recovered at d 60 pi ( Figure 4C ) , we scored the uterine egg and Mf contents of female parasites to determine whether PD-1 blockade reduced blood Mf by inhibiting fecundity . Changes in helminth fecundity are often a sensitive and quantitative measure of the efficacy of host immunity , even when it is insufficient to kill adult parasites [43] . There was a significant reduction in the number of healthy uterine eggs within female parasites from PD-1 treated mice at d 60 pi ( Figure 4D ) . In addition , the number of female parasites with Mf within their uteri was reduced three-fold following PD-1 treatment ( Table 1 ) , although those with uterine Mf tended to have similar levels as female parasites from the IgG controls ( Figure S2A ) . Thus , in vivo PD-1 blockade promotes host resistance to established L . sigmodontis infection resulting in impaired fitness and fecundity in a proportion of the female parasites , and reduced levels and incidence of circulating transmission stage Mf within the host's blood . PD-1 blockade could enhance protective immunity to L . sigmodontis by restoring the functional quality of hypo-responsive Th2 cells and/or by increasing the overall quantity of Th2 cells . To address this we treated L . sigmodontis infected BALB/c IL-4gfp reporter mice with an anti-PD-1 blocking mAb from d 28–43 pi and quantified the number and antigen-responsiveness of IL-4gfp+ Th2 cells at d 60 pi ( Figure 4A ) . No differences were found in the proportion or total number of IL-4gfp+ Th2 cells within the PC or tLN at d 60 pi ( Figure 5A–D ) , indicating that PD-1 blockade does not result in a long-term elevation in Th2 cell numbers . To examine if PD-1 blockade increased the antigen-specific functional quality of the hypo-responsive Th2 cells , IL-4gfp+ Th2 cells were purified from the PC and tLN of control and PD-1 treated mice 60 d pi and equal numbers of Th2 cells were restimulated in vitro with LsAg using naïve irradiated splenocytes as APC . Due to the low number of IL-4gfp+ T cells present within the PC it was necessary to perform the assays on pooled cells from 6–10 mice . PC IL-4gfp+ Th2 cells purified from anti-PD-1 treated mice showed significantly increased antigen-specific proliferation and elevated IL-5 production compared to IL-4gfp+ Th2 cells from control mice ( Figure 5E and F ) . PD-1 blockade also increased the capacity of purified tLN IL-4gfp+ Th2 cells to secrete IL-5 in response to LsAg at d 60 ( Figure 5G ) . LsAg-specific production of IL-4 , IL-10 and IFN-γ by tLN and PC IL-4gfp+ Th2 cells was not consistently detectable ( data not shown ) . Thus , PD-1 blockade results in a long-term enhancement of Th2 immunity by augmenting the functional quality of parasite-specific Th2 cells , rather than increasing the overall number of Th2 cells . During chronic viral infections PD-1 blockade acts directly on exhausted CD8+ T cells to restore their function [28] . Similarly , our data showed that in vitro PD-1 blockade directly enhanced the functional quality of L . sigmodontis-specific hypo-responsive IL-4gfp+ Th2 cells ( Figure 3F and G ) , and in vivo blockade led to increased antigen-specific responsiveness of IL-4gfp+ Th2 cells 20 d after treatment had finished . This predicts that in vivo PD-1 blockade during L . sigmodontis infection would initially enhance the functional quality of existing IL-4gfp+ Th2 effector cells within the PC . However , when PC Th2 cell responses were assayed immediately following treatment ( d 40 pi , Figure 4A ) there were no increases in the proportion or total numbers of IL-4gfp+ Th2 cells within the PC ( Figure 6A and B ) . There was also no increase in the proportion of IL-4gfp+ Th2 cells capable of producing IL-4 or IL-5 protein following stimulation with PMA and ionomycin ( Figure 6C and D ) . In contrast , PD-1 blockade caused a 2-fold increase in the proportion and total numbers of IL-4gfp+ T cells within the tLN ( Figure 6E and F ) , although again had no impact on the proportion of IL-4gfp+ Th2 cells producing IL-4 or IL-5 protein ( Figure 6G and H ) . Consistent with the expression pattern of PD-1 , the increase in tLN IL-4gfp+ T cells was caused by an expansion of both IL-4gfp+CXCR5− Th2 cells and IL-4gfphighCXCR5+ Tfh cells , with IL-4gfp+CXCR5− Th2 cells accounting for 44% of the expansion ( data not shown ) . These data suggest that , although in the long-term PD-1 blockade increased the antigen-specific functional quality of IL-4gfp+ Th2 cells at the infection site , anti-PD-1 treatment did not recover the responsiveness of IL-4gfp+ Th2 cells to PMA and ionomycin . Instead it initially enhanced Type 2 responses within the tLN resulting in a temporary increase in the number of IL-4gfp+ Th2 and Tfh cells . PD-1 interacts with two ligands , PD-L1 and PD-L2 [44] , and to identify through which ligand PD-1 was acting L . sigmodontis infected BALB/c mice were treated with blocking anti-PD-L1 and/or anti-PD-L2 mAbs [45] from d 28–43 pi ( Figure 4A ) . At d 40 pi , when PD-1 blockade results in an expansion of IL-4gfp+ Th2 cells within the tLN ( Figure 6E and F ) , significantly increased numbers of IL-4 and IL-5 producing CD4+ T cells were found following combined blockade of PD-L1 and PD-L2 ( Figure 7A and B ) . Blockade of PD-L1 or PD-L2 alone had no effect on the numbers of IL-4 and IL-5 producing CD4+ T cells , indicating that PD-L1 and PD-L2 synergise to regulate the expansion of IL-4 and IL-5 secreting T cells within the tLN . In contrast , blockade of PD-L2 alone was sufficient to enhance resistance and impair the development of patent infections , demonstrated by a significant two-fold reduction in the incidence of mice with Mf within their blood at d 68 pi compared to IgG controls ( Table 2 ) . This was associated with a significantly reduced incidence of Mf in the pleural cavity , suggesting a lower release of Mf by female parasites . Interestingly , although mice treated with both anti-PD-L1 and anti-PD-L2 had a lower incidence of blood Mf , PD-L1 neutralisation alone resulted in a trend towards an increased number of mice harbouring blood Mf . This suggests that PD-L1 may promote rather than inhibit protective immunity to L . sigmodontis , but that the inhibitory role of PD-L2 is dominant . Whilst anti-PD-L2 treatment significantly reduced the number of mice developing patent infections , those that presented with circulating Mf had similar levels within the blood and pleural cavity to the IgG control group ( Figure S2B and C ) . The increased resistance resulting from blockade of PD-L2 was associated with significantly elevated production of IL-5 protein ( Figure 7C ) , as well as IL-4 ( Figure 7D ) , by tLN cells restimulated in vitro with LsAg . Thus , while PD-L1 and PD-L2 act synergistically to control Th2 cell expansion in the tLN , PD-L2 plays the dominant role in dampening IL-4 and IL-5 production and resistance towards L . sigmodontis . Alternatively activated macrophages can inhibit Th2 responses to helminths through PD-L1 and PD-L2 [37] or PD-L2 alone [35] . Expression of PD-L1 on macrophages , independent of alternate activation , also inhibits T cell responses to S . mansoni [36] . AAM are elicited during L . sigmodontis infection resulting in T cell suppression [16] , suggesting that they could drive the hypo-responsive Th2 cell phenotype via PD-L1 or PD-L2 . To test this , the expression of PD-L1 and PD-L2 on F4/80high pleural cavity AAM was assessed during L . sigmodontis infection . Analysis was performed at d 60 pi when PC derived F4/80high macrophages are known to be alternatively activated [16] . Although F4/80high macrophages from naïve mice did not express PD-L1 or PD-L2 constitutively , levels of both were up-regulated 11-fold following infection ( Figure 8A and B ) . To determine whether AAM inhibit Th2 cells via PD-L1 and/or PD-L2 , we purified and restimulated d 60 PC IL-4gfp+CD4+ Th2 cells with LsAg in the presence of d 60 PC AAM or naïve control macrophages . Irradiated naïve splenocytes were used as APC . The ability of the hypo-responsive IL-4gfp+ Th2 cells to proliferate in response to LsAg was then assessed following the addition of neutralising antibodies to PD-1 , PD-L1 and PD-L2 . In the presence of AAM , the LsAg-specific proliferation of IL-4gfp+CD4+ Th2 cells was significantly reduced compared to culture with naïve control macrophages confirming that the AAM were suppressive ( Figure 8C ) . However , blocking PD-1 , PD-L1 , PD-L2 , or a combination of PD-L1 and PD-L2 , failed to restore LsAg-specific proliferation ( Fig . 8C ) , indicating that AAM-mediated suppression of proliferation was not via the PD-1 pathway . Similarly , L . sigmodontis-elicited AAM inhibited the OVA-specific proliferation of naïve DO11 . 10 T cells independently of PD-1 , PD-L1 and PD-L2 ( Figure 8D ) . Consistent with our previous work showing that AAM only inhibit T cell proliferation and not cytokine production [16] , the addition of AAM did not reduce Th2 cell production of IL-5 or IL-4 ( data not shown ) . Thus , L . sigmodontis-elicited AAM do not suppress the antigen-specific proliferation of committed Th2 cells or naïve T cells via the PD-1 pathway .
Suppression of protective immunity during helminth infections is known to involve a wide range of Th2 cell extrinsic immune regulators [2] , [12] . However , the intrinsic fate of parasite-specific Th2 cells within a chronic immune down-regulatory environment , and the resultant impact such fate changes may have on host resistance is unknown . In this study we used IL-4gfp reporter mice to demonstrate that during chronic filarial nematode infection CD4+ Th2 cells are conditioned towards an intrinsically hypo-responsive phenotype , characterised by a loss of functional ability to proliferate and produce IL-4 , IL-5 and IL-2 cytokines . The development of Th2 cell hypo-responsiveness was a key element in determining susceptibility to L . sigmodontis infection , and could be reversed in vivo by blockade of the PD-1/PD-L2 pathway resulting in the long-term recovery of Th2 cell functional quality and enhanced resistance . The hypo-responsive Th2 cell phenotype during L . sigmodontis infection had some parallels with T cell exhaustion , which leads to impaired Th1 immunity towards viruses [28] and protozoan parasites [29] , [30] . Similar to exhaustion , Th2 cell hypo-responsiveness was mediated through PD-1 co-inhibition , and was characterised by a sequential loss of cytokine production with IL-4 being lost prior to IL-5 . In the future it will be important to confirm whether Th2 cell hypo-responsiveness also extends to other Th2 cytokines , such as IL-13 , as limited cell numbers restricted the cytokines we could measure in this study . Alongside the similarities to exhaustion there were also notable differences . PD-1 predominantly mediates CD8+ T cell exhaustion via interactions with PD-L1 [28] , [30] , whereas Th2 hypo-responsiveness was driven through interactions with PD-L2 . This preferential regulation of Type 2 immunity by PD-L2 is consistent with its expression being specifically induced by IL-4 and STAT-6 signalling , contrasting with PD-L1 , which is preferentially regulated by Type 1 stimuli [46] , [47] . Also , PD-1 interactions with PD-L1 are actively required for maintaining exhaustion , with PD-L1 blockade immediately boosting the functional quality of exhausted CD8+ T cells [28] . Although in vitro PD-1 blockade enhanced the antigen-specific ability of hypo-responsive Th2 cells to produce Th2 cytokines , stimulating them with PMA and ionomycin , which bypasses the PD-1 pathway , failed to recover their function . Similarly , the Th2 cells remained hypo-responsive to PMA and ionomycin stimulation immediately following in vivo PD-1 blockade , although it led to a recovery in their functional ability to respond to parasite antigens later in infection . Thus , the hypo-responsive Th2 cell phenotype is likely distinct from exhaustion , and appears to be more deep-seated , involving more mechanisms , than PD-1 co-inhibition alone . The disparity between GFP expression , which marks IL-4 mRNA , and IL-4 protein suggests that the loss of cytokine production by hypo-responsive Th2 cells is due to post-transcriptional regulation , which is an essential step in the production of Th2 cytokines [32] . This has parallels with anergic self-reactive T cells that express mRNA for effector cytokines such as IFN-γ , IL-4 , and IL-13 , but are unable to produce protein because translation is blocked by AU-rich elements within the cytokine 3′UTRs [48] . The description of an anergic molecular signature within the PBMC of filariasis patients and the findings that addition of IL-2 can restore the in vitro immune responsiveness of human PBMC [3] , [49] , reinforce the idea that Th2 hypo-responsiveness is a form of anergy . If so , it is more likely to represent a form of adaptive tolerance than classical clonal anergy as it is not rescued by stimulation with PMA and ionomycin , and results in the shutdown of multiple cytokines , not just IL-2 [50] . Similarly , during S . mansoni infection the anergy factor GRAIL is responsible for driving Th2 cells towards an intrinsically hypo-responsive state with characteristics of adaptive tolerance [24] . Interestingly , there are differences in Th2 cell hypo-responsiveness during filariasis and schistomiasis . Firstly , GRAIL is not part of the anergic signature of PBMC from filariasis patients [3] . Secondly , S . mansoni induced Th2 cell hypo-responsiveness does not relate to PD-1 [24] . Thus , while an intrinsic functional shut-down of Th2 cells appears common to different chronic helminth infections , it may involve distinct mechanisms . Consistent with the hypothesis that multiple factors maintain Th2 cell hypo-responsiveness , in vivo PD-1 blockade failed to initially expand or recover the function of the hypo-responsive Th2 cells at the infection site . Instead it first caused a temporary expansion of CXCR5−IL-4gfp+ Th2 cells and CXCR5+ IL-4gfp+ Tfh cells within the draining LN , followed by the appearance of functionally superior IL-4gfp+ Th2 cells at the infection site 20 days later . In contrast to the PC , CD4+ T cells in the LN did not lose the ability to produce IL-4 protein during L . sigmodontis infection . Tfh cells are the predominant source of IL-4 in the LN and demonstrate distinct control of IL-4 gene expression compared to Th2 cells [39] , [40] , [41] , [51] . Thus , similar to viral infections where Tfh cells do not become exhausted [52] , Tfh cells may remain functionally responsive during chronic helminth infection and maintain a source of IL-4 . It is interesting to speculate that , rather than directly rescuing the hypo-responsive Th2 cells , PD-1 blockade acted by expanding a reservoir of still responsive IL-4gfp+ T cells within the LN , either Tfh or Th2 cells , that over time replaced the unresponsive Th2 cells at the infection site . Alternatively , PD-1 can inhibit T cell priming [53] and so its blockade may have favoured the generation of new responsive Th2 cells . The involvement of PD-L2 , rather than PD-L1 , indicates that professional immune cells regulate CD4+ Th2 cell hypo-responsiveness . Suppression of T cell responses by PD-1 during helminth infections has mainly been attributed to macrophages expressing PD-L1 and/or PD-L2 , and the PD-1 pathway has been shown to be an important mechanism of suppression by AAM [35] , [36] . Although L . sigmodontis infection induces suppressive AAM [16] , the proliferative suppression of Th2 cells and naïve T cells by L . sigmodontis-elicited AAM was independent of PD-1 , PD-L1 and PD-L2 . Thus , whilst AAM are clearly able to suppress T cells via the PD-1 pathway they do not do so in all Th2 contexts , and it is not their dominant mechanism of suppression during L . sigmodontis infection . Furthermore , as we have previously shown [16] , suppression by L . sigmodontis-elicited AAM was restricted to T cell proliferation and did not inhibit the production of Th2 cell cytokines . As reduced Th2 cytokines were a defining characteristic of hypo-responsive Th2 cells it indicates that AAM are not driving hypo-responsiveness , although in vivo AAM studies are required to confirm our in vitro findings . Interestingly , B cell deficient mice are more resistant to primary L . sigmodontis infection indicating a regulatory role for B cells [54] . B cells can express PD-L2 [44] and up-regulate it during L . sigmodontis infection ( van der Werf , Taylor , unpublished data ) raising the possibility that B cells are involved in conditioning Th2 cells towards hypo-responsiveness . Alternate candidates that may influence the intrinsic functional quality of Th2 cells include DC and Foxp3+ Tregs . The development of functionally impaired CD4+ Th2 cells provides a potential explanation for why protective memory to helminths takes decades to develop in humans [14] . Hypo-responsive Th2 cells may fail to develop into memory cells as seen with exhausted CD8+ T cells [22] , and consistent with this filariasis patients show contractions in their central memory CD4+ T cell pool [55] . Alternatively , a tolerised memory response may develop as anergic T cells can show long-term survival and maintain their unresponsive phenotype even in the absence of antigen [56] . A failed or tolerised memory response may also explain why helminth-infected individuals become rapidly re-infected following drug clearance , even though some aspects of immune suppression are lifted . PD-1 blockade in combination with drug treatments may thus represent a new strategy for restoring protective Th2 memory , particularly as we find PD-1 blockade has a long-term effect on Th2 cell quality and it has been successfully used in clinical trials to treat cancer [57] , [58] . Alternate targets include GITR , as providing co-stimulation through GITR increases the functional quality of L . sigmodontis specific Th2 cells [59] , and CTLA-4 , which promotes the expression of T cell anergy factors and inhibits protective Th2 immunity during filarial infections [3] , [26] . The development of Th2 hypo-responsiveness also has implications for vaccine development . Even the best live-attenuated filarial vaccines are only 70% effective [60] , meaning that residual infections could condition vaccine-elicited Th2 cells towards hypo-responsiveness resulting in vaccine failure . Altogether , our data demonstrates that intrinsic changes in Th2 cell quality lead to the development of a functionally hypo-responsive phenotype that plays a key role in determining susceptibility to filarial nematode infection , and that can be therapeutically manipulated to promote resistance . Alongside its relevance to the treatment of helminth infections , a deeper understanding of how Th2 cells are conditioned towards hypo-responsiveness will help define the checkpoints that determine whether a T cell remains inflammatory or becomes tolerised during chronic immune challenge . This may help determine why Th2 cells fail to shutdown naturally in settings of chronic pathology , such as in allergic inflammation or fibrosis , and potentially lead to novel approaches for tolerising pathogenic Th2 cells .
All animal work was approved by the University of Edinburgh Ethics Committee ( PL02-10 ) and by the UK Home Office ( PPL60/4104 ) , and conducted in accordance with the Animals ( Scientific Procedures ) Act 1986 . Female BALB/c and IL-4gfp 4get reporter mice on the BALB/c background ( courtesy of Markus Mohrs , The Trudeau Institute ) [27] were bred in-house and maintained under specific pathogen-free conditions at the University of Edinburgh . Mice were used at 6–12 weeks of age . The L . sigmodontis life cycle was maintained in gerbils using the mite vector Ornithonyssus bacoti [61] . Mice were infected s . c . on the upper back with 30 L . sigmodontis L3 larvae . Adult parasites were recovered by lavage and fixed in 70% ethanol for morphological analysis . The analysis of fecundity of female L . sigmodontis parasites was performed as previously [43] . The numbers of healthy eggs and Mf within the anterior , median and posterior of the uterus were semi-quantitatively scored on scales of 0–5 . Each region's scores were summed giving a total possible score of 15 . To quantify blood Mf , 30 µL of tail blood was collected in FACS lysing solution ( Becton-Dickinson ) . L . sigmodontis antigen ( LsAg ) was prepared by collecting the PBS-soluble fraction of homogenized adult male and female worms . Mice received i . p . injections of 250 µg of blocking anti-PD-1 mAb ( RMP1-14 , Bioxcell ) , 250 µg of blocking anti-PD-L2 mAb ( Ty25 , Bioxcell ) or 200 µg of blocking anti-PD-L1 mAb ( MIH5 , in house ) every three days from d28–43 pi An equivalent dose of rat IgG ( Sigma-Aldrich ) was used as control . The parathymic , posterior , mediastinal and paravertebral LN , were taken as a source of tLN draining the PC . PC cells were recovered by lavage . TLN and spleen cells were dissociated and washed in RPMI-1640 ( invitrogen ) supplemented with 0 . 5% mouse sera ( Caltag-Medsystems ) , 100 U/ml penicillin , 100 µg/ml streptomycin and 2 mM L-glutamine . To purify GFP+CD4+ T cells from IL-4gfp mice PC or tLN cells were enriched for CD4+ T cells by magnetic negative selection ( DynaMag , Dynal ) using anti-CD8 ( 53–6 . 72 ) , anti-B220 ( RAB632 ) , anti-MHC class II ( M5/114 . 15 . 2 ) , anti-Gr1 ( RB6-8C5 ) and anti-F4/80 ( A3-1 ) , followed by sheep anti-rat IgG Dynal Beads ( Invitrogen ) . Cells were stained with allophycocyanine-conjugated anti-CD4 ( RM4-5 ) . To purify GFP+CD4+ T cells from anti-PD-1 treated mice cells were stained with phycoerythrin-conjugated anti-CD4 followed by positive magnetic section with anti-phycoerythrin MicroBeads ( Milenyi Biotec ) . GFP+CD4+ T cells were then purified using a FACSAria flow sorter ( Becton-Dickinson ) . On average , sorted cells were 98 . 3% positive for CD4 , of which 97 . 6% were GFP+ . Due to limited cell numbers it was necessary to pool CD4+GFP+ T cells from 10–15 mice to obtain sufficient numbers . Whole tLN cells were cultured at 5×105 cells/well and spleen cells at 1×106 cells/well in 96 well plates ( Nunc ) . Purified GFP+CD4+ T cells were cultured at 5–10×104 cells/well with 1×106 irradiated ( 30 Gy ) naïve splenocytes . For in vitro restimulations , cells were cultured in medium alone or with 10 µg/ml LsAg for 72 hours followed by addition of 1 µCi/well [Methyl-3H]-Thymidine ( PerkinElmer ) for 16 h to measure proliferation . Blocking antibodies against PD-1 , PD-L1 and PD-L2 were used at 20 µg/ml as detailed in the results . For macrophage suppression assays , PC cells were adhered to 96-well flat-bottom plates at 1×105 cells/well for 2 h at 37°C and the non-adherent fraction rinsed off . GFP+CD4+ T cells or DO11 . 10 CD4+ T cells were added at 5×104 cells/well and after 72 h the cultures were pulsed with thymidine as described . DO11 . 10 cells were restimulated with 0 . 5 µg/ml OVA peptide ( ISQAVHAAHAEINEAGR ) from Advanced Biotechnology Centre ( Imperial School of Medicine , London , U . K . ) . For measurement of intra-cellular cytokines cells were stimulated for 4 hours with 0 . 5 µg/ml PMA ( Sigma-Aldrich ) and 1 µg/ml Ionomycin , with 10 µg/ml Brefeldin A added for the final 2 hours ( all from Sigma-Aldrich ) . The following antibodies were used: Alexafluor700-conjugated anti-CD4 ( RM4-5 ) , polyclonal anti-GFP ( Ebioscience ) , Alexafluor488-conjugated goat anti-rabbit IgG ( Invitrogen ) , eFluor450-conjugated anti-IL-2 ( JES6-5H4 , Ebioscience ) , phycoerythrin-conjugated anti-IL-4 ( 11B11 , Biolegend ) , allophycocyanine-conjugated anti-IL-5 ( TRFK5 , Biolegend ) , phycoerythrin-conjugated or biotinylated anti-PD-1 ( J43 , Ebioscience ) , biotinylated anti-PD-L1 ( MIH5 , Ebioscience ) , phycoerythrin-conjugated anti-PD-L2 ( Ty25 , Ebioscience ) , biotinylated anti-CXCR5 ( RF8B2 , BD Biosciences ) and allophycocyanine-conjugated streptavidin ( Biolegend ) . Non-specific binding was blocked with 4 µg of rat IgG/1×106 cells . For intracellular cytokine staining dead cells were excluded using Aqua Dead Cell Stainkit ( Molecular Probes ) , and the cells fixed and permeabilized using the BD Cytofix/Cytoperm kit . Staining was compared with the relevant isotype controls to verify specificity . Flowcytometric acquisition was performed on a FACSCANTO II or LSR II ( BD Biosciences ) and data were analyzed using Flowjo Software ( Tree Star ) . Antibody pairs used for cytokine ELISA were as follow: IL-4 ( 11B11/BVD6-24G2 ) and IL-5 ( TRFK5/TRFK4 ) . Recombinant murine IL-4 and IL-5 ( Sigma-Aldrich ) were used as standards . Biotin detection antibodies were used with ExtrAvidin-alkaline phosphatase conjugate ( Sigma-Aldrich ) and Sigma Fast p-nitrophenyl phosphate substrate ( Sigma-Aldrich ) . Statistical analysis was performed using JMP version 8 ( SAS ) . Parametric analysis of combined data from multiple repeat experiments , or of experiments containing more than two groups , was performed using ANOVA followed by Tukey's post-hoc tests when required . When using two-way ANOVA to combine data from multiple experiments , experimental effects were controlled for in the analysis and it was verified that there were no significant qualitative interactions between experimental and treatment effects . Mf incidence was analysed using a GLM with a binomial distribution .
|
Helminth parasites mount chronic infections in over 1 billion people worldwide , of which filarial nematode infections account for 120 million . A major barrier to the development of protective Th2 immunity lies in the dominant down-regulatory immune responses invoked during infection . Although this immune suppression is linked with a range of Th2 cell-extrinsic immune regulators , the fate of CD4+ Th2 cells during chronic infection , and the role of Th2 cell-intrinsic regulation in defining protective immunity to infection is largely unknown . In this study , we use a murine model of filarial nematode infection to show that as infection progresses the Th2 effector cells responsible for killing helminths become functionally hypo-responsive , developing a phenotype similar to adaptive tolerance or exhaustion , and their ability to clear infection becomes impaired . We further demonstrate that we can therapeutically manipulate the intrinsic functional quality of hypo-responsive Th2 cells via the PD-1/PD-L2 co-inhibitory pathway to reawaken them and enhance resistance to infection . Thus , our data provide the first demonstration that Th2 cell-intrinsic hypo-responsiveness plays a key role in determining susceptibility to helminth infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunomodulation",
"adaptive",
"immunity",
"immune",
"cells",
"immunity",
"t",
"cells",
"immune",
"defense",
"immunology",
"biology",
"immune",
"suppression",
"immunity",
"to",
"infections",
"immunoregulation",
"immune",
"response"
] |
2013
|
Th2 Cell-Intrinsic Hypo-Responsiveness Determines Susceptibility to Helminth Infection
|
Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts . Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation . However , the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated . To identify candidate genes associated with senile osteoporosis , we performed genome-wide expression analyses of differentiating osteoblasts and adipocytes . Among transcription factors that were enriched in the early phase of differentiation , Id4 was identified as a key molecule affecting the differentiation of both cell types . Experiments using bone marrow-derived stromal cell line ST2 and Id4-deficient mice showed that lack of Id4 drastically reduces osteoblast differentiation and drives differentiation toward adipocytes . On the other hand knockdown of Id4 in adipogenic-induced ST2 cells increased the expression of Pparγ2 , a master regulator of adipocyte differentiation . Similar results were observed in bone marrow cells of femur and tibia of Id4-deficient mice . However the effect of Id4 on Pparγ2 and adipocyte differentiation is unlikely to be of direct nature . The mechanism of Id4 promoting osteoblast differentiation is associated with the Id4-mediated release of Hes1 from Hes1-Hey2 complexes . Hes1 increases the stability and transcriptional activity of Runx2 , a key molecule of osteoblast differentiation , which results in an enhanced osteoblast-specific gene expression . The new role of Id4 in promoting osteoblast differentiation renders it a target for preventing the onset of senile osteoporosis .
Senile osteoporosis or age-related osteopenia is accompanied by increased bone marrow tissue adiposity [1] . Bone marrow adipocytes and osteoblasts are thought to originate from common mesenchymal stem cells ( MSCs ) . Therefore , it has been suggested that the excessive accumulation of marrow adipocytes following bone loss is caused by unbalanced differentiation of MSCs into marrow adipocytes and osteoblasts [2] . Support for this hypothesis comes from studies of peroxisome proliferators-activated receptor-γ ( Pparγ ) , a master regulator of adipocyte differentiation , deficient embryonic stem cells that showed an increase in osteoblast differentiation [3] . In contrast , calvarial adipocyte differentiation is augmented when runt-related transcription factor 2 ( Runx2 ) , a master regulator of osteoblast differentiation has been knocked out [4] . Transcription factors Runx2 and Sp7 transcription factor 7 ( Sp7 ) regulate MSC commitment to osteoblast differentiation along with bone morphogenetic protein ( BMP ) signaling pathway [5] . Conversely , Pparγ and CCAAT/enhancer binding protein ( C/EBP ) transcription factor family members drive MSCs differentiation toward adipocytes [6] . Other proteins that regulate the balance between adipocyte and osteoblast differentiation are tafazzin , Wnt5a , Wnt10b , Msx2 , C/EBPβ and basic helix-loop-helix ( bHLH ) family member e40 ( Bhlhe40 ) [6]–[8] . Aforementioned transcription factors suppress adipocyte differentiation and promote osteoblast differentiation . Regardless of these studies , the precise molecular mechanisms that regulate the balance between osteoblast and adipocyte differentiation in the bone marrow has yet to be elucidated . Hence , we aimed to identify transcription factors that regulate the direction of differentiation toward osteoblast or adipocyte by analyzing their genome-wide expression profiles in differentiation time series experiments . We noticed in early phases a subgroup of transcription factors that appeared to function in both osteoblasts and adipocytes differentiation . Particularly , bHLH superfamily transcription factors were significantly enriched and up-regulated in the early phase of osteoblast differentiation . The bHLH superfamily comprises transcription factors that form homo- or heterodimers and typically bind to a consensus sequence ( CANNTG ) called an E-box [9] . It is well known that bHLH transcription factors play important roles in development and cell differentiation . For example , Myod1 is a key differentiation factor of myoblasts and Srebf1 is involved in adipocyte differentiation [10] , [11] . Hairy and enhancer of split ( Hes ) family members of bHLH superfamily are crucial regulators of cortical development [12] . Here , we have identified Inhibitor of DNA binding 4 ( Id4 ) , which also belongs to the bHLH superfamily as a key molecule that regulates the direction of differentiation toward osteoblast or adipocyte in vitro and in vivo using genome wide expression study . Furthermore , we established that Id4 promotes osteoblast differentiation by enhancing Runx2 transcriptional activity through stabilization of Runx2 protein . The new role of Id4 in directing osteogenic and adipogenic cell fate makes it a likely target for preventing the onset of senile osteoporosis .
To delineate the sequential changes of transcription factors activating and repressing downstream osteogenic and/or adipogenic target genes , we evaluated the differentiation capability toward both osteoblasts and adipocytes using six cell lines ( ST2 , C2C12 , DFAT-D1 , PA6 , 10T1/2 , NRG ) . Of these , bone marrow-derived stromal cell line ST2 differentiated most efficiently into both osteoblasts and adipocytes ( data not shown ) . Using Affymetrix mouse GeneChip , we aimed to identify clusters of transcription factors that are temporally co-regulated in one but not in another cluster ( CIBEX Accession number: CBX90 ) . Of 1 , 270 transcription factors , 407 genes were significantly up- or down- regulated in either osteoblast or adipocyte differentiation compared to the non-induced control ( Table 1 and Table S1 ) . Hierarchical clustering analysis of transcription factor gene expression data at 15 osteoblast and seven adipocyte differentiation time points ( Figure 1A ) revealed distinct clusters that represent phases of sequentially expressed transcription factors ( Figure 1B ) . Differentiation into osteoblasts is characterized by five phases ( Figure S1 ) whereas adipocyte differentiation resulted in four phases ( Table S1 ) . The early phases of osteoblast ( 1 hr ) and adipocyte ( 48 hr ) differentiation showed the greatest variability in transcription factor expression levels ( Figure 2A and Table S1 ) . Chi-square testing for over-representation of transcription factors in each differentiation phase supported only six up-regulated bHLH superfamily members ( Id1 , Id2 , Npas4 , Id4 , Hes1 and Bhlhe40 ) of the immediate early phase osteoblast differentiation ( 1 hr ) as significantly ( p<0 . 01 ) enriched ( Figure 2B ) . Since Id4 , Hes1 and Bhlhe40 expression increased ( decreased ) twofold or greater during osteoblast ( adipocyte ) differentiation compared to the control ( Figure 2C and Table 2 ) , these transcription factors are likely to play a pivotal role in the regulation of osteoblast and adipocyte differentiation . Indeed , Hes1 and Bhlhe40 are known to be involved in both differentiation pathways [8] , [13] , [14] , whereas Id4 has not yet been implicated in either differentiation pathways . Additionally , Id4 expression patterns in osteoblast and adipocyte differentiation were also compared by quantitative real-time PCR ( qRT-PCR ) . Expression of Id4 significantly increased during osteoblast differentiation , attained a peak on day 4 and decreased thereafter ( Figure S2A ) . In contrast , Id4 expression decreased during adipocyte differentiation ( Figure S2B ) . Expression levels of Id1 and Id2 were also up-regulated in the early stage ( 1 hr ) of osteoblast differentiation , but thereafter their expression dropped to base levels ( Figure 2C , upper panel ) . Therefore , we hypothesized that Id4 may act as a novel molecular switch in osteoblast and adipocyte differentiation . Aside from Id4 , Hes1 and Bhlhe40 , we identified additional bHLH members and various hypothetical and non-bHLH transcription factors as phase-specific candidate regulators of osteo- and adipogenesis ( Figure 2A and Table S1 ) . The genes listed in Table S1 await further functional characterization regarding their involvement in osteoblast and/or adipocyte differentiation . To evaluate the potential role of Id4 in ST2 osteoblast differentiation , Id4 was suppressed by siRNA knockdown . As shown in Figure 3A , Id4 siRNA ( siId4 ) -treated ST2 cells differentiating into osteoblasts showed a significant decrease in Id4 expression . The decline of Id4 expression was accompanied by weak alkaline phosphatase ( ALP ) activity and reduced bone γ carboxyglutamate protein 1 ( Bglap1 also called osteocalcin ) expression ( Figure 3B and 3C ) . Since both are markers of osteoblast differentiation , it appeared that Id4 is important in osteoblast differentiation of MSCs . We next evaluated whether forced expression of Id4 can promote osteoblast differentiation in MSCs by retroviral systems ( Figure 3D ) . ST2 cells infected with Id4 recombinant retrovirus showed increased expression levels of ALP and Bglap1 compared to cells infected with control virus independent of the presence or absence of BMP4 ( Figure 3E and 3F ) . Taken together , Id4 promotes osteoblast differentiation of MSCs . Id4 knockdown in adipogenesis-induced ST2 cells ( Figure 4A ) significantly increased expression levels of other adipogenic marker genes such as Pparγ2 [15] and Adipoq [16] ( Figure 4B and 4C ) . Concomitantly , the number of Oil Red O stained lipid droplets and triglyceride levels also increased ( Figure 4D and 4E ) . Forced expression of Id4 was confirmed by transfection into Cos7 cells with Id4 expression vector ( Figure 4F ) . Adipocytes differentiated from ST2 cells transfected with Id4 expression vector showed slightly but significantly decreased lipid accumulation compared to empty vector transfectants ( Figure 4G ) . The combined results of Id4 siRNA knockdown and overexpression in ST2 suggest that Id4 attenuates differentiation of MSCs into adipocytes . Previously Id4−/− mice were studied only in context of neural development [17] . We confirmed that Id4 expression was highest in the brain followed by cortical bone , kidney , thymus and bone marrow of C57BL/6J mice ( Figure 5A ) . The body length and weight of 4 weeks old Id4−/− mice was 13–15% shorter and 35–40% lower compared to wild-type ( Id4+/+ ) littermates ( Figure 5B and 5C ) . Id4−/− mice showed severe growth retardation and died by 5 weeks . In addition , we observed visible skeletal phenotypes of Id4−/− mice , but no skeletal deformities ( data not shown ) . Altogether , our data hint at an important role of Id4 in bone formation . Bone histological analysis of Id4−/− mice revealed significantly decreased bone volume ( BV ) in the 6th lumbar ( Figure 5D and 5E ) . The bone formation rate ( BFR ) was decreased in Id4−/− mice compared to Id4+/+ mice ( Figure 5F and 5G ) . The BV to total volume ratio , BFR to bone surface ( BS ) ratio and mineral apposition rate ( MAR ) of Id4−/− mice were 57 . 3% , 28 . 1% and 30 . 7% lower compared to Id4+/+ mice in the 6th lumbar , respectively ( Figure 5N–5P ) . In Id4+/+ mice , active cuboidal-shaped osteoblasts ( type II osteoblasts ) were distributed in a row along the lumbar BS ( Figure 5H ) , whereas in the corresponding region of Id4−/− mice osteoblasts were predominantly flat and resting ( type IV osteoblasts; lining cells ) ( Figure 5I ) . The number of osteoblasts as a whole did not change significantly between Id4+/+ and Id4−/− mice ( data not shown ) . However , in Id4−/− mice the population of active osteoblasts was reduced ( type II , Figure 5Q ) , whereas inactive osteoblasts accumulated ( type IV , Figure 5R ) . These findings imply that Id4 modulates both differentiation of osteoblasts from pre-osteoblasts and regulation of osteoblast maturation . Impaired bone formation was also observed in the lateral calvaria of Id4−/− mice ( Figure 5K and 5M ) . In wild type mice , osteoblasts were closely lined up along the calvarial BS ( Figure 5J ) . In contrast , no osteoblasts were observed along the calvarial bone of Id4−/− mice ( Figure 5K ) . The osteoid thickness , BFR to BS ratios and MAR of Id4−/− mice calvarial bones were 61 . 5% , 49 . 1% and 65 . 2% of Id4+/+ mice , respectively ( Figure 5S , 5O , and 5P ) . These results suggest that Id4 is important for both endochondorial and membranous ossification . Growth Plate Width and Longitudinal Growth Rate ( Lo . G . R ) of Id4−/− mice tibia were 68 . 4% and 57 . 1% of Id4+/+ mice , respectively ( Figure S3A , S3B , S3C , S3D ) , which may have caused the growth retardation of Id4−/− mice . Id family members are known to heterodimerize with other bHLH transcriptional factors , thus inhibiting the binding to the E-box motif [18] . To explore whether heterodimerized Id4 switches the direction of osteoblast and adipocyte differentiation , we assayed Id4 protein-protein interactions and analyzed their effects . Using immunoprecipitation we attempted to capture for candidate bHLH transcription factors that bind to Id4 . Out of four tested bHLH transcription factors ( Hes1 , hairy/enhancer-of-split related with YRPW motif 1; Hey1 , hairy/enhancer-of-split related with YRPW motif 2; Hey2 and Bhlhe40 ) ( Figure S4A ) , only Hey2 bound to Id4 ( Figure 6A , Figure S4A and S4B ) . An earlier study demonstrated that Hey2 is forming heterodimers with Hes1 , which then bind to the E-box motif and repress transcription [19] . Therefore , we tested the effect of Id4 on transcriptional repression of Hey2/Hes1 heterodimers against the E-box element . Transcriptional repression onto E-box element in the presence of either Hey2 or Hes1 showed no effect or 39% inhibition of E-box transcriptional activity relative to control ( empty expression vector ) , respectively ( Figure 6B ) . Although luciferase activity was lowest in the presence of both Hey2 and Hes1 , inhibition of transcriptional repression by Id4 increased in dose-dependent manner ( Figure 6B ) . We also demonstrated that Hey2-Hes1 binding was abrogated with the dose-dependent increase of Id4 ( Figure 6C , lane 5 and lane 6 ) . Taken together , we confirmed that Id4 reverses the transcriptional repression by Hey2-Hes1 heterodimer in a dose-dependent manner . The presence of inactive osteoblasts ( Figure 5I and 5R ) in the bone tissues of the Id4−/− mice let us assume that Id4 may affect the actions of Runx2 and Sp7 , a key osteogenic differentiation molecule [20]–[22] . Osteoblast marker gene Bglap1 expression level decreased not only in primary osteoblasts but also in embryonic day18 . 5 ( E18 . 5 ) limb of Id4−/− mice ( Figure S5A and S5B ) . Bglap1 , a target gene of Runx2 has an E-box element other than osteoblast-specific element 2 ( OSE2 ) , which binds Runx2 to the promoter [23] . Therefore , we measured the promoter activity to examine the influence of Id4 on Bglap1 E-box promoter-dependent transcriptional activity of Runx2 . Although the suppression of Bglap1 promoter activity by addition of Hes1 and Hey2 was not detected , a dose-dependent increase of transcriptional activity by Id4 was observed when testing the OSE2 element-containing promoter . When using the promoter without OSE2 the increase in transcriptional activity was not seen ( Figure 7A ) . Since direct interaction between Id4 and Runx2 was ruled out experimentally ( data not shown ) , Id4 may indirectly influence Runx2 transcriptional activity through Hes1 . Hes1 is known to stimulate the transcriptional activity of Runx2 protein by increasing its stability during osteoblast differentiation [24] . We also confirmed that the addition of Hes1 stabilizes Runx2 protein . Interestingly , the addition of Id4 further increased the stabilization and accumulation of Runx2 ( Figure 7B ) . Taken together , it appears that Id4 enhances Runx2 transcriptional activity through stabilization of Runx2 protein . Taking into account the timing of the elevated Id4 expression ( Figure 2C and Figure S2A ) , our results strongly suggest that Id4 is indirectly driving the Hes1-mediated Runx2 stabilization during osteoblast differentiation . The facts that both Hes1 and Hey2 bind to the OSE2 element-containing Bglap1 promoter region assessed by ChIP-qPCR , and that the amount of bound Hes1 and Hey2 decreased in ST2 osteoblasts ( Figure 7C ) further support this idea . However , the exact binding site of Hes1-Hey2 heterodimer remains to be identified . The proposed mechanism of Id4 action during osteoblast differentiation is illustrated in Figure 7D . Id4 knockdown promoted adipocyte differentiation in ST2 cells ( Figure 4B–4E ) . Histological analysis of Id4−/− tibia bones revealed elevated numbers of adipocytes in epiphyseal bone marrow of tibia compared to Id4+/+ mice ( Figure 8A–8D ) . The entire analyzed area of epiphyseal tibia bone marrow was occupied by adipocytes in Id4−/− mice ( Figure 8E ) . Moreover , Pparγ2 expression levels were also increased in bone marrow cells of femur and tibia of Id4−/− mice ( Figure 8F ) . In comparison to Id4+/+ mice , the number of adipocytes in the lateral calvaria was markedly increased in Id4−/− mice ( Figure 5K ) . These aberrant traits observed in Id4−/− mice implicate Id4 as a crucial molecule in the lineage choice of MSCs differentiating into either osteoblasts or adipocytes ( Figure 8G ) .
In this study , we have delineated clusters of transcription factors that act as key regulators in the osteoblast and adipocyte differentiation network . The observation of sometimes disparately regulated transcription factors , led us to hypothesize a molecular switch function that promotes lineage-specific differentiation ( e . g . osteoblast differentiation ) and inhibits alternative differentiation pathways ( e . g . adipocyte differentiation ) . To substantiate the hypothesis , we clustered gene expression profiles during osteoblast/adipocyte differentiation and identified Id4 as a candidate regulator of cell lineage choice . Id family members Id1–4 also belong to the bHLH superfamily , but lack the DNA binding domain . Heterodimerization of Id proteins with other bHLH proteins facilitates dominant negative regulation . A study by Bedford et al . using Id4−/− mice established Id4 as a regulator of proliferation and differentiation of neural precursor cells [17] . Until now , however , bone and skeletal abnormalities of this mouse model have not been reported . Besides our report , expression profile studies of BMP-independent osteoblast differentiation of human MSCs and BMP2-induced osteoblast differentiation using calvarial cells derived from Runx2-deficient mice [25] , [26] demonstrated that the expression level of Id4 gene increases during osteoblast differentiation . These results suggest that Id4 plays an important role during osteoblast differentiation . Yet , the precise mechanism of Id4 action and regulation remained enigmatic . We have clearly demonstrated by in vitro and in vivo loss-of-function analysis that Id4 enhances osteogenic differentiation . Furthermore , we established a model of Id4 playing the role of molecular switch in osteoblast differentiation of MSCs ( Figure 7D ) . Id4 expression increases upon BMP-induced osteoblast differentiation . Accumulating Id4 proteins transiently interact with Hes1-bound Hey2 , thus triggering the release of Hes1 and the formation of Id4-Hey2 heterodimers and Hes1-Runx2 complexes . The binding of Hes1 to Runx2 potentiates the transcriptional activity of Runx2 and therefore osteoblast differentiation . Hes1 and Hey2 are the target molecules of Notch signaling [19] . Until now , the relationship between Notch and BMP signaling pathways has been characterized by conflicting reports . On one hand experiments using ST2 cells showed that Notch1 suppresses the BMP-induced differentiation into osteoblasts [27] . On the other hand , Nobta et al . [28] reported that Notch signaling enhances BMP-induced osteoblast differentiation of C2C12 or MC3T3-E1 cells . At this point , there are insufficient data to resolve the controversy about the role of Notch signaling in BMP-induced osteoblast differentiation . However , our model ( Figure 7D ) may help to clarify the function of Notch signaling . In the absence of Id4 , Hes1-Hey2 heterodimer just occupies the promoter region of the Runx2 target gene , whereas in the presence of Id4 , Id4-Hey2 and Hes1-Runx2 complexes increase simultaneously . The concomitant increase of both complexes enhances the transcriptional activity of Runx2 . Thus , we propose that availability and concentration of Id4 might account for the disparate roles of Notch signaling . In Id4−/− mice , the drop of calvarial BFR is consistent with the phenotype of Id1/Id3 heterozygous knockout mice . After BMP stimulation , Id1/Id3 heterozygous knockout mice-derived calvarial cells showed reduced proliferation activity compared to calvarial cells derived from wild-type mice [29] . Thus , the decreased rate of calvarial bone formation in Id4−/− mice might be the consequence of reduced osteoblast proliferation . The expression levels of Id1and Id2 were also up-regulated in the early stage of BMP4-induced osteoblast differentiation ( Figure 2A ) . Indeed , it has been reported that Id1 is an important early gene in osteoblasts after BMP stimulation [30] , [31] . Although the biological significance of Id1 in the regulation of MSCs has to be elucidated in future studies , in ST2 cells , expression levels of Id1 and Id2 immediately returned to base levels ( Figure 2C ) . In contrast , Id4 expression levels in ST2 and 3T3-E1 cells continued to rise until 4 days ( Figure 2C and Figure S2A ) and 7days , respectively [32] . Systemic hormones and local cytokines are known to be central regulators of bone formation . Serum levels of growth hormone ( IGF1 ) and thyroid hormones ( T3 and T4 ) did not change significantly between Id4+/+ and Id4−/− mice ( data not shown ) . Hence , impaired bone formation is most likely independent of hormonal factors and caused by repression of osteoblast differentiation . Since the expression level of Id4 decreases during adipocyte differentiation ( Figure 2C and Figure S2B ) , Id4 was believed to inhibit MSCs differentiation into adipocytes . We demonstrated that Id4 suppression promoted adipocyte differentiation ( Figure 4B–4E and Figure 8A–8E ) , but Id4 overexpression slightly decreased lipid accumulation level in ST2 adipocytes ( Figure 4G ) . In an effort to shed light on the molecular mechanism , we assayed the expression level of Pparγ2 , a master regulator of adipocyte differentiation . Pparγ2 expression increased in adipogenic-induced ST2 cells when Id4 was knocked down ( Figure 4B ) and in bone marrow cells of femur and tibia of Id4−/− mice ( Figure 8F ) . However , the results of luciferase reporter assays ruled out effects of Id4 on the promoter activity of Pparγ2 ( data not shown ) . Pparγ2 down-regulation by Id4 might involve a yet unknown , indirect regulatory mechanism . We noticed that the number of osteoclasts increased in the tibial epiphyseal regions and the 6th lumbar vertebra ( data not shown ) . In view of an earlier report on Pparγ promoting osteoclast differentiation by activating c-fos [33] , we interpret the increased number of adipocytes and osteoclasts in 6th lumbar and tibial bone of Id4−/− mice as a result of indirect activation of Pparγ1 and/or Pparγ2 transcriptional activity by lack of Id4 . To corroborate these assumptions , additional analyses of the relationships and interactions of Id4 , Pparγ and c-fos in context of adipocyte and osteoclast differentiation are necessary . In summary , delineating clusters of transcription factors is a powerful strategy to identify cell fate-determining members of regulatory networks . Concerted application of our genome-wide expression profiling analyses and validation of transcription factor candidate regulators synthesize knowledge of specific molecular mechanism underlying osteoporosis and/or metabolic disease . In case of Id4 , our findings reflect the potential pen-ultimate position of Id4 in the Runx2 activation/repression , which permits the differential integration of various upstream signals . Since BMP and Notch signaling affect osteoblast differentiation at different phases of differentiation , modulation of Id4 expression may create new venues for treating the onset of osteoporosis .
ST2 cells were obtained from RIKEN BioResource Center ( BRC , Tsukuba , Japan ) and cultured as described [34] . Primary osteoblasts were isolated from Id4+/+ and Id4−/− neonatal calvarial bone as described previously [35] . Osteogenic differentiation was induced by changing the medium every three days to culture medium supplemented with 100 ng/ml of bone morphogenetic protein 4 ( BMP4 ) ( R&D Systems , Mineapolis , MN ) and adipogenic differentiation was induced by changing the medium to differentiation medium supplemented with 10% fetal bovine serum ( FBS ) , 0 . 5 mM 3-isobutyl-1-methlxanthine , 0 . 25 µM dexamethasone , and insulin-transferrin-selenium-X supplement containing 5 µg/ml of insulin ( Invitrogen , Carlsbad , CA ) and 1 µM rosiglitazone . After 48 hr , the differentiation medium was replaced with culture medium supplemented with 10% FBS . siRNA sequences targeting the mouse Id4 transcript were purchased from Ambion ( for adipocyte ) and Invitrogen ( for osteoblast ) . AllStar Negative Control siRNA ( QIAGEN , cat . No . , 1027281 ) and Negative Universal Control Med#2 ( Invitrogen , cat . No . , 12935-112 ) was used as a negative control in adipocyte and osteoblast differentiation , respectively . The sequences of siRNA used for Id4 knockdown were as follows; sense , CCUUUGUAUUUGACGUGUAtt; antisense , UACACGUCAAAUACAAAGGtt ( Ambion , cat No . AM16704 , ID . 159536 ) ; for adipocyte differentiation; sense , UUAAUUUCUGCUCUGGCCCUCCCUU; antisense , AAGGGAGGGCCAGAGCAGAAAUUAA ( Invitrogen , stealth_455 , cat No . 10620312 ) ; for osteoblast differentiation . For siRNA transfection , a complex of Lipofectamine 2000 ( Invitrogen ) and 20 nM siRNA was prepared according to the manufacturer's instruction and directly mixed with cells in the culture plates . The medium was replaced at 4–6 hr after transfection with fresh differentiation medium ( adipogenic induction ) or 10% FBS supplemented with 100 ng/ml of BMP4 ( osteogenic induction ) . Lipid accumulation in adipocytes was detected by using Oil Red O staining as described previously [36] . The triglyceride content in adipocytes was determined as follows . ST2 cells were washed with cold phosphate-buffered saline ( PBS ) and total lipids were extracted with chloroform/methanol ( 2∶1 , v/v ) . The lower organic phase was dried , and the lipids were dissolved in 2-propanol . The triglyceride content was measured using Triglyceride E-test ( Wako , Japan ) according to the manufacturer's instructions . Protein concentrations were determined with Quick Start Bradford Dye Reagent ( BIO RAD , 500-0205 ) , using bovine gamma globulin as standard . ALP staining and measurements were performed as described previously [34] . Total RNA was isolated from liver , brain , kidney , thymus , brown adipose tissue ( BAT ) , heart , white adipose tissue ( WAT ) , adrenal gland , cortical bone , calvaria , bone marrow and posterior limb of E18 . 5 mouse embryo using TRIzol reagent ( Invitrogen ) and RNeasy columns ( QIAGEN , Hilden , Germany ) according to the manufacturer's instructions . Bone marrow was obtained by slicing of the ends of femur and tibia bones and then flushing it out with PBS using a syringe . Yield and quality of RNA were determined with a NanoDrop spectrometer ( NanoDrop Technology , San Diego , CA ) and a BioAnalyzer ( Agilent Technologies , Santa Clara , CA ) . Gene expression levels were measured by qRT-PCR as described previously [34] . The sequences of forward and reverse primers used for each gene amplification were as follows; gapdh , GAPDH_768Fw_qPCR 5′-TGGAGAAACCTGCCAAGTATG-3′ , GAPDH_889Rv_qPCR 5′-GGAGACAACCTGGTCCTCAG-3′; Id4 , Mm_Id4_532Fw 5′-AGGGTGACAGCATTCTCTGC-3′ , Mm_Id4_658Rv 5′-CCGGTGGCTTGTTTCTCTTA-3′; Pparγ2 , PPARg2Fw 5′-ATGGGTGAAACTCTGGGAGA-3′ , PPARg2-1Rv 5′-GAGCTGATTCCGAAGTTGGT-3′; Bglap1 , OC ( PM15547142 ) Fw 5′-CTCTGTCTCTC TGACCTCACAG-3′ , OC ( PM15547142 ) Rv 5′-GGAGCTGCTGTGACATCCATAC-3′; Adipoq , Mm_AdipoQ_298Fw 5′-GATGGCACTCCTGGAGAGAA-3′ , Mm_AdipoQ_443Rv 5′-GCTTCTCCAGGCTCTCCTTT-3′ . RNA was extracted from differentiating ST2 osteoblasts and adipocytes after induction of differentiation , using PureLink miRNA Isolation Kit ( Invitrogen ) according to the manufacture's instructions for total RNA purification . Total RNA derived from ST2 at 0 hr was used as control . Biotin-labeled cRNA was synthesized as recommended by Affymetrix guidelines . Labeled samples were hybridized to the Affymetrix GeneChip Mouse Genome 420 2 . 0 arrays according to the manufacturer's protocol . Scanning and intensity data analysis was preformed as described elsewhere [37] . Collected microarray expression data was background-subtracted , and normalized using the robust multi-array analysis method [37] . Differentially expressed genes were determined by selecting expression subgroups that contained the probe sets of up/down-regulated genes . Genes were considered up-regulated ( down-regulated ) if their log2 intensity ratio was greater ( less ) than 1 ( −1 ) , or greater ( less ) than the mean plus ( minus ) 3-times standard deviation . All gene and probe set annotations were derived from Ensembl release 52 . Genes with transcription-related Gene Ontology ( GO ) annotations ( Table 3 ) were considered as transcription factor-coding genes . Genes with InterPro accession IPR001092 were annotated as bHLH transcription factor-coding genes . Spotfire DecisionSite version 8 . 1 . 1 ( TIBCO Software , Inc . ) was used for hierarchical clustering and generating the gene expression heat maps . Bglap1 promoter regions were cloned by PCR from the mouse genome . 6×E-box sequence ( CGCGTCCACGTGGGGCCACGTGGGGCCACGTGGGGCCACGTGGG GCCACGTGGGGCCACGTGGGGA ) and cloned fragments were ligated to the firefly luciferase gene ( derived from pGL4 . 10 , Promega ) . CV1 cells were co-transfected with the firefly luciferase reporter vectors , expression vectors and the internal control Renilla luciferase vector ( pGL4 . 74 , Promega ) using Lipofectamine 2000 ( Invitrogen ) . Luciferase activities were measured with Wallac 1420 Multilabel counter ( PerkinElmer Life and Analytical Sciences , Turku , Finland ) . These experiments were performed in triplicate . Cos7 cells were transfected with FLAG-Id4 expression vector with either HA tagged expression vector ( Hes1 , Hey1 , Hey2 , Bhlhe40 ) . The extracts from the transfected cells were incubated with Protein G sepharose beads and precipitated with either anti-FLAG antibody ( SIGMA ) or normal mouse IgG ( Santa cruz ) overnight at 4C° . After washing with PBS , bound proteins were separated by SDS-PAGE followed by Western blot analysis with anti-HA antibody , anti-FLAG antibody . GST-Id4 expression vector , Flag-Hey2 expression vector and Flag-empty vector were expressed in E . coli . The crude extract of GST-Id4 or GST expressed in E . coli was incubated with glutatihione sepharose beads for 4 hr at 4C° . The precipitate was incubated with the extract of Flag-Hey2 overnight at 4C° . After washing , the bound proteins were separated by SDS-PAGE followed by Western blot analysis with anti-Flag antibody . ChIP was performed as described previously [38] . ST2 cells were cultured for 4 days with or without 100 ng/ml BMP4 , respectively . The antibodies used for ChIP were anti-Hey2 ( Protein Tech Group , cat No . 10597-1-AP ) , anti-Hes1 ( Santa Cruz , H-140 ) and normal rabbit IgG ( Santa Cruz , sc-2027 ) as negative control . Forward and reverse qPCR primer sequences contained OSE2 of the Bglap1 promoter ( Bglap2_ChIP_L789 , 5′-GATTGTGGCCTCTCGTC-3′;Bglap2_ChIP_R8 , 5′- ATCGGCTACTCTGTGCTCT-3′ ) . Id4−/− mice previously generated by Bedford et al . ( 2005 ) were kindly supplied by Dr . Kondo who received them originally from Dr . Sablitzky ( University of Nottingham ) . All mice used in this study were maintained and handled according to the protocols approved by the Animal Research Committee of Saitama Medical University . To assess the static and dynamic parameters of bone histomorphometry , 3 weeks old female mice were labeled with intraperitoneal injections of 20 mg/kg of tetracycline hydrochloride ( Sigma ) at 4 days before sacrifice . Two days before sacrifice , the mice were injected with 10 mg/kg of calcein ( Dojindo Co . , Kumamoto , Japan ) . Tibiae and lumbar vertebrae were removed from each mouse , and fixated with 70% ethanol . The bones were trimmed to remove the muscle , stained with Villanueva bone stain for 5 days , dehydrated in graded concentrations of ethanol , and embedded in methyl-methacrylate ( Wako Chemicals , Kanagawa , Japan ) without decalcification . Sagittal plane sections ( 5 µm thick ) of the lumbar vertebrae were cut using a Microtome ( Leica , Germany ) . Bone morphometric analyses were performed using a semi-automatic image analyzing system software ( System Supply , Nagano , Japan ) and Optiphot fluorescent microscope ( Nikon , Tokyo , Japan ) .
|
Increased bone marrow adiposity is observed in the bone marrow of senile osteoporosis patients . This is caused by unbalanced differentiation of mesenchymal stem cells ( MSCs ) into osteoblast or adipocyte . Previous reports have indicated that several transcription factors play important roles in determining the direction of MSCs differentiation into osteoblast or adipocyte . So far , little is known about the overall dynamics and regulation of transcription factor expression changes leading to the imbalance of osteoblast and adipocyte differentiation inside the bone marrow . We have performed genome-wide gene expression analyses during the differentiation of MSCs into osteoblast or adipocyte . We identified basic helix-loop-helix transcription factor family member Id4 as a leading candidate controlling the differentiation toward adipocyte or osteoblast . Suppression of Id4 expression in MSCs repressed osteoblast differentiation and increased adipocyte differentiation . In contrast , overexpression of Id4 in MSCs promoted osteoblast differentiation and attenuated adipocyte differentiation . Moreover , Id4-mutant mice showed abnormal accumulation of lipid droplets in bone marrow and impaired bone formation activity . In summary , we have demonstrated a molecular function of Id4 in osteoblast differentiation . The findings revealed that Id4 is a molecular switch enhancing osteoblast differentiation at the expense of adipocyte differentiation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/stem",
"cells",
"molecular",
"biology/transcription",
"initiation",
"and",
"activation",
"genetics",
"and",
"genomics/gene",
"expression",
"developmental",
"biology/cell",
"differentiation",
"genetics",
"and",
"genomics/gene",
"function",
"cell",
"biology/gene",
"expression"
] |
2010
|
Id4, a New Candidate Gene for Senile Osteoporosis, Acts as a Molecular Switch Promoting Osteoblast Differentiation
|
SARS-coronavirus ( SARS-CoV ) genome expression depends on the synthesis of a set of mRNAs , which presumably are capped at their 5′ end and direct the synthesis of all viral proteins in the infected cell . Sixteen viral non-structural proteins ( nsp1 to nsp16 ) constitute an unusually large replicase complex , which includes two methyltransferases putatively involved in viral mRNA cap formation . The S-adenosyl-L-methionine ( AdoMet ) -dependent ( guanine-N7 ) -methyltransferase ( N7-MTase ) activity was recently attributed to nsp14 , whereas nsp16 has been predicted to be the AdoMet-dependent ( nucleoside-2′O ) -methyltransferase . Here , we have reconstituted complete SARS-CoV mRNA cap methylation in vitro . We show that mRNA cap methylation requires a third viral protein , nsp10 , which acts as an essential trigger to complete RNA cap-1 formation . The obligate sequence of methylation events is initiated by nsp14 , which first methylates capped RNA transcripts to generate cap-0 7MeGpppA-RNAs . The latter are then selectively 2′O-methylated by the 2′O-MTase nsp16 in complex with its activator nsp10 to give rise to cap-1 7MeGpppA2′OMe-RNAs . Furthermore , sensitive in vitro inhibition assays of both activities show that aurintricarboxylic acid , active in SARS-CoV infected cells , targets both MTases with IC50 values in the micromolar range , providing a validated basis for anti-coronavirus drug design .
In 2003 , the severe acute respiratory syndrome coronavirus ( SARS-CoV ) , which was likely transmitted from bats , was responsible for a worldwide SARS-outbreak [1] . Coronaviruses belong to the order Nidovirales and are characterized by the largest positive-strand RNA ( ( + ) RNA ) genomes ( around 30 , 000 nt ) known in the virus world . The enzymology of their RNA synthesis is therefore thought to be significantly more complex than that of other RNA virus groups [2] , [3] , [4] . The 5′-proximal two-thirds of the CoV genome ( open reading frames 1a and 1b ) are translated into the viral replicase polyproteins pp1a and pp1ab ( Figure 1 ) , which give rise to 16 nonstructural proteins ( nsps ) by co- and post-translational autoproteolytic processing . The 3′-proximal third encodes the viral structural proteins and several so-called accessory proteins , which are expressed from a set of four to nine subgenomic ( sg ) mRNAs . The latter are transcribed from subgenome-length minus-strand templates , whose production involves a unique mechanism of discontinuous RNA synthesis ( reviewed by [5] , [6] ) . To organize their complex RNA synthesis and genome expression , the CoV proteome includes several enzyme activities that are rare or lacking in other ( + ) RNA virus families ( reviewed in [2] ) . In the years following the 2003 SARS outbreak , bioinformatics , structural biology , ( reverse ) genetics and biochemical studies have contributed to the in-depth characterization of CoV nsps in general and those of SARS-CoV in particular [7] . Currently documented enzyme activities include two proteinases ( in nsp3 and nsp5; [8] , [9] ) , a putative RNA primase ( nsp8; [10] ) , an RNA-dependent RNA polymerase ( nsp12; [11] , [12] ) , a helicase/RNA triphosphatase ( nsp13; [13] , [14] ) , an exo- and an endoribonuclease ( nsp14 and nsp15; [15] , [16] , and an S-adenosyl-L-methionine ( AdoMet ) -dependent ( guanine-N7 ) -methyltransferase ( N7-MTase ) , which were proposed to play a role in the formation of CoV mRNA caps ( nsp14; [17] ) . Based on comparative sequence analysis , nsp16 presumably encodes an AdoMet-dependent mRNA cap ( nucleoside-2′O ) -methyltransferase ( 2′O-MTase ) [3] , [18] , [19] . For SARS-CoV nsp16 , however , this enzyme activity has remained elusive thus far , and experimental evidence for its existence has only been obtained for the related feline coronavirus ( FCoV ) nsp16 [18] . CoV nsps form the viral replication/transcription complex ( RTC ) , which is thought to localize to a network of endoplasmic reticulum-derived , modified membranes in the infected cell [20] , [21] . Protein-protein interactions were proposed to be essential for the assembly of the RTC and may therefore also regulate the activities of enzymes involved in viral RNA synthesis . Although the 5′ ends of SARS-CoV mRNAs have not been characterized yet , they are assumed to carry a cap structure . This assumption is based on the characterisation of genomic and subgenomic mRNAs of the coronavirus murine hepatitis virus ( MHV ) [22] , [23] and the related equine torovirus ( EToV or Berne virus ) , which also belong to the Coronaviridae family [23] , [24] . The mRNAs of both viruses were concluded to carry a 5′-terminal cap structure . Moreover , in the coronavirus and torovirus genome three enzymes putatively involved in mRNA capping have been identified , although they remain poorly characterised [13] , [14] , [17] , [18] , [19] . Cap structures promote initiation of translation and protect mRNAs against exoribonuclease activities [25] , [26] , [27] . The synthesis of the cap structure in eukaryotes involves three sequential enzymatic activities: ( i ) an RNA triphosphatase ( RTPase ) that removes the 5′ γ-phosphate group of the mRNA; ( ii ) a guanylyltransferase ( GTase ) which catalyzes the transfer of GMP to the remaining 5′-diphosphate terminus; and ( iii ) an N7-MTase that methylates the cap guanine at the N7-position , thus producing the so-called “cap-0 structure” , 7MeGpppN . Whereas lower eukaryotes , including yeast , employ a cap-0 structure , higher eukaryotes convert cap-0 into cap-1 or cap-2 structures [25] , [26] , [28] by means of 2′O-MTases , which methylate the ribose 2′O-position of the first and the second nucleotide of the mRNA , respectively . RNA cap methylation is essential since it prevents the pyrophosphorolytic reversal of the guanylyltransfer reaction , and ensures efficient binding to the ribosome [25] , [26] . In the case of ( + ) RNA viruses such as alphaviruses and flaviviruses , mutations in RNA cap methylation genes were shown to be lethal or detrimental to virus replication [29] , [30] , [31] , [32] , [33] . For coronaviruses , a functional and genetic analysis performed on MHV temperature sensitive mutants mapping to the N7-MTase domain of CoV nsp14 and in the 2′O-MTase nsp16 indicated that both are involved in positive-strand RNA synthesis by previously formed replicase-transcriptase complexes [11] . The importance of nsp14 and nsp16 for viral RNA synthesis is further supported by data obtained by mutagenesis of MTase catalytic residues in SARS-CoV RNA replicon systems [17] , [30] . In the case of coronaviruses , the machinery putatively involved in equipping both genome and subgenomic mRNAs with a cap-1 structure is thought to consist of ( i ) the multifunctional nsp13 , which may contribute the RTPase activity of the helicase domain [13] , [34] , ( ii ) a still unknown GTase , ( iii ) the C-terminal domain of nsp14 , which was recently identified as the N7-MTase [17] and ( iv ) nsp16 , the putative 2′O-MTase [3] , [17] , [18] . Using mammalian and yeast two-hybrid systems as well as pull-down assays , it was shown that SARS-CoV nsp14 and nsp16 specifically interact with nsp10 [35] , [36] suggesting that nsp10 may play a role in the viral capping pathway . The crystal structure of nsp10 , a small RNA-binding protein that contains two zinc fingers , was recently solved [37] , [38] , but its role and mode of action in the viral replicative cycle remains elusive . In view of the phenotype of some mouse hepatitis virus ( MHV ) mutants , a role in viral RNA synthesis was postulated [11] , [39] , but other studies implicated nsp10 in replicase polyprotein processing [40] . SARS-CoV nsp10 was also shown to bind single- and double-strand RNA and DNA with low affinity and without obvious sequence specificity [37] . In this study , we report the discovery of a function for SARS-CoV nsp10 as an essential factor to trigger full nsp16 2′O-MTase activity . We deciphered the RNA cap methylation sequence where the guanine-N7-methylation by nsp14 necessarily precedes the 2′O-methylation by the nsp10/nsp16 pair . The SARS-CoV nsp10/nsp14/nsp16 trio constitutes an attractive target package for antiviral drug discovery and design; and indeed nsp14 and nsp16 seem to play an important role in viral replication [11] , [17] , [30] . Accordingly , we set up sensitive inhibition tests for both activities , validated by low IC50 values of known AdoMet-dependent MTase inhibitors . Moreover , we show that aurintricarboxylic acid ( ATA ) , which was shown to inhibit SARS-CoV replication [41] , targets both MTases indeed .
Unlike flaviviruses , which use a single active site in the NS5 protein for both N7- and 2′O-MTase activities [32] , [42] , coronaviruses presumably encode two separate MTases that catalyze the last two steps in the formation of a methylated RNA-cap structure . SARS-CoV nsp14 has been shown to be an RNA-cap N7-MTase [17] . Sequence motifs that are canonical in 2′O-MTases were identified in nsp16 [3] , [19] , but the experimental verification of the MTase activity has not been reported , in contrast to FCoV nsp16 , for which a rather low activity could be demonstrated [18] . SARS-CoV nsp10 was previously shown to interact with both nsp14 and nsp16 [35] , [36] , suggesting its involvement in RNA capping and/or methylation . Consequently , we cloned and expressed both nsp10 and nsp16 in E . coli and purified both recombinant proteins , using their N-terminal His6-tag , by metal affinity chromatography . Nsp14 was expressed as a fusion protein with an intein tag at its C-terminus . The nsp14-intein product was bound to a chitin affinity column and the untagged protein was eluted after removal of the tag by DTT treatment . All three proteins were further purified by size exclusion chromatography . Upon SDS-PAGE , the purified proteins migrated as single bands corresponding to their expected molecular masses ( nsp14: 57 kDa; His6-nsp16: 35 kDa , and His6-nsp10: 15 kDa ) ( Figure 2A ) . The identity of the recombinant proteins was confirmed by trypsin digestion and mass spectrometry ( ( MALDI-TOF ) , data not shown ) . Using the purified recombinant proteins , we first conducted in vitro MTase assays on short capped RNA substrates methylated or not at the N7-position of the guanine cap ( 7MeGpppAC5 and GpppAC5 ) . We used all possible combinations of the three proteins ( nsp10 , nsp14 , and nsp16 ) and incubated them with the substrate in the presence of the tritiated methyl donor [3H]-AdoMet . The extent of [3H]-CH3 transfer was quantified after reaction times of 5 , 30 , and 240 min by using a DEAE filter-binding assay ( see Materials and Methods ) . Figure 2B shows that nsp14 methylated GpppAC5 in a time-dependent manner whereas neither nsp16 nor nsp10 alone did . Apparently , the activity of nsp14 was barely influenced by the presence of nsp10 or nsp16 . In addition , we observed that nsp14 did not methylate 7MeGpppAC5 ( Figure 2C ) suggesting that nsp14 methylates only the N7-position of the cap structure . In contrast to nsp14 , nsp16 catalyzed methyltransfer to neither GpppAC5 nor to 7MeGpppAC5 under these reaction conditions . Surprisingly , when nsp16 activity assays were supplemented with nsp10 , robust methylation of 7MeGpppAC5 was observed ( Figure 2C ) , but not of GpppAC5 ( Figure 2B ) . In control reactions , containing either nsp10 alone or nsp10 supplemented with nsp14 no 7MeGpppAC5-specific MTase activity was detected ( Figure 2C ) . When the GpppAC5 substrate was incubated with a combination of nsp10 , nsp14 , and nsp16 ( Figure 2B ) , the level of substrate methylation was enhanced compared to reactions performed with nsp14 alone . After overnight incubation of GpppAC5 with the three proteins , the methyl incorporation reached a plateau and the incorporation level was twice higher than after a reaction in the presence of nsp14 alone ( not shown ) . In contrast , no significant difference was observed between the methylation level reached after incubation of the 7MeGpppAC5 substrate with either all three proteins or the nsp16-nsp10 pair only ( Figure 2C ) . Taken together , these results suggest that , ( i ) SARS-CoV nsp14 methylates GpppAC5 at the N7-position of the cap guanine and indeed acts as an N7-MTase on these substrates , ( ii ) nsp16 acts as an nsp10-dependent 2′O-MTase on 7MeGpppAC5 , ( iii ) the 2′O-MTase activity of nsp16-nsp10 requires the presence of a cap structure already methylated at its N7-position and ( iv ) nsp14 and the nsp16-nsp10 pair can perform sequential double methylation of GpppAC5 , presumably at the N7- and 2′O-positions . To determine how nsp10 stimulated nsp16 MTase activity , we co-expressed in E . coli an N-terminally Strep-tagged nsp10 and a His6-tagged nsp16 . The bacterial cell lysate containing these proteins was incubated with Strep-Tactin beads ( see Materials and Methods ) , in order to bind the tagged nsp10 . After extensive washing , the proteins bound to the beads were analysed using SDS-PAGE . Figure 2D indicates that nsp16 remained associated with nsp10 , whereas nsp16 alone was unable to bind to the beads . These data suggest that nsp10 can stimulate the MTase activity of nsp16 by direct association resulting in the formation of a nsp10/nsp16 complex . When the intensities of the bands corresponding to nsp10 and nsp16 were quantified , a ratio of nsp10 to nsp16 of 1 . 1 was obtained . Correcting for the respective molecular masses , and assuming that they bind Coomassie blue dye with the same affinity , this yields a nsp10 to nsp16 ratio of about 2 . 3 . This suggests that the complex does not contain a large molar excess of nsp10 , as one might have expected due to the fact that nsp10 seems to form dodecamers under certain conditions [38] . In order to test MTase activities of nsp14 and nsp10/nsp16 on virus-specific capped RNA substrates , we synthesized a 5′-triphosphate-carrying RNA corresponding to the first 264 nucleotides of the SARS-CoV genome using the T7 RNA polymerase . Since the canonical T7 promoter inefficiently directs transcription of RNA beginning with an A , as is required to make transcripts resembling the 5′ end of coronavirus RNAs , we used the T7 class II φ2 . 5 promoter [43] . Additionally , we introduced a U→G substitution in the 2nd position of the RNA to increase the in vitro transcription efficiency ( data not shown ) . The RNA was capped with [α-32P]-GTP using the vaccinia virus ( VV ) capping enzyme ( containing RTPase , GTase and N7-MTase activities , see Materials and Methods ) in the presence or absence of the methyl donor AdoMet . The substrates GpppAG-SARS-264 and 7MeGpppAG-SARS-264 were then incubated with various combinations of nsp14 , nsp16 , and nsp10 . Reaction products were digested by nuclease P1 in order to release the RNA cap structure . Radiolabeled cap molecules were subsequently separated on TLC plates and visualized using autoradiography . The comparison with commercially available and in-house synthesized cap analogs allowed the identification of the methylation position of the cap structure . Figure 3A shows that the cap structure released after nuclease P1 digestion of substrates GpppAG-SARS-264 and 7MeGpppAG-SARS-264 RNA co-migrated , as expected , with GpppA and 7MeGpppA cap analogs , respectively . In the presence of nsp14 , or the VV:N7-MTase positive control , the GpppA cap structure present at the 5′ end of the RNA was converted into 7MeGpppA ( left panel of Figure 3A ) . We also observed that the methylation of the N7-position induced by nsp14 was weakly stimulated in the presence of nsp10 , but was not influenced by the presence of nsp16 . Indeed , nsp14 converts 83% of the substrate into the 7MeGpppA product , whereas in the presence of nsp10 97% of the substrate was converted , as judged by autoradiography analysis . Nsp10 or nsp16 alone did not show any MTase activity . When all three proteins are present , the substrate is fully methylated at the N7- and 2′O-positions of the cap , as judged by the comparison with products generated by the bifunctional N7- and 2′O-MTase domain of dengue virus protein NS5 ( DV:NS5MTase ) , which was used as a positive control [32] , [42] . The right panel of Figure 3A shows that incubation of 7MeGpppAG-SARS-264 RNA , with nsp14 , nsp16 or nsp10 alone did not result in 2′O-methylation of the 7MeGpppA structure . The same was true when nsp14/nsp10 or nsp14/nsp16 combinations were tested . In contrast , 2′O-methylation of the cap structure of 7MeGpppAG-SARS-264 occurred upon incubation with nsp10/nsp16 , and also when all three proteins were used together . We therefore conclude that capped RNA corresponding to the first 264 nucleotides of the SARS-CoV genome represents a bona fide substrate to follow the RNA cap MTase activities of SARS-CoV nsp14 and nsp10/nsp16 . Moreover , the TLC analysis allowed us to demonstrate that nsp14 indeed specifically methylates RNA cap structures at the N7-position and that nsp10/nsp16 methylates capped RNA at the 2′O-position of the first nucleotide after the N7-methylated cap . As also observed when using short substrates , nsp10/nsp16 could only methylate 7MeGpppAG-SARS-264 and not GpppAG-SARS-264 , suggesting that N7-methylation by nsp14 must precede 2′O-methylation by nsp10/nsp16 . We conclude that nsp14 exhibits N7-MTase activity in the absence of nsp10 , whereas the latter is an absolute requirement for nsp16-mediated 2′O-methylation of the cap structure . Nsp10 , which was previously shown to interact with both nsp14 and nsp16 [35] , [36] , modestly stimulates the nsp14-mediated cap N7-MTase activity ( Figure 3A and S1B; 10 to 15% increase of activity at a broad optimum around a 4-fold molar excess ) . In order to directly monitor the order of SARS-CoV RNA-cap methylation , we performed a time-course experiment using the GpppAG-SARS-264 substrate in conjunction with nsp10 , nsp14 , and nsp16 . The results , shown in Figure 3B , indicate that methylation of the substrate indeed starts at the N7-position . Subsequently , the 7MeGpppA cap-0 structure is converted to an 7MeGpppA2'OMe cap-1 structure . A GpppA2'OMe structure was never observed in this assay , not even when using larger amounts of nsp10/nsp16 or nsp16 ( data not shown ) , in agreement with the data presented in Figures 2B and 3A that show that GpppAC5 and GpppAG-SARS-264 substrates are not methylated by nsp10/nsp16 . Thus , the N7-methylation of the SARS-CoV cap structure by nsp14 is a pre-requisite for its recognition by the nsp10/nsp16 pair , which then converts the cap-0 into a cap-1 structure by 2′O-methylation . The recent identification of the C-terminal domain of nsp14 as an N7-MTase [17] revealed that this replicase subunit is a multifunctional protein , since it also carries an exoribonuclease activity embedded in its N-terminal domain [16] . The interplay between these two functionalities was analyzed using mutagenesis experiments . We mutated conserved residues in both the MTase and the exoribonuclease domain to evaluate the possible interplay or long-range regulation of both activities . The conserved residue D331 , which is presumably involved in AdoMet-binding , was mutated to alanine . In the exoribonuclease domain , we replaced conserved residues from exonuclease motifs I ( D90XE92 ) , II ( D243 ) and III ( D273 and H268 ) of the DE ( A/D ) D nuclease superfamily . All the His-tagged nsp14 mutant proteins could be expressed , except the D243A mutant , which was barely soluble . Figure 4A shows that they migrated at a molecular mass similar to that of wt nsp14 upon SDS-PAGE . We next analyzed their N7-MTase activity on GpppAC5 using [3H]-AdoMet as methyl donor . The results show that the D331A point mutation completely abolished nsp14 N7-MTase activity . This is in agreement with the hypothesis [17] that the MTase domain is located in the C-terminal half of nsp14 protein and that the conserved residue D331 is important for N7-MTase function . In contrast , the mutations in the exonuclease domain did not significantly interfere with nsp14 MTase activity , excepted in the case of the motif I-double mutant ( D90XE92 ) which displayed attenuated N7-MTase activity ( ∼2-fold ) . This observation is in agreement with the fact that a N-terminal truncation of 90 amino acids of the nsp14 exoribonuclease domain abolished the N7-MTase activity in a yeast trans-complementation assay [17] . Thus an altered N-terminus of the exoribonuclease domain may still interfere with the MTase activity to a certain extent . In order to ascertain that nsp16 supports the 2′O-MTase activity and not the nsp10 protein , we engineered and characterized a set of nsp16 point mutations . We mutated the conserved residues K46-D130-K170-E203 , which form the canonical catalytic tetrad of mRNA cap 2′O-MTases [42] , [44] . The putative catalytic residues of SARS-CoV nsp16 were identified using sequence alignment with the homologous FCoV nsp16 2′O-MTase and other family members [18] . Three of the four alanine point mutants could be expressed as efficiently as wt nsp16 , allowing their purification to homogeneity using a single-step of affinity chromatography ( see Materials and Methods ) . Still , smaller amounts of the fourth mutant ( K46A ) could also be produced and purified . We obtained sufficient soluble protein to perform MTase assays , although protein yield and purity were lower than for the other mutants ( Figure 4B ) . For all mutant proteins , the 2′O-MTase activity was tested on 7MeGpppAC5 and compared to that of the wt nsp16/nsp10 control pair . The 2′O-MTase activity was indeed completely abolished by any single mutation of the putative K46-D130-K170-E203 catalytic tetrad residues of nsp16 . This result demonstrated that although nsp10 stimulates the 2′O-MTase activity by a yet unknown mechanism , the catalytic activity itself resides in nsp16 . Viral MTases exhibit many original features relative to their host cell MTase counterparts , and are increasingly explored as putative targets for the development of antivirals [45] . In order to set up sensitive N7- and 2′O-MTase inhibition tests , we determined more precisely the conditions to measure optimum MTase activity for nsp14 and nsp16/nsp10 using their respective substrates GpppAC5 and 7MeGpppAC5 ( see Text S1 ) . We thus defined the following standard assay conditions: the N7-MTase activity of nsp14 was measured in presence of 40 mM Tris-HCl , pH 8 . 0 and 5 mM DTT . For the 2′O-MTase assays , the same buffer was used together with 1 mM of MgCl2 . As Figure S1B illustrates , nsp10 stimulates nsp16 2′O-MTase activity in a dose-dependent manner . We used a 6-fold molar excess of nsp10 over nsp16 corresponding to ≈75% of the maximal stimulation that could be achieved . Inhibition was tested for two AdoMet analogs with documented mRNA cap MTase inhibition properties: AdoHcy ( S-adenosyl-l-homocysteine ) , the co-product of methyl transfer , and sinefungin [18] , [46] , [47] , [48] , [49] . We also used compounds known to target other AdoMet-dependent MTases , such as SIBA , 3-deaza-adenosine [50] and MTA [51] . Based on their adenosine or guanosine-containing structures , adenosine- and AdoMet-analogs 2′ , 3′ , 5′-tri-O-acetyl-adenosine and S-5′-adenosyl-L-cysteine were tested as well as GTP , 7MeGTP , GTP- or cap-analogs ( ribavirin and its triphosphate as well as EICAR-triphosphate , GpppA and 7MeGpppA ) . Finally , we included two inhibitors of flavivirus mRNA cap MTase activites: aurintricarboxylic acid ( ATA ) , which is expected to bind to the MTase active site [52] , and a substituted adamantane compound supposedly binding to the AdoMet-binding site [53] . Interestingly , ATA has been shown recently to inhibit SARS-CoV replication by an unknown mechanism of action [41] . Nsp14 and nsp16/nsp10 were first incubated with 100 µM of each candidate inhibitor in the presence of [3H]-AdoMet . N7- and 2′O-MTase activities were determined by quantification of methyl transfer to the GpppAC5 and 7MeGpppAC5 RNA substrates , respectively . As shown in Figure 5A , 10 out of 16 tested molecules barely inhibited the SARS-CoV MTases . Cap analogs ( GpppA and 7MeGpppA ) showed limited ( 50% ) inhibition capacity on both SARS-CoV MTases . In contrast , we observed that AdoHcy , sinefungin and ATA efficiently inhibited both enzymes at 100 µM . The IC50 values of AdoHcy were 16 and 12 µM for the N7- and 2′O-MTase activities , respectively ( Figure 5B ) ten-fold higher than Ki values reported for VV:N7- and 2′O-MTases ( 1 and 0 . 5 µM , respectively , [47] ) . Sinefungin , a potent inhibitor of VV:N7- and 2′O-MTases with reported IC50 values of 12 . 0 and 39 . 5 nM , respectively [46] , showed the most potent inhibition profile on nsp14 and nsp10/nsp16 with IC50 values of 496 nM and 736 nM , respectively ( Figure 5C ) . These values are similar to the IC50 value reported for the inhibition of the 2′O-MTase activity of DV:NS5MTase ( 420 nM [49] and 630 nM [48] ) . The obtained IC50 values of ATA for SARS-CoV nsp14 and nsp10/nsp16 were 6 . 4 µM and 2 . 1 µM , respectively ( Figure 5D ) . These results demonstrate that sensitive assays are now available to discover and characterize inhibitors of the SARS-CoV N7- and 2′O-MTases rendering low IC50 values of known AdoMet-dependent MTase inhibitors like AdoHcy and sinefungin . Moreover we have shown that nsp14 and nsp16 MTases are two putative targets of ATA , that was shown to inhibit SARS-CoV replication in infected cells [41] .
The nsp10 protein was previously proposed to play a role in viral RNA synthesis [11] , [39] , [40] and replicase polyprotein processing [40] on the basis of the analysis of MHV nsp10 mutants . In this work , we propose a new function for nsp10 as a regulator of an enzyme involved in the methylation of cap structures . Our observation seems not directly related to the phenotype previously described for nsp10 mutants [11] , [39] , [40] . Nevertheless , RNA cap methylation defects should limit RNA stability and may therefore contribute to a decrease in viral RNA synthesis observed in MHV mutants [11] , [39] , [40] . Here , we show that nsp10 itself is catalytically inert in methylation reactions ( Figures 2 , and 3 ) and that it forms a complex with nsp16 ( Figure 2C ) . Interestingly , whereas at least a 10-fold molar excess of nsp10 is required for maximal stimulation of nsp16 ( Figure S1B ) , quantification of the protein bands of nsp10 and nsp16 in the purified complex indicates a maximum ratio of 2 . 3 ( Figure 2D ) . We assume that , under conditions of maximal stimulation , nearly all nsp16 molecules are associated with one or two nsp10 molecules . Considering that the reaction mixture at 50% stimulation contained 200 nM of nsp16 and around 400 nM of nsp10 ( Figure S1B ) , the dissociation constant of the nsp10/nsp16 complex can roughly be estimated to be in the order of 400 nM for a 1∶1 complex or 200 nM for a 2∶1 complex . This is in agreement with a Kd of 250 nM determined by plasmon surface resonance analysis ( Lecine P . personal communication ) . What could be the mechanism of nsp16 activation by nsp10 ? Nsp10 may increase the stability of nsp16 , stabilize the nsp16 RNA binding groove , contribute to RNA substrate binding and/or allosterically regulate its substrate affinity and activity . Similar activation of an MTase involved in the capping pathway was previously reported for the VV capping enzyme [54] . The catalytic efficiency of the N7-MTase domain of the VV:D1 protein was 370-fold stimulated by addition of an equimolar concentration of the small VV:D12 protein , which does not contain any catalytic residues [55] . Activation is achieved through increase of substrate and co-substrate affinity as well as of the turn over number . At the same time , VV:D12 exerts a stabilizing effect on VV:D1 [55] . The determination of the crystal structure of the protein complex VV:D1/D12 [56] revealed that the VV:D12 protein is structurally homologous to the cap 2′O-MTase of reovirus , with a truncation of the AdoMet binding domain . The SARS-CoV nsp10 crystal structure did not reveal any similarity to an MTase fold nor to any protein in the Protein Data Bank ( PDB ) [37] , [38] , but the activating effect of nsp10 on nsp16 might also be exerted on different levels via allosteric activation by increasing substrate affinity and/or turn over number , and/or by stabilization of nsp16 . The presence of two Zn fingers is a major structural feature of nsp10 that is likely related to its biological functions , since Zn fingers typically function as interaction modules binding to proteins , nucleic acid and small molecules [57] . Interestingly , several MTases have previously been shown to be regulated through specific interactions with Zn finger domains [58] , [59] . Since the first Zn finger of nsp10 lies in a positively charged surface patch , it might be involved in the low affinity interaction of nsp10 with single- and double-strand RNA and DNA [37] . The affinity of nsp10 for single–stranded RNA appears too weak to explain a direct role in RNA recruitment for nsp16 [36] . We expect that SARS-CoV nsp16 contains a specific binding site for a cap-0 structure followed by a small stretch of 3 to 4 nucleotides as predicted for FCoV nsp16 from enzymatic assays [18] . The formation of the complex nsp10/nsp16 might provide a longer substrate-binding site and in that way enhance affinity of nsp16 for its RNA substrate . Nevertheless , given the fact that the full activation effect by nsp10 is also seen when short substrates containing the cap and 5 nucleotides are used , we surmise that extension of the RNA binding site is of minor importance . Further work is needed in order to understand the molecular basis of nsp16 activation by nsp10 . There are indications that CoV genomic RNAs and subgenomic RNAs carry a 5′-terminal cap-1 structure ( see Introduction ) and three of four putative cap-forming enzyme functions required to produce this structure have now been identified for SARS-CoV ( nsp13 , nsp14 , and nsp16 ) [3] , [17] , [18] . The CoV cap structure methylation seems to follow the “classic” sequence of N7-methylation preceding the 2′O-methylation . The modular structure of two separate single-domain enzymes corresponds to the scenario in metazoan and plants [25] , [26] . It contrasts to dsRNA reoviruses where one multi-domain protein contains two MTase domains [60] and to flaviviruses and negative-strand RNA ( ( - ) RNA ) vesiculoviruses where both MTase activites reside in a single domain of larger proteins and use a single active site [32] , [61] . A characteristic feature of CoV MTases is that nsp14 recognizes non-methylated RNA cap exclusively , and nsp10/nsp16 recognizes N7-methylated RNA cap exclusively . In contrast , bi-functional MTases recognize both non-methylated and methylated cap structures with equal affinity [48] , [62] , [63] . Interestingly , the flaviviral N7-MTase activity is regulated by specific 5′-proximal viral RNA secondary structures and both N7- and 2′O-MTase activities seem to require in particular the terminal dinucleotide AG [32] , [64] . Since the SARS-CoV nsp14 N7-MTase activity can complement N7-MTase defects in yeast , [17] , it suggests that specific sequences and/or RNA structures are not required for this activity . This was confirmed in our in vitro assays , where both N7- and 2′O-methylation was observed using small GpppAC5 RNA substrates that do not correspond to the natural sequence present at the 5′ end of CoV mRNAs . Nevertheless , the CoV capping machinery is likely to act specifically on viral mRNA substrates , which present a common 5′-terminal leader sequence ( 72 nucleotides long in the case of SARS-CoV [4] ) . The mechanism to achieve this selectivity may depend on the GTase reaction or on the fine regulation of capping enzymes by protein-protein interactions within the replication and transcription complex . The regulation of the 2′O-MTase activity of nsp16 by the small nsp10 protein is clearly an original feature of CoV mRNA cap methylation . Virally encoded RNA cap N7- and 2′O-MTase activities have been identified in various virus families , such as dsDNA poxviruses [65] , [66] , dsRNA reoviruses [67] , [68] , ( - ) RNA viruses such as vesicular stomatitis virus [61] , and ( + ) RNA viruses like flaviviruses [33] , [42] , [69] . For many of them , including coronaviruses [17] , [30] , it has been shown that mutations abolishing the N7-MTase activity have a clear detrimental effect on replication [32] , whereas 2′O-MTase knockouts exerted more moderate effects [32] , [33] . These observations suggest that compounds specifically inhibiting cap MTases could be potent antiviral agents . Although some viral MTase inhibitors have also been reported to inhibit mammalian MTases [70] , [71] , sinefungin or other AdoMet analogs might have higher specificity towards viral MTases . Accordingly , it has been shown that sinefungin inhibits fungal mRNA cap N7-MTases with 5 to 10 times more potency than the human isoform [71] . Here , we report assays using GpppAC5 and 7MeGpppAC5 substrates that constitute sensitive screening tests for the identification and characterization of inhibitors of the N7- and 2′O-MTase activities , respectively , of SARS-CoV . We confirmed this by obtaining low IC50 values of known AdoMet-dependent MTase inhibitors AdoHcy and sinefungin . Furthermore , we found that ATA , a compound previously reported as a putative blocker of the catalytic site of NS5MTase of flaviviruses [52] , and of SARS-CoV replication in infected cells [41] , inhibited both SARS-CoV MTase activities with IC50 values of 2 . 1 and 6 . 4 µM , respectively . Thus , we propose that nsp14 and nsp16/nsp10 are two of the SARS-CoV targets of ATA leading , or at least contributing , to the inhibition of SARS-CoV replication . In conclusion , our results identify and characterize the main viral protein players of SARS-CoV mRNA cap methylation . Its specificity and mechanistic originality remain unparalleled thus far and should open new avenues to investigate viral RNA capping , a field that is increasingly permeable to drug design projects .
AdoMet and cap analogs GpppA and 7MeGpppA were purchased from New England BioLabs . The compounds tested as MTase inhibitors were purchased from the following providers: Sigma-Aldrich: AdoHcy ( adenosine-homocysteine ) , GTP , 7MeGTP , 3-deaza-adenosine , SIBA ( 5′-S-isobutylthio-5′-deoxyadenosine ) , sinefungin ( adenosyl-ornithine ) , ribavirin ( 1-β-D-ribofuranosyl-1 , 2 , 4-triazole-3-carboxamide ) , MTA ( 5′-deoxy-5′-methylthio-adenosine ) , 2′ , 3′ , 5′-tri-O-acetyladenosine , S-5′-adenosyl-L-cysteine , 1 , 2- ( ( ( 3- ( 4-methylpenyl ) adamantine-1-yl ) cabomoyl ) and ATA ( aurintricarboxylic acid ) ; TriLink Biotechnologies: Ribavirin-triphosphate and ribavirin . EICAR- ( 5-Ethynyl-1-β-D-ribofuranosylimidazole-4-carboxamide ) -triphosphate was a kind gift from P . Herdewijn ( Leuven , Belgium ) . They were dissolved in H2O or DMSO as previously described [18] , [52] , [53] and ATA was dissolved in 0 . 1 M NaOH as described in [52] . Concentrations were set to 10 mM and compounds stored at -20°C . All radioactive reagents were purchased from Perkin Elmer . The SARS-CoV nsp10- , nsp14- , and nsp16-coding sequences were amplified by RT-PCR from the genome of SARS-CoV Frankfurt-1 ( accession number AY291315 ) as previously described [72] . The nsp10 , nsp14 , and nsp16 genes ( encoding residues 4231–4369 , 5903–6429 , and 6776–7073 of replicase pp1ab ) were cloned using Gateway technology ( Invitrogen ) into expression vector pDest14 ( pDest14/6His-nsp10 , pDest14/6His-nsp14 and pDest14/6His-nsp16 ) to produce recombinant proteins carrying an N-terminal His6-tag . The nsp14 gene was also cloned into the pTXB1 vector from the Impact kit ( New England Biolabs ) to generate the pTXB1-nsp14 plasmid that allows the expression of the nsp14 protein fused to the intein-chitin binding domain . SARS-CoV nsp10/nsp16 complex was produced in E . coli in a bi-promotor expression plasmid kindly provided by Bruno Coutard ( AFMB France ) . In this backbone , SARS CoV nsp10 can be expressed under a tet promoter and encodes a protein in fusion with a N-terminal strep tag , whereas nsp16 is expressed under a T7 promoter and encodes a protein in fusion with a N-terminal hexa-histidine tag . The single point mutants of pDest14/6His-nsp14 ( the mutant numbering starts at the beginning of the nsp14 sequence; D90A & E92A , H268A , H268L , D273A and D331A ) and the mutants of pDest14/6His-nsp16 ( the mutant numbering starts at the beginning of the nsp16 sequence; K46A , D130A , K170A , E203A ) were generated by PCR using the Quickchange site–directed mutagenesis kit ( Stratagene ) , according to the manufacturer's instructions . E . coli C41 ( DE3 ) cells ( Avidis SA , France ) , containing the pLysS plasmid ( Novagen ) , were transformed with the various expression vectors and grown in 2YT medium containing ampicillin and chloramphenicol . Protein expression was induced by addition of IPTG to a final concentration of 500 µM ( nsp10 ) or 50 µM ( nsp14 and nsp16 ) , when the OD600 nm value of the culture reached 0 . 5 . Nsp10 expression was performed during 4 h at 37°C , whereas nsp14- and nsp16-expressing bacteria were incubated during 16 h at 17°C . Bacterial cell pellets were frozen and resuspended in lysis buffer ( 50 mM HEPES , pH 7 . 5 , 300 mM NaCl , 5 mM MgSO4 , 5 mM β-mercaptoethanol ( only for nsp10 ) supplemented with 1 mM PMSF , 40 mM imidazole , 10 µg/ml DNase I , and 0 . 5% Triton X-100 . After sonication and clarification , proteins were purified by two steps of chromatography except the nsp14 mutants , which were purified by one-step of IMAC ( HisPurTM Cobalt Resin; Thermo Scientific ) and concentrated on 50-kDa centrifugal filter units ( Millipore ) . Two-step purification of the His6-tagged proteins started with IMAC ( HisPurTM Cobalt Resin; Thermo Scientific ) eluting with lysis buffer supplemented with 250 mM imidazole . Protein fractions were then loaded on a HiLoad 16/60 Superdex 200 gel filtration column ( GE Healthcare ) , and eluted with 10 mM HEPES , pH 7 . 5 , 150 mM NaCl . The protein fractions were concentrated to around 2 mg/ml and stored at −20°C in the presence of 50% glycerol . The nsp14 protein expressed in fusion with the intein-chitin binding domain was purified on a chitin column using the IMPACT kit ( New England Biolabs ) . The bacterial lysate was loaded onto the column , washed with 50 mM HEPES pH 7 . 5 , 1 M NaCl and 0 . 5% Triton X-100 . The column was then incubated in 50 mM HEPES pH 7 . 5 , 500 mM NaCl , 50 mM DTT at 4°C for 48 hours in order to induce the intein cleavage . Next , the protein was eluted in 50 mM HEPES pH 7 . 5 , 1 M NaCl buffer and subsequently purified on a HiLoad 16/60 Superdex 200 gel filtration column ( GE Healthcare ) as describe above . The identity of each of the purified proteins was confirmed by MALDI-TOF after trypsin digestion . SARS-CoV nsp10/nsp16 co-expression was performed in E . coli strain C41 ( DE3 ) ( Avidis SA , France ) transformed with the pLysS plasmid ( Novagen ) . Cultures were grown at 37°C until the OD600nm reached 0 . 6 . Expression was induced by adding 50 µM IPTG and 200 µg/L of anhydrotetracycline; then cells were incubated for 16 h at 24°C . Bacterial pellets were treated as given above and the soluble protein fraction incubated with Strep-Tactin sepharose ( IBA Biotagnology ) . After 3 washes , bound proteins were eluted with 2 . 5 mM D-desthiobiotin in binding buffer . After analysing the purified protein complex by SDS-PAGE , the intensities of Coomassie-stained bands were quantified using ImageJ . Short capped RNAs ( 7MeGpppAC5 , GpppAC5 , were synthesized in vitro using bacteriophage T7 DNA primase and were purified by high-performance liquid chromatography ( HPLC ) as previously described [69] . RNA substrate corresponding to the 5′-terminal 264 nucleotides of the SARS-CoV genome ( 5′ SARS-264 ) was prepared as follows . The 5′ UTR of the SARS-CoV genome Frankfurt-1 was amplified by PCR using the primers BamH1-T7phi2 . 5-5′SARS ( s ) ( CGGGATCCCAGTAATACGACTCACTATTATATTAGGTTTTTACCTACCC ) and EcoRI-SARS-264 ( as ) ( GGAATTCCTTACCTTTCGGTCACAC ) and cloned in the pUC18 ( Fermentas ) plasmid after BamHI/EcoRI restriction-ligation procedure . The T7 class II Φ2 . 5 promoter [43] was used ( underlined in the primer ) and the second nucleotide of the genome ( U ) was substituted by a G . The transcription matrix , was amplified by PCR ( primers BamH1-T7phi2 . 5-5′SARS-AG ( s ) ( CGGGATCCCAGTAATACGACTCACTATTAGATTAGGTTTTTACCTACCC ) and SARS-264 ( as ) ( CTTACCTTTCGGTCACAC ) ) and purified on agarose gel using the QIAquick gel extraction kit ( Qiagen ) . The AG-SARS-264 RNA substrate was synthesized by in vitro transcription using the MEGAshortscript T7 RNA polymerase kit ( Ambion ) . After DNase treatment ( Ambion ) , and purification by RNeasy mini kit ( Qiagen ) , the AG-SARS-264 RNA was incubated for 1 h at 37°C with the VV capping enzyme ( ScriptCap m7G Capping kit , Epicentre Biotechologies ) in a reaction volume of 20 µl , either in the absence or in the presence of AdoMet , according to the instructions of the manufacturer . 10 µCi [α-32P]-GTP ( PerkinElmer , Boston , MA ) and 0 . 05 units of inorganic pyrophosphatase ( Sigma–Aldrich ) were used . Radiolabeled capped RNAs GpppAG-SARS-264 and 7MeGpppAG-SARS-264 were then purified with the RNeasy mini kit ( Qiagen ) . MTase activity assays were performed in 40 mM Tris-HCl , pH 8 . 0 , 5 mM DTT , 1 mM MgCl2 ( only for nsp16/nsp10 ) , 2 µM 7MeGpppAC5 or GpppAC5 , 10 µM AdoMet , cand 0 . 03 µCi/µl [3H]AdoMet ( GE Healthcare ) . In the standard assay , nsp10 , nsp14 , and nsp16 were added at final concentrations of 1 . 2 µM , 50 nM , and 200 nM , respectively . The final concentrations of nsp14 and nsp16 used in the assays were chosen so as to stay in the linear phase of product formation after a 1 h incubation when using GpppAC5 or 7MeGpppAC5 as substrates . A 6-fold molar excess of nsp10 over nsp16 was chosen to achieve about 75% of the maximal stimulation of 2′O-MTase activity . Under these conditions , the nsp14 and nsp10/nsp16 methylation reactions converted similar amounts of substrate after 1 h of reaction . No sign of protein inactivation was found up to the apparent end of the linear phase . Reaction mixtures were incubated at 30°C and stopped after the indicated times by a 10-fold dilution of the reaction mixture in 100 µM ice-cold AdoHcy . Samples were kept on ice and then transferred to glass-fiber filtermats ( DEAE filtermat; Wallac ) by a Filtermat Harvester ( Packard Instruments ) . Filtermats were washed twice with 0 . 01 M ammonium formate , pH 8 . 0 , twice with water , and once with ethanol , dried , and transferred into sample bags . Betaplate Scint ( Wallac ) scintillation fluid was added , and the methylation of RNA substrates was measured in counts per minute ( cpm ) by using a Wallac 1450 MicroBeta TriLux liquid scintillation counter . For inhibition assays , we set up the reactions as described above with 7MeGpppAC5 for nsp16 and GpppAC5 for nsp14 in the presence of 100 µM inhibitor candidate . Enzymes and RNA substrates were mixed with the inhibitor before the addition of AdoMet to start the reaction . The final concentration of DMSO in the reaction mixtures was below 5% , and control reactions were performed in presence of DMSO , which does not alter MTase activity . Reaction mixtures were incubated at 30°C for 4 h and analyzed by filter binding assay as described above . The IC50 ( inhibitor concentration at 50% activity ) value of AdoHcy , sinefungin and ATA were determined using Kaleidagraph . Data were adjusted to a logistic dose-response function , % activity = 100/ ( 1+[I]/IC50 ) b , where b corresponds to the slope factor and [I] corresponds to the inhibitor concentration [73] . MTase activity assays were performed in 40 mM Tris-HCl , pH 8 . 0 , 5 mM DTT , 1 mM MgCl2 ( only for nsp16/nsp10 ) , 50 µM AdoMet and 0 . 75 µM of capped AG-SARS-264 RNA at 30°C . The reaction was stopped after different reaction times by incubating samples for 5 min at 70°C . Samples were treated overnight with proteinase K ( 0 . 1 µg/µl , Invitrogen ) . Proteinase K was inactivated by addition of 5 mM PMSF; and the RNAs were subsequently digested for 4 h with nuclease P1 ( 0 . 05 U/µl , USBiological ) . Radiolabeled cap analog standards were produced by direct digestion of the substrates leading to GpppA and 7MeGpppA or digestion after methylation of the 2′O-position using VV 2′O-MTase ( ScriptCap 2′O-methyltransferase kit , Epicentre Biotechnologies ) leading to GpppA2'OMe and 7MeGpppA2'OMe . Digestion products were separated on polyethyleneimine cellulose thin-layer chromatography ( TLC ) plates ( Macherey Nagel ) using 0 . 45 M ( NH4 ) 2SO4 as mobile phase . After drying TLC plates , the caps released by nuclease P1 were visualized using a phosphorimager ( Fluorescent Image Analyzer FLA3000 ( Fuji ) ) .
|
In 2003 , an emerging coronavirus ( CoV ) was identified as the etiological agent of severe acute respiratory syndrome ( SARS ) . SARS-CoV replicates and transcribes its large RNA genome using a membrane-bound enzyme complex containing a variety of viral nonstructural proteins . A critical step during RNA synthesis is the addition of a cap structure to the newly produced viral mRNAs , ensuring their efficient translation by host cell ribosomes . Viruses generally acquire their cap structure either from cellular mRNAs ( e . g . , “cap snatching” of influenza virus ) or employ their own capping machinery , as is supposed to be the case for coronaviruses . mRNA caps synthesized by viruses are structurally and functionally undistinguishable from cellular mRNAs caps . In coronaviruses , methylation of mRNA caps seems to be essential , since mutations in viral methyltransferases nsp14 or nsp16 render non-viable virus . We have discovered an unexpected key role for SARS-CoV nsp10 , a protein of previously unknown function , within mRNA cap methylation . Nsp10 induces selective 2′O-methylation of guanine-N7 methylated capped RNAs through direct activation of the otherwise inactive nsp16 . This finding allows the full reconstitution of the SARS-CoV mRNA cap methylation sequence in vitro and opens the way to exploit the mRNA cap methyltransferases as targets for anti-coronavirus drug design .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"virology/emerging",
"viral",
"diseases",
"virology/viral",
"replication",
"and",
"gene",
"regulation",
"virology/antivirals,",
"including",
"modes",
"of",
"action",
"and",
"resistance"
] |
2010
|
In Vitro Reconstitution of SARS-Coronavirus mRNA Cap Methylation
|
Cationic and heavy metal toxicity is involved in a substantial number of diseases in mammals and crop plants . Therefore , the understanding of tightly regulated transporter activities , as well as conceiving the interplay of regulatory mechanisms , is of substantial interest . A generalized thermodynamic description is developed for the complex interplay of the plasma membrane ion transporters , membrane potential and the consumption of energy for maintaining and restoring specific intracellular cation concentrations . This concept is applied to the homeostasis of cation concentrations in the yeast cells of S . cerevisiae . The thermodynamic approach allows to model passive ion fluxes driven by the electrochemical potential differences , but also primary or secondary active transport processes driven by the inter- play of different ions ( symport , antiport ) or by ATP consumption ( ATPases ) . The model—confronted with experimental data—reproduces the experimentally observed potassium and proton fluxes induced by the external stimuli KCl and glucose . The estimated phenomenological constants combine kinetic parameters and transport coefficients . These are in good agreement with the biological understanding of the transporters thus providing a better understanding of the control exerted by the coupled fluxes . The model predicts the flux of additional ion species , like e . g . chloride , as a potential candidate for counterbalancing positive charges . Furthermore , the effect of a second KCl stimulus is simulated , predicting a reduced cellular response for cells that were first exposed to a high KCl stimulus compared to cells pretreated with a mild KCl stimulus . By describing the generalized forces that are responsible for a given flow , the model provides information and suggestions for new experiments . Furthermore , it can be extended to other systems such as e . g . Candida albicans , or selected plant cells .
System responses to cation induced stress play a pivotal role in a wide range of essential cellular processes . A major challenge for the cell is to maintain optimum cytoplasmic concentrations of cations even under rapidly changing external conditions and perturbations such as salt , osmotic , or alkaline pH stress . The alkali metals such as sodium , potassium ( or lithium ) are considered as vitally important co-factors for a variety of enzymatic reactions and for structural and functional roles in cell metabolism [1 , 2] . However , they are also potent toxic pollutants at high concentrations and relevant for severe biological and medical phenomena ( i . e . blocking of functional groups on important bio-molecules as well as denaturation of enzymes and DNA damage ) [3] [4] . For the unicellular eukaryote Saccharomyces cerevisiae most of the proteins responsible for uptake and extrusion of sodium , potassium , protons and chloride across the cellular membrane have been identified ( see Fig 1 ) and some transport mechanisms are well described ( see Table 1 and [5 , 6] [7] ) . However , despite considerable experimental work and some modeling efforts [8 , 9] the integration of transport systems to ensure homeostasis and the interplay between particular ion transport proteins and factors controlling the rate of transport are not fully understood . Filling this gap could positively affect a wide area of application: Geo- and natural sciences , as well as agronomists consider the issue under the aspects of environmental pollution caused by extensive use of some ( heavy ) metals and metal compounds as e . g . in fungicides and disinfectants . Related agricultural research concerned the ability of plants to tolerate or adapt to a range of environmental stress conditions like e . g . aridity or very high or almost nil concentrations of salt . In biomedical sciences ion homeostasis receives increasing attention due to its role in a number of pathological conditions , such as a variety of neurodegenerative diseases , metabolic disorders and malignant transformations [10] [11] . Therefore , the understanding of tightly regulated transporter activities and the interplay of regulatory mechanisms is of substantial interest and could contribute to the developments in plant growing sciences or to improvements regarding food safety . Furthermore , a better understanding could influence the development of new treatments for fungal infections or the design of new pharmacological agents to treat neurodegenerative diseases . We suggest a predictive mathematical model to gain better understanding of the principles of homeostasis employed by nature . The regulation of intracellular cation content is an important and complex cellular task . In comparison to the relatively controlled environment of most animal cells ( within the tissue context ) , single-celled organisms like e . g . some algae and fungi must tolerate a wide range of sometimes rapidly changing environmental conditions such as osmotic pressures , pH , or salt concentrations in their natural habitats . Moreover , yeast cells accumulate potassium from relatively dilute solutions to sustain a cytosolic K+ concentration within the range of approximately 175–300 mM to counterbalance the intracellular high negative charge from proteins as well as inorganic and organic negatively charged polyanions [6 , 12] . Besides supporting a stable and balanced intracellular cation content , monovalent cation transport is also required for other physiological functions such as maintenance of the cell volume and internal pH , the membrane potential , protein synthesis , and enzyme activation [13–15] . To ensure viability even under adverse external environmental conditions yeast has evolved several response systems to saline , osmotic and alkaline pH stress [12 , 16 , 17] . To maintain an optimum cytoplasmic pH of about 6 . 5 and a stable balanced intracellular sodium/potassium ratio yeast cells invest high amounts of biological energy through ATP hydrolysis and employ three distinct strategies [5]: i ) strict discrimination between alkali metal cations at the level of influx ( e . g . higher affinity of transporters for potassium than for sodium ) , ii ) proper disposal of toxic cations and iii ) selective sequestration of cations in organelles . Eight transport proteins relevant to the regulation and maintenance of intracellular alkali-metal cation content are well characterized ( see Table 1 ) . Comprehensive reviews detail further specifics and mechanisms , regulatory elements and the "long-term" regulation processes by transcription [5 , 6 , 12] . The paper is organized as follows: We first introduce a general thermodynamic concept for the description and analysis of cellular cation fluxes and concentrations . Second , we assign specific parameters , which were obtained from experiments with starved yeast cells . We then use the experimental data for parameter estimation and present model simulations predictive for scenarios not used for parameterization . The underlying experimental scenario is as follows: Yeast cells are starved overnight in water to lose all mobile nutrients and cations . Fluxes are measured from time 0 . At time 300 s the cells are exposed to defined concentrations of KCl ( 0 . 01–10 mM ) . At time 600 s , glucose is added . Potassium and proton fluxes are measured with specific electrodes via the MIFE method ( see Materials and Methods ) .
Our description of ion fluxes and their mutual dependencies is based on the concepts of Non-Equilibrium Thermodynamics ( NET ) . Since decades various theories and mathematical descriptions of active and passive transport executed by transmembrane proteins have been developed . These approaches are as different as complex and have already been extensively published [18–22] to mention just a few of them . The classical studies of ion fluxes ( e . g . on nerves ) have mainly focused on the measurement of the relation between currents and voltage and on the modeling of fluxes caused by combination of single transport systems [23–28] . Typically , every channel or transporter is described with an expression for its current as a function of the membrane potential and the actual concentration of the respective ion . These rate expressions are based on the assumption of linear force-flux relationships , yielding , however , non-linear relations between ion concentrations and ion fluxes . When modeling the behavior of living cells , the selective description of individual channels/transporters carries the risk of overlooking other ion transport processes by transporters that are not yet characterized or known transporters that have additional functions ( e . g . non-specific transport ) or membrane leakage . Thus , understanding the system’s behavior requires the integrative investigation of all transport processes , in addition to exploring individual transporters . Many features change simultaneously and should be integrated into a global model in order to obtain a comprehensive picture of the underlying physical processes . This includes transient pH , enzyme activities , cytosolic buffer capacities , chemical reactions , and changes in membrane potential or concentrations of other important ions . However , due to the complexity of the problem and the sparseness of data , typical kinetic network models that describe every reaction and transport step in detail are not yet feasible . The concept of Non-Equilibrium Thermodynamics , deployed to derive individual transport expressions , provides also a theoretical background to correlate driving forces and the resulting fluxes in cellular systems in a formal manner independent of specific kinetic or statistical models . The relevant forces are the differences in the electrochemical potential of the cations and reaction affinities of biochemical reactions . Fluxes are the resulting fluxes of cations in or out of the cell and the rates of biochemical reactions , respectively . All these irreversible processes lead to a production of entropy . The entropy production for a cellular system can be characterized by the entropy production density [29 , 30] σ=J→Qgrad ( 1T ) −∑i=1nfJ→ifgrad ( ηiT ) +∑i=1nrJirAiT ( 1 ) where σ denotes the local entropy production density , T is the temperature , J→Q is the heat flow density , J→if is the diffusion density of component i , ηi is the electrochemical potential of component i , Jir is the rate of reaction i , Ai is the affinity of reaction i , and nf and nr are the numbers of compounds and reactions , respectively . The various flows and forces are not independent of each other . A temperature gradient could , for example , induce the diffusion flux of a chemical compound besides the heat flux . Due to the constant temperature in the considered experiments , we can disregard temperature gradients and heat flux in the following reasoning . We take generalized forces as Xj . The fluxes are in general non-linear functions of these forces . However , at equilibrium all forces and fluxes vanish . Only in vicinity to equilibrium we can express the fluxes as linear combinations of all forces , based on a Taylor expansion until first order terms as follows: Jif , r=∑j=1nf+nr∂Ji∂XjXj=∑j=1nf+nrLijXj ( 2 ) The partial derivatives of the fluxes with respect to the forces are called phenomenological coefficients and will be denoted with Lij . The Lii are referred to as the "straight coefficients" since they relate the flow Ji to its conjugate driving force Xi , in the analogy with either Ohm‘s or Fick‘s laws . The "cross coefficients" Lij , with j ≠ i , reflect to which extent the flux of species i is affected by the non-conjugate forces , Xj , in the system . The phenomenological coefficients have to fulfill a number of conditions . Since in the absence of other forces , a single force induces a positive conjugate flux , it holds: Lii≥0 ( for alli ) ( 3 ) The fact that the dissipation function is positive implies further that Lij=Lji , ( 4 ) which is also known as “Onsager’s reciprocity relation” [31 , 32] , and that Det[Lij]≥0 . ( 5 ) In the following we specify the relevant forces and fluxes for ion transport and biochemical reactions in the considered experiments . In general , these phenomenological coefficients combine kinetic parameters and transport coefficients and are functions of the parameters of the system but are independent of the flows and forces . Once determined from experimental data they provide an informative basis on the control exerted by the coupled fluxes . Specifically interesting for the maintenance of the intracellular cation concentration is the thermodynamic coupling of the individual fluxes . This enables that a flux may occur without or even against its conjugate thermodynamic driving force , which may be a gradient of the electrochemical potential or reaction affinity . For the cellular response of starved yeast cells to the addition of KCl and glucose we considered the forces resulting from the electrochemical gradients of protons , K+ , Na+ , Cl- , denoted as grad ηH , grad ηK , grad ηNa , and grad ηCl , respectively , as well as the affinity AAr of the reactions converting ATP into ADP or reverse . The conjugated fluxes are the fluxes of protons , JH , potassium , JK , sodium , JNa , and chloride , JCl , as well as the conversion of ATP to ADP or back , JAr . This resulted in the following phenomenological equation system: JH=−LHHgrad ( ηHT ) −LHKgrad ( ηKT ) −LHNagrad ( ηNaT ) −LHClgrad ( ηClT ) +LHArAArTJK=−LKHgrad ( ηHT ) −LKKgrad ( ηKT ) −LKNagrad ( ηNaT ) −LKClgrad ( ηClT ) +LKArAArTJNa=−LNaHgrad ( ηHT ) −LNaKgrad ( ηKT ) −LNaNagrad ( ηNaT ) −LNaClgrad ( ηClT ) +LNaArAArTJCl=−LClHgrad ( ηHT ) −LClKgrad ( ηKT ) −LClNagrad ( ηNaT ) −LClClgrad ( ηClT ) +LClArAArTJAr=−LArHgrad ( ηHT ) −LArKgrad ( ηKT ) −LArNagrad ( ηNaT ) −LArClgrad ( ηClT ) +LArArAArT ( 6 ) Next , we replaced the electrochemical potentials with the expression ηi=μi0+RTlnci+ziFφ ( i∈{H , K , Na , Cl} ) ( 7 ) with ci being the ion concentrations and zi being their charge number , F is Faraday‘s constant and φ is the membrane potential . Since we assume homogeneity of concentrations inside and outside of the cell , the gradient of ηi refers to the derivative of ηi with respect to the spatial direction normal to the cell surface . We approximated it with the difference of ηi between cellular environment ( out , “o” ) and cytoplasm ( in , “i” ) , i . e . Δηi=ηio−ηii . Combined , these considerations resulted in the following equation system: JH=R ( LHHlncHicHo+LHKlncKicKo+LHNalncNaicNao+LHCllncClicClo ) +FTΔφ ( LHH+LHK+LHNa−LHCl ) +LHArAArTJK=R ( LKHlncHicHo+LKKlncKicKo+LKNalncNaicNao+LKCllncClicClo ) +FTΔφ ( LKH+LKK+LKNa−LKCl ) +LKArAArTJNa=R ( LNaHlncHicHo+LNaKlncKicKo+LNaNalncNaicNao+LNaCllncClicClo ) +FTΔφ ( LNaH+LNaK+LNaNa−LNaCl ) +LNaArAArTJCl=R ( LClHlncHicHo+LClKlncKicKo+LClNalncNaicNao+LClCllncClicClo ) +FTΔφ ( LClH+LClK+LClNa−LClCl ) +LClArAArTJAr=R ( LArHlncHicHo+LArKlncKicKo+LArNalncNaicNao+LArCllncClicClo ) +FTΔφ ( LArH+LArK+LArNa−LArCl ) +LArArAArT ( 8 ) The fluxes are considered as outward directed , i . e . Ji=Jii→0and membrane potential difference is Δφ = φi − φo . The generalized thermodynamic description was developed for the complex interaction of specific cation plasma membrane transporters , the membrane potential , and the consumption of energy for maintaining and restoring the respective intracellular cation concentrations based on the theory of NET . The model was then challenged with experimental data representing independent measurements of potassium and proton fluxes ( Fig 2A ) in S . cerevisiae wild type strains after treatment with four different concentrations of KCl followed by addition of glucose ( S1 Data ) . The phenomenological coefficients were estimated to define the degree of coupling between the considered ion fluxes as well as the rate of ATP/ADP conversion . The dynamics of the phenomenological coefficients as well as a basic sensitivity analysis can be found in the S1 Text . Below we discuss two model variants and their biological interpretation .
We introduced a general thermodynamic model for the regulation of ion fluxes through the yeast cellular membrane . This model is based on the acting forces–the electrochemical potentials of the ions–and their interrelations . Using a linear approach we expressed the resulting fluxes without taking into account precise knowledge about the involved channels and transporters . We restricted the model in its application here to the fluxes of the major cations H+ , K+ , Na+ and of the anion Cl− , the conversion of ATP to ADP as an active driving force , the calculation of the internal pH as well as the change in the membrane potential . This was based on the specific experimental scenario analyzed here . Such conditions enable to measure fluxes of protons , potassium , and chloride . However , the theoretical approach presented here should also be applicable to more complex situations with further ions involved . The systematic thermodynamic formulation of the major components contributing to the maintenance of a stable intracellular cation content may become well suited for the purpose of modeling this complex system , particularly at the current early stage of understanding . An approach used by others [8 , 23 , 41] is to model each transporter or channel separately in great detail . We refrained from doing so due to the unavailability of suitable data that describe the contribution of each individual component to measured overall fluxes . Furthermore , detailed modeling of individual transport reactions increases the complexity of the model and a massive amount of parameters must be estimated or taken from sources in which the experimental conditions might not be comparable with those conditions used here . The entirely phenomenological approach applied here does not depend on a detailed understanding and description of structure , function , molecular details , or kinetic parameters of individual constituent as parts of the system . Instead , a level of complexity was chosen which is in accordance with the availability of data for net ion flux measurements obtained under physiologically relevant conditions . By identification of the generalized forces that are responsible for the flux of a given ion , the model is able to assist reinterpreting classical findings on ion flux propagation and provides directions for further efforts aimed at defining transport processes at the molecular level . The results of the simulations are in good agreement with the experimental observations and the theoretical predictions achieved for the values of the phenomenological coefficients are reasonable from the biological point of view . For example , the predicted and validated Cl- influx in addition to the H+ efflux and K+ influx is a reasonable feature from the biological perspective . Since the proton efflux does not reach the same magnitude as the potassium influx , electroneutrality must be ensured by another charged ion . Due to the nature of the experiment ( addition of potassium chloride ) , chloride is available and its influx can compensate the flow of charges by potassium . The chloride flux is likely to affect the membrane potential and , as predicted by the model , counteract the excess of charge , which would normally build up caused by the asymmetry of the H+ and K+ . At the applied experimental conditions , no Na+ fluxes were obtained during the simulation . However , it is also possible that other ions can affect the membrane potential , which are not yet included in the model ( e . g . bicarbonate [8] and phosphate [42] ) and for which no experimental data were available under the present conditions . As a future perspective , it could be very interesting to consider e . g . recent work on the two main high–affinity phosphate transporters , Pho84 and Pho89 [43 , 44] for further improvement of the model . In any case the model is still amenable to development in view of a more comprehensive picture of cation homeostasis . Perspectives and weaknesses of the approach will be discussed as follows . First of all , the restriction set on the system is that it acts close to equilibrium , which is a prerequisite for the linear approach to hold , and thus that fluctuations are insignificant . This implies certain limitations on the processes . If the gradients of the intensive parameters within the system are large it might not satisfy these requirements . The range of applicability of this theory cannot be specified on a priori grounds , and the justification of its use rests , eventually , on the validity of the results obtained . Furthermore , in the model the distribution of substances in the internal as well as the external volume are assumed to be homogeneous . Although this assumption was used previously [8 , 45 , 46] , it might be useful to analyze the effect of spatial gradients in future models . Some intracellular transporters have only recently been identified and characterized . These comprise mainly alkali-metal cation/H+- antiporter , located in the vacuolar membrane ( Vnx1 ) , [47] endosomal membrane ( Nhx1 ) [48] and the Golgi apparatus membrane ( Kha1 ) [49] . These organellar systems also serve to regulate the intracellular K+ — and pH-homeostasis and may play an important role in detoxification of sodium by sequestration in the vacuole . For these intracellular transport systems almost no time resolved biochemical transport data are currently available and were thus not included in the presented model . A description of the temporal behavior should in general also incorporate the rates of changes of the cell volume due to effects on the intracellular osmolarity and changes of the permeabilities for the ions over time [50–53] . These terms would , in turn , simultaneously affect the values of intracellular cation concentrations [50 , 54] . Here , the volume was assumed to remain constant during the simulation . This is a reasonable assumption since the concentrations used in the experiments are far below any critical value ( experiments studying the osmotic stress response via the activation of the Hog-pathway usually start with concentrations of several hundreds of mM NaCl [55–57] ) and already at 0 . 05 M the Hog activation is down to a tenth of the maximum amplitude [58] . Therefore , it is highly unlikely that salt concentrations lower than 0 . 01 M induce any significant osmotic or volume effects . On the other hand substantial progress has already been made in the field of modeling response to osmotic stress via volume and turgor regulation in the yeast S . cerevisiae [59–61] and both models could highly benefit by getting joined . For further and extended versions of the presented model , a combined observation of the regulation of the osmotic response as well as the homeostasis of the major cations Na+ , K+ and intracellular pH should be envisaged for a broader understanding . As a second future perspective the model should also be validated with the support of proper deletion mutants lacking specific transport systems . The impact of such mutant data would provide insights on the reliability of the model when it was confronted with actual measurements .
Data acquisition was performed by using monolayers of S . cerevisiae cells ( grown in YNB-F supplemented with 50 mM KCl till late-log phase , harvested by centrifugation and washed twice with double-distilled water ) immobilized on poly-L-lysine treated glass coverslips . Each cover slip was placed in a total of 3 ml sample buffer volume in a Petri dish . After addition of the specific concentration of KCl the cells were energized with glucose to enable generation of ATP and thus the performance of secondary active transport mechanisms . Net fluxes of K+ and H+ were measured non-invasively using the microelectrode ion flux measuring ( MIFE; University of Tasmania , Hobart , Australia ) technique as described by Shabala et al . [62] [63] The surface of all cells , Surf and the inner volume , Vin were calculated from the detected optical density ( 1 . 2 · 107 cells per ml OD 1 ) applied to achieve a cell monolayer and by assuming a single cellular surface of 63 , 6 μm2 ( based on a round cell with a diameter of 4 . 5 μm ) and a volume of 50 fL according to [64] . The value for Vout was obtained directly from the experimental setup . ATP was estimated to be between 0 and 2 . 5 mM ahead of the glucose addition . The available ATP after the glucose stimulus was supposed to reach 2 . 5 mM , according to previous observations by [65] , and described respectively in Eq 11 . It was assumed that in the starved cells no ATP is available for other than basic vital processes and that addition of glucose is necessary to induce primary and secondary active transport mechanisms [35 , 36] . Accordingly , the parameters LiAr ( i ϵ {H , K} ) were initially set to 0 . It was assumed that only those parameters directly or indirectly involved in primary active transport LiAr ( i ϵ {H , K} ) and Lii ( i ϵ {H , K} ) can change after glucose and that the Onsager relation holds . The model implementation , time course simulation and parameter estimation were performed in COPASI [66] . COPASI comes with a set of implemented optimization methods , which can be used to estimated parameters and initial conditions of mathematical models . Of the given methods , the particle swarm optimization method gave the best results for the model at hand . The particle swarm optimization method [67] imitates the behavior of a biological swarm ( e . g . a flock of birds ) to iteratively optimize model parameters . Starting with given parameter values , the method searches through the parameter space to find the optimal parameter set , i . e . the parameter set which minimizes the error between the current model solution and the experimental values . For this , each parameter set has a position and velocity in the parameter space and also remembers its best-achieved value and position . Depending on its own information and the position of its neighbors a new velocity is calculated and the parameters are updated . More information about the implementation of the algorithm in COPASI can be found at http://www . copasi . org . To minimize the problem of being trapped in local minima , a Python script was implemented to run the particle swarm algorithm 1000 times with random initial parameter values as well as random upper and lower parameter bounds . For the estimation of the initial conditions experimentally verified concentration ranges were used ( see Tables 3–5 ) . The “straight coefficients" Lii were allowed to be positive only , the “cross coefficients" Lij were allowed to be either positive or negative . The options iteration limit 400 , swarm size 40 , standard deviation 1e−6 , random number generator Mersenne Twister [68] and random seed showed good results at a reasonable duration . The best matching parameter sets of the 1000 runs were finally taken; in case a parameter was located at a boundary , this boundary was extended by a factor of 100 and subsequent parameter estimation was performed . The time course simulation was solved with the deterministic LSODA method [69] .
|
Metals , and particularly their positively charged ions ( cations ) , are an integral part of our environment , and all living organisms are exposed to metals in their natural habitat . Even though significant efforts have already been made by experimental and theoretical analysis of the individual components of transport systems and individual transport-mechanisms , such efforts did not result in an integration of the highly connected and complex system . The development of kinetic networks might well contribute to the understanding and visualization of cation homeostasis . However , such kinetic systemic analysis would require more detailed biochemical information than is currently available . We circumvented this problem by using an entirely phenomenological approach of the theory of non-equilibrium thermodynamics . The methodology does not require the detailed understanding of structure , function or kinetic parameters of individual constituents of the system but produces some unique parameters related to thermodynamic couplings between different ion fluxes and ATP consumption . These estimated phenomenological constants combine the kinetic parameters and transport coefficients and control the coupling of fluxes . The model predictions are in good agreement with the biological understanding of the roles of the transporter proteins . Our modeling approach might contribute to the development of new diagnostic and therapeutic purposes with cation-homeostasis as key-target .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"protons",
"medicine",
"and",
"health",
"sciences",
"chemical",
"compounds",
"membrane",
"potential",
"ions",
"electrophysiology",
"carbohydrates",
"organic",
"compounds",
"glucose",
"sodium",
"organisms",
"fungi",
"model",
"organisms",
"biological",
"transport",
"cations",
"thermodynamics",
"physical",
"chemistry",
"saccharomyces",
"research",
"and",
"analysis",
"methods",
"chemistry",
"nucleons",
"yeast",
"physics",
"biochemistry",
"organic",
"chemistry",
"nuclear",
"physics",
"physiology",
"monosaccharides",
"biology",
"and",
"life",
"sciences",
"yeast",
"and",
"fungal",
"models",
"physical",
"sciences",
"saccharomyces",
"cerevisiae",
"metabolism",
"chemical",
"elements"
] |
2016
|
A Thermodynamic Model of Monovalent Cation Homeostasis in the Yeast Saccharomyces cerevisiae
|
Exchange of O2 and CO2 of plants with their environment is essential for metabolic processes such as photosynthesis and respiration . In some fruits such as pears , which are typically stored under a controlled atmosphere with reduced O2 and increased CO2 levels to extend their commercial storage life , anoxia may occur , eventually leading to physiological disorders . In this manuscript we have developed a mathematical model to predict the internal gas concentrations , including permeation , diffusion , and respiration and fermentation kinetics . Pear fruit has been selected as a case study . The model has been used to perform in silico experiments to evaluate the effect of , for example , fruit size or ambient gas concentration on internal O2 and CO2 levels . The model incorporates the actual shape of the fruit and was solved using fluid dynamics software . Environmental conditions such as temperature and gas composition have a large effect on the internal distribution of oxygen and carbon dioxide in fruit . Also , the fruit size has a considerable effect on local metabolic gas concentrations; hence , depending on the size , local anaerobic conditions may result , which eventually may lead to physiological disorders . The model developed in this manuscript is to our knowledge the most comprehensive model to date to simulate gas exchange in plant tissue . It can be used to evaluate the effect of environmental stresses on fruit via in silico experiments and may lead to commercial applications involving long-term storage of fruit under controlled atmospheres .
Exchange of O2 and CO2 of plants with their environment is essential for metabolic processes such as photosynthesis and respiration . Plants do not have specialised systems for gas exchange but rely on apertures in the epidermis such as stomata and lenticels and the intercellular air space within the tissue [1] . Also , in metabolically active organs such as leaves , the diffusion path is usually very short , thus facilitating gas transport . O2 and CO2 gradients have , however , been observed in plant organs such as roots [2] , tubers [3] , stems [4] , inflorescences [5] , seeds [6] and fruit [7] . In roots and bulky storage organs such as fruit and tubers , where the length of the diffusion path may be considerable , anoxic conditions may even occur . Geigenberger et al . [3] observed internal O2 concentrations below 5 kPa , causing partial inhibition of respiration , decrease in the cellular energy status , and partial inhibition of other energy-consuming processes . In some fruits such as pears , which are typically stored under a controlled atmosphere with reduced O2 and increased CO2 levels to extend their commercial storage life , anoxia may even occur , eventually leading to cell death and loss of the product [8] . Similar atmosphere conditions , however , do not seem to affect other fruit such as apples appreciably [9] , [10] . While it is likely that this is related to differences in concentration gradients resulting from differences in tissue diffusivity and respiratory activity , there is little information about such gas gradients in fruit in the literature . Such knowledge would be , nevertheless , very valuable both to understand gas exchange in plant tissue but also to guide commercial storage practices , since disorders under controlled atmosphere related to fermentation are a prime cause of concern [10]–[13] . Microsensors have been used to measure oxygen concentrations in stem transects and phloem exudate of intact Ricinus communis plants [4] , roots [14] , and fruit [15] , [16] . However , no matter how small the electrodes , insertion in fruit tissue causes damage that may result in measurement artefacts . Morison et al . [17] used chlorophyll fluorescence imaging to investigate CO2 diffusion into leaves; while this technique provides spatial information it obviously can only be used when there is an active photosynthetic system , which is not the case in fruit parenchyma cells . Biochemical measurements of indicators of anaerobiosis in roots such as acetaldehye , ethanol and alcohohol dehydrogenase have been carried in roots [18] and in fruit [19] but are indirect and do not provide quantitative data on gas concentrations . As there is , to date , no good method to measure in vivo internal gas concentrations in fruit , a mathematical modelling approach would provide an alternative to predict the internal gas concentrations . Also , once validated such a model could be used conveniently to perform in silico experiments to evaluate the effect of , e . g . , fruit size or ambient gas concentration on internal O2 and CO2 levels without the need for extra experimental effort . Denison [20] developed a reaction-diffusion model for oxygen diffusion and respiration in legume root nodules and found large effects of flooding of the intercellular space on the O2 permeability . Aalto and Juurola [21] constructed a three-dimensional model of CO2 transport in leafs and implemented it into a computational fluid dynamics code . The model accounts for the actual 3D microstructure of a leaf . The authors used the model to investigate the effect of stomatal opening , photosynthetic capacity , temperature and increased ambient CO2 levels on total CO2 flux . Gas exchange in fruit and other bulky storage organs was first modelled macroscopically with Fick's first law as a diffusion process , which is driven by concentration gradients [22]–[24] . The concentration gradients appear because of consumption of O2 and production of CO2 . However , Fick's first law is not capable of describing spatial gas concentration gradients . Several authors [7] , [25] , [26] therefore , developed reaction-diffusion models to describe the exchange of O2 and CO2 inside fruit of different plant species . Diffusion properties of fruit tissue were determined by measuring gas exchange through small tissue samples [27]–[32] . The results showed that the CO2 diffusivity in apple and pear tissue was much higher than the O2 diffusivity . However , as this may cause the outflow of CO2 to be larger than the inflow of O2 , a pressure difference between the inside of the fruit and the external atmosphere may develop . Hence , besides gas diffusion driven by concentration gradients , gas exchange in the fruit may occur by permeation due to pressure gradients in the fruit tissues . The aforementioned models are not capable of describing this effect , and Ho et al . [31] therefore developed a permeation-diffusion-reaction model for describing O2 , CO2 and N2 exchange in pear fruit which does take into account permeation . While this model was used successfully to simulate transport properties in simple disk-shape geometries , it cannot be used to study gas transport in intact pear fruit for the following reasons: The objective of this manuscript was , therefore , to extend this model to account for O2 and CO2 dependent respiration and fermentation processes . The resulting nonlinear model will be numerically solved for an actual pear geometry and validated using measurements on intact pears . In silico experiments will be carried out to study the effect of shape , size , temperature and storage atmosphere composition on macroscopic gas exchange in intact fruit .
A permeation-diffusion-reaction model was constructed to describe exchange of the three major gas atmospheric gases O2 , CO2 , and N2 in pear fruit based on the model described in [31] . The model assumes that gas exchange can be modeled by the lumped properties of the different fruit tissues . Gas exchange properties were independently and experimentally determined . The measurement protocols of gas exchange properties of pear epidermis and cortex tissue were described by Ho et al . [30] , [31] . The driving force for gas exchange was mainly diffusion . Differences in diffusion rates of the different gasses led to total pressure gradients that caused convective exchange as described by Darcy's law [31] . Gas exchange was coupled with the respiration kinetics of fruit tissue . A non-competitive inhibition type of respiration kinetics was applied for O2 consumption and CO2 production [33] , [34] . Kinetic parameters were estimated by means of respiration experiments . The permeation-diffusion-reaction model was applied to the axi-symmetric geometry of pear with variations of gas concentrations in the radial ( r ) and vertical axis ( z ) ( see Materials and Methods ) . The full set of model variables is listed in Table 1 . Both steady and transient simulations were carried out with different external conditions to study the spatial distribution of metabolic gasses in intact pears of different shapes and sizes . The non-competitive inhibition model for O2 consumption and CO2 production described the measured values well with an adjusted R2 of 0 . 94 ( Figure 1 ) , indicating that the model was able to explain 94% of the total variability of the data after correction for the number of degrees of freedom . The correlation coefficients were all smaller than 0 . 71 , suggesting that the model was not overparameterised . Note that because of this correlation between the parameters the confidence intervals are likely to be underestimated and are larger in reality . The estimated parameters for Vm , O2 and Vm , f , CO2 of cortex tissue were ( 2 . 39±0 . 14 ) ×10−4 mol m−3 s−1 and ( 1 . 61±0 . 13 ) ×10−4 mol m−3 s−1 , respectively ( Table 1 ) . The confidence interval is dominated by the biological variability . Km , O2 , a measure for the saturation of respiration with respect to O2 was relative small and equal to ( 1 . 00±0 . 23 ) kPa . A significant but low inhibition effect of CO2 on O2 consumption of pear cortex tissue was found ( Kmn , CO2 = 66 . 4±21 . 3 kPa ) . The respiration quotient rq , ox was 0 . 97±0 . 04 and showed that the O2 consumption was about the same as the oxidative CO2 production . The value Km , f , O2 is a measure of the extent to which fermentation can be inhibited by O2 . The estimated value of 0 . 28±0 . 14 kPa implies that fermentation was already inhibited at very low levels of O2 concentration . The accuracy of the estimated parameter is reflected in the standard errors of estimation . The high standard error of Km , f , O2 is due to the limited amount of information available in the data on the inhibition of fermentation by O2 since in the experimental used set-up it was not possible to obtain very small values of O2 partial pressure could not be obtained . Temperature had a significant effect on the respiration of the pear cortex tissue with values of Ea , Vm , O2 and Ea , Vmf , CO2 equal to ( 80 . 2±12 . 3 ) kJ mol−1 and ( 56 . 7±13 . 3 ) kJ mol−1 , respectively . To study the effect of permeation on gas exchange in whole fruit , Equations 7–9 were solved without and with permeation taken into account . Both simulations were done at 20 kPa O2 and 0 kPa CO2 as external conditions , both at 1°C . There was a significant effect of the permeation on the simulated result ( Figure 3 ) . The O2 and CO2 gas partial pressure profiles along the radial direction from the center to the surface of the pear are shown in Figure 3 . Both the internal O2 and CO2 partial pressure was higher when permeation was included . While diffusion is the main process for the gas exchange inside the pear , the permeation clearly affects the gas exchange profiles . Because there was an effect of permeation on gas exchange inside the fruit , at a certain environment atmosphere , the N2 partial pressure inside the fruit is not the same as the N2 partial pressure of the environment . Due to the respiration of the tissue , the O2 gas partial pressure decreased from the surface to the center of the pear while CO2 decreased in the opposite direction . An increase of N2 from the surface to the center of the pear was found ( Figure 3 ) . The absolute ratio of inward convective over the total pear surface was equal to 0 . 08 , 0 . 0 and 1 . 0 for O2 , CO2 and N2 , respectively . While the convective flux is affected by the local magnitude of concentration , the diffusive flux is affected by the local gradient . The 0 value for CO2 is due to the fact that the concentration of CO2 is 0 at the surface . The value for O2 indicates that diffusion dominates the exchange , but permeation is not negligible . For N2 both mechanisms are equally important . This is confirmed by the profiles in Figure 3 showing the differences when permeation is included or not . Gas exchange was simulated for four pear shapes with different equatorial radii of 2 . 6; 3 . 2; 3 . 4 and 3 . 7 cm . In Figure 4A the respiratory gas partial pressure profiles in the four pears are shown for a storage gas atmosphere composition of 20 kPa O2 , 0 kPa CO2 and 80 kPa N2 at −1°C ( further called “regular air storage” ) . As expected , the gas concentration profiles are parallel to the boundary of the fruit . Due to the gas exchange barrier properties of the cortex and epidermis tissue , the partial pressures of O2 and CO2 in the center of the smallest pear ( 8 . 1 and 2 . 3 kPa ) were significantly higher and lower , respectively , than those of the largest pear ( 1 . 1 and 3 . 74 kPa ) . The values of the other pears were in between these extremes . In Figure 4B the simulations were repeated for a storage gas atmosphere composition of 0 . 5 kPa O2 , 5 kPa CO2 and 94 . 5 kPa N2 at −1°C ( further called “core breakdown inducing controlled atmosphere storage” ) . The profiles are now very different from the previous ones . The partial pressures of O2 and CO2 in the center of the smallest pear were 1 . 23×10−3 and 8 . 14 kPa , respectively . In the largest pear they were 1 . 14×10−3 and 10 . 6 kPa , respectively .
Early models for gas exchange in plant tissue were based on Fick's first law [22]–[24] . They rely on the assumption that the diffusion resistance of the cortex tissue is low compared to that of the skin , which would exclude the existence of a gas gradient in the cortex tissue . The corresponding O2 and CO2 diffusion coefficients are then measured by effusion experiments . However , the steep gas gradient in Figures 3 and 4 indicate that these models are not applicable to pear cv Conference . Further , in the effusion method the diffusion coefficients of O2 and CO2 are calculated from that of an inert gas using Graham's law . This law states that the rate of effusion of a gas is inversely proportional to the square root of its molecular mass and would imply that the ratio of CO2 to O2 diffusivity would be 0 . 85 . However , Schotsmans et al . [28] have shown that this law does not hold for a complex matrix such as fruit tissue and leads to underprediction of the CO2 diffusivity . This is confirmed by our data ( Table 1 ) , which suggest that the CO2 diffusivity of the skin ( 5 . 06×10−10 m2/s ) is 2 . 7 times higher than that of O2 ( 1 . 86×10−10 m2/s ) . This is probably due to the larger solubility of CO2 in water than that of O2; while O2 would be transported mostly through the apoplast , CO2 would also diffuse through the cytoplasm . More advanced reaction-diffusion models describing O2 and CO2 exchange in fruit have been reported in the literature [7] , [25] , [26] , [35] . Mannapperuma et al . [25] found values of 2 . 67×10−9 m2 s−1 and 3 . 28×10−9 m2 s−1 for the O2 and CO2 diffusivity in ‘Golden Delicious’ apple tissue , which is larger than the values reported here ( Table 1 ) . This might be explained by the larger porosity of apple compared to that of pear . Schotsmans et al . [28] found values for the O2 diffusivity of skin ( 3 . 3×10−10 m2 s−1 ) and cortex tissue ( 4 . 3×10−10 m2 s−1 ) after 3 months of storage , which were comparable those reported here ( Table 1 ) . Further , they reported CO2 diffusivity values of 4 . 3×10−10 m2 s−1 and 1 . 73×10−9 m2 s−1 m2 s−1 for skin and cortex , respectively , which also correspond well with the values found here . Likewise , Lammertyn et al . [26] , [27] found O2 diffusivity values of 2 . 84×10−10 m2 s−1 and 1 . 71×10−9 m2 s−1 , and CO2 diffusivity values of 9 . 11×10−10 m2 s−1 and 1 . 95×10−8 m2 s−1 for skin and cortex respectively . It is not clear why the CO2 diffusivity of cortex found by Lammertyn et al . [26] is about ten times higher than that reported here . Note that in our model a distinction was made between the diffusivity in the axial and radial direction to account for the larger diffusivity in the axial direction due to vascular bundles which run from the stem to the calyx . The higher diffusivity in the axial direction compared to that along the radial direction is probably due to the fact that vascular bundles may be not fully filled with sap during storage of the fruit . It is , therefore , well possible that the vascular bundles along the axis of the pear indeed facilitate gas exchange . Moreover , the orientation of the cells along the vertical axis could be different from that of cells in the radial direction , and further difference in gas exchange properties may be due to enhanced interconnectivity of the gas intercellular space along the vertical axis compared to the radial direction [31] . Finally , while gas exchange properties might be affected by the developmental stage of the fruit through changes in tissue microstructure , it is interesting to note that Schotsmans et al . [28] did not find appreciable changes in gas diffusion properties of apple tissue during a period of seven weeks after harvest . It should be emphasised that , because of the difference in diffusion coefficient , the produced CO2 leaves the fruit at higher rates than O2 is entering the fruit . This causes a pressure gradient inside the fruit . This pressure gradient initiates convective transport . Lammertyn et al . [26] found that the O2 partial pressure was under-predicted by this model and increased the O2 diffusivity parameter 3 times to improve the correspondence between measured and predicted O2 concentration . Such an adjustment was not required in the permeation-diffusion-reaction model presented here . The pressure gradient was alleviated in the model by a flux of N2 towards the center of the fruit . While in the validation experiment at 1°C the correspondence between predicted and measured gas profiles was excellent , there was an increasing deviation for the CO2 profile with increasing temperature . As , in contrast to gas transport properties , the parameters of the respiration kinetics are highly dependent on temperature [33] , [36] , [37] it is likely that this mismatch can be related to the latter . We believe that this is due to the fact that fruit used for validation were different from those used for parameter estimation . In fact , the respiratory activity of pear depends on its maturity which can vary from season to season or batch to batch [16] , [26] . Also , the preparation of disk samples for the respiration measurements might have caused an increase of the respiration rate [38] , [39] due to an ethylene wound response [39] , [40] . However , the available validation data are insufficiently informative to allow for re-estimating the respiration parameters . Novel experiments , possibly also providing data on internal gas concentrations , would be required . Other models for gas exchange in plant organs have been developed . Denison [20] developed such a model for oxygen diffusion and respiration in legume root nodules while Parkhurst and Mott [41] described a reaction-diffusion model for CO2 assimilation in leaves . Aalto and Juurola [21] developed a model for CO2 exchange in leave parenchyma tissue . These models are based on the microscale geometry , and application to large organs such as fruit would require huge computer resources if possible at all . In contrast , the model developed here can be used well to predict gas exchange at the macroscale but does not provide detailed predictions of gas concentration at the microscale . We believe that microscale gas exchange models such as the ones developed by Denison [20] and Parkhurst and Mott [41] can be combined advantageously with macroscale models such as the one developed in this article . In such a multiscale approach , the macroscopic apparent diffusion coefficients can be estimated from in silico experiments using the microscale model . Multiscale modelling is an active area of materials engineering and physics [42] and has not been applied to plant physiology so far . Tissue properties were measured using cylindrical tissue samples . The cutting process caused a film of juice at the cut surface of the samples which may fill up pores and , hence , affect the exchange properties . The cut surface was , therefore , always wiped off with cotton tissue . Further , the cell injury due to cutting leads to local enzymatic oxidation reactions which probably would not affect the apparent respiration rate considerably . However , cutting may possibly also illicit a stress response which might increase respiration . Such effects are difficult to quantify because there is currently no method available to measure in vivo gas exchange properties . However , it may explain some of the mismatches between measured and predicted respiration parameters of intact fruit . Michelis-Menten kinetics are widely used to describe the relationship between the O2 concentration and the O2 consumption rate of whole intact fruit [43] . However , the O2 consumption rate is inhibited at high CO2 concentrations and the production of CO2 results from both oxidative and fermentative processes . As the Michelis-Menten model is not capable of describing such behaviour , it has been extended by various authors [34] , [44] , [45] . Such extended Michelis-Menten models can still be used as a semi-empirical model to describe the respiration characteristics of the whole intact fruit or vegetable . Here we have used such a model described by Equations 1–4 to describe both respiration of whole intact as well as tissue disks . However , the Michaelis-Menten constant Km , O2 of the pear cortex tissue ( 1 . 00±0 . 23 kPa ) was 6 times lower than for the intact pear ( 6 . 2±0 . 9 kPa ) ( Tables 1 and 2 ) . This illustrates that the Km , O2 value measured on the intact pears does not only contain information of the respiration but also about the macroscopic gas diffusion through pear cortex tissue and skin [35] . An even smaller value was also found for pear cell protoplast respiration ( Km , O2 = 3 . 0±0 . 3 µM corresponding to 0 . 18±0 . 03 kPa in the equilibrium gas phase ) by Lammertyn et al . [33] . A similar result was also found for the inhibition of fermentation by CO2: the value for intact pear , Km , f , O2 , was 0 . 69±0 . 17 kPa while it was 0 . 28±0 . 14 kPa for cortex tissue , or more than 2 times less . The high value of Kmn , CO2 ( 66 . 4±21 . 3 and 70 . 7±21 . 6 kPa for cortex tissue and intact pear , respectively ) indicates that the inhibition effect of CO2 on respiration was small . This value is not exceptionally large , similar values were also found by Peppelenbos and Van't Leven [34] for Golden Delicious apple ( 64 . 1±49 . 8 kPa ) , Elstar apple ( 91±126 kPa ) and asparagus ( 45 . 1±6 . 1 kPa ) . Smaller values were found for broccoli ( 11 . 5±2 . 3 kPa ) , mungbean sprouts ( 14 . 2±3 . 1 kPa ) and cut chicory ( 13 . 5±4 . 8 kPa ) . There is no clear reason why there should be such a difference; in fact , relatively little is known about the effect of CO2 on the activity of respiratory enzymes . The respiration quotient of pear cortex tissue ( rq , ox = 0 . 97±0 . 04 ) was higher than that of intact pear ( rq , ox = 0 . 76±0 . 03 ) . We believe that the difference in rq , ox between cortex tissue and intact pear is due to the fact that CO2 has a high solubility in the water phase of fruit tissue ( the CO2 capacity in the tissue αCO2 is equal to 0 . 948 at 20°C ) . As the estimation of rq , ox is essentially based on transient measurements of the gas profiles in the jar , it is well possible that CO2 is still accumulating in the intact pear because of the much larger internal gas exchange resistance compared with that of cortex tissue . Similar observations were made by Lammertyn et al . [26] . A good agreement was found between the Vm , O2 values of intact pear and pear cortex tissue , while the value of Vm , O2 of the skin was 3 . 5 times higher than the maximal respiration rate of the cortex tissue . A large respiration rate of the epidermis was also found by Lammertyn et al . [27] and Schotsmans et al . [28] . This may be due to the high density of the small cells in the epidermal region compared to the larger cells of the cortex region . The respiration of the skin as such might also be higher than that of cortex tissue . The value of Vm , f , CO2 of the cortex tissue was 1 . 6 times higher than that of intact pear . This could be explained by the fact that the high solubility of CO2 in the water phase of fruit tissue leads to underestimation of the CO2 production of the intact pear . However , the value of Vm , f , CO2 for the tissue samples led to an over predicted value of the CO2 concentration in the validation experiment . Using the intact fruit value even resulted in better comparison with the validation set , but was outside the 95% confidence interval of the parameter . The reason for this mismatch is today unclear , but could be related to microscale balances of the different chemical forms of CO2 that are present in the intracellular liquid [46] . To resolve this issue , a microscale model of gas exchange and respiration in tissues that unravels the different mechanisms and species balances is required . The O2 consumption rate of the intact pear was based on the O2 concentration decrease of the air atmosphere in the jar over a certain period of time . As the solubility of O2 in the water phase of fruit cortex tissue is low ( αO2 is equal to 1 . 01×10−1 at 20°C ) , there was less effect on Vm , O2 of intact pear while the high solubility of CO2 in the water phase ( αCO2 is equal to 9 . 49×10−1 at 20°C ) of fruit cortex tissue could have significant affected Vm , f , CO2 and rq , ox of the intact pear . Temperature is the most important factor to control the fruit metabolism during storage . The influence of the temperature kinetic parameters can be described by the activation energy . Both the activation energy for O2 consumption ( Ea , Vm , O2 = 80 . 2±12 . 3 kJ mol−1 ) and fermentative CO2 production ( Ea , Vmf , CO2 = 56 . 7±13 . 3 kJ mol−1 ) of the cortex tissue were close to that of intact pear ( Ea , Vm , O2 = 64 . 6±4 . 7 kJ mol−1 and Ea , Vmf , CO2 = 58 . 5±8 . 9 kJ mol−1 ) described by Lammertyn [35] . Temperature effects on respiration rate are well known , however , attempts to characterise temperature influence on tissue diffusion have not revealed substantial temperature effects [30] . Temperature had a small influence on the diffusion while tissue respiration showed a strong effect by temperature . A high concentration gradient was found at high temperatures . Therefore , storage temperatures should be low enough to have low respiration activity resulting in small gas gradients . Cytochrome c oxidase has been reported as the rate limiting enzyme in the respiration pathway [47] . Solomos obtained a value of 0 . 1 µM for the Km , O2 for isolated cytochrome c oxidase for apple [48] . The calculated O2 concentration expressed in µM in the center of the smallest and largest pear under regular air storage was equal to 111 and 15 µM and , hence , much larger than this Km , O2 value . Consequently , the O2 concentration will not be rate limiting and the respiratory pathway will be active . In contrast , under core breakdown inducing conditions the O2 concentration was equal to 1 . 69×10−2 and 1 . 56×10−3 µM , well below the cytochrome c oxidase Km , O2 value . Under such conditions , and particularly in the large pear , the respiratory pathway would be blocked and fermentation is likely to occur . The latter storage conditions are in fact known to cause the physiological disorder core breakdown in pear , and large fruit are known to be much more susceptible to this disorder than small fruit [12] . These results show that the model developed in this article helps in explaining the occurrence of controlled atmosphere related physiological storage disorders in pear . This is a major step forward in understanding the biophysical processes underlying physiological disorders compared to statistical models such as the one developed by Lammertyn et al . [12] . A permeation-diffusion-reaction model was developed to study gas exchange of intact pear at the macroscale level . The model accounts for both diffusion and pressure driven exchange of these gasses and incorporates anisotropic transport properties . O2 depletion and CO2 production because of respiration were modelled by means of Michaëlis Menten kinetics which were modified to account for O2 and CO2 inhibition effects . As the pear shape cannot be approximated by a generic geometry such as slab , sphere or cylinder , a computer vision system was used to reconstruct the actual geometry of the pear and the model equations were discretised over this geometry . The model was validated successfully under steady and transient conditions at 1°C; there was an increasing deviation for the CO2 profile with increasing temperature , probably due to season or batch effects on the parameters of the respiration kinetics . The model structure is generic: application of the model to other fleshy fruit is straightforward but the model parameters and the fruit geometry need to be measured . Based on an in silico study it was found that considerable gradients of metabolic gases may exist in fruit , hereby invalidating earlier models in which it was assumed that gas transport could be lumped . Higher values of the Michaëlis-Menten parameters of the respiration of intact fruit compared to those of cortex tissue could be attributed to the gas exchange barrier function of fruit tissue . The larger the fruit , the lower and higher the O2 and CO2 partial pressures in the fruit center , respectively , indicating a larger susceptibility to fermentation and storage disorders . Further , the large differences in apparent diffusion coefficient for O2 and CO2 result in an underpressure in the centre of the fruit which causes permeation gas transport . However , diffusion remains the main mechanism of gas exchange . An in silico study revealed that , in contrast to small pears , in large pears and under extreme storage conditions the oxygen concentration can decrease well below the Michaëlis Menten constant for cytochrome c oxidase , the rate limiting enzyme of the respiration pathways . This most probably leads to fermentation and physiological disorders which have been observed under such conditions . For the first time a plausible and quantitative biophysical explanation is given for the well-known role of gas exchange in the development of physiological disorders in fruit such as core breakdown . The model developed in this article is a first step towards a comprehensive model of gas exchange of pear fruit . Further advances require that the internal microstructure of the tissue is investigated to explain differences in gas exchange properties and to quantify the cellular and intercellular pathways for gas exchange . Also , the respiration and fermentation submodels are phenomenological and do not allow to evaluate the effect of internal gas concentrations on cellular metabolic fluxes . Such information would help to explain physiological disorders related to oxidative stresses such as typical browning patterns in pear tissue stored under hypoxic conditions . Mechanistic models incorporating more detailed knowledge of the respiratory and fermentative pathways are currently being developed in our group . Finally , the respiratory metabolism does change dramatically during maturation and ripening of climacteric fruit such as pear in response to ethylene biosynthesis . Hence , the parameters of the respiration and fermentation submodels are likely to change as well and need to be estimated for different development stages .
Pears ( Pyrus communis cv . ‘Conference’ ) were harvested on September , 8th , 2004 , at the pre-climacteric stage at the Fruitteeltcentrum ( Rillaar , Belgium ) , cooled and stored according to commercial protocols for a period of 21 days at −0 . 5°C preceding CA storage ( 2 . 5 kPa O2 , 0 . 7 kPa CO2 at −0 . 5°C ) until they were used for the respiration experiments on tissue discs . A non-competitive inhibition model [34] , [44] , [45] was used to describe consumption of O2 by respiration as formulated by Equation 1: ( 1 ) with Vm , O2 ( mol m−3 s−1 ) the maximum oxygen consumption rate , PO2 ( kPa ) the O2 partial pressure , PCO2 ( kPa ) the CO2 partial pressure , Km , O2 ( kPa ) the Michaelis-Menten constant for O2 consumption , Kmn , CO2 ( kPa ) the Michaelis-Menten constant for non-competitive CO2 inhibition , and RO2 ( mol m−3 s−1 ) the O2 consumption rate of the sample . The equation for production rate of CO2 consists of an oxidative respiration part and a fermentative part [43] . ( 2 ) with Vm , f , CO2 ( mol m−3 s−1 ) the maximum fermentative CO2 production rate , Km , f , O2 ( kPa ) the Michaelis-Menten constant of O2 inhibition on fermentative CO2 production , rq , ox the respiration quotient at high O2 partial pressure , and RCO2 ( mol m−3 s−1 ) the CO2 production rate of the sample . The effect of temperature was described by Arrhenius' law [45] . ( 3 ) ( 4 ) with Vm , O2 , ref ( mol m−3 s−1 ) and Vm , f , CO2 , ref ( mol m−3 s−1 ) the maximal O2 consumption rate and maximal fermentative CO2 production rate at Tref = 293°K , respectively; Ea , VmO2 ( kJ mol−1 ) the activation energies for O2 consumption; Ea , VmfCO2 ( kJ mol−1 ) the activation energies for fermentative CO2 production; T ( K ) temperature; and R ( 8 . 314 J mol−1 K−1 ) the universal gas constant . It was assumed that the other parameters in Equations 1 and 2 do not depend on temperature [45] . Asymptotic confidence intervals were calculated from the asymptotic covariance matrix C of the parameterswith J the Jacobian matrix with respect to the estimated parameters , and s2 the mean squared error . The asymptotic ( 1−α ) % confidence interval on the i-th parameter estimate Pi was calculated aswith t the Student t-distribution , n the number of measurements , p the number of parameters , and Ci , i the i-th diagonal element of C . The tissue structure of the fruit is considered to contain mainly two phases , the intra-cellular liquid phase of the cells and the air-filled intercellular space . Assuming local equilibrium at a certain concentration of the gas component i in the gas phase Ci , g ( mol m−3 ) , the concentration of the compound in the liquid phase of fruit tissue normally follows Henry's law . If the tissue has a porosity ε , the volume-averaged concentration Ci , tissue ( mol m−3 ) of species i is then defined as: ( 5 ) with Hi ( mol m−3 kPa−1 ) Henry's constant of component i ( i is O2 , CO2 or N2 ) , R the universal gas constant ( 8 . 314 J mol−1 K−1 ) and T ( K ) the temperature . From this definition , we derive the following expression for the gas capacity αi of the component i of the tissue ( 6 ) Henry's constant was reported by Lide [49] . The porosity of Conference pear was determined by Schotsmans [50] from the density of intact fruit and juice , and was equal to 0 . 07 . A permeation-diffusion-reaction model was constructed describing the diffusion and permeation processes in pear tissue for the three major atmospheric gases O2 , CO2 and N2 . Equations for transport of O2 , CO2 and N2 were established by Ho et al . [31] , ( 7 ) At the boundary: ( 8 ) with Di ( m2 s−1 ) the apparent diffusion coefficient , u ( m s−1 ) the apparent velocity vector , Ri ( mol m−3 s−1 ) the production term of the gas component i related to O2 consumption or CO2 production ( Equations 1–4 ) , ∇ ( m−1 ) the gradient operator , and t ( s ) the time . The index ∞ refers to the gas concentration of the ambient atmosphere . The first term in Equation 7 represents the accumulation of gas i , the second term permeation transport driven by an overall pressure gradient , the third term molecular diffusion due to a partial pressure gradient , and the last term consumption or production of gas i because of respiration or fermentation . If , for example , oxygen is consumed in the center of the fruit , it creates a local partial pressure gradient which drives molecular diffusion . However , if the rates of transport of different gasses are different , overall pressure gradients may build up and cause permeation transport . Nguyen et al . [51] observed based on nuclear magnetic resonance imaging that the water concentration in pear fruit is almost uniform; gradients were restricted to a thin layer just beneath the surface . As a consequence , the water vapour pressure is also almost uniform within the fruit so that there was no need to model water vapour transport in the food . It is important to note that the apparent diffusion coefficients are not physical properties as such but rather phenomenological parameters which depend on both the actual gas diffusion properties and fruit microstructure . Also , we have assumed that the size of the pores and channels connecting the pores are large compared to the mean free path of molecular motions which is typically 0 . 07 µm for N2 at 20°C and 105 Pa [52] . As the structure of the intercellular space is essentially three-dimensional , appropriate visualisation techniques such as microfocus computer tomography are required to test this hypothesis [53] . Permeation through the barrier of tissue by the pressure gradient was described by Darcy's law [54]: ( 9 ) with K ( m2 ) the permeation coefficient; P ( Pa ) the pressure and µ ( Pa . s ) the viscosity of the gas . The relation between gas concentration and pressure was assumed to follow the ideal gas law ( P = CRT ) . Respiration rate measurements on pear tissue were carried out at 20°C at 0 , 0 . 5 , 1 , 3 , 5 , 10 , 30 kPa O2 combined with 0 kPa of CO2 as described by Schotsmans et al . [28] . To study the inhibitory effect of CO2 , respiration measurements were carried out at 0 , 5 , 10 and 30 kPa O2 in combination with 10 kPa CO2 . For quantifying the effect of temperature on the respiration rate , measurements were carried out at 5 , 10 and 20°C at 0 and 30 kPa O2 in combination with 0 kPa CO2 . The samples were prepared in the same manner as the samples for the diffusion measurement as described by Ho et al . [30] , [31] . Samples of cortex tissue were first cut with a professional slice cutter ( EH 158-L , Graef , Germany ) . Subsequently , small cylinders with a diameter of 24 mm were cut with a cork borer . The thickness of the cortex tissue sample ranged from 1 . 5 to 2 mm . Skin samples ( including both the epidermis and the hypodermis of the fruit ) were cut and removed the flesh until a thickness of around 1mm was obtained . Samples of 55–65 pieces ( ∼50–60 g ) were placed on metal meshes in 1 . 7 L glass jars . Three jars were connected in series and flushed with each gas mixture during 30 minutes . The jars were then closed and the initial gas mixture ( O2 , CO2 and N2 ) was measured with a gas chromatograph ( Chrompack CP 2002 , The Netherlands ) . Percentages of O2 , CO2 and N2 were converted to partial pressures using the total pressure in the jar that was measured with a pressure sensor ( DPI 142 , GE Druck , Germany ) . The headspaces were analysed again after 17 h . The difference in gas partial pressure was converted to molar concentrations according to the ideal gas law , and from this the O2 consumption and CO2 production rates were calculated and expressed in mol per volume of sample ( m3 fresh volume of sample ) and per unit time ( s ) . All parameters of the respiration models ( Equations 1–4 were estimated simultaneously by fitting Equations 1–4 to the experimental data using a non-linear least squares regression in MATLAB [The Mathworks] ) . The data on O2 consumption and CO2 production rates were pooled , and the same weight was attributed to both gases . Permeation properties of pear epidermis and cortex tissue were determined by measuring the total pressure difference between two chambers separated by a tissue sample [31] . Both chambers were flushed with humidified N2 gas at 10 L/h . The pressure was adjusted so as to obtain a 6 kPa pressure difference between the measurement and flushing chamber . The inlet and outlet valves of one chamber were closed , and the decrease in pressure of this chamber was monitored for at least 4 h . The permeability was then estimated from this pressure drop using the procedure described by Ho et al . [31] . For the measurement of the diffusion properties , different gas concentrations were applied in both chambers [30] and the change of O2 and CO2 partial pressure in time was measured by means of fluorescent optical probes ( Foxy-Resp and FCO2-R , Ocean Optics , Duiven , The Netherlands ) . The O2 and CO2 gradients were chosen in such a way that the resulting O2 and CO2 fluxes through the sample would compensate each other avoiding a total pressure difference between the two chambers . Pressure sensors ( PMP 4070 , GE Druck , Germany ) monitored the pressure changes in each chamber during the measurements . The gas diffusion properties were then estimated from the gas concentration profiles as described by Ho et al . [30] . The N2 diffusivity was determined indirectly from the total pressure and the O2 partial gas pressure of the binary O2-N2 gas mixture [31] . The values used in this article were taken from Ho et al . [30] . Since the geometry of pear can be considered as axi-symmetric , there are variations of gas concentrations in the radial direction ( r ) and vertical axis ( z ) only and not in the angular direction . Therefore , the problem can be solved in two dimensions in the r-z plane instead of using a full three-dimensional model . This can save considerable memory and computation time resources . The two-dimensional shape of the fruit was constructed with a machine vision system for shape description [55] . An intact pear was put on a rotation table with a computer controlled stepper motor ( Apollo , C-630 . 32 , Physik Instrumentc GmbH , German ) and pictures were taken with a CCD color digital video camera ( DFW-VL500 , Sony , Japan ) along the fruit equator . The geometrical model of the pear was reconstructed using image processing software written in MATLAB . The image was segmented in object and background using an automatic threshold on the saturation value of the color information , and the contour of the object was extracted from the image . Subsequently , a cubic spline ( smooth polygonal approximation ) was fitted on the contour . In every node the normal vector to the contour was calculated , and the skin was defined as to have a thickness of 1 mm along this normal vector . The epidermis tissue ( skin ) was created by shrinking the contour along this normal vector until a skin thickness of 1 mm was obtained in every node . Note that skin here includes both the epidermis and the hypodermis–a relatively tightly packed diffuse layer of cells located in between the epidermis and cortex tissue to mimic the skin sample of gas exchange and respiration measurement . The same skin thickness was assumed for estimating the gas exchange properties [30] , [31] . The geometrical description based on contour information was transferred to the Femlab version 3 . 1 . finite element program ( Comsol AB , Stockholm ) package , where a finite element mesh was generated on the pear geometry . An axisymmetric geometry model was created for the pear in the jar ( Figure 5 ) . In total , 5441 quadratic finite elements with triangular shape were used . Note that Conference pears typically do not have an empty core , there was no need to incorporate a hole in the finite element model . To study the effect of pear shape on the local respiratory gas inside the fruit , four geometries were established representing pears of different equatorial radius ( 2 . 6; 3 . 2; 3 . 4 and 3 . 7 cm - Figure 5 ) . For gas exchange in intact fruit , Equations 1–9 were solved using the finite element method in Femlab version 3 . 1 . ( Comsol AB , Stockholm ) . Anisotropic gas exchange properties were applied in the radial ( r ) and vertical ( z ) direction . Since the model for consumption of O2 inside the fruit ( Equation 1 ) does not exclude negative concentrations , numerical problems may occur when the oxygen concentration approaches zero , resulting in non-physical negative results . Therefore , two alternative approaches were introduced to solve this problem . The first method was based on modifying the respiration term to ensure that the rate of O2 consumption became zero when the O2 concentration approached zero . Another method was based on the exponential transformation of the O2 variable in the model equations in such a way that the solution is guaranteed to be positive ( see Text S1 ) . A good agreement was found for both two solutions ( not shown ) .
|
Respiration plays an important role in the overall metabolism of plants , and certainly is related to gas exchange of plants with the environment . In roots and bulky storage organs such as fruit and tubers , where the length of the diffusion path may be considerable , anoxic conditions may even occur . This is of particular importance in fruit , which are often stored under low-oxygen conditions to extend their storage life . In this manuscript , we have developed a new mathematical model to describe the gas transport and respiration kinetics in intact pear fruit . Michaelis-Menten kinetics was used to describe the respiration behavior of tissues . Diffusion was the main driving force for gas exchange . Differences in diffusion rates of the different gasses led to total pressure gradients that caused convective exchange as described by Darcy's law . The model incorporates the actual shape of the fruit and was solved using fluid dynamics software . It is a first step towards a multiscale model that addresses all spatial scales relevant to gas transport . These findings can be used to evaluate the effect of environmental stresses on fruit via in silico experiments and may lead to commercial solutions for long-term storage of fruit under controlled atmospheres .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"biology/plant-environment",
"interactions",
"plant",
"biology/plant",
"biochemistry",
"and",
"physiology"
] |
2008
|
A Continuum Model for Metabolic Gas Exchange in Pear Fruit
|
Many tumors are characterized by genetic instability , producing an assortment of genetic variants of tumor cells called subclones . These tumors and their surrounding environments form complex multi-cellular ecosystems , where subclones compete for resources and cooperate to perform multiple tasks , including cancer invasion . Our recent empirical studies revealed existence of such distinct phenotypes of cancer cells , leaders and followers , in lung cancer . These two cellular subclones exchange a complex array of extracellular signals demonstrating a symbiotic relationship at the cellular level . Here , we develop a computational model of the microenvironment of the lung cancer ecosystem to explore how the interactions between subclones can advance or inhibit invasion . We found that , due to the complexity of the ecosystem , invasion may have very different dynamics characterized by the different levels of aggressiveness . By altering the signaling environment , we could alter the ecological relationship between the cell types and the overall ecosystem development . Competition between leader and follower cell populations ( defined by the limited amount of resources ) , positive feedback within the leader cell population ( controlled by the focal adhesion kinase and fibronectin signaling ) , and impact of the follower cells to the leaders ( represented by yet undetermined proliferation signal ) all had major effects on the outcome of the collective dynamics . Specifically , our analysis revealed a class of tumors ( defined by the strengths of fibronectin signaling and competition ) that are particularly sensitive to manipulations of the signaling environment . These tumors can undergo irreversible changes to the tumor ecosystem that outlast the manipulations of feedbacks and have a profound impact on invasive potential . Our study predicts a complex division of labor between cancer cell subclones and suggests new treatment strategies targeting signaling within the tumor ecosystem .
Lung cancer is the second most prevalent type of cancer causing over 150 , 000 deaths per year in the United States [1] . Insufficient progress has been made in achieving efficacious treatments . One of the main barriers in developing new treatment strategies is the vast diversity between and within cancers; heterogeneity exists between patients with the same tumor type , between tumor loci within a patient ( i . e . metastases and primary tumor ) , and within the primary tumor itself [2 , 3] . Cancer is distinguished by loss of normal control over cell processes leading to genetic instability and unregulated growth . Genetic instability creates array of different clonal populations with different cell fitnesses , renewal and invasion potential [4] . Competition between different cancerous subclones and between cancerous and normal cell types sets the stage for classical ecological dynamics in the tumor microenvironment . The outcome of this process determines success of the tumor progression and its understanding may help discover novel treatment strategies [5 , 6] . Invasion of surrounding tissue , either locally or distally via metastasis , is a hallmark of cancer [7] . Extensive research has detailed that invasion is mediated by interactions between tumor and extracellular matrix [8 , 9] and cancer-associated fibroblasts [10] , but there is a lack of focus on the cooperative interactions between different cancer cell types , either phenotypically or genotypically distinct . Indeed , in mouse models of lung cancer , collective invasion of cancer cells was shown to correspond markedly more successful metastasis [3 , 11–13] , confirming the critical role of collective invasion in driving cancer progression . We recently developed a novel image-guided genomics approach termed SaGA that allowed us to identify at least two distinct phenotypic cell types in lung cancer invasion packs: highly migratory leader cells and highly proliferative follower cells [14] . Genomic and molecular interrogation of purified leader and follower cultures revealed differential gene expression prompting distinguishing phenotypes . Specifically , leader cells utilized focal adhesion kinase signaling to stimulate fibronectin remodeling and invasion . Leader cells also overexpressed many components of the vascular endothelial growth factor ( VEGF ) pathway facilitating recruitment of follower cells but not the leader cell motility itself [14] . However , leader cells proliferated approximately 70% slower than follower cells due to a variety of mitotic and doubling rate deficiencies . These deficiencies could be corrected by addition of cell media extracted from the follower only cell cultures , leading to conclusion that follower cells produce an unknown extracellular factor responsible for correcting mitotic deficiencies in the leader cells . In sum , leader cells provide an escape mechanism for followers , while follower cells ( and follower cell media only ) help leaders with increased growth . Together , these data support a service-resource mutualism during collective invasion , where at least two phenotypically distinct cell types cooperate to promote their escape . In this new study , we developed population-level computational model to explore impact of the complex interactions between leaders and followers cell types on cancer progression . The model implemented effects of critical signaling factors controlling the communication between cell types and the interaction between cells and environment . We derived analytic boundaries dividing parameter space , representing the major signaling feedbacks , by the critical changes to invasion dynamics . Our study predicts the critical role of specific signaling pathways involved in the symbiotic interactions between cancer subclones for the overall success of cancer progression .
Previous 3D spheroid experiments show that invasion occurs on a much faster time scale than reproduction [14] . By assuming that factors ( V , P , N ) and domains ( ΩL , ΩF ) change much faster than cell counts ( equivalently γV , γP , γN , γOL , γOF ≫ rL , rF ) , one can reduce these equations to a set of two equations ( L , F ) , where variables in Eqs ( 3 ) – ( 7 ) are at their equilibria VSS=βVγVL;PSS=βPγPF;NSS=βNγNL;ΩLSS=βOLγOLN;ΩFSS=βOFγOFV; ( 8 ) Using this reduction drastically decreased the complexity of the system . This allowed a two-dimensional phase-space representation , facilitating the presentation of the results , and analytical derivation of many of the bifurcation conditions in the system . To perform this reduction , we first defined the feedbacks based on the reduced system . The feedback that determines the leaders impact on their own domain expansion was denoted by sL=βNβOLγNγOL , for the strength of the leader only feedback . The feedback that determines the leaders impact on follower cell growth was denoted by sLF=βVβOFγVγOF , for the strength of the leader to follower feedback . The feedback that determines the followers impact on leader cell growth was denoted by sFL=βPγPδ , for the strength of the follower to leader feedback . Second , using these assumptions , we re-wrote the leader-follower system as L′L=rL[1− ( L/ΩLSS ( L ) ) +c ( F/ΩFSS ( L ) ) KL ( F ) ] ( 9 ) F′F=rL[1− ( F/ΩFSS ( L ) ) +c ( L/ΩLSS ( L ) ) KF] ( 10 ) where ΩLSS ( L ) =sLL+ΩL0;ΩFSS ( L ) =sLFL+ΩF0;KL ( F ) =KL0+ ( KF−KL0 ) sFLF1+sFLF . Using this reduction we can derive several critical points in invasion . The reduced system ( 9 ) , ( 10 ) may have five equilibrium points: extinction of leaders ( O1: L = 0 , F>0 ) , followers ( O2: L>0 , F = 0 ) , both ( O3: L = 0 , F = 0 ) , and two coexistence points ( O4 , O5 ) ( where both leaders and followers populations are non-zero: L>0 , F>0; O4 is always stable , wheras O5 is unstable ) . Changes in the feedback strengths cause fundamental shifts in dynamics . In the following we used parameter values ΩL = 1 , ΩF = 1 . To match experimental observations that leader cells grow slower and less effeciently , we set rL = 0 . 3 and KL0 = 0 . 3 while rF = 1 and KF = 1 . The strengths of the various feedbacks , sL , sLF , and sFL are varied systematically below . We have summarized the parameters in Table 1 . To determine the critical points in the leader-follower system , we calculated the Jacobian of the reduced system evaluated for the leader extinction equilibrium ( O1: L = 0 , F = FLE = ΩF ∙ KF ) . Here KLSS=KL0+ ( KF−KL0 ) sFL⋅FLE1+sFL⋅FLE , the value of KL when F = FLE . The Jacobian has eigenvalues λ=[rL ( 1−cKFKLSS ) , −rF] ( 12 ) For c<KLSSKF , O1 is unstable and O4 ( steady state where both L>0 and F>0 ) is stable . At c=KLSSKF these two equilibria coincide , and for c>KLSSKF equilibrium O4 moves to the left of the L = 0 axis and becomes unstable while O1 gains stability . Thus , extinction of leaders ( O1 ) is stable as long as c>KLSSKF , which determines an upper bound on competition where leader and followers can coexist and a bifurcation we call the transcritical bifurcation at zero . The system undergoes a saddle node bifurcation when two coexistence equilibria ( O4 and O5 ) , representing non-zero populations of both leaders and followers , coincide and disapper . Beyond this bifurcation point the leader/follower populations undergo unbounded growth . This bifurcation was determined numerically using MatCont [18] . We found that this bifurcation point depends critically on both the leader feedback strength , sL , and on the competition strength , c . One of these coexistence points is effected by the transcritical bifurcation , below . When the leader feedback strength is sufficiently high relative to competition , leaders and followers may undergo unbounded growth from the initial conditions belonging to the certain regions of the phase space . We describe this scenario as an attractor basin in the phase space for the stable infinity attractor . However , if sL is reduced ( or c is increased ) beyond a certain threshold , infinity becomes unstable . This corresponds precisely with the loss of an unstable coexistence equilibrium with non-zero values of both leaders and followers ( O5 ) . Leaders and followers that are coexisting must satisfy LΩL+cFΩF=KL ( F ) ( 13 ) and FΩF+cLΩL=KF or equivalently , FΩF=KF−cLΩL . ( 14 ) In the case that follower populations are large relative to δ , KL ( F ) → KF , we substituted ( 13 ) into ( 14 ) to find L=KFΩL0 ( 1+c ) ( 1−KFsL1+c ) ( 15 ) which has a discontinuity at c=KFsL−1 ( 16 ) defining the loss of one of the coexistence equilibrium points ( O5 ) when it moves to infinity . We describe this as the transcritical bifurcation at infinity as the stability of infinity changes at this point .
Leader and follower cell types in non-small cell lung cancer spheroids were previously isolated using a fluorescence technique termed SaGA [14] ( Fig 1A ) . We found that leaders and followers are genotypically and phenotypically distinct populations of cancer cells that exchange a variety of signaling molecules to coordinate complex behavior during invasion . In this new work , we focus on four main channels of communication ( see Fig 1B ) . Through the activation of focal adhesion kinase ( FAK ) , leader cells secrete fibronectin in an autocrine manner . This leads to ECM restructuring and expansion of leader cell domain , ΩL , ( see Methods ) which ultimately increases the leader cell count . The strength of this positive feedback is characterized in our model by sL ( strength of Leader only feedback ) . Leader cells also secrete VEGF . In the leader-follower ecosystem this promotes follower cells to track expanding leader cells , increases follower domain size ( ΩF ) , and ultimately , follower cell count . In our model , the strength of this feedback is given by sLF ( strength of Leader to Follower feedback ) . Follower cells secrete an undetermined proliferation signal , as evidenced by the observation that follower-only cell media increases leader cell growth rate [14] . The strength of this feedback is given by sFL ( strength of Follower to Leader feedback ) in the model . Finally , both cell types compete for the same resources . This has an effect of limiting the capacity of the each cell type through competition , modeled here by the feedback c [16 , 17] . These feedback mechanisms were incorporated into a modified Lotka-Volterra type competition-cooperation model . We chose a Lotka-Volterra model to focus on the ecological aspects of competition in the cancer ecosystem . Here , the leader cells could grow to a total capacity KL , which is an increasing function of the proliferation signal secreted by the follower cells . This capacity was reached when a combination of leader and follower cell densities ( cell counts divided by domains ) exceeds KL ( see Methods ) . Increases in the domain size of each type ( by Fibronectin secretion in the leader case and VEGF in the follower case ) limited the overall density of that cell type and mitigated its impact on the overall capacity of the system . Increasing competition , for example by limiting resources , increased the impact of either cell type on the conjugate capacity type ( e . g . how leader density , L/ΩL , impacts follower capacity KF ) . This system of the feedbacks between the leader and follower cells describes a complex dynamical ecosystem . The impact these feedbacks may have on cancer growth or invasion is unclear . Leader and follower cells are engaged in competition for resources but can also be engaged in cooperation and play supportive roles . For example , invasive leader cells provide new territory for the follower cell population and are supported by proliferative follower cells . In the following , we analyzed the model to find critical turning points for the ecosystem dynamics . We found that multiple feedbacks between the leader and follower cell populations could produce a wide variety of complex dynamics . When competition strength , c , was high and the strength of the leader only feedback , sL , was moderate , population dynamic was bounded and resulted in a stable cell count for both leader and follower cell populations , with the former decaying to zero , as well as a stable domain size ( Fig 2A ) . In contrast , when feedback was large and competition was moderate , population dynamics revealed an unbounded growth ( Fig 2B ) . Intermediate values of both c and sL led to dynamic regimes that depended on the initial cell count: ecosystems with large initial cell count underwent unbounded growth , while small ecosystems attained a stable size ( Fig 2C ) . Many of the predictions of our study are based on analysis of a reduced model system we assumed that extra-cellular factors , such as VEGF and fibronectin , change much faster than leader and follower cell counts . We found that dynamics of leaders and followers were consistent with the full system across many orders of magnitude of the ratio of these two rates ( Fig 2D ) . These types of dynamics are in a qualitative agreement with experimental studies which revealed ( a ) rapid expansion of intact leader-follower ecosystem and ( b ) that blocking specific feedback mechanisms in vitro can reduce or block cell population growth . Specifically , blockade of fibronectin signaling or blockade of VEGF signaling led to significantly reduced invasion [14] . This array of behaviors can be explained by the critical shifts in the cell population dynamics due to the changes in the feedbacks strength . We found that depending on the level of competition , c , and the strength of invasiveness of leaders , sL , the leader-follower ecosystem can operate in one of five different regimes , as described below ( Fig 3 ) . During multimodal dynamics ( e . g . , Fig 3E ) , leader and follower cell populations can undergo explosive growth or achieve a stable count depending on the initial size of the ecosystem . We examined the impact of limiting the invasive leader feedback in scenarios of this type ( Fig 4 ) . Even when the ecosystem was initially sufficiently large to support unbounded growth , after reducing invasive leader feedback sL ( Fig 4A ) , the ecosystem was forced into the non-invasive dynamics type and the total bulk of the cell population reduced reaching a steady-state ( Fig 4E ) . Importantly , the leader and follower cell populations remained stable and bounded after restoring invasive leader feedback to its original strength ( Fig 4E , right side ) . From the point of view of the dynamical systems analysis , reducing leader feedback changed the phase space , so the only stable attractor was non-zero equilibrium ( O4 ) ( Fig 4C ) . In this regime , unlimited growth was abandoned and the system converged to the equilibrium state ( O4 ) corresponding to the bounded size of both cell populations . This equilibrium remained stable even after the feedback was restored to its original level ( Fig 4D ) . Our model predictions ( Fig 5A ) are consistent with in vitro data ( Fig 5B ) . Using siRNA blocking we previously showed that expression of fibronectin ( which is characterized by the strength of leader only feedback , sL , in the model ) led to the low invasion potential and a stable cell population size [14] . We next tested effect of increasing competition between leader and follower cell populations on the ecosystem dynamics ( Fig 6 ) . Leader cells excrete extracellular factors that induce the death of the followers and leaders alike [14] , which supports competition . Here , we again started from aggressive unbounded type of dynamics and then increased competition strength ( Fig 6A ) . This caused change of the ecosystem dynamics . Both cell populations reduced the size , with leader cell population going to extinction state ( Fig 6E ) . However , upon restoring competition to the original level , leader and follower cells reemerge and grow unboundedly again . The last can be avoided if no leader cells remain ( complete extinction ) . Again , this dynamic can be easily understood using bifurcation analysis . Increasing competition strength made leader extinction equilibrium state O1 stable ( Fig 6C ) . However , when competition was restored to its original level , O1 became unstable again and leader and follower cells returned to escape dynamics ( Fig 6D ) . Importantly , in the extreme case of very small cell populations , cells undergo discrete and stochastic dynamics and complete extinction of a small population of leaders is possible in a finite time , leading to irreversible changes due to competition increase ( similar dynamics was described in our previous study [20] ) . Changing the strength of the feedbacks that determine the interaction between leaders and followers ( sLF and sFL ) could also impact the dynamics . Leader cells secrete VEGF ( denoted here by sLF ) that helps follower cells to expand their territory and follower cells secrete a proliferation signal ( denoted here by sFL ) that allows leaders to increase their proliferative capacity . These two feedbacks have distinct impacts on the overall ecosystem dynamics . Perturbations to sLF ( changing the impact that leaders have on followers ) changed the system dynamics ( assuming that the cell count was small enough at the time of the intervention ) from unlimited growth to the bounded type . The size of both leader and follower cell populations decreased reaching non-zero steady-state ( Fig 7E ) . This regime persisted as long as the feedback from the leaders to followers remained low . However , increasing sLF to its original level restored the system dynamics with unlimited cell population growth ( Fig 7E , right side ) . Using bifurcation analysis , we found that reducing impact that leaders have on followers shifted the location of the saddle node bifurcation boundary that separated state with unlimited growth only dynamics and a state with coexistence of the unlimited growth and a stable equilibrium attractor ( O4 ) regimes ( Fig 7A ) . Effectively , decreasing sLF increased the threshold level of the invasive leader feedback ( sL ) needed to cause unbounded growth . Thus , reducing sLF made the system to converge to the stable equilibrium state O4 corresponding to the bounded size of both cell populations ( Fig 7C ) . However , increasing sLF to its original level changed the phase space again , so infinity became the only stable attractor ( Fig 7D ) and unlimited growth dynamics resumed . Our model predictions ( Fig 5C ) are consistent with in vitro data ( Fig 5D ) . Using siRNA to block the VEGF receptor VEGFR2 ( siKDR in Fig 5D ) , we previously showed that blocking the leader to follower feedback led to the limited invasion potential and stable cell population size ( Fig 5D ) [14] . Finally , we tested the role of the follower to leader feedback ( sFL ) and found that perturbations to sFL have a significant impact on the system dynamics . In contrast to sLF , changes to the sFL changed both the location of the saddle node bifurcation boundary and the transcritical bifurcation boundary of the leader extinction ( Fig 8A ) . Therefore , decreasing sFL both increased the threshold on the leader invasion strength ( sL ) needed to cause unbounded population growth and decreased the threshold of the competition strength ( c ) needed to induce leader population extinction . We have exploited this to show that decreasing sFL can cause irreversible change in the cell population bulk . Again , starting with unlimited growth dynamics ( Fig 8B ) , decreasing follower to leader feedback , sLF , reversed the dynamics and both leader and follower cell population reduced in size converging to the steady-state ( Fig 8E ) . This regime with bounded ecosystem size persisted after the feedback was restored ( Fig 8E , right side ) . Using dynamical systems analysis , we found that reducing follower to leader feedback ( sFL ) triggered the system convergence to the stable attractor ( O1 ) representing the leader extinction state ( Fig 8C ) . When the feedback was restored , O1 becomes unstable but the ecosystem fell to the attraction basin of the stable equilibrium O4 and avoided regime of unlimited growth ( Fig 8D ) . In a more general case , the outcome depended on the balance between the leader to follower , sFL , and follower to leader , sLF , feedbacks , with higher sLF requiring more significant sFL decrease to avoid unbounded growth ( Fig 8F ) . A complex balance of the feedbacks within the cancer cell ecosystem allows for some alterations of the feedback parameters to have significant impacts on the ecosystem dynamics . We summarized these different possibilities in Table 2 from the perspective of achieving the goal to reduce cell population bulk . Hence , manipulating sL , sLF , sFL should be interpreted as decreasing these feedbacks , whereas manipulating c should be interpreted as increasing c . We also examined the possibility of non-targeted cell death , such as might occur during non-specific chemotherapy ( implemented via a non-targeted “enforced” reduction of the cell population ) . Manipulations were either irreversible , so the system dynamics remained altered upon cessation of the perturbation ( e . g . irreversible leader extinction or irreversible stabilization of the cell count ) , or caused only temporal and reversible reduction of the cell bulk . In some cases , such as leader extinction with escape and multimodal dynamics ( see Fig 3 ) , the size of the initial cell bulk dictated possible outcomes of the feedback perturbations . The outcomes described in Table 2 represent the best-case scenario . Thus , perturbations were started from an appropriate initial state and maintained long enough to achieve the desired effect . This analysis revealed that certain parameter regimes are more sensitive to the perturbations than others . Specifically , in the leader extinction with escape regime ( area ( 2 ) in Fig 3A ) and the multimodal dynamics regime ( area ( 4 ) in Fig 3A ) perturbations could have irreversible impacts on the ecosystem . In these cases , any perturbation ( death , reduction in sL , sLF , sFL , or increase in c ) can potentially force the system to cross the critical boundary ( separatrix ) and transition from explosive growth to a steady-state dynamic . These regimes give a unique opportunity to impact the invasiveness of the ecosystem . Also , certain perturbations could force the ecosystem into a state where leader extinction ( O1 ) is stable . This occurs when applying sufficient increases in the competition pressure , c , or decreases in the support from followers to leaders , sLF . In these cases , it is possible for the discrete and stochastic nature of the cell population dynamics to define the ecosystem fate . Thus , a sufficiently long perturbation could irreversibly eradicate a sufficiently small discrete number of leader cells [20] . Leader and follower cells may have distinct phenotypes because of underlying genetic or epigenetic differences . For an example of the latter , during angiogenesis , stimulation of endothelial cells by VEGF creates the epigenetic emergence of tip and stalk cell phenotypes with distinct roles in new vessel formation [21] . It remains an open question as to which is the case with leader and follower cells in lung cancer . We have shown that: a ) leader cells are a phenotypically distinct subpopulation of lung cancer cells; b ) leader and follower cells show distinct genetic expression profiles [14] . Observations of leader only populations over multiple months show that the leader cell phenotype is stable over many generations , maintains invasive morphology , and does not return to the follower phenotype . Similar observations of follower only populations do show an emergence of leader cell phenotype suggesting that follower cells can convert to the leader phenotype . This would suggest that the emergence of leaders from followers is due to epigenetic plasticity and additional unpublished data from the Marcus lab support this . In accordance with the possibility that follower cells can convert to the leader phenotype , we have completed simulations to show our main result—the relative strengths of invasiveness and competition determine the dynamic regime of the leader follower system—remains true in this case . We found that when follower cells can convert to leaders , leader extinction is no longer possible . However , in agreement with previous results we observed that: i ) high competition and low invasiveness led to only tumors of fixed size; ii ) low competition and high invasiveness led to tumors growing unboundedly; iii ) moderate competition and invasiveness led to scenarios where the outcome of tumor growth depended on initial conditions ( Fig 9 ) .
Heterogeneity of tumors , at the genetic , epigenetic , and phenotypic levels , is one of the main obstacles to developing new effective treatment strategies . Tumor cells rapidly evolve forming highly efficient symbiotic systems with well-defined labor division targeted to augment tumor survival and expansion . In lung cancer collective invasion packs observed in vitro , two distinct populations of cancer cells—highly migratory leader cells and highly proliferative follower cells–have been recently identified [14] . In this new study , we used computational models to explore collective dynamics of the leader-follower ecosystem and to exploit approaches that can effectively disrupt it . We found that competition between two populations ( defined by the limited amount of resources ) , the positive feedback within the leader cell population ( controlled by the focal adhesion kinase and fibronectin signaling ) and impact of the follower cells to the leaders ( represented by yet undetermined proliferation signal ) all had major effects on the outcome of the collective dynamics . While increase of the positive feedback within the leader cell population would ultimately lead to the system state with unbounded growth , manipulating follower to leader feedback or increasing competition between leader and follower cell populations was able to reverse this dynamic and to form a stable configuration of the leader and follower cell populations . Our model highlights the importance of fibronectin remodeling in invasion . Fibronectin is the major ligand of the focal adhesion kinase ( FAK ) pathway . Our previous empirical work showed that FAK signaling was a key distinguishing feature between leader and follower cells and critical for invasive leader behavior [14] . While we do not model FAK directly , our model predicts that fibronectin remodeling is the main driver of invasion by leader cells and disruptions in the FAK driven feedback loop will cause critical changes in the leader-follower population dynamics . Indeed , FAK is a well-known regulator of the tumor micro-environment: promoting cell motility and invasion [22] . FAK expression is upregulated in ovarian [23] and breast cancer [24] tumors with expression levels correlating with survival [25 , 26] . Many FAK inhibitors , such as defactinib , are currently in clinical trials with promising results [22 , 27 , 27–31] . A key advantage of FAK inhibitors is that they impact both the tumor itself and the surrounding stroma where tumor associated fibroblasts also utilize FAK signaling to promote tumor invasiveness [32 , 33] . While commonly associated with angiogenesis in healthy and cancerous tissue , our previous work showed that VEGF mediates communication between leader and follower cells [14] . There is a long history of targeting VEGF to limit tumor invasiveness [34 , 35] . While great success has been seen in preclinical models [36 , 37] , only moderate success was seen in clinical trials with anti-VEGF drugs such as bevacizumab [38 , 39] . This is largely due to cancers developing resistance to specific VEGF-therapeutics . In our model , VEGF stimulated followers to shadow leaders and expand their domain . However , we found that inhibition of VEGF had little impact on the ecosystem dynamics relative to the perturbations of the other axes ( such as FAK or competition for resources ) . Competition for resources is one of the principal forces that structures any ecosystem , including tumor ecosystems [6 , 40] . Our modeling work predicts that competition was a critical component in the leader-follower ecosystem . We found that when the strength of competition exceeded a critical threshold , leaders ( the weaker competitor ) were driven to extinction . Further , enhancements of the competition in the model changed the fundamental cell population dynamics . In some cases this meant stopping unbounded growth and promoting the extinction of the leader cells . Our previous in vitro work demonstrated that leaders may inhibit the growth of followers through an unknown secreted factor in cell media [14] . While still in the early stages , exploiting this inhibition may also provide similar benefits to those shown here as increases in competition . Our previous study also revealed a currently unknown extracellular factor secreted by followers that corrects mitotic deficiencies and enhances leader proliferation [14] . Our modeling highlights this factor as having critical impact on the ecosystem dynamics . We found that blockade of this proliferation factor , modeled here by the strength of the follower to leader feedback , can cause critical shifts in the population dynamics . More work needs to be done to identify and understand the mechanism of this action , but preliminary results suggests that this may be a potential novel treatment axis that specifically targets the mutualistic interaction between leaders and followers . Ecological forces shape the exchange of biomaterial between different biotic and abiotic environmental agents . These forces determine capacity of the ecosystem for different species ( subclones ) and the environment ultimately sets the fitness of each of the competitors . Classic ecological theory dictates that an abundance of many similar species ( such as similar subclonal populations ) will lead to a high competition for resources [41 , 42] . This competition can force the exclusion of inferior competitors and ultimately may reduce heterogeneity of the system . However , when symbiotic and mutualistic interactions occur , otherwise competitive species support each other and increase the capacity of the ecosystem [43 , 44] . Symbiosis between different subclonal populations may be particularly important during critical times when the tumor survival is in peril ( such as hypoxia , metastasis or therapy ) . One critical moment in tumor progression occurs when highly proliferative tumor cells saturate the resource potential of their current environment . In order to obtain more resources , tumors need to invade new territory . Collective invasion is a spatial phenomenon , where leader cells form the invasive periphery trailed by follower cells to invade new territory . We used a simplified non-spatial model here to make possible a quantitative bifurcation analysis that allowed us to calculate critical shifts in cell dynamics in response to the shifts in the biophysical model parameters . We focused our efforts on the balance of symbiotic and competitive effects in this complex tumor ecosystem: largely non-spatial phenomenon . To capture the benefits of invading novel territory to the cancer system , we used dynamic variables to represent the domain size of both leader and follower cells ( ΩL and ΩF ) . The advantages of this approach include: ( 1 ) biophysical properties are lumped into a few effective parameters with clear biophysical meanings , e . g . , strength of interaction between populations , providing qualitative understanding of the complex interactions; ( 2 ) the low dimensional parameter space allows for systematic analysis to explore and determine the critical boundaries corresponding to disruption of collective invasion . While these simplifications allowed for useful analytical techniques , they also come with some limitations . Our model assumed that leader cells , follower cells , and extracellular factors ( VEGF , Fibronectin , etc . ) were distributed in a spatially homogeneous manner , which is likely not the case in vivo . In particular , for successful collective invasion , leader cells must be at the periphery of an invasive front . Further , VEGF acts as a chemo-attractant in healthy cells and in most cancers [21 , 34] , stimulating other cells to move up the VEGF gradient . These concepts of invasive front or VEGF gradient cannot be captured in our non-spatial model . Our model also fails to describe the motion of cells that cannot be accounted for by a simple increase in domain size , e . g . , the impact of leader cell invasion to free up more room for growth and to colonize new sites . Despite these limitations the model reproduces many essential properties of the complex interactions found in experiments with the leader-follower tumor ecosystem and makes predictions about critical tipping points in the collective invasion of simplified leader follower cell populations . Future work is necessary to extend our results to models incorporating the spatial evolution of leader cells , follower cells , and extracellular factors ( VEGF , Fibronectin , etc . ) . One possibility includes using cellular Potts models to study invasion in cancer [45] to derive a reaction diffusion simplification using the procedure outlined in [46] . This approach should produce a spatially dependent continuous probability density approximation of a discrete and stochastic model . This model could allow us to extend our understanding of the spatially important aspects of the tumor ecosystem dynamics addressed here as well as investigate novel phenomena such as the impact of the extra cellular matrix organization and the interactions with cancer associated fibroblasts on collective invasion . Previous results to model complex tumor cell population dynamics range from detailed cellular level models ( e . g . [9 , 47–49] ) to continuous models with a different degree of complexity ( e . g . [20 , 50–53] ) similar to that proposed in our new study . While cellular level models can directly incorporate heterogeneous cell types and intrinsic tumor properties , including proliferation , metabolism , migration , protease and basement membrane protein expression , and cell-cell adhesion , they typically have high-dimensional variables and parameter space that is difficult to explore . Advantages of the reduced type of models include the low dimensional parameter space , where parameters have clear biophysical meanings , and which allows for systematic analysis to rapidly explore and determine the sensitive parameter space . We previously applied this approach to study cell interactions in chronic cancers and predicted conditions for explosive tumor growth [20] . Similar approach was applied to model cancer cell population dynamics in many other types of cancer [50 , 53 , 54] . The vast diversity between different cancers and even between different cell types within a single tumor remains one of the biggest hurdles to overcome to achieve personalized cancer treatment . This diversity leads to a complex array of interactions between different tumor cell types and the healthy surrounding tissue: the tumor ecosystem . Our work has isolated phenotypically unique lung cancer cells and taken a dynamical approach to understanding the interactions within the tumor ecosystem . We identified the critical features and interactions composing the leader-follower ecosystem , to explore vulnerabilities of the lung cancer invasive cell populations .
|
Cancer is an elusive disease due to the wide variety of cancer types and adaptability to treatment . How is this adaptability accomplished ? Loss of genetic stability , a hallmark of cancer , leads to the emergence of many different types of cancer cells within a tumor . This creates a complex ecosystem where cancer cell types can cooperate , compete , and exploit each other . We have previously used an image-guided technology to isolate distinct cancer subclones and identify how they interact . Here , we have employed mathematical modeling to understand how the dynamic feedbacks between different cancer cell types can impact the success of invasion in lung cancer . We found that successful invasion required for feedbacks to support the less viable but more invasive cell types . These predictions may have implications for novel clinical treatment options and emphasize the need to visualize and probe cancer as a tumor ecosystem .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"ecology",
"and",
"environmental",
"sciences",
"medicine",
"and",
"health",
"sciences",
"vegf",
"signaling",
"population",
"dynamics",
"cancer",
"treatment",
"cancers",
"and",
"neoplasms",
"oncology",
"systems",
"science",
"mathematics",
"population",
"biology",
"conservation",
"biology",
"computer",
"and",
"information",
"sciences",
"system",
"stability",
"ecosystems",
"lung",
"and",
"intrathoracic",
"tumors",
"dynamical",
"systems",
"conservation",
"science",
"signal",
"transduction",
"species",
"extinction",
"cell",
"biology",
"ecology",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"evolutionary",
"biology",
"cell",
"signaling",
"evolutionary",
"processes"
] |
2018
|
The complex ecosystem in non small cell lung cancer invasion
|
Asymmetric segregation of damaged proteins at cell division generates a cell that retains damage and a clean cell that supports population survival . In cells that divide asymmetrically , such as Saccharomyces cerevisiae , segregation of damaged proteins is achieved by retention and active transport . We have previously shown that in the symmetrically dividing Schizosaccharomyces pombe there is a transition between symmetric and asymmetric segregation of damaged proteins . Yet how this transition and generation of damage-free cells are achieved remained unknown . Here , by combining in vivo imaging of Hsp104-associated aggregates , a form of damage , with mathematical modeling , we find that fusion of protein aggregates facilitates asymmetric segregation . Our model predicts that , after stress , the increased number of aggregates fuse into a single large unit , which is inherited asymmetrically by one daughter cell , whereas the other one is born clean . We experimentally confirmed that fusion increases segregation asymmetry , for a range of stresses , and identified Hsp16 as a fusion factor . Our work shows that fusion of protein aggregates promotes the formation of damage-free cells . Fusion of cellular factors may represent a general mechanism for their asymmetric segregation at division .
A dividing cell can deal with damaged material in two different ways . First , the damaged material can be segregated asymmetrically during division , such that it is concentrated in one of the two newborn daughter cells , while the other cell is born clean . The damage is then removed from the population when the cell retaining the damaged material dies . Second , in phases of rapid growth , damaged material can be segregated randomly , leading to less asymmetric segregation of damage between daughters . In this case , accumulation of damage within any cell is prevented by rapid divisions that dilute the damaged material . Protein aggregates are a type of damaged material , composed of insoluble and dense protein particles [1] . These aggregates , instead of being degraded , accumulate in the cell during stress and aging [2]–[4] . Once formed , aggregates can interfere with cell cycle progression and cell function [5] and correlate with cell death [6] . To deal with protein aggregates during cell division , Escherichia coli and Saccharomyces cerevisiae , as well as stem cells , use asymmetric segregation , where aggregates are retained by one cell , generating a clean sister cell [2] , [3] , [7]–[10] . In E . coli , protein aggregates accumulate at the cell poles and often segregate with the old cell pole [3] . In the case of S . cerevisiae , asymmetric segregation of aggregates is achieved through a combination of retention in specialized compartments [8] , [11]–[14] , active transport [8] , and limited diffusion through the bud neck [9] . However , the mechanisms underlying aggregate segregation in eukaryotic cells that divide symmetrically are unclear . We have recently shown that the symmetrically dividing fission yeast Schizosaccharomyces pombe does not show aging under favorable conditions , which suggests that aggregates are segregated symmetrically [6] . After stress , however , the cells inheriting large aggregates do age and eventually die , while their sisters with small or no aggregates do not age [6] . How a large aggregate arises after stress , and how the generation of aggregate-free cells is achieved , remained unknown . Here we study the mechanism underlying the transition from symmetric to asymmetric aggregate segregation . By combining in vivo quantification of aggregate nucleation , movement , fusion , and segregation with a mathematical model , we show that under favorable conditions aggregates fuse rarely and segregate symmetrically at division . Using the total amount of aggregates , measured as the total fluorescence intensity in puncta of the GFP-tagged Hsp104 disaggregase [6] , to identify different levels of aggregation in response to stress , our experiments show that an increase in fusion facilitates asymmetric segregation of aggregates and production of aggregate-free cells . These results are consistent with the predictions of our model , which provides support for the conclusion that the formation of damage-free cells is promoted by aggregate fusion .
We monitored protein aggregates using the Hsp104 disaggregase , a chaperone that binds and separates aggregated proteins [15] , labeled with GFP ( Figure 1A , Figure S1 , and Text S1 ) . We have shown before that Hsp104 from S . pombe is active as a disaggregase in vitro and in vivo [6] and that the puncta of Hsp104-GFP observed in the cytoplasm represent endogenous aggregates . We also observed diffuse Hsp104-GFP in the nucleus ( Figure 1A ) and in the cytoplasm ( see Figure S2F ) , as shown previously in S . cerevisiae [16] . While the lower disaggregase activity of Hsp104 from S . pombe , when compared to its S . cerevisiae homolog [6] , likely accounts for the presence of aggregates under favorable conditions , deleting hsp104 resulted in increased aggregation ( Figure S1F–I ) and increased cell death after stress [6] , while labeling the endogenous Hsp104 with GFP has no effect on stress recovery [6] . The Hsp104-GFP puncta are composed of aggregated proteins and chaperones ( Figure S1 ) , as reported for other organisms [5] . To study aggregate dynamics during the cell cycle , we followed Hsp104-associated aggregates with wide-field fluorescence microscopy ( Materials and Methods ) . Aggregates nucleated equally often in each of the two respective cytoplasmic regions ( compartments ) between the nucleus and the old cell pole , and the nucleus and the new cell pole , generated in the previous division ( 1 . 3±0 . 2 nucleation events/cell cycle , n = 162 cells; Figure S2A and S2B ) . After nucleation , aggregates typically remained in the same compartment ( only 3 . 2±1 . 5% of aggregates moved between the compartments , n = 126 cells ) . Aggregates moved and contact between them resulted in their fusion ( 94/100 contacts resulted in fusion; 0 . 40±0 . 06 fusion events/cell cycle , n = 200 cells; Figure 1A , Movie S1 ) . Fission of aggregates was rare ( 0 . 006±0 . 005 events/cell cycle ) , and disappearance of aggregates was not observed ( n = 498 cells ) . We tracked individual aggregates on time scales from milliseconds to tens of minutes and observed dynamics suggesting diffusive motion ( Figures 1B and S2C–F and Movie S2 ) . To test whether aggregate movement was diffusive and not linked with the movement of other subcellular components , we performed a combination of tests , which confirmed that aggregates ( 1 ) move according to Stokes diffusion ( Figure 1B , inset ) , ( 2 ) do not co-localize with the cytoskeleton ( actin or microtubules ) or a wide range of lipid structures ( cellular membrane , endosomes , Golgi , vacuoles , and nuclear membrane ) ( Figure S2G and S2H ) , and ( 3 ) still undergo diffusion and fusion when the cytoskeleton is depolymerized ( Figures S2I–K; see also Text S1 ) . We next studied how aggregates are segregated between cells at division . Because aggregates nucleate and move randomly , we hypothesized that sister cells arising from a morphologically symmetrical division inherit the same number of aggregates on average . Indeed , the aggregates did not segregate specifically to a cell inheriting the new or the old pole ( Figure S2B; the small bias can be a consequence of the displacement of aggregates towards the old pole by the nucleus during anaphase ) . In the wild type , the two equally sized sister cells inherited on average the same number of aggregates ( Figure 1C and 1D ) . Because asymmetric cell division may lead to biased segregation of aggregates towards the larger sister cell , we enforced asymmetry in cell division by using a Δpom1 mutant , in which the division plane is displaced off-center , resulting in two cells of different size [17] . We observed that cells were up to 70% larger than their smaller sisters , and larger cells retained correspondingly more aggregates ( Figure 1C and 1D and Movie S3 ) . These results show that aggregate segregation in S . pombe is unbiased . We conclude that aggregate nucleation and movement is random , resulting in random aggregate segregation at division . Based on our experimental observations , we developed a stochastic aggregation model ( Figure 2A ) that allows for the simulation of aggregate size distributions ( Figure 2B ) , which can be compared with the experimentally observed size distributions ( measured by the intensity of Hsp104-GFP in each puncta , a . u . ) . A key feature distinguishing the proposed model from other models [18]–[20] is that aggregate segregation asymmetry is an output rather than an input of our model . Three key processes operate on size distributions of aggregates in each of the two compartments of a cell ( Figure 2A ) : ( 1 ) generation of the smallest size aggregates at rate r; ( 2 ) fusion of aggregates of sizes i and j at rate K ( i , j ) to create an aggregate of size i+j; and ( 3 ) random segregation of aggregates to two new compartments at division . We use the Brownian kernel: ( 1 ) where k = K ( 1 , 1 ) is a parameter to be determined . This well-established kernel [21] , [22] can be derived from Brownian diffusion of aggregates with Stokes friction , a fusion rate increasing in proportion to the sum of the aggregates' radii , and aggregate packing such that size ( volume ) is proportional to radius cubed . In this manner , the effect of spatial diffusion on fusion rate is incorporated into the model , without explicitly simulating spatial diffusion [9] . We introduce a visibility threshold ν below which aggregates cannot be detected by wide-field fluorescence imaging ( Figure S3A ) . A visible nucleation event occurs when two nondetectable aggregates fuse , forming a detectable one . Generation and fusion of aggregates within compartments were simulated with a stochastic aggregation algorithm [23] , which in turn was embedded within another algorithm that implemented random aggregate segregation among compartments at division ( Text S1 ) . The testable predictions of our model are ( i ) large aggregates are rare , while small ones are more abundant; ( ii ) an increase in the number of aggregates at cell birth gives rise to a decrease in aggregate nucleation and ( iii ) to an increase in fusion; ( iv ) at cell division , the pattern of aggregate segregation into the daughter cells is between a completely symmetric and a random one; and ( v ) aggregate fusion increases their segregation asymmetry at cell division and promotes the birth of aggregate-free cells . These model predictions are general features of the model behavior and are not dependent on specific parameter values . We will now compare predictions i–iv with our experimental results . Prediction v will be tested in the response-to-stress extension of the model described below . The experimentally measured size distribution of aggregates shows that small aggregates are found more frequently than large ones ( Figure 2B ) , confirming prediction i . Whereas the experimentally measured number of fusion events increases with the total number of aggregates ( Figure 2C ) , the number of nucleation events shows the opposite trend ( Figure 2D ) , confirming predictions ii and iii . The model therefore shows that in the presence of a high number of visible aggregates , an invisible aggregate is increasingly likely to fuse with a visible aggregate rather than fusing with another invisible aggregate to create a visible aggregate , which is observed as nucleation . Parameter values were then fitted ( Figure S3A ) to obtain quantitative as well as qualitative consistency for these three predictions ( Text S1 ) . The parameter values were additionally corroborated by theoretical arguments ( Text S1 ) . The parameterized model predicts a pattern of aggregate segregation at cell division by aggregate number that is between completely symmetric segregation , where the difference in the aggregate number is the minimal possible , and fully random segregation , where each aggregate can segregate to either of the two newborn cells , corresponding to the model without compartmentalization . The experimentally measured segregation pattern closely matches that predicted by the model , thereby confirming prediction iv ( Figure 2E ) . Thus , our results do not support a biased segregation ( by compartment ) of aggregates in fission yeast . If the average aggregate amount formed per cell cycle is substantially less than the amount which affects cell growth ( death threshold “d” , 5 a . u . ) [6] , symmetric segregation at division is sufficient to dilute the aggregates and allow survival , but if the average amount is more than what would be required to kill both daughter cells , asymmetric segregation may be necessary for one of the daughter cells to survive . We tested the effect of a range of aggregate levels on segregation dynamics and on cell viability . To increase the aggregate amount , we used stress conditions such as oxidative stress ( H2O2 ) and transient or continuous heat stress ( T = 40°C ) ( Figure 3A ) . Both types of stress increased the number of aggregate nucleation and fusion events ( Figure 3B ) . As in the control situation , aggregate movement after heat stress was consistent with Stokes diffusion ( Figure S4A and S4B ) and 97 out of 103 aggregate contacts resulted in fusion . During recovery from stress , aggregates did not co-localize significantly with actin structures or microtubules ( Figure S4C ) . As under control conditions ( Figure S2J ) , nucleation and fusion of aggregates after stress occurred also in the absence of actin or microtubule structures ( for cells treated with Lat . B or MBC , 94/102 or 90/97 contacts resulted in fusion , respectively; Figure S4D ) . Remarkably , fusion converted the aggregates into a single large one within the first few cell cycles after stress ( Figure 3A ) . This single aggregate was asymmetrically segregated to one of the sister cells at division ( Figure 3A ) , while the other sister cell was born without aggregates ( segregation was not biased towards the old or the new cell pole; Figure S4E ) . Cells with an aggregate amount greater than d typically died ( 28/49 cells ) , whereas their sisters survived ( 48/49 cells ) , indicating that the clearance of aggregates through asymmetric segregation is important for viability . To address whether the aggregate number has an effect on the cell cycle [7] of cells born with similar aggregate amounts , we compared the division time of cells inheriting only one aggregate with that of cells inheriting two or more aggregates ( Figure S4F ) . We observed no significant difference in the division time of cells containing one or more aggregates ( Figure S4F ) , which agrees with our previous observation that the total aggregate amount correlates more strongly with cell death than aggregate number [6] . To test whether the transition to asymmetric segregation could be reproduced theoretically , we introduced stress into the model , using the parameters fitted for control conditions . We raised the aggregate generation rate r to obtain the experimentally observed aggregate nucleation upon heat stress ( Figure 3B ) in one simulated cell cycle , and then returned r to the control value and simulated for another cycle before the first cell division ( r values are shown in Figure S3A ) , to account for the duration of the experimental stress recovery . The experimentally observed size distributions ( Figure S4G ) , dependence of fusion on the number of aggregates ( Figure S4H ) , and aggregate segregation patterns ( Figure S4I ) were consistent with the model including stress , indicating that the model is robust . The model shows a 10-fold increase in the number of fusion events compared to the control situation , which is explained by the increased aggregate number ( Figure S4H ) . Fusion causes a shift toward large aggregate sizes after stress , and faster recovery to the control size distribution for small aggregate sizes at division 2 , in both model predictions and experimental results ( Figure S4G ) . Thus , the stochastic aggregation model is consistent with the observed aggregate behavior after stress . To understand which segregation modes maximize daughter cell survival for a given total aggregate amount , we model the effect of the segregation asymmetry on cell survival by assuming that , as observed experimentally [6] , a cell dies if it has a total aggregate amount at birth above the death threshold d . This leads to three distinct optimal segregation regimes that maximize the number of surviving cells: ( 1 ) any segregation asymmetry when the total aggregate amount at division is below d , ( 2 ) low segregation asymmetry when the amount is between d and 2d , and ( 3 ) high asymmetry when the amount is above 2d ( Figure 3C , scheme and corresponding gray regions in graph ) . The model predicts that fusion facilitates asymmetric segregation in response to different levels of stress , where high asymmetry is optimal ( Figure 4C , filled circles ) . This behavior was also observed experimentally for a range of stresses ( Figure 4C , filled squares ) . We observed that in divisions 2 and 3 after stress , the percentage of cells born without aggregates was higher for stress conditions that originated in a higher aggregate amount ( Figure S4J ) . This phenomenon can be explained by the higher number of fusion events observed for high stress levels ( e . g . , heat stress as opposed to oxidative stress; Figure 3B ) , which can result in the faster generation of a single large aggregate . Once large aggregates are formed , nucleation of aggregates decreases in favor of the growth of the large aggregates: as observed for unstressed cells ( Figure S4C ) , the nonvisible aggregates have a higher probability to fuse with large preexisting aggregates . We conclude that in response to increased aggregate amount , an increase in fusion leads to fewer aggregates and thus more asymmetric segregation , which promotes the formation of aggregate-free cells . The model predicts that reducing fusion decreases segregation asymmetry ( Figure 3C , empty circles ) . To test the prediction , we needed to identify a molecular factor that would reduce fusion . Small heat shock proteins are a special class of chaperones , which bind and sequester misfolded proteins [24] . The fission yeast small heat-shock protein 16 ( Hsp16 ) was described to co-aggregate with misfolded proteins during stress [25]; therefore , we hypothesized that Hsp16 has a role in the fusion of aggregated proteins in vivo . Indeed , we observed that when we deleted Hsp16 , the number of aggregate contacts resulting in fusion decreased ( Figure 4A and 4E ) and aggregate fusion per cell cycle also decreased ( Figure 4B ) , which correlated with an increase in the number of cells containing aggregates in the population ( Figure S4M ) . Aggregate nucleation ( Figure 4C ) and fission ( Figure 4D ) per cell cycle was not significantly altered in the absence of Hsp16 . The total amount of aggregates was unaffected by the deletion of Hsp16 ( Figure S4L ) , which argues against the possibility that in the absence of Hsp16 there are generally more damaged proteins . Thus , Hsp16 is primarily an aggregate fusion factor . The decrease in fusion efficiency was specific to Hsp16 deletion , as deleting Hsp40 or Hsp70 , molecular chaperones that participate in protein disaggregation [26] , did not interfere with fusion or fission significantly ( Figure 4A , 4B , and 4D ) . Contrary to Hsp16 deletion , deleting Hsp40 or Hsp70 caused an increase in aggregate nucleation ( Figure 4C ) and total amount per cell ( Figure S4L ) , whereas an increase in total aggregate number per cell was observed in all three deletions ( Figure S4M ) . Taken together , these results suggest that the increase in the number of aggregates in Δhsp16 cells compared to the wild type is a consequence of reduced fusion . We proceeded to test the prediction of the model in the strain deleted for Hsp16 . We observed that decrease in fusion resulted in a decrease in the segregation asymmetry of aggregate amount ( Figure 4F and 4G ) , as expected from the model where , as a qualitative approximation , aggregates were not allowed to fuse after stress ( Figure 3C ) . The model including aggregate fusion also precisely predicted the fraction of cells born without stress-induced aggregates at each division after stress in the wild type ( Figure 4H ) . Remarkably , in spite of the fact that 10 aggregates on average were formed after stress ( Figure 3B ) , by the second and third division , ∼15% and 50% of the cells were born clean of aggregates , respectively ( Figure 4H ) . Importantly , when the aggregates were not allowed to fuse in the model including stress , the fraction of cells born free of aggregates was halved ( Figure 4H ) . Parameter sensitivity analysis shows that the fraction of cells born clean after stress is highly sensitive to the strength of the fusion process during recovery ( k ) , and is also decreased by a faster generation of aggregates ( r ) during stress ( Figure S3B ) , as would be intuitively expected . The average number of aggregates per cell immediately after stress is increased by generation during stress ( r ) and decreased by fusion combining aggregates together ( k ) ( Figure S3C ) . Both the fraction of cells born clean and the number of aggregates after stress are insensitive to the generation rate and fusion rate before stress was applied , as well as to the number of aggregates with which the first cells in the simulations were initialized . As predicted by the model without fusion , we observed in the experiments a ∼50% decrease in the fraction of aggregate-free cells in Δhsp16 compared to wild-type cells ( Figure 4H ) , which correlated with an increase in the fraction of dead cells after heat stress ( 17±2% in Δhsp16 versus 9±1% in wild type , mean ± SEM , n = 123 and 140 cells , respectively ) . We conclude that fusion facilitates asymmetric damage segregation and accelerates the generation of cells clean of stress-induced aggregates , as stated in prediction v described above .
We have demonstrated that the symmetrically dividing cells of S . pombe undergo a transition to highly asymmetric segregation of protein aggregates , which is facilitated by aggregate fusion . As we observed that aggregates occur in the absence of Hsp104 , both under favorable and stress conditions ( Figure S1F–H ) , fusion is likely occurring for aggregated proteins in general , and is not specific of Hsp104-associated aggregates . In response to increased aggregate nucleation , two distinct mechanisms—stochastic movement and chaperone-mediated fusion of aggregates—combine to generate a single large unit of damage , which has to be segregated asymmetrically , resulting in the birth of a damage-free cell ( Figure 4I ) . Creation of a single large unit requires extensive fusion , which is promoted by an increase in the number of aggregates and a higher Hsp16 chaperone level ( Figure S1F ) , as a consequence of heat stress [27] . It is possible that fusion has a cytoprotective effect [28] by merging the aggregates in a single unit , such as during the first two cell cycles following stress recovery , before a clean cell is born . However , irrespective of the number of aggregates , if the cell is born with a total aggregate amount above the death threshold , this cell is likely to die [6] . Due to the geometry of cell division in S . pombe , the asymmetry in segregation can only be established at the second division after stress . This becomes clear when considering the extreme scenario where all aggregates fuse into a unit in both cell compartments within the first cell cycle after stress . In this case , each sibling receives one large aggregate after the first division . In the second division , 50% of cells inherit this single aggregate , while their sisters are born clean . This , however , occurred only in a smaller percentage of the cells . The cells took , on average , one extra cell cycle to generate an aggregate-free cell , at the third division . This delay may be because the frequency of aggregate fusion events decreases over the first and second division , as the total number of aggregates is reduced . It is likely that the activated stress response promotes survival of cells with a high total aggregate amount for more than two divisions after stress , to ensure survival until cells with nonlethal amounts of aggregates are generated . How do protein aggregate dynamics and segregation in S . pombe compare to those in other organisms ? In S . cerevisiae and in kidney and ovary cells , aggregates are anchored to or transported by the cytoskeleton [8] , [10] , [29] , [30] and localize to functionally distinct protein quality control compartments [11] , [13] , [31] , [32] , which may also be involved in the asymmetric segregation of aggregates [11] , [12] . In budding yeast , the sorting of misfolded proteins into these compartments is dependent on a small heat-shock protein , Hsp42 [12] , [14] , [31] . Hsp42 carries an N-terminal extension , which may promote anchoring of aggregates to the cytoskeleton [14] or membrane compartments [11] , thus ensuring their selective retention in the mother cell . Small heat-shock proteins in S . pombe , however , lack this N-terminal domain and do not interact with the cytoskeleton or organelles , which agrees with our observation that aggregate movement is random . The specific role of Hsp16 in aggregate fusion and cell survival after stress [6] suggests that fusion is a regulated process that is essential for the cell , as opposed to the consequence of an unregulated aggregate seeding process , observed in cells lacking Hsp40 or Hsp70 . Taken together , these findings suggest that an organisms' mode of cell division—morphologically symmetric versus asymmetric—generates specific evolutionary constraints , which may be counterbalanced by the invention or refinement of molecular pathways for concentrating and inheriting protein aggregates . While in S . cerevisiae [11]–[13] and mammalian neurons [29] aggregates associate with subcellular structures , in E . coli and neuroblast cells aggregates localize to nucleoid-free [33] or organelle-free cytoplasmic regions [34] , respectively . A common aspect of aggregate behavior in all these different systems is movement—either by diffusion [9] , [28] , [31] , [35] or active transport [8] , [29]—which may allow for contacts and fusion between aggregates to occur . Therefore , fusion might be a conserved mechanism that contributes to asymmetric segregation of aggregates . Fusing a number of molecules/components in a cell represents an opportunity to segregate asymmetrically . In mathematical terms , fusion increases the difference between the number of aggregates inherited by daughter cells at segregation . While low numbers of a component that is randomly segregated at division assures a higher variability in individual cells in the population , the formation of a unitary component assures a complete asymmetry in segregation that might be important when minimizing damage or maximizing resources . Fusion might also be a mechanism to establish asymmetry in the localization of aggregated functional molecules within the cell [36] , [37] , as an increase in the size of the aggregate will lower its diffusion or cause it to be physically trapped between large organelles . The concept of fusion as a mechanism to achieve asymmetry may extend to other phase-partitioned molecules , such as prions [38] , metabolic enzymes [39] , [40] , or RNA granules [41] . In general , fusion of cellular factors may represent a general mechanism to achieve asymmetric localization and segregation at cell division .
Cells were grown as described before [42] . For imaging , cells were transferred to a MatTek dish ( MatTek , Ashland , USA ) and imaged in liquid media ( YE5 or EMM ) or covered with a solid agarose pad ( YE5-4% Agarose , SeaKem , Hessisch Oldendorf , Germany ) at 30°C . For stress resistance , assays cells were treated with water , as a control , or oxidative stress with 1 mM H2O2 ( Sigma-Aldrich , Hannover , Germany ) followed by growth at T = 30°C ( 70% of cells undergo mitosis , n = 30 ) , heat stress of 40°C for 30 min followed by growth at T = 30°C ( 67% of cells undergo mitosis , n = 30 ) , or continuous heat ( stress of 40°C for 1 h followed by growth at 37°C , 53% of cells undergo mitosis , n = 30 ) . Under favorable conditions , 99 . 7% of cell complete mitosis successfully [6] . Strains were constructed using a PCR-based gene targeting technique [43] , where the label was inserted in the C-terminal region of the target gene in the native genomic locus , keeping it under the control of native expression regulators . Cells were imaged in a DeltaVision core microscope , with a motorized XYZ stage ( AppliedPrecision , USA ) . An Olympus UPlanSApo 100× 1 . 4 NA Oil ( R . I . 1 . 516 ) immersion objective was used ( Olympus , Tokyo , Japan ) . The illumination was provided by a LED ( transmitted light ) and Lumicore solid-state illuminator ( SSI-Lumencore , fluorescence ) , and the images were acquired with a Cool Snap HQ2 camera ( Photometrics , Tucson , AZ , USA ) and the SoftWorx software ( AppliedPrecision , USA ) , using 2×2 pixel binning , to minimize light exposure ( pixel size = 0 . 1288 µm ) . For long-term time lapse imaging , Z-stacks for 6–12 nonoverlapping imaging areas in the sample were acquired every 10 min ( total time = 20 h ) and in short time-lapses every minute ( total time = 1–3 h ) . For single Z-stacks cells were imaged with exposure = 0 . 05–0 . 20 s , 2%–50% transmission , depending on the protein and fluorescent label . As a control for photo-toxicity , cell cycle duration and protein aggregate number were measured and found similar in the presence and absence of continuous illumination . To quantify the total number of aggregates and to visualize small fast-moving aggregates and fusion events , we used highly inclined and laminated optical sheet microscopy ( HILO ) [44] with a high laser power , on a total internal reflection fluorescence ( TIRF ) microscopy setup . Whereas TIRF illuminates up to 200 nm from the surface of the coverslip , HILO allowed us to image deeper in the cytoplasm , up to a depth of about 1 . 5 µm [44] . An Olympus-IX71 ( Olympus , Tokyo , Japan ) inverted microscope was used . Incidence angle of a DPSS 491 nm laser was changed to allow for excitation of the fluorophores in the sample up to 1 µm deep ( 1/3 of the cell volume was illuminated ) . Cells close to the glass surface of a MatTek dish ( MatTek , Ashland , USA ) were imaged , one at a time , with continuous excitation and laser power of 80% for fast imaging ( 200 frames/s , duration 20 s ) and 10% for slow imaging ( 10 frames/s ) . An Olympus PlanApo 100×1 . 45 NA TIRFM objective ( Olympus , Tokyo , Japan ) and an Andor iXon EM+ DU-897 BV EMCCD ( Andor , Belfast , UK ) camera were used . Images were acquired while incubating the cells in EMM at 25°C , in order to decrease autofluorescence . Protein aggregates and subcellular structures were imaged simultaneously to test for co-localization and coordinated movement using bright field , a complementary set of fluorescent proteins ( GFP , RFP , or mCherry ) and dyes ( Phalloidin and FM-464 ) . We labeled protein aggregates indirectly with Hsp104-GFP or Hsp104-mCherry . Bright field was used to directly visualize cell poles and the division plane . Actin was indirectly labeled in vivo by expressing a calmodulin domain coupled to an N-terminal GFP ( GFP-CHD ) and directly labeled ex vivo in formaldehyde fixed cells with 2 . 5 µM phalloidin . Microtubules and the microtubule nucleating center ( the spindle-pole body , SPB ) were directly labeled using two structural components , atb2-mCherry and sid4-RFP , respectively . The nuclear membrane was directly labeled with bqt4-mCherry , an integral nuclear membrane protein . Incubating cells in 1 mM FM-464 for 10 h resulted in the direct labeling of several lipid structures [45] ( cellular membrane , vacuoles , endosomes , and the Golgi complex ) .
|
During their lifetime , cells accumulate damage that is inherited by the daughter cells when the mother cell divides . The amount of inherited damage determines how long the daughter cell will live and how fast it will age . We have discovered fusion of protein aggregates as a new strategy that cells use to apportion damage asymmetrically during division . By combining live-cell imaging with a mathematical model , we show that fission yeast cells divide the damage equally between the two daughter cells , but only as long as the amount of damage is low and harmless . However , when the cells are stressed and the damage accumulates to higher levels , the aggregated proteins fuse into a single clump , which is then inherited by one daughter cell , while the other cell is born clean . This form of damage control may be a universal survival strategy for a range of cell types , including stem cells , germ cells , and cancer cells .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"computer",
"and",
"information",
"sciences",
"mathematical",
"computing",
"model",
"organisms",
"mathematics",
"cell",
"biology",
"theoretical",
"biology",
"biology",
"and",
"life",
"sciences",
"computing",
"methods",
"physical",
"sciences",
"yeast",
"and",
"fungal",
"models",
"molecular",
"cell",
"biology",
"biophysics",
"research",
"and",
"analysis",
"methods"
] |
2014
|
Fusion of Protein Aggregates Facilitates Asymmetric Damage Segregation
|
Specialized microenvironments called niches regulate tissue homeostasis by controlling the balance between stem cell self-renewal and the differentiation of stem cell daughters . However the mechanisms that govern the formation , size and signaling of in vivo niches remain poorly understood . Loss of the highly conserved histone demethylase Lsd1 in Drosophila escort cells results in increased BMP signaling outside the cap cell niche and an expanded germline stem cell ( GSC ) phenotype . Here we present evidence that loss of Lsd1 also results in gradual changes in escort cell morphology and their eventual death . To better characterize the function of Lsd1 in different cell populations within the ovary , we performed Chromatin immunoprecipitation coupled with massive parallel sequencing ( ChIP-seq ) . This analysis shows that Lsd1 associates with a surprisingly limited number of sites in escort cells and fewer , and often , different sites in cap cells . These findings indicate that Lsd1 exhibits highly selective binding that depends greatly on specific cellular contexts . Lsd1 does not directly target the dpp locus in escort cells . Instead , Lsd1 regulates engrailed expression and disruption of engrailed and its putative downstream target hedgehog suppress the Lsd1 mutant phenotype . Interestingly , over-expression of engrailed , but not hedgehog , results in an expansion of GSC cells , marked by the expansion of BMP signaling . Knockdown of other potential direct Lsd1 target genes , not obviously linked to BMP signaling , also partially suppresses the Lsd1 mutant phenotype . These results suggest that Lsd1 restricts the number of GSC-like cells by regulating a diverse group of genes and provide further evidence that escort cell function must be carefully controlled during development and adulthood to ensure proper germline differentiation .
Stem cells undergo self-renewing divisions in which at least one daughter retains its stem cell identity , while the second daughter may or may not differentiate , depending on intrinsic and extrinsic cues . A balance between stem cell self-renewal and differentiation must be maintained for proper organ formation during development and tissue homeostasis in adulthood . Stem cells often reside in microenvironments called niches , and specific mechanisms tightly regulate the size and signaling output of these structures [1] . However , in vivo niches have often proven difficult to identify in mammalian tissues . As a result , much of the current understanding of niches stems from the study of invertebrate models such as the germline stem cells ( GSCs ) of the Drosophila ovary . Drosophila female GSCs reside in a well-characterized niche at the tip of a structure called a germarium ( Figure 1A ) . Within germaria , GSCs lie immediately next to a somatic cell niche comprised of cap cells and terminal filament cells [2] . Escort cells reside adjacent to the cap cells and line the anterior portion of the germarium . These cells act to shepherd the germ cells during the earliest stages of their differentiation [3] , [4] , after which developing germline cysts are enveloped by follicle cells derived from a second stem cell population within the germarium . Cap cells produce Decapentaplegic ( Dpp ) , which in turn activates a canonical Bone Morphogenic Protein ( BMP ) signal transduction pathway in GSCs [5] , [6] . BMP pathway activation results in the transcriptional repression of bag of marbles ( bam ) [7]–[9] , a factor both necessary and sufficient for germ cell differentiation [10] , [11] . Ectopic Dpp signaling outside the tip of the germarium results in an expanded GSC phenotype [5] , [9] . Other pathways and neighboring cells likely regulate niche specific BMP signaling . For example , a recent study provides evidence that hedgehog ( hh ) produced by the cap cells stimulates the anterior escort cells to produce niche specific signals [12] Moreover , several additional intrinsic and extrinsic mechanisms help restrict Dpp ligand production and diffusion within the niche ( reviewed in [13] , [14] ) . One such mechanism involves the histone demethylase Lysine Specific Demethylase 1 ( Lsd1 ) . Lsd1 uses a flavin-dependent monoamine oxidative based mechanism to remove mono- and di-methyl groups from histone H3 on lysine 4 ( H3K4me1 and H3K4me2 ) [15] . In mammals , Lsd1 has been shown to silence a number of distinct gene sets in different cellular contexts , including Notch targets , TGFβ-1 and various loci involved in the maintenance of embryonic stem cells [16]–[20] . Additional studies suggest that Lsd1 may also promote gene expression under certain circumstances [21] . Disruption of Drosophila Lsd1 results in a male and female sterile phenotype , marked by the expansion of GSC-like cells in the germarium [22] , [23] . These cells exhibit ectopic BMP responsiveness and fail to initiate a normal differentiation program once they leave the cap cell niche [24] . To characterize the molecular mechanism by which Lsd1 restricts signaling outside the Drosophila female GSC niche , we used ChIP-seq to define direct binding sites of Lsd1 specifically in either escort cells or cap cells . These experiments revealed that Lsd1 binds to over one hundred sites in escort cells and provide further insights into how Lsd1 contributes to the chromatin programming of cells inside and outside of an in vivo niche .
Escort cells send out extensions that closely contact germline cysts undergoing the early steps of differentiation [3] , [4] . Escort cell death or genetically disrupting escort cell extensions can lead to an inappropriate expansion of GSC-like cells in the germarium [3] . Previous results showed that Lsd1 functions within escort cells to prevent expanded BMP signaling outside of the GSC niche [24] . This phenotype was accompanied by widespread cell death in both somatic cells and germ cells . Therefore we considered the possibility that the expansion of BMP signaling exhibited by Lsd1 mutants may depend on changes to escort cell morphology and number . To test this , we knocked down the expression of Lsd1 specifically in the escort cells and early follicle cells by crossing UAS-Lsd1RNAi into a c587-gal4; UAS-mCD8::GFP background and stained the resulting ovaries for GFP and the fusome marker Hts . Fusomes are highly vesiculated organelles that appear round in GSCs and cystoblasts , and become branched as these germ cells differentiate into multi-cellular cysts [25] , [26] . Three days after eclosion , control samples appeared normal . These germaria typically contained two to four single cells ( GSCs and cystoblasts ) with round fusomes and escort cells that extended cytoplasmic processes between the developing cysts ( Figure 1B ) . In contrast , the Lsd1 RNAi samples showed an expansion of GSC-like cells with round fusomes . Escort cell extensions were clearly present in some germaria , but were missing in others ( Figure 1C , D ) . These observations suggested that while the knockdown of Lsd1 caused changes in escort cell morphology , the presence of extra single cells with round fusomes did not absolutely depend on a complete loss of escort cell extensions . However changes in escort cell morphology likely contributed to the phenotype over time . In addition , expression of Lsd1RNAi also led to an increase of death within escort cells , consistent with the widespread cell death previously noted in Lsd1 null mutant germaria ( Figure 1E , F ) [24] . Next we performed clonal analysis using the mosaic analysis with a repressible cell marker ( MARCM ) system to further analyze the Lsd1 mutant phenotype . Clonal germaria were stained for the positive clone marker GFP and for the fusome marker Hts . We categorized the relative position of escort cell clones along the anterior-posterior axis of the germarium . Cells were considered anterior escort cells if they were immediately next to the cap cells , posterior escort cells if they were immediately adjacent to the follicle stem cells and middle escort cells if they were located in any position in between . We induced control and Lsd1 mutant clones in parallel . Control escort cell clones were never associated with an obvious robust germline tumor phenotype , although we noted one exception in which a single germarium with control escort cell clones contained six single germline cells with round fusomes ( 1 out of 143 counted ) . By contrast , 17% ( 27/155 ) of the germaria that contained Lsd1 mutant escort cell clones displayed an expanded germline stem cell-like cell phenotype ( Figure 1G–J ) . The relative position of Lsd1 mutant clones appeared to correlate with the appearance of a germline phenotype . The vast majority of germaria ( 96%; n = 27 ) that contained greater than 5 germline stem cell-like cells carried at least one Lsd1 mutant middle escort cell clone . We observed one example in which a germarium with a mild expansion of GSC-like cells contained an Lsd1 mutant anterior clone and posterior clone but no middle escort cell clones ( Figure 1H ) . Of note , most germaria that carried middle escort cell clones did not exhibit a GSC expansion phenotype ( 98/125 germaria ) . While their appearance was rare , germaria with only anteriorly or posteriorly ( Figure 1K ) positioned escort cell clones did not display a robust GSC-like cell expansion phenotype . Similarly , loss of Lsd1 in the terminal filament did not result in an obvious phenotype ( Figure 1L ) . Germaria that contained Lsd1 mutant escort cell clones and exhibited an increased number of GSCs occasionally had an elongated and abnormal morphology ( Figure 1J ) . Moreover , 22 . 1% of the germaria ( n = 199 ) from Lsd1 mutant females lacked marked escort cell clones , compared to 13 . 9% of control germaria ( n = 166 ) , and the average number of Lsd1 mutant clones per germarium ( 4 . 72 escort cell clones/germarium ) was lower compared to controls ( 8 . 77 escort cell clones/germarium ) , suggesting that either Lsd1 mutant escort cell progenitors exhibited reduced proliferation during development or died during the course of the experiment . If increased death within the escort cell population accounted for all the observed phenotypes , one might predict that complete loss of all Lsd1 mutant escort cell clones within a particular germarium would result in an increased number of GSC-like cells . However , we did not observe an expanded GSC phenotype in germaria that lacked clones from Lsd1 mutant females . Together all the phenotypic data suggest both that escort cells require Lsd1 function to limit GSC number and that loss of Lsd1 compromises the growth and survival of escort cells , consistent with previous observations [24] and those noted above , which in turn further exacerbates the observed germ cell phenotypes . To directly define the molecular mechanisms by which Lsd1 influences escort cell function , we elected to identify direct targets of Lsd1 regulation in these cells . Determining whether Lsd1 targeted potential candidate genes represented a significant challenge . For example , the size and complexity of the dpp promoter precluded our ability to assay whether Lsd1 directly targeted this gene using a PCR based chromatin immunoprecipitation ( ChIP ) approach . To systematically define Lsd1 binding sites , we conducted ChIP experiments coupled with massive parallel sequencing ( ChIP-seq ) . We used a number of different Hemagglutinin ( HA ) tagged transgenes , including a N-terminally tagged UASt-HA::Lsd1 transgene that exhibits high expression in the somatic cells and a N-terminally tagged UASp-HA::Lsd1 transgene that displays relatively lower levels of expression in the somatic cells ( Figure 2; S1 ) . The UASt-HA::Lsd1 and UASp-HA::Lsd1 transgenes both fully rescued the Lsd1ΔN GSC tumor phenotype when driven by the c587-gal4 driver . Because Lsd1 is expressed ubiquitously throughout the ovary [24] , we sought to determine whether this protein bound to distinct sites in different cell populations within the germarium . We expressed the UASt-HA::Lsd1 and UASp-HA::Lsd1 trangenes in cap cells and terminal filament cells using hh-gal4 ( Figure 2A; S1 ) and in the escort cells and early follicle cells using the c587-gal4 driver ( Figure 2B; S1 ) . HA-directed ChIP assays were performed on dissected ovaries and the immunoprecipitated chromatin was compared to input chromatin as a control . Within escort cells and early follicle cells , products of the UASp-HA::Lsd1 and UASt-HA::Lsd1 trangenes bound to 207 and 191 sites respectively ( Based on the FindPeaks algorithm using a p-value threshold of 1 . 00e-3 to maximize the number of potential peaks; Table S1 , S2 ) , with 100 common sites sharing some degree of overlap ( Figure 2C ) . Within cap cells and terminal filament cells , the UASp-HA::Lsd1 and UASt-HA::Lsd1 transgenic products associated with 98 and 167 genomic loci respectively ( Table S3 , S4 ) , with 37 overlapping loci in common between the two datasets ( Figure 2C ) . Comparing all four datasets revealed 66 common peaks between terminal filament/cap cells and escort cells/early follicle cells ( Figure 2C , D ) . 232 peaks appeared specific for escort cells and early follicle cells and 162 specific for cap cells and terminal filament cells ( Figure 2C , D ) . MACs analysis [27] showed similar but broader peak calls ( Table S5 , S6 , S7 , S8 ) . Lsd1 enrichment peaks were spread throughout the Drosophila genome ( Figure S2 ) and showed a preference for the promoter and 5′UTR regions of genes ( Figure S3 ) . We were unable to isolate a sufficient number of cells to map H3K4 methylation across the escort cell genome . However , comparing our data with available data from the modENCODE project revealed that Lsd1 binding peaks correlate with valleys of H3K4 methylation in embryos ( Figure S4 ) , consistent with the established biochemical activity of Lsd1 . Strikingly , we did not observe any enrichment for Lsd1 binding near the dpp locus in escort cells ( Figure 2E ) , indicating that the repression of BMP signal transduction by Lsd1 must be through an indirect mechanism . We examined the annotation of genes near escort cell and early follicle cell peaks , cap cell and terminal filament peaks , shared peaks and from the UASt-HA::Lsd1 data sets ( Table S9 , S10 , S11 , S12 ) . This analysis indicated that genes near escort cell specific Lsd1 binding peaks encode products with a diverse array of functions needed for development , basic cellular processes and reproduction ( Figure S5A ) [28] , [29] . Further analysis of this gene set did not reveal significant enrichment for components of specific pathways . MEME analysis showed an enrichment of ACTGGAA elements within Lsd1 binding sites ( Figure S5B ) . The significance of this enrichment remains unclear . These results suggested that the mis-expression of a functionally diverse set of genes likely contributes to the Lsd1 mutant phenotypes . The engrailed gene stood out as one potentially relevant target among the list of candidate genes . engrailed encodes a homeobox transcription factor that acts as a segment polarity gene during embryogenesis [30]–[32] . Previous results showed that engrailed regulates early ovarian development and that Engrailed protein expression is restricted to the terminal filament and cap cells in adult germaria [33] . Engrailed functions within these cells to help maintain GSCs [12] . Our ChIP-seq data revealed that Lsd1 exhibits enriched binding to a 2 kb region of the engrailed promoter in the escort cells ( Figure 3A ) . We performed RNA RT-qPCR to look at the transcript levels of engrailed in Lsd1 mutants . We compared bam mutants to bam Lsd1 double mutants because these samples are comparable in size and have the same basic cellular makeup ( Figure S6 ) . This analysis revealed that engrailed transcript levels increased 6 fold in the absence of Lsd1 ( Figure 3B ) . Next , we tested whether Engrailed protein expression expanded in the absence of Lsd1 . In wild type germaria , cap cells and terminal filament cells express readily detectable levels of Engrailed , whereas the escort cells do not ( Figure 3C ) [12] , [33] . In Lsd1ΔN mutants , however , we observed ectopic Engrailed protein expression in a limited number of escort cells , in addition to the terminal filament and cap cells , in 85 . 7% ( n = 91 ) of the germaria examined ( Figure 3D ) . These Engrailed expressing escort cells tended to be positioned immediately adjacent to the normal niche , although occasionally we observed Engrailed expressing escort cells several cell positions away from the cap cells ( Figure 3E ) . We cannot rule out the possibility that other cells also mis-expressed Engrailed , but at a level below our detection threshold . These data together suggest that Lsd1 serves to repress engrailed expression within a subpopulation of escort cells . To test the functional relevance of ectopic Engrailed expression in escort cells , we assayed whether disruption of engrailed function , either through RNAi knockdown or loss-of-function mutations , modified the Lsd1 mutant phenotype . Knockdown of engrailed in an Lsd1 RNAi background ( Figure 4A ) suppressed the expanded GSC-like cell Lsd1 mutant phenotype ( Figure 4B , E , F ) . Furthermore , three independent engrailed mutations also suppressed the Lsd1 RNAi-induced phenotype , so that the number of single cells with round fusomes decreased and cyst development within the germarium proceeded normally ( Figure 4C–F ) . In all cases , engrailed suppression of the Lsd1 RNAi phenotype resulted in the formation of morphologically normal ovarioles with maturing egg chambers . In Drosophila , Engrailed drives the expression of hedgehog ( hh ) , which in turn leads to the expression of dpp in adjacent cells [34]–[37] . Previous analysis showed an expansion of hh expression in Lsd1 mutant germaria [24] . To determine whether the mis-expression of hh in escort cells contributed to the Lsd1 mutant phenotype , we crossed both hh-specific UAS RNAi and hh mutant lines into a c587-gal4>UAS-Lsd1RNAi background . This analysis revealed that loss of hh function , similar to engrailed , suppressed the GSC-like expansion phenotype , resulting in the formation of germaria that exhibited normal germ cell differentiation ( Figure 4G–J ) . To assess whether mis-expression of engrailed and hh are sufficient to expand the number of stem cell-like cells in the germarium , we expressed transgenes corresponding to both genes within escort cells and early follicle cells using the c587-gal4 driver . Similar to the phenotype exhibited by Lsd1 mutants , ectopic expression of engrailed resulted in a stem cell-like cell expansion within 49 . 5% of germaria examined ( n = 111 ) . Many of these germline cells remained as single cells with round fusomes ( Figure 5A ) . However , mis-expression of engrailed did not completely block cyst development and many ovarioles from c587-gal4>UAS-engrailed females contained maturing egg chambers . In contrast to engrailed , over-expression of hh using two different transgenes did not obviously perturb early germ cell differentiation ( Figure 5G , H ) . However , the mis-expression of these transgenes did result in follicle cell defects , consistent with previously published results [38] . These results indicated that the hh transgene is active in these cells but that hh over-expression in the escort cells and early follicle cells is not sufficient to induce an expansion of GSC-like cells in germaria . Loss of Lsd1 results in expanded BMP signaling within the germline [24] . Based on the expansion of Engrailed expression in Lsd1 mutants and the similarities between the Lsd1 mutant and engrailed over-expression phenotypes , we reasoned that mis-expression of engrailed may also induce ectopic BMP signaling in the ovary . To test this , we used a Dad-lacZ enhancer trap as a positive transcriptional reporter of dpp signal transduction [9] , [39] . In control ovarioles , stem cells express high levels of Dad-LacZ , whereas the expression of this reporter sharply decreases in differentiating cysts ( Figure 5B ) . Upon engrailed mis-expression in the escort cells , the number of Dad-LacZ positive germline cells increases , likely reflecting expanded Dpp signaling ( Figure 5C ) . Next , we knocked down the expression of dpp in the presence of the engrailed transgene and found that disruption of dpp suppressed the engrailed over-expression phenotype ( Figure 5D–F ) . Together these results suggest that mis-expression of engrailed in Lsd1 mutants drives ectopic BMP signaling , resulting in the expanded GSC-like cell tumor phenotype . To test whether ectopic engrailed expression can specifically affect adult escort cells , we performed a temporally controlled over-expression experiment . c587-gal4>UAS-engrailed larvae were kept at low temperature to prevent robust expression of the engrailed transgene . Ovaries from adult females maintained at a low temperature did not display ectopic Engrailed expression or an expanded undifferentiated cell phenotype ( Figure 6A , A′ ) . However , shifting c587-gal4>UAS-engrailed females to a higher temperature after eclosion resulted in ectopic engrailed expression in escort cells and early follicle cells , and a concomitant expansion of germline stem cell-like cells ( Figure 6B–C ) . Thus , engrailed expression specifically in adults appears sufficient to induce ectopic BMP signaling in the anterior region of the germarium . Lsd1 associates with the promoters of many genes besides engrailed , some of which could potentially play a role in regulating escort cell function . To begin to characterize whether Lsd1 modulates the expression of other potential target genes , we stained c587-gal4 control and c587-gal4>UAS-Lsd1RNAi ovaries using available antibodies . Cap cells and escort cells exhibit a shared peak of Lsd1 binding near the Rho1 gene ( Table S11 , 12 ) . Previous results showed that loss of Rho1 results in escort cell defects and an expansion of GSC-like cells [3] . Knocking down Lsd1 levels did not appear to result in any dramatic change in Rho1 expression within the escort cells ( compare Figure 7A and 7D ) . Likewise , Lsd1 also exhibits enriched binding near Apc1 ( Tables S9 , S12 ) , a component of the Wnt signaling pathway . However antibody staining showed that Apc1 protein levels did not change to an appreciable degree upon knock-down of Lsd1 ( Figure 7B , E ) . In contrast , the product of a third potential Lsd1 target gene , Broad , exhibited increased expression in c587-gal4>UAS-Lsd1RNAi samples relative to controls ( Figure 7C , F ) . However , loss of broad did not appear to suppress the Lsd1 mutant phenotype ( data not shown ) . The raw gene functions in the developing gonad to regulate the morphology of somatic cells as they interact with primordial germ cells [40] , [41] . Lsd1 exhibits enriched binding just 3′ to the raw transcription termination site ( Figure 7G ) . Antibodies were not available to assay whether loss of Lsd1 caused a change in Raw expression levels but raw mutant and RNAi lines partially suppressed the Lsd1 phenotype ( Figure 7H–L ) . The raw134 . 47 allele weakly modified the GSC-like cell expansion phenotype exhibited by c587-gal4>UAS-Lsd1RNAi germaria , while both rawRNAi and a single copy of raw155 . 27 more strongly suppressed the c587-gal4>UAS-Lsd1RNAi phenotype , giving rise to a reduced number of germaria that carried more than 5 single cells with round fusomes . These genetic interactions suggest that mis-regulation of raw expression or activity also contributes to the Lsd1 mutant phenotype . Encouraged by the finding that disruption of raw suppressed the Lsd1 mutant phenotype , we crossed a number of additional knockdown lines , corresponding to other putative Lsd1 target genes , into the c587-gal4>UAS-Lsd1RNAi background . We counted the total number of single germ cells with round fusomes within individual germaria from the resulting ovaries . This analysis showed that knockdown of 7 out of the 34 genes tested suppressed the c587-gal4>UAS-Lsd1RNAi phenotype to the point where fewer than 50% of the assayed germaria contained greater than 5 single cells with round fusomes ( Figure 8A ) . This group included FK506-binding protein 1 ( FK506-bp1 ) , Glutamine:fructose-6-phosphate aminotransferase 1 ( Gfat1 ) , CG11779 , ken and barbie ( ken ) , Anaphase Promoting Complex subunit 7 ( APC7 ) , barren ( barr ) and Hepatocyte nuclear factor 4 ( Hnf4 ) . These genes have varied functions and play roles in cell cycle regulation ( APC7 and barr ) , juvenile hormone signaling ( FK506-bp1 ) , development of the genitalia ( ken ) and lipid metabolism ( Hnf4 ) . Lack of a clear functional link between these suppressors suggests that escort cells are particularly sensitive to perturbations in their gene expression programs . Together these data show that disruption of Lsd1 results in a complex phenotype , marked by increased BMP signaling in the germline and disruption of normal escort cell function , which likely involves the mis-expression of several direct and potentially indirect target genes ( Figure 8B ) .
We have found Lsd1 associates with a limited number of loci within two different cell populations . Lsd1 exhibits fairly broad peaks of binding , ranging in size from 166–262 bp based on the FindPeaks algorithm . MACs analysis calls even wider peaks ( Supplementary Tables S5 , S6 , S7 , S8 ) . The significance of the width of these peaks remains unclear but suggests that Lsd1 either does not associate with single sequence specific elements at these sites or exhibits a certain degree of spreading upon recruitment to a particular locus . In Drosophila escort cells , Lsd1 binds to over 100 sites spread throughout the genome . Lsd1 binds to fewer sites in cap cells . While some Lsd1 binding sites overlap in cap cells and escort cells , the relatively large number of different sites suggests that Lsd1 recruitment depends on multiple and perhaps distinct cell-specific co-factors . MEME analysis [42] , [43] reveals that many of the identified Lsd1 binding sites contain ACTGGAA elements . GGAA sequences are often present in the core binding sites of ETS transcription factors . The Drosophila genome encodes a number of ETS family members , none of which have been characterized in the somatic cells of the germarium . Determining the functional relevance of these specific GGAA sites within gene promoters and identifying the transcription factors that bind to them will require additional efforts . For technical reasons and to enable comparisons of Lsd1 binding between escort cells/early follicle cells and cap cells/terminal filament cells , we elected to express the Lsd1 HA-tagged transgenes in an otherwise wild-type background . We acknowledge the possibility that endogenous Lsd1 may outcompete the HA-tagged transgenes for binding at specific sites in the escort cells and early follicle cells . Therefore sites identified in this study may be an underrepresentation of the total number of sites bound by endogenous Lsd1 . Repeating the ChIP-seq analysis using material from rescued Lsd1ΔN females that express the HA-tagged Lsd1 transgene in escort cells and early follicle cells represents important work for the future . We found that Lsd1 mutant samples exhibit a 6-fold increase in engrailed transcript levels relative to controls . Curiously , ectopic Engrailed protein expression was only observed in a small number of escort cells . Perhaps additional post-transcription mechanisms regulate the translation of Engrailed , and potentially other proteins , inside and outside of the cap cell niche . Such mechanisms would allow these cells to fine-tune their signaling output more than what could be achieved through transcriptional based mechanisms alone . Results presented here also suggest that escort cells are not uniform in nature and perhaps have specific functions or capabilities depending on their lineage and where they reside within the germarium . MARCM analysis shows that the loss of Lsd1 in some but not all escort cells results in a marked expansion of GSC-like cells within the germarium . Previous studies have also suggested that specific escort cells have distinct roles in supporting GSCs [12] . Technical considerations aside , the severity of the Lsd1 null phenotype compared to the engrailed over-expression phenotype , both in terms of the penetrance and extent of the GSC expansion phenotype and the accompanying germline and somatic cell death , suggests that engrailed is not the only biologically relevant target of Lsd1 regulation in the escort cells . Based on expression analysis ( Figure 7 ) , Lsd1 regulates the expression of some but not all genes adjacent to its binding sites . Our genetic analysis suggests that mis-regulation of the putative target raw ( Figure 7 ) and several additional genes ( Figure 8 ) also contribute to the Lsd1 mutant phenotype . Characterizing the transcriptional profile of escort cells from wild-type and Lsd1 mutant samples , which will have to await for improvements in current cell isolation and RNA profiling techniques , will help to further resolve which genes are direct and indirect targets of Lsd1 regulation . Such approaches may also reveal additional genes that participate in niche formation and function . Of note , the observation that functionally diverse genes can suppress the Lsd1 mutant phenotype suggests that escort cells are acutely sensitive to changes in their gene expression programs . While our data support a model that loss of Lsd1 initially results in mis-regulation of engrailed and other genes that , in turn , drive GSC expansion , it is clear that many of the escort cells that experience reduced Lsd1 function retract their cellular extensions and undergo cell death . This loss of escort cells further exacerbates the GSC expansion phenotype . Given the phenotypic complexity described here and elsewhere [3] , care should be taken when analyzing gene function within the escort cell population . How niches maintain stem cells and adjust their signaling output to ensure tissue homeostasis remains a fundamental question in stem cell biology . Elegant work has shown that terminal filament cells , cap cells and escort cells help to support the self-renewal of two to three germline stem cells at the tip of Drosophila germaria [5] , [44] . The predominant signal emanating from the anterior tip of the germarium is Dpp , which acts locally to induce a canonical signal transduction cascade in GSCs , which in turn represses their differentiation [5] , [9] . Several expression and genetic studies strongly suggest that terminal filament and cap cells , and perhaps the most anterior escort cells , are the primary source Dpp ligand [5] , [9] . More recent work has suggested that Engrailed expression in cap cells non-autonomously promotes dpp expression in escort cells through a hedgehog dependent mechanism [12] . Loss of Lsd1 results in ectopic expansion of hh expression in escort cells [24] and data shown here ( Figure 4 ) reveals that disruption of hh partially suppresses the Lsd1 mutant phenotype . However , consistent with previous results [38] , over-expression of hh in escort cells does not result in an Lsd1-like mutant tumor phenotype ( Figure 5G , H ) , demonstrating that hh is not sufficient to induce ectopic BMP signaling in the germarium . Given these observations , ectopic engrailed expression in escort cells likely targets additional genes besides hh to induce ectopic BMP signaling and promote the expansion of undifferentiated germ cells . The finding that loss of Lsd1 or mis-expression of engrailed in adult escort cells leads to expanded Dpp signal transduction within germ cells throughout the anterior portion of the germarium indicates that subpopulations of escort cells are capable , and perhaps even poised , to express dpp under certain conditions . Such plasticity might allow the niche to expand and contract in response to various stimuli and environmental cues . Indeed , previous studies have shown that Jak/Stat and insulin signaling can influence the number of GSCs in the ovary [45]–[49] . Moreover , ongoing dynamic regulation of signaling may be a regular feature of niches under resting homeostatic conditions . The observation that long-term knock-down of dpp in escort cells results in a reduced number of GSCs at the tip of the germarium , but not their complete elimination , is consistent with the notion that escort cells contribute to the maintenance of GSCs in some manner [12] . Further work , with single-cell spatial and small-scale temporal resolution , will be needed to help clarify what cells express niche signals and when . Inappropriate and extensive expansion of niches would be predicted to upset tissue homeostasis and perhaps even result in pathological conditions . Therefore robust but flexible mechanisms that depend on chromatin factors such as Lsd1 may be in place to precisely control the expansion and contraction of in vivo stem cell niches . The continued study of Drosophila cap cells and escort cells will provide further insights into how chromatin programming regulates niche plasticity .
Drosophila stocks were maintained at room temperature on standard cornmeal-agar medium unless specified otherwise . The following fly strains were used in this study: w1118 was used as a control; Lsd1ΔN was provided by N . Dyson ( Massachusetts General Hospital Cancer Center , Charlestown , MA ) ; hh-gal4 and UAS-hh lines [50] were provided by J . Jiang ( University of Texas Southwestern , Dallas , TX ) ; c587-gal4 and Dad-LacZ were provided by A . Spradling ( Carnegie Institution for Science , Baltimore , MD ) ; the UAS-engrailed::GFP transgenic line was provided by Florence Maschat ( Institute of Human Genetics , France ) ; the raw134 . 47 and raw155 . 27 alleles were provided by Jennifer Mierisch ( Loyola University of Chicago ) ; en7 , en4 , enspt , UAS-mCD8::GFP , UAS-dppRNAi-1 ( BL#-31172 ) , UAS-dppRNAi-2 ( BL#-31530 ) , UAS-dppRNAi-3 ( BL#-31531 ) and UAS-rawRNAi ( BL#-31393 ) , UAS-enRNAi-1 ( BL#-33715 ) , UAS-enRNAi-2 ( BL#-26752 ) , UAS-hhRNAi ( BL#-31042 ) , hhAC ( BL#-1749 ) , hh2 ( BL#-3376 ) , broadnpr-3 ( BL#-29971 ) , broad5 ( BL#-29972 ) , par-1HMS00405 ( BL#- 32410 ) , NaPi-THMS00966 ( BL#- 34003 ) , CG17186JF02425 ( BL#- 27079 ) , CG12054HMJ03134 ( BL#- 50910 ) , Atg1HMS02750 ( BL#- 44034 ) , mudHMS01458 ( BL#- 35044 ) , CG12128HMS00960 ( BL#- 33997 ) , Nek2HM05088 ( BL#- 28600 ) , GstS1HM05063 ( BL#- 28885 ) , RhoGEF2HMS01118 ( BL#- 34643 ) , lwrHMS01648 ( BL#- 37506 ) , UGPHMJ03120 ( BL#- 50902 ) , Nmdar2HMS02176 ( BL#- 40928 ) , FdhHMS01268 ( BL#- 34937 ) , SpredHMS00637 ( BL#- 32852 ) , CG10949JF02129 ( BL#- 26231 ) , CG13192HMS01384 ( BL#- 34390 ) , LaspJF02075 ( BL#- 26305 ) , ApcHMS00188 ( BL#- 34869 ) , CycAGLV21059 ( BL#- 35694 ) , ari-1JF03352 ( BL#- 29416 ) , CG16989HMJ21141 ( BL#- 51017 ) , PezHMS00862 ( BL#- 33919 ) , AcCoASHMS02314 ( BL#- 41917 ) , Pdk1HMS01250 ( BL#- 34936 ) , LrchHMJ03119 ( BL#- 50901 ) , DabHMS02482 ( BL#- 42646 ) , FK506-bp1HMS00339 ( BL#- 32348 ) , Gfat1HMS02585 ( BL#- 42892 ) , CG11779GL01496 ( BL#- 43155 ) , kenHMS01219 ( BL#- 34739 ) , APC7GL01114 ( BL#- 38932 ) , barrHMS00049 ( BL#- 34068 ) and Hnf4JF02539 ( BL#- 29375 ) lines were obtained from the Bloomington Stock Center . UAS-Lsd1RNAi was obtained from the National Institute of Genetics , Japan . Lsd1 mutant MARCM clones were generated by crossing Lsd1ΔN FRT 2A to yw122 tub-gal4 UAS-GFP;;tub-gal80 FRT 2A/TM6B ( gift from Ben Ohlstein ) . The resulting larvae were heat-shocked twice a day at 37°C on days 5–7 after the cross was set . The resulting adult females were dissected and stained 7 days after they eclosed . The HA tagged transgenes of Lsd1 were created using Gateway Cloning ( Invitrogen ) . The open reading frame ( ORF ) of Lsd1 was cloned into modified pTHW and pPHW destination vectors ( http://emb . carnegiescience . edu/labs/murphy/Gateway%20vectors . html ) that contained φC31 attB sites [51]–[53] . These constructs were injected into flies and transformed using φC31 integrase into the 51D landing site on the 2nd chromosome . Adult ovaries were dissected in Grace's medium and fixed in 4% ( vol/vol ) formaldehyde for 10 min . The ovaries were washed with PBT ( 1X PBS , 0 . 5% BSA , and 0 . 3% Triton-X 100 ) and stained with primary antibody overnight at 4°C . The ovaries were washed and incubated in secondary antibody at room temperature for 5 hrs . Ovaries were then washed again and mounted in Vectashield containing DAPI ( Vector Laboratories ) . The following primary antibodies were used: mouse anti-Hts ( 1B1 ) ( 1∶20 ) , mouse anti-Engrailed ( 4D9 ) ( 1∶2 ) , mouse anti-Broad-core ( 25E9 . D7 ) ( 1∶10 ) , mouse anti-Rho1 ( P1D9 ) ( 1∶50 ) and rat anti-VASA ( 1∶20 ) ( Developmental Studies Hybridoma Bank ) , mouse anti-β-galactosidase ( 1∶200 ) ( Promega ) , rabbit anti-APC1 [54] ( 1∶1000 ) ( gift of E . Wieschaus ) , Rabbit anti-α-Spectrin [55] ( 1∶1000 ) ( gift from Ron Dubreuil ) , rabbit anti-GFP ( 1∶1000 ) ( Molecular Probes ) , rat anti-HA 3F10 ( Roche ) and rabbit anti-cleaved Caspase-3 ( 1∶250 ) ( Cell Signaling Technology ) . Fluorescence-conjugated secondary antibodies ( Jackson Laboratories ) were used at a dilution of 1∶200 . RNA was isolated from bamΔ86 and Lsd1ΔN bamΔ86 mutant ovaries using TRIzol ( Invitrogen ) . The RNA was treated with DNase and subjected to RT-qPCR reaction using the Superscript III First-Strand Synthesis SuperMix ( Invitrogen ) . The primers used to amplify engrailed mRNA are as follows: engrailed forward: 5′ - GCCCGCCTGGGTGTACTG engrailed reverse: 5′ - CGCTTCTCGTCGTTGGTCTTG We used 1000 pairs of ovaries for each ChIP-seq reaction . Every 200 pairs of ovaries were dissected , fixed , washed and frozen immediately at −80°C . The entire protocol was done at 4°C unless otherwise indicated . The ovaries were dissected and fixed in 1 ml of 1% formaldehyde at room temperature for 10 mins . The crosslinking was stopped by the addition of 100 ml 1 . 25M glycine solution . The ovaries were washed three times with 1X cold PBS buffer and then sonicated in 500 µl ChIP Sonication Buffer ( 1%Triton X-100 , 0 . 1% Deoxycholate , 50 mM Tris 8 . 1 , 150 mM NaCl , 5 mM EDTA ) on ice to achieve a final DNA length of 100 to 600 base pairs . The sample was centrifuged at maximum speed at 4°C to remove cell debris . The supernatant was transferred to a new tube and the sonicated sample was then blocked by adding Protein G agarose beads and incubating at 4°C for one hour . The beads were removed . 1% of the sample was kept aside as INPUT and to the remaining sample 3 ug rabbit-HA antibody ( Abcam ) was added and incubated overnight at 4°C . The next day protein agarose G beads were added and incubated for 3 hours at 4°C . The beads was then washed well with ChIP Sonication Buffer ( two times ) , High Salt Wash Buffer ( 1% Triton X-100 , 0 . 1% Deoxycholate , 50 mM Tris 8 . 1 , 500 mM NaCl , 5 mM EDTA ) ( three times ) , LiCl Immune Complex Wash Buffer ( two times ) and TE buffer . The protein bound to the beads was eluted using 500 µl Elution Buffer ( 1% SDS , 0 . 1M NaHCO3 ) . The elution buffer was added to the INPUT samples and they were treated the same as the IP samples from this point . 20 µl of 5M NaCl was added to 500 µl of elution buffer and incubated at 65°C overnight . The third day , the sample was treated with RNase A , Proteinase K and the DNA isolated using Qiagen PCR Purification kit . Subsequent library construction and sequencing of the input and immunoprecipitated DNA were conducted by the UT Southwestern McDermott Sequencing Center . The primary sequencing data was mapped to the fly reference genome dm3 using BioScope ( 1 . 2 . 1 ) . During the alignment , three filter steps were applied to remove low quality , ambiguous and redundant reads . HA-Lsd1 binding regions were identified as genomic regions with a significant read enrichment and binding peak profile in the ChIP reads over the input reads using the FindPeaks module in the Homer software tool [56] with 10% false discovery rate ( FDR ) . ChIP enrichment at important genome features such as specific chromosomes , promoters , downstream , exonic , intronic and distal intergenic regions was statistically analyzed with the Cis-regulatory Element Annotation System ( CEAS ) [57] . De novo motif discovery analysis for HA-Lsd1 binding regions was performed with the Multiple EM for motif elicitation ( MEME ) software tool [42] , [43] . High quality motifs were aligned against transcription factor motifs retrieved from JASPAR [58] and TRANSFAC [59] using the TOMTOM software tool [42] to identify known transcription factor motifs that match the MEME predicted motifs . Potential protein-coding target genes associated with the identified HA-Lsd1 binding regions were identified based on the distance of their transcription start sites ( TSSs ) according to their RefSeq annotation in the dm3 assembly to binding peak summits . Genes with TSSs within 5 kb or nearest to an HA-Lsd peak summit were called as target genes . ChIP-Seq data has been deposited with NCBI GEO ( http://www . ncbi . nlm . nih . gov/geo ) under the accession code GSE54376 .
|
The mechanisms that govern the formation , size and signaling output of in vivo niches remain poorly understood . Studies of Drosophila germline stem cells ( GSCs ) have suggested that chromatin programming greatly influences the behavior of these cells and their progeny . Previous work has shown that loss of the highly conserved histone demethylase Lsd1 results in ectopic niche signaling and an expanded GSC phenotype . To determine direct regulatory targets of Lsd1 , we employed chromatin immunoprecipitation coupled with massive parallel sequencing ( ChIP-seq ) using specific cell populations inside and outside of the GSC niche . These experiments revealed that Lsd1 exhibits highly enriched binding to over one hundred genomic sites within a specific cell population . Furthermore , mis-regulation of some of these direct targets contributes to the expanded stem cell phenotype observed in Lsd1 mutants . These results provide insights into how Lsd1 directly restricts the size of the GSC microenvironment and establish a platform for understanding and exploring chromatin programming inside and outside an in vivo stem cell niche .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"cell",
"fate",
"determination",
"model",
"organisms",
"stem",
"cells",
"molecular",
"development",
"gene",
"expression",
"genetics",
"epigenetics",
"biology",
"cell",
"differentiation"
] |
2014
|
Lsd1 Restricts the Number of Germline Stem Cells by Regulating Multiple Targets in Escort Cells
|
Coral snakes of the genus Micrurus have a high diversity and wide distribution in the Americas . Despite envenomings by these animals being uncommon , accidents are often severe and may result in death . Producing an antivenom to treat these envenomings has been challenging since coral snakes are difficult to catch , produce small amounts of venom , and the antivenoms produced have shown limited cross neutralization . Here we present data of cross neutralization among monovalent antivenoms raised against M . dumerilii , M . isozonus , M . mipartitus and M . surinamensis and the development of a new polyvalent coral snake antivenom , resulting from the mix of monovalent antivenoms . Our results , show that this coral snake antivenom has high neutralizing potency and wide taxonomic coverage , constituting a possible alternative for a long sought Pan-American coral snake antivenom .
Coral snakes of the genus Micrurus and Micruroides represent a highly diverse neotropical monophyletic assembly of about 80 species distributed from the southern United States to northern Argentina [1] . Although uncommon ( 1–2% of the snake bites in the Americas ) [2–4] , Micrurus envenomation can be lethal due to the presence of potent toxic factors , mainly neurotoxins , causing peripheral paralysis resulting in respiratory failure [5] . The neurotoxic activity of coral snake venoms is mainly due to the presence of non-enzymatic competitive inhibitors of acetylcholine receptors at the neuromuscular junction known as α-neurotoxins of the three-finger ( 3FTx ) protein superfamily and phospholipase A2 ( PLA2 ) enzymes with pre-synaptic activity [5] . These two components have been revealed as the most abundant components in Micrurus venoms and vary in their proportion according to the species [5 , 6] . Snake antivenom production takes several stages and therefore considerable amounts of venom , in order to guarantee the quality of the medicament [7–10] . First , the toxicity of the venoms used for immunization must be determined ( e . g . median lethal dose ) , then , animals ( i . e . horses , goats ) are inoculated with non-lethal doses of venom to produce a hyperimmune serum and subsequently , potency trials ( e . g . median effective dose ) must be carried out at different times in order to test the efficacy and stability of the product [9 , 10] . Micrurus snakes have relatively small sizes , which results in low venom yields , are difficult to find in the field and to maintain in captivity for extended periods of time . These aspects constitute serious setbacks for gathering sufficient amounts of venom for the production of coral snake antivenoms [11] . Antivenoms capable of neutralizing the toxic activities of a large range of heterologous Micrurus venoms have been long sought . Initially , as a mean to use antivenoms derived from snakes capable of yielding large amounts of venom against the toxic activities of snakes considered a public health threat but yielding very low amounts of venom per individual [12 , 13] . Later , as a way to produce antivenoms capable of neutralizing the lethal activities of a wide range of coral snake venoms that could be used in the Americas [8] . However , although antibody cross-reactivity has been widely observed between monovalent antisera and heterologous Micrurus venoms , in many cases resulting the ability of the antivenom to neutralize the lethal activity of the heterologous venom [14–16] , in a number of cases and despite cross-reactivity , antivenoms are unable to neutralize the lethal effect of heterologous venoms [8 , 15 , 17 , 18] . In the Americas , anti-coral snake antivenoms are produced by the Instituto Nacional de Producción de Biolo’gicos ( ANLIS ) “Dr Carlos Malbrán” in Argentina , the Clodomiro Picado Institute ( ICP ) in Costa Rica , the Butantan Institute in Brazil , Instituto Bioclon in Mexico [19] and Laboratorios Probiol in Colombia [20] . However , while the antivenoms produced in Central America can neutralize the lethal activities of M . nigrocinctus , M . mosquitensis , M . dumerilii , M . fulvius , M . clarki , M . alleni and M . tener , they are unable to neutralize the lethal activities of M . mipartitus , M . surinamensis , M . spixii and M . pyrrhocryptus [21–24] . Likewise , those produced in South America , while able to neutralize the lethal activities of M . frontalis , M . corallinus , M . pyrrhocryptus , M . fulvius , M . nigrocinctus and M . surinamensis , are unable to neutralize the lethal activities of M . altirostris , M . ibiboboca , M . lemniscatus and M . spixii [25–27] . Based on the large extent of cross-reactivity between elapidic antivenoms and elapidic heterologous venoms and the cross neutralization of the lethal activity of a Notechis scutatus antivenom against the lethal activity of the M . fulvius venom [28] , polyvalent anti-elapidic antivenoms have thus been considered as an alternative for the long sought development of a Pan-American anti-coral snake antivenom . In fact , a pentavalent anti-elapidic antivenom developed by CSL Limited in Australia using as antigens Notechis scutatus , Pseudechis australis , Pseudonaja textilis , Acanthophis antarcticus and Oxyuranus scutelatus venoms has been shown to neutralize the lethal activities of M . corallinus , M . frontalis , M . fulvius , M . nigrocinctus and M . pyrrhocryptus [29] . Here we report the production of a horse polyvalent anti-coral ( Micrurus ) snake antivenom derived from the mixing of monovalent antivenoms against M . dumerilii , M . mipartitus , M . isozonus and M . surinamensis venoms . The polyvalent antivenom is capable of neutralizing the lethal activity of M . dumerilii , M . mipartitus , M . isozonus , M . surinamensis , M . medemi , M . lemniscatus and M . spixii venoms thus constituting a promising Pan-American anti-coral antivenom .
The lyophilized venoms were obtained from the venom bank at the Instituto Nacional de Salud ( INS ) de Colombia , Bogotá . Venoms were kept frozen at -40°C . Species included in the study were chosen based on venom availability and inclusion on different Micrurus phyletic lineages [30 , 31]: M . mipartitus ( Middle Magdalena Valley–MMV ) of the bicolored group; M . dumerilii ( MMV ) , M . medemi ( Orinoco Basin—OB ) from the monadal group and M . isozonus ( OB ) , M . lemniscatus ( OB ) , M . surinamensis ( OB ) of the triadal group ( Fig 1 ) . All venoms used were obtained from Colombian specimens . Eight mixed breed horses were used with weights between 325–370 kg and between four to six years old . Horses were kept in the open , in pasture enclosures in a farm of the INS in Bojacá , Cundinamarca , Colombia , under veterinary care . Horses were vaccinated against tetanus and equine influenza , dewormed for gut helminths and washed to remove potential external parasites . Hematological , hepatic and kidney health was tested every six months and only horses with healthy organs until the last inspection were used for immunization . Mice CD-1 ICR strain , of 16–20 g , were obtained from the animal facility at the INS , Bogotá . Experiments followed ethical procedures established in the protocols for animal experimentation at the INS ( INT-R04 . 0000 . 01 ) and by the World Health Organization [9 , 10] . Animal experimentation was approved by the Institutional Committee for Animal Use and Care at the National Health Institute ( Comité Institucional para el Cuidado y Uso de los Animales en el Instituto Nacional de Salud -CICUAL-INS ) , resolution 0052 of 2018 . Hyperimmune horse sera was obtained following the World Health Organization ( WHO ) guidelines [9 , 10] and the internal immunization protocol defined by the INS . In order to evaluate the immunogenicity of individual venoms and the capacity of individual antisera to cross neutralize heterologous venoms , experimental monospecific antivenoms were produced with the venom of four Micrurus species: M . dumerilii , M . isozonus , M . mipartitus and M . surinamensis . For each species venom , two horses were used . The immunization scheme for each horse lasted for up to three months , with injections administered every 5 to 15 days . For the first immunization , the venom was dissolved in Freund’s adjuvant ( Becton Dickinson ) , whereas the remaining ones were dissolved in saline solution 0 . 85% ( SS ) . Each injection had a volume between 0 . 5–5 mL , with 15–20 mg of venom , depending on the venom´s toxicity . Once the immunization scheme was completed , animals were bled to test whether there were quantifiable titers following neutralization procedures ( see below ) . When appropriate antivenom neutralization titers were attained ( ≥3 LD50 ) , horses were bled through puncture in the jugular vein . Up to eight liters of blood were collected in sterile plastic bags with anticoagulant , and plasma separation from cells was made by gravity . Cells were subsequently reinjected back into the horses for a better and faster recovery . Plasma was subsequently purified by means of precipitation with ammonium sulfate and sterilizing filtration , in order to obtain the concentrated antivenom immunoglobulin solution and stored at 2–8°C [32] . Polyvalent antivenom was produced by mixing of monovalent antivenoms and diluted to reach neutralization titers of 0 . 3 mg/mL of M . dumerilii and M . surinamensis , 0 . 8 mg/mL of M . mipartitus and 2 mg/mL of M . isozonus . This antivenom corresponds to the "Antiveneno Anticoral Polivalente" , produced by the Instituto Nacional de Salud ( INS ) , batch number 15AMP01 , with expiration date of March of 2018 . Protein concentration was determined by the Kjeldahl method [10 , 33] , following standardized protocol INS ( MEN-R04 . 6020–010 ) . Values correspond to grams per 100 mL and are expressed as percentage .
Protein content for antivenoms were 10 . 8% for anti-dumerilii , 8 . 2% for anti-mipartitus , 9 . 3% for anti-isozonus , 9 . 4% for anti-surinamensis and 8 . 1% for the polyvalent . Venoms derived from the seven species studied showed a wide variation in lethality . Venom from M . mipartitus showed the lowest lethality ( 1 . 87 μg/g ) , whereas M . isozonus ( 0 . 35 μg/g ) venom displayed the highest one ( Table 1 ) . Monovalent antivenoms showed appropriate neutralization titers against homologous venoms . M . dumerilii and M . isozonus showed the lowest and highest titers , respectively ( Table 2 ) . The anti-dumerilii antivenom neutralized the lethality of M . isozonus and M . mipartitus venoms , with higher titers than those against the homologous venom , but with low titers against M . surinamensis venom . Anti-mipartitus antivenom showed low neutralization activity against M . dumerilii and moderate against M . isozonus and M . surinamensis venoms . The anti-isozonus antivenom displayed low neutralization titers against M . dumerilii , moderated against M . surinamensis and high against M . mipartitus venoms . Finally , the anti-surinamensis antivenom showed low neutralization capability against all heterologous venoms . The antivenom showed a high capacity of neutralizing the effect of both homologous and heterologous venoms ( Table 2 ) . Neutralization capacity against homologous venoms , was lowest against M . surinamensis , and highest against M . isozonus . The antivenom was able to neutralize the lethal effects of heterologous venoms derived from M . spixii ( 1 . 58 mg/mL ) , M . lemniscatus ( 0 . 58 mg/mL ) and M . medemi ( 0 . 68 mg/mL ) . Surprisingly , its neutralization titers against the heterologous venoms tested were higher than the titers against the homologous venoms derived from M . dumerilii and M . surinamensis . Noteworthy , the neutralization titer against the M . spixii venom was the second highest ( Table 2 ) .
Protein content of some of the monovalent antivenoms surpass the upper limit of 10% recommended by WHO [10] ( e . g . anti-dumerilii 10 . 8% ) . Nevertheless , the polyvalent antivenom used as therapy , has a protein content below this limit ( 8 . 1% ) . This value is higher than the 5 . 5% reported for the antivenom produced by the Instituto Nacional de Producción de Biológicos , Argentina and 4% reported for the Coralmyn , Bioclon , Mexico[26] . Such differences in protein content might be associated to the polyvalence of the antivenom and to the relatively high neutralization titers . It is believed that high protein concentration might increase the probability of adverse reactions [10] . Additionally , the relatively high neutralization titers compensate for this , since less medicament is required , therefore diminishing the total amount of protein administered to the patient . Our results show a wide variation within the seven venoms tested and important differences as compared with the LD50 values found for the same species in other studies ( Table 1 ) . Estimations of the LD50 for the venom of a given species varied within studies , to the extent that the maximum value was almost 12 times the value of the minimum measurement ( i . e . M . surinamensis; Table 1 ) . It is difficult to explain the amount of variability within a species , given the number of variables that may influence the final results . Methods to estimate LD50 values vary according to several factors: mice weight and strain , volume of administration , venom treatment ( e . g . dried vs lyophilized ) , inoculation route ( e . g . intravenous vs intraperitoneal ) , etc . All these variables have proven to influence the final results [43] . On the other hand , differences in venom lethality may be the result of geographical variation [5] . For example , the venoms of M . dumerilii in this and other studies come from the middle Magdalena River Valley region of Colombia and LD50 are relatively similar among studies ( Table 1 ) . In the case of M . surinamensis , where LD50 varied widely , venoms originated from specimens captured over a large geographical distribution in the Orinoco and Amazonas basins [26 , 37 , 38] . Different regions may differ in many aspects ( e . g . climate , geography ) that may influence venom quality . Moreover , results by the same authors [26 , 41] for M . surinamensis from the same region , apparently using the same methodology , reached different results ( Table 1 ) . Therefore , at this point , conclusions regarding what is influencing differences in venom lethality may be hasty . Future efforts should be made to standardize procedures among laboratories in order to get comparable results . As shown here , previous works found that monovalent antivenoms neutralize the lethal effects of homologous venoms [8 , 13 , 14 , 44] ( Table 2 ) . All monovalent antivenoms described in this study showed some degree of cross neutralization . Likewise , Cohen and collaborators [13 , 14] , produced experimental monovalent antivenoms in rabbits by immunization with the venom of M . dumerilii , reaching high titers when neutralizing the homologous venom and moderate titers against two ( M . fulvius and M . spixii ) out of the seven venoms studied . In our trials , all monovalent antivenoms showed low neutralization titers against the lethal effect of M . dumerilii venom , contrary to other reports showing that this venom was neutralized by three ( M . frontalis , M . fulvius , M . nigrocinctus ) out of the four heterologous monovalent antivenoms tested [13 , 14] . On the other hand , the anti-surinamensis serum , as reported by several studies , showed low cross-neutralization [44] . Herein , we tested for the first time the neutralization capability of M . mipartitus and M . isozonus monovalent antivenoms: the first only showed high cross neutralization titers against M . isozonus and the second only against M . mipartitus ( Table 2 ) . It should be noted that Cohen and collaborators [14] tested the anti-dumerilii antivenom against the venom of a subspecies called M . mipartitus hertwigii , but this taxon is currently recognized as M . multifasciatus [45] . Our results show that cross neutralization does not operate in both directions . As stated before , anti-dumerilii antivenom showed high titers against M . mipartitus and M . isozonus , but low titers were recovered from anti-isozonus antivenom against M . dumerilii venom ( Table 2 ) . This observation is not new , other works using monovalent antivenom have found similar results [8 , 13 , 14 , 44] . This is an important fact that must be accounted for when designing antivenoms or eventually , when choosing antivenoms for envenomation treatments . For example , the antivenom produced in Costa Rica , which is produced using M . nigrocinctus venom as an antigen , neutralizes the lethality of M . dumerilii [23] , one of the coral snakes involved in a large proportion of coral snake bite accidents in Colombia but the anti-dumerilii monovalent antivenom does not neutralize the activities of the M . nigrocintus venom [14] . Our data shows that the INS coral antivenom has good direct and cross neutralization titers ( Tables 2 and 3 ) . Particularly , the neutralization titers against all the heterologous venoms were higher than those against the homologous M . dumerilii and M . surinamensis venoms , as measured by either the amount of venom or the number of neutralized LD50s . Currently available Latin American coral snake antivenoms have shown different neutralization capabilities . The Brazilian , Instituto Butantan ( raised against M . corallinus and M . frontalis ) , has proven to properly neutralize the venom of five species , but was ineffective against five [16 , 29 , 44 , 46] . Costa Rican monovalent antivenom ( antiM . nigrocinctus ) , produced by Instituto Clodomiro Picado , has shown to be efficient against five species but unable to neutralize the venom of other two [21–24 , 47 , 48] . Mexican Coralmyn monovalent antivenom ( against M . nigrocinctus ) , manufactured by Bioclon Laboratory , neutralizes the venom of three species , but is ineffective against four [25–27] . Finally , the monovalent Argentinian antivenom ( raised against M . pyrrhocryptus ) produced by Instituto Nacional de Productos Biológicos , has been shown to neutralize the venom of four species , but unable to neutralize the venom of other two [26] . The INS antivenom presented herein has wide neutralization capability against seven species . Further neutralization experiments against a wide range of Micrurus venoms are highly desirable . The different neutralization range between the INS antivenom and other Latin American antivenoms is likely associated to the fact that most Micrurus antivenoms are mono or bivalent , whereas the INS is a mixture of antibodies raised against four phylogenetically different species . An early experimental polyvalent antivenom produced by Bolaños et al . [37] showed somehow similar results . This antivenom was raised against venoms derived from M . pyrrhocryptus ( referred as M . frontalis pyrrhocryptus ) , M . multifasciatus ( referred as M . mipartitus hertwigi ) and M . nigrocinctus; and was able to neutralize the lethal effect of homologous and heterologous venoms ( M . fulvius , M . dumerilii , M . frontalis , M . corallinus , M . spixii , M . mipartitus , M . alleni and M . lemniscatus . However , it was unable to neutralize the venom from M . surinamensis . Contrarily , an experimental polyvalent antivenom produced by Tanaka et al . [44] , as a mixture of monovalent antivenoms raised against M . spixii , M . frontalis , M . corallinus , M . altirostris and M . lemniscatus , showed limited neutralizing efficacy . Antivenoms from Brazil , Costa Rica and Mexico have not included the venom of M . surinamensis in their immunization schemes , and have very low or no neutralization capacity against this venom . The antivenom we developed includes the venom of this species in the immunization scheme , and displays high neutralization titers against the lethal effects of the M . surinamensis venom ( Table 3 ) . Given the particularities of this venom and the inability of heterologous antivenoms to neutralize M . surinamensis venom , the inclusion of venom derived from this species as an immunogen is important in the production of antivenoms in countries where this species occur , such as Brazil , Ecuador , Peru and Venezuela , in order to provide proper therapeutic alternatives [49] . Surprisingly , the commercial monovalent antivenom produced in Argentina , raised against M . pyrrhocryptus , proved to be effective against this species , which is another therapeutic alternative for this difficult to neutralize species venom ( Table 3 ) [26] . Another antivenom that apparently neutralizes the venom of M . surinamensis is the one produced by Probiol [20] . This antivenom , derived from the immunization with M . lemniscatus , M . spixii and M . surinamensis venoms , claims to neutralize the venoms from M . mipartitus , M . surinamensis , M . dumerilii , M . medemi and M . spixii [20] . Nevertheless , the titers of neutralization are not known and no information is provided for the neutralization capacity against the homologous venom from M . lemniscatus . When comparing the INS antivenom neutralization capacity against the species tested with other antivenoms , INS antivenom showed higher titers with respect to both the amount of venom and the number of median lethal doses neutralized , except for M . surinamensis which is more efficiently neutralized by the antivenom from the Instituto Nacional de Producción de Biológicos , Argentina . ( Table 3 ) . All studies here compared appraised the neutralization ability of antivenoms against three LD50 , except for Tanaka et al . [16 , 44] , that challenged against two , which might imply that Butantan’s antivenom might have lower neutralization capability . Additionally , our results proved that the INS antivenom neutralizes with high efficacy the lethality of a broad range of Micrurus species venoms ( Table 3 ) . These properties are desirable in the clinical practice . First , because with such titers , less amounts ( volume and protein ) of medicament are needed and the probability of adverse reactions reduces . Second , because a wide taxonomic coverage is always desired , since most of the time there is no appropriate identification of the species causing the accidents . Comparisons among the neutralization capabilities of antivenoms , as for LD50 toxicity measurements , is difficult . Trials among studies vary widely in methodological aspects like the strain of mice , weight , challenging doses ( i . e . from 2–5 LD50 ) , value determination method ( e . g . Spearman-Kärber , Probits ) or route of injection ( e . g . intraperitoneal vs . intravenous ) . Nevertheless , even if neutralization values vary , the fact that the tested antivenoms are or are not able to neutralize the studied venoms is hardly obscured . The outcomes of this study show that INS antivenom is the best therapeutic alternative to treat coral snake envenomation in Colombia . Furthermore , this antivenom is the closest version of a long sought Pan-American anti-coral snake antivenom . Because most of the coral snake species whose venoms are neutralized by this antivenom are present in other south American countries , where no coral snake antivenom is produced , like Ecuador , Peru and Venezuela [50 , 51] , or even Brazil , where the antivenom produced has a restricted efficacy for some species [16 , 44] , this antivenom represent a treatment alternative for coral snake envenomation . Additionally , this antivenom might work in North America , given that cross neutralization of anti-M . dumerilii antivenom against M . fulvius venom has been reported [13 , 14] . On the other hand , the ability to neutralize the venom of Central American species remains to be proven , since only anti-dumerilii antivenom have been tested against M . nigrocinctus venom with negative results [14] . As aforementioned , the design of coral snake antivenoms has been hampered by low venom yields and unpredictable cross neutralization . Production of monovalent experimental antivenoms , evaluation of cross neutralization capacity and finally mixing of appropriate monovalent antivenoms to the desired neutralization titers is an effective approach for the production of polyvalent antivenoms . This way , producers might maximize limited resources ( venom ) while gaining knowledge on venom immunogenicity and sera cross reactivity . Despite our promising results , various aspects must be accounted for . Around eighty species of Micrurus occur in the Americas , of which close to 30 occur in Colombia . We have tested the neutralization capacity against the venoms of only seven species . Even if those are the ones more often involved in accidents , there is a substantial number of questions that require our understanding . Examples of this are the spectrum of neutralization of this antivenom , the neutralization capacity against independent activities , such as neurotoxicity and myotoxicity and the best formulation of venom combinations required to produce an antivenom with high and broad neutralization capacities . An understanding of these aspects might also come from clinical results . Finally , this warrant large collaborative efforts to standardize neutralizations tests for comparative purposes and test anti-coral snake antivenoms produced in the Americas against a large number of Micrurus venoms .
|
Coral snakes are distributed in the Americas form Southern United States to Argentina . These snakes cause envenomings that , despite not being common , often lead to death . The antivenoms currently produced to treat accidents caused by these snakes have limitations regarding the number of species venoms they could neutralize . Here , we present an antivenom with a wide spectrum of neutralization , when compared to other Anticoral antivenoms . Nevertheless , more studies are still necessary to evaluate its neutralization capacity against the venoms of other species . This antivenom has great potential , as it neutralizes the lethal effects of some of the most common Micrurus species in the Americas .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"toxins",
"immune",
"physiology",
"pathology",
"and",
"laboratory",
"medicine",
"immunology",
"tropical",
"diseases",
"vertebrates",
"animals",
"mammals",
"toxicology",
"toxic",
"agents",
"toxicity",
"routes",
"of",
"administration",
"reptiles",
"neglected",
"tropical",
"diseases",
"pharmacology",
"antibodies",
"cross",
"reactivity",
"snakebite",
"venoms",
"immune",
"system",
"proteins",
"proteins",
"snakes",
"biochemistry",
"eukaryota",
"intraperitoneal",
"injections",
"squamates",
"horses",
"physiology",
"biology",
"and",
"life",
"sciences",
"equines",
"amniotes",
"organisms"
] |
2019
|
A polyvalent coral snake antivenom with broad neutralization capacity
|
Cerebral malaria , a major cause of death during malaria infection , is characterised by the sequestration of infected red blood cells ( IRBC ) in brain microvessels . Most of the molecules implicated in the adhesion of IRBC on endothelial cells ( EC ) are already described; however , the structure of the IRBC/EC junction and the impact of this adhesion on the EC are poorly understood . We analysed this interaction using human brain microvascular EC monolayers co-cultured with IRBC . Our study demonstrates the transfer of material from the IRBC to the brain EC plasma membrane in a trogocytosis-like process , followed by a TNF-enhanced IRBC engulfing process . Upon IRBC/EC binding , parasite antigens are transferred to early endosomes in the EC , in a cytoskeleton-dependent process . This is associated with the opening of the intercellular junctions . The transfer of IRBC antigens can thus transform EC into a target for the immune response and contribute to the profound EC alterations , including peri-vascular oedema , associated with cerebral malaria .
Each year 3 . 2 billion people worldwide are exposed to the threat of malaria , resulting in around 2 million deaths [1] . Even with the best antiparasitic treatments , patients with cerebral malaria ( CM ) have no significant improvement in their prognosis , with an average fatality rate of 30 to 50% [1] . This outcome is due to a neurovascular pathology characterised by the accumulation of both infected red blood cells ( IRBC ) and host cells ( leucocytes and platelets ) in deep brain microvessels , leading to microcirculation impairment [2] . Leakage of the blood-brain-barrier and local arrest of leucocytes is associated with cytoadhesion of IRBC and microcirculation impairment , increased blood volume due to sequestration , and increased blood flow resulting from seizures and anaemia [2] . Cytokines and parasite toxins have also been shown to cause direct damage to the blood-brain barrier [3] , [4] . On the whole , severe increased intracranial pressure [2] and brain oedema [5] are associated with poor outcome for patients with CM . Of note however , the sequestration of IRBC in deep vessels is a normal step in the life cycle of the Plasmodium parasite and does not always trigger severe disease . Most of the molecules implicated in the adhesion of IRBC on EC have previously been described . They involve a series of endothelial molecules and parasite membrane proteins such as PfEMP1 and RIFINS [6] . This cytoadhesion helps the parasite avoid splenic clearance and favours its development in a low oxygen pressure microenvironment . Specific localisation of the parasites in the brain seems to be a complex feature involving both expression of human adhesion molecule isoforms and parasitic var proteins polymorphism [7] . However , the fine mechanisms of microvascular endothelial cell alterations are not yet fully understood . Cellular interactions in microvessels have mostly been described in the context of transmigration of cells through the endothelial layer . Such transmigration occurs through either openings between adjacent endothelial cells or through a single endothelial cell , mainly when leukocytes migrate to tissues or during the diffusion of metastatic cells . This is a stepwise process involving rolling , adhesion , firm adhesion , and finally diapedesis . The formation of a docking structure or “transmigratory cup” was recently described and involves several endothelial adhesion and signalling molecules [8]–[10] . Human lymphocytes use another process and palpate the surface of EC with podosomes before forming transcellular pores through the endothelium [11] . Yet another mechanism of cell-cell interaction , named trogocytosis , was more recently described in mice and human immune cells , but not in EC . Trogocytosis involves the transfer of membrane compounds during short term cell interactions [12]–[13] , and is defined as the uptake of membrane fragments and associated molecules from one cell to another . Moreover cell interaction by any of the above mechanisms can activate EC . Therefore , it is essential to understand the binding mechanism and the repercussions of the IRBC adhesion on EC in order to develop new preventive or therapeutic interventions for the treatment of cerebral malaria treatment . The present study demonstrates , that IRBC undergo close association with EC in a manner reminiscent of both trogocytosis and transmigration . In this in vitro system , adhesion and transfer of material involved 10 to 20% of the IRBC in contact with the EC . This process involves engagement of ICAM-1 , or other EC adhesion molecules , in the binding of IRBC . It triggers transfer of membrane material and malaria antigens from the IRBC to the brain EC in a trogocytosis-like manner and in a second step the development of a transmigration cup-like structure , which results in EC activation and opening of the intercellular junctions .
Upon incubation with human brain EC ( HBEC 5i and hCMEC/D3 lines ) , IRBC bound tightly onto the endothelial surface . To study the transfer of IRBC constituents to EC we fluorescently-labelled both the IRBC membrane , using the membrane-intercalating agents PKH26 or PKH67 , and the cytoplasm , using calcein-AM . We then followed IRBC material transfer by confocal microscopy and estimated the amount of fluorescence incorporated into the EC . As seen in Fig . 1 , after 30 min , IRBC were seen attached to hCMEC/D3 , with a halo-like diffusion from the IRBC PKH-labelled elements present on the HBEC surface around the area of attachment of IRBC ( Fig . 1A–C ) . This process was enhanced after one hour of co-incubation , with a pattern of dense punctuate patches visible on the HBEC surface after 90 min ( Fig . 1D ) . , After 3 h the fluorescent dye had migrated into the HBEC away from the original IRBC attachment point ( Fig . 1E ) . The labelled elements transferred from IRBC were detected on the HBEC surface up to 24 h after their co-incubation , even if the IRBC had been removed from the culture at 3 h post-incubation . On the other hand , calcein remained localised within the IRBC for up to 1 h after incubation with HBEC ( Fig . 1D ) . Calcein-labelled IRBC could still be detected as globular shapes on the HBEC , after 90 min of co-culture . However , after 3 h of incubation , the green dye was detectable in the HBEC far from the IRBC docking area ( Fig . 1E ) . Time-dependent transfer of PKH67 dye to HBEC was quantified by the amount of fluorescence present in HBEC after extensive washing of the endothelial monolayer to remove any unbound IRBC ( Fig . 2A ) . This transfer was significantly enhanced by TNF stimulation of the HBEC prior to incubation with IRBC ( Fig . 2 A–B ) . No dye transfer was detected when HBEC were incubated either with fluorescent non-infected RBC ( Fig . 2 A ) or when the labelled IRBC were mildly trypsinised prior to incubation with HBEC ( Data not shown , DNS ) . We assessed cytoskeletal involvement in this transfer process by incubating the HBEC with optimal concentrations of cytoskeleton mobilisation inhibitors prior to co-culture with IRBC , followed by quantitation of the transferred fluorescence . Nocodazole ( 1 or 10 µM ) , a microtubule stabiliser , and cytochalasin D ( 20 or 200 µM ) , an actin reorganisation inhibitor , were the most effective in blocking the transfer of IRBC membrane elements , reaching a 6-fold inhibition ( Fig . 3 ) . Amiloride ( 5 or 50 µM ) , a micropinocytosis inhibitor , was less effective at blocking the transfer of IRBC membrane elements . We attempted to identify the cellular compartment involved in the IRBC material transfer to the HBEC by selectively labelling early endosomes ( EE ) , lysosomes or clathrin-coated pits . After less than 90 min of incubation , only the surface of HBEC appeared labelled with PKH26 , in a trogocytosis-like process ( Fig . 4 A ) . At longer incubation times ( 90 min to 3 h ) PKH26 was partially detected in EE ( Fig . 4 B ) but not in either lysosomes or clathrin-coated vesicles ( DNS ) . We evaluated the transfer of malaria antigens upon adhesion of IRBC to HBECs using a pool of human adult immune serum ( HIS ) originating from a dispensary in South Senegal , an area where malaria transmission is mesoendemic and where adults develop premunition against malaria . A pool of serum from age-matched adults from non malaria endemic areas was used as control . Western blot analyses indicated that the HIS pool recognised parasite antigens as well as parasite-encoded erythrocyte membrane proteins . In contrast , HIS could not detect any malaria antigens in proteins extracted from HBEC containing fluorescent compounds transferred from IRBC . This could be due either to sensitivity , with insufficient amounts of parasite proteins transferred to the HBEC to allow detection by Western blot or to degradation of the parasite antigens during the cell-to-cell transfer . However , using immunofluorescence deconvolution microscopy , HIS readily detected parasite proteins transferred to HBEC . It strongly detected the IRBC , but not the non-infected RBC on the HBEC surface ( Fig . 5 ) . This labelling can be detected even without any permeabilization of the cell membrane with triton . After 30 to 90 min of co-culture , HIS revealed a malarial antigen pattern on HBEC closely related to that obtained with PKH26-labelled IRBC ( Fig . 5 A–C ) . However , after a 2 h co-culture , PKH-labelled elements and malarial antigens could clearly be located in different areas on the surface of HBEC ( Fig . 5 A–C and Fig . 5F ) . This disparity may result from the different metabolic pathways to which the lipids and proteins transferred from the IRBC are subjected . At 24 h post-incubation , malarial antigens were still detected inside HBEC ( Fig . 5 D–E ) . However there was no longer any detectable labelling of the HBEC plasma membrane as it is not detectable without permeabilization of the cell membrane with triton data not shown ) . We also used HIS to evaluate the role of IRBC-surface antigens in IRBC/HBEC adhesion with a view to determine the putative role of the antibodies present in immune sera in protection against CM . Pre-incubation of IRBC with HIS , but not with non-immune serum , abrogated IRBC adhesion on HBEC as well as the transfer of PKH26-labelled material , as observed by both microscopy ( data not shown ) and by fluorescence quantification ( Fig . 2 B–C ) . As expected this pre-incubation had no effect on the adhesion of non-infected RBC used as control ( Fig . 2C ) . This observation strongly supports a role for humoral immunity in the protection against the IRBC/HBEC binding process . At present , the fine IRBC/EC contact structure had not been totally described . We conducted a detailed study of the IRBC/EC adhesion area using two HBEC cells lines , named 5i and hCMEC/D3 which presented marked differences in their surface morphology in standard culture conditions . HBEC-5i have defined surface structures , such as microvilli , podocytes and cups ( Fig . 6 ) , close to those described in vivo [14]–[15] . In the opposite way , as described by Weksler ( 2005 ) , cultured hCMEC/D3 present a very smooth surface ( Fig . 7A ) . Structures found on the 5i surface in resting condition could be related to a partial activation of these cells , as suggested by their high basal level of ICAM-1 expression . Overnight incubation of the HBEC 5i cells with 10 to 100 ng/ml of TNF induced dramatic changes in these structures , with an enlargement of the microvilli into leaf-like structures ( at 10 ng/ml ) ( Fig . 6C–D ) and to finger-like structures ( at 100 ng/ml ) ( Fig . 6E ) . The highest TNF concentration induced large areas of bubbling microparticles , as described earlier [16]–[17] ( Fig . 6F ) . We observed differences in the first contact between IRBC and HBEC according to the type of HBEC lines used and the type of surface involved . In the case of HBEC-5i , IRBC adhesion occurred on the microvilli , in a capture-like process ( Fig . 7B–C ) . The subsequent engulfing structure appeared to be closely related to that described for leukocytes ( Fig . 7D–I ) . The microvilli were progressively emitted from the surface at the same time as a transmigration cup-like structure was formed ( Fig . 7D–E ) . This cup-like structure progressively covered and engulfed the IRBC ( Fig . 7F–I ) . Fig . 8C–D shows a confocal image of IRBCs in these cup-like structures . FRC 3Ci is a parasite strain selected for its ability to bind to CD36 and ICAM-1 , whereas the CS2 strain mainly binds to CSA . hCMEC/D3 are known to poorly express CD36 , a fact we confirmed by flow cytometry ( DNS ) . However both hCMEC/D3 and -5i are known to express ICAM-1 on their plasma membrane , especially following stimulation by TNF [17] . We analysed whether actin , ICAM-1 and/or VCAM-1 play an active role in this engulfing process by imaging their distribution during the co-culture . Actin displayed a sub-membranous labelling pattern ( Fig . 8E ) , originally described as stress fibres [18] . However , a crown of actin was also detected , preferentially located around the parasite in the digitations of the cup ( Fig . 8C–E ) . ICAM-1 displayed a pattern of membrane folds on HBEC or at the border of cells when there are not fully confluent ( Fig . 8A–B ) . At higher magnification , was also detected at the bottom of the cup-like structures , under the IRBC and forming part of the cup digitations themselves ( Fig . 8A–D ) . While VCAM-1 was weakly expressed on the HBEC surface , a definite labelling was found at the bottom but not on the borders of the of cups ( Fig . 8F ) . In combination , these results suggest that IRBC engulfment is a process closely related to leukocyte transmigration , which involves adhesion to ICAM-1 . On the IRBC side , membrane molecules such as PfEMP1 are likely to be involved in the binding to ICAM-1 , and their removal by trypsin would explain the abolishment of the binding to HBEC . Consistent with this , hCMEC/D3 incubated with anti-ICAM-1 , but not with anti-VCAM-1 , antibody prior to co-culture with IRBC displayed reduced binding of 3Ci , but not of CS2 IRBC ( Fig . 2C ) . However , other adhesion molecules could be involved in this EC/IRBC binding which could explain this partial inhibition . A major event driving brain pathophysiology during malaria infection is the opening of the blood-brain barrier ( BBB ) . We used hCMEC/D3 , capable of forming a monolayer and establishing tight intercellular junctions involving VE-cadherin and ZO-1 [19] , to analyze the signals responsible for opening of intercellular junctions . Electric cell–substrate impedance sensing ( ECIS ) of the HBEC monolayer was used to assess trans-endothelial electrical resistance ( TEER ) , which reflects opening of the intercellular junctions . Experiments were done more than ten times , but only illustrations are showed in figures as summarizing ECIS data is not accurate . Four days after seeding , impedance of the monolayer was stable , with only minor fluctuations ( see “control” Fig . 9A–D ) . Overnight pre-activation of the confluent monolayer with 10 ng TNF/ml did not cause any modification in the TEER ( DNS ) . Histamine ( 100 µM ) was used as a positive control and induced a two-phase junction opening process , with a rapid decrease in TEER , within 30 min of addition , followed by a slow and steady TEER decrease , lasting for several hours ( Fig . 9B ) . We found that 3Ci-IRBC , but not non-infected RBC , induced a opening of the junctions after 2 h of incubation ( Fig . 9A ) . This opening depended on parasiteamia and lasted for over 24 h , even if the RBCs were carefully removed after 4 h of incubation ( Fig . 9A ) . In contrast , CS2 IRBC were only capable of inducing a minor decrease in the monolayer's TEER ( Fig . 9B ) . When the RBCs were not removed after just 4 h but co-cultured with the HBEC monolayer overnight , they induced a slight decrease in TEER which was apparent even with non-infected RBC ( DNS ) . This effect may be due to changes in the culture medium composition due to RBC lysis . We then proceeded to use the ECIS to test compounds that would inhibit the junction-opening effect of the 3Ci IRBC . Pre-incubation of the HBEC monolayer with 10 µM nocodazole abrogated the IRBC-induced junction opening ( Fig . 9C ) . In contrast , 10 µM rolipram , a compound known to strengthen junctions by maintaining/stimulating cAMP signalling , had no effect on 3Ci IRBC-induced opening of the junctions ( Fig . 9D ) . Pre-incubation of HBEC with anti-ICAM-1 antibodies ( 10 µg/ml ) had no effect on monolayer TEER ( DNS ) , but partially inhibited the opening of the junctions induced by 3Ci IRBC ( Fig . 9E ) . This effect is consistent with the partial inhibition that the anti-ICAM-1 antibodies caused on the IRBC binding to HBEC .
Here we demonstrate that the first step during the IRBC/HBEC interaction is a diffusion of IRBC membrane elements on the surface of HBEC , with features similar to those of trogocytosis . This process originally described during amoeba infection [20] , is also used by all hemopoietic cells [21] and plays a major regulatory role in immunity . Both T and B cells acquire their antigens by trogocytosis , in the same way that Natural Killer ( NK ) cells modulate IL-4-polarised monocytes [22] , regulatory T cells acquire their allo-antigens to kill syngeneic CD8 T cells [23] , and CTLs capture membrane fragments from their targets [24] . Additionally , T cells , NK , gamma-delta T cells and monocytes use trogocytosis to interact with cancer cells [12] , [25] . However , it was not until this year that this mechanism was encountered in non-immune cells when Waschbish et al found that the capture of myoblast membrane patches by T-cells occurred by trogocytosis [26] . Here we describe , for the first time , this trogocytosis-like interaction process between two non-immune cells , i . e . endothelial cells and red blood cells . Using human malaria-immune serum , we were able to demonstrate diffusion of malaria antigens from IRBC to HBEC during the early stage of trogocytosis . This process could result , during malaria infection , in the transfer of malaria antigens to HBEC during short interactions , such as the rolling of infected cells on the endothelium . It has also been shown that in T cells [27] trogocytosis requires actin polymerization and involves kinase signaling pathways . Our results , showing that both nocodazole and cytochalasin-D were capable of inhibiting this process , as well as the actin redistribution observed by microscopy , strongly support actin involvement in the HBEC/IRBC interaction . After 1 to 3 h of co-culture , the contact between IRBC and HBEC became tighter and involved the formation of an engulfing cup-like structure . The formation of the cup was morphologically related to the structure formed during leukocyte transmigration . We found reorganisation of actin in the protrusions of the cup as well as a localized concentration of ICAM-1 , and , to a lesser extent , of VCAM-1 , in the bottom of the cup . This engulfing process has been analyzed in depth for leukocyte transmigration . During this process , a cup is formed with projections surrounding the leukocyte [9]–[10] . These projections were enriched in actin , but not microtubules , and required both intracellular calcium mobilisation and intact microfilament and microtubule cytoskeletons [28] . Disruption of these projections with cytochalasin D or colchicine had no affect on the adhesion of leukocytes but affected the cup formation itself [29] . Importantly a similar engulfing process has already been described for pathogens such as bacteria [30]–[31] and yeasts [32] . Bacteria were previously described to aggregate , before engulfing , in a specific structure called “invasome” which is highly enriched in actin , ICAM-1 and phosphotyrosine [30] . Formation of the invasome was found to be inhibited by cytochalasin D but not by nocodazole . Here we describe a potentially similar cup-like formation and engulfing process during IRBC/HBEC interaction . However , the fact that both cytochalasin-D and nocodazole inhibited the transfer of material from IRBC to EC suggested that , in our case , there are most likely different steps involved in the interaction . The type of adhesion molecules involved in this interaction process depends on the type of cells interacting with the EC . For leukocytes , in response to LFA-1 engagement , the endothelium forms an ICAM-1-enriched cup-like structure that surrounds adherent leukocytes . Polymorphonuclear neutrophils use ICAM-1 , but not VCAM-1 , to move across activated EC monolayers [33] . On the other hand , the transmigration of THP-1 cells was reduced only when VCAM-1 or both ICAM-1 and VCAM-1 were blocked [34] . Similarly , a large panel of molecules is involved in the adhesion of IRBC on EC , including PECAM-1 , CD36 , chondroitin-sulphate A , ICAM-1 , thrombospondin , αvβ3 E-selectin , P-selectin , and VCAM-1 [35]–[36] . The data we obtained for the two different parasite strains; 3Ci ( which binds ICAM-1 and CD36 ) and CS2 ( which mainly binds chondroitin-sulphate A ) , illustrates this diversity of these interactions . However , ICAM1 is a major adhesion molecule in HBEC largely increased during TNF stimulation , thus facilitating leukocytes migration through HBEC-D3 [33] . Additionally , upregulation of ICAM-1 has been described on brain microvessels in patients who died with CM [37]–[38] and correlates with adhesion of IRBC and the severity of attack in patients [39] . Taken together , our results provide new explanations for this increase in malaria pathology . After adhesion , IRBC were progressively engulfed in the EC monolayer and subsequently altered . As revealed by the use of human immune sera , our results highlight the diffusion of malarial antigens into HBEC . These antigens were first transferred onto the endothelial surface , in a trogocytosis-like process . Later on , the membrane dye , the cytosolic material of the red blood cells and malaria antigens were recycled in the endosomal compartment of the HBEC . Of note they were readily detected in these cells up to 24 h after incubation . As HBEC are known to be antigen-presenting cells [40] , we attempted to detect the malaria antigens on their surface after a 24 h co-incubation . After this time , the anti-malaria serum pool very slightly detects malaria antigens on the HBEC surface , however this could be due to degradation of the IRBC proteins ( and epitopes ) by EC . The observed transfer of antigens to the EC involves dramatic implications for the interaction of EC with the immune system , as it could transform the EC into a new target for the immune response , especially during the rolling of immune cells on EC , and trigger major pathophysiological changes during CM . More experiments are required using immune cells from donors from endemic areas , to study the interaction between the immune system and the “IRBC-loaded” HBEC . As occurs with sepsis and viral infections , a major element in the pathophysiology of CM is the opening of the intercellular junctions . We report here that the opening of these junctions occurred shortly after the beginning of the IRBC/EC co-culture and was closely related to adhesion of the IRBC on the HBEC , as the non-infected RBC or non-binding IRBC , such as CS2 , did not induce any significant junction opening . This also implies that neither metabolic modifications of the culture medium nor proteins secreted by the parasite were , in our culture conditions , sufficient to induce junction opening . A decrease in trans-endothelial electrical resistance ( TEER ) in the endothelial monolayer is well known during leukocyte transendothelial migration [41] and has also been suggested during in vivo infection of mice with P . berghei [42]–[44] . Three primary signaling pathways are activated by leukocyte adhesion: Rho GTPases , reactive oxygen species , and tyrosine phosphorylation of junctional proteins [45] . The pathways activated during both cup formation and opening of the EC junctions , need to be further explored for IRBC attachment and transmigration . ICAM-1 engagement by leukocytes has been shown to enhance trans-endothelial permeability by tyrosine phosphorylation of VE-cadherin [46] . However , in our results , treatment with anti-ICAM-1 antibodies had no effect on the increase of permeability induced by leukocytes on HBEC-D3 , although it decreased leukocyte migration [33] . Interaction of ICAM-1 and VCAM-1 with adhesive molecules regulates the different steps of diapedesis by modulating either i ) the GTPase pathway ( Rho and Rac ) [29] , [34] ii ) and the MAP-kinase pathway ( Ca++ , CaMKK , and AMPK ) [47] . In our study , the opening of the EC junctions was independent from cAMP activation and suggested a MAP kinase pathway activation , as previously reported for P . falciparum [48] . However , the direct pathogenic effect of IRBC adhesion on the HBEC TEER must also be taken into account , as it up-regulates several TNF-superfamily genes and apoptosis-related genes such as Bad , Bax , caspase-3 , SARP2 , DFF45/ICAD , IFN-receptor2 , Bcl-w , Bik , and iNOS [49] . This could account for the increase of permeability of the HBEC monolayer we observed after 6 or 8 h of IRBC/HBEC co-culture . Adhesion of IRBC on EC is a key step in the life cycle of the plasmodium parasite and this study highlights new implications for this adhesion . We showed that a first step of rapid transfer of material from IRBC to HBEC presented features of a trogocytosis-like mechanism . This was shortly followed by a tighter adhesion , which appears to divert the natural transmigration pathway of leukocyte-EC and involves a cup-like engulfing process . Malarial antigens then entered the HBEC endosomal pathways and were detected inside the HBEC up to 24 h later . This could be followed by their presentation to the immune system . IRBC transfer was closely followed by a rapid opening of the EC intercellular junctions , an event that may contribute to cerebral oedema . All the mechanisms hereby described can have dramatic implications in the pathophysiology of CM . The relevance of these in vitro observations during CM is first supported by the experimental conditions used . Activation of the ECs and detection of TNF secreting monocytes in brains vessels in the same time as IRBC were reported by Pongponratn and Porta et al [37] , [50] who showed images of IRBC sequestered in vessels in the same time as leukocytes . Sequestration of IRBC and CM seem closely related to TNF overproduction , as reported by Grau et al and Kwiatkowski et al [51] , [52] . The range of TNF we used to activate ECs and inducing adhesion of IRBC is the same as already detected in vivo ( 100 pg/ml with high range near 500 pg/ml [53] , [54] ) . This elevated level was also detected in Cerebrospinal Fluid [55] , [56] especially in patients who died from CM . Upregulation of TNF-receptor 2 ( TNFR2 ) seems also related to CM [57] . Along the same line , focal induction of ICAM-1 expression in infected brain vessels was also reported years ago . Brown et al [58] described activation of EC and macrophages and disruption of endothelial intercellular junctions in vessels containing sequestered parasitized erythrocytes . These findings suggest that BBB breakdown occurs in areas of parasite sequestration during CM in African children . Porta et al [37] , showed CD68 leukocytes coexisting with infected erythrocytes in capillaries , whereas in venules the monocyte population outnumbered the erythrocytes . They also showed expression of ICAM-1 on EC surface in vessels with sequestered cells but not in unaffected vessels . Similarly , Esslinger et al reported that in vivo stimulation of human vascular EC with P . falciparum-infected erythrocytes resulted in the non-transient up-regulation of ICAM-1 expression on endothelial surfaces [59] . The soluble form of ICAM-1was also found significantly higher during acute malaria in children and correlated with levels of TNF , IL-1 alpha and interferon gamma [60] . Clark et al [61] showed inducible nitric oxide synthase staining of ECs which suggested intense inflammatory mediator activity . These alterations can be detected in other organs than brain especially in children who died during severe malaria without true CM . Deposits of malaria antigens in vessels were also reported earlier during autopsies of patients dying from CM . Pongponratn et al first reported images of IRBC sequestered in vessels some associated with or beneath ECs [50] . Boonpucknavig et al demonstrated intense deposition of P . falciparum antigens , IgG and fibrin in cerebral vessels associated with hemorrhages [62] . Immunofluorescent studies also demonstrated the extravascular deposits of P . falciparum granular antigens associated with acute inflammatory lesions in cerebral tissue . IgE was also reported in these depositions especially in the white matter [63]–[65] . They were also found beneath ECs suggesting transfer of material . In the same line pLDH or pAldolase were detected in a variety of organs during CM but were most abundant in the blood vessels of brain , heart , and lung tissues , also detectable in ECs [66] . All these data strongly suggest transfer of malaria antigen in or beneath the EC wall in the brain . Our in vitro observations are thus relevant in regard to these in vivo findings and can explain a part of the pathophysiology of CM . Presentation of malaria antigens by ECs to immune cells and activation of cytotoxic mechanisms could be another step in the explanation of this pathology . Analysis of this mechanism will require malaria immune cells from tropical area countries and is currently in process .
The following antibodies and dyes used were: PKH-26 or -67 ( MINI26-1KT or 67-IKT ) and Phalloidin-FITC ( P5282 ) from Sigma; anti-ICAM1 ( 0544 ) and anti-VCAM1 ( 1244 ) from Immunotech; ER tracker red BodiPyTR ( E34250 ) , Calcein-AM ( C3099 ) and Lysotracker Red DND-99 ( L7528 ) from Invitrogen; anti-EEA1 ( 610457 ) and anti-clathrin ( 07339 ) from BD Bioscience; Hoechst 33258; anti-human-IgG FITC ( 733175 ) and anti-glycophorin A ( PN IM2210 ) from Beckman Coulter . Other compounds used were: albuMAX II ( 10021-037 Gibco ) , HMDS hexamethyldisilazane ( H4875 , Sigma ) ; collagen ( BD Biosciences ) ; TNF ( PreproTech , 300-01A ) . Immortalised human brain endothelial cells 5i ( CDC Atlanta ) were grown in DMEM/F12 , whereas hCMEC/D3 [19] were grown in EBM-2 medium ( Lonza CC-3156 ) , in 24 well plates or on glass cover-slips coated with collagen . TNF activation of HBEC was carried out by treating the cells with 10ng/ml TNF for 18h . Plasmodium falciparum strains FCR 3Ci and CS2 ( kindly donated by S . Rogerson ) were grown in RPMI+0 . 5% Albumax , as previously described [67] and periodically selected for knob expression [68] Late stage IRCB were selected and concentrated using Automacs ( MiltenyR ) , according to manufacturer instructions , to an average of 80–90% parasitaemia . The IRBC were then co-incubated with HBEC [69] at a 20 RBC: 1 HBEC ratio ( i . e . 2×106 IRBC per well in a 24-well plate ) . For overnight incubations , non-adherent RBCs were gently removed from the HBEC , after 4 hours of incubation , by washing the cells three times with pre-warmed medium . For trogocytosis studies , IRBC/RBC were labelled , according to manufacturers' instructions , with either PKH-26 or -67 [70] , calcein-AM or Hoechst . Labelled RBCs were incubated , at 37°C for 30min , in parasite media prior to the last wash . Immunofluorescence detection was carried out on cells fixed in 2% paraformaldehyde ( PAF ) for 10min . Cells were treated with 25mM NH4Cl , permeabilized in 0 . 1% Triton X-100 , and incubated for 30min in 3% bovine serum albumin ( BSA ) prior to antibody reactions ( see list below ) for 45min ( in PBS containing 0 . 3% BSA ) . Detection of P . falciparum ( Pf ) antigens was performed using a pool of 15 human plasma samples selected out of 100 samples from Senegalese Pf-immune adults ( used at 1∶500 ) . The samples were selected for their high titer ( >1024 ) in plasmodium antibodies [71] and for their low background on HBEC ( checked individually by immunofluorescence ) . A pool of plasma from non-immune adults was used as a negative control . For microscopy examination cover-slips were mounted in moviol and examined either under an Olympus FV1000 confocal microscope ( magnification 600 or 1000 ) or on an Olympus-IX71 fluorescent microscope equipped with a F-View CCD camera ( Soft Imaging Sys . ) . Laser 405nm was used with Differential Interferential Contrast ( DIC ) to generate bright field images . Quantitation of fluorescence was carried out in 24-wells plates on a Fluostar Optimax Spectrophotometre ( BMG LabTech ) at the relevant wavelengths ( 100 spots/well were read ) . For scanning electron-microscopy , HBEC were grown on 10 mm glass coverslides in 24-well plates for 5 days . They are co-cultured with IRBC as previously described . were fixed first in PAF 2% for 10 min and glutaraldehyde 2% in cacodylate buffer for 30min , followed by potassium ferrocyanate–osmium ( 1% each ) post-fixation . Dehydration was performed in grading alcohols , with a final step in HMDS for 3 min . Transendothelial impedance was measured every 10 minutes over the course of experiments using electric cell–substrate impedance sensing ( ECIS ) system . hCMEC/D3 were seeded at 20 , 000 cells/wells in 8-well slides and allowed to grow for 3 to 4 days , until confluent , in complete HBEC medium . Confluent hCMEC/D3 monolayers ( estimated 100 , 000 cells/well ) were activated with TNF ( 10 ng/ml ) for 18 hours . Drugs were then added directly to wells 40 min prior to addition of IRBC ( 3Ci- or CS2 ) or NRBC at a ratio of 20 IRBC/cell . Red blood cells were removed from the HBECs by gentle washing , 4 hours after beginning of incubation . Histamine was used as a positive control for TEER modification . For each well , impedance at time t was normalized according to the impedance of the well at the beginning of the co-culture ( t0 ) and plotted according to time as: ( I ( t ) −I ( t0 ) ) /I ( t0 ) . I ( 0 ) was evaluated as the mean impedance over 50 min just before beginning of experiments .
|
Cerebral malaria , a major cause of death during malaria infection , is characterised by the sequestration of infected red blood cells ( IRBC ) in brain microvessels . This study describes the interactions between plasmodium infected red blood cell and human brain endothelial cells . It highlights the activation of a trogocytosis-like mechanism followed by an engulfment of the infected red blood cells by endothelial cells ( EC ) . This transfer concerns up to 20% of the IRBC cocultured with EC . This means that the parasite infected erythrocyte can mimic the leukocytes interaction with endothelial cells . This process is associated with i ) a transfer of malaria antigens to the EC which can inappropriately activate the immune system and ii ) an opening of the intercellular junctions , which can trigger blood-brain-barrier leakage during cerebral malaria . This transfer of IRBC antigens can thus transform EC into a target for the immune response and contribute to cerebral malaria pathogenesis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/infectious",
"diseases",
"of",
"the",
"nervous",
"system",
"cell",
"biology",
"microbiology/parasitology",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases",
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis",
"cell",
"biology/cytoskeleton"
] |
2010
|
Plasmodium falciparum Adhesion on Human Brain Microvascular Endothelial Cells Involves Transmigration-Like Cup Formation and Induces Opening of Intercellular Junctions
|
DNA methylation is involved in gene silencing and genome stability in organisms from fungi to mammals . Genetic studies in Neurospora crassa previously showed that the CUL4-DDB1 E3 ubiquitin ligase regulates DNA methylation via histone H3K9 trimethylation . However , the substrate-specific adaptors of this ligase that are involved in the process were not known . Here , we show that , among the 16 DDB1- and Cul4-associated factors ( DCAFs ) encoded in the N . crassa genome , three interacted strongly with CUL4-DDB1 complexes . DNA methylation analyses of dcaf knockout mutants revealed that dcaf26 was required for all of the DNA methylation that we observed . In addition , histone H3K9 trimethylation was also eliminated in dcaf26KO mutants . Based on the finding that DCAF26 associates with DDB1 and the histone methyltransferase DIM-5 , we propose that DCAF26 protein is the major adaptor subunit of the Cul4-DDB1-DCAF26 complex , which recruits DIM-5 to DNA regions to initiate H3K9 trimethylation and DNA methylation in N . crassa .
The Cul4-DDB1 complex , a major class of cullin-RING ubiquitin ligases ( CRLs ) , is evolutionarily conserved from yeasts to humans . Previous studies have indicated that Cul4-DDB1-regulated ubiquitination is linked to multiple processes , such as cell cycle regulation , DNA replication licensing , DNA repair , and gene expression processes [1]–[3] . In the CRLs , cullin associates with substrates via adaptor molecules in the N terminus , and interacts with the E2 enzyme via the RING finger protein Hrt1/ROC1/Rbx1 in the C terminus [4] . Substrate-specific adaptors , such as the F-box-containing proteins in SCF complexes and the BTB domain-containing proteins in Cul3-based ubiquitin ligases , determine substrate-specific ubiquitination in many biological processes [5] . Although the different structural states of DDB1 may allow it to directly recruit substrates to the Cul4-based E3 platform , studies have demonstrated that ubiquitination of several characterized CUL4-DDB1 substrates requires additional substrate-specific adaptors [6] , [7] . Recent studies showed that a class of adaptors called DCAFs ( DDB1- and Cul4-associated factors ) [4] are employed by Cul4-based E3 ligases to identify specific proteins for ubiquitination . Most DCAFs are WD40-containing proteins with relatively conserved “WDXR” motifs that interact with DDB1 protein . However , several DCAF proteins lacking this conserved motif are still able to bind DDB1 in vivo [3] , [4] , [8] , [9] . Among the well-characterized DCAF proteins , mammalian WDR5 and RBBP5 are essential components of the histone methyltransferase complex that methylates histone H3 on lysine 4 ( H3K4 ) [10]–[12] . Further studies showed that Cul4-DDB1 can interact with WDR5 and RBBP5 and regulate histone H3K4 methylation . Down regulation of each of these genes by siRNA severely reduces the tri- and monomethylation of histone H3K4 , but not H3K4 dimethylation [13] . Interestingly , inactivation of Cul4 or DDB1 also causes a significant inhibition of histone H3K9 and H3K27 trimethylation [13] . However , none of these DCAFs were shown to be involved directly in DNA methylation in eukaryotes . In fission yeast , the Cul4-Rik1 E3 ubiquitin ligase associates with the histone methyltransferase Clr4 on heterochromatic regions to methylate histone H3K9 , contributing to heterochromatin assembly and maintenance [14] . The catalytic activity of Cul4 is required for its proper function in heterochromatin formation . This study suggests that the activity of Cul4-based E3 ligase is required for histone H3K9 methylation . In addition , a WD-40-containing protein , Raf1/Dos1/Clr8/Cmc1 , is required for histone H3K9 methylation and heterochromatin formation in S . pombe [15]–[18] . Thus , these studies imply that Raf1/Dos1/Clr8/Cmc1 functions as an adaptor protein associated with Cul4-Rik1 complex in S . pombe . We previously demonstrated that Cul4-DDB1 E3 ligase is essential for DNA methylation in N . crassa by regulating histone H3K9 trimethylation [19] . These results suggest that Cul4-DDB1 ubiquitin ligase is required for epigenetic control in higher eukaryotes . However , the substrate-specific adaptors of Cul4-DDB1 E3 ligase and the requirement of DCAFs as the substrate adaptors in DNA methylation are unknown in N . crassa . Here , we identified three DCAFs that could strongly interact with DDB1 protein in vivo , out of 16 candidates in the N . crassa genome . DNA methylation analysis in knockout strains of the 12 dcaf genes showed that dcaf26 was essential for DNA methylation in N . crassa . The dcaf26 deletion mutant also lost histone H3K9 trimethylation . Our protein interaction results suggest that DCAF26 functions as an adaptor subunit of the Cul4-DDB1-DCAF26 complex by recruiting histone methyltransferase DIM-5 to DNA methylation regions in N . crassa . In addition , we show that the interaction of DCAF26 with DDB1 was required to enable the Cul4-DDB1-DCAF26-DIM-5 complex to regulate H3K9 trimethylation and DNA methylation in this organism .
We searched the N . crassa genome for WD-40-containing proteins with WDXR and DxR motifs ( also known as a DWD motif ) . The conserved 16 amino acid sequence [IFVL]-[IFVL]-[AGST]-[AGST]-[AGST]-x-[DE]-x ( 2 ) -[IFVL]-x-[IFVL]- [WY]-[DE]-[IFVL]-[RK] [20] was used as the seed to search for WD-40-containing proteins . Five putative DCAFs met the criteria ( Table 1 ) . Based on the sequences of hundreds of DCAF proteins from yeast to human that have been identified by protein interaction experiments and bioinformatics analysis , we identified another 11 putative DCAF proteins ( Table 1 ) . In total , we identified 16 putative DCAF proteins in the N . crassa genome ( Figure 1A ) . To identify the true DCAFs in N . crassa , we examined the interactions between DDB1 and the predicted DCAF proteins . We first made constructs in which the DCAF ORF was under the control of a quinic acid ( QA ) –inducible promoter [21] . To facilitate the detection of DCAF expression , five copies of the c-Myc epitope and six histidine residues [22] were inserted into the N terminus of the DCAF ORF . The constructs were then transformed into a wild-type strain and Myc-DCAF expression in the resulting transformants in the presence of QA was confirmed by western blot analysis using the c-Myc antibody . Afterwards , immunoprecipitation assays were used to examine the interactions between Myc-DCAF proteins and DDB1 in the transformants . As shown in Figure 1B , three Myc-tagged DCAFs , DCAF11 , DCAF2 , and DCAF26 , interacted strongly with the DDB1 protein in vivo . Our DDB1 antibody depleted with tissue of the ddb1KO strain specifically recognized a 128-kDa band in the wild-type strain , but not in the ddb1 mutant ( Figure S1 ) . DCAF11 and DCAF2 had two conserved WDXR motifs , while DCAF26 had only one conserved WDXR motif ( WNVR ) . In contrast , only weak interactions were detected between DDB1 and the other Myc-DCAFs ( Figure S2 ) . These results suggest that DCAF11 , DCAF2 , and/or DCAF26 could be the adaptor ( s ) in the Cul4-DDB1 E3 ligase complex in N . crassa . Our previous study showed that the Cul4-DDB1 E3 complex is required for DNA methylation in N . crassa [19] . To investigate the function of the putative DCAFs in DNA methylation , we tried to generate deletion strains of the 16 candidate dcaf genes by gene replacement in the ku70RIP strain . However , we could not obtain the homokaryotic deletion strains of four genes ( NCU01595 , NCU02729 , NCU05426 , and NCU09521 ) , suggesting that they are important for cell viability in N . crassa . Several independent homokaryotic knockout strains of the other 12 dcaf genes were obtained by microconidia purification . PCR analysis confirmed the integration of the knockout cassette at the endogenous dcaf locus , and no dcaf ORF signals were detected in these knockout mutants . To identify the DCAF protein ( s ) required for DNA methylation , we measured the cytosine methylation states of all homokaryotic dcaf mutants . Genomic DNA of the wild-type strain and ku70RIP , dim-2KO , and dcaf mutants was digested with DpnII or BfuCI ( Sau3AI ) . Undigested and digested DNA was then used as templates for PCR . Three representative methylated regions , the ku70RIP locus , ζ-η , and ψ63 , were examined in the wild-type strain , ku70RIP , dim-2KO , and dcaf mutants . As shown in Figure 2 , no PCR products were detected with DpnII- or BfuCI-digested genomic DNA as templates in the dcaf26KO mutant , the same as for the dim-2KO mutant . To further confirm these results , we tested the known methylation region on centromere VII of N . crassa . As expected , methylation on this DNA region was also lost in the dcaf26KO mutant ( Figure 2 ) , indicating that DCAF26 plays an essential role in DNA methylation . In contrast , the other 11 homokaryotic dcaf mutants exhibited normal cytosine methylation patterns at ζ-η and ψ63 regions , the same as those in the wild-type strain ( Figure S3 ) . This demonstrated that they were not essential for DIM-2–dependent DNA methylation ( Table 1 ) . Taken together , these results suggest that DCAF26 was a key regulator of DNA methylation in N . crassa . In N . crassa , proper DNA methylation depends on histone H3K9 trimethylation , which is controlled by the histone methyltransferase DIM-5 [23] , [24] . When we compared the growth and developmental phenotypes of the dcaf knockout strains to those of the wild-type strain and cul4KO , ddb1KO , and dim-5KO mutants , we found that the dcaf26 mutant exhibited dense , cauliflower-like growth patterns with abnormal hyphae and asexual spores on plates ( Figure 3A ) . This was similar to the phenotypes of the cul4 , ddb1 , and dim-5 deletion strains [19] ( Figure 3A ) . The dcaf26KO mutant also exhibited slow growth rates on racetubes compared to that of the wild-type strain ( Figure 3B ) ; these rates were similar to those of the cul4KO , ddb1KO , and dim-5KO strains . These results suggest that DCAF26 affected DNA methylation by regulating H3K9 trimethylation in the same pathway as the Cul4-DDB1 complex . Therefore , we next examined H3K9 trimethylation levels by chromatin immunoprecipitation ( ChIP ) in the wild-type strain , the ku70RIP strain , and the dcaf26 mutant . Chromatin samples were immunoprecipitated with antibody against trimethylated Lys9 of histone H3 and analyzed by PCR with primers targeted to methylated DNA regions . As shown in Figure 3C , trimethylated H3K9 was associated with the methylated ku70RIP region in the ku70RIP strain , whereas trimethylated H3K9 at the ku70RIP region was abolished in the dcaf26 mutant . Similarly , trimethylated H3K9 at the ζ-η and ψ63 regions in the ku70RIP strain was observed at levels comparable to the wild-type strain ( Figure 3C ) . In contrast , H3K9 trimethylation was lost in the dcaf26 mutant ( Figure 3C ) . Taken together , these data indicate that N . crassa DCAF26 was required for trimethylation of histone H3K9 at methylated DNA regions . To investigate the effect of DCAF26 protein on global trimethylated H3K9 in N . crassa , we tested the levels of histone H3 or trimethylated H3K9 using western blot analysis in wild-type , dcaf26KO , cul4KO , ddb1KO , and dim-5KO strains . As shown in Figure 3D , all of the strains had similar levels of histone H3 . In contrast to the robust H3K9 trimethylation in the wild-type strain , very little trimethylated H3K9 was detected in dcaf26KO , cul4KO , ddb1KO , dim-5KO strains . Together , these results strongly suggest that DCAF26 protein was required for histone H3K9 trimethylation . Having identified DCAF26 as a DCAF protein that interacted strongly with DDB1 protein , we next tested whether DCAF26 was a key component in the Cul4-DDB1-DIM-5 complex for DNA and histone H3K9 methylation . We did so by performing an immunoprecipitation assay to detect interactions between Myc-DCAF26 and Flag-Cul4 and between Myc-DCAF26 and Flag-DIM-5 . As shown in Figure 4A , Myc-tagged DCAF26 specifically interacted with one of two Flag-Cul4 species ( neddylated/unneddylated Cul4 ) . To determine whether DCAF26 preferentially interacts with neddylated or unneddylated Cul4 , we loaded protein extract from a csn-2KO strain , in which Cul4 remained in a hyperneddylated state , side by side with Myc-DCAF26/Flag-Cul4 to show that the upper band in the input and the Myc-DCAF26-interacting Cul4 band were neddylated Cul4 ( Figure 4A ) , similar to the association between DIM-5 and neddylated Cul4 species in N . crassa [19] . We then examined the interactions between DCAF26 protein and DIM-5 . As expected , the Flag antibody pulled down the Myc-tagged DCAF26 in the strain that coexpresses Flag-DIM-5 and Myc-DCAF26 ( Figure 4B ) , indicating that DCAF26 was a component of the Cul4-DDB1-DIM-5 complex . These data explain the similar phenotypes in dcaf26KO , cul4KO , ddb1KO , and dim-5KO mutants . We next investigated the function of DCAF26 in this complex . We checked the interactions of DDB1-DIM-5 in the dcaf26KO strain and in a dim-5KO , qa-Myc-DIM-5 transformant . As shown in Figure 4C , the interactions between DDB1 and DIM-5 were severely impaired in the dcaf26KO strain , while DIM-5 strongly interacted with DDB1 in the presence of DCAF26 . This indicates that DCAF26 was required for recruiting DIM-5 to the Cul4-DDB1 complex . Furthermore , the interaction between DDB1 and Cul4 was not affected in the dcaf26KO mutant ( Figure 4D ) , confirming that DCAF26 was an adaptor protein in the Cul4-DDB1-DIM-5 complex . The finding that N . crassa DCAF26 interacts with DDB1 and neddylated Cul4 to form a complex prompted us to investigate the functional importance of the interaction between DCAF26 and DDB1 . As shown in Figure 5A , DCAF26 and Cul4 protein interactions were totally abolished in the ddb1KO mutant , suggesting that DDB1 served as a bridge between Cul4 and DCAF26 to form the complex . This result suggests that DDB1 , DCAF26 , and their interactions contributed the H3K9 and DNA methylation functions of the Cul4-DDB1-DCAF26-DIM-5 complex . DCAF26 ( NCU01656 . 3 ) contains some interesting sequence features , including one WDXR motif ( WNVR ) and WD-40 repeat regions . When the DCAF26 protein sequence was queried in a blast search against protein databases , DCAF26 was found to be similar to various fungal homologs . Many DCAF26 homologs contain one WDXR motif and one WDTA , or another WDXR motif located separately between consecutive “propeller blade” folds of the protein ( Figure 5B ) . N . crassa DCAF26 protein contains one WDTA ( aa 917–920 ) motif and one conserved WDXR ( WNVR973–976 ) motif ( Figure 5B ) . To determine which domains of DCAF26 are involved in the DCAF26-DDB1 interaction , we mutated arginine 976 to alanine in the WNVR motif ( Figure 5C ) in qa-Myc-His-DCAF26 construct . As shown in Figure 5D , this mutation of DCAF26 reduced binding with DDB1 compared to the binding between wild-type DCAF26 and DDB1 in dcaf26KO transformants . However , this DCAF26 mutation did not affect the interactions between DCAF26R ( 976 ) A and DIM-5 ( Figure 5E ) . We then deleted 24 amino acids ( 960–983 ) from DCAF26; this amino acid stretch included the WNVR motif and the third WD-40 domain ( Figure 5C ) . As shown in Figure 5D , the interaction of DCAF26dWD3 with DDB1 was totally abolished in dcaf26KO qa-Myc-DCAF26dWD3 transformants . However , this DCAF26 deletion did not affect interactions between DCAF26dWD3 and DIM-5 ( Figure 5E ) . These results indicate that the WNVR motif and adjacent amino acids were important for interactions with DDB1 , not interactions with DIM-5 . To further examine the function of the interaction between DCAF26 and DDB1 , we investigated the function of these mutated DCAF26 in dcaf26KO transformants . As shown in Figure 6A , the expression of Myc-tagged wild-type DCAF26 fully rescued the growth and developmental defects of the dcaf26KO mutant , resulting in a similar growth rate as the wild-type strain on plates . Importantly , the DNA methylation ( Figure 6B ) and the H3K9 trimethylation ( Figure 6C and 6D ) in the dcaf26KO , qa-Myc-His-DCAF26 transformant were also restored . The expression of Myc-DCAF26R ( 976 ) A mutant protein can restore the growth and developmental phenotypes ( Figure 6A ) , as well as DNA methylation ( Figure 6B ) and H3K9 trimethylation ( Figure 6C and 6D ) of dcaf26KO mutant . These results indicated that the weak interaction of DCAF26-DDB1 is sufficient for the formation of Cul4-DDB1-DCAF26-DIM-5 complex . In contrast , the expression of Myc-DCAF26dWD3 mutant protein failed to rescue the growth and developmental phenotypes ( Figure 6A ) and the defects of DNA methylation ( Figure 6B ) and H3K9 trimethylation ( Figure 6C and 6D ) of dcaf26KO mutant , indicating that the interaction of DCAF26-DDB1 was required for the proper function of Cul4-DDB1-DCAF26-DIM-5 complex . Taken together , these results further demonstrate that DCAF26 is a critical component in the Cul4-DDB1 ubiquitin ligase in N . crassa . Recent studies demonstrate the biochemical function of the DCAF protein DDB2 as a substrate receptor for XPC ubiquitination in DDB1-DDB2-CUL4A-Rbx1 complex in human cell lines [25] . Since we have demonstrated that DCAF26 is required for recruiting DIM-5 to the Cul4-DDB1 complex , we wondered whether there are other substrates associated with the complex . To better understand the substrate adaptor role of DCAF26 for the Cul4-DDB1 E3 ligase , we attempted to purify this protein in N . crassa . To do so , we expressed Myc-His-DCAF26 protein by inoculating the dcaf26KO , qa-Myc-His-DCAF26 strain in liquid media containing quinic acid . Then Myc-His-DCAF26 protein was purified by nickel-column followed by immunoprecipitation using the c-Myc monoclonal antibody . As shown in Figure 7A , several major protein bands were specifically observed in the Myc-His-DCAF26 sample but not in the negative control ( WT lane ) . The LC-MS/MS analysis of excised gel bands led to the identification of five well-known proteins , DCAF26 , Cul4 , DDB1 , Nedd8 , DIM-5 ( the histone H3K9 methyltransferase in N . crassa ) ( Figure 7A and 7B ) . All proteins were represented with three or more peptides . The coexistence of Nedd8 peptides with Cul4 was consistent with previous results showing that DCAF26 preferentially interacted with neddylated Cul4 proteins in vivo , further confirming that DCAF26 is a key component of Cul4-DDB1 E3 ligase . In addition , we also identified other four DCAF26 co-purified proteins ( Figure 7A and 7B ) encoded by NCU07855 , NCU04152 , NCU06123 , and NCU11350 , respectively . Among these proteins , NCU04152 ( DIM-7 ) is also required for DNA methylation and H3K9 trimethylation ( Figure S4 ) . Since the submission of this paper , similar results were recently shown by Lewis et al . [26] . Furthermore , the absence of ubiquitin peptides in the purification products suggests that either the ubiquitinated substrate is released immediately from Cul4-DDB1 complex or its ubiquitination level is too low to be detected .
Recent studies demonstrated that three proteins , DIM-5 [23] , HP1 [27] , and DIM-2 [28] , are essential for DNA methylation in N . crassa , which function in histone H3K9 trimethylation and DNA methylation . To understand the regulation of DNA methylation in N . crassa , we sought to identify the proteins operating upstream of DIM-5 . Previously , we showed that DDB1 and Cul4 function in an early step of DNA methylation by forming a complex with DIM-5 to regulate H3K9 trimethylation in N . crassa [19] . To determine the precise function of this complex , we sought to identify the DDB1- and Cul4-associated factors ( DCAFs ) involved in this pathway . In mammalian cells , the DCAF protein WDR5 is a core component of the histone methylation complex essential for H3K4 methylation [12] , and loss of WDR5 specifically affects tri- and monomethylated H3K4 [13] . However , there is limited evidence to suggest that histone H3 methylation is directed by DCAF protein , which recruits a specific histone methyltransferase . In fission yeast , a putative DCAF protein , Dos1/Raf1/Clr8/Cmc1 15–18 , interacts with Cul4 , Rik1 , and Clr4 ( histone H3K9 methyltransferase ) to regulate the heterochromatin formation . It was reported that Dos1 , which is associated with Rik1 and important for the function of the Clr4-Rik1 complex , is essential for the recruitment of Clr4 in the RNAi-dependent heterochromatin pathway [17] . To find out how N . crassa DCAF proteins participate in histone H3K9 methylation and DNA methylation , we explored potential DCAF proteins that might interact with Cul4-DDB1 E3 ubiquitin ligase . We found that DCAF26 was associated with DDB1 and was essential for H3K9 trimethylation and DNA methylation . Protein interaction experiments revealed that , as with DIM-5 [19] , DCAF26 preferentially interacted with neddylated Cul4 species . Interactions between DDB1 and DIM-5 were dependent on DCAF26; this indicates that DCAF26 served as a link between Cul4-DDB1 and DIM-5 in this pathway , thus regulating H3K9 trimethylation . Interestingly , in fission yeast , the loss of H3K9 methylation in dos1 deletion mutants is similar to that in rik1 and clr4 mutants , and more severe than in RNAi mutants [17] , suggesting that Dos1 is required for histone H3 modification in the same pathway as Rik1 and Clr4 . Immunoprecipitation experiments revealed that DCAF26 bridges the Cul4-DDB1 complex to DIM-5 and functions in the same DNA methylation pathway in N . crassa . If DCAF26 protein interacts with DDB1 , Cul4 , and DIM-5 to form a complex , we would expect the association of DCAF26-DDB1 to play an essential role in the function of the Cul4-DDB1-DCAF26-DIM-5 complex . Recent studies showed that many DCAF proteins contain two conserved WDXR motifs that are the key interacting modules with DDB1 in Cul4-DDB1 E3 ubiquitin ligases [3] , [4] , [13] , [29] , [30] . In this study , we showed that deletion of a region with a WDXR motif in DCAF26 , but not the single-amino acid substitution of WNVR976A , eliminated DCAF26-DDB1 interactions and H3K9 trimethylation and DNA methylation in vivo , indicating that the interaction between DCAF26 and DDB1 is required for H3K9 trimethylation and DNA methylation . Although several studies showed that the arginines in conserved WDXR motifs in DCAF proteins are required for the association between DCAFs and DDB1 , some DCAFs that lack the conserved motifs can still interact with DDB1 and Cul4 proteins [8] , [9] . Interestingly , S . pombe Dos1/Raf1/Clr8/Cmc1 contains two conserved WDXR motifs [4]; however , mutagenesis studies of these motifs to examine the interactions with Rik1 protein have not yet been performed . Alignment of these two motifs and adjacent regions in S . pombe Dos1 with the corresponding region in N . crassa showed that they share a high similarity , suggesting that this region is important for interactions with DDB1 . Indeed , the results of our deletion and mutagenesis studies revealed that the WDXR-containing WD3 region , but not the arginine residue , was necessary for productive assembly with DDB1 into a functional H3K9 methyltransferase complex under physiological conditions . In addition , we found that the WDXR-containing WD3 region was not required for interactions between DCAF26 and DIM-5 , and confirmed that the association of DCAF26-DDB1 was essential for recruiting DIM-5 to regulate H3K9me3 . Thus , the Cul4-DDB1-DCAF26 complex serves to recruit the histone methyltransferase DIM-5 for H3K9 trimethylation , which serves as a mark for DNA methylation . Our results indicate that DCAF26 protein was necessary for recruiting DIM-5 into the Cul4-DDB1 complex . In addition , both DCAF26 and DIM-5 preferentially interacted with neddylated Cul4 species . These data suggest that the Cul4-DDB1-DCAF26 complex is required to recruit DIM-5 or to ubiquitinate a specific substrate ( s ) to perform its epigenetic functions . In fission yeast , in vitro data show that H2B can be polyubiquitinated by a purified complex containing Cul4-Rik1-Raf1-Raf2-Clr4 [16] . In mammalian cells , the putative targeting substrate of Cul4-DDB1-WDR5 is histone H3 [13] . In human cells , Cul4-DDB1DDB2 promotes the ubiquitination of histones H3 and H4 [31] . However , under normal growth conditions , the Cul4-DDB1-DCAF26 complex mainly recruits DIM-5 to regulate H3K9 trimethylation and DNA methylation . In contrast , histones H2B and H4 were copurified with ubiquitin , Cmc1 , and Clr4 in Rik1 purification products and were suggested as the likely targets of Cul4-mediated ubiquitination in fission yeast [15] . In mammalian cells , XPC was identified as a substrate directly targeted by the DCAF protein DDB2 to the DDB1-DDB2-CUL4A-Rbx1 E3 complex [25] . In S . pombe , the DCAF protein Cdt2 is required for the degradation of Spd1 through ubiquitination by the Cul4-DDB1 E3 ligase [7] . However , no direct binding is observed between Cdt2 and its target protein Cdt1 in mammalian cells [29] . These results suggest that it may be difficult to identify the substrate of a specific DCAF by copurifying its interacting proteins . We tried to identify the substrate of the Cul4-DDB1-DCAF26 complex by purification of Myc-His-DCAF26 in N . crassa . In Myc-His-DCAF26 affinity purification products , Cul4 , DDB1 , DIM-5 , and Nedd8 were copurified , strongly suggesting that they form an E3 ubiquitin ligase . Unlike the Rik1 purification in fission yeast , no ubiquitinated protein was detected in the purification . This result suggests that the substrate is ubiquitinated at low levels , such as mono-ubiquitination , by the Cul4-DDB1-DCAF26 complex , or that the ubiquitinated substrate is released immediately from its E3 complex . Alternatively , it is also possible that ubiquitinated protein ( s ) do not associate tightly with this complex during H3K9 methylation and DNA methylation . The activating signals of DNA methylation can trigger assembly of the Cul4-DDB1-DCAF26 complex , in which neddylated Cul4 promotes the complex formation with DDB1 and DCAF26 , and then recruits DIM-5 at specific DNA regions for H3K9 trimethylation . This functional complex would link the initial signals of DNA methylation , and downstream epigenetic modifications on histones and DNA . Together , our results suggest that in the DNA methylation process , the biochemical function of the Cul4-DDB1-DCAF26 complex is to recruit DIM-5 to control H3K9 methylation and DNA methylation in N . crassa . Because Cul4-DDB1 complexes are conserved in higher eukaryotes , we propose that analogous Cul4-DDB1-DCAF complexes may have a similar role in these organisms .
In this study , 87-3 ( bd a ) was used as the wild-type strain . All of the dcaf gene knockout mutants were newly generated from the bd ku70RIP genetic background strain and are listed in Table 1 . The ddb1KO , cul4KO , dim-5KO , and dim-2KO strains generated previously [19] were also included in this study . The 301-6 ( bd , his-3 , A ) , ddb1KO ( bd , his-3 ) , and dim-5KO ( bd , his-3 ) strains were used as the host strain for the his-3 targeting constructs . Liquid cultures were grown in minimal medium ( 1× Vogel's , 2% glucose ) . For QA-induced gene expression , 0 . 01 M QA ( pH 5 . 8 ) was added into liquid medium containing 1× Vogel's , 0 . 1% glucose , and 0 . 17% arginine [32] . For the racetube assay , the medium contained 1× Vogel's , 0 . 1% glucose , 0 . 17% arginine , 50 ng/mL biotin , and 1 . 5% agar . Full-length open reading frames ( ORFs ) and the 3′-UTR of all putative DCAF proteins were PCR amplified from genomic DNA and cloned into pqa-5Myc-6His . To study the interaction of Myc-tagged DCAF26 with Flag-tagged Cul4 or Flag-DIM-5 , the Myc-tagged construct was introduced into transformants expressing Flag-Cul4 or Flag-DIM-5 by cotransformation with pBT6 ( containing the benomyl resistance gene , obtained from the Fungal Genetics Stock Center ) . Western blot analyses using a monoclonal c-Myc antibody ( 9E10 , Santa Cruz Biotechnology ) were performed to identify the positive cotransformants . Immunoprecipitation assays using c-Myc antibody or Flag antibody ( F3165-5MG , Sigma ) were performed to test the interactions between Myc-tagged DCAF26 and Flag-Cul4 or Flag-DIM-5 in positive cotransformants . Protein extraction , quantification , western blot analysis , and immunoprecipitation assays were performed as described previously [32] , [33] . Sixteen dcaf gene knockout mutants were generated following the knockout procedures described previously [19] . Briefly , the entire ORF knockout cassette of each gene was created by PCR . The hph gene replacement cassette was introduced into the ku70RIP strain by electroporation . The transformants with hph at the ORF of the targeted dacf gene locus were passaged on minimal slants with hygromycin for five generations . The homokaryotic knockout strains of these dacf genes were then obtained by conidia purification and confirmed by PCR analysis . The protocol of DNA methylation assay was the same as described previously [19] . Briefly , genomic DNA ( 200 ng ) was digested with DpnII or BfuCI ( Sau3AI ) in 50 µL reaction system . No enzyme was added to the control samples . The PCR primers for ku70 , ζ-η , Ψ63 , and cen VII regions are listed in Table 2 . PCR was performed using 1 µL of the digested DNA as a template in a 50 µL reaction system , with a program of 5 min at 94°C , followed by 31 cycles at 94°C ( 30 sec ) , 53°C ( 30 sec ) , and 72°C ( 1 min ) . The PCR products were resolved by electrophoresis on 2% agarose gels . Each experiment was performed independently at least three times . For the ChIP assay , tissues were fixed in minimal media containing 1% formaldehyde for 10 min at 25°C . ChIP was performed using 8 µL of antibody to H3K9me3 ( 07-442 , Upstate Biotechnology ) or 10µL of antibody to H3 ( 06-755 , Upstate Biotechnology ) for 6 mg/ml protein . After washing with 70% ethanol , extracted DNA pellets were resuspended in 30 µL of double-distilled water , and 0 . 5 µL of the DNA solution was used for PCR . The primers for ku70 , ζ-η , Ψ63 , and hH4 regions are listed in Table 2 . PCR conditions were as follows: 5 min at 94°C , 26–30 cycles at 94°C ( 30 sec ) , 53°C ( 30 sec ) , and 72°C ( 1 min ) . Different PCR cycles were tested to ensure that DNA amplification was within the exponential amplification range . PCR products were resolved by electrophoresis on 2% agarose gels . ChIP assays with anti-Myc antibody or no antibody were used as negative controls . Each experiment was independently performed at least three times . N . crassa histone proteins were extracted from the wild-type strain , dcaf26KO , ddb1KO , cul4KO , and dim-5KO strains , as described previously [34] . Equal amounts of histone protein extracts were loaded onto 15% SDS-PAGE gels . Western blot analysis was performed using antibodies against trimethylated H3 Lys9 ( 07-442 Upstate Biotechnology ) or H3 ( 06-755 Upstate Biotechnology ) . dcaf26KO Myc-His-DCAF26 strain and the wild-type strain ( as the negative control ) were cultured for approximately 20 hr in constant light ( LL ) in liquid medium containing QA ( 0 . 01 M QA , 1× Vogel's , 0 . 1% glucose , and 0 . 17% arginine ) . Approximately 10 g of tissue from each strain grown in LL was harvested . The purification procedure was the same as described previously [22] . Fractions containing purified Myc-His-DCAF26 were immunoprecipitated by adding 20 µL of c-Myc monoclonal antibody-coupled agarose beads ( 9E10AC , Santa Cruz Biotechnology ) . The precipitates were analyzed by SDS-PAGE ( 2%–20% ) , which was subsequently silver stained following the manufacturer's instructions ( ProteoSilver Plus , Sigma ) . The specific bands were excised and subjected to tryptic digestion and liquid chromatography–mass spectrometry/mass spectrometry analysis ( LC-MS/MS ) .
|
DNA associates with histones to form chromatin in eukaryotes . Epigenetics refers to DNA and histone modifications in chromatin that persist from one cell generation to the next , controlling gene expression and genome stability . These epigenetic changes are crucial for the development and differentiation of the various cell types in eukaryotes . In this study , we identified DCAF26 as a crucial regulator of DNA methylation . Inactivation of this gene in N . crassa resulted in loss of both DNA methylation and histone H3K9 trimethylation . We found that the resulting severe defects in the development and growth of dcaf26 mutants were similar to those found in cul4 , ddb1 , and dim-5 mutants , suggesting that these four genes function in the same pathway . Furthermore , we showed that DCAF26 functioned as an adaptor protein for the Cullin4-DDB1 complex to recruit the histone methyltransferase DIM-5 and regulate trimethylation of histone H3K9 , which marks DNA for methylation . Our results reveal important roles for DCAF26 in H3K9 trimethylation and DNA methylation in N . crassa and suggest a conserved mechanism for DNA methylation in eukaryotic organisms .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology/microbial",
"growth",
"and",
"development",
"genetics",
"and",
"genomics/epigenetics",
"biochemistry/protein",
"chemistry"
] |
2010
|
DCAF26, an Adaptor Protein of Cul4-Based E3, Is Essential for DNA Methylation in Neurospora crassa
|
Charcot-Marie-Tooth disease type 2D ( CMT2D ) is a dominantly inherited peripheral neuropathy caused by missense mutations in the glycyl-tRNA synthetase gene ( GARS ) . In addition to GARS , mutations in three other tRNA synthetase genes cause similar neuropathies , although the underlying mechanisms are not fully understood . To address this , we generated transgenic mice that ubiquitously over-express wild-type GARS and crossed them to two dominant mouse models of CMT2D to distinguish loss-of-function and gain-of-function mechanisms . Over-expression of wild-type GARS does not improve the neuropathy phenotype in heterozygous Gars mutant mice , as determined by histological , functional , and behavioral tests . Transgenic GARS is able to rescue a pathological point mutation as a homozygote or in complementation tests with a Gars null allele , demonstrating the functionality of the transgene and revealing a recessive loss-of-function component of the point mutation . Missense mutations as transgene-rescued homozygotes or compound heterozygotes have a more severe neuropathy than heterozygotes , indicating that increased dosage of the disease-causing alleles results in a more severe neurological phenotype , even in the presence of a wild-type transgene . We conclude that , although missense mutations of Gars may cause some loss of function , the dominant neuropathy phenotype observed in mice is caused by a dose-dependent gain of function that is not mitigated by over-expression of functional wild-type protein .
Charcot-Marie-Tooth disease ( CMT ) is a heterogeneous group of inherited neuropathies affecting approximately 1 in 2 , 500 people [1] . CMT is divided into type 1 forms , characterized by demyelination and decreased nerve conduction velocity , type 2 or axonal forms , characterized by axon loss and reduced evoked potential amplitudes , and intermediate forms having features of both demyelinating and axonal neuropathy [2] , [3] . As the genetic causes of CMT have been identified , shared mechanisms have been elucidated that help explain the myelin degeneration in CMT type 1 and axon degeneration in CMT type 2 . Disruption of myelin structure through mutation of proteins produced by peripheral Schwann cells is a recurring mechanism in type 1 CMTs [4]–[6] . Defects associated with vesicle trafficking [7] , [8] , mitochondrial morphology [9]–[11] , and cytoskeletal integrity [12] , [13] have each been implicated in multiple axonal forms of CMT . Other axonal and intermediate CMTs have been linked to mutations in tRNA synthetase genes . The first to be identified and best characterized is CMT type 2D , caused by mutations in the glycyl-tRNA synthetase gene ( GARS , MIM ID 601472 ) [14] . Subsequently , mutations in tyrosyl-tRNA synthetase ( YARS , MIM ID 608323 ) were identified in patients with dominant intermediate CMTC [15]; a single missense change in the alanyl-tRNA synthetase gene ( AARS , MIM ID 613287 ) was associated with axonal CMT2N [16]; and most recently compound heterozygous frame shift/missense mutations in the lysyl-tRNA synthetase gene ( KARS , MIM ID 613641 ) were reported in a patient with recessive intermediate CMTB [17] . While human genetic studies have implicated mutations in multiple tRNA synthetase genes , the pathogenic mechanism for these neuropathies is still unclear , although a shared mechanism is an attractive hypothesis [18] . In particular , it is unclear whether the mutations result in a pathological gain of function , a partial loss of activity related to translation , an impact on an unknown , noncanonical activity , or a combination of these mechanisms . tRNA synthetases covalently link tRNAs with their cognate amino acids to translate the genetic code . These enzymes serve an essential , nonredundant role in protein synthesis . It has been suggested that a reduction of this tRNA-charging function could result in neuropathy , and peripheral nerves with long , large-diameter axons may be especially vulnerable to decreased activity because of their unusual transport and metabolic demands [15] , [19] . Consistent with this , several disease-causing mutations in GARS are associated with a reduction in charging function in cell-free assays , and this is roughly correlated with a decreased ability to rescue nonviability in yeast caused by deficiency of GRS1 , the ortholog of GARS . However other mutations do not impair this function [19]–[21] . Structural studies have shown that many of the mutations alter dimer association , affecting homodimer formation that is essential for tRNA-charging activity [20] , [22] . Furthermore , all mutations tested alter the subcellular distribution of GARS in transfected cells , also suggesting a possible loss of function at the cellular level through mislocalization , even if charging activity is preserved [19]–[21] , [23] , [24] . Two mouse models of CMT2D that share pathological features with the human disease , with differing severity , are caused by dominant amino acid substitutions in Gars . The GarsNmf249 allele ( hereafter abbreviated Nmf249 ) causes reduced body weight and impaired mobility in heterozygous mice [25] . Axon number and neuromuscular junction ( NMJ ) morphology are normal at post-natal day 7 , but subsequently axons are lost without a reduction in myelin thickness; NMJs show partial and sometimes complete denervation . The Nmf249 allele is an insertion in the Gars gene that substitutes lysine and tyrosine for proline at position 278 in the mouse GARS protein , equivalent to a P234KY change in human GARS ( Note: numbering differences are because the human annotation does not consider the N-terminal mitochondrial localization signal appended through alternative start codon usage ) . The GarsC201R allele ( hereafter abbreviated C201R ) is less severe and was identified in a chemical mutagenesis screen . In addition to impaired grip strength , these mice have impaired motor control , diminished muscle force , reduced weight , a shift towards smaller axon diameters , and some muscle denervation [26] . The mouse C201R substitution is equivalent to C157R in human GARS . These two alleles demonstrate the spectrum of phenotypic severity in mice and provide a range of tests that can be used to quantify the effects on neuromuscular function . Previous studies in mice are consistent with either a pathological gain-of-function for the mutant protein , or a partial loss-of-function , or both . Mouse and human mutations both cause dominantly inherited neuropathy . Moreover , mice heterozygous for a gene trap allele ( GarsXM256/+ , a presumed null allele , hereafter abbreviated XM256 ) do not have a phenotype , arguing against a simple loss-of-function and ruling out haploinsufficiency as a cause of the neuropathy phenotype [25] . As expected for a gene with such a critical activity , homozygous gene trap mice die as embryos . Mice homozygous for the C201R allele are more severely affected than heterozygotes of either mutant allele and die at about two weeks of age [26] . This increased severity may be the result of doubling a pathological gain of function associated with the C201R protein , or the inability of the mutant protein to actively perform its normal function , or a combination of these effects . Consistent with the inability of the mutant protein to sustain its normal function , both the C201R and the Nmf249 mutations fail to complement the loss-of-function XM256 allele , resulting in embryonic death in the absence of wild-type protein , without an increase in the genetic dosage of the mutant allele [25] , [26] . The embryonic death of these mice may indicate that wild-type GARS is mitigating a toxic gain of function , or that the mutant proteins do not retain their normal function , or it may indicate a combination of these mechanisms . We hypothesized that a partial loss-of-function could be corrected by transgenic over-expression of a functional wild-type GARS protein , whereas a pathological gain-of-function could be independent of wild-type activity and therefore would not necessarily be corrected by increased wild-type expression . In order to determine whether increased wild-type GARS rescues the Gars mutant mice , we crossed transgenic mice that over-express the wild-type human GARS gene to both the Nmf249/+ and C201R/+ mice , and analyzed the effects on the phenotype . We found a recessive reduction in perinatal viability in C201R as a homozygote or in combination with the XM256 gene trap allele , which could be rescued by wild-type GARS over-expression . However , wild-type over-expression did not substantially mitigate the neuropathy phenotype in heterozygous Nmf249/+ or C201R/+ mice , consistent with a predominant gain of function as the cause of peripheral neuropathy in these mice .
Wild-type human GARS was expressed in mice using a transgene construct with the full-length human GARS open reading frame under the control of a CAG promoter [27] , which is a fusion of the CMV early enhancer and the chicken β actin promoter and leads to strong ubiquitous transcription of downstream elements ( Figure 1A ) . Two independent transgene founder strains , designated Transgene A ( TgA ) and Transgene D ( TgD ) , were identified and used in this study . These two lines over-express GARS in spinal cord and sciatic nerve at similar levels ( >10 times endogenous levels ) , as measured by immunoblotting ( Figure 1B ) . In order to examine in situ expression of the transgenic protein in relevant cell types , we excised and fixed the sciatic nerve and teased the fibers apart to improve antibody penetration and to allow visualization of individual axons . Endogenous GARS is present at low levels in the sciatic nerve ( Figure 1C and [21] ) . In exposure-matched confocal images , anti-GARS staining was increased in animals with either TgA or TgD over the endogenous levels in strain matched FVB/N control mice without the transgene . The pattern of GARS immunoreactivity in transgenic mice was also similar to that of wild type mice , with staining found in both the axon and Schwann cells , suggesting the transgenic protein localizes normally ( Figure 1C ) . Therefore , the transgenes produce protein that is present in Schwann cells and transported to peripheral axons , as indicated by overlapping neurofilament staining . To examine the effect of over-expressing wild-type GARS on the neuropathy phenotype , the more severe Nmf249/+ mice were crossed with hemizygous transgenic mice and the four resulting F1 genotypes were analyzed: wild type , WT; Tg , Nmf249/+ , and Nmf249/+; Tg . The mice were analyzed at post-natal day 30 ( P30 ) . Mice with the transgene had much stronger levels of GARS protein expression than non-transgenic littermates in spinal cord and sciatic nerve on immunoblots of animals with both wild-type and Nmf249/+ backgrounds ( Figure 1D , 1E ) . Transgene expression was confirmed by immunoblot in mice with each genotype for crosses with both Nmf249/+ and C201R/+ ( Figure S1 ) . There was no difference overall in GARS levels between wild type and Nmf249/+ or C201R/+ , however , both transgenic strains result in expression well above endogenous levels . Consistent with the increased GARS protein , aminoacylation activity was also increased , indicating the transgenic protein is enzymatically active . Homogenates from the spinal cord of wild type and WT;TgA and TgD mice were prepared and assayed for the activity of both GARS and alanyl tRNA synthetase ( AARS ) as an internal control . As anticipated , no increase in activity was seen for AARS ( Figure 1F ) , whereas GARS activity was increased at least 10 fold ( as judged by the initial rate of tRNA glycylation ) in each transgenic strain ( Figure 1G and data not shown ) . To assess the effect of the transgenic GARS on peripheral neuropathy , we examined the femoral nerve , which consists of a primarily motor branch innervating the quadriceps , and a primarily sensory branch that becomes the saphenous nerve and innervates the skin of the lower leg . In Nmf249/+ mice , both branches had a reduction in myelinated axon number , whereas C201R/+ mice had normal axon numbers [25] , [26] . We isolated motor and sensory branches of the femoral nerve from F1 progeny from our cross between Nmf249/+ mice and GARS wild-type transgenic mice at one month of age . The nerves were fixed and embedded , and semi-thin sections were stained with toluidine blue for quantification of axon number and size ( Figure 2A–2L ) . In these cross sections , the size of the femoral nerves was reduced in the presence of the Nmf249/+ allele ( Figure 2A–2F compared to Figure 2G–2L ) . This was quantified by counting myelinated axons , which showed on average a 26% reduction in axons in motor nerves with the Nmf249/+ allele compared to wild-type littermates . There was no significant improvement in the Nmf249/+ axon numbers in motor or sensory nerves in mice with TgA or TgD ( Figure 2M ) . We next examined the distribution of motor axon diameters to determine whether there was any improvement in motor nerve pathology that was not detected with the axon counts . A cumulative histogram of the frequency of observed axon diameters shows the distribution and range of axon diameters in this study . The plot shows a marked shift from large diameter axons ( 4–6 µm ) to small diameter axons ( 0–3 µm ) in Nmf249/+ mice ( Figure 2N ) . Both TgA and TgD showed small but significant improvements in axon diameter in Nmf249/+ mice by a nested-ANOVA analysis ( p = 0 . 006 ) . There was no impact of either transgene on axon diameter in an otherwise wild-type background . With and without the transgene , the Nmf249 allele significantly reduced mean axon diameter , while the proportional observed decrease in myelin thickness is not as dramatic ( Figure S2 ) . Consistent with the slight improvement in axon diameters observed in Nmf249/+ mice with TgA and TgD ( Figure 2N ) , there was trend towards improvement in nerve conduction velocity , but this was not significant . Nerve conduction in Nmf249/+ mice is significantly reduced to approximately 25% of wild-type velocities . Nmf249/+; TgA and Nmf249/+; TgD mice had NCVs that did not differ significantly from Nmf249/+ alone ( Figure 3A ) . Previous studies show that between 2 and 4 weeks of age , mice with the Nmf249/+ allele stop gaining weight and become significantly smaller than littermate controls [25] . Various factors are likely to contribute to the decreased weight . Denervation decreases muscle mass and probably compromises ability to feed . As a measure of overall health , we weighed the mice in this study . Consistent with measures of peripheral nerve function , mutant mice with TgD trended toward being heavier , but neither TgA nor TgD significantly improved the body weights of Nmf249/+ mice , and all mutant animals were still significantly lighter than littermate control mice ( Figure 3B ) . The loss of motor axons in peripheral nerves of Nmf249/+ mice also results in a disruption of the neuromuscular junction ( NMJ ) . Mature , healthy motor neurons innervate muscle with pretzel-shaped presynaptic terminals . During development , post-synaptic regions mirror the shape of the axon terminal in regions of specialization where acetylcholine receptors concentrate to define the muscle side of the NMJ . The loss of distal motor axons is reflected in the NMJs of Nmf249/+ mice , which are severely dysmorphic . Many junctions in mutant mice are partially or completely denervated by post-natal day 30 [25] . To further study whether over-expression of GARS affects the motor phenotype in CMT2D mice , we looked at NMJ morphology and occupancy . NMJs from wild-type mice with and without the transgene had normal “pretzel-like” morphology with full overlap between pre- and post-synaptic terminals ( Figure 4A–4C ) . In mutant mice ( Figure 4D ) , there are regions where the presynaptic markers are absent in areas where there is post-synaptic staining ( arrowheads ) . There are also post-synaptic junctions that have no associated nerve terminal , indicating that the muscle fiber has been denervated ( arrows ) . The morphology and occupancy of NMJs in Nmf249/+; TgA mice ( Figure 4E ) and Nmf249/+; TgD ( Figure 4F ) were not improved . In each animal , NMJs were scored based on the overlap between pre- and post-synaptic markers and classified as fully innervated , partially denervated , or fully denervated . This assessment of NMJ occupancy showed there was no significant improvement in mutant mice with transgenes over mutant mice without transgenes ( Figure 4G ) . Therefore , with the exception of a slight increase in axon diameters , the over-expression of wild type GARS as a transgene did not lead to significant improvements in any phenotypic measure in the Nmf249/+ mice . To further substantiate these findings , we also tested the effects of both TgA and TgD in a second pathological Gars allele . The milder CMT2D disease model , C201R/+ , has less severe overt neuromuscular phenotypes than the Nmf249/+ mice . In this model , behavioral measures of peripheral nerve dysfunction are useful to detect the subtler phenotype . One behavioral measure is a wire hang test of grip strength . Mice were placed on a wire grid that was then inverted and the time that mice were able to suspend themselves was recorded . At 3 and 6 weeks of age , wild-type mice are often able to hang for a full minute , when the test is stopped . Neither transgene significantly improved performance on this test at either age tested ( Figure 5A–5D ) . To look for subclinical improvements in motor unit function , we tested nerve conduction on mice from this cross as well . Nerve conduction in C201R/+ mice is significantly reduced to approximately 55% of wild-type levels . Neither TgA nor TgD significantly improved NCVs in the C201R/+ mice ( Figure 5E , 5F ) . In summary , there were trends towards slight and variable improvements in body weight , axon diameter , and NCV in CMT2D mouse models when wild-type GARS is ubiquitously over-expressed , but none of these improvements were statistically significant , and the mice still have compromised motor function assessed by behavioral , histological , and electrophysiological measures compared to control animals . Although there was a robust increase in wild-type GARS protein detected by immunoblotting in both TgA and TgD , and animals with the transgenes had significantly higher tRNAGly charging activity , it remained to be demonstrated that the transgene products in these mice can substitute for a loss of wild-type Gars . Human GARS can functionally replace the fruit fly ortholog , Aats-gly [28] , but does not rescue yeast lacking GRS1 ( A . A . unpublished data ) . To confirm that our human GARS transgene could replace mouse Gars , we tested whether the transgenes could restore wild-type function in place of the XM256 loss-of-function gene trap allele [25] . The XM256 allele unambiguously causes a loss-of-function by intercepting splicing and reducing mRNA levels of Gars assayed by northern blot , as well as reducing enzymatic activity in tissue homogenates from heterozygous mice [25] . Compound heterozygotes of the gene trap allele with either mutant allele ( C201R/XM256 and Nmf249/XM256 ) die embryonically [25] , [26] . We crossed XM256/+; TgA or TgD mice with C201R/+ mice , and the offspring included both viable C201R/XM256; TgA and C201R/XM256; TgD mice . This shows that both TgA and TgD were able to restore viability by substituting for the endogenous wild-type Gars allele . We expected C201R/XM256; Tg mice to have a mild neuropathy because of the pathogenic C201R allele , and “full rescue” would therefore constitute viable mice with a phenotype comparable to C201R/+ . Chi-square analysis showed that C201R/XM256; TgA and C201R/XM256; TgD mice were born at expected Mendelian ratios ( 6/48 , p = 1 . 0 , and 4/63 , p = 0 . 14 , respectively ) , while C201R/XM256 mice without the transgenes were not viable , as expected , and represented a significantly absent class ( p = 0 . 009 , p = 0 . 003 , respectively ) . In addition to restoration of viability , the C201R/XM256 mice with the transgenes were restored to a C201R/+-like neuropathy . The rescued mice had femoral nerve pathology and axon numbers that were not significantly different from C201R/+ mice or controls at eight weeks of age ( Figure 6A–6J , 6L ) . As previously reported , neither the XM256/+ nor the C201R/+ mice had a decrease in myelinated axon number in the motor or sensory branch of the femoral nerve , whereas the Nmf249/+ mice do have reduced axon numbers ( Figure 6 and [25] , [26] ) . Therefore , the rescued mice do not show an increased severity in their neuropathy by this measure . We also tested this functionally by measuring nerve conduction velocities , which are normal in XM256/+ mice ( Figure 6K ) , but are significantly reduced in C201R/+ mice ( Figure 5E and 5F , Figure 6K ) . Conduction velocities in rescued mice were significantly below control values , and were not significantly different than C201R/+ values . To further verify that the transgenes fully rescued the neuropathy to the severity anticipated for C201R/+ , we also examined NMJ morphology and occupancy at 8 weeks of age . The NMJs of XM256/+ mice are indistinguishable in morphology and occupancy from wild-type mice ( Figure 7A and not shown ) , and form complex pretzel structures with complete overlap between pre and post-synaptic markers . NMJs in C201R/+ mice ( Figure 7B ) have regions of immature morphology or denervation that are noticeably different from wild-type , but are not as dysmorphic as the NMJs in Nmf249/+ mice . C201R/XM256 mice with TgA or TgD had neuromuscular junction morphology similar to that of C201R/+ mice ( Figure 7C , 7D ) . No significant difference in the proportion of NMJs that were fully occupied was observed between C201R/+ , C201R/XM256; TgA , and C201R/XM256; TgD mice ( Figure 7E ) . While the severity of the neuropathy was the same in C201R/+ and C201R/XM256; Tg mice , the rescued mice had significantly lower body weights than wild type or XM256/+ animals ( Figure S3A ) . The muscle weight/body weight ratio was not reduced in these mice , suggesting that the lower body weight was not a result of neuropathic muscle degeneration ( Figure S3B ) . Therefore , the reduced body weight probably reflects some insufficiency in transgene expression in other tissues . However , the viability of compound heterozygous C201R/XM256 mice with TgA and TgD indicates that both produce functional protein and both are capable of substituting for a wild type allele of Gars . To examine the effects of increasing the genetic dose of the mutant alleles of Gars and to further parse if there is a loss-of-function component to the amino acid substitutions , we generated C201R homozygotes and C201R/Nmf249 compound heterozygotes , both with and without TgD . C201R homozygous mice have a more severe neuropathy phenotype than C201R/+ heterozygotes , and typically die at about two weeks of age [26] . It is unclear whether the more severe phenotype in homozygotes is due to a double-dose of a toxic mutant protein , to a compounded loss-of-function , or a combination of these effects . Based on the ability of TgD to substitute for a wild type Gars allele in rescuing viability in combination with XM256 , we hypothesized that a loss of function would be corrected by the presence of the transgene , whereas increased toxicity from the higher dose of mutant protein would not be corrected , based on the inability of the transgene to improve the neuropathy phenotype in C201R/+ mice . Consistent with previous reports , we found that C201R/C201R mice were subviable ( X2 p = 0 . 016 ) [26] . Only two homozygous C201R mice were recovered in 69 offspring ( 1/8 anticipated ) , and these died by P12 before they could be analyzed . However , C201R/C201R; TgD mice were born at expected Mendelian ratios ( 11/69 , X2 p = 0 . 39 ) , and consistently lived to post-natal day 17 , when tissues were collected and analyzed . The maximum observed lifespan for these mice was to P20 . Despite the restoration of wild-type GARS function with TgD , these mice had a more severe neuropathy than C201R/+ heterozygotes . The C201R/C201R;TgD mice had approximately a 50% reduction in axon numbers in the motor branch of the femoral nerve ( Figure 8A , 8B , 8D , 8G ) , and the mice were <5 grams in weight at P17 ( Figure 8H ) . Neuromuscular junction defects were similarly increased in severity ( Figure 8I , 8J , 8L , 8M , 8P ) . At P17 , wild-type NMJs have developed into mature pretzel shapes , but C201R/+ NMJs are arrested at a less-mature , plaque-like morphology , and show an increased incidence of partially innervated junctions . The C201R/C201R;TgD mice demonstrated frank denervation at almost half of the postsynaptic sites . In agreement with this , we could not obtain nerve conduction velocities from these mice , because muscle action potentials were too small to reliably record ( n = 8 ) . Thus , the reduced viability embryonically and in neonates seen in C201R homozygous mice was corrected by the TgD , as demonstrated by the recovery of C201R/C201R;TgD mice at the expected Mendelian ratios and their survival to P17 . However , the increased genetic dosage of the C201R allele leads to a more severe neuropathy . To further examine this effect of genetic dosage and apparent recessive partial-loss-of-function , we also made compound heterozygous C201R/Nmf249 mice . Interestingly , both C201R/Nmf249 and C201R/Nmf249; TgD mice were viable and born at expected Mendelian frequencies ( 5/33 , X2 p = 0 . 95 and 4/33 , p = 0 . 65 , respectively ) . Considering that both C201R/XM256 and Nmf249/XM256 are nonviable in the absence of a wild-type transgene , the viability of C201R/Nmf249 mice suggests that there is intragenic complementation between the two mutant alleles that alleviates the loss-of-function and subsequent reduction in viability at birth . Like homozygous C201R/C201R; TgD mice , the motor branch of the femoral nerve is noticeably smaller and axon numbers are significantly reduced in C201R/Nmf249 and C201R/Nmf249; TgD mice compared to wild-type or heterozygous littermate controls ( Figure 8A–8G ) . No significant difference in axon numbers was seen between the C201R/C201R; TgD , C201R/Nmf249 , and C201R/Nmf249; TgD genotypes . The same qualitative and quantitative differences were seen in the sensory nerves of these animals ( Figure S4 ) . The overall health and overt appearance of the compound heterozygous mice was better than that of homozygous C201R/C201R;TgD mice . The body weights of C201R/Nmf249 and C201R/Nmf249; TgD mice were significantly lower than C201R/+ mice ( Figure 8H ) , and C201R/C201R; TgD weighed significantly less than C201R/Nmf249 mice . Morphological changes seen in the neuromuscular junctions of C201R/Nmf249 and C201R/Nmf249; TgD mice were also more severe than either allele as a heterozygote and reflected the axon loss seen in the femoral nerves . Like C201R/+ mice at P17 , Nmf249/+ mice have partially denervated NMJs ( Figure 8K ) with areas of disorganized post-synaptic staining , but also more examples of complete denervation . Like the C201R/C210R;TgD mice , compound heterozygotes with or without TgD had even more dysmorphic NMJ morphology than Nmf249/+ heterozygotes , with a majority of NMJs that were partially or fully denervated and very few that were fully innervated ( Figure 8N–8P ) . There were significantly more denervated NMJs in C201R/C201R; TgD , C201R/Nmf249 , and C201R/Nmf249; TgD mice compared to Nmf249/+ mice ( Figure 8P ) . Compound muscle action potentials were again too small to reliably record in C201R/Nmf249 ( n = 4 ) , and C201R/Nmf249; TgD ( n = 5 ) mice . Therefore , the presence of TgD did not alter viability , axon number , body weight , or NMJ occupancy of the compound heterozygous mice , consistent with intragenic complementation improving the recessive loss-of-function sub-viability phenotype observed in C201R homozygotes . In both C201R/Nmf249 compound heterozygotes and C201R homozygotes , the severity of the neuropathy increases as the genetic dosage of the mutant Gars increases , even in the presence of the wild-type transgene .
Overall , no significant improvement in axonopathy phenotypes was seen in CMT2D model mice over-expressing wild-type GARS . Two transgenes with similar levels of expression were used in these crosses and yielded effectively the same results . Neither transgene prevented axon degeneration or improved nerve conduction velocity or NMJ morphology and occupancy in the Nmf249/+ mice at one month of age . The only positive effect of the transgenes was a minor improvement in axon diameter . Similarly , neither transgene improved behavioral measures at three or six weeks of age , or NCVs at eight or twelve weeks of age in C201R/+ mice . Thus , over-expression of wild-type GARS did not suppress the dominant neuropathy phenotype . It is also notable that the over-expression of wild-type GARS did not cause any phenotype on its own in either transgenic line . These crosses , and the observation that XM256/+ mice do not have a neuropathy , show that the mutant protein itself is toxic and causes peripheral nerve degeneration . The toxicity can be intensified , and the neuropathy worsened , by increasing the dose of mutant protein in either homozygotes or compound heterozygotes . Lifespan , NMJ occupancy , axon numbers and body weight are significantly reduced in C201R/Nmf249 , C201R/Nmf249; TgD , and C201R/C201R; TgD mice below the levels of Nmf249/+ and C201R/+ mice , which only have one copy of the mutant protein . This is consistent with experiments with YARS in Drosophila , which also indicate that the mutant tRNA synthetase has a dose-dependent toxicity [29] . Although the peripheral axon degeneration is caused by toxicity of the mutant protein , the mutations do have loss-of-function characteristics . Homozygous C201R mice are subviable , and neither allele is viable in combination with the gene trap allele , despite the Nmf249/+ P278KY protein being fully active in cell-free activity assays of amino acylation and tRNA charging [25] . The embryonic lethality observed in these Gars alleles is probably not related to the neuropathy phenotype . In fact , a functioning nervous system is not required during embryonic development . Mice deficient for proteins that are crucial for the function of the central and peripheral nervous system are born in the anticipated numbers , but do not survive independently after birth [30]–[32] . GARS is necessary for translation in every cell , and loss of function in non-neurological tissue is a likely cause of the embryonic lethality . With transgenic over-expression of wild-type protein , we were able to restore full viability to C201R/XM256 mice , which otherwise die embryonically , and C201R/C201R mice , which are otherwise subviable . It is notable that we were unable to rescue XM256 as a homozygote with either transgene . This may be due to a closely linked second mutation on the gene trap chromosome , but is more likely due to an insufficiency of transgene expression at some critical point in development . This is supported by the reduced body weight of XM256/C201R mice with transgene rescue despite full rescue of viability and neurological function equivalent to a wild type allele . Presumably , the C201R allele provides sufficient GARS activity in whatever tissue may be lacking transgene expression , allowing rescue of the point mutation over the gene trap . Thus , over-expression of wild-type GARS can rescue postnatal viability , but does not improve the neuropathic phenotype , suggesting the loss of viability is caused by a loss of function for which the transgene can compensate , whereas the neuropathy is a gain of function that the transgene cannot correct . C201R homozygous mice have decreased viability , and when they are born they have a severe neuropathy . We expected C201R/Nmf249 mice to be at least as severe because the Nmf249 allele is more pathogenic than the C201R allele despite its normal enzymatic activity . Surprisingly , the compound heterozygous mice were as healthy as or even healthier than C201R homozygotes with TgD . The C201R/Nmf249 mice were fully viable and weighed significantly more than C201R/C201R; TgD mice , although their neuropathy was markedly more severe than either allele as a heterozygote . Therefore , the C201R and Nmf249 alleles are capable of intragenic complementation in regard to the loss-of-function phenotype , but still display “additive” severity for the gain-of-function neuropathy phenotype . Over-expression of wild-type GARS did not improve the phenotype in the compound heterozygous mice , which are severely affected because they express two mutant versions of the protein . This suggests that the loss-of-function aspect of the C201R homozygotes that is rescued by the transgene is not a factor in the compound heterozygotes , and that the dose of the mutant protein determines the severity of the neuropathy . It also suggests that this loss of function , perhaps in enzyme charging function , differs between the alleles , because C201R/Nmf249 mice are more viable than C201R/C201R mice even though the Nmf249 allele is more neurotoxic than the C201R allele . Dominant mutations in GARS , YARS , and AARS all cause CMT [14]–[16] . Our results suggest that mutant forms of GARS adopt a pathological function that may be impacting the normal role of GARS in translation , but that the loss-of-function effects are recessive , and would not be an important factor in CMT patients with dominantly inherited disease . Instead , the neuropathy is a caused by a gain of function , demonstrated by the inability of functional wild-type transgenic GARS to rescue the phenotype either by restoring lost activity or outcompeting this pathological function . One patient reported to carry compound heterozygous mutations in KARS may be the exception to this , but it is notable that this genotype was associated with peripheral neuropathy with additional neurological and non-neurological symptoms [17] . The interplay between normal protein function and pathogenic function has been dissected in other neurodegenerative diseases . For example , hereditary sensory and autonomic neuropathy ( HSAN ) type 1A is caused by mutations in the serine palmitoyl transferase gene ( SPTLC1 ) , which alter the protein's amino acid substrate specificity so that the mutant produces two neurotoxic atypical deoxysphingoid bases [33]–[35] . Over-expression of wild-type SPTLC1 rescued a transgenic mouse model of the disease by outcompeting mutant forms of SPTLC1 in heterodimer formation with SPTLC2 , restoring the substrate specificity , lowering levels of neurotoxic sphingoid bases , and demonstrating that mutant SPTLC1 is not inherently toxic [36] . Our work suggests that mutant GARS protein is toxic independent of wild-type protein levels . These results are more like what has been observed in SOD1-linked amyotrophic lateral sclerosis , which is caused by dominant mutations and is not improved with wild-type over-expression [37] . These conclusions have implications for therapeutic approaches . To reduce the effect of mutant GARS , the expression of the mutant allele must be diminished . Future therapeutic approaches should focus on allele specific knockdown of the mutant gene expression; alternatively , the specific pathways affected by mutant GARS toxicity could be identified and targeted .
The Ins-CMV-C-B-A vector [38] was modified to include a Gateway conversion cassette ( Invitrogen ) in the multiple cloning site , which includes a ccdB cassette flanked by attR1 and attR2 recombination sequences . A Gateway LR clonase reaction was used to insert a PCR amplicon of the GARS cDNA ( human ) into the pINS2-Gateway vector . The cDNA amplicon that was inserted into pINS2 included 47 basepairs of the endogenous GARS 5′ UTR upstream of the start site of the mitochondrial isoform , and 19 basepairs of endogenous 3′UTR flanked by 5′ and 3′ untranslated regions ( UTR ) from rabbit β globin also containing a polyadenylation signal at the 3′ end . The cDNA and control elements are flanked by two chicken β-globin 5′HS4 insulators , which have been shown to reduce variability in transgene expression caused by position effects of insertion site [39] . Pronuclear injection of this construct into single cell FVB/N embryos was performed in the NHGRI Transgenic Mouse Core according to existing protocols [40] . All mouse husbandry and procedures were conducted according to the NIH Guide for Care and Use of Laboratory Animals and were approved by NINDS or The Jackson Laboratory Animal Care and Use Committee . Tail , toe or ear tissue was lysed with proteinase K incubation at 55°C and boiled for 10 min to inactivate the proteinase K . DNA derived from the mouse tissue was then used in PCR to determine genotype . Primers GARS WT Tg F ( 5′-CCCATTACTGGAAATGATCTA-3′ ) and GARS WT Tg R ( 5′-TTTCCGAGCGGACTGTCCGC-3′ ) , which anneal to exons 7 and 9 , respectively , were used to determine if the wild-type transgene was present . Primers targeting Gars intron 6F ( 5′-GCCTTGTTCTGTAACGTTTGCAC-3′ ) and a primer specific to the Nmf249 allele ( 5′-CCAGGCATATTTCCTCCATATTT-3′ ) were used to identify mice with the Nmf249 mutation [25] . Primers Gars C201R F ( 5′-CACGTGCTTGCTCTAGCAAGA-3′ ) and Gars C201R R ( 5′-GTCTACCACTGAACACAGTCC-3′ ) were used in PCR reaction , and the product was digested with HhaI restriction enzyme . PCR products containing the pathogenic mutation are digested into two smaller bands [26] . Primers BgeoR ( 5′-CGCCAGGGTTTTCCCAGT-3′ ) and En2-i1F ( 5′-AATGCCCAACACTTGTATGG-3′ ) were used to determine if the XM256 gene trap allele was present . To screen for XM256/XM256 mice , primers flanking the gene trap insertion 519 bp into intron 2 of Gars , GarsXMvsWT2F ( 5′-GCTTCCGCACTACCTGAACCCAAACT-3′ ) and GarsXMvsWT2R ( 5′-TGAATTCAGCAGCCCCCTCTGTACCC-3′ ) , were used . No XM256/XM256 mice were identified , with or without the transgene . PCR amplification indicated the wild-type allele was present . All genotyping products were resolved on 2% agarose gels with ethidium bromide ( Sigma , St . Louis , MO ) . Nmf249 mice are maintained on a C57BL/6 background and are occasionally outcrossed to CAST/Ei to improve their ability to breed [21] . C201R mice were originally on a mixed C57BL/6 and C3H background and subsequently bred into a C57BL/6 background . The TgA and TgD alleles were maintained on a pure FVB/N background with one exception: the TgA mice that were used in the cross with C201R mice were on a FVB/N X C57BL/6 F1 hybrid background . Therefore , experiments were done primarily in a [FVB/N X BL/6] F1 background unless two matings were required to generate homozygotes or compound heterozygotes , in which case mice were effectively in an [N2] C57BL/6 background . All control animals were siblings of the experimental genotypes . Spinal cord and sciatic nerve were isolated from animals immediately after they were euthanized by CO2 inhalation . The tissues were frozen in liquid nitrogen and stored at −80°C . The tissues were then homogenized in 1% NP-40 in phosphate buffered saline ( PBS ) supplemented with Protease Inhibitor Cocktail Tablets ( Roche , Basal , Switzerland ) using a PowerGen Model 125 Homogenizer ( Fisher Scientific , Pittsburgh , PA ) then centrifuged at 14 , 000 g for 10 min at 4°C . Cleared homogenates were then sonicated at 4°C and centrifuged again at 14 , 000 g for 10 min . Protein concentrations were assessed using a Bradford assay ( BioRad , Hurcules , CA ) . 20 µg of protein was then analyzed by immunoblot . Protein lysates were resolved on Novex 10% Tris-Glycine Gels ( Invitrogen , Carlsbad , CA ) and transferred to an Invitrolon PVDF membrane for western blot analysis . Membranes were blocked with 5% skim milk in TBST ( 1× Tris-buffered saline , 0 . 1% Tween-20 ) , and incubated overnight with GARS rabbit polyclonal antibody ab42905 ( 1∶2 , 000 ) ( Abcam , Cambridge , MA ) and β actin mouse monoclonal antibody clone AC-74 ( 1∶10 , 000 ) ( Sigma Aldrich , St . Louis , MO ) diluted in blocking solution at 4° C . Following three 10 min washes in TBST , the blots were incubated with the appropriate horseradish peroxidase-conjugated secondary antibodies ( Jackson ImmunoResearch , West Grove , PA ) diluted in blocking solution . After three 10-min washes in TBST , the blots were developed using Western Lightening Plus-ECL , Enhanced Chemiluminescence Substrate ( Perkin Elmer , Waltham , MA ) . Teased nerve fibers were stained as described in the methods of [21] , [41] . In brief , sciatic nerves were excised , immediately placed in fresh 4% paraformaldehyde , and fixed on ice for 15 minutes . Nerves were then transferred to ice cold PBS for dissection and teasing . Using #5 forceps and 30 gauge needles , nerve sheaths were removed and the nerves were cut into 1 cm segments and teased apart at one end . The nerve segments were then transferred to a fresh Superfrost Plus Gold slides ( Fisher Scientific , Pittsburgh , PA ) and pulled from a drop of PBS onto a dry section of the slide to straighten the fibers for imaging . The slides were then dried overnight at room temperature and incubated in acetone at −20°C for 10 min . The samples were then rehydrated with two 5 min incubations in PBS and blocked with 5% normal goat serum in PBS with 0 . 5% Triton X-100 for 1 h at room temperature . Primary antibodies rabbit anti-GARS ( 1∶500 ) ( Abcam ) , mouse anti-neurofilament with the 2H3 antibody ( 1∶500 ) ( Developmental Studies Hybridoma Bank , Iowa City , IA ) were gently placed on the slide , covered with Parafilm coverslips ( Pechinery Plastic , Chicago , IL ) and stored in a humidified chamber overnight at 4° Celsius . After three 5-min washes in PBS , the samples were incubated in the following secondary antibodies diluted 1∶1 , 000 in blocking solution: AlexaFluor 555 goat anti-rabbit , and AlexaFluor 488 goat anti-mouse IgG1 ( y1 ) ( Invitrogen , Carlsbad , CA ) . The samples were covered with Parafilm coverslips and incubated for 2 h at room temperature . The samples were then washed three times in PBS for 5 min each in watch glasses and mounted with Vectashield ( Vector Labs , Burlingame , CA ) . Aminoacylation assays were performed at room temperature in a reaction mixture containing 50 mM HEPES ( pH 7 . 5 ) , 20 mM KCl , 2 mM ATP , 5 mM MgCl2 , 1 mM DTT , 19 µM L-glycine ( or L-alanine ) , 1 µM 3H-L-glycine ( or 3H-L-alanine ) , 2 µM transcribed human tRNAGlyCCC [for GlyRS activity] or 120 µM yeast total tRNA ( Roche Diagnostics , Indianapolis , IN ) [for AlaRS activity] and 30 µg total protein from tissue homogenates . Reactions were initiated by addition of reaction mixture and tRNA to tissue homogenates . Aliquots were quenched at different time points and precipitated in 96-well Multiscreen filter plates ( Millipore ) as described previously [42] . After washing and elution by NaOH , samples were counted in a MicroBeta plate reader ( PerkinElmer Life Sciences ) . Initial rates were measured from slopes obtained by fitting the data to a non-linear regression curve using GraphPad Prism 5 software . For TgA , 3 wild type and 4 transgenic littermates were sampled at 9 weeks of age: for TgD , 4 wild type and 3 transgenic littermates were tested at 6 weeks of age . The sensory and motor branches of the femoral nerve were isolated and fixed overnight in 2% glutaraldehyde and 2% paraformaldehyde in a 0 . 1 M cacodylate buffer . The tissue was then processed for transmission electron microscopy and embedded in plastic before 0 . 5 µm sections were cut and stained with toluidine blue . For more information see [43] . For axon counting and axon diameter measurement the images were captured using a Nikon Eclipse E600 microscope with 40× and 100× objectives . Axon counts were done using the Cell Counter Plug-in in ImageJ . Left and right nerves were averaged . Axon diameters were measured using the Measure and Label Plugin , also in ImageJ . Mouse plantaris muscles were surgically removed and fixed in freshly prepared 2% paraformaldehyde in PBS for four hours . The samples were then transferred to a blocking and permeabilizing solution of 5% normal goat serum and 0 . 5% Triton-X 100 in PBS for 1 h before they were pressed between two glass slides using a binder clip for 15 min , after which they were returned to the blocking and permeabilizing solution . The samples were then incubated overnight at 4°C with 1∶1 , 000 dilutions of anti-SV2 and anti-neurofilament ( 2H3 ) primary antibodies ( Developmental Studies Hybridoma Bank , Iowa City , IA ) . After at least three 1 h washes in PBS with 0 . 5% Triton-X 100 , the samples were transferred to blocking and permeabilizing solution with AlexaFluor 488 goat anti-mouse IgG1 ( y1 ) ( Invitrogen , Carlsbad , CA ) and α-bungarotoxin conjugated with Alexa Fluor 594 . After incubation overnight at 4°C , the samples were washed three times for 1 h each and mounted with Vectashield mounting media ( Vector Labs , Burlingame , CA ) and imaged using a confocal microscope . Confocal images were gathered using a Carl Zeiss LSM 710 or Leica SP5 laser-scanning confocal microscope with a 63× objective . Z stacks were collapsed into projected images and merged using ImageJ ( NIH , http://rsb . info . nih . gov/ij/ ) . The color balance of the NMJ images was adjusted for clarity . Sciatic nerve conduction velocity was calculated by measuring the latency of compound motor action potentials recorded in the muscle of the left rear paw . The mice were anesthetized with 1% isofluorane and placed on a thermostatically regulated heating pad to maintain normal body temperature . Action potentials were produced by subcutaneous stimulation at the sciatic notch and at the ankle . For recording , the active needle electrode was inserted in the center of the paw and a reference electrode was placed in the skin between the first and second digits . Statistical tests were performed using GraphPad's Prism 5 software . Statistical significance was determined using a one-way ANOVA and a post hoc Tukey test for individual differences when appropriate . A threshold of p<0 . 05 was considered significant . The use of other tests is noted in the text . All results are presented as means ± SD .
|
Mutations in the glycyl-tRNA synthetase gene ( GARS ) cause Charcot-Marie-Tooth disease type 2D , a disease characterized by neuronal axon loss in the arms and legs , resulting in weakness and sensory problems . The GARS protein is essential for protein synthesis in every cell , and it has been difficult to determine whether the mutations result in disease because they impair this function or whether GARS somehow becomes toxic when it is mutated . We generated mice that overexpress normal GARS and mated these to two different mouse models of the disease to determine whether a restoration of normal function could prevent the disease . These crosses demonstrated that the mutant forms of GARS are toxic , and this toxic effect increases as the amount of mutant protein increases . Furthermore , this toxicity cannot be reduced or prevented by providing additional normal GARS . Therefore , these results suggest that , for most patients , therapies need to specifically target the mutant form of GARS or the toxic function .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"neurobiology",
"of",
"disease",
"and",
"regeneration",
"animal",
"genetics",
"genetic",
"mutation",
"neuroscience",
"gene",
"function",
"mutation",
"types",
"biology",
"neurological",
"disorders",
"neurology",
"neuromuscular",
"diseases",
"genetics",
"genetics",
"of",
"disease",
"genetics",
"and",
"genomics"
] |
2011
|
Charcot-Marie-Tooth–Linked Mutant GARS Is Toxic to Peripheral Neurons Independent of Wild-Type GARS Levels
|
Rabies is an ancient neglected tropical disease that causes tens of thousands of human deaths and millions of cattle deaths annually . In order to develop a new vaccine for potential use in bats , a reservoir of rabies infection for humans and animals alike , an in silico antigen designer tool was used to create a mosaic glycoprotein ( MoG ) gene using available sequences from the rabies Phylogroup I glycoprotein . This sequence , which represents strains more likely to occur in bats , was cloned into raccoonpox virus ( RCN ) and the efficacy of this novel RCN-MoG vaccine was compared to RCN-G that expresses the glycoprotein gene from CVS-11 rabies or luciferase ( RCN-luc , negative control ) in mice and big brown bats ( Eptesicus fuscus ) . Mice vaccinated and boosted intradermally with 1 x 107 plaque forming units ( PFU ) of each RCN-rabies vaccine construct developed neutralizing antibodies and survived at significantly higher rates than controls . No significant difference in antibody titers or survival was noted between rabies-vaccinated groups . Bats were vaccinated either oronasally ( RCN-G , RCN-MoG ) with 5x107 PFU or by topical application in glycerin jelly ( RCN-MoG , dose 2x108 PFU ) , boosted ( same dose and route ) at 46 days post vaccination ( dpv ) , and then challenged with wild-type big brown variant RABV at 65 dpv . Prior to challenge , 90% of RCN-G and 75% of RCN-MoG oronasally vaccinated bats had detectable levels of serum rabies neutralizing antibodies . Bats from the RCN-luc and topically vaccinated RCN-MoG groups did not have measurable antibody responses . The RCN-rabies constructs were highly protective and not significantly different from each other . RCN-MoG provided 100% protection ( n = 9 ) when delivered oronasally and 83% protection ( n = 6 ) when delivered topically; protection provided by the RCN-G construct was 70% ( n = 10 ) . All rabies-vaccinated bats survived at a significantly ( P ≤ 0 . 02 ) higher rate than control bats ( 12%; n = 8 ) . We have demonstrated the efficacy of a novel , in silico designed rabies MoG antigen that conferred protection from rabies challenge in mice and big brown bats in laboratory studies . With further development , topical or oronasal administration of the RCN-MoG vaccine could potentially mitigate rabies in wild bat populations , reducing spillover of this deadly disease into humans , domestic mammals , and other wildlife .
Rabies is a fatal viral zoonotic disease known to humans for nearly four millennia that continues to cause significant public health concern with over 50 , 000 human deaths every year [1] . Fortunately , over 15 million people receive post-exposure prophylaxis for rabies exposure , which effectively prevents rabies if administered promptly [2] . In Mexico and Central and South America , rabies transmitted by vampire bats is a tremendous public health and economic issue , as it threatens not only the people in these areas , but also an at-risk population of more than 70 million head of cattle [3–6] . Vampire bats were thought to have caused cattle losses in Latin America worth more than $40 million US in 1983 , and again in 1984 [7] , and these losses , coupled with the cost of measures to prevent bovine rabies , are a significant economic burden . Rabies virus ( RABV , Family: Rhabdoviridae , Genus: Lyssavirus ) has adapted to numerous mammalian reservoirs that maintain transmission , typically by bite , and as a result has evolved into specific lineages and variants . Bats are considered the primary evolutionary host of RABV [8] and harbor a diversity of other lyssaviruses , all of which cause rabies disease , with non-RABV lyssaviruses occurring in the Old World and Australia [9 , 10] . Lyssaviruses are divided into distinct phylogroups based on serological analysis and genome sequence [11] . While lyssaviruses within phylogroup I ( PG-I ) are considered cross-protective immunologically , epidemiologically important antigenic variation between vaccine strains and wild-type rabies viruses have been observed [12] and variable vaccine efficacy has been reported against some PG-I viruses[13] . In addition , numerous antigenic variants of rabies have been found in bats in the Americas [14] . In Brazil , nine different variants have been reported; in Mexico , at least 7 , and antigenic variants differ between bats species and geographic locations . Rabies in terrestrial wild mammals can be successfully controlled , and in some areas , eliminated through the use of oral rabies vaccination ( ORV ) campaigns [15–17] , but similar mass vaccination has not yet been attempted for wild bats . Recombinant viral-vectored vaccines have been developed to make use of the antigenicity of the RABV surface glycoprotein ( G ) . The main benefit of these viral-vectored constructs is their ability to induce immunity when given orally , which makes them effective and efficient for vaccinating wildlife . A vaccinia virus construct expressing the G protein ( or V-RG ) has been used extensively for wild carnivores , but this construct can cause vaccinia infection in humans that are inadvertently exposed to the vaccine , especially in immuno-compromised individuals [18–20] . More recently a similar vaccine has been developed and licensed using a human adenovirus vector ( ONRAB ) [21] , but to our knowledge , that vector ( and vaccine ) has not yet been tested in bats . Our previous study showed that RCN is a suitable vaccine vector for bats; it safely expressed exogenous antigens and induced significant immune responses following mucosal exposure of Tadarida brasiliensis bats [22] . The safety profile of the RCN vector has been evaluated previously [23–25] , and a RCN-based sylvatic plague vaccine is under evaluation in field trials in prairie dog populations [26] . In this study , we used G sequences from 664 RABV to design a novel PG-I lyssavirus mosaic glycoprotein gene ( MoG ) that could potentially provide broader antigenic coverage for the variety of rabies strains circulating in bats , and perhaps a more effective vaccine . We successfully expressed MoG in the RCN vaccine vector and then evaluated its efficacy in preventing rabies mortality in mice and big brown bats ( Eptesicus fuscus ) in laboratory challenge studies , comparing it to a previously reported RCN-G construct that expresses the CVS-11 glycoprotein [27] . Our results suggest that MoG is a successful rabies antigen as both mucosal and topical application of RCN-MoG protected against high-dose rabies virus challenge .
Recombinant viruses were generated and amplified on cell monolayers of rat embryonic fibroblasts ( Rat-2 , ATCC #CRL-1764 ) or African Green monkey ( Chlorocebus sabaeus ) kidney epithelial cells ( BSC40 , ATCC #CRL-2761 , or Vero , ATCC #CCL-18 ) . Cell cultures were maintained at 37°C and 5% CO2 in Dulbecco’s Modified Eagle Medium ( DMEM ) or Opti-MEM ( Life technologies , Madison , WI 53719 ) , supplemented with 2–5% fetal bovine serum ( FBS ) . Recombinant RCN-G [3] and wild-type RCN ( RCN-wt ) viruses were provided by the Centers for Disease Control ( CDC ) , Atlanta , GA , while the RCN-luc strain used in this study was previously described [28] . The RABV CVS-11 ( GenBank accession no AB069973 ) strain used in mouse challenge studies was provided by the Wisconsin State Laboratory of Hygiene and was amplified on baby hamster kidney cells ( BHK-21 , ATCC #CCL-10 ) in DMEM as described elsewhere [29] . The virus was titered by infecting BHK-21 cells in 96-well plates with serial dilutions in quadruplicate . After 72 hours , the cells were fixed with 80% acetone and subsequently probed with a FITC-conjugated rabies antibody ( LIGHT DIAGNOSTICS Rabies DFA Reagent 5100 , Millipore , Billerica , Massachusetts , USA ) to determine focus forming unit ( FFU ) titer . The wild type big brown bat variant RABV used for bat challenge has been previously described ( GenBank #JQ685920 . 1 ) ; it was isolated from the salivary glands of a naturally infected big brown bat in Pennsylvania during 2006 and subsequently passaged once through murine neuroblastoma cell culture [30] . The virus was provided under a cooperative research and development agreement with the CDC ( A06-3684 ) .
The antigenic coverage of the designed MoG sequence ( S1 ) achieves 61% exact matches of putative T cell epitopes with an epitope length set to 12 amino acids ( Fig 1A ) . This improves to 84% matches if 1 of those 12aa is allowed to be a mismatch ( off-by-1 ) and 92% for off-by-2 . This is similar to the results for previously described , effective mosaic proteins[43 , 44] . If the nominal epitope length is set to 9 amino acids , the coverage increases to 67% exact matches; 87% off by 1; 94% off by 2 ( Fig 1B ) . Comparing epitope coverage of the MoG to the other PG-I lyssaviruses used for its design , it is better than any single "wild type" virus ( Fig 1C ) . A comparison of amino acid sequences of four major and one minor PG-I antigenic sites reveal that MoG retains most RABV sequences ( Table 1 ) . Immunofluorescence assays of cultured cells infected with RCN-MoG , RCN-IRES-MoG , and RCN-G confirmed presence of rabies virus antigen when compared to the RCN-GFP negative control ( Fig 2A ) . Western blot analysis revealed bands visible at ~60kDa in the pellet of the RCN-MoG , RCN-IRES-MoG , and RCN-G infected cells , and absent in the negative control , demonstrating expression of an antigenic glycoprotein ( Fig 2B ) . The RCN-IRES-MoG seems to be slightly smaller and have a secondary band , which may indicate variation in glycosylation [46] or production of truncated forms of the MoG . Serum samples from mice ( n = 16 per group ) were tested by the RFFIT assay ( at CDC ) . All RCN-rabies constructs induced significant antibody titers when measured at 45 dpv ( Fig 3 ) . No significant differences in antibody levels were observed between groups ( P = 0 . 399 ) . Following rabies virus challenge , one mouse each from the RCN-G and RCN-luc groups were euthanized due to loss of ≥ 20% of their body weight within 3 days post challenge ( dpc; Table 2 ) . Two other mice , one in each of the RCN-G and RCN-IRES-MoG groups were found to have lost ≥ 20% of their body weight by14 dpc , the last day of the trial . All four of these mice were rabies negative by the dFA test ( Table 2 ) and were censored in the survival analysis . All other mice that were euthanized with signs of disease during the challenge were positive by dFA . All RCN-rabies treatment groups had statistically higher survival than the RCN-luc negative controls ( P<0 . 03 ) . All mice survived to day 14 in the RCN-MoG group compared to 50% ( 3/6 ) in the RCN-IRES-MoG group , 80% ( 4/5 ) in the RCN-G group and 0/5 in the RCN-luc group . Although no significant difference ( P >0 . 05 ) in survival was detected between groups that received the three rabies vaccines ( Fig 4 ) , RCN-IRES-MoG was not included in further studies in bats . After inoculation with RCN-vectored vaccines , no signs of clinical disease were evident in any of the bats . Topically vaccinated bats also showed no evidence of adverse effects due to the glycerin jelly application or the vaccine virus . No significant change in weight was evident in the groups after initial vaccination or boost ( P>0 . 05 , S1 Fig ) . After initial vaccination , 2/9 bats from the RCN-MoG ON group had titers between 0 . 1–0 . 4 IU/ml and 4/10 bats from the RCN-G ON group responded with titers >0 . 5 IU/ml , while no detectable antibodies were found in any of the bats from the RCN-luc group or the RCN-MoG topically vaccinated bats ( Table 3 , Fig 5 ) . After boost , 2/8 bats tested in the RCN-MoG ON group had titers > 0 . 5 IU/ml , and an additional 4 bats had titers of 0 . 1–0 . 4 . In the RCN-G ON group , 6/10 bats had RVNA levels ≥ 0 . 5 IU/ml , 3 had levels of 0 . 1–0 . 4 , and one bat had no detectable RVNA . Even though more bats that received RCN-G ON had RVNA titers compared to RCN-MoG ON , no significant difference in titer was detected between these groups ( P = 0 . 22 ) . Bats in the RCN-luc and RCN-MoG topically vaccinated groups had no detectable neutralizing antibodies prior to challenge . After challenge with rabies virus , all vaccine treatment groups had significantly greater ( P ≤ 0 . 02 ) rates of survival than the negative control ( RCN-luc ) group ( Fig 6 ) . The first confirmed rabies deaths occurred at 12 dpc and the final at 27 dpc . The majority of mortalities occurred between 12 and 19 dpc . All bats administered RCN-MoG by the ON route survived challenge , although interestingly only 2/8 had pre-challenge RVNA levels above 0 . 5 IU/ml ( Table 2 , Fig 5 ) . Likewise , 5/6 ( 83% ) of the bats that received RCN-MoG topically survived challenge , despite none having seroconverted . Comparatively , 7/10 of the RCN-G ON vaccinated group survived challenge , including two bats with antibody titers below 0 . 5 IU/ml . Interestingly , one bat in this group with a titer of 0 . 5 IU/ml succumbed to rabies challenge and 1/8 bats immunized with RCN-luc survived challenge . No clinical signs were observed in any of the surviving bats . Direct FA confirmed rabies diagnoses consistent with our survival analysis ( Table 2 ) . All bats that were found dead or euthanized were rabies positive , while all remaining bats at the study end were negative .
Rabies spillover from wildlife , particularly by vampire bats ( Desmodus rotundus ) , continues to be an important public health and economic issue in Mexico and Central and Latin America [17 , 47] , despite using culling of bats as a control measure[48–50] . In this study , we demonstrated that an in silico designed mosaic lyssavirus PG-I glycoprotein ( MoG ) is an effective immunogen against rabies in mice and bats . Furthermore , a recombinant RCN-vectored vaccine expressing MoG , delivered by mucosal or topical routes , protected bats against rabies challenge . While survival did not differ significantly among any of the vaccine treated groups ( P = 0 . 08 ) , RCN-MoG provided 100% protection in ON immunized bats challenged with a wild-type big brown bat RABV variant . As in our previous study [22] , both RCN vaccine constructs were safe; no evidence of morbidity was observed in treated bats . Though these results are very promising , additional challenge studies with other bat RABV variants , are needed to assess whether our bioinformatically designed RCN-MoG vaccine is an improvement over RCN-G . Currently available rabies vaccines , which are almost entirely developed from lab-adapted strains ( e . g . CVS-11 ) , are considered protective against all PG-I lyssaviruses when given at the recommended dose and schedule . However , antigenic variation in PG-I strains has been identified and may lead to inconsistent protection [12 , 13] . The CVS-11 strain has been passaged over a thousand times in rabbit and mouse brains and cell culture [51] . One study showed that 5 . 1 units of antigenic difference exists between CVS-11 and “wild type” RABV strains isolated from different hosts , equivalent to a more than 10-fold dilution in antibody titer[12]; thus higher titers are needed for protection . For wildlife consuming variable doses of vaccines via the oral route of delivery , it is important to use the most efficient vaccine , protective at the lowest titer possible with the fewest doses , as boosts are generally unfeasible . Although bats were boosted in our initial study to optimize their response , testing of a single dose application will be critical in future studies . In an attempt to maximize vaccine efficiency , we designed MoG to be more broadly representative of all PG-I lyssavirus glycoproteins . MoG has 93% similarity to the wild-type big brown bat variant RABV used in the challenge study . The glycoprotein of the CVS-11 strain has 94 . 7% consensus amino acid similarity to MoG , but only 90% similarity to the big brown bat variant RABV . The higher level of similarity between MoG and the challenge strain , as compared to the CVS-11 G protein , may have resulted in the slightly higher survival of RCN-MoG vaccinated bats ( survival 9/9 ) compared to RCN-G vaccinated bats ( survival 7/10 ) , although the difference observed between these small groups was not statistically significant . Mosaic proteins are synthetically designed to represent all potential epitopes from related input sequences and have been shown to induce greater cross-reactivity than consensus sequences [52] . Thus , we expected the immune response elicited by vaccination with MoG to be more efficient at neutralizing naturally circulating RABV than current antigens , however this was not detected by RFFIT ( Table 2 ) . Interestingly , RVNA did not correlate directly with survival . Specifically , topically vaccinated bats , as well as some bats vaccinated ON with RCN-MoG , did not seroconvert prior to challenge , yet survived . While it is generally believed that RVNA are needed for protection , results similar to ours have been reported elsewhere [53–56] . In our case , it is possible that the RCN-MoG vaccine may be better at priming TH cells or activating other adaptive cellular immune responses necessary for clearance of RABV [57–61] . The use of viral vaccine vectors usually leads to a Th1 , CTL response directed at the target antigen . The earlier production of antigen due to the S E/L promoter also leads to an increased CTL response[62] . It is possible that CD8 cells , elicited by vaccination with RCN-MoG , lysed infected cells shortly after challenge , resulting in protection in the absence of detectable neutralizing antibody responses . The enhanced inflammatory response induced by activated CD8 T cells may also have contributed to antibody-mediated clearance , as has been previously suggested[60] . In follow-up studies , it would be useful to assess the cellular immune response to vaccination . Alternatively , it is possible that RVNA induced by RCN-MoG were not properly recognized due to the use of CVS-11 strain in the RFFIT analysis . Thus , it might be necessary to develop a RIFFT assay with MoG as the substrate antigen and to compare the neutralizing capacity of antibodies induced by both RCN-MoG and RCN-G constructs to various divergent lyssaviruses . The studies presented here are especially relevant for vampire bats . So far , most efforts to reduce their threat have centered on culling through the application of anticoagulants to individual bats that are released to poison additional bats through contact and commensal grooming . Vampire bats in particular are known to practice self and social grooming at a very high rate [63] , so this method of application is very effective . Unfortunately , culling of bats has largely failed to reduce the incidence of bovine rabies and may be counterproductive for disease control [49 , 50 , 64] . Also , this method frequently leads to indiscriminate killing of other bat species [3] , which are key members of their ecosystems . Instead , by immunizing certain vampire bat populations against rabies with sufficient coverage to create herd immunity , it may be possible to reduce rabies transmission , thereby lowering the risk of exposure to humans and livestock . Previous laboratory studies have demonstrated successful topical vaccination of Desmodus using a vaccinia virus expressing the glycoprotein from the ERA strain of rabies ( VR-G ) [53 , 65 , 66] . However , the vaccinia vector can infect humans , especially immunocompromised individuals [18 , 67] , and oral delivery of this vaccine to vampire bats induced lower levels of rabies neutralizing antibodies than oral delivery of RCN-G to E . fuscus in this study and T . brasiliensis in our previous study [22] . With further testing in vampire bats , RCN-MoG may offer a safer , more effective alternative that could be delivered topically via glycerin jelly or another medium . For a topical vaccine to be practical and effective , it must induce significant immunity after limited oral exposure and must be applied in an appropriate medium that maintains vaccine titer for extended periods in ambient conditions and attaches firmly to the fur of the target species . Although glycerin jelly was effective in our initial studies , more work is required to determine its utility as a delivery medium for free-ranging bats . An alternative to topical application of vaccine may be aerosolized application to roost sites in caves , but that remains to be tested . Finally , this approach could be adapted for other species or groups of bats and for other important diseases , such as white nose syndrome , a fungal disease killing millions of bats in North America [68] . While much effort has gone into identifying and characterizing the pathogens carried by bats , little has been done to prevent disease in bat hosts . Successful vaccination of bats against rabies could potentially lead to the development of other bat-targeted vaccines .
|
Rabies remains a significant and costly zoonotic disease worldwide . While control of canine rabies can significantly diminish the threat to human health , spillover of rabies and related lyssaviruses from bats into terrestrial animals and humans continues to be an important issue . Here we describe the development of a novel rabies vaccine , using raccoonpox virus ( RCN ) as a viral vector , and a computer designed rabies virus mosaic antigen . We demonstrate that this new vaccine leads to protection against experimental challenge in wild caught big brown bats when administered oronasally or topically . This technology could be adapted to target other bat species and also be directly applicable toward control of vampire-bat associated rabies in Mexico and Central and South America .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"immune",
"physiology",
"pathology",
"and",
"laboratory",
"medicine",
"pathogens",
"immunology",
"tropical",
"diseases",
"microbiology",
"vertebrates",
"animals",
"mammals",
"viruses",
"vaccines",
"preventive",
"medicine",
"rabies",
"rna",
"viruses",
"neglected",
"tropical",
"diseases",
"infectious",
"disease",
"control",
"antibodies",
"glycoproteins",
"vaccination",
"and",
"immunization",
"rabies",
"virus",
"public",
"and",
"occupational",
"health",
"immune",
"system",
"proteins",
"infectious",
"diseases",
"zoonoses",
"proteins",
"medical",
"microbiology",
"microbial",
"pathogens",
"biochemistry",
"lyssavirus",
"eukaryota",
"viral",
"pathogens",
"bats",
"physiology",
"biology",
"and",
"life",
"sciences",
"viral",
"diseases",
"amniotes",
"glycobiology",
"organisms"
] |
2017
|
Protection of bats (Eptesicus fuscus) against rabies following topical or oronasal exposure to a recombinant raccoon poxvirus vaccine
|
Chikungunya virus ( CHIKV ) is a reemerging mosquito-borne pathogen that has recently caused devastating urban epidemics of severe and sometimes chronic arthralgia . As with most other mosquito-borne viral diseases , control relies on reducing mosquito populations and their contact with people , which has been ineffective in most locations . Therefore , vaccines remain the best strategy to prevent most vector-borne diseases . Ideally , vaccines for diseases of resource-limited countries should combine low cost and single dose efficacy , yet induce rapid and long-lived immunity with negligible risk of serious adverse reactions . To develop such a vaccine to protect against chikungunya fever , we employed a rational attenuation mechanism that also prevents the infection of mosquito vectors . The internal ribosome entry site ( IRES ) from encephalomyocarditis virus replaced the subgenomic promoter in a cDNA CHIKV clone , thus altering the levels and host-specific mechanism of structural protein gene expression . Testing in both normal outbred and interferon response-defective mice indicated that the new vaccine candidate is highly attenuated , immunogenic and efficacious after a single dose . Furthermore , it is incapable of replicating in mosquito cells or infecting mosquitoes in vivo . This IRES-based attenuation platform technology may be useful for the predictable attenuation of any alphavirus .
Chikungunya ( CHIK ) virus ( CHIKV ) is a reemerging arboviral pathogen that has recently caused explosive urban outbreaks involving millions of persons in Africa and Asia . The virus was first isolated from a human in Tanzania in 1953 during a major epidemic [1] , and derives its name from a Makonde word meaning “that which bends up , ” which describes the posture observed in afflicted persons . CHIKV typically causes a febrile illness and severe joint pain , which is clinically similar to dengue fever . These 2 viruses also share similar endemic distributions in the Eastern Hemisphere , resulting in many CHIKV cases being misdiagnosed when laboratory testing is not available [2] . Large CHIK outbreaks were described during the 1950's and 60's in India and Southeast Asia [3] , [4] . However , it was not until 2005 that CHIKV gained widespread public attention due to massive outbreaks on islands of the Indian Ocean [5] and later in India [6] and Southeast Asia [7] . In total , several million persons have been affected [8] , [9] . On the Island of Reunion alone , ca . 300 , 000 persons or one-third of the population was affected [10] . Another factor driving the resurgence of interest in CHIK is the detection of occasional fatal cases , which were not documented before . Previously , individuals who became severely ill typically presented with hemorrhagic manifestations and occasionally shock [11] , [12] , [13] . However , the recent outbreaks have been linked to thousands of deaths in Reunion and India due to neurologic disease [14] , [15] , [16] . CHIKV exists in two transmission cycles: an enzootic or sylvatic cycle and an endemic/epidemic urban cycle . The African sylvatic cycle likely involves several arboreal Aedes mosquitoes as vectors and nonhuman primates as reservoir/amplifying hosts [17] . African outbreaks occur from direct enzootic spillover or when CHIKV is introduced into an urban areas inhabited by the anthropophilic mosquito vector , Aedes aegypti . [17] , [18] . More permanent endemic/epidemic transmission cycles were established when the virus was introduced into Asia ca . 1950 , and into the Indian Ocean region , India and then Southeast Asia since 2005 [19] . A mutation in the E1 envelope glycoprotein gene that results in an A226V amino acid substitution dramatically increased the infectivity of some epidemic strains for an alternative urban vector , Ae . albopictus [8] , [20] . The nearly ubiquitous distribution of Ae . aegypti , and the expanding distribution of Ae . albopictus into tropical and temperate regions of both hemispheres has raised concern that CHIKV may spread outside of its previous endemic region into the Western Hemisphere and Europe . The latter scenario was realized in 2007 during a small epidemic in Italy [21] and during autochthonous transmission in southern France during 2010 ( ProMED archive 20100926 . 3495 ) . CHIKV belongs to the family Togaviridae , genus Alphavirus , whose members are enveloped virions that contain a positive sense , single stranded , RNA genome of ∼12 kb . The genome encodes 4 non-structural proteins ( nsP1-4 ) and 3 major structural proteins ( Capsid , E1 , and E2 envelope glycoproteins ) ( Fig . 1A ) . During replication , two distinct RNA's are produced: the genomic and subgenomic RNAs . A negative sense template RNA is also produced . The nonstructural polyprotein open reading frame ( ORF ) is translated via a cap-dependant mechanism from the genomic RNA , whereas the structural protein gene ORF is translated from the subgenomic RNA , also in a cap-dependent manner . The subgenomic RNA is transcribed late during infection from its promoter , which is found in the 3′ end of the nsP4 gene [22] . There is no licensed vaccine or therapeutic CHIK , so outbreaks can only be controlled by preventing the exposure of people to infected mosquito vectors . Scientists at the Walter Reed Army Institute of Research produced an investigational vaccine called 181/clone 25 ( hereafter called 181/25 ) during the 1980s . This live-attenuated strain was generated via serial plaque-to-plaque passages of a wild-type Thai CHIKV strain using MRC-5 cells [23] . The virus is attenuated in both rodents and non-human primates and is highly immunogenic in humans . However , during phase II trials , strain 181/25 caused mild , transient arthralgia in 5 of 59 vaccinees [24] . Also , strain 181/25 can be transmitted experimentally by the natural mosquito vector , Ae . aegypti [25] . To be effective in resource-limited nations that are endemic for CHIK as well as to combat an epidemic , an ideal CHIK vaccine would induce rapid and long-lived immunity after a single dose , have a low risk of reactogenicity and reversion to virulence , and be inexpensive . Vaccines against arboviral diseases should also have a low risk of transmission from vaccinated persons via mosquitoes in the event that viremia occurs , especially those used in non-endemic regions . Although replication-defective vaccine candidates have been described that emphasize safety [26] , [27] , [28] , none has been shown to induce rapid or long-lived immunity after a single dose , and some may be expensive to produce . In contrast , live-attenuated vaccines like the yellow fever 17D vaccine [29] have been spectacularly successful in preventing disease in developing tropical regions . To generate a safer and more effective live-attenuated CHIK vaccine that meets the criteria outlined above , we previously produced and tested a series of chimeric alphaviruses containing either Venezuelan equine encephalitis virus ( VEEV ) , eastern equine encephalitis or Sindbis virus non-structural protein genes along with the CHIKV structural protein genes [30] . These vaccines produce robust neutralizing antibody ( Ab ) responses and provide complete protection against disease after CHIKV challenge . However , some residual ability to infect potential mosquito vectors remains , and attenuation is dependent on an intact murine interferon response ( SCW , unpublished ) . To overcome these limitations , we developed a new attenuation strategy and conducted proof-of-principle studies with another alphavirus , VEEV vaccine strain TC-83 . Both attenuation and elimination of mosquito infectability relied on the inactivation of the subgenomic promoter , and addition of a encephalomyocarditis virus ( EMCV ) internal ribosome entry sequence ( IRES ) to drive translation of the structural protein genes [31] . Chimeric alphaviruses incorporating the IRES element have also been generated as vaccine candidates [32] . The EMCV IRES also mediates inefficient translation in arthropod cells [33] , rendering these mutants unable to infect mosquitoes . However , starting with the attenuated TC-83 strain , the IRES-based attenuation resulted in inadequate immunogenicity and the lack of a neutralizing Ab response . Here , we implemented this IRES-based vaccine design for CHIKV using a cDNA clone generated from the wild-type La Reunion strain [34] . Testing of this novel vaccine candidate in several murine models indicated that it is highly attenuated , even in the absence of an intact murine IFN response , is immunogenic and efficacious in preventing CHIK disease , and is unable to infect mosquitoes .
The CHIKV/IRES vaccine candidate was generated in cDNA form using standard recombinant DNA techniques using the IRES-based attenuation strategy tested previously in TC-83 [31] . The IRES element was amplified from the original TC-83/IRES construct including the first 4 codons from the EMCV sequence that were previously shown to have no effect on viral replication [31] . The IRES sequence was placed directly downstream from the subgenomic promoter of the La Reunion ( LR ) CHIKV infectious cDNA clone ( Fig . 1B ) [34] . The subgenomic promoter was inactivated using 13 synonymous mutations to preserve the wild-type amino acid sequence of nsP4 ( Fig . 1C ) . The resultant virus , rescued by electroporation of in vitro-transcribed RNA into Vero cells , contained a non-functional subgenomic promoter as indicated by the absence of subgenomic RNA within infected cells ( Fig . 2A ) . Titers of CHIKV/IRES collected 30 h after electroporation were 6×106 plaque forming units ( PFU ) /ml , in comparison to titers of 1 . 1x107 for wild-type ( wt ) CHIKV strain LR . To assess replication kinetics , viruses derived from the electroporation were compared after infection of Vero cells . The CHIKV/IRES replicated more slowly than 181-25 or wt-CHIKV , requiring 48 hours at 37°C to reach a peak titer of 2 . 5×107 PFU/ml . Strain 181-25 replicated almost to peak titer within 24 hours and reached 7 . 9×107 PFU/ml . The wt-CHIKV also replicated close to its peak titer by 24 hours and reached 4 . 2×107 ( Fig . 2B ) . Unlike wt-CHIKV , which produced visible plaques within 48 hours of Vero cell infection , the CHIKV/IRES plaques were not readily visible before 3 days of incubation at 37°C . CHIKV/IRES plaques were 0 . 5–2 mm in diameter , whereas vaccine strain 181/25 produced 2–4 mm and wt CHIKV produced ca . 6 mm plaques under 0 . 4% agarose at 3 days post infection ( Fig . 2C ) . To assess phenotypic and genetic stability , CHIKV/IRES was passaged 10 times in Vero cells at 37°C using a multiplicity of infection of 0 . 1 PFU/cell . The plaque morphology remained heterogeneous but consistent after the 10 passages ( Fig . 2C ) . Sequencing of reverse transcription-polymerase chain reaction ( RT-PCR ) amplicons covering the entire genome revealed no consensus mutations aside from the presence of adenine insertions within a poly-A track of the IRES element itself . Plaque purified clones were sequenced through the IRES to determine the frequency of these mutations; 8 of 10 plaque clones examined had 7 As like the original cDNA clone and the 10th passage consensus sequence . However , 3 biological clones had up to 17 As in this region . These differences in sequence showed no obvious correlation with plaque size ( data not shown ) . CHIKV/IRES was also blind-passaged 5 times in C6/36 Ae . albopictus cells and the presence of virus was detected by the ability to produce cytopathic effects ( CPE ) on Vero cells and by RT-PCR amplification . Virus was detected only after the first passage , which presumably reflected residual virus that could not be washed from the cells after inoculation , and was not detected thereafter ( data not shown ) . In contrast , the wt-CHIKV strain replicated in the mosquito cells throughout the passages , with titers ranging from 3–5×107 PFU/ml . Infant outbred CD1 mice develop CHIK disease similar in many ways to that seen in humans [35] . We therefore used this model to evaluate the attenuation of our CHIKV/IRES vaccine candidate . Cohorts ( N = 3 ) of 6-day-old CD1 mice were injected subcutaneously ( SC ) with 105 PFU ( A high dose to increase sensitivity to detect virulence ) of strains 181/25 , wt LR , or CHIKV/IRES , and were sacrificed on days 2 , 4 , 6 , and 8 to compare viral loads . Blood , brain , and leg tissue ( including the knee ) were collected and titrated for infectious virus . The CHIKV/IRES strain produced no detectable virus in any tissue measured throughout the sampling period . In contrast , both vaccine strain 181/25 and wt CHIKV produced measurable and significantly higher viremia through day 4 ( p<0 . 05 ) ( Fig . 3A ) . Surprisingly , vaccine strain 181/25 produced higher viral titers in leg tissue than wt strain LR , and both wt-CHIKV and 181/25 leg titers were significantly higher than those of CHIKV/IRES ( p<0 . 05 ) ( Fig . 3B ) . The wt CHIKV strain produced significantly higher brain titers than either vaccine strain on day 2 ( p<0 . 05 ) ( Fig . 3C ) . These results indicated that CHIKV/IRES is strongly attenuated in the baby mouse model . Another murine model for CHIKV pathogenesis is the A129 mouse , which lacks functional type I interferon receptors . This model has the advantage of producing disease in adult animals , thus permitting efficacy testing using wt-CHIKV challenge [36] . Cohorts of 10-week-old homozygous A129 mice were injected intradermally in the footpad with 104 PFU ( more than 100 LD50 for wt-CHIKV ) of either CHIKV/IRES ( N = 7 ) or 181/25 ( N = 4 ) , and negative controls were sham ( PBS ) -infected ( N = 6 ) . Mice infected with the CHIKV/IRES vaccine showed no visible signs of illness ( weight loss , temperature change , ruffling of fur or hunched posture ) during 14 days of observation . Mice receiving strain 181/25 exhibited significant hyperthermia from day 4–5 , and also showed significant weight loss on day 6 post vaccination ( p<0 . 05 ) , compared to the more constant temperatures and weight increases observed in the mice receiving CHIKV/IRES ( Figs . 4A and B ) . Both CHIKV/IRES and 181/25 produced viremia in A129 mice , but mean titers were consistently lower for CHIKV/IRES ( Fig . 4C ) . These data suggested greater attenuation of CHIKV/IRES compared with181/25 . Another sign of disease monitored in A129 mice was swelling of the feet . For this measurement , mice were vaccinated as described above and subsequently challenged with 100 PFU of wt-CHIKV one month post-vaccination in the same foot as the vaccination site . Two days after vaccination or challenge , the vertical heights of the hind feet were measured using a caliper at the balls . PBS and 181/25 vaccination produced small and similar amounts of swelling ( ca . 0 . 05 mm ) , while CHIKV/IRES vaccination produced slightly greater but still minimal swelling of 0 . 1 mm ( Fig . 5 ) . Sham-vaccinated mice that were challenged showed a strong inflammatory response with a mean increase of 0 . 8 mm in footpad thickness . In contrast , both vaccines protected significantly against swelling ( p<0 . 001 ) with no significant difference between 181/25 and CHIKV/IRES . Attenuation of the 2 vaccine candidates was also compared by infection of 3-week-old A129 mice . Cohorts of 5 were injected intradermally with 104 PFU ( >100 LD50 for wt-CHIKV ) of either 181/25 or CHIKV/IRES . The mice were monitored for weight and survival . There was no significant difference between the weight changes of the two cohorts ( Fig . 6A ) . All animals that received the 181/25 vaccine died or had to be euthanized by day 8 ( Fig . 6B ) . In contrast , none of the animals inoculated with the CHIKV/IRES vaccine showed any signs of illness and all survived to the end of the study 14 days after infection . All A129 mice that received vaccine candidates 181/25 ( N = 4 ) or CHIKV/IRES ( N = 7 ) at a dose of 104 PFU seroconverted . All titers measured 35 days after vaccination exceeded 320 , except for one mouse immunized with strain 181/25 that had a PRNT80 titer of 160 . None of the animals that received CHIKV/IRES or 181/25 showed a significant temperature change ( data not shown ) or any other signs of illness ( as described above ) after challenge with 100 PFU of wt CHIKV , and all survived until day 14 after challenge , when the study was terminated . Mice vaccinated with 181/25 exhibited stable or slightly increasing weight after challenge , while the CHIKV/IRES-vaccinated mice lost some weight on days 8 and 9 post challenge , then recovered . In sharp contrast , sham-vaccinated animals rapidly lost weight before succumbing to infection ( Fig . 7A and B ) . Both vaccines were significantly ( Kaplan-Meier , p<0 . 05 ) and equally efficacious in preventing fatal CHIK in the A129 model . The ability of the CHIKV/IRES vaccine candidate to protect against disease was also measured histopathologically in A129 mice after wt-CHIKV challenge . Because unprotected mice die before muscle or joint lesions develop ( SCW , RS , unpublished ) , we examined the spleen , where earlier lesions occur . Cohorts of three 8–10-week-old A129 mice were vaccinated intradermally in the footpad with either 104 PFU of CHIKV/IRES or were sham-vaccinated with PBS . One mouse from each cohort was sacrificed 4 days post vaccination , and the remaining 2 mice were challenged with 100 PFU of wt-CHIKV at 26 days post-vaccination , then sacrificed 4 days post-challenge . The spleens of the sham-vaccinated mice challenged with CHIK-LR exhibited severe necrosis with markedly reduced numbers of small lymphocytes in the mantle and marginal zones . Only the central portion of the remnant lymphoid follicle remained . In addition , monocytoid cells with abundant eosinophilic cytoplasm in the interfollicular region were observed ( Fig . 8C ) . In contrast , the spleens of animals receiving the vaccine as well as CHIKV/IRES-vaccinated mice challenged with wt-CHIKV ( Fig . 8B & D ) exhibited normal splenic architecture with intact lymphoid follicles and appropriate quantities of white and red pulp . The key histopathologic finding was the absence of any necrosis in the CHIK/IRES-vaccinated animals , when compared to the sham-vaccinated mice . To evaluate the duration of immunity and protection after vaccination , cohorts of six A129 mice were immunized with CHIKV/IRES as described above , bled 21 , 42 , 56 and 92 days later , then challenged 94 days after vaccination . Similar to the results described above , no significant weight loss , footpad swelling , or other signs of disease were noted after vaccination compared to sham-vaccination ( data not shown ) . Antibody PRNT80 titers prior to challenge were all ≥640 . After challenge with 100 PFU of wt-CHIKV , vaccinated animals were significantly protected against foot swelling , fever and mortality ( 6/6 sham-vaccinated mice died by day 5 , whereas all CHIKV/IRES-vaccinated mice survived until day 14 when the study was terminated ) ( Fig . 9A and B ) . The sham-vaccinated group experienced significant hyperthermia on day 2 , followed by significant hypothermia on day 3 as the animals became moribund ( Fig . 9C ) . There were no significant differences in weight change between the two cohorts ( Fig . 9D ) . To test the immunogenicity and efficacy of the CHIKV/IRES vaccine candidate compared with strain 181/25 in immunocompetent mice , cohorts ( N = 9-10 ) of 3-week-old C57BL/6 mice were vaccinated SC with 105 PFU , or with PBS as negative controls . Although 14-day-old and adult C57BL/6 mice develop lesions in the leg after footpad inoculation with wt CHIKV [37] , [38] , we used a more stringent , lethal intranasal ( IN ) challenge C57BL/6 model with the neuroadapted Ross CHIKV strain for efficacy testing [30] . Three weeks after infection , all mice were bled and Ab titers were measured using an 80% plaque reduction neutralization test ( PRNT80 ) . The mean Ab titers in response to strains CHIKV/IRES and 181/25 were nearly equal , with all animals exhibiting PRNT80 titers ≥20 ( p>0 . 1; Table 1 ) . The mice were then challenged IN with 106 PFU of the Ross CHIKV strain . All vaccinated animals survived without any signs of disease ( weight loss , temperature change , ruffling of fur or hunched posture ) through day 14 . One of ten sham-vaccinated mice died on day 9 and 6 died on day 10 after challenge . These results demonstrated the immunogenicity and significant efficacy of the CHIKV/IRES vaccine candidate in immunocompetent mice . To confirm that neutralizing antibodies mediated protection of A129 mice from CHIKV challenge , pooled serum collected 21 days after immunization of A129 mice was inoculated intraperitoneally into naïve 6–7-week-old A129 mice ( N = 5 ) either undiluted or at dilutions of 1:2 or 1:4; undiluted normal mouse serum was used as a negative control . Following challenge with 100 PFU of wt CHIKV , mortality was monitored for 15 days . All mice that received immune serum exhibited increased survival compared with those that received normal mouse serum ( Kaplan Meier , p<0 . 001 ) and greater dilutions of the immune serum resulted in reduced survival ( Fig . 10 ) . These data indicate that neutralizing antibodies protected against fatal CHIK and indicate a correlation between Ab levels and protection . To confirm that the CHIKV/IRES strain was incapable of replicating in mosquitoes , cohorts of 20 adult female Ae . albopictus , a highly susceptible urban vector [20] , were inoculated intrathoracically with ca . 1 . 0 µl of a 104 PFU/ml suspension of either CHIKV/IRES or the wt LR strain . Intrathoracic infection was used rather than oral exposure because mosquitoes are uniformly susceptible to small CHIKV doses delivered via this route , whereas the oral portal of entry is less permissive even after large doses . After 7 days of incubation at 27°C , mosquitoes were triturated and serial 10-fold dilutions were tested for virus by inoculation of Vero cells followed by examination for cytopathic effects ( CPE ) through day 7 . Mosquitoes inoculated with CHIKV/IRES as well as PBS-inoculated negative control mosquitoes produced no detectable CPE . In contrast , all 20 mosquitoes receiving wt CHIKV produced extensive CPE on the Vero cells . To ensure that temperature sensitive or host-restricted mutants were not generated following mosquito infection , RT-PCR targeting the 5′ end of the capsid gene was also used to detect viral RNA . No amplicons were detected from the CHIKV/IRES-infected mosquitoes by gel electrophoresis , whereas all mosquitoes injected with wt CHIKV produced strong bands of the expected size ( Fig . S1 ) .
Nearly 80 years after the introduction of the first vaccine against an arboviral disease , yellow fever [39] , vaccination remains the most effective method to protect against arboviruses and many other infectious agents . In the case of CHIK , the 181/25 live-attenuated vaccine developed during the 1980s showed promise in preclinical studies [23] but was mildly reactogenic in human trials [24] . More recent vaccine development has focused on inactivated [26] , DNA [27] or virus-like particle approaches [28] . However , in our opinion , the requirements for multiple doses administered over several weeks and/or the higher cost of such vaccines , as well as the probability that boosters will be required to maintain immunity , will limit their usefulness in the developing nations of Africa and Asia where CHIKV is endemic . We have therefore focused on live-attenuated vaccines to prevent both endemic and epidemic CHIK . The maturity of reverse genetic technology has provided unprecedented opportunities for manipulation of the alphaviral genome to improve attenuation strategies [40] . Thus , unlike traditional attenuation approaches that rely on cell culture passages , which typically result in attenuation that depends only on small numbers of attenuating point mutations [41] , alternative genetic strategies such as viral chimeras offer the promise of more stable attenuation [30] , [42] , [43] , [44] . In addition to the risk of reactogenicity , attenuation based on small numbers of mutations can also result in residual alphavirus infectivity for mosquito vectors . This risk , which was underscored by the isolation of the TC-83 VEEV vaccine strain from mosquitoes in Louisiana during an equine vaccination campaign designed to control the 1971 epidemic [45] , is especially high when a vaccine that relies on a small number of point mutations is used in a nonendemic location that could support a local transmission cycle . To overcome the aforementioned limitations , we exploited the finding that the EMCV IRES sequence functions inefficiently for translation in insect cells [33] , yet can replace the alphavirus subgenomic promoter to mediate translation of the structural polyprotein open reading frame from the genomic RNA in mammalian cells [31] , [32] . The resultant CHIKV strain replicated efficiently in Vero cells , an acceptable vaccine substrate , and exhibited a stable plaque morphology and consensus genome sequence after 10 passages in this cell line . The CHIKV/IRES vaccine candidate was unable to replicate in mosquito cells or in the mosquito vector , Ae . albopictus , an important safety feature for an live arbovirus vaccine that may be administered to travelers or laboratory workers in nonendemic locations . Attenuation , immunogenicity and efficacy of the CHIKV/IRES vaccine candidate was assessed alongside that of the 181/25 CHIKV strain , which is highly immunogenic in humans and other animals yet inadequately attenuated . The goal was to equal the immunogenicity of the 181/25 vaccine strain but to achieve greater attenuation . Using infant and adult immunocompetent [35] and interferon type I receptor-deficient mouse models [36] , we demonstrated that CHIKV/IRES met both goals . As measured by survival and weight gain or maintenance , CHIKV/IRES was similarly or better attenuated than 181/25 in multiple mouse models , yet generated comparable neutralizing Ab titers and nearly complete protection against disease or mortality after CHIKV challenge . Immunity and protection were maintained for at least 3 months . Viremia after CHIKV/IRES vaccination was never detected in infant CD-1 mice , and was transiently present at a very low level in immunocompromised A129 mice , an important attenuation phenotype considering that viremia could potentially lead to mosquito infection . However , even in the unlikely event that vaccination of an immunocompromised human led to viremia , the mosquito-incompetent phenotype discussed above should prevent transmission . The only measure of efficacy for which strain 181/25 exhibited a slight superiority was in the prevention of footpad swelling post challenge; CHIKV/IRES-vaccinated A129 mice challenged with wt-CHIKV exhibited a greater mean of 0 . 15mm swelling versus only 0 . 09 mm for strain 181/25 . However , both vaccines provided significant protection compared with sham-vaccination . Splenic histopathology was used as a second measure of protection . Mice challenged with wt-CHIKV after sham vaccination developed severe necrosis along with a monocytoid infitrate . in contrast , the CHIKV/IRES vaccine induced no splenic histopathology and protected against splenic lesions upon challenge . Previous attempts to use the EMCV IRES to generate an alphavirus vaccine used the VEEV live-attenuated vaccine strain TC-83 [30] . Although these studies succeeded in eliminating the ability of TC-83 to infect mosquito vectors , immunogenicity was reduced to the point where most vaccinated mice did not develop detectable neutralizing antibodies ( although significant protection against challenge was still detected ) . In contrast , our CHIKV vaccine started with the genetic backbone of a virulent wt alphavirus ( LR ) ( Fig . 1A ) , and robust immunogenicity was maintained despite strong attenuation . These results suggest that the IRES attenuation level may be optimal when applied to other wild-type alphavirus backbones . The application of this platform for attenuation is now being applied to Venezuelan , western , and eastern equine encephalitis viruses to test this hypothesis . In summary , a novel CHIK vaccine candidate , CHIKV/IRES , was generated by manipulation of the structural protein expression of a wt-CHIKV strain via the EMCV IRES . This vaccine candidate exhibits a high degree of murine attenuation that is not dependent on an intact interferon type I response , yet is highly immunogenic and protects against CHIKV challenge . This promising vaccine candidate is being tested in nonhuman primates to determine if it is suitable for evaluation in humans .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Institutional Animal Care and Use Committees of the University of Texas Medical Branch or the University of Wisconsin . Vero African green monkey kidney cells were obtained from the American Type Cell Culture ( Bethesda , MD ) . The cells were maintained at 37°C in Eagles minimum essential media ( MEM ) supplemented with 10% fetal bovine serum ( FBS ) , penicillin and streptomycin . C6/36 Ae . albopictus cells were also maintained in MEM containing 10% FBS at 32°C and supplemented with 10% tryptose phosphate . The CHIKV cDNA clone containing the EMCV IRES with the subgenomic promoter ablated using 13 synonymous mutations ( CHIKV/IRES ) was produced using standard recombinant DNA techniques in which the infectious clone of La Reunion strain ( LR ) described previously was used as a template [34] . This CHIKV clone , a gift from Stephen Higgs , contains an SP6 bacteriophage promoter for transcription of RNA that is identical to genomic viral RNA . The IRES sequence was PCR amplified from a cDNA clone described previously [31] . The inactivation of the subgenomic promoter was done using site-specific mutagenesis . An intermediate construct encoding the 3′ end of the nsP4 gene through the subgenomic promoter was produced using PCR with high fidelity Phusion DNA polymerase from Finnzymes ( Espoo , Finland ) . The resultant amplicon was cloned into a shuttle vector , prS2 , and was sequenced using the BigDye kit ( Applied Biosystems , Foster City , CA ) . The 5′ end of capsid gene from the LR strain was amplified using PCR with an overhang complementary to the IRES sequence . The IRES-containing and capsid fragments were then joined using fusion PCR , and this fragment was cloned back into the shuttle vector and resequenced . The IRES/Capsid fragment and the mutated subgenomic fragment were finally ligated together through the SpeI site introduced into both fragments . The completed insert was then cloned into the LR backbone and this final construct was completely sequenced . Large-scale plasmid purification was done using CsCl preparations . The purified DNA was then linearized using NotI restriction endonuclease ( New England BioLabs , Ipswich , MA ) , and a small sample was analyzed on a 1 . 2% agarose gel to verify linearization . The remaining DNA was transcribed using an Ambion SP6 In vitro transcription kit . The RNA was quantified and used to electroporate Vero cells using a BTX ECM 830 electroporator . Briefly , two T-150 flasks containing 90% confluent Vero cells were trypsinized and washed 3 times in RNAse-free DPBS . The cells were resuspended in 700 µl of DPBS and 10 µg of RNA was added . The solution was placed in a 4mm cuvette and was pulsed 2 times at 250v for 10 msec at 1 sec intervals . The cells were then left at room temperature for 10 minutes before being plated in T-75 flasks . The virus was harvested at 24 hours post-electroporation and centrifuged at 771×g . Supernatant was collected and titered by plaque assay on Vero cells . The CHIKV/IRES vaccine candidate was passaged in Vero and C6/36 cells to assess phenotypic and genetic stability . T-25 flasks were grown to 90-95% confluency , then were infected at a multiplicity ( MOI ) of 0 . 1 Vero PFU/cell . Following 30 h of incubation at 37°C or 32°C , respectively , the medium was diluted and used to infect another flask with a MOI of 0 . 1 . Following 10 serial passages , consensus sequences were determined for both passaged populations and plaque-purified biological clones by RT-PCR amplification and amplicon sequencing . We also selected 10 well-isolated , random plaques , harvested virus using a plastic micropipette tip . The agar plug containing the plaque was placed in 300 µl of MEM containing 2% FBS and RNA was extracted using TRIzol LS ( Invitrogen , Carlsbad , CA ) . RT-PCR and sequencing were performed as described above . Vero plaque sizes were measured and compared to assess stability . Replication kinetics was measured in 35 mm 6-well plates with duplicates for each virus tested . The wells were seeded to a confluency of 95% using Vero cells . Media was removed and they were infected at an MOI of . 1 for one hour . Then 2 . 1 ml of DMEM containing 5% FBS was added . A 0 time point was immediately removed ( 100 µl ) . At each of the remaining time points 12 , 24 , 36 and 48 100 µl was removed and replaced . The samples were tittered as described above . Depending on containment requirements and sensitivity needs , virus stocks and experimental samples were titered by plaque assay as previously described [46] or were estimated using quantitative real-time PCR with dilutions of virus to generate standard curves from which PFU titers could be extrapolated . This assay used primers ( 5′-GAYCCCGACTCAACCATCCT-3′ ) and ( 5′-CATMGGGCARACGCACTGGTA-3′ ) and the probe ( 5′-AGYGCGCCAGCAAGGAGGAKGATGT-3′ ) which contained the dye FAM . Ab titers were measured using plaque reduction neutralization tests with 80% reduction endpoints [46] . Vero cells were infected on 35 mm2 6 well plates at an MOI of 20 . The media was removed 18 hours after infection and replaced with . 8 ml of complete media with 1 µg/ml of actinomycin D from Sigma , and 20 µCI of [5 , 6-3H] uridine from Moravak Biochemicals ( Brea , CA . ) . The cells were then incubated for 4 hours and RNA is removed by TRIzol extraction . The RNA was placed into a sodium phosphate buffer containing DMSO and glyoxal at 50°C for 1 hour . The RNA was loaded into a 1% agarose gel and run at 150 v for 3–4 hours . The gel was then washed twice in methanol for 30 minutes . Then a 2 . 5% PPO and methanol solution was placed with the gel overnight . The gel was washed with DI water to precipitate the PPO and the gel was then dried . The gel is then placed with X-OMAT AR film ( Kodak ) , at −80°C for 8 hours . Five-to-seven-day-old CD1 outbred mice [35] were obtained from Charles River ( Wilmington , MA ) . These animals were infected subcutaneously ( SC ) with 105 PFU and were serially sacrificed on days 2 , 4 , 6 , 8 , and 10 . Blood , brain , and hind femoral tissues were collected for assays of virus content . C57BL/6 mice were obtained from Jackson labs ( Bar Harbor , ME ) and used in challenge experiments as described previously [30] . Briefly , the animals were infected SC at 3 weeks of age with 105 PFU in the hind leg and observed for signs of illness for 21 days . Then , they were challenged intranasally ( IN ) with 106 . 5 PFU of the neuroadapted Ross CHIKV strain . The animals were observed daily for illness and were sacrificed when they became moribund . A129 mice were bred at the University of Wisconsin from a breeding pair obtained from B & K ltd . Grimston , England . Animals 3 or 10 weeks of age , were infected with 1x104 PFU of vaccine strains ID in the left rear footpad . Footpad measurements were taken 48 hours post vaccination with a caliper as the vertical height of the hind feet at the balls . The animals were maintained for 38 days and bled on days 21 and 35 . These animals were then challenged with 100 PFU of wt CHIKV and were monitored for morbidity and mortality . All animals were euthanized by CO2 overdose if they became moribund . A129 animals were used for a longitudinal study of protection in which they were challenged with 100 PFU ID of wt-CHIKV 94 days after being vaccinated . Tissues were fixed in 10% neutral buffered formalin ( RICCA Chemical Company , Arlington , TX . ) . Bone tissue was decalcified overnight using fixative/decalcifier ( VWR International , Radnar , PA . ) . Tissue was then embedded in paraffin wax and 5 um sections were cut for analysis . Sections for hematoxylin and eosin staining were deparaffinized in Xylene for 15 minutes . Sections were then rehydrated in ethanol and ethanol/water mixtures as follows: 100% ethanol for 9 minutes , 95% ethanol/5% deionized water for 3 minutes , 80% ethanol/20% deionized water for 5 minutes . Sections were then stained with hematoxylin ( Richard-Allan Scientific ) for 3 minutes and then rinsed with deionized water . Sections were then rinsed in tap water for 5 minutes and placed in Clarifier I ( Richard-Allan Scientific , Kalamazoo , MI . ) for 5 minutes . Sections were then rinsed in tap water for 2 minutes and then in deionized water for 2 minutes . Sections were then stained in eosin ( Richard-Allan Scientific ) for 30 seconds . They were then dehydrated as follows: 95% ethanol/5% deionized water for 15 minutes , 100% ethanol for 15 minutes and then Xylene ( Richard-Allan Scientific ) for 15 minutes . Cover slips were applied to slides using Permount ( Fisher Scientific ) and dried overnight . Deparaffinizing and hematoxylin-eosin staining was performed on the Varistain Gemini ES ( Shandon , Thermo Fisher Scientific ) . All animal studies were approved by the UTMB and/or the Univ . Wisconsin Institutional Animal Care and Use Committee . An Ae . albopictus colony established in 2003 from mosquitoes collected in Galveston , TX was used for these experiments . This species was selected because it is highly susceptible to the LR CHIKV strain [20] . Adult female mosquitoes collected 3–4 days post-eclosion were anesthetized using a chill table ( Bioquip , Rancho Dominguez , CA ) and were then injected intrathoracically with ca . 1 . 0 µL of a 104 Vero PFU/ml virus stock . The mosquitoes were incubated for 7 days at 27°C with 10% sucrose provided ad libitum . The mosquitoes were then frozen and triturated in MEM containing 2% FBS and fungicide using a Tissuelyser II ( Qiagen , Venlo , Netherlands ) for 2 min . Following centrifugation for 10 minutes at 10 , 000×G , the supernatant was plated on Vero cells using 96 well plates . The cells were infected for 1 hour at 37°C and then covered with 2% FBS containing MEM and allowed to incubate for 48 hr to measure CPE . RNA was collected through Qiagen RNeasy columns ( Qiagen , Venlo , Netherlands ) or TRIzol LS ( Invitrogen ) using the manufacturer's protocols . 130 µl of sample were taken from the mosquito homogenates and the RNA was collected . The RNA was then amplified via RT-PCR using a Titan single step RT-PCR kit ( Roche , Basel , Switzerland ) . The primers used to amplify annealed to the 5′end of capsid , 5′-TGGCCTTTAAGCGGTC-3′ and 5′-TATGGTCTTGTGGCTTTATAGAC-3′ . Student's T-tests were performed using Excel ( Microsoft , Redmond , WA ) . ANOVA tests were performed using SPSS v18 ( IBM Corporation , Somers , NY ) . Kaplan-Meier tests were performed using Prism 5 ( GraphPad Software , La Jolla , CA ) . P-values <0 . 05 were considered significant . Negative data points were counted at one-half of the corresponding limit of detection for statistical analyses .
|
Chikungunya virus ( CHIKV ) is a mosquito-borne alphavirus that has reemerged since 2004 to cause millions of cases of severe and often persistent arthralgia . Because no licensed vaccine exists to prevent this disease , we utilized an attenuation approach to produce a live CHIKV vaccine candidate that elicits a robust , protective immune response yet causes no detectable disease in mice . It is also incapable of infecting mosquito vectors , an important safety feature for a live virus vaccine that may be used in nonendemic locations to immunize travelers or laboratory personnel . This vaccine approach , which exploits the attenuating effect of altering the expression of the alphavirus structural proteins with a picornavirus IRES , may be broadly applicable to other alphaviruses that cause important febrile diseases as well as encephalitis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"infectious",
"diseases",
"global",
"health",
"genetics",
"immunology",
"biology",
"microbiology",
"genetics",
"and",
"genomics"
] |
2011
|
Novel Chikungunya Vaccine Candidate with an IRES-Based Attenuation and Host Range Alteration Mechanism
|
Human decisions are based on accumulating evidence over time for different options . Here we ask a simple question: How is the accumulation of evidence affected by the level of awareness of the information ? We examined the influence of awareness on decision-making using combined behavioral methods and magneto-encephalography ( MEG ) . Participants were required to make decisions by accumulating evidence over a series of visually presented arrow stimuli whose visibility was modulated by masking . Behavioral results showed that participants could accumulate evidence under both high and low visibility . However , a top-down strategic modulation of the flow of incoming evidence was only present for stimuli with high visibility: once enough evidence had been accrued , participants strategically reduced the impact of new incoming stimuli . Also , decision-making speed and confidence were strongly modulated by the strength of the evidence for high-visible but not low-visible evidence , even though direct priming effects were identical for both types of stimuli . Neural recordings revealed that , while initial perceptual processing was independent of visibility , there was stronger top-down amplification for stimuli with high visibility than low visibility . Furthermore , neural markers of evidence accumulation over occipito-parietal cortex showed a strategic bias only for highly visible sensory information , speeding up processing and reducing neural computations related to the decision process . Our results indicate that the level of awareness of information changes decision-making: while accumulation of evidence already exists under low visibility conditions , high visibility allows evidence to be accumulated up to a higher level , leading to important strategical top-down changes in decision-making . Our results therefore suggest a potential role of awareness in deploying flexible strategies for biasing information acquisition in line with one's expectations and goals .
Many decisions can be formalized as a process of accumulation of evidence over time , ultimately favoring one alternative over another [1] , [2] . Evidence accumulation models have successfully captured the neural dynamics of simple decisions in a visual motion categorization task [3] as well as more complex decisions in which discrete pieces of evidence need to be integrated [4] . Here we investigate whether accumulation of evidence is affected by the level of awareness of the information . Visual subliminal priming studies have shown that perceptual [5]–[7] , cognitive [8] , [9] , motor [10] , and executive [11] , [12] stages can all be influenced by subliminal information . Furthermore , the amount of priming and subliminal processing increases linearly with prime processing [13] , [14] , suggesting that some stages of evidence accumulation can proceed without awareness . Also , relatively long-term effects of subliminal priming have sometimes been observed [15]–[18] , suggesting that accumulation of unconscious information is possible . However , it is an open question whether and how awareness modulates the way evidence is accumulated during decision-making . Contemporary models of subliminal information processing posit that subliminal information is marked by a lack of “global ignition” [19] , meaning that it cannot enter into a global workspace system that allows it to be held in working memory and broadcasted to a variety of higher level neural processors . This lack of ignition may preclude “access” to the information . Therefore , awareness may be a necessary condition for biasing and modifying the sensory evidence in line with one's expectations and goals during decision-making . In this study , we directly test the potential role of awareness in human decision-making using a previously described task in which participants have to accumulate sequentially presented pieces of evidence across an extended period of time . We previously observed a dependency of evidence accumulation on the amount of prior accumulated evidence: when prior evidence was already strong , participants weighted the newly incoming information much less than when prior evidence was weak and indecisive [20] . Here we hypothesize that this top-down modulation may depend on awareness . While accumulation may be possible irrespective of the level of awareness [15]–[18] , it may appear qualitatively different depending on awareness level . Specifically , if awareness is necessary for top-down biasing of information during decision-making , low-visible evidence may be accumulated in a linear fashion , i . e . adding and subtracting new information without regard to the history of prior accumulated evidence . Non-linearities in evidence accumulation ( e . g . , giving less weight to new information under conditions of high certainty [20] , [21] ) , which are a more optimal decision strategy within a Bayesian decision-making framework [22] , may be present only for high-visible evidence . We tested this hypothesis by using a decision-making task in which a sequence of five arrows was presented at either high or low visibility ( HV versus LV ) , by means of masking ( Figure 1A ) . In a series of behavioral experiments , we established whether and how evidence is accumulated over time , depending on the level of awareness . We also assessed the relationship between accumulated evidence and subjective decision confidence for stimuli at both awareness levels . Finally , we tracked accumulation-related neural activity over time in the human brain for both types of information , using magneto-encephalography ( MEG ) .
On each trial , participants ( N = 16 ) were presented with a stream of five arrows , each of which could point to the left or right with equal probability . Participants had to quickly decide on the overall direction of the arrows by pressing a button at the end of each stream with their left or right index finger , guessing if necessary ( Figure 1A ) . Strength of the evidence could range from one ( low evidence , e . g . two left and three right arrows ) to five ( high evidence , e . g . five right arrows , see evidence accumulation diagram in Figure 1B ) . Visibility of the arrows was manipulated by masking them with an effective “metacontrast” mask ( leading to low visibility , LV ) or with an equiluminant but less effective “pseudo” mask ( leading to high visibility , HV; see Figure S1 for details ) [14] , [23] . On each trial , all arrows were either LV or HV . Stimulus and mask duration were identical for LV and HV conditions , allowing us to compare behavioral performance of evidence accumulation and the underlying neural responses without confounding stimulus visibility with basic task parameters [24] . A six-choice discrimination task performed after the main experiment confirmed that visibility of the arrows was much poorer on LV trials than on HV trials ( 31% correct versus 73% correct , Figure 1C; difference: p<0 . 001 , see Materials and Methods for further details ) . In the decision-making task , behavioral performance was less accurate for LV than for HV trials ( 60% versus 81% correct , p<0 . 001 ) . Nevertheless , for both LV and HV trials , performance increased with increasing amount of evidence ( both p<0 . 001 ) , and thus evidence was accumulated for both trial types . For HV trials , performance approached a ceiling level of 100% correct for the highest evidence levels . For LV trials , the increase in performance was linear , peaking at 73% correct on trials with five identical arrows ( Figure 1D ) . There was a trend of a right-side bias for LV trials when all arrows pointed in the same direction ( 67% versus 79%: T = 1 . 78 , p = 0 . 096 ) . Although we had no a priori hypothesis for such a bias , the finding is in line with earlier psychophysical studies showing that choices can be strongly biased by hand-preference especially under conditions of uncertainty ( as in the case of the LV stimuli ) [25]–[27] . While evidence accumulation was present for both LV and HV stimuli , there were striking behavioral differences in terms of how evidence was accumulated between conditions . First , the speed of decision-making was modulated by the amount of accumulated evidence for HV ( p<0 . 001 ) but not for LV information ( p = 0 . 31 ) , leading to a significant interaction ( p = 0 . 025 , Figure 1E ) . Second , the “impact” of each successive arrow on the final decision varied as a function of time and accumulated evidence only for HV trials . We defined the impact of an arrow as the extent to which the arrow changed the response proportion in the direction of the arrow ( see Materials and Methods for details on the exact quantification procedure ) . We observed a monotonically increasing impact of arrows on the decision as a function of time for HV stimuli ( p<0 . 001 ) , while this modulation of time was only marginal for LV stimuli ( p = 0 . 07 ) , leading to a significant interaction ( p<0 . 001 , Figure 1F ) . Moreover , for HV arrows , the influence of the last arrow , defined as the extent to which it changed the response probability in the direction of the arrow , decreased linearly with the amount of previously accumulated evidence: the larger the amount of accumulated evidence , the less influence the last arrow had on the decision ( p<0 . 001 ) , as expected from a rational strategy of progressively disregarding the arrows once sufficient evidence is obtained ( Figure 1B ) . This modulation of accumulation by prior evidence was absent for LV stimuli ( p = 0 . 44 ) , leading to a significant interaction ( p<0 . 001 , Figure 1G ) . Together , these results show that strategic effects on decision-making strongly depend on the awareness level of the stimuli . Interestingly , these results were not simply due to the possibility that , during HV trials , participants stopped performing the task after having observed a sufficient amount of arrows . A “logical counting” algorithm would not give any weight to the last arrow when two or four pieces of evidence had already been accumulated , since the last arrow cannot change the decision anymore . In our data , however , the last arrow did have a sizeable influence on the decision even when four pieces of evidence had already been accumulated ( Figure 1G , red line , right data point ) . We further explored the relationship between decision-making performance and subjective confidence in a new group of 16 participants; this time we additionally asked them to rate their confidence of having responded correctly after every trial on a 6-point scale ( 1 = pure guess , 6 = 100% sure ) . Overall decision-making performance was similar as in the MEG environment ( in terms of overall performance and increase in performance with increasing evidence ) . As expected , overall confidence for LV arrows was much lower than for HV arrows ( 1 . 9 versus 3 . 8: p<0 . 001; Figure 1H ) . More interestingly , participants' confidence level for correct responses and incorrect responses was nearly equal for LV arrows ( difference = 0 . 05 , p = 0 . 093 ) , but strongly dissociated for HV arrows ( difference = 1 . 07 , p<0 . 001; Figure 1I ) , resulting in a significant interaction ( p<0 . 001 ) . Thus participants had little insight in their accuracy level when arrows were strongly masked ( LV ) , but they could very well distinguish correct from error trials when arrows were only weakly masked ( HV ) . Since the inability to perform second-order confidence judgments has been proposed as a marker of lack of awareness [28] , the results confirm that awareness was strongly reduced on LV compared to HV trials . When directly correlating decision-making performance and confidence for the correct trials , there was a strong correlation between these measures for HV trials ( r = 0 . 77 , p<0 . 001 ) , while there was only a weak and marginally significant correlation for LV arrows ( r = 0 . 23 , p = 0 . 087 , Figure 1J ) . However , this was likely due to the restricted range of confidence during LV since most participants reported low confidence levels for LV trials . When the range was restricted to the lowest three confidence levels , there was in fact a significant correlation between decision-making performance and confidence also for LV trials ( r = 0 . 66 , p<0 . 001 ) . Overall , the results revealed that participants had markedly reduced confidence in their decision making for LV arrows , but could still use the information to achieve above-chance performance on the decision task . Finally , we tested whether there was a difference in “stimulus strength” between the LV and HV arrows . In all experiments described so far , the arrow stimuli themselves were identical between conditions , and the only difference was the efficacy of the mask . Therefore , theoretically , the bottom-up stimulus strength , i . e . the ability of the stimulus to automatically climb up the sensorimotor pathways , may be equal for both conditions , even though visibility was strongly dissociated . To test this notion directly , we assessed and directly compared the priming strength of the LV and HV stimuli . Sixteen participants performed a simple masked priming experiment in which they responded as fast as possible to the direction of the mask ( whose external outline was changed to a left- or right-pointing arrow; see Figure S1 and [14] ) . The mask was preceded by a LV or HV prime arrow pointing into the same or the opposite direction as the target . Congruence of the arrow prime resulted in significantly shorter reaction times ( RT ) and lower error rates ( ER ) to the mask for both LV and HV primes ( all p<0 . 001 ) . Crucially , this priming effect was not significantly different between LV and HV primes ( RT priming effect: LV = 55 ms , HV = 50 ms , p = 0 . 13; ER priming effect: LV = 18% , HV = 17% , p = 0 . 39; Figure 1K ) , in line with earlier findings [29] . This shows that the bottom-up stimulus strength is equal for LV and HV arrows , and points to an interesting dissociation between the “direct” priming impact of a stimulus and its visibility and its long-term effect on decision-making . Using MEG , we first investigated whether LV and HV arrows were processed differently in the human brain , irrespective of evidence or direction . We used a cluster-level statistic to establish the significance of differences between conditions . This method effectively controls the type I error rate in situations involving multiple comparisons ( such as 275 sensors ) by clustering neighboring sensor pairs that exhibit the same effect ( see Materials and Methods for more details ) . A direct comparison of LV and HV arrows , collapsed across all five arrows , revealed that there was larger activity for HV than LV arrows over left frontal and fronto-central sensors ( 50–100 ms interval , pcluster = 0 . 018 and pcluster = 0 . 016 , respectively ) . At a later interval , there was larger activity for HV than LV arrows over parietal ( 100–150 ms interval , pcluster = 0 . 001 ) and occipital ( 150–300 ms interval , pcluster<0 . 001; Figure 2 ) sensors . A detailed time course analysis estimated the first point of significant difference at 55 ms for the frontal cluster , 125 ms for the parietal cluster , and 145 ms for the occipital cluster ( Figure 2B ) . The early frontal difference between HV and LV arrows was present for all arrows except for the first arrow of the sequence ( Figure S2A ) , while the occipital and parietal amplification for HV arrows was visible for each and every arrow ( Figure S2B , C ) . Interestingly , there was a behavioral counterpart of the frontal asymmetry between the first and subsequent arrows: whereas the first arrow had equal effects on the decision for LV and HV arrows , there were large differences in the weight of the subsequent arrows on the decision ( Figure 1F ) . Previously we identified an inverse relationship between parietal and central neural activity and the amount of accumulated evidence: when more evidence was accumulated , neural activity evoked by new incoming stimuli was attenuated [20] ( see [30] , [31] for comparable results ) . This pattern is consistent with the strategy to reduce the weight of new evidence once substantial evidence has already been accumulated . Behavioral results indeed showed that the impact of the last arrow decreased with the total amount of previously accumulated evidence , but for HV arrows only ( Figure 1G ) . For the analysis of evidence accumulation in the MEG environment , we compared activity for LV and HV arrows that had “low prior accumulated evidence” and “high prior accumulated evidence , ” averaged across the third to fifth arrow presentation ( the first two arrow presentations are not taken into account since there is no differential amount of prior accumulated evidence until after the first two arrows have been presented ) . Low evidence consisted of trials with zero ( for third and fifth arrow ) or one ( for fourth arrow ) prior accumulated evidence at the onset of the arrow . High evidence consisted of trials with two ( for third and fifth arrow ) , three ( for fourth arrow ) , or four ( for fifth arrow ) prior accumulated evidence at arrow onset . We found that when participants had high prior accumulated evidence , the newly incoming arrows evoked a smaller activity at right occipito-parietal and central sensors . Crucially , this phenomenon was significant only for HV arrows ( central sensors: 150–200 ms interval , pcluster = 0 . 014; occipito-parietal sensors: 250–300 ms interval , pcluster = 0 . 041 ) ( Figure 3A , top row ) , while there was only a non-significant trend for LV arrows in central sensors ( 150–200 ms interval , pcluster = 0 . 077 ) ( Figure 3A , middle row ) . This resulted in a significant difference between conditions over right occipito-parietal sensors ( HV versus LV: 250–300 ms interval , pcluster = 0 . 042 ) ( Figure 3A , bottom row ) . Whereas neural responses are collapsed across arrows in this figure , Figure S2B shows that this effect was robustly observed in response to individual arrow presentations preceded by low and high evidence ( a difference defined only for the third to fifth arrow , since differences in amount of accumulated evidence only arise after two arrows have been presented ) . Under conditions of purely linear addition and subtraction of information , the direction of the previous arrow should not influence how the current arrow is processed . However , previous studies have described an automatic influence of repetition compared to alternation during decision-making [32] , and previously we also showed a large reduction in neural activity for repeated compared to non-repeated arrows under conditions of high visibility [20] . When directly contrasting “repeat” arrows ( i . e . arrows that were preceded by an arrow with the same direction ) with “change” arrows ( i . e . arrows that were preceded by an arrow with the opposite direction ) , we observed a large neural activity reduction for arrow repetitions ( neural responses are collapsed across arrows ) . For HV arrows , this reduction was visible at occipito-parietal ( 100–150 ms interval , pcluster = 0 . 030; 150–200 ms interval , pcluster = 0 . 005; 200–250 ms interval , pcluster = 0 . 022 ) and central ( HV: 200–250 ms interval , pcluster = 0 . 019 ) sensors ( Figure 4A , top row ) . A similar effect was also observed for LV arrows at central sensors only ( 200–250 ms interval , pcluster = 0 . 022 ) ( Figure 4A , middle row ) , in line with earlier studies showing subliminal repetition suppression effects [9] , [33] . Nevertheless , a direct comparison between both conditions shows that this suppression effect was significantly larger for HV than LV arrows ( HV versus LV: 100–150 ms interval , pcluster = 0 . 039; 150–200 ms interval , pcluster = 0 . 015; 200–250 ms interval , pcluster = 0 . 05 ) ( Figure 4A , bottom row ) . Examination of the neural response to each individual “change” and “repeat” arrows ( defined only for the second to fifth arrow , since the first arrow does not have a preceding arrow ) shows that this effect was robustly found whenever a new arrow was presented , with no tendency to decrease with time ( Figure S2C ) . Further , restricting the LV analysis to the poorest perceivers who scored at chance level in the six-choice discrimination task ( 16 . 7% ) showed that this effect was present equally robustly for these nine “poor perceivers” ( see Figure S3 ) .
In a combination of behavioral and electrophysiological studies , we showed that while participants are able to accumulate evidence over time independently from the level of awareness of the evidence , there were marked differences between accumulation of low-visibility ( LV ) and high-visibility ( HV ) information , both in terms of brain activity and behavior . Although the amount of bottom-up information provided by a single HV or LV arrow was identical , as measured by priming ( Figure 1K ) , the overall decision-making performance was much less accurate when based on LV evidence than on HV evidence ( Figure 1D ) . More interestingly , decision-making speed was modulated by the amount of accumulated evidence , but only for HV stimuli ( Figure 1E ) . Also , subjective confidence in decision making was markedly lower for LV than HV evidence ( Figure 1H ) . Together , this suggests that while participants could accumulate LV evidence over time , there are qualitative differences in accumulation of evidence depending on the level of awareness of the sensory information . We observed a strong top-down biasing effect of the amount of previously accumulated information , only for HV evidence: the impact of the last arrow stimulus on the final decision decreased linearly with the amount of previously accumulated evidence ( Figure 1G ) . Interestingly , participants did not stop accumulating HV evidence altogether when they had accrued enough information for their decision: even when a large amount of evidence ( 4 units ) had already been accrued for one of the two decisions , the last arrow still had an impact on the decision process , which was equally large as the impact of any of the LV stimuli . This suggests that participants did not adopt a fully “logical” or digital counting strategy ( perhaps for lack of time , as arrows come in at a fast pace of one every 300 ms ) . Rather , on HV trials only , they attributed a weight to later arrows that was inversely related to the amount of already accumulated evidence . These behavioral findings constrain the theoretical modeling of the task . The observed strategy is not predicted by simple linear accumulation models [34] , since these would predict equal weighting of later arrows , independently of the amount of previously accumulated evidence . It is also not in line with a simple gain of accumulation from LV to HV stimuli , since this would result in overall larger weights of each arrow , but no differential modulation by time and prior accumulated evidence . Rather , the results suggest a more sophisticated mode of evidence accumulation , in which the update signal is scaled with respect to the previously accumulated evidence . This behavior arises naturally from Bayesian and sequential sampling ( SPRT ) models [20] , [21] , where evidence is only accumulated up to a bound . Beyond this bound , further evidence no longer contributes to the decision , with two consequences: ( 1 ) on average , later evidence is given a smaller weight , especially when early evidence is strong and the bound is therefore likely to be reached; ( 2 ) response time accelerates in proportion to the likelihood of reaching the bound . Both of these properties accurately characterize the participants' behavior on HV trials . Importantly however , this modulation of evidence accumulation by prior accumulated evidence was absent for LV stimuli , where the impact of each arrow was not dependent on temporal position or prior amount of accumulated evidence . Such a purely linear accumulation of evidence is exactly what is predicted from optimal Bayesian integration , assuming that the amount of available evidence is low and therefore the accumulated amount rarely reaches threshold ( see [20] , Figure 2C ) . This hypothesis can also explain why RT remained constant on LV trials , independently of total evidence: even when five arrows point in the same direction , the total accumulation would still remain below the decision threshold on most trials , thus always requiring a forced-choice decision . Overall , the simplest theoretical model therefore is that LV and HV trials were processed through a similar accumulation-decision pathway , yet with LV trials yielding a much lower level of evidence and therefore remaining far from decision threshold . Conversely , full awareness of the stimuli may be necessary for their accumulated evidence to reach a decision threshold which enables strategic top-down biasing of later evidence accumulation based on the past accumulation . Magneto-encephalographic ( MEG ) recordings lend further support to this view . They showed that , while initial perceptual processing was identical for LV and HV evidence , there was a late divergence between LV and HV , which could be seen ∼145 ms after stimulus onset over occipital cortex ( Figure 2 ) . This late divergence between LV and HV stimuli has been observed earlier using different masking paradigms [35]–[37] , and these findings are generally in good accordance with a feedback view of masking , in which initial processing in visual areas is intact but late amplification by feedback is disturbed [19] , [38]–[40] . Note , however , that our data do not allow us to make firm claims about the underlying mechanisms of metacontrast masking , as different explanations have also been put forward to explain the late sensory divergence ( e . g . , [37] ) . There was also a neural difference between LV and HV stimuli over left frontal and fronto-central sensors , which became significant as early as ∼55 ms . This early frontal difference could be seen for all arrows except for the first arrow of the sequence ( Figure S2A ) . Interestingly , there was a behavioral counterpart of this effect: whereas the first arrow had equal effects on the decision for LV and HV arrows , there were large differences in the weight of the subsequent arrows on the decision ( Figure 1F ) . This suggests that only after the visibility of the sequence was established , on the basis of the first arrow , did participants treat the incoming information differently for LV and HV arrows . We speculate therefore that this frontal amplification may be a source of the behaviorally observed biasing effect [41] . While a change in evidence increased activity over parietal and central areas for both HV and LV evidence ( albeit weaker , Figure 4 ) , a neural influence of accumulated evidence on the processing of the current arrow was again found only for HV evidence . This MEG observation corroborates earlier behavioral and neural results [20] and suggests a neural implementation of the biasing of later information by past visible information , namely by a late ( ∼200–300 ms after stimulus onset ) top-down modulation of sensory representations ( Figure 3 ) . By manipulating the configuration of the mask only , we created large differences in stimulus visibility without introducing differences in stimulus strength [29] , as evidenced by equal priming effects under LV and HV conditions when a single arrow was presented ( Figure 1K ) . Given that priming was unrelated to stimulus awareness , it is quite remarkable that the accumulation of evidence was . What may underlie these differences ? Direct automatic priming effects are probably mediated by fast feedforward activations , which directly influence the evolving motor decision program [10] . These feedforward activations are relatively “automatic” [35] and have been found to be unaffected by stimulus visibility [14] , although they can be modulated by several top-down factors , such as attention [42] , [43] and task-set [44] . In contrast , the slow accumulation of evidence over time , as probed in the present study , may require self-sustainable recurrent interactions between distant brain regions , which may only be present when participants have complete access to ( i . e . , full awareness of ) the stimuli [19] . Previous studies have shown that subliminal information can be accumulated linearly over a few hundreds of milliseconds [13] , [14] , [45]–[47] . Although indirect consequences of subliminal information can be measured for several minutes [17] and up to even as long as 24 h after its presentation [18] , these effects may betray a form of learning and therefore synaptic changes rather than long-lasting subliminal activation . Indeed , most priming studies reveal a fast decay of subliminal information within less than one second [48] , [49] . Relative to this state of knowledge , the current study is the first to show that information from sequentially presented masked stimuli can be accumulated linearly over a long duration of more than a second . However , we also show a qualitative difference in how evidence is treated by the nervous system depending on the level of sensory awareness . As noted above , this qualitative difference need not imply that the processing pathway is entirely different for HV compared to LV trials . Rather , the same decision mechanism may be involved , with the main difference being that only a trickle of evidence is accumulated on LV trials , with the consequence that the decision threshold is typically not reached , therefore preventing the subsequent deployment of top-down strategies for down-weighting further incoming arrows . Indeed , our results suggest that the parietal and prefrontal regions that implement such decision making by evidence accumulation [1] , [2] may integrate sensory evidence across long periods of time , whether or not the original information was above or below the threshold for conscious access , but with a much weaker signal in the latter case . A similar conclusion was reached by Sackur and Dehaene [50] when studying sequential two-step tasks with subliminal versus visible digits . As here , a qualitative behavioral difference was seen: participants were only able to perform a chained task of addition followed by comparison when the target digits were consciously seen , although they could perform each individual computation above chance when the digits were subliminal . This difference , although qualitative , could have arisen from the fact that subliminal digits did not yield enough evidence to ever reach threshold for the first computational step of the chained task . Thus , as in the present case , the same processing chain could have been in place on both conscious and non-conscious trials , but with non-conscious stimuli providing much smaller evidence that did not allow participants to go past the first processing stage and deploy further strategies . There has been ample speculation about the function of awareness , ranging from none whatsoever [51] , [52] to enabling social communication [53] . Our results suggest a potential role of awareness in biasing information processing , namely the strategic exploitation of information in line with prior expectations and goals . This proposal fits with earlier hypotheses which link conscious access with flexible information processing , owing to the possibility of quickly circulating the conscious information to virtually all of the brain's higher level processors [54]–[57] . It also fits with a role of consciousness in enabling “meta-cognition , ” the ability to introspect about self-performance , which also has been associated with high-level processing in the prefrontal cortex [58] . Here , this strategic biasing process showed clear behavioral and neural advantages: it sped up processing and reduced neural computations related to the decision process when enough evidence had already been accrued . Under conditions of severely degraded evidence ( such as near-threshold or subliminal information ) , the most rational strategy could , however , be to give each piece of evidence equal weight [20] . Interestingly , the strategic biasing process for highly visible information may exactly be the reason why “conscious” decision-making may in some special cases actually be poorer than “unconscious” decision-making [59] , [60] , namely when an unbiased ( equal ) weighting of the evidence is required .
All participants in all experiments had normal or corrected-to-normal vision . The study was approved by the local institutional review board ( CMO Arnhem-Nijmegen ) , and a written informed consent was obtained from the participants according to the Declaration of Helsinki , explicating that they agreed to participate in the MEG and behavioral experiments . The experimental stimuli in all experiments were leftward and rightward pointing arrows . Stimuli were black , presented on a grey background , and subtended visual angles of 2 . 0°×0 . 87° ( see Figure S1 ) . Stimuli were presented using a PC running Presentation software ( Neurobehavioral systems , Albany , USA ) and shown on a screen that was ∼75 cm away from the participant . Mask stimuli were constructed such as to either substantially reduce visibility of the stimuli ( metacontrast mask ) , leading to low-visibility ( LV ) stimuli , or have only weak masking properties ( pseudo mask ) , leading to high-visibility ( HV ) stimuli . Masks were identical in terms of overall luminance . Sixteen healthy participants ( 5M/11F , age range 23–35 ) participated in the decision-making task ( 640 trials ) within the MEG environment . Participants were presented with sequences of five successive arrows , each of which were briefly presented ( 17 ms ) , and followed 50 ms after its onset by a mask ( 100 ms ) , and a blank ( 150 ms ) . Therefore , the stimulus onset asynchrony ( SOA ) between successive arrows was 300 ms . Half of the trials contained metacontrast masks ( leading to low-visibility [LV] stimuli ) and the other half pseudo-masks ( leading to high-visibility [HV] stimuli; see Figure 1A ) . Each arrow sequence contained either all LV or all HV arrows . At the end of each arrow sequence , the fixation square turned green , and the participants had to decide as quickly as possible whether the predominant direction of the arrow stimuli was left or right , by pressing a button with their left or right hand . Participants had to respond within a 500 ms time window . Each trial was followed by a baseline interval , during which a red fixation square was displayed for an average duration of 2 , 000 ms ( between 1 , 750 and 2 , 250 ms ) . Several days before the MEG experiment participants were invited to the lab day to practice the task ( ∼0 . 5 h ) . Prior to MEG data acquisition , participants engaged in an additional brief training session . During MEG data acquisition , participants engaged in 10 task blocks , each block consisting of 64 trials . Total duration of the experiment was ∼60 min . For five participants , we collected only eight task blocks , due to time constraints . For the analysis of reaction times ( RT ) and responses , we discarded trials to which participants responded very early ( RT<150 ms ) , after the reaction time cut-off ( RT>500 ms ) or not at all ( missed trials ) . For the analysis of responses , we compared the proportion of left/right responses as a function of the amount of accumulated evidence for a left/right response , for HV and LV trials ( Figure 1D ) . For reaction times , we compared the RTs as a function of accumulated evidence for HV and LV trials ( Figure 1E ) . For the analysis of arrow impact as a function of time , we used a logistic multiple regression analysis , in order to independently estimate the effect of each arrow on the decision ( Figure 1F ) . For the analysis of arrow influence as a function of previously accumulated evidence , we quantified the change in proportion of left/right response as a function of the direction of the last arrow , for the three levels of previously accumulated evidence ( 0 , 2 , and 4; see Figure 1B and Figure 1G ) . To investigate ( differences in ) linear trends as a function of accumulated evidence or time , we performed linear regression analysis for each participant and tested the significance of ( differences in ) slopes using ( paired samples ) t tests . We recorded ongoing brain activity during Experiment 1 using a whole-head MEG with 275 axial gradiometers ( VSM/CTF Systems , Port Coquitlam , British Columbia , Canada ) . Head localization was monitored continuously during the experiment using coils that were placed at the cardinal points of the head ( nasion , left and right ear canal ) . The magnetic fields produced by these coils were used to measure the position of the participant's head with respect to the MEG sensor array . In addition to the MEG , the electrooculogram ( EOG ) was recorded from the supraorbital and infraorbital ridge of the left eye for the subsequent artifact rejection . All data analysis was performed using the FieldTrip toolbox developed at Donders Institute for Brain , Cognition and Behaviour [61] using Matlab 7 ( MathWorks , Natick , MA , USA ) . Data were checked for artifacts using a semiautomatic routine that helped detecting and rejecting eye blinks , muscle artifacts , and jumps in the MEG signal caused by the SQUID electronics . Subsequently , independent component analysis was used to remove any heart artifacts and eye movements not rejected by the semiautomatic routine . Finally , we low-pass filtered the data using a two-pass Butterworth filter ( filter order of 6 , frequency cut-off of 40 Hz ) . We did not apply any high-pass filter . We calculated an estimate of the planar gradient for the data analysis on the sensor level . The horizontal and vertical components of the planar gradients were calculated for each sensor using the signals from the neighboring sensors , thus approximating the signal measured by MEG systems with planar gradiometers . The planar field gradient simplifies the interpretation of the sensor-level data because the maximal signal typically is located above the source [62] . We established the significance of the differences in field strength for each experimental factor at the cluster level , using a nonparametric cluster randomization test . This test effectively controls the type I error rate in situations involving multiple comparisons ( such as 275 sensors ) by clustering neighboring sensor pairs that exhibit the same effect . The randomization method first identified sensors whose t statistics exceeded a critical value when comparing two conditions sensor by sensor ( p<0 . 05 , two-sided ) . In the second step , to correct for multiple comparisons , contiguous sensors ( separated by <5 cm ) that exceeded the critical value ( as defined in the first step ) were considered a cluster . The cluster-level test statistic was defined from the sum of the t values of the sensors in a given cluster . The cluster with the maximum sum was used in the test statistics . The type I error rate for the complete set of 275 sensors was controlled by evaluating the cluster-level test statistic under the randomization null distribution of the maximum cluster-level test statistic . This was obtained by randomizing the data between the two conditions across multiple participants , calculating t statistics for the new set of clusters . A reference distribution of cluster-level t statistics was created from 1 , 000 randomizations . The p value was estimated according to the proportion of the randomization null distribution exceeding the observed maximum cluster-level test statistic ( the so-called Monte Carlo p value ) . MEG data analysis focused on ( 1 ) overall differences between processing of LV and HV information; ( 2 ) neural markers of accumulated evidence for LV and HV information; and ( 3 ) effects of change in evidence ( i . e . , repeated versus different arrow direction ) for LV and HV information . In all cases , we performed statistical tests ( corrected for multiple comparisons ) at five intervals after the onset of the arrow stimulus ( from 50–300 ms in 50 ms steps ) . The first 50 ms after the onset of each arrow stimulus were used as a baseline interval . This “baseline” interval was physiologically motivated , for it takes approximately 50 ms for a visual stimulus to reach the cortex [63] . The aim of this baseline procedure was to effectively remove spill-over of overall activity from the previous arrow by subtracting out the activity at the onset of the arrow stimulus . A caveat of this procedure is that the previous LV/HV arrow may lead to a late ( >350 ms ) difference in evoked activity , which is misinterpreted as early differential activity evoked by a later arrow . Inspection of non-baseline-corrected traces suggests that this was not the case for our data ( see Figure S2A , lower panel ) , but this possibility can nevertheless not be conclusively ruled out . For the analysis of overall differences between LV and HV arrows , we compared activity during LV and HV arrows , averaged across all five arrow presentations . For the analysis of global effects of accumulation evidence , we compared activity for LV and HV arrows that had “low prior accumulated evidence” and “high prior accumulated evidence , ” averaged across the third to fifth arrow presentation ( since there is no differential amount of prior accumulated evidence until after the first two arrows are presented ) . Low evidence consisted of trials with zero ( for third and fifth arrow ) or one ( for fourth arrow ) prior accumulated evidence at the onset of the arrow . High evidence consisted of trials with two ( for third and fifth arrow ) , three ( for fourth arrow ) , or four ( for fifth arrow ) prior accumulated evidence at the onset of the arrow . For the analysis of the effect of change in evidence , we compared activity for LV and HV arrows that were either preceded by the same arrow ( repeat ) or preceded by the opposite arrow ( change ) , averaged across the second to fifth arrow presentation ( since there is no preceding arrow until after the first arrow is presented ) . We also sought to establish the first time point of significant differences between LV and HV stimuli for the three clusters that showed a significant difference between stimulus types ( fronto-central , parietal , and occipital clusters ) . We carried out t tests on 5 ms time intervals for the 50–300 ms interval after stimulus onset , on the difference wave between HV and LV stimuli , for each cluster . We defined the first time point of significant difference between HV and LV stimuli as the first sample in which five contiguous samples ( i . e . , 25 ms ) showed a significant ( p<0 . 05 , two-tailed ) difference between conditions . All participants of Experiment 1 also participated in Experiment 2 , while still in the MEG environment . To test visibility of strongly and weakly masked arrows , participants engaged in a six-choice discrimination task ( 120 trials , 50% LV and 50% HV ) . Stimulus and trial timing was exactly the same as in the experimental task with the exception that after the presentation of a trial , the question “How many arrows were pointing to the left/right ? ” was presented . This question remained on the screen until the participant made a response , after which a new trial started . Participants had to indicate their decision by pressing one of six response buttons . Whether participants were instructed to detect right- or left-pointing arrows was counterbalanced across participants . Before administering this task , participants were told that only accuracy was important in this task , not the speed of responding . To minimize strategic guessing , participants were notified of the fact that in this task , overall , equal numbers of trials ( 10 ) of each evidence level were presented . Sixteen participants ( 5M/11F , age range 20–32 ) , who did not participate in Experiments 1 and 2 , took part in the confidence-rating task ( 512 trials ) . Here , we assessed the relationship between decision-making performance and subjective confidence . Stimulus parameters and timing were all identical to Experiment 1 , with the exception of an additional confidence question at the end of each trial , after the participant had given his/her response . The following question was presented , 1 s after the participants' response: “How confident are you about your response ? ” This sentence remained on the screen until the participant made a response , after which a new trial started . Participants had to indicate the confidence in their decision by pressing one of six buttons on the keyboard ( 1 = “pure guess” , 6 = “100% sure” ) . The confidence response was unspeeded . All participants of Experiment 3 also participated in Experiment 4 . Here we assessed the amount of priming engendered by LV and HV arrows , using a masked priming experiment ( 640 trials ) . Here , the outline of the mask also formed an arrow stimulus ( see Figure S1 ) . Participants were instructed to respond as fast as possible to the direction of the mask arrow while ignoring the preceding prime arrow . Stimulus duration was the same as in Experiment 1 . Each trial was followed by a baseline interval with an average duration of 1 , 000 ms ( between 750 and 1 , 250 ms ) .
|
When making a decision , we gather evidence for the different options and ultimately choose on the basis of the accumulated evidence . A fundamental question is whether and how conscious awareness of the evidence changes this decision-making process . Here , we examined the influence of sensory awareness on decision-making using behavioral studies and magneto-encephalographic recordings in human participants . In our task , participants had to indicate the prevailing direction of five arrows presented on a screen that each pointed either left or right , and in different trials these arrows were either easy to see ( high visibility ) or difficult to see ( low visibility ) . Behavioral and neural recordings show that evidence accumulation changed from a linear to a non-linear integration strategy with increasing stimulus visibility . In particular , the impact of later evidence was reduced when more evidence had been accrued , but only for highly visible information . By contrast , barely perceptible arrows contributed equally to a decision because participants needed to continue to accumulate evidence in order to make an accurate decision . These results suggest that consciousness may play a role in decision-making by biasing the accumulation of new evidence .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cognitive",
"neuroscience",
"cognition",
"decision",
"making",
"consciousness",
"biology",
"neuroscience",
"neuroimaging"
] |
2011
|
How Awareness Changes the Relative Weights of Evidence During Human Decision-Making
|
Hereditary hypertrichoses are a group of hair overgrowth syndromes that are extremely rare in humans . We have previously demonstrated that a position effect on TRPS1 is associated with hypertrichosis in humans and mice . To gain insight into the functional role of Trps1 , we analyzed the late morphogenesis vibrissae phenotype of Trps1Δgt mutant mice , which is characterized by follicle degeneration after peg downgrowth has been initiated . We found that Trps1 directly represses expression of the hair follicle stem cell regulator Sox9 to control proliferation of the follicle epithelium . Furthermore , we identified a copy number variation upstream of SOX9 in a family with hypertrichosis that significantly decreases expression of the gene in the hair follicle , providing new insights into the long-range regulation of SOX9 . Our findings uncover a novel transcriptional hierarchy that regulates epithelial proliferation in the developing hair follicle and contributes to the pathology of hypertrichosis .
Hypertrichosis is defined as excessive hair growth for a particular site of the body or age of a patient that is not hormone-dependent . Hypertrichoses are characterized on the basis of multiple criteria: cause ( genetic or acquired ) , age of onset , extent of hair distribution ( universal or localized ) and affected sites . Hereditary hypertrichoses are very rare in humans , affecting as few as one in one billion individuals [1] . Whereas many additional anomalies are associated with hypertrichosis , only a subset of disorders with congenital hypertrichosis present with excessive hair as the primary clinical feature . These include hypertrichosis universalis ( OMIM 145700 ) [2] , Ambras type ( OMIM 145701 ) [3] , X-linked hypertrichosis ( OMIM 307150 ) [4] and generalized hypertrichosis terminalis with or without gingival hyperplasia ( OMIM 135400 ) [5] . We previously demonstrated that a position effect on the zinc-finger transcription factor TRPS1 is associated with two hypertrichosis models , Ambras syndrome ( AS ) in humans and the Koala phenotype in mice [6] . Consistent with a causative role for Trps1 in hypertrichosis , the protein is expressed in the nuclei of mesenchyme-derived dermal papilla cells and the proliferative epithelial cells of human and mouse hair follicles [7] . Heterozygous germline mutations in TRPS1 on chromosome 8q23 in humans result in autosomal dominant inheritance of trichorhinophalangeal syndrome types I and III ( TRPS1 I , OMIM 190350; TRPS III , OMIM 190351 ) [8] , [9] , which are characterized by sparse and slow-growing scalp hair , as well as craniofacial and skeletal abnormalities [10] . Correspondingly , homozygous mutant mice in which the GATA-type zinc-finger domain of Trps1 was deleted ( Trps1Δgt/Δgt ) were reported to have a number of hair follicle , craniofacial and skeletal defects that mirror the phenotypic characteristics of human TRPS patients [11] . Trps1Δgt/Δgt mice die within six hours of birth due to respiratory failure stemming from thoracic skeletal defects . Homozygous mutant mice were reported to completely lack vibrissae follicles during late gestation . In addition , neonatal Trps1Δgt/Δgt mice had an approximately 50 percent reduction in dorsal pelage follicle density compared to their wild-type littermates , whereas heterozygous mice had an intermediate pelage phenotype [11] . Trps1−/− null mice were subsequently generated and were similarly reported to display severe hair follicle abnormalities [12] . We recently performed a detailed histological analysis of early vibrissa follicle morphogenesis in Trps1Δgt/Δgt embryos from E12 . 5–E13 . 5 [13] . We found that the mutant vibrissae were reduced in number , irregularly spaced and developmentally delayed when compared to their wild-type counterparts [13] . Additional analyses revealed that these defects were likely due to disruption of Wnt signaling and the misexpression of several transcription factors and extracellular matrix proteins regulated by Trps1 in the mutant whisker pads [13] . While these studies collectively revealed a requirement for Trps1 during early vibrissa follicle formation , they did not address the mechanism ( s ) underlying the follicle degeneration observed later in these embryos . Hypertrichosis had previously been reported in a case of partial trisomy 17q22-qter associated with a de novo unbalanced translocation [14] , suggesting that the distal portion of human chromosome 17q may contain dosage-sensitive genes that contribute to excessive hair growth . Recently , a series of microdeletions were reported on chromosome 17q24 . 2–q24 . 3 in three cases of familial congenital generalized hypertrichosis terminalis with gingival hyperplasia ( CGHT ) , as well as a de novo microduplication within this same region in a case of sporadic CGHT [15] . The minimal region common to each of these cases lies 2 . 5 Mb upstream of SOX9 , a gene previously shown to be required for the specification and maintenance of hair follicle stem cells in mice [16] , [17] . Here , we uncover a novel transcriptional hierarchy in the hair follicle in which Trps1 regulates Sox9 to control epithelial proliferation in the developing vibrissa follicle in mice . Furthermore , we identify a copy number variation less than 1 Mb upstream of SOX9 in a family with CGHT that significantly decreases expression of the gene in the hair follicle , providing significant insight into the pathology of human hypertrichosis .
We began by performing a thorough histological analysis of vibrissa follicle morphogenesis during late gestation in Trps1Δgt/Δgt embryos . Similar to the defects observed during early morphogenesis in these embryos [13] , the mutant vibrissae follicles that were present at E16 . 5 were reduced in number , irregularly spaced and smaller than wild-type vibrissae , with evidence of both an epithelial peg and dermal condensate ( Figure 1A–1E ) . However , the development of these mutant vibrissae follicles was subsequently arrested , and they degenerated after peg downgrowth had been initiated so that they were rarely visible at birth ( Figure 1F–1J ) . Interestingly , heterozygous Trps1+/Δgt embryos displayed an intermediate vibrissae phenotype ( Figure 1D and 1G ) , with vibrissae follicles that were slightly larger , more advanced in development and greater in number than those detected in Trps1Δgt/Δgt mutant embryos ( Figure 1E and 1H ) , indicating a dose-dependent requirement for Trps1 in multiple hair types . We additionally confirmed the reduction in pelage follicle density reported in homozygous mutant animals [11] ( Figure 1K and 1L ) . To assess the mechanisms underlying vibrissa follicle degeneration in Trps1Δgt/Δgt mutant embryos , we examined the levels of proliferation and apoptosis in these follicles , as well as the expression of numerous cell-type specific markers at embryonic day 16 . 5 ( E16 . 5 ) . Immunofluorescence analyses revealed consistent keratin 14 ( K14 ) expression in the epithelial compartments of wild-type and mutant vibrissae follicles ( Figure 2A and 2B ) , and alkaline phosphatase staining displayed an intact dermal papilla , but a considerably smaller and less dense collage capsule surrounding Trps1Δgt/Δgt mutant vibrissae ( Figure 2C and 2D ) . Collagen type I expression was comparable in the glassy ( basement ) membranes of wild-type and Trps1Δgt/Δgt vibrissae follicles ( Figure 2E and 2F ) . Immunofluorescence analyses of Ki67 expression revealed a marked increase in proliferation throughout the developing Trps1Δgt/Δgt vibrissa follicle ( Figure 2G and 2H ) , while the TUNEL assay indicated similar levels of apoptosis between the two follicle types ( Figure 2I and 2J ) . Of note , expression of the Wnt effector Lef1 was consistent in the dermal papillae and matrix cells of Trps1+/+ and Trps1Δgt/Δgt vibrissae follicles at this timepoint ( Figure 2K and 2L ) , indicating that the deregulation of the canonical Wnt pathway detected in Trps1Δgt/Δgt vibrissae placodes at E12 . 5 [13] is no longer observed during later morphogenesis . Having previously demonstrated that Trps1 directly regulates the expression of the bulge stem cell compartment markers Lhx2 and Tnc in the murine whisker pad [13] , we next asked whether Trps1 might also regulate Sox9 in the hair follicle . As mentioned above , Sox9 crucially regulates several aspects of hair follicle stem cell activity in mice [16] , [17] and lies near the minimal region common to several cases of CGHT [15] . We began by performing immunofluorescence analysis examining the expression of Sox9 during vibrissa follicle morphogenesis . At E12 . 5 , Sox9 was expressed throughout the whisker pad epidermis , with increased expression in the suprabasal layers of the epithelial placode ( Figure S1A ) . By the peg stage at E14 . 5 , Sox9 was expressed throughout the epithelial compartment of the downgrowing follicle , with the exception of the matrix cells ( Figure S1B ) . From E16 . 5–E18 . 5 , Sox9 continued to be expressed throughout the follicle epithelium , with increased expression in the matrix , inner root sheath and outer root sheath layers ( Figure S1C and S1D ) . By P0 however , Sox9 expression became noticeably restricted to the outer root sheath cells extending along the length of the follicle ( Figure S1E and S1E′ ) . Interestingly , faint Sox9 expression was also detected in the dermal papilla as early as E14 . 5 ( Figure S1B , S1C′ , S1D′ and S1E″ ) , as well as in the dermal cells of the collagen capsule surrounding the developing vibrissae follicles ( Figure S1B–S1E ) . With few exceptions , this pattern of Sox9 staining in the vibrissa follicle is consistent with that reported for the developing pelage follicle [16] , [17] , and also with the expression pattern of Trps1 in developing vibrissae [6] . We next performed qRT-PCR analysis comparing the expression of Sox9 in wild-type versus Trps1Δgt/Δgt whisker pad samples at E12 . 5 , when the vibrissae placodes are initially discernible and Sox9 expression is first observed . We found that Sox9 was upregulated 1 . 80-fold ( ±0 . 05; p<0 . 001 ) in the mutant samples compared to wild-type expression levels ( Figure 3A ) . Furthermore , immunofluorescence analyses at E16 . 5 demonstrated continued , increased Sox9 protein expression throughout the epithelial compartment and surrounding collagen capsule of Trps1Δgt/Δgt vibrissae follicles ( Figure 3B and 3C ) . To further dissect the relationship between Trps1 and Sox9 , we performed endogenous chromatin immunoprecipitation experiments in HEK 293T cells to determine whether Trps1 can directly bind the SOX9 promoter . TRPS1 has previously been shown to specifically bind the consensus GATA sequence ( WGATAR ) in DNA [18] , [19] . Upon identifying seven consensus GATA-binding sites within 3 kb of the transcriptional start site of SOX9 ( Figure 3E ) , we found that Trps1 bound up to five of these sites in the SOX9 promoter ( Figure 3D ) . We next performed luciferase reporter promoter assays in HEK 293T cells and demonstrated that Trps1 represses SOX9 transcription ( 31 . 11±5 . 44%; p = 0 . 118 ) in a dose-dependent manner ( Figure 3F ) . This repression was alleviated upon mutation of each of the Trps1-binding sites from WGATAR to WGATCR ( p<0 . 01; Figure 3F ) . Decreased Sox9 expression was previously observed in both Shh−/− and Gli2−/− mutant hair germs [17] , indicating that Shh signaling may also regulate Sox9 expression in the hair follicle . This relationship is supported by numerous reports that implicate SHH activation of Sox9 expression during chondrogenesis in chick [20] , mouse [21] , [22] and humans [23] . To determine whether Trps1 colocalizes with cells expressing Shh in the vibrissa follicle , we performed immunofluorescence analyses on serial sections of adult ShhIres-nLacZ vibrissae follicles , wherein nuclear β-galactosidase staining is observed in cells expressing Shh . We demonstrated that Trps1 colocalizes with β-galactosidase in cells of the matrix and inner root sheath layers , indicating coexpression of Trps1 and Shh in these proliferative cells at the base of the follicle ( Figure S2 ) . Postulating that Shh signaling and Trps1 expression would have opposing effects on Sox9 expression in the hair follicle , we next asked whether introduction of a Shh null allele could rescue the vibrissae phenotype of Trps1+/Δgt embryos . We generated Trps1+/Δgt;Shh+/GFP-cre compound heterozygous mice and performed detailed histological examinations of their vibrissae follicles at multiple timepoints throughout embryogenesis . Transverse whisker pad sections revealed that Trps1+/+;Shh+/GFP-cre vibrissae ( Figure 4C , 4G , 4K and 4O ) developed similarly to wild-type follicles from E12 . 5–E18 . 5 ( Figure 4A , 4E , 4I and 4M ) . As expected , Trps1+/Δgt;Shh+/+ embryos exhibited a reduction in vibrissae placode number at E12 . 5 ( Figure 4B ) , and displayed follicles that were reduced in number , irregularly spaced and slightly smaller than wild-type vibrissae throughout the remainder of embryogenesis ( Figure 4F , 4J and 4N ) . However , this phenotype was completely rescued at all timepoints in Trps1+/Δgt;Shh+/GFP-cre compound heterozygous mice ( Figure 4D , 4H , 4L and 4P ) . Importantly , the expression of Sox9 transcripts returned to wild-type levels in compound heterozygous whisker pads ( Figure 4Q ) and Sox9 protein expression was restored to wild-type levels throughout the epithelial compartment of the vibrissae follicles in Trps1+/Δgt;Shh+/GFP-cre embryos ( Figure 4R and 4S ) . We previously demonstrated that a position effect on TRPS1 is associated with cases of hypertrichosis in both humans and mice [6] . Here , we report a family in which the father ( patient I-1 ) and son ( patient II-2 ) exhibited CGHT with mild gingival hyperplasia ( Figure 5A ) . The father is of French and African descent , while the mother is of German descent . The affected patients presented with striking generalized hypertrichosis , which was most prominent on the face , ears and upper trunk . Both father and son displayed bushy eyebrows with synophrys and elongated eyelashes , as well as downslanted fissures and epicanthic folds . The hair covering the face and body was often coarse , straight and black . The parents reported that the son developed progressive hypertrichosis shortly after birth . Both patients additionally exhibited bulbous nasal tips , thick nasal wings , a long , prominent philtrum with a deep groove and mild thoracic kyphoscoliosis . No lip swelling or eversion was observed . Endocrine and metabolic assessments were unremarkable for both patients . To search for chromosomal anomalies in these patients , genomic DNA was isolated from peripheral blood samples collected from the family members and genotyped using the Affymetrix Cytogenetics Whole-Genome 2 . 7 M Array and Affymetrix Genome-Wide Human SNP Array 6 . 0 for Cytogenetics . The resulting data were analyzed with the Affymetrix Chromosome Analysis Suite Version 1 . 0 . 1 software . We obtained consistent results with both arrays , identifying a series of four novel duplications with sizes of 391 kb , 66 kb , 1 . 2 Mb and 35 kb , respectively , within a 2 . 4 Mb region in chromosome 17q24 . 2–q24 . 3 in both affected patients . The telomeric end of this region lies 975 kb upstream of the Trps1 target gene SOX9 ( Figure 5B ) . While eight duplications with a combined size of 487 kb are reported in this region in the public Database of Genomic Variants , our findings uncover approximately 1 . 2 Mb of novel duplicated chromosomal material within this region . Furthermore , the duplicated region encompasses the 1 . 4 Mb duplication identified in a sporadic case of CGHT reported by Sun et al . [15] , and extends 86 kb beyond the centromeric border and 917 kb beyond the telomeric border of that region ( Figure 5B ) . To confirm the duplications , we performed quantitative PCR analysis using the DNA of patient II-2 , the proband , as well as that of an unaffected control individual , to examine the relative copy number of amplicons across the region . Patient II-2 had a 2 . 24-fold increase ( ±0 . 12; p<0 . 001 ) in relative copy number of one amplicon within the region ( amplicon 2 ) , and a 1 . 54-fold increase ( ±0 . 18; p<0 . 05 ) of a second amplicon within the duplication region ( amplicon 3 ) as compared to an unaffected control individual . There were no significant changes in relative copy number of two amplicons ( amplicons 1 and 4 ) on either side of the duplication region in patient II-2 ( Figure 5C ) . We next performed fluorescent in situ hybridization ( FISH ) analysis to determine the orientation of the large 1 . 2 Mb duplication within our candidate region . Interphase chromosome spreads prepared from the blood of patient II-2 were hybridized with green 5-Fluorescein dUTP labeled probe RP11 clone 164B17 and orange 5-TAMRA dUTP labeled probe RP11 clone 831L20 , which span chromosome 17q base pairs 65 , 334 , 626–65 , 500 , 838 and 66 , 328 , 117–66 , 543 , 177 , respectively . FISH analysis revealed one wild-type chromosome with a single hybridization signal for each probe in the patient cells , as well as one chromosome containing duplicated genetic material with two hybridization signals for each probe ( Figure S3 ) . The pattern of probe hybridization in the rearranged chromosome ( green-orange-orange-green ) demonstrated that the 1 . 2 Mb duplication in patient II-2 was an inverted duplication ( Figure S3 ) . To determine the effect of the duplications in the proband on SOX9 expression in the skin and hair follicle , we performed immunofluorescence analyses on a biopsy taken from the posterior neck of patient II-2 and a sample taken from the lower scalp of an unaffected control individual . Patient II-2 had a striking decrease in SOX9 protein expression throughout the follicle epithelium as compared to normal expression levels , primarily in the proliferative epithelial cells at the base of the follicle ( Figure 6A and 6B ) . Histological analyses demonstrated that the patient follicles were more highly pigmented than those of the unaffected control individual , and larger in diameter , particularly in the medulla layer in the center of the hair shaft ( Figure 6C and 6D ) . TRPS1 expression was similar within the follicles of patient II-2 and the control individual ( Figure 6E and 6F ) , consistent with its role upstream of SOX9 expression . In conclusion , these results demonstrate that a large 2 . 4 Mb duplication 975 kb upstream of SOX9 significantly decreases the expression of the gene in the hair follicle , consistent with a position effect on SOX9 .
While human hypertrichoses have been described in literature dating back to the 16th century , the genetic determinants and molecular mechanisms underlying these conditions have remained elusive . We have previously demonstrated that a position effect on TRPS1 is associated with hypertrichosis in both humans and mice [6] , providing the first evidence for a position effect associated with abnormalities in hair follicle development . Here , we establish that a position effect on the Trps1 target gene SOX9 is likely involved in the pathology of human hypertrichosis . Our findings provide the first instance of direct upstream regulation of the hair follicle stem cell specification gene Sox9 , revealing its role in regulating epithelial proliferation downstream of both Trps1 and the Shh pathway in the developing follicle . Our data indicate that Trps1 expression and Shh signaling balance the regulation of Sox9 expression in proliferative hair follicle epithelial cells , with Shh and its downstream effector ( s ) acting as positive regulators of Sox9 expression and Trps1 repressing Sox9 transcription . Gli2 is the main mediator of Shh signaling in the skin and hair follicle [24] and ectopic overexpression of a constitutively active form of Gli2 , ΔNGli2 , in the basal layer of the skin is sufficient to induce Sox9 expression , suggestive of direct activation of Sox9 expression by Gli2 [17] . We did not identify either of the reported consensus GLI binding sites [25] , [26] within the 3 kb SOX9 promoter that we analyzed , indicating that Trps1 may regulate SOX9 expression at distinct sites from Gli proteins . Consistent with our model , we demonstrated that a Shh null allele is able to completely rescue the vibrissae phenotype of Trps1+/Δgt embryos in compound heterozygous mice and restore Sox9 expression to wild-type levels . Consistent with a downstream convergence of Trps1 and Shh pathway signaling in the hair follicle , Trps1Δgt/Δgt follicles share a number of phenotypic similarities with Shh−/− and Gli2−/− mutant follicles , most notably a reduction in follicle number and follicle arrest shortly after induction [24] , [27] , [28] . While Shh−/− embryos were reported to develop vibrissae follicles despite their extensive craniofacial defects , Gli2−/− mice had fewer and under-developed vibrissae [24] . Furthermore , the number of pelage follicles in Shh−/− and Gli2−/− mutant mice is reduced by 25 to 60 percent . The pelage follicles that do form have small hair germs that arrest shortly after induction , with evidence of both epithelial invasion of the dermis and dermal condensation of the mesenchyme at the base of the germ [24] , [27] , similar to the phenotype observed in Trps1Δgt/Δgt mutant embryos . When grafted onto immunocompromised nude mice , whole embryonic dorsal Shh−/− skin exhibited increased proliferation in the follicle epithelium [27] , [28] , comparable to the increased proliferation observed throughout Trps1Δgt/Δgt vibrissae follicles . Conditional ablation of Sox9 in the epidermal compartment of the skin and hair follicle during embryogenesis ( K14-Cre;Sox9fl/fl ) resulted in an 80 percent reduction in vibrissae follicle number at birth and the absence of an external pelage hair coat as early as P6 [16] , akin to the sparse vibrissae and pelage observed in Trps1Δgt/Δgt mice . Similarly , postnatal ablation of Sox9 in the skin epithelia ( Y10-Cre;Sox9fl/fl ) resulted in small , atrophic pelage hairs in the caudal region of the body , many of which degenerated after the first hair cycle [17] , pointing to a requirement for Sox9 in maintenance of the hair follicle after early development . Furthermore , both homozygous mutant Y10-Cre;Sox9fl/fl and K14-Cre;Sox9fl/fl mice exhibited a decrease in the number of proliferative matrix cells [16] , [17] . As our results indicate that Trps1 represses Sox9 expression , this reduced proliferation is analogous to the opposite phenotype of increased proliferation throughout Trps1Δgt/Δgt vibrissae . Shh is a morphogen that plays a key role in regulating the proliferation and downgrowth of the follicular epithelium during late morphogenesis [27]–[29] , and in promoting anagen initiation during postnatal hair follicle cycling [30] , [31] . Transient , ectopic expression of Shh in the dorsal skin can initiate anagen in resting telogen follicles and accelerate hair growth [30] . Notably , excessive activation of the Shh signaling pathway is a common feature of many hair follicle tumors , including basal cell carcinomas ( BCC ) [32]–[34] . Overexpression of Shh , Gli1 , Gli2 or an activated mutant allele of Smo in the murine epidermis was sufficient to induce BCC formation [32] , [34]–[36] , further supporting a role for the Shh pathway in regulating cell proliferation in the epithelia of the hair follicle . Sox9 expression is upregulated in both mouse and human BCC tumors [17] and was later shown to be a general marker of human BCC and additional hair follicle-derived tumors [37] , consistent with its activation downstream of Shh signaling . We found that Trps1 colocalizes with cells expressing Shh in the matrix and inner root sheath layers of the vibrissa follicle , and furthermore , that Sox9 is also expressed in these cells beginning at mid-morphogenesis . The highly proliferative matrix epithelial cells at the base of the follicle give rise to the various differentiating layers of the inner root sheath during hair follicle morphogenesis [38] . Postnatally , interactions between the mesenchyme-derived dermal papilla and the epithelial matrix cells similarly result in growth of the hair shaft during anagen [39] . The coexpression of Trps1 , Shh and Sox9 in the matrix cells and their inner root sheath derivatives suggests a role for Trps1 in regulating vibrissa follicle proliferation during epithelial growth through its direct regulation of Sox9 . Sox9 has previously been shown to be required for specification of hair follicle stem cells [16] . Furthermore , genetic marking techniques have demonstrated that Sox9-derived progeny give rise to all the epithelial cells of the hair follicle [16] . We propose that the dysregulation of Sox9 in the absence of Trps1 would result in a defect in progenitor cell activity in the hair follicle . Upon increased Sox9 expression in Trps1Δgt/Δgt mutant vibrissae , additional hair follicle progenitor cells would be specified . However , in the absence of Sox9 repression by Trps1 , these cells would proliferate prematurely , thereby depleting the follicle of slow-cycling progenitor cells with long-term proliferative potential . Consistent with this hypothesis , Trps1Δgt/Δgt embryos exhibit increased proliferation throughout vibrissae follicles prior to their degeneration . In the absence of progenitor cells to fuel the epithelial proliferation necessary to complete morphogenesis , these Trps1Δgt/Δgt follicles arrest . Lending support to this notion , conditional ablation of Smo in the hair follicle epithelium ( K14-Cre;Smofl/fl ) resulted in decreased Shh signaling and Sox9 expression in these cells . Importantly , these changes were accompanied by reduced proliferation in the matrix and depletion of the hair follicle stem cell niche [40] . A number of mutations in and around the human SOX9 gene result in diseases with phenotypic similarities to TRPS types I and III . Notably , the two patients with CGHT reported here share many phenotypic similarities with AS patients , including hypertrichosis of the face , ears and upper trunk , a bulbous tip of the nose , thick nasal wings and a long , prominent philtrum with a deep groove [3] , providing further evidence that SOX9 and TRPS1 function in the same developmental pathway . Position effects have previously been described for a number of Trps1 target genes , including SOX9 [41] , [42] , which lead to rare genetic skeletal disorders . Taken together , our data implicate that position effects on TRPS1 as well as its target gene SOX9 may play a causative role in human hypertrichoses . Thus , while intragenic mutations or deletions of each of these genes result in hair and bone abnormalities , they are also subject to long-range regulation that , upon disruption , can generate unique phenotypes at sites of the body where these genes are expressed .
Upon obtaining informed consent , peripheral blood samples were collected from family members under approval of the Institutional Review Board of Columbia University and in adherence to the Declaration of Helsinki Principles . All mouse experiments were performed under approval of the Institutional Animal Care and Use Committee of Columbia University . Trps1+/tm1Shiv mice [11] , referred to in the text as Trps1+/Δgt , were a generous gift of Dr . Ramesh Shivdasani , Dana-Farber Cancer Institute , Harvard Medical School . Shh+/tm4Amc mice [43] , [44] , referred to in the text as Shh+/Ires-nLacZ , were a generous gift of Dr . Ed Laufer , Columbia University . Shh+/tm1 ( EGFP/cre ) Cjt mice [45] , referred to in the text as Shh+/GFP-cre , were obtained from The Jackson Laboratory . Heterozygous Shh+/tm1 ( EGFP/cre ) Cjt males were bred to heterozygous Trps1+/tm1Shiv females to generate compound heterozygous mice . Whole mouse muzzle skin and/or whole mouse dorsal skin was dissected at multiple timepoints from E12 . 5 ( 12 . 5 days post coitus , day of plug considered 0 . 5 days ) through P0 ( postnatal day 0 ) in 1× phosphate-buffered saline ( PBS ) , fixed in 10% formalin for up to 72 hrs , washed through an ethanol series and embedded in paraffin . After deparaffinization and rehydration , 8 µm sections were stained with hematoxylin and eosin and permanently mounted with Permount ( Thermo Fisher Scientific , Inc . , Waltham , MA , USA ) for observation under a light microscope . Sections were photographed using an HRC Axiocam fitted onto an Axioplan2 fluorescence microscope ( Carl Zeiss , Inc . , Thornwood , NY , USA ) . Sections of patient skin biopsies mounted in O . C . T . compound ( Sakura Finetek USA , Inc . , Torrance , CA , USA ) and frozen in liquid nitrogen were similarly stained and photographed . Sections of whole mouse muzzle skin or patient skin biopsies mounted in O . C . T . compound ( Sakura Finetek USA , Inc . ) and frozen in liquid nitrogen were fixed in 4% paraformaldehyde ( PFA ) /0 . 1% Triton-X for 10 min at room temperature or in methanol for 15 min at −20°C followed by acetone for 2 min at −20°C and washed in PBS . The sections were then blocked for 1 hr in 10% heat-inactivated goat serum in PBS and incubated overnight at 4°C in primary antibody diluted in 1% serum in PBS . Primary antibodies and dilutions were as follows: anti-keratin 14 ( 1∶5 , 000; gift of Dr . Jurgen Schweizer , German Cancer Research Center ) ; anti-Collagen type I ( 1∶500; Developmental Studies Hybridoma Bank ) ; anti-Ki67 ( 1∶1 , 000; Abcam Inc . , Cambridge , MA , USA ) ; anti-Lef1 ( 1∶25; Santa Cruz Biotechnology , Santa Cruz , CA , USA ) ; anti-Sox9 ( 1∶1 , 000; Santa Cruz Biotechnology ) ; anti-Trps1 ( 1∶5 , 000; gift of Dr . Ramesh Shivdasani , Dana-Farber Cancer Institute , Harvard Medical School; [18] ) ; anti-β-galactosidase ( 1∶1 , 000; MP Biomedicals , Solon , OH , USA ) . After washing in PBS , the sections were incubated in either an Alexa Fluor 594 goat anti-rabbit IgG or Alexa Fluor 488 goat anti-rabbit IgG ( Molecular Probes , Invitrogen , Carlsbad , CA , USA ) secondary antibody ( 1∶500 ) diluted in 1% serum in PBS for 1 hr . Sections were mounted in VECTASHIELD mounting medium with DAPI ( Vector Laboratories , Burlingame , CA , USA ) and photographed using an HRC Axiocam fitted onto an Axioplan2 fluorescence microscope ( Carl Zeiss , Inc . ) or an LSM 5 laser scanning Axio Observer Z1 confocal microscope ( Carl Zeiss , Inc . ) . Alkaline phosphatase activity was detected based on a previously published protocol [46] . Briefly , 8 µm sections of E16 . 5 whole mouse muzzle skin mounted in O . C . T . compound ( Sakura Finetek USA , Inc . ) and frozen in liquid nitrogen were fixed in acetone at −20°C for 5 min and washed in PBS for 5 min at room temperature . The sections were then washed in buffer containing 0 . 1 M Tris-HCl pH 9 . 5 and 0 . 1 M NaCl for 5 min at room temperature and incubated in substrate containing 250 µg/mL 4-Nitro blue tetrazolium chloride ( NBT; Roche Applied Science , Indianapolis , IN , USA ) and 125 µg/mL 4-toluidine salt ( BCIP; Roche Applied Science ) diluted in the above buffer for 12 min in the dark . After a 5 min wash in PBS , sections were mounted in VECTASHIELD mounting medium for fluorescence ( Vector Laboratories ) and photographed using an HRC Axiocam fitted onto an Axioplan2 fluorescence microscope ( Carl Zeiss , Inc . ) . TUNEL staining was performed on 8 µm sections of E16 . 5 whole mouse muzzle skin mounted in O . C . T . compound ( Sakura Finetek USA , Inc . ) and frozen in liquid nitrogen . Sections were fixed in 1% PFA/PBS for 10 min , washed in PBS and post-fixed in 2∶1 ethanol∶acetic acid for 5 min at −20°C before being fluorescently stained using the ApopTag Plus Fluorescein In Situ Apoptosis Detection Kit ( Millipore , Billerica , MA , USA ) according to the manufacturer's instructions . Sections were mounted in VECTASHIELD mounting medium with DAPI ( Vector Laboratories ) and photographed using an HRC Axiocam fitted onto an Axioplan2 fluorescence microscope ( Carl Zeiss , Inc . ) . All positive signals were confirmed by DAPI staining . Total RNA was isolated from whole mouse muzzle skin at E12 . 5 or E16 . 5 using the RNeasy Mini Kit ( Qiagen Inc . , Valencia , CA , USA ) according to the manufacturer's instructions . First-strand cDNA was synthesized using a ratio of 2∶1 random primers: Oligo ( dT ) primer and SuperScript III RT ( Invitrogen ) according to the manufacturer's instructions . qRT-PCR was performed on an ABI 7300 machine and analyzed with ABI Relative Quantification Study software ( Applied Biosystems , Foster City , CA , USA ) . Primers were designed according to ABI guidelines and all reactions were performed using Power SYBR Green PCR Master Mix ( Applied Biosystems ) , 250 nM primers ( Invitrogen ) and 100 ng cDNA in a 20 µL reaction volume . The following PCR protocol was used: step 1: 50°C for 2 min; step 2: 95°C for 10 min; step 3: 95°C for 15 s; step 4: 60°C for 1 min; repeat steps 3 and 4 for 40 cycles . All samples were run in quadruplicate for three independent runs and normalized against an endogenous internal control , B2m . PCR products were electrophoresed on a 1% agarose/TBE gel containing ethidium bromide and photographed on a Kodak Electrophoresis Documentation and Analysis System 120 Camera ( Kodak , Rochester , NY , USA ) to confirm amplicon size . The qRT-PCR primers used can be found in Table S1 . HEK 293T cells were seeded onto 10 cm dishes and cultured to 80–90% confluency in Dulbecco's modified Eagle's medium ( DMEM; GIBCO , Invitrogen ) supplemented with 10% fetal bovine serum ( GIBCO ) , 100 IU/mL penicillin and 100 µg/mL streptomycin . The cells were treated with 1% formaldehyde for 10 min at 37°C , washed twice with cold PBS containing protease inhibitors and harvested . Chromatin immunoprecipitation was carried out using the Chromatin Immunoprecipitation ( ChIP ) Assay Kit ( Millipore ) according to the manufacturer's instructions . Cell lysates were precipitated with 3 µg of either an anti-Trps1 rabbit polyclonal antibody ( gift of Dr . Ramesh Shivdasani , Dana-Farber Cancer Institute , Harvard Medical School; [18] ) or normal rabbit IgG ( Santa Cruz Biotechnology ) as a negative control . After elution , DNA was recovered using the Rapid PCR Purification System ( Marligen Biosciences , Inc . , Ijamsville , MD , USA ) . PCR reactions were performed using input , IgG-precipitated and Trps1-precipitated DNA samples , Platinum PCR SuperMix ( Invitrogen ) and 0 . 67 µM primers ( Invitrogen ) in a 30 µL reaction volume . The primers used for the various promoter regions as well as coding sequence negative controls can be found in Table S2 . The following PCR protocol was used: step 1: 94°C for 5 min; step 2: 94°C for 45 s; step 3: 55°C for 30 s; step 4: 72°C for 1 min; repeat steps 2–4 for 36–40 cycles; step 5: 72°C for 10 min . PCR products were electrophoresed on a 1% agarose/TBE gel containing ethidium bromide and photographed on a Kodak Electrophoresis Documentation and Analysis System 120 Camera ( Kodak ) . Positive immunoprecipitation results were confirmed in at least two independent trials . To generate the mTrps1 expression plasmid , the open reading frame of Trps1 was amplified by PCR and subcloned into the SacI and KpnI sites of the mammalian expression vector pCXN2 . 1 [47] . The hSOX9 promoter ( 3145 bp ) was amplified by PCR from BAC clone RP11-727K24 using the following primers: hSOX9p-F-MluI: 5′-CAAACGCGTTTCTACCTGTGTCTGAGGTC-3′ hSOX9p-R-HindIII: 5′-GACAAGCTTAGGGGTCCAGGAGATTCATA-3′ The amplified product was subcloned into the MluI and HindIII sites of the luciferase reporter vector pGL3-Basic ( Promega , Madison , WI , USA ) . Mutated promoter reporter plasmids were generated by introducing a point mutation in select consensus GATA binding sites ( WGATAR→WGATCR ) using the QuikChange II XL Site-Directed Mutagenesis Kit ( Agilent Technologies , Inc . , Santa Clara , CA , USA ) according to the manufacturer's instructions . Mutagenic primers were designed using the web-based QuikChange Primer Design Program ( http://www . stratagene . com/qcprimerdesign ) and can be found in Table S3 . HEK 293T cells were seeded onto 6-well dishes 24 hr before transfection . At 80% confluency , a hSOX9 promoter reporter plasmid or pGL3 backbone vector ( 1 µg ) were transfected into each well in combination with the mTrps1 expression plasmid or pCXN2 . 1 backbone vector ( 1 µg ) using Lipofectamine 2000 ( Invitrogen ) . A plasmid encoding a β-galactosidase reporter ( 0 . 5 µg ) was also transfected for normalization of transfection efficiency . The cells were cultured for 24 hr after transfection in Opti-MEM ( GIBCO , Invitrogen ) , harvested and lysed . Luciferase and β-galactosidase signals were measured using the Luciferase Assay System ( Promega ) and β-Galactosidase Enzyme Assay System with Reporter Lysis Buffer ( Promega ) , respectively , according to the manufacturer's instructions . All assays were performed in triplicate for three independent trials . Peripheral blood samples were collected from family members in EDTA-containing tubes . Genomic DNA was isolated using the Gentra Puregene Blood Kit ( Qiagen Inc . ) according to the manufacturer's instructions . Genomic DNA was electrophoresed on a 1% agarose/TBE gel containing ethidium bromide to ensure that approximately 90 percent of the sample was greater than 10 kb in size . Samples with an OD 260/280 ratio between 1 . 8–2 . 0 and an OD 260/230 ratio greater than 1 . 5 were considered pure . DNA was processed according to the manufacturer's instructions for the Affymetrix Cytogenetics Whole-Genome 2 . 7 M Array and the Affymetrix Genome-Wide Human SNP Array 6 . 0 for Cytogenetics ( Affymetrix , Inc . , Santa Clara , CA , USA ) . Briefly , approximately 100 ng of genomic DNA was denatured and amplified during a 3 hr PCR reaction . After purification , a Nanodrop spectrophotometer ( Thermo Fisher Scientific , Inc . ) was used to ensure a DNA concentration greater than 0 . 55 ng/µL and an OD 260/280 ratio between 1 . 8–2 . 0 . The DNA was then fragmented into 50–300 bp fragments which were confirmed by agarose gel electrophoresis . The samples were subsequently labeled before hybridization in an Affymetrix GeneChip hybridization oven ( Affymetrix ) . Washes and staining of the arrays with streptavidin-phycoerythrin conjugates were performed with an Affymetrix GeneChip Fluidics Station 450 ( Affymetrix ) , and images were obtained using an Affymetrix GeneChip scanner 3000 ( Affymetrix ) . Quality assessments of the raw data and copy number analyses were performed with Affymetrix Chromosome Analysis Suite Version 1 . 0 . 1 software ( Affymetrix ) . For quality control , the Median Absolute Pairwise Difference ( MAPD ) metric was used to estimate variability on a per-chip basis . If log2 ratios are distributed normally with a constant standard deviation ( SD ) , MAPD/0 . 96 is equal to SD and MAPD*1 . 41 is equal to interquartile range . With a constant log2 ratio SD of 0 . 3 , MAPD values less than 0 . 27 were considered acceptable for copy number analysis . In accordance with the software baseline parameters , a default diagonal weight of 0 . 995 was employed to minimize frequent changes in copy number . Copy number variants greater than 200 kb in length were considered significant . A pan-ethnic control reference set derived from 24 males and 24 females generated in our facility was incorporated into the analysis . qPCR was performed on an ABI 7300 machine and analyzed with ABI Relative Quantification Study software ( Applied Biosystems ) . Primers were designed according to ABI guidelines and all reactions were performed using Power SYBR Green PCR Master Mix ( Applied Biosystems ) , 500 nM primers ( Invitrogen ) and 50 ng genomic DNA in a 20 µL reaction volume . The following PCR protocol was used: step 1: 50°C for 2 min; step 2: 95°C for 10 min; step 3: 95°C for 15 s; step 4: 60°C for 1 min; repeat steps 3 and 4 for 40 cycles . All samples were run in triplicate for three independent runs and normalized against an internal control , GAPDH . PCR products were electrophoresed on a 1% agarose/TBE gel containing ethidium bromide and photographed on a Kodak Electrophoresis Documentation and Analysis System 120 Camera ( Kodak ) to confirm amplicon size . The qPCR primers used can be found in Table S4 . Lymphoblasts from peripheral patient blood samples were cultured and harvested and interphase chromosome spreads were prepared using standard cytogenetic protocols . Slides were dried at room temperature overnight , then washed in 2× saline sodium citrate ( SSC ) buffer at 73°C for 2 min and dehydrated through an ethanol series . Fluorescent labeled probes ( Empire Genomics , Buffalo , NY , USA ) were diluted to a final concentration of 40 ng/µL in hybridization buffer ( Empire Genomics ) and denatured at 73°C for 2 min . After probe application , slides were covered with glass coverslips and hybridized at 37°C for 16 hours in a StatSpin ThermoBrite system ( Iris Sample Processing , Inc . , Westwood , MA , USA ) . After removal of the glass coverslips , slides were placed in buffer containing 0 . 4× SSC and 0 . 3% NP-40 at 73°C for 10 s with agitation , followed by a 2 min incubation without agitation . Slides were then transferred to buffer containing 2× SSC and 0 . 1% NP-40 at room temperature for 1 min . Slides were dried in the dark and 10% DAPI was applied to counterstain chromosomes . Hybridized interphase chromosomes were photographed using a Nikon microscope fitted with a filter wheel and Cytovision Applied Imaging software .
|
The various ectodermal appendages found in nature have evolved over time to allow organisms to better adapt to their environment . These include hair , feathers , scales , nails , teeth , beaks , horns , and a wide array of eccrine glands . The hair follicle is an ectodermal appendage unique to mammals that serves a wide array of functions , including thermoregulation , sensation , and communication . Hair follicle formation begins during embryogenesis through a series of interactions between adjacent epithelial and mesenchymal tissues . The mechanisms by which the diverse cells types of the hair follicle arise and the contribution of progenitor cells to the processes of growth and differentiation are not completely understood . Here , we have identified the transcription factor Trps1 as a novel regulator of epithelial proliferation in the developing hair follicle , through its control of Sox9 , a gene known to regulate hair follicle stem cells . Moreover , we demonstrate that duplicated genetic material upstream of SOX9 , which alters expression of the gene , results in a rare form of hereditary hair overgrowth syndrome in humans .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"growth",
"control",
"gene",
"networks",
"animal",
"genetics",
"genetic",
"mutation",
"functional",
"genomics",
"chromosome",
"structure",
"and",
"function",
"gene",
"regulation",
"dna",
"transcription",
"gene",
"function",
"animal",
"models",
"genetics",
"of",
"disease",
"developmental",
"biology",
"model",
"organisms",
"organism",
"development",
"molecular",
"development",
"molecular",
"genetics",
"morphogenesis",
"embryology",
"genomics",
"chromosome",
"biology",
"gene",
"expression",
"organogenesis",
"biology",
"mouse",
"signaling",
"heredity",
"genetics",
"human",
"genetics",
"cytogenetics",
"genetics",
"and",
"genomics"
] |
2012
|
Trps1 and Its Target Gene Sox9 Regulate Epithelial Proliferation in the Developing Hair Follicle and Are Associated with Hypertrichosis
|
The 2015-16 Zika virus pandemic originating in Latin America led to predictions of a catastrophic global spread of the disease . Since the current outbreak began in Brazil in May 2015 local transmission of Zika has been reported in over 60 countries and territories , with over 750 thousand confirmed and suspected cases . As a result of its range expansion attention has focused on possible modes of transmission , of which the arthropod vector-based disease spread cycle involving Aedes species is believed to be the most important . Additional causes of concern are the emerging new links between Zika disease and Guillain-Barre Syndrome ( GBS ) , and a once rare congenital disease , microcephaly . Like dengue and chikungunya , the geographic establishment of Zika is thought to be limited by the occurrence of its principal vector mosquito species , Ae . aegypti and , possibly , Ae . albopictus . While Ae . albopictus populations are more widely established than those of Ae . aegypti , the relative competence of these species as a Zika vector is unknown . The analysis reported here presents a global risk model that considers the role of each vector species independently , and quantifies the potential spreading risk of Zika into new regions . Six scenarios are evaluated which vary in the weight assigned to Ae . albopictus as a possible spreading vector . The scenarios are bounded by the extreme assumptions that spread is driven by air travel and Ae . aegypti presence alone and spread driven equally by both species . For each scenario destination cities at highest risk of Zika outbreaks are prioritized , as are source cities in affected regions . Finally , intercontinental air travel routes that pose the highest risk for Zika spread are also ranked . The results are compared between scenarios . Results from the analysis reveal that if Ae . aegypti is the only competent Zika vector , then risk is geographically limited; in North America mainly to Florida and Texas . However , if Ae . albopictus proves to be a competent vector of Zika , which does not yet appear to be the case , then there is risk of local establishment in all American regions including Canada and Chile , much of Western Europe , Australia , New Zealand , as well as South and East Asia , with a substantial increase in risk to Asia due to the more recent local establishment of Zika in Singapore .
In May 2015 , a Zika disease outbreak originated in Brazil , and by October 5 , 2016 , local transmission of the Zika virus had been reported in over 60 countries and territories , with over 750 thousand estimated cases [1] . The World Health Organization ( WHO ) previously predicted that the virus would establish itself in all countries in the Americas except Canada and Chile [2] , and with few exceptions this scenario has proved true . Travel-imported cases have also been increasingly reported throughout the United States , as well as in Australia , New Zealand , Canada , Western Europe , and China [3] , representing the first time Zika has been reported in many of these western countries . The Zika virus was first isolated in 1947 in a sentinel monkey in the Zika forest of Uganda [4] which gave the virus its name . It was first found in humans in 1952 [5] . However , only 14 human cases were documented prior to 2007 [6] , and these were limited to small isolated epidemics in equatorial Africa and tropical Asia [6] . Since the 1950s the virus has spread eastwards from Africa through Asia and the Pacific , culminating with the 2015-16 outbreak in Latin America [7 , 8] . The first documented recent outbreak of Zika disease occurred on Yap Island in the Federated States of Micronesia in the North Pacific in 2007 with less than 200 acknowledged cases [6] . In 2013 another outbreak occurred in French Polynesia , with around 28 , 000 suspected cases , at which point Zika began to be generally recognized as a re-emerging infectious disease [9] . The outbreak subsequently spread from French Polynesia to other Pacific Islands including New Caledonia , Cook Island , and Easter Island , where autochthonous transmission cycles were established [10] . Travel–imported cases were also documented in Japan [11] , Germany [12] and Norway [10] , among other regions . The recent outbreak in Latin America began in Brazil , with the first documented Zika case reported in May , 2015 [13] , although phylogenetic analyses of virus RNA sequences suggest that the virus was introduced into the Americas between May and December 2013 [14] . The virus quickly spread from Brazil throughout Latin America; by February 2016 , an estimated 31 , 555 cases were identified in Colombia alone [2] . Historically , Zika infection has been associated with mild symptoms typically resembling and milder than those of related arboviruses such as dengue and chikungunya; many cases of infection show no symptoms at all . However , the recent outbreaks in French Polynesia and Latin America have been associated with much more serious clinical manifestations of the virus . In Brazil and French Polynesia , a link between Zika and a rare congenital disease , microcephaly , has been identified [15–22] . Additionally , Guillain-Barre Syndrome ( GBS ) has been reported in patients infected with Zika , firstly in the 2013 French Polynesia outbreak [23] , and since in greater numbers in Brazil , El Salvador , Venezuela , Colombia , and Suriname [22] . The unprecedented size of the outbreak , rate of spread , and potential links with microcephaly and GBS prompted the WHO to declare the current Zika virus outbreak a public health emergency of international concern [24] . Zika now joins a list of arboviral diseases such as dengue and chikungunya that are being increasingly reported in new parts of the world , all likely introduced through global transport systems such as passenger air travel and maritime freight [14 , 25] . Geographic spread of the virus occurs when infected travelers travel from affected regions to ones without local establishment of the disease , but in which the known and suspected vector species have established populations . Like dengue and chikungunya , Zika is known to be spread by Aedes aegypti; it is also strongly suspected to be spread by Aedes albopictus . While vectorial competence of Ae . aegypti is well established [26–29] , and it is now confirmed to be the primary vector in spreading Zika [30–32] , the capacity of Ae . albopictus as a secondary vector for spreading Zika is still unclear . There is evidence of the potential role of Ae . albopictus [33 , 34] , however , there is limited and conflicting quantitative estimate of its efficiency [35 , 36] . Jupille et . al . [35] found that both Ae . aegypti from Madeira Island and Ae . albopictus from France were able to transmit the Zika virus , however Ae . albopictus from France was found to be less suitable to sustain local transmission . Chouin-Carneiro et . al . [36] observed high infection but low transmission rates for both Ae . aegypti and Ae . albopictus , while WHO [31] notes the vector competence for both species is similar , but Ae . albopictus is considered to have lower vector capacity than Ae . aegypti . The outcomes from these studies suggests both species are capable of Zika transmission , while also highlighting the uncertainty in the role that Ae . albopictus may play in transmitting , spreading , and helping to maintain the virus in many areas of the world . Further , potential virus adaptation to new vectors , as demonstrated in the case of Chikungunya in La Reunion [37 , 38] , introduces additional uncertainties . The uncertainty surrounding the vectorial competence of different Aedes species in spreading Zika serves as the main motivation for the present analysis . This study explicitly addresses the differences in the potential geographical risk of Zika spread and local disease cycle establishment if Ae . aegypti is the sole competent vector versus if both Ae . aegypti and Ae . albopictus are competent for this purpose . Scenarios which further vary in the relative capacity of Ae . albopictus as a secondary vector are also considered . As noted earlier , available evidence indicates that the two species differ in their vectorial competence . Moreover , the two species also vary widely in their present geographic distribution: Ae . aegypti is mainly present in wet tropical regions , while Ae . albopictus , a much better disperser , has a wider global presence in temperate regions , including the northern United States and parts of Canada , southern regions of the Americas including Chile , parts of Western Australia and East Asia . The analysis presented here is global and carried out at the finest resolution ( 1 arc-minute ) that was permitted by the available data . Some preliminary findings were reported earlier [39] but the methodology was not described; all the analyses have been expanded and updated here and expectations from those preliminary findings were used to validate conclusions from the analysis using “back-testing” . Several recent studies have mapped the potential spread of Zika into new regions [40–43] . These studies differ from the present one in either the assumptions made about the competence of potential vector species , in the spatial resolution or geographical extent of the study areas used , or in the methodological tools that were used . Monaghan et . al . [42] simulated Ae . aegypti and Ae . albopictus mosquito abundance based on meteorological models , and overlaid the results with travel and socioeconomic factors to estimate the cities in the United States with the highest expected cases of travel-imported Zika . Nah et . al . [43] presented a global risk model for Zika importation which used survival analysis and publicly available epidemiological and air travel data to predict the risk of importation and local transmission of Zika at the country level . In one study , Bogoch et . al . [40] presented an air travel-based risk map of Zika spread from Brazil into the rest of the Americas , and in another study modeled risk posed to Africa and the Asia Pacific region [41] . Both works [40 , 41] implicitly assumed Zika to be equally efficiently spread by both Ae . aegypti and Ae . albopictus , and all studies only considered airline travelers departing the Americas . However , on August 28 , 2016 local Zika spread was confirmed in Singapore , and autochthonous Zika transmission has since been reported across multiple community clusters [44] . With Singapore serving as a new potential source of Zika infected travelers , a substantially higher risk is posed to South and South-east Asia , where Aedes mosquito populations are well established , and Zika and dengue are endemic . The present analysis extends previous work by presenting a global risk analysis based on a new mathematical framework to estimate Zika importation and establishment risk at a city level based on the most recent state of the outbreak , and accounting for uncertainties regarding the vectorial competence of Ae . albopictus . The risk analysis reported in this paper considers six scenarios , A , B , C , D , E and F , respectively , which vary in their assumed relative capacity of Ae . albopictus compared to Ae . aegypti , as a secondary spreading vector of Zika . The scenarios are bounded by two extreme assumptions; in Scenario A spread is assumed to be driven by Ae . aegypti presence alone , while in Scenario F spread is driven by Ae . aegypti and Ae . albopictus presence equally . In Scenarios B through E spread is driven predominately by Ae . aegypti presence with Ae . albopictus presence playing a lesser role . These scenarios are further described in the Materials and Methods section . Besides air travel data , this work utilizes ecological vector habitat suitability models for Ae . aegyti and Ae . albopictus previously developed to analyze the role of air travel in the risk of geographical spread of dengue [45–47] . Those models are relevant to the risk of Zika spread because the same two vector species are implicated with one difference: while Ae . aegypti is known to be an efficient vector for both diseases , in the case of dengue Ae . albopictus is also known to be a competent but less efficient vector , whereas in the case of Zika it is a likely vector but its relative competence is unknown . Thus , the focus of this analysis will be on four questions: The analysis reported here only considers potential vectorial transmission of Zika . It ignores other modes of transmission that have been reported including sexual transmission [22] and congenital transmission [22] .
The following protocol was used for a scenario specific risk analysis . Six scenarios are considered , A–F , which vary in the assumed relative capacity of Ae . albopictus as a spreading vector of Zika . The six scenarios are bounded by Scenario A , where spread is assumed driven by air travel and Ae . aegypti presence alone , and Scenario F , where spread is assumed to be driven by air travel and both species equally . Scenario B , C , D and E represent cases where Ae . albopictus plays a secondary role to Ae . aegypti . Specifically , the relative capacity of Ae . albopictus compared with Ae . aegypti ranges from 10% to 75% across these scenarios . Assigned weights are used in the six scenarios to represent the relative capacity , and are w = 0 , 0 . 10 , 0 . 25 , 0 . 5 , 0 . 75 and 1 for Scenarios A–F , respectively . In Scenario A the assigned weight is 0 , representing the case where Ae . albopictus has no capacity to spread Zika , while in Scenario F the assigned weight is equal to 1 . 0 , representing equal capacity for the two species . The range of weights is selected to demonstrate the variability in the risk posed to or from a particular location as a function of the relative capacity of Ae . albopictus to transmit Zika . Because Ae . aegypti has been confirmed as the primary spreading vector of Zika , the sensitivity analysis is more focused on the lower relative capacities of Ae . albopictus , which is suspected to play a much lesser role . Given these six scenarios , the protocol consists of seven stages: A separate analysis was conducted to evaluate the performance of the risk model . The protocol described above was re-implemented , wherein the set of source airports , S , was defined as those in areas with autochthonous Zika transmission as of February 15 , 2016 rather than October 5 , 2016 [39] . Between February 15 and October 5 , 2016 , 29 new countries and territories were added to the CDC list of affected regions . The ranking and relative risk quantified by the proposed model for each scenario for these 29 countries is presented and discussed . This analysis also serves to identify the sceanrio most consistent with the observed outbreak , and thus the role played by the secondary spreading vector , Ae . albopictus . The proposed risk model is based on data from the global air traffic network and species distribution models for the principle spreading vectors species .
The destination risk model results are illustrated in Fig 1 . The top 100 cities to which Zika may be imported from affected regions for scenarios A , C , D , E and F are shown . The results for Scenario B are too hard to distinguish from A and C in the figure , so it is left out . The size of the circle represents the estimated expected relative risk posed to each city , with the color indicating the scenario . For those cities which are served by more than one international airport , the relative risk for all airports which serve the given city are aggregated . Solid dark red indicates the risk from Ae . aegypti alone , i . e . , Scenario A , and the color of the circles lightens progressively from Scenario A to Scenario F . All risk values are computed using eq ( 3 ) , for their respective scenarios . S1 Table contains the list of the top 100 at risk destination cities included in the map for all six scenarios , including their corresponding rank , relative risk , and designated country . To gain a better understanding of the risk posed by outgoing travelers , the risk posed by each city in a known affected region for exporting infected travelers is also assessed . The top 100 origin cities in the affected regions likely to export Zika to new regions are listed in S2 Table , including their corresponding rank , relative risk , and designated country . Similarly to the destination risk , the relative risk at the city level is aggregated over all airports which serve a given city . S3 and S4 Tables further breaks down the previous results to identify those routes which carry the most risk into and out of cities , and include the top 100 highest risk origin-destination city travel pairs for Scenario A and F , respectively . Finally , in regard to validation , the model was run for each scenario using the set of sources as of February 15 , 2016 along with travel data for February 2015 . The destination risk results were aggregated to the country level , ranked and compared with the actual set of 29 counties/territories that were added to the CDC list of confirmed affected regions between February 15th , 2016 and October 5 , 2016 . Results from the back-testing analysis for each scenario are presented in S5 and S6 Tables . S5 Table lists the set of 29 Countries with local Zika transmission confirmed between February 15 and October 5 and the relative ranking for each of those countries computed for each of the six scenarios . S6 Table lists the top 29 countries at risk for the six scenarios . The results reveal Scenario A identified more of the 29 countries in it’s top 29 ranking than the other three scenarios , however all scenarios identified at least 15 of the 29 , in their top 29 . A more detailed discussion of these results will be presented as part of the Discussion below .
As the Zika outbreak continues to progress , the number of countries with local transmission is increasing , and this was especially the case during the first half of 2016 . The results presented thus far serve as projected relative risk estimates for each city , and can be used to identify the locations most likely to see imported cases followed by local outbreaks in the near future . However , in an attempt to evaluate the model’s ability to accurately identify the regions most likely to experience future outbreaks , as well as identify the level of contribution of Ae . albopictus in the outbreak , we implemented the model using the state of the outbreak in February 15 , 2016 ( to define the set of high risk sources ) , and compared the model outcomes across all scenarios with the actual set of regions later confirmed to be infected . ( These earlier results were partially noted in [39] ) . In fact , all six scenarios ranked Miami , Florida as the top at-risk destination by a significant margin , and in late July , 2016 the first autochthonous Zika cycle in the United States was reported to have been established in the Miami , Florida region . Between February 15th , 2016 and October 5 , 2016 29 new counties or territories were added to the CDC list of confirmed affected regions . These countries are listed in S5 Table . For each of the six scenarios considered , a country level ranking was computed by aggregating the incoming risk across all cities in a given country , and ranking the countries accordingly . These country-level results from the back-testing are presented in S5 with their respective ranking , alongside the list of new countries added to the CDC list during that time . All six scenarios identified at least 15 of the 29 countries in their respective top ranked 29 . However , Scenario A outperformed the other five scenarios , with 21 of the top ranked 29 countries accounted for . As the assumed relative capacity of Ae . albopictus increased , the number of top ranked countries matching the 29 confirmed affected countries decreased . This result suggest that Scenario A , which only accounts for Ae . aegypti presence , is the most accurate model for identifying the regions most likely to experience local establishment in the future . However , it is important to recognize the discrepancy in the rankings across scenarios highlights an important factor; when comparing the performance of the different scenarios it is important to distinguish between risk of importation and risk of local establishment , the later of which we are comparing the results with . In the five scenarios which account for the additional presence of Ae . albopictus , an increasing number of countries identified as high risk ( these are listed in S6 Table ) are in more developed regions , compared with those countries identified by Scenario A . This discrepancy is because suitable habitats for Ae . albopictus expand much further north and south of the equator when compared with Ae . aegypti , therefore many cities in Europe , as well as Japan , Australia , New Zealand , and major cities in the northern U . S . are at substantially increased risk of Zika establishment only if Ae . albopictus is a capable spreading vector . While these locations , critically , have established vector populations and have experienced a high number of imported cases [3] , with the sole exception of Miami , they did not lead to local establishment , likely due to the resources available for local mosquito control and surveillance . Therefore , until the capacity , or lack there of , of Ae . albopictus is confirmed , the cities identified at highest risk in all Scenarios should continue to be subject to a high level of surveillance . Finally , the country level risk predictions in [43] are also consistent with the outcomes of this study . After aggregating the city level relative risks to the country level , the United States and Argentina were identified to be at highest risk in the present study . Nah et . al . [43] ( who excluded the U . S . ) also identified Argentina to be at highest risk of Zika importation , followed by Portugal , Uruguay , Spain , and Peru , which are also among our top ranked countries across the scenarios . While many of the same countries were identified to be at high risk by both models , discrepancies in the rankings exists for various reasons . Firstly , Nah et . al . [43] estimated the risks of importation and local transmission separately , while our model combines the two within a single risk modeling framework . Secondly , the present study was conducted at a later state in the outbreak when more countries were confirmed to have local transmission; these countries are listed in [43] as at-risk of importation , while in the present study they are considered to pose additional risk . Additionally , the present study is conducted at the city level instead of the country level , and due to the more spatially disaggregate analysis , the results can not be directly compared . Although the methodologies vary substantially between these studies , the consistency among the model results serves to further validate the present study . The preliminary findings did not identify the Federated States of Micronesia or the Marshall Islands as high at-risk destinations of any rank , which highlights one of the potential limitations of this analysis that will be explicitly discussed below . This work takes a major step towards improving our understanding of the spreading risk posed by Zika , however there are six limitations of this analysis , including persistent uncertainties regarding epidemiological parameter estimates , which must be noted here and addressed in future research: Results from this analysis highlight the substantial geographic and quantitative increase in global risk posed as a function of the relative capacity of Ae . albopictus as a secondary spreading vector of Zika , and reveal the set of cities at greatest risk of Zika importation and establishment . The results from the back-testing suggest that the geographic spread of Zika is driven primarily by Ae . aegypti , which is consistent with other studies [30–32] . However , the results from the different scenarios also highlight the increased risk posed to new parts of the world , specifically the U . S . and Europe , if Ae . albopictus were to become a more capable spreading vector . To control the spread of Zika geographically , local surveillance and control efforts are required in both known affected regions and at-risk regions yet to report cases . This is true for locations with reported travel-imported cases that have yet to see locally established cases . As the Zika outbreak continues to spread internationally , so does the uncertainty surrounding the local transmission mechanisms and clinical manifestations of the disease . The possibility of direct human-to-human Zika transmission demands further immediate investigation , and the link between Zika and microcephaly and GBS are of vital concern . Lastly , the uncertainty associated with Zika risk is further compounded based on the implications from the analysis presented here which shows that the vector competence of Ae . albopictus relative to Ae . aegypti demands further investigation . This goal can only be achieved through a combination of field studies to collect a representative variety of strains of these vectors followed by laboratory studies of virus transmission .
|
Between 1952 , when the Zika virus was first found in humans , and 2007 Zika disease outbreaks were limited to small isolated epidemics in equatorial Africa and tropical Asia . However , the recent outbreak , which began in Brazil in May 2015 , resulted over 750 thousand estimated cases and confirmed local transmission in more than 60 countries by October , 2016 . Like dengue and chikungunya , Zika is spread by Aedes aegypti mosquitoes and possibly , other species including Aedes albopictus . Geographic spread of the virus occurs when infected travelers travel from affected regions to ones without an established local Zika disease cycle , but in which the known and potential vector species have established populations . We estimate the risk of Zika importation and establishment into new regions using air travel data and ecological vector habitat suitability models for Ae . aegypti and Ae . albopictus . Given the uncertainties surrounding the vectorial competence of Aedes mosquitoes , we compare the geographic risk profiles when spread is driven by air travel and Ae . aegypti presence alone , with spread driven by air travel and both species . We conclude that there is a much higher global risk of Zika spread under the latter scenario , although it is the least likely .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"chikungunya",
"infection",
"engineering",
"and",
"technology",
"transportation",
"pathogens",
"geographical",
"locations",
"microbiology",
"tropical",
"diseases",
"animals",
"viruses",
"rna",
"viruses",
"neglected",
"tropical",
"diseases",
"insect",
"vectors",
"infectious",
"diseases",
"south",
"america",
"aedes",
"aegypti",
"medical",
"microbiology",
"microbial",
"pathogens",
"disease",
"vectors",
"insects",
"brazil",
"arthropoda",
"people",
"and",
"places",
"mosquitoes",
"asia",
"flaviviruses",
"viral",
"pathogens",
"biology",
"and",
"life",
"sciences",
"species",
"interactions",
"viral",
"diseases",
"airports",
"organisms",
"zika",
"virus"
] |
2017
|
Vector status of Aedes species determines geographical risk of autochthonous Zika virus establishment
|
Apicomplexan parasites are responsible for numerous important human diseases including toxoplasmosis , cryptosporidiosis , and most importantly malaria . There is a constant need for new antimalarials , and one of most keenly pursued drug targets is an ancient algal endosymbiont , the apicoplast . The apicoplast is essential for parasite survival , and several aspects of its metabolism and maintenance have been validated as targets of anti-parasitic drug treatment . Most apicoplast proteins are nuclear encoded and have to be imported into the organelle . Recently , a protein translocon typically required for endoplasmic reticulum associated protein degradation ( ERAD ) has been proposed to act in apicoplast protein import . Here , we show ubiquitylation to be a conserved and essential component of this process . We identify apicoplast localized ubiquitin activating , conjugating and ligating enzymes in Toxoplasma gondii and Plasmodium falciparum and observe biochemical activity by in vitro reconstitution . Using conditional gene ablation and complementation analysis we link this activity to apicoplast protein import and parasite survival . Our studies suggest ubiquitylation to be a mechanistic requirement of apicoplast protein import independent to the proteasomal degradation pathway .
Apicomplexans are eukaryotic pathogens and responsible for important human and animal diseases including malaria and toxoplasmosis . The Apicomplexa evolved from single-celled photosynthetic algae , and their adaptation to animal parasitism likely predates the emergence of animals from water to land . The presence of a plastid , the apicoplast , is the most important remnant of this evolutionary past [1] , [2] . While no longer photosynthetic , the organelle synthesizes isoprenoids and fatty acids [3] . The apicoplast is essential for parasite survival , and its metabolism , biogenesis and maintenance are important targets for anti-parasitic drug treatment . The apicoplast was derived by secondary endosymbiosis , where a unicellular red alga was incorporated into a heterotrophic protist . As a consequence of this secondary endosymbiosis the apicoplast is surrounded by four membranes . The organelle carries a genome , yet most of its proteins are nuclear-encoded and imported into the organelle after translation . Targeting depends on a bipartite leader peptide , the first section of which mediates co-translational import into the endoplasmic reticulum , and the second part mediates delivery to the apicoplast , likely through fusion of endosomal vesicles with the outermost membrane of the organelle [4] . Three translocons breaching successive membranes have been proposed to act in the further transport of proteins into the stroma of the apicoplast [5] . The two inner membranes of the apicoplast are homologous to the membranes of the primary chloroplast and protein transport depends on systems derived from the chloroplast TIC and TOC machinery [6] , [7] , [8] , [9] . Insight into the third translocon emerged first in cryptomonads , an algal group that like Apicomplexa harbors a secondary plastid . The secondary plastids of cryptomonads retained a remnant of the algal nucleus , the nucleomorph . Analysis of the gene content of the nucleomorph led to the discovery of plastid proteins that resembled components of the endoplasmic reticulum associated degradation ( ERAD ) machinery [10] . ERAD is a quality control mechanism that retro-translocates misfolded secretory proteins across the ER membrane [11] . Sommer and colleagues proposed that this mechanism has been adapted for protein import in secondary plastids [10] . There is now significant support for this hypothesis . Homologs of ERAD proteins have been identified and localized to plastids in various algal and apicomplexan species including a core of the membrane protein Der1 , the AAA ATPase Cdc48 and its cofactor Ufd1 [10] , [12] , [13] , [14] , [15] . Recombinant plastid proteins can complement yeast ERAD mutants [14] . Importantly , genetic ablation of the ERAD component Der1Ap in T . gondii blocks apicoplast protein import , producing a phenotype that closely resembles ablation of the apicoplast TIC component Tic20 [6] , [15] . During classical ERAD , protein translocation coincides with ubiquitylation , a process that typically employs a cascade of three enzymes: ubiquitin-activating enzyme ( E1 ) , ubiquitin-conjugating enzyme ( E2 ) , and ubiquitin ligase ( E3 ) [16] , [17] . Consuming ATP , the E1 enzyme adenylates ubiquitin at the C-terminus , creating a mixed anhydride . The sulfhydryl group of the E1 active-site cysteine then attacks the anhydride , which results in the formation of a high-energy thio-ester linking ubiquitin to E1 . Ubiquitin is then passed to the active-site cysteine of the E2 enzyme . Lastly , with the aid of an E3 ligase , ubiquitin is transferred from E2 and covalently attached to the ε-amino group of a lysine in the target protein . Although clearly important in mediating ERAD , the role of ubiquitylation in protein import into secondary plastids is unclear . Interestingly , some ERAD-like ubiquitylation factors are observed in the plastids of cryptomonads , diatoms , and Apicomplexa [12] , [18] , [19] . While protein degradation is the key function of classical ERAD this could seem counterintuitive in the context of apicoplast protein import . However ubiquitin's functions are not limited to proteasomal degradation and extend to a variety of cellular protein trafficking systems [20] . Furthermore , ubiquitylation may be a critical mechanistic requirement of protein transport via the ERAD translocon [11] , [21] . Some authors now view the ERAD associated E3 ligase Hrd1 as a favored candidate for the actual protein-conducting pore [22] . In this study , we elucidate the function of ubiquitylation in the apicoplast . We identify and localize a comprehensive set of ubiquitylating components in the apicomplexan parasites P . falciparum and T . gondii . Using recombinant apicoplast enzymes from P . falciparum we reconstitute ubiquitylation in vitro using a variety of heterologous and homologous cofactors . By genetic analysis in T . gondii we demonstrate that loss of the apicoplast-localized ubiquitin-conjugating enzyme leads to loss of apicoplast protein import and parasite demise . Importantly complementation of this mutant depends on an active site cysteine required for enzymatic activity . Taken together our experiments suggest an essential mechanistic role for the ERAD-like ubiquitylation machinery in apicoplast protein import .
Using a combination of computational approaches we identified a comprehensive set of proteins that may act as apicoplast ubiquitylation system ( see Materials and Methods ) . The results of these analyses ( summarized in Table S1 in Text S1 ) identified apicoplast candidates for E1 , E2 and E3 enzymes in both P . falciparum and T . gondii . We next determined whether these candidates are indeed targeted to the apicoplast . We targeted the locus of T . gondii TgE1Ap by single homologous integration and placed a haemagglutinin ( HA ) epitope tag at the C-terminus of the protein . Stable transgenic clones show apicoplast staining when labeled with an anti-HA antibody by immunofluorescence ( Fig . 1A , the P . falciparum homolog E1 is also localized to the apicoplast [12] ) . Our attempts to localize the candidates for apicoplast E2 by tagging the respective genes directly in the locus did not produce viable transgenics in either T . gondii or P . falciparum . Epitope fusion close to the C-terminal active domain may interfere with function and prevent replacement of the native gene . However , the coding sequence of TgE2Ap could be fused to an epitope tag in the context of an ectopic expression plasmid ( maintaining the native locus ) . Parasites expressing this construct show apicoplast labeling indistinguishable from that observed for E1 when probed with an epitope specific antibody . To localize the Plasmodium homolog ( and to aid subsequent biochemical analysis ) we also expressed a portion of Mal13P1 . 227 fused to an affinity tag in E . coli and used the purified recombinant protein to raise a specific antiserum . Immunofluorescence assays on P . falciparum parasites with this serum produced labeling that coincides with labeling for the apicoplast marker ACP ( Fig . 1 C ) . Two putative apicoplast E3 ubiquitin ligases were identified in Plasmodium , PfE3cAp ( PFC0740c - PF3D7_0316900 ) and PfE3wAp ( PFC0510w - PF3D7_0312100 ) , and two in Toxoplasma ( TGME49_226740 and TGME49_304460 ) . We attempted to tag the proteins by placing different epitopes at the C-terminus through homologous gene targeting but were not successful . In case of PfE3cAp transgenics that showed initial locus targeting were quickly lost upon selection ( Fig . S1A in Text S1 ) . However , we recovered viable transgenic parasites tagged in the PfE3wAp locus . Targeted integration of the cassette and transcription of PfE3wAp-GFP was confirmed by PCR and RT-PCR ( Fig . S1B–C in Text S1 ) . Immunofluorescence assays showed PfE3wAp-GFP to localize to the apicoplast ( Fig . 1D ) . Finally , using an episomal expression vector , we found that the first 167 amino acids of PfE3cAp target a GFP reporter to the apicoplast ( Fig . 1E ) . Apicoplast proteins are often processed at the N-terminus removing a leader peptide [4] . We analyzed processing for TgE1Ap , TgE2Ap and PfE2Ap for which suitable reagents were available . TgE1Ap produces the pattern typical for apicoplast proteins , two major bands likely corresponding to the precursor ( heavier band ) and mature protein ( lighter band ) Fig . 1F . Interestingly both TgE2Ap and PfE2Ap blots showed additional bands potentially arising from further post-translational modification ( Fig . 1 G , H ) . While the immunofluorescence assays indicate apicoplast localization of the ubiquitylation enzymes , overlap with luminal markers is only partial ( see enlarged insert in Fig . 1A ) . We fixed and processed TgE2AP-HA parasites for electron microscopy and incubated cryo-sections with an anti-HA antibody . Note that gold particles are found in the membranous periphery of the apicoplast ( Fig . 2 and Fig . S4 in Text S1 ) . This labeling is indistinguishable from that previously observed for the apicoplast ERAD-like proteins Der1Ap and Cdc48Ap [15] and the periplastid protein PPP1 [23] . We conclude that the apicoplast has a full complement of E1 , E2 and E3 ubiquitylation enzymes localized to the periphery of the organelle , most likely the periplastid compartment as observed for the ERAD-like system in the diatom Phaeodactylum tricornitum [14] , [18] , [19] . We next sought to establish whether the candidate apicoplast ubiquitylation system is capable of activating and ligating ubiquitin . We amplified or synthesized sequences encoding full length PfE1LAp and PfE2Ap , or the RING domains of PfE3wAp and PfE3cAp respectively , and engineered them to be expressed as recombinant fusion proteins carrying an N-terminal glutathione S-transferase ( GST ) and/or six-histidine ( HIS ) affinity tag . Proteins of the expected size could be purified for all four constructs ( Fig . 3A , B ) . We established biochemical ubiquitylation assays using combinations of parasite enzymes and commercially available heterologous components ( Fig . 3C , recombinant human factors are shown in red , Plasmodium enzymes in green ) . Enzymes were incubated with recombinant human ubiquitin in a buffer containing an ATP regenerating system . When analyzed by Western blot , ubiquitin chains can be detected as ladders of high molecular weight bands [24] . Among the numerous human ubiquitin-activating enzymes tested , UBCH5a and UBCH13 were found to be suitable partners for PfE3cAp and PfE3wAp leading to robust ubiquitylation . Note that this activity is strictly dependent on the recombinant parasite E3 and absent in controls ( Fig . 3D , E ) . The pattern obtained differed between the two E2 enzymes and suggested ubiquitylation of the RING domain in the context of only UBCH5a , while interaction with UBCH13 appeared to produce free poly-ubiquitin . Variation of ubiquitylation pattern depending on the E2 partnered with the ligase is frequently observed [25] . To test this independently we probed the in vitro reaction with anti-GST antibody to visualize the E3 and its higher molecular weight ubiquitin adducts . Consistently , this revealed shifts in molecular weight of PfE3cAp and PfE3wAp only when incubated with UBCH5a ( Fig . 3F ) as free polyubiquitin is not detected in this assay format . Next we tested whether ubiquitylation activity can be reconstituted entirely with parasite enzymes . When recombinant PfE1LAp and PfE2Ap were incubated with ubiquitin alone ( Fig . 3G , left lane ) , no ubiquitylation was detected . However , upon addition of recombinant E3 ligase PfE3wAp or PfE3cAp , ubiquitylation was readily observed . Lastly we wished to evaluate the activity for native parasite enzymes . Among the reagents generated and tested in this study a custom-made antibody to PfE2Ap was found suitable for immunoprecipitation under native conditions . Often the conjugating and ligating enzymes form a complex and can be co-precipitated and detected by their combined activity [26] , [27] . We incubated pull down fractions from parasite lysates with recombinant human UBA1 , and biotinylated-ubiquitin ( using tagged ubiquitin enhances sensitivity and focuses the assay on only newly ubiquitylated proteins ) . We observed significant ubiquitylation that was dependent on the immunoprecipitate and UBA1 ( Fig . 3H ) . Taken together our observations provide biochemical support for the notion that the apicoplast ERAD-like system is capable of mediating ubiquitylation . The apicoplast ERAD system has a critical role in protein import into the organelle [5] , [18] . We tested whether ubiquitylation is a mechanistic requirement of this process by genetic ablation of the apicoplast ERAD-like ubiquitylation enzymes . We attempted disruption of the loci of PfE3cAp , PfE3wAp , and PfsUBA1 . We isolated strains bearing drug marker insertions in the PfE3wAp gene and documented loss of associated transcription ( Fig . S2B , S3C in Text S1 ) . However , we also noted multiple genomic duplications in these strains complicating interpretation ( Fig . S3D in Text S1 ) . We did not obtain viable parasites with disrupted PfE3cAP or PfsUBA1 loci . This is consistent with a potentially essential role for these proteins , and we therefore turned to T . gondii where the construction of conditional mutants is feasible . We engineered a parasite strain where the endogenous promoter of the TgE2Ap gene was replaced by a regulatable promoter in the following referred to as ( i ) ΔTgE2Ap ( Fig . 4A , [23] ) . This was accomplished by double cross over in the T . gondii TATiΔKu80 background , a parasite line that favors homologous recombination and expresses a transactivator that can be modulated using anhydrotetracycline ( ATc ) . Drug resistant parasite clones were tested by PCR and integration of the promoter was confirmed by Southern blot . We monitored the level of TgE2Ap mRNA in response to ATc by quantitative PCR . Fig . 4D shows down-regulation of the transcript below 10% of its normal level at day four of ATc treatment . We asked whether loss of TgE2Ap affects parasite growth and performed plaque and real-time fluorescence assays . Parasites grow normally in the absence of ATc indicated by formation of plaques , however in the presence of ATc , plaque formation is severely attenuated ( Fig . 4F ) . Similarly , ( i ) ΔTgE2Ap parasites show significant growth reduction in the fluorescence assay in the presence of ATc ( Fig . 4E ) , preincubation of parasites in ATc abolished growth entirely . We conclude , that TgE2Ap is critical for parasite growth . We next tested the ability of ( i ) ΔTgE2Ap parasites to import apicoplast proteins in the absence or presence of ATc and measured the import-dependent lipoylation of the apicoplast pyruvate dehydrogenase E2 subunit [6] . ( i ) ΔTgE2Ap parasites were treated with ATc for different periods and pulse-labeled for one hour with [35S] methionine/cysteine . For the chase samples the radioactive isotope was removed , and cells were incubated for two additional hours in normal media . The samples were then used for immunoprecipitation with an anti-lipoic acid antibody followed by separation on SDS-PAGE . Treatment of cells with ATc for 2 days resulted in attenuation of import , leading to complete loss after 4 days ( Fig . 4G , H ) . Lipoylation of two mitochondrial enzymes remained unaffected . We also monitored apicoplast loss , a frequent consequence of interference with apicoplast protein import [6] , [15] . We observed a drop over time , but note that loss of import significantly precedes plastid loss . Loss of apicoplast protein import has also been shown to result in loss of leader peptide removal and backing up of precursor protein into the ER and other elements of the secretory pathway [6] , [15] , [28] We therefore measured the levels of precursor and processed mature form of the apicoplast reporter protein FNR-RFP [29] . . We grew parasites for 0 to 4 days on ATc and performed Western blots using parasite protein extracts from each day . Probing these blots with an antibody against RFP revealed that precursor levels of FNR-RFP remained unchanged throughout the 4 days , while the mature protein was no longer detected after 2 days on ATc further supporting a strong import defect ( Fig . 4I ) . We also monitored the localization of FNR-RFP in treated and untreated ( i ) ΔTgE2Ap parasites by immunofluorescence assay . In untreated parasites FRN-RFP is restricted to the apicoplast ( Fig . 4K ) . After 48 hours of ATc treatment 38% of parasite vacuoles also show significant labeling outside of the apicoplast surrounding the nucleus likely representing the ER ( Fig . 4J , untreated TgE2Ap or ATc treated wild type parasites showed such labeling in <3% of counted four cell vacuoles , n = 200 ) . We conclude that apicoplast protein import is impaired in the absence of TgE2Ap . Apicoplast ubiquitylation enzymes are capable of synthesizing ubiquitin chains in vitro , but is this activity required in vivo ? To test this we established a complementation assay . The coding sequence of the TgE2Ap gene driven by a constitutive promoter was introduced into the uracil-phosphoribosyltransferase ( UPRT ) locus of the ( i ) ΔTgE2Ap mutant ( Fig . 5C ) . Parasites were selected for the loss of UPRT activity using 5-fluorodeoxyuridine [30] and a clonal cell line that now constitutively expressed a second copy of TgE2Ap in the conditional knock down background was isolated . We confirmed correct integration by PCR ( Fig . 5D ) . We tested the ability of this strain to form plaques when expression from the native locus is ablated by ATc treatment , and found that genetic complementation fully rescued growth ( Fig . 5E ) . Multiple sequence alignment of TgE2Ap and E2 enzymes from a wide range of eukaryotes showed that TgE2Ap shares conserved features , reported earlier to be critical for this class of enzymes . We therefore modelled the C-terminal domain of TgE2Ap onto the structure of UBC4 , a well characterize yeast ubiquitin conjugating enzyme [31] . Multiple sequence alignment and homology modelling identified C573 as the presumptive active site cysteine ( Fig . 5A , B , see Fig . S3 in Text S1 ) . Most E2 enzymes possess a signature HPN triad proximal to the active site cysteine [32] . The histidine has been previously suggested to be dispensable for E2-catalyzed ubiquitylation , but is important for the folding of the active site in other systems [33] . The asparagine residue on the other hand was consistently found to be important for RING-E3/E2-dependent ubiquitin conjugation [34] . A conserved HXH triad is found at this position in apicomplexans ( Fig . 5B ) . We engineered a series of point mutants in TgE2Ap replacing C573 , H563 , and H565 with alanine respectively . These genes were then introduced into the ( i ) ΔTgE2Ap mutant as described above and tested for their ability to complement loss of TgE2Ap upon ATc treatment using plaque assay . Expression of the H563A point mutant fully complemented loss of native TgE2Ap ( Fig . 5E ) and parasites now grow even in the presence of ATc . In contrast , despite numerous attempts we were unable to establish a stable parasite line expressing H565A , which may suggest dominant effects of this mutation . We were able to isolate mutants expressing C573A , however these strains show no complementation , and are still fully susceptible to ATc treatment ( Fig . 5E ) . We conclude that enzymatic activity is a requirement for TgE2Ap function in vivo and that C573 and H565 residues are critical for the function of the enzyme while H563 is likely dispensable .
Endosymbiosis is a key evolutionary mechanism underlying the emergence and diversification of eukaryotes – in particular for photosynthetic eukaryotes . The acquisition of a eukaryotic red algal symbiont led to the chromalveolates , a large super-phylum of tremendous ecological diversity that includes apicomplexan parasites . The descendent of the algal symbiont , the apicoplast , maintains a highly compartmentalized organization , and nuclear encoded proteins have to overcome four membranes on their journey to the stroma . An apicoplast-localized ERAD-like system appears to play an important role in apicoplast protein import . Recent reports have identified and characterized components of this ERAD–like system in different algal and parasite species [7] , [10] , [12] , [13] , [14] , [15] . In this study we provide significant biochemical and genetic evidence for the hypothesis that an apicoplast localized ubiquitylation cascade is an essential element of this protein import system . We identify apicoplast ubiquitin activating , conjugating and ligating enzymes in two important apicomplexan parasites , P . falciparum and T . gondii . We show in vitro and in vivo that these proteins have conserved biochemical activities and are capable of ubiquitin transfer . Finally , in genetic studies , we show that TgE2Ap , for which we were able to isolate a conditional mutant , is essential for apicoplast protein import , organellar maintenance and parasite growth . Overall these observations support a direct mechanistic role of ubiquitylation in protein translocation independent of ubiquitin's function in proteasomal degradation [11] . The classical ERAD system is believed to recognize and respond to the folding state of secretory proteins . Interestingly , recent studies show that the transit peptide of apicoplast proteins is primarily unstructured and that this conformation may be critical for proper transport to the organelle [35] . This model would need a distinguishing element to avoid elimination of apicoplast proteins by the classical ERAD . Specific chaperone sets could potentially provide such specificity , but remain to be discovered . A recent study in Arabidopsis has identified a role for ubiquitylation also in primary plastids , however this role appears to be distinct from secondary plastids . In this case ubiquitylation results in degradation of the components of the TOC complex and is thought to more globally regulate chloroplast biogenesis during plant development [36] . The identity of the apicoplast ubiquitin or ubiquitin-like modifier remains a significant unresolved question . Our results demonstrate that apicoplast enzymes are capable of acting on archetypical ubiquitin ( recombinant human protein ) , studies in P . tricornitum show similar activity for a E3 ligase found in the diatom secondary chloroplast [18] . However whether the apicoplast system actually utilizes ubiquitin in vivo remains to be established . As shown in Fig . 1G and H Western blots for TgE2Ap and PfE2Ap show additional bands . It is conceivable that these bands represent ubiquitin or a ubiquitin-like protein covalently bound to the active site of the apicoplast localized E2 . However we note that , for TgE2A , none of the bands was affected by reduction of the protein or point mutation of the active site cysteine ( data not shown ) . Alternatively this may indicate an ubiquitin-like protein bound to a residue different from the active site of the enzyme or multiple processing steps as have been observed for some apicoplast membrane proteins [37] . Our efforts to demonstrate ubiquitin bound to apicoplast ubiquitylation enzymes purified from P . falciparum or T . gondii so far did not result in robust detection ( using either antibodies or mass spectrometry , data not shown ) . Furthermore ubiquitylation of plastid-bound cargo proteins is not readily observed in apicomplexans or diatoms . A reasonable candidate for which apicoplast localization has been suggested [12] is an atypical , large ubiquitin-like protein ( PF08_0067 ) . Curiously , this protein lacks the di-glycine motif typically required for the formation of the isopeptide bond and a homolog has yet to be identified in the Toxoplasma genome . Similarly , plastid ubiquitin candidates from algae show lack of sequence motifs typically required for polyubiquitylation [19] . It is conceivable that this ubiquitin-like protein could be processed and/or ligated in a novel fashion that does not depend on a di-glycine sequence . Alternatively , its function may resemble that of the HERP protein in the classical ERAD pathway . Like PF08_0067 , HERP has an ubiquitin-like domain at the N-terminus followed by transmembrane domains at the C-terminus [38] . HERP is believed to interact with HRD1 and to regulate the ubiquitylation activity of the ERAD translocon in response to folding stress [39] . In that case PF08_0067 is likely not the main substrate for the apicoplast ubiquitylation system and the modifier is yet to be discovered . Studying the apicoplast ubiquitin faces technical obstacles that so far prevented direct tagging of the candidate ubiquitin and subsequent detection of modified cargo . There are several strong candidates for plastid-localized deubiquitylation enzyme in apicomplexans and diatoms ( Table S1 in Text S1 , [13] , [18] ) . The activity of these enzymes may dramatically shorten the time ubiquitin remains on proteins and thus prevent the robust detection of ubiquitin adducts [22] . Isolation of mutants lacking apicoplast deubiquitylation might allow testing of this hypothesis and potentially lead to accumulation of modified cargo proteins . While a number of mechanistic details of the apicoplast ubiquitylation system remain to be elucidated , we demonstrate that the system is essential to the organelle and the parasite . Building on a longstanding effort to target ubiquitylation for the development of anti-cancer drugs [40] may potentially lead to new anti-parasitic compounds in the future .
P . falciparum strains 3D7 , D10_ACP- ( leader ) -GFP ( MR4 , MRA568 ) and derivatives were cultured in human O+ red blood cells [41] . T . gondii RH strain parasites and derivatives were propagated in human fibroblasts and genetically modified as described [6] , [15] . For in vitro ubiquitylation assays recombinant P . falciparum enzymes were incubated with recombinant human or parasite factors . Typically 50–200 µM recombinant ubiquitin , 0 . 05–0 . 2 µM E1 enzyme , 1–5 µM E2 enzymes , and 1–12 . 5 µM of E3 ligases were incubated in 50 mM Tris-HCl , pH 7 . 4 , 1 mM DTT in presence of a re-energizing system ( BostonBiochem ) containing the ATP and ATP regenerating enzymes to recycle hydrolyzed ATP needed for the assay , for 2 hours at 37°C followed by SDS-PAGE and immunoblotting . Ex vivo ubiquitylation assays were performed by lysing 3D7 P . falciparum in 20 mM HEPES pH 7 . 9 , 10 mM KCl , 1 mM EDTA , 1 mM EGTA , 1 mM DTT , 0 . 5 mM AEBSF ( Fisher Scientific ) , 0 . 65% Igepal v/v , and protease inhibitor cocktail ( Roche ) , or 20 mM HEPES pH 7 . 9 , 0 . 1 M NaCl , 0 . 1 mM EDTA , 0 . 1 mM EGTA , 1 . 5 mM MgCl2 , 1 mM DTT , 1 mM AEBSF and protease inhibitor cocktail ( Roche ) . Supernatants were pooled and proteins were precipitated using the indicated antibodies and magnetic Protein A beads . Proteins bound to beads were mixed with re-energizing buffer , 0 . 5 µg/µl biotin-conjugated ubiquitin , 5 mM AEBSF and protease inhibitor cocktail . Reactions were incubated at 30°C with gentle agitation for two hours . Samples were eluted with 4× Laemmli buffer and analysed using biotin affinity blots . Human recombinant UBE1 and UBC enzymes , E3 ligases biotin conjugated ubiquitin and re-energizing buffer used in these assays were purchased from Boston Biochem . T . gondii gene models were tested by 5′- and 3′-RACE . Note that additional exons were identified for TgE2Ap ( see genbank JX431938 for correct sequence ) . A conditional TgE2Ap knock-out was generated by exchanging the native promoter for the tetracycline inducible t7s4 promoter in the TATiΔKu80 parasite background . The targeting construct used 1 . 2 kb up- and 1 . 5 kb downstream of the TgE2Ap start codon introduced into vector pDT7S4 . Linearized plasmid was transfected into the parental strain followed by pyrimethamine selection . To complement the knock-out , a TgE2Ap minigene was inserted into the UPRT locus under the control of a constitutive sag1 promoter . Transgenics were isolated in 5 µM 5-FUDR and identified by PCR . Parasite growth was measured by fluorescence and plaque assay in the presence and absence of 0 . 5 µm anhydrotetracycline ( ATc ) . Please refer to the supplement materials for a more detailed description of materials and methods used in this study ( including a table of all primers ) .
|
The apicoplast is an essential parasite organelle derived from an algal endosymbiont . Most apicoplast proteins are nuclear encoded and post-translationally imported . Part of this journey utilizes the endoplasmic reticulum associated degradation or ERAD system of the algal endosymbiont . Typically , the ERAD system is ubiquitylation-dependent and acts in the retrotranslocation across the ER membrane and proteasomal destruction of misfolded secretory proteins . In the apicoplast , this system has been retooled into a protein importer . The apicoplast ERAD system is broadly conserved between most apicomplexans and surprisingly retains the ubiquitylation machine typically associated with destruction . This study brings together biochemical studies in Plasmodium and genetic studies in Toxoplasma . Together they provide significant mechanistic insight into the process of protein import into the apicoplast . We provide evidence that ubiquitylation may be a mechanistic requirement for import and demonstrate it to be essential to the parasite , thus providing new opportunities for drug development .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"parasitology",
"biology",
"microbiology"
] |
2013
|
An Apicoplast Localized Ubiquitylation System Is Required for the Import of Nuclear-encoded Plastid Proteins
|
Genetic strategies that reduce or block pathogen transmission by mosquitoes have been proposed as a means of augmenting current control measures to reduce the growing burden of vector-borne diseases . The endosymbiotic bacterium Wolbachia has long been promoted as a potential vehicle for introducing disease-resistance genes into mosquitoes , thereby making them refractory to the human pathogens they transmit . Given the large overlap in tissue distribution and intracellular localization between Wolbachia and dengue virus in mosquitoes , we conducted experiments to characterize their interactions . Our results show that Wolbachia inhibits viral replication and dissemination in the main dengue vector , Aedes aegypti . Moreover , the virus transmission potential of Wolbachia-infected Ae . aegypti was significantly diminished when compared to wild-type mosquitoes that did not harbor Wolbachia . At 14 days post-infection , Wolbachia completely blocked dengue transmission in at least 37 . 5% of Ae . aegypti mosquitoes . We also observed that this Wolbachia-mediated viral interference was associated with an elevated basal immunity and increased longevity in the mosquitoes . These results underscore the potential usefulness of Wolbachia-based control strategies for population replacement .
Dengue fever and its associated condition , the highly lethal dengue hemorrhagic fever , are emerging globally as the most important arboviral diseases currently threatening human populations . Approximately 2 . 5 billion people are at risk of contracting dengue-associated disease , with an estimated 50–100 million cases occurring each year [1] . Dengue virus ( DENV ) is transmitted to humans by aedine mosquitoes , primarily Aedes aegypti and , to a lesser extent , Aedes albopictus . At present , no treatment or vaccine is available for dengue fever; thus , vector control is currently the primary intervention tool . One such method is population replacement , in which natural Ae . aegypti populations would be replaced with modified populations that are unable to transmit DENV . Recently , significant progress has been made in producing Ae . aegypti strains that are refractory to DENV [2] , [3] and in exploring transgene drivers for population replacement [4] , [5] . One of the most promising transgene drivers is a maternally transmitted Gram-negative endosymbiotic bacterium , Wolbachia . Significantly , Wolbachia is able to spread rapidly within an uninfected Ae . aegypti laboratory population after the population has been seeded with infected females [6] . Wolbachia induces a reproductive abnormality known as cytoplasmic incompatibility ( CI ) , which results in early embryo death when a Wolbachia-infected male has mated with a female that is uninfected or harboring a different Wolbachia type . Since uninfected males can successfully mate with infected females , Wolbachia and any gene it carries can spread quickly in a population . Two control approaches using Wolbachia-based population replacement have been proposed: One potential approach involves linking a transgene to Wolbachia . The mosquito's vectorial capacity is reduced as the transgene is carried by Wolbachia into the target population . The second approach utilizes the ability of Wolbachia itself to modify both the sexual reproduction and vectorial capacity of the host . For example , after mosquitoes are fed an infectious blood meal , a period of 7–14 days ( depending on environmental and intrinsic factors ) is required before the mosquitoes are able to transmit DENV to a new host [7] , [8] . One strain of Wolbachia , called popcorn , has been shown to reduce the longevity of mosquitoes , causing the insects to die before they can transmit viruses [9] , [10] . Wolbachia , introduced into wild vector populations , will inevitably encounter DENV , given large overlap in tissue distribution and intracellular localization of these two microorganism [8] , [11] . However , at present it is still unclear how Wolbachia and DENV interact in the mosquito . Recent studies in Drosophila have shown that Wolbachia can confer resistance to diverse RNA viruses and protect flies from virus-induced mortality [12] , [13] . Two groups have independently reported that Wolbachia significantly reduces the infection level of the Drosophila C virus , a member of the Dicistroviridae , in different lines of D . melanogaster . When compared to flies cured of Wolbachia infection , those with an active Wolbachia infection showed a significantly delayed mortality induced by Drosophila C virus infection . A similar antiviral effect was also observed in Wolbachia-infected flies challenged with cricket paralysis virus ( Dicistroviridae ) , Nora virus ( a new picorna-like virus family ) and flock house virus ( Nodaviridae ) . Since Drosophila C virus and DENV are both single-stranded positive-sense RNA viruses , these findings strongly support the existence of an overarching mechanism that is also applicable to Wolbachia-DENV interactions in their mosquito hosts . Although Ae . aegypti is not naturally infected by Wolbachia , infection has been achieved by transfection with wAlbB , an infection type of Wolbachia from Ae . albopictus , by means of embryonic microinjection [6] . wAlbB is able to induce a complete CI in Ae . aegypti , and this phenotype can be reversed by tetracycline treatment . Moreover , it has a 100% maternal transmission rate , with no fitness costs observed [6] . Since it was introduced , this infection has been stably maintained in Ae . aegypti for about 6 years in the laboratory . Our previous studies have shown that the mosquito's endogenous bacterial flora boost the basal level of immunity in the mosquito and that their removal leads to an increase in the level of dengue infection [14] . In the Drosophila S2 cell line , we also found that Wolbachia activates immune signaling pathways and induces the expression of antimicrobial peptide genes [15] . In Ae . egypti , we have further demonstrated that the anti-bacterial defense responses can control dengue infection [14] . Here , we have asked whether Wolbachia , a component of the mosquito's microbial flora , can suppress DENV in Ae . aegypti . We found that Wolbachia can indeed inhibit DENV infection in Ae . Aegypt , and this inhibition was associated with an elevated immune response and an increase in the mosquito's longevity .
To characterize the effect of Wolbachia on DENV infection in Ae . aegypti , we compared DENV dynamics within the mosquito between the original wild-type Waco strain ( Wolbachia-free ) and the Waco-derived WB1 strain ( Wolbachia-transfected ) . Mosquitoes were fed sheep blood containing the New Guinea C strain of DENV serotype 2 ( DENV-2 ) , with viral titers of 2 . 0×107 PFU/ml . Using an indirect fluorescent antibody assay ( IFA ) performed on head squashes at 14 days after the infectious meal , we had previously confirmed that this virus titer resulted in a >90% infection rate in experimentally infected Waco females . The number of copies of DENV-2 genomic RNA was monitored in mosquito midguts by quantitative reverse transcriptase PCR ( qRT-PCR ) at 3 , 6 , 9 , 12 , 15 and 18 days post-infection . Five biological replicates were used for each time point . The number of copies of DENV-2 RNA in the WB1 strain was significantly lower than that in Waco strain at all five time points , with the exception of Day 9 ( Mann-Whitney U test , P<0 . 05 ) ( Figure 1 ) . On Days 3 and 6 , DENV was detectable in only one of ten WB1 samples , whereas all the Waco samples were positive for dengue infection . On Day 9 , the median viral titer in the WB1 strain reached 9 . 1×103 genome copies per midgut , whereas the median titer in the Waco strain was 2 . 4×106 genome copies per midgut; however , this difference was not statistically significant . RNA copy numbers remained at a high level in the midguts of Waco strain mosquitoes from Day 9 to 18 . The strongest Wolbachia-mediated virus inhibition was observed on Day 12 , when the amount of DENV-2 in the midguts of the WB1 strain mosquitoes was 5 . 6×104 times lower than that in the midguts of the Waco strain . The dengue infection level in the WB1 midgut was maintained at 1 . 9×104 and 3 . 1×104 times lower than that in Waco midguts on Days 15 and 18 , respectively . A low level of DENV-2 infection , ranging from 23 . 0 to 31 . 5 copies per midgut , was maintained in the midguts of the WB1 line from Day 12 to 18 ( Figure 1 ) . We also compared the dissemination of DENV-2 within the WB1 and Waco strains of Ae . aegypti by measuring the number of copies of the dengue genome in the mosquito thorax . From Day 3 to Day 9 , we saw no significant difference in the level and prevalence of dengue infection between the WB1 and Waco strains . A very low level of infection was detected in one of five replicates in both strains on Day 6 . On Day 9 , all five Waco replicates and four of the five WB1 replicates were positive for dengue infection . Whereas DENV-2 accumulated in the thorax of the Waco strain mosquitoes from Day 12 to 18 , a strong Wolbachia-mediated inhibition effect was observed in the WB1 mosquitoes . On Day 12 , the amount of DENV-2 in the thoraces of the WB1 mosquitoes was 2 . 6×105 times lower than in the Waco strain ( Mann-Whitney U test , P<0 . 05 ) ( Figure 2A ) . On Days 15 and 18 , three of five WB1 replicates had no detectable dengue infection , whereas all the Waco thoraces were heavily infected by DENV . Similar results were obtained when we used IFA to assay female heads . Only 38 . 9% of the mosquitoes were positive for the DENV-2 E protein in the heads of WB1 mosquitoes by Day 14 , as compared to 94 . 4% of the Waco mosquitoes ( Fisher's exact test , p<0 . 05 ) . By Day 21 , 91 . 7% of the Waco strain mosquitoes were positive for DENV in the head squash assay , whereas only 5 . 6% of the WB1 strain mosquitoes were positive ( Fisher's exact test , p<0 . 05 ) ( Figure 2B ) . These results indicate that inhibition of DENV dissemination in the mosquito increases with time . Experiments were also conducted to examine whether a similar Wolbachia-mediated inhibition of DENV could occur in Ae . albopictus . After both Wolbachia-infected and uninfected Ae . albopictus were fed on the same infectious blood , 100% of the mosquitoes were positive in the head squash assay in both groups ( Figure 2B ) . Thus , Wolbachia-mediated inhibition of DENV was not observed in Ae . albopictus , at least not when this particular viral titer of the infectious blood was used to infect the mosquitoes . To determine whether mosquitoes' potential to transmit DENV-2 was inhibited by Wolbachia , we compared the levels of virus particles released during feeding from the proboscis of WB1 and Waco strain mosquitoes . At 14 days post-infection , the mosquitoes were allowed to feed on an artificial feeding solution for 90 min , and the viral titers in the solution were then measured by plaque assay . The median titer of viruses released from the mosquito proboscis was 12 times higher in the Waco strain ( 5 . 5×102 pfu/ml ) than in the WB1 strain ( 45 pfu/ml ) ( Mann-Whitney U test , P<0 . 05 ) ( Figure 3 ) . The virus infection rate of the feeding solution from the Waco strain was also significantly higher than that from the WB1 strain . Of the eight groups of pooled feeding solution from WB1 mosquitoes , three had no titer of virus at all , and one had a titer of 10 pfu/ml . Because each feeding group consisted of eight female mosquitoes , this result indicates that Wolbachia can completely block dengue transmission potential in at least 37 . 5% ( 24 of 64 ) of WB1 mosquitoes . In contrast , positive titers were detected in all the eight groups of pooled feeding solution from the Waco strain , and three groups had viral titers of 1 . 1×104 to 7 . 6×104 pfu/ml . These observations were consistent with the results from trituration of the whole bodies from each mosquito group: The median titer of the five Waco groups was 1 . 6×104 pfu/ml virus , as compared to 2 . 5×103 pfu/ml virus for the eight WB1 groups . No virus was detected in one of eight WB1 whole-body groups ( Figure 3 ) . These results suggest that the DENV-2 transmission potential had been greatly reduced by Wolbachia in Ae . aegypti . In order to allow us to correlate the data between different assays , we compared the dengue infection levels in the Waco and WB1 strains at 7 days post-infection , in parallel with the results of the qRT-PCR and plaque assays . Although both the assays showed a significant reduction in the viral infection in the midguts and whole bodies , qRT-PCR showed a higher -fold reduction than the plaque assay in both tissues ( Table S1 ) . In particular , the virus infection in whole bodies and midguts were reduced by 2 . 4×104- and 100-fold according to the qRT-PCR results , but only by 139 . 4- and 10 . 6-fold , respectively , when measured by plaque assay . Moreover , comparison of the inhibition in midguts and whole bodies also showed a difference , with whole bodies exhibiting stronger inhibition than midguts at 7 days post-infection ( Table S1 ) . Wolbachia-mediated viral inhibition might be related to the tissue distribution , density and infection frequency of Wolbachia in WB1 mosquitoes . In our analysis of these aspects of Wolbachia infection , we focused on midguts and salivary glands , two important tissues targeted by DENV . The number of copies of Wolbachia genomic RNA in the two tissues was measured by quantitative PCR and compared to that in the ovaries . Wolbachia was present in both midguts and salivary glands at a 3- to 5-fold lower density than in ovaries: Specifically , there were 16 . 5 and 27 . 2 copies of the Wolbachia genome ( normalized by the ribosomal protein S6 [RPS6] copy number ) in the midguts and salivary glands , respectively , as compared to 91 . 5 copies in the ovaries ( Figure 4 ) . In order to confirm that each individual WB1 mosquito was carrying the Wolbachia bacterium , we randomly selected 15 females from the current WB1 population cage and tested their infection status by PCR . As had been observed 6 years ago [6] , all of the 15 were positive for Wolbachia . The results of our previous studies have suggested that microbial flora in the mosquito might mediate the anti-dengue response by boosting the mosquito's basal immunity [14] . We therefore investigated the possibility that Wolbachia can elevate basal immunity in Ae . aegypti . By comparing the expression of selected immune genes in 4- or 5-day-old non-blood-fed females of the Waco and WB1 strains , we found that a number of immune genes were up-regulated by Wolbachia ( Figure 5 ) . Specifically , Wolbachia induced a 17-fold increase in defensin expression and 4 . 49-fold increase in cecropin expression . Up-regulation was also observed for other Toll pathway genes , including Rel1 , Spz1A and GNBPB1 . These results indicate Wolbachia can activate the Toll pathway and boost basal level immunity in Ae . aegypti . Considering that the mosquito Toll pathway can control dengue infection in mosquitoes , this effect might represent a potential mechanism underlying the suppression of dengue infection by Wolbachia . To determine whether suppression of DENV-2 infection by Wolbachia provides any benefit to the mosquito , we compared the relative survival of the Waco and WB1 strains after infection with DENV-2 . WB1 females lived significantly longer than Waco females ( logrank test , P<0 . 05 ) ( Figure 6A ) . This difference was manifested at a late stage , with all of the Waco females having died by 26 days post-infection , but 10% of the WB1 females living for up to 12 additional days . This result produced a “long tail” effect in the survivorship distribution . To determine whether this increase in WB1 survival was specifically associated with DENV-2 infection , we fed Waco and WB1 mosquitoes with blood lacking DENV . Under these conditions , we observed no difference in survival between the two strains ( Figure 6B ) . These results indicated that Wolbachia can slightly increase the longevity of WB1 only when the mosquitoes are infected with DENV .
Ae . aegypti is not naturally infected by Wolbachia , but a transfected line WB1 was previously successfully developed in the laboratory . This WB1 line was able to invade the wild-type laboratory population; population replacement can occur in seven generations after the initial release [6] . Although Wolbachia is widely used as a driver to spread disease-resistant genes into the mosquito , the impact of Wolbachia itself on pathogens has not been well understood . Given the large overlap in the tissue distribution and intracellular localization of Wolbachia and DENV in mosquitoes , we conducted experiments to characterize the interactions between Wolbachia and DENV . Our results show that Wolbachia inhibits viral replication , dissemination and transmission in mosquitoes . This inhibitory effect was associated with an elevated level of basal immunity in the mosquitoes . We found that the inhibition of DENV infection in Wolbachia-infected WB1 mosquitoes occurred in a variety of tissues . This observation might reflect the broad tissue distribution of wAlbB in the WB1 strain , especially in those tissues in which DENV replicates and resides within the mosquito . DENV enters the mosquito midgut epithelial cells following an infectious bloodmeal , with the infection reaching a peak in the midgut from 7 to 10 days post-infection , in the salivary glands from 10 to 17 days post-infection , and in the head after 14 days post-infection [8] . We confirmed the presence of Wolbachia in the midguts and salivary glands as well as the ovaries of WB1 mosquitoes . Although the amount of Wolbachia in ovaries was three to five times higher than that in the midguts and salivary glands , a significant level of Wolbachia was also present in those two tissues . This distribution pattern of wAlbB was consistent with what was observed in the original host , Ae . albopictus , in which Wolbachia is widely distributed throughout the host tissues , both reproductive ( e . g . , ovaries and testes ) and non-reproductive ( e . g . , hemolymph , midgut , muscle , wing and head ) [11] . In our study , the viral inhibitory effects mediated by Wolbachia were consistently observed in different assays , at different time points and in different tissues . At 14 days post-infection , all the Waco strain feeding solutions contained DENV , but at least 37 . 5% of the WB1 feeding solutions had no DENV , as determined by plaque assay . Similarly , the DENV genome could not be detected by qRT-PCR in 40% ( 6/15 ) of the WB1 midguts or 60% ( 9/15 ) of the WB1 thoraces at 15 days post-infection; 61 . 1% of the WB1 mosquito heads were also negative for the DENV-2 E protein , as detected by IFA at 14 days post-infection . However , it appeared that Wolbachia differentially affects the replication of DENV and the formation of infectious virions , since the inhibitory effect in both the midguts and whole bodies at 7 days post-infection was higher when measured by qRT-PCR than when measured by plaque assay . Our results also indicated that the level of inhibition was different in different tissues and at different time points . This variation might be related to the dynamics of DENV and the distribution of Wolbachia in mosquitoes . For example , Wolbachia might mediate a stronger viral inhibition in a tissue that contains a higher amount of Wolbachia but a low level of DENV than in another tissue that contains a low amount of Wolbachia but a high level of DENV . Although a significant reduction in dengue infection was observed on Days 3 , 6 , 12 and 15 in the midguts of WB1 mosquitoes , the number of viral genome copies on Days 3 to 9 was not significantly different in the thoraces of WB1 mosquitoes than in those of Waco mosquitoes . In contrast , only a trend toward a reduction was observed , perhaps because most of the DENV had not yet escaped from the midgut during this period . The very low number of virus particles present there made it difficult to distinguish between signal and noise in the assay . Inhibition of DENV might be caused by the activation of certain host defense responses as a result of Wolbachia infection . Virus-inhibitory effects have been observed in human infected with a close relative of Wolbachia , Orientia tsutsugamushi; these effects appear to be caused by binding to the virus of antibodies against bacteria [16] . In arthropods , innate immunity plays an important role in limiting pathogen infection . Such immune responses are largely regulated by two main pathways , the Toll and Imd pathways [17] , [18] . In Drosophila , the Toll pathway is mainly involved in defense against fungi and Gram-positive bacteria , while the Imd pathway affects resistance to Gram-negative bacteria . In response to either the Drosophila X virus ( a member of the Birnaviridae ) or E . coli infection , D . melanogaster induces the same antimicrobial peptide genes . This commonality suggests that these two diverse classes of pathogen can activate the same immune response pathway in the insect host [19] . More importantly , we have recently found that activation of the mosquito Toll pathway can suppress DENV infection [14] . A recent genome-wide analysis of the Wolbachia-host interaction has revealed that Wolbachia infection has an impact on a broad range of physiological systems in the host , including innate immunity [15] . In the present study , we also observed an elevated mosquito immune response in the WB1 strain . Thus , the observed inhibition of dengue infection in the WB1 strain may be partially explained by a Wolbachia-induced up-regulation of Toll pathway genes . Alternatively , Wolbachia-mediated viral interference could also be the result of a direct competition between DENV and Wolbachia for the same resources , or of an indirect perturbation by Wolbachia of the cellular environment required by DENV . As a parasite , DENV depends on the metabolic network of the host cell to provide the energy and macromolecular subunits necessary for its replication . By producing metabolic alterations in its host , Wolbachia may interfere with dengue replication . It is unlikely that the inhibitory effects on DENV that we observed in the WB1 mosquitoes were caused by differences in genetic background between the WB1 and Waco strains . After the WB1 strain was initially produced from the Waco strain by embryo microinjection , 50 virgin WB1 females were out-crossed with 50 Waco males for six generations to homogenize their genetic background [6] . Since then , the population cages housing the Waco and WB1 strains have been maintained in the laboratory under identical environmental conditions . While this manuscript was in review , an independent report with similar findings to ours was published: In agreement with our data , another type of Wolbachia , popcorn , was found to inhibit the ability of a range of pathogens , including DENV , Chikungunya , and Plasmodium , to infect Ae . aegypti [20] . This result indicates that Wolbachia may induce a general killing mechanism in the host or influence common host factors or networks that are required for a variety of parasites . It appears that such an effect occurs locally but not systematically , because DENV can be present in cells of Wolbachia-infected mosquitoes that lack Wolbachia , and the strength of the effect depends on the on-site density and the type of Wolbachia . In addition , in neither this published study nor our current study was a similar interference effect observed in Ae . albopictus or Ae . fluviatillis , in which Wolbachia infection occurs naturally . This apparent selectivity suggests that the observed interference may require a specific Wolbachia/host combination , or it may be associated with the recent establishment of Wolbachia in the host . Our results suggest the DENV-2 transmission potential in Ae . aegypti can be strongly inhibited by concurrent infection with Wolbachia . At 14 days post-infection , Wolbachia in Ae . aegypti could completely block dengue transmission in at least 37 . 5% of the mosquitoes . This inhibitory effect appeared to become stronger over time . While more than 90% of the female heads were infected in the Waco strain at both 14 and 21 days post-infection , the infection rate dropped from 38 . 9% to 5 . 6% between those two days in the case of the WB1 strain . Wolbachia-induced inhibition of DENV infection provides us with a bonus for using this endosymbiont to block dengue transmission in the mosquito . The anti-dengue effect of this endosymbiont is not solely dependent on the effector transgenes carried by Wolbachia . Therefore , the main requirement for the effector transgenes is merely to eliminate any dengue viruses that survive the Wolbachia-induced suppression . This added advantage might enhance the efficiency of an anti-dengue effector , because a lesser dose of effector would be necessary when it is expressed by and delivered from Wolbachia than if it were to function alone . The anti-dengue effect of Wolbachia can also reduce concerns over losing the link between antipathogen and the transgene driver , because Wolbachia alone can confer resistance to DENV in mosquitoes . Also , Wolbachia may be able to be used directly to blocking dengue transmission without linkage to an anti-dengue gene . This strategy will , however , require a better understanding of the mechanism underlying the dengue inhibition effect conferred by Wolbachia . By improving the efficiency of this inhibition mechanism , a complete blockade of dengue transmission could potentially be achieved . Finally , although DENV was still present in the proboscis of some WB1 mosquitoes in our study , the titer was 12 times lower than in the Waco strain . It will be interesting to know whether this level is below the threshold viral titer that is required to cause infection in humans . As has been reported in Drosophila [12] , [13] , we observed that wAlbB could increase the survival rate of the dengue-infected mosquitoes . Such an increase in survival was not observed when WB1 were fed uninfected blood . However , in another study , when Ae . albopictus were fed with blood without DENV , Wolbachia ( a superinfection of wAlbA and wAlbB , referred as wAlbA&B ) was reported to provide a fitness advantage , including an increase in the mosquitoes' longevity [21] . This difference in the observed results might reflect differences in experimental design , infection status , or mosquito species . Thus far , Wolbachia has been reported to affect the life span of its mosquito hosts in two different directions , with the longevity reduced or increased by wMelPop or wAlbA&B , respectively [9] , [10] , [21] . Although the underlying mechanism is still unclear , it is possible that Wolbachia interacts with certain biological pathways , such as the insulin signaling pathway [22] , which can influence the host's life span . It is still unknown whether this slight increase in survival that we observed for the infected mosquitoes could have a negative effect on disease control . To test this possibility , it will be necessary to determine whether this small fraction of older WB1 mosquitoes has cleared the viral infection , and whether these mosquitoes still have the ability to feed on their hosts . Moreover , the longevity of mosquitoes in the field , where the majority live fewer than 30 days , is quite different from that of mosquitoes reared under laboratory conditions . Future studies are needed to assess the overall impact on dengue transmission of this wAlbB-induced resistance to dengue infection and increase in life span . In summary , we have demonstrated an inhibitory effect of Wolbachia on DENV in Ae . aegypti . This inhibition , which was found to occur in the midgut , thorax and head , further reduced the DENV transmission potential of the mosquitoes . We have also provided evidence that the inhibitory effect may be related to an elevated basal immunity produced by the Wolbachia . Our results provide support for future experiments to elucidate the mechanism underlying the inhibition of dengue infection by Wolbachia and to dissect the three-way interactions among DENV , Wolbachia and the mosquito . From an application standpoint , we have demonstrated that Wolbachia can be used not only as a transgene driver but also as an effector to suppress dengue infection in the mosquito Ae . aegypti . When compared to other potential driver systems , the effector function of Wolbachia offers an additional advantage and facilitates its implementation as a means of blocking dengue transmission by mosquitoes .
All the mosquito strains used in these experiments , including the wild-type Waco strain and the transfected line WB1 of Ae . aegypti , the wild-type Houston strain and tetracycline-treated HT1 strain of Ae . albopictus , were maintained on sugar solution at 27°C and 85% humidity with a 12-hr light/dark cycle according to standard rearing procedures . The Ae . albopictus cell line C6/36 was grown in minimal essential medium ( MEM ) with 10% heat-inactivated FBS , 1% L-glutamine , and 1% non-essential amino acids at 32°C and 5% CO2 . The New Guinea C strain of DENV-2 was propagated in C6/36 cells according to standard conditions [23]: In brief , 0 . 5-ml aliquots of virus stock were used to infect 75-cm2 flasks of C6/36 cells , at 80% confluence , with a multiplicity of infection ( MOI ) of 3 . 5 virus particles/cell . Infected cells were incubated for 10 days , and the medium was changed on Day 5 . Cells were harvested with a cell scraper and lysed by repeated freezing and thawing in dry ice and a 37°C water bath . The resulting virus suspension was mixed 1∶1 with commercial human blood . A flask with uninfected C6/36 cells was maintained under similar conditions and used to create the noninfectious blood meal that served as our control . The blood meal was maintained at 37°C for 30 min prior to use for feeding 7-day-old mosquitoes ( http://www . jove . com/index/Details . stp ? ID=220 ) . Mosquitoes at 3 , 6 , 9 , 12 and 15 days post-infection were dissected to collect the midguts and thorax in RNALater , with three individual mosquitoes in a single replicate . Five replicate biological assays were performed . Total RNA was extracted using the RNeasy kit ( QIAGEN ) . To measure the virus titers in mosquito bodies , at 14 days after a blood meal , mosquitoes were briefly washed in 70% ethanol , then rinsed in sterile distilled water . The midgut and thorax were dissected in sterile PBS and transferred separately to microcentrifuge tubes containing 150 µl of MEM , then homogenized with a Kontes pellet pestle motor in a sterile environment . To measure the number of viral genome copies , total virus RNA was extracted using the RNeasy kit ( QIAGEN ) and reverse-transcribed using Superscript III ( Invitrogen , Carlsbad , California , USA ) with random hexamers . qRT-PCR was conducted using primers targeting the dengue NS5 gene and the host RPS6 [24] . The dengue genome copy number was normalized using the RPS6 results . Two recombinant plasmids containing the targeted fragments were diluted from 101 to 108 copies/reaction and used to generate separate standard curves for NS5 and RPS6 . Real-time quantitation was performed using the QuantiTect SYBR Green PCR Kit ( Qiagen ) and ABI Detection System ABI Prism 7000 ( Applied Biosystems , Foster City , California , USA ) . Three independent biological replicates were assayed , and all PCR reactions were performed in triplicate . To determine the number of copies of the Wolbachia genome and assess the expression of mosquito immune genes , real-time PCR was carried out as previously described [14] , [25] . Virus titers in the tissue homogenates were measured as previously reported ( http://www . jove . com/index/Details . stp ? ID=220 ) : The virus-containing homogenates were serially diluted and inoculated into C6/36 cells in 24-well plates . After incubation for 5 days at 32°C and 5% CO2 , the plates were assayed for plaque formation by peroxidase immunostaining , using mouse hyperimmune ascitic fluid ( MHIAF , specific for DENV-2 ) and a goat anti-mouse HRP conjugate as the primary and secondary antibodies , respectively . On Days 14 and 21 after infection , the viral antigen in the heads of mosquitoes was detected by using an indirect IFA . Mosquito heads were cut off from the thorax with a razor blade , transferred to a pre-cleaned glass microscope slide , and then squashed under a cover slip . After being air-dried for 10 min at room temperature , the slides were fixed in cold acetone ( −20°C ) for 10 min and then dried . A mouse anti-dengue complex monoclonal antibody ( Millipore ) and a fluorescein-conjugated affinity-purified secondary antibody ( Millipore ) were used in all head squash assays . Specimens were examined with a Zeiss ( Germany ) fluorescence microscope . For the samples that yielded ambiguous results in the IFA assay , RT-PCR was conducted in parallel to confirm the infection status . Adult female 1-week-old mosquitoes were fed with either blood alone or with blood mixed with DENV-2 , as described in the section on DENV-2 infections . After 30 min of feeding , the engorged females were sorted on the Carbon Dioxide Staging , transferred to cardboard containers and then incubated at 27°C with 80% humidity while being fed a 10% sucrose solution . All containers were checked for deaths daily , and the surviving mosquitoes were transferred to a new clean container every week until all the mosquitoes died . The parameter used to measure lifespan was the mean of the survival percentages for three biological replicates of 25 mosquitoes each . Mosquitoes that had been infected with DENV-2 as described above were maintained for 14 or 21 days for forced salivation assays . The assays were conducted as previously reported [2] , [26]: In brief , mosquitoes were deprived of food for 24 h prior to forced salivation . The legs and wings of each mosquito were cut away , and the proboscis was inserted into 25 µl of feeding solution ( 50% FBS/164 mM NaCl/100 mM NaHCO3/0 . 2 mM ATP/≈50 µg sucrose/phenol red , pH 7 . 0 ) [2] in a 0 . 2-ml PCR tube . After 90 min , the mosquitoes were removed , and the feeding solutions from eight mosquitoes ( one group ) were combined and sterilized by Millex-GV filter for plaque assays . Whole bodies of eight mosquitoes from the same group were homogenized in 350 µl MEM . After filtration , the supernatant was used for plaque assay . Eight biological replicates were used for each treatment . The Entrez Gene IDs for the genes and proteins mentioned in the text are 5565922 ( Cactus ) , 5569526 ( REL1A ) , 5578608 ( Caspar ) , 5569427 ( REL2 ) , 5579094 ( DEF ) , 5579377 ( CEC ) , 5578028 ( Attacin ) , 5565542 ( Diptericin ) , 5579192 ( GNBPB1 ) and 5564993 ( Gambicin ) .
|
Dengue fever and its associated condition , dengue hemorrhagic fever , are emerging globally as the most important arboviral diseases currently threatening human populations . Dengue virus is transmitted to humans by aedine mosquitoes , primarily Aedes aegypti and , to a lesser extent , Aedes albopictus . No treatment or vaccine is currently available for dengue fever; thus , vector control remains the primary intervention tool . One novel control strategy for reducing or blocking dengue transmission by mosquitoes involves the endosymbiotic bacterium Wolbachia , which has long been promoted as a potential vehicle for introducing anti-dengue genes into mosquitoes . Here , we have characterized the interaction of Wolbachia with dengue viruses in Ae . aegypti . Wolbachia alone was able to inhibit viral replication , dissemination and transmission in these mosquitoes . In addition , this Wolbachia-mediated viral interference was associated with an elevation of basal immunity and increase in longevity in the mosquitoes . Our study provides novel insights into the usefulness of Wolbachia for blocking dengue transmission by mosquitoes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology/applied",
"microbiology",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"infectious",
"diseases/viral",
"infections",
"public",
"health",
"and",
"epidemiology/global",
"health",
"microbiology/applied",
"microbiology",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases"
] |
2010
|
The Endosymbiotic Bacterium Wolbachia Induces Resistance to Dengue Virus in Aedes aegypti
|
Coronaviruses raise serious concerns as emerging zoonotic viruses without specific antiviral drugs available . Here we screened a collection of 16671 diverse compounds for anti-human coronavirus 229E activity and identified an inhibitor , designated K22 , that specifically targets membrane-bound coronaviral RNA synthesis . K22 exerts most potent antiviral activity after virus entry during an early step of the viral life cycle . Specifically , the formation of double membrane vesicles ( DMVs ) , a hallmark of coronavirus replication , was greatly impaired upon K22 treatment accompanied by near-complete inhibition of viral RNA synthesis . K22-resistant viruses contained substitutions in non-structural protein 6 ( nsp6 ) , a membrane-spanning integral component of the viral replication complex implicated in DMV formation , corroborating that K22 targets membrane bound viral RNA synthesis . Besides K22 resistance , the nsp6 mutants induced a reduced number of DMVs , displayed decreased specific infectivity , while RNA synthesis was not affected . Importantly , K22 inhibits a broad range of coronaviruses , including Middle East respiratory syndrome coronavirus ( MERS–CoV ) , and efficient inhibition was achieved in primary human epithelia cultures representing the entry port of human coronavirus infection . Collectively , this study proposes an evolutionary conserved step in the life cycle of positive-stranded RNA viruses , the recruitment of cellular membranes for viral replication , as vulnerable and , most importantly , druggable target for antiviral intervention . We expect this mode of action to serve as a paradigm for the development of potent antiviral drugs to combat many animal and human virus infections .
Prior to the emergence of the highly pathogenic severe acute respiratory syndrome-associated coronavirus ( SARS-CoV ) in 2003 [1]–[3] only two circulating human coronaviruses ( HCoVs ) , HCoV-229E [4] and HCoV-OC43 [5] causing relatively mild common cold-like respiratory tract infections , were known , and coronaviruses have not been regarded as significant threat for human health . Now , more than ten years later , the emergence of another highly pathogenic coronavirus of zoonotic origin , the Middle East respiratory syndrome coronavirus ( MERS-CoV ) [6]–[8] , boosted community awareness towards the pending need to develop effective therapeutic options to combat coronavirus infections . Coronaviruses are enveloped viruses and their positive strand RNA genome , the largest of all RNA viruses , encodes for as many as 16 non-structural proteins ( nsps ) , 4 major structural proteins , and up to 8 accessory proteins ( reviewed in [9] ) . Many of these proteins provide essential , frequently enzymatic , functions during the viral life cycle and are therefore attractive targets for antiviral intervention . Antiviral strategies are mainly proposed for targeting coronavirus entry and essential enzymatic functions , such as coronavirus protease or RNA-dependent RNA polymerase ( RdRp ) activities . For example , the spike ( S ) protein mediates binding of different HCoVs to their specific cellular receptors [10]–[14] , an event associated with preferential virus tropism for either ciliated or non-ciliated cells of the airway epithelium [15] . The S protein also mediates fusion between lipids of the viral envelope and the host cell plasma membrane or membranes of endocytic vesicles to promote delivery of viral genomic RNA into the cytoplasm . Virus binding and cell entry events can be inhibited by antibodies directed against the S protein , antibodies or small molecules interfering with the virus receptors , or synthetic peptides derived from the fusion-triggering heptad repeat regions of the S protein ( reviewed in [16] ) . Following virus entry , the coronavirus genome , a positive sense , capped and polyadenylated RNA strand , is directly translated resulting in the synthesis of coronavirus replicase gene-encoded nsps . Coronavirus nsps are translated as two large polyproteins harboring proteolytic enzymes , namely papain-like and chymotrypsin-like proteinases that extensively process coronavirus polyproteins to liberate up to 16 nsps ( nsp 1–16 ) [9] , [17]–[20] . These proteolytic functions are considered essential for coronavirus replication and , consequently , a number of candidate drugs were reported to inhibit coronavirus polyprotein processing [21]–[26] . Likewise , the coronavirus RdRp activities , which reside in nsp8 [27] and nsp12 [28] , are considered essential for coronavirus replication and attractive targets for antiviral intervention . In addition to these classical drug targets , coronaviruses encode an array of RNA-processing enzymes representing additional candidate targets . These include a helicase activity linked to an NTPase activity in nsp13 , a 3′-5′-exonuclease activity linked to a N7-methyltransferase activity in nsp14 , an endonuclease activity in nsp15 , and a 2′-O-methyltransferase activity in nsp16 ( reviewed in [28] ) . Like all positive strand RNA viruses , coronaviruses synthesize viral RNA at organelle-like structures in order to compartmentalize this critical step of the viral life cycle to a specialized environment that is enriched in replicative viral and host-cell factors , and at the same time protected from antiviral host defense mechanisms [29]–[31] . There is now a growing body of knowledge concerning the involvement , rearrangement and requirement of cellular membranes for RNA synthesis of a number of positive-strand RNA viruses , including coronaviruses [30] , [32]–[35] . Three coronaviral nsps , i . e . , nsp3 , nsp4 , and nsp6 [9] , [36] , [37] are thought to participate in formation of these sites for viral RNA synthesis . In particular , these proteins contain multiple trans-membrane domains that are thought to anchor the coronavirus replication complex through recruitment of intracellular membranes to form a reticulovesicular network ( RVN ) of modified , frequently paired , membranes that includes convoluted membranes [32] and double membrane vesicles ( DVM ) [38] interconnected via the outer membrane with the rough ER [32] . Indeed , Angelini and colleagues [39] have recently shown that co-expression of all three transmembrane domain-containing SARS-CoV nsps ( nsp3 , nsp4 , and nsp6 ) is required to induce DMVs that are similar to those observed in SARS-CoV-infected cells . Such organelle-like compartments harboring membrane-bound replication complexes show remarkable parallels amongst a broad range of positive-strand RNA virus families , and are potentially evolutionary linked to similar mechanisms in the life cycle of double-strand ( ds ) RNA , reverse-transcribing , and cytoplasmic replicating DNA viruses [29] . Coronavirus ER-derived DMVs are induced early after virus entry into the host cell cytoplasm [9] , [32] , [34] , [38]–[43] , and display striking similarities to DMVs induced by hepatitis C virus [33] . The evolutionary conservation of engaging host cell-derived organelle-like membranous structures for virus RNA synthesis and genetic evidence that impairment of coronavirus DMV integrity is associated with severe reduction of virus replication [44] , [45] suggest that antiviral intervention by targeting membranes involved in virus replication represents an attractive , however yet largely unexplored approach . In this work , we describe a novel inhibitor of coronavirus replication that specifically interferes with membrane-bound coronaviral RNA synthesis . This novel mode-of-action is characterized by severe impairment of DMV formation that results in near-complete inhibition of RNA synthesis . Notably , the inhibitor displayed antiviral activity against a broad range of animal and human coronaviruses , including the recently emerging MERS-CoV .
To identify novel inhibitors of coronavirus infectivity we screened the ChemBioNet collection of 16671 compounds for antiviral activity against HCoV-229E . To this end , MRC-5 cells growing on 384-well plates were supplemented with a specific library compound ( 20 µM ) and then inoculated with HCoV-229E . Compounds that reduced or abolished viral cytopathic effect were re-tested in 24-well plate format for more precise evaluation of their antiviral potential . This two-step screening procedure resulted in several hits including two structurally similar compounds referred to as K22 ( Figure 1A ) and J15 ( Figure S1A ) . The former compound , K22 , whose structural name is ( Z ) -N- ( 3- ( 4- ( 4-bromophenyl ) -4-hydroxypiperidin-1-yl ) -3-oxo-1-phenylprop-1-en-2-yl ) benzamide was examined in detail . The compound was completely soluble in medium up to 50 µM . The concentration of K22 that inhibited the number of HCoV-229E plaques by 50% ( IC50 ) was 0 . 7 µM ( Figure 1B ) . K22 did not reduce viability of MRC-5 cells by >50% ( CC50 ) at a concentration range of 0 . 032–500 µM ( Figure 1C ) . However this compound decreased proliferation of MRC-5 cells with a CC50 value of 110 µM ( Figure 1C ) . Hence , using the CC50 value determined in cell proliferation assay , the selective index for K22 , i . e . the CC50/IC50 quotient , was 157 . Compound J15 , although showing anti-HCoV-229E activity similar to that of K22 exhibited a somewhat less favorable cytotoxicity profile in the cell viability assay ( Figure S1B ) . To assess which step of the HCoV-229E life cycle is affected by K22 , a time-of-addition/removal experiment was performed . K22 ( 4 µM ) was incubated with cells for a period of only two hours either prior to , during , or after infection with HCoV-229E . As shown in Figure 1D , K22 treatment prior to infection resulted in only marginal reduction of virus infectivity thus excluding blockade of cellular receptor ( s ) for HCoV-229E as its mode-of-action . Simultaneous addition of K22 and virus resulted in ∼50% reduction of virus infectivity suggesting that the compound may interact with viral particles thus inactivating their binding or cell-entry activity . To clarify this possibility , the virus was incubated with ∼70 IC50 doses of K22 or DMSO solvent for 15 min at 37°C , followed by virus dilution and its titration at non-inhibitory compound concentrations . Similar titers were observed for the virus treated with K22 ( 7 . 2×105/ml±8 . 9% ) and DMSO ( 7 . 5×105/ml±4 . 7% ) ( n = 2; two experiments ) , indicating that K22 exhibited no virus particle-inactivating activity . Thus , the ∼50% reduction in plaque number ( Figure 1D ) observed by simultaneous addition of K22 and virus is likely due to cellular uptake of K22 and inhibitory activity of probably not yet metabolically processed compound during a very early step of virus replication rather than the drug binding to viral particles and interference with their penetration into cells . This idea is further corroborated by the most pronounced inhibition of HCoV-229E replication when K22 was added after infection ( Figure 1D ) . To more precisely determine the time window of efficient K22-mediated inhibition of HCoV-229E , K22 ( 10 µM ) was added to infected cells at different time points post infection ( p . i . ) , and intra- and extracellular viral RNA , and infectious particles were quantified at 24 hours p . i . . As shown in Figures 1E-F , K22 addition within the first 6 hours p . i . resulted in near complete inhibition of viral RNA synthesis and ∼1000-fold reduction of produced infectious virus , suggesting that K22 inhibits most potently post virus entry during the early phase of the HCoV-229E life cycle . To obtain further insight concerning the target of K22 inhibition we aimed to generate K22-resistant mutants and therefore subjected plaque purified HCoV-229E to 10–13 consecutive passages on MRC-5 cells in presence of increasing concentrations of K22 ( 2–16 µM ) . In two independent experiments we isolated and plaque purified several variants displaying moderate ( ∼2-fold ) to strong ( ∼12-fold ) K22 resistance ( IC50 of 1 . 6–8 . 5 µM; Table 1 ) . Whole genome sequencing analysis of wild type ( wt ) HCoV-229E , mock passaged virus , and K22 passaged virus revealed two amino acid substitutions within nsp 6 ( H121L; M159V ) that were associated with strong K22 resistance ( Table 1 ) . Sequence alignment and prediction of potential transmembrane regions of nsp6 homologs of HCoV-229E and other coronaviruses used in this study , revealed presence of 7 potential membrane-spanning domains ( Figure 2 ) 6 of which are proposed to be used as membrane anchors in other coronaviruses [36] , [37] , and that mutations conferring resistance to K22 are located in or near these regions ( Figure 3A ) . Subsequent generation of recombinant mutants , designated HCoV-229EH121L , HCoV-229EM159V , and HCoV-229EH121L/M159V , carrying the nsp6 mutations individually or combined by reverse genetics confirmed that these mutations confer resistance to K22 inhibition as revealed by plaque inhibition ( Table 1 ) and the time-of-addition ( Figures 3B-C ) assays . Thus , as expected from the previous experiment ( Figure 1E ) , K22 addition within the first 6 hours p . i . with the wt HCoV-229E resulted in near complete inhibition of viral RNA synthesis ( Figure 3C ) , an effect completely abrogated in the drug-resistant recombinant mutant viruses ( Figure 3B ) . Notably , although the amount of intracellular ( Figure 3D ) and extracellular ( Figure 3E ) viral RNA was comparable between K22-resistant mutants and parental wt HCoV-229E , production of infectious particles during infection with K22-resistant mutant viruses was greatly reduced ( up to 34 fold at 48h p . i . ) ( Figure 3F ) . This difference cannot be attributed to the presence of free viral RNA in preparations of extracellular virus , since the treatment of K22-resistant HCoV-229EM159V mutant virus with ribonuclease A did not reduce the quantity of viral RNA ( Figure S2 ) . This observation suggests that K22 resistance-conferring mutations in nsp6 are associated with a fitness cost ( reduced specific infectivity ) . The observation that amino acid substitutions in nsp6 confer K22 resistance strongly suggests a mode-of-action based on interference with host cell membranes required for coronavirus replication . Nsp6 is expressed as a membrane-spanning integral component of the viral replication complex , and is , together with nsp3 and nsp4 , implicated in anchoring the coronavirus replicase complex to DMVs or related membrane structures [9] , [36] , [37] , [39] , [43] . Indeed , there is genetic and experimental evidence concerning nsp4-mediated alterations of coronavirus DMVs [44] , [45] , and that ectopic expression of nsp6 results in the formation of ER-derived vesicles [46] . We therefore assessed if K22 may impact the formation of coronavirus-induced DMV by electron microscopy ( Figure 4 ) . As expected , perinuclear DMV clusters as well as viral particles were readily detectable in wt HCoV-229E-infected cells ( Figure 4A ) . In sharp contrast , no DMV clusters or viral particles were detectable in wt HCoV-229E-infected and K22-treated ( 4 µM ) cells ( Figure 4A ) . Since double-stranded ( ds ) RNA is indicative of coronavirus replication and has been shown to reside predominantly within the inner lumen of coronavirus-induced DMVs [32] we also performed immunofluorescence analysis and stained HCoV-229E-infected cells for viral replicase complex ( nsp8 ) and dsRNA . Strikingly , the characteristic perinuclear immunofluorescence staining pattern for viral replicase complexes and dsRNA visible in wt HCoV-229E-infected cells was completely absent under K22 treatment ( Figure 5 ) , confirming the remarkable efficacy of K22-mediated inhibition of viral replication and supporting the notion that K22 blocks the formation of DMVs . In contrast to parental wt HCoV-229E and irrespectively whether K22 was applied , recombinant K22 escape mutants were still capable of inducing the formation of DMVs ( Figure 4B ) and displayed the characteristic staining pattern for replicase complexes and dsRNA ( Figure 5 ) . Likewise , compound J15 efficiently blocked replication ( Figure S1B ) and DMV formation of wt HCoV-229E but not K22 resistant nsp6 recombinant HCoV-229EM159V ( Figure S3 ) suggesting that J15 may have the same target and mode-of-action . Notably , in cells infected with K22 escape mutants the overall number of DMVs per cell was reduced ( 30 . 3±29 . 7 in HCoV-229EM159V versus 65±50 . 1 in wt HCoV-229E infected cells; P<0 . 05; n = 20 ) , similar as previously described for mouse hepatitis virus ( MHV ) nsp4 mutants [44] , [45] , while the number of intracellular viral particles that were often packed in tubular vesicle-like structures ( Figures 4A-B ) was comparable to that of wt virus ( 471 . 8±212 . 6 in HCoV-229EM159V versus 438 . 3±96 . 8 in wt virus infected cells; n = 10 ) . We could also frequently detect DMVs displaying partially collapsed inner membranes in cells infected with K22 escape mutants ( irrespectively whether or not K22 was applied; Figure 4B ) , again similarly as reported for MHV nsp4 mutants [45] , suggesting that nsp6 , like nsp4 , has a pivotal role in coronavirus DMV formation . Overall , these findings demonstrate that the antiviral activity of K22 ( and that of the structurally similar compound J15 ) results in complete loss of DMVs . This efficient block in replication can be overcome by resistance mutations in nsp6 , and DMVs induced by nsp6 mutant viruses are reduced in numbers and structurally impaired – both findings concurring with the established function of nsp6 in DMV formation . Our data show that K22 targets a very early step in the HCoV-229E life cycle , and the appearance of resistance-conferring mutations in nsp6 suggests that K22 impairs DMV formation . We therefore assessed if K22 treatment may , independent of virus infection , impact autophagy , a cellular process displaying similarities to coronaviral DMV formation . To this end we first transfected Huh7 cells with a plasmid encoding LC3B-GFP in order to trace rapamycin-induced autophagsomes by life imaging . This analysis revealed that three to six hours after adding rapamycin to the culture medium green fluorescent autophagocytic vesicles become apparent , irrespectively if K22 ( 20 µM ) was added or not ( data not shown ) . We corroborated this result by immunofluorescence analysis of Huh7 cells that were stained for endogenous LC3B at six hours post addition of rapamycin . As shown in supplementary Figure S4 rapamycin-incuced autophagocytic vesicles were again readily detectable in the presence of K22 ( 20 µM ) , suggesting that K22 does not impact cellular autophagy . Since K22 inhibits a crucial step in the HCoV-229E life cycle , we assessed the antiviral activity of K22 against a panel of diverse coronaviruses representing the major phylogenetic lineages of α- , β- and ? ? ? -coronaviruses . As shown in Figure 6A-D and supplementary Figure S5 , K22 indeed displayed antiviral activity against recombinant MHV ( strain A59 [47] ) expressing Gaussia luciferase as marker for virus replication , recombinant type-I feline coronavirus ( FCoV; strain Black [48] ) expressing Renilla luciferase as marker for virus replication , avian infectious bronchitis virus ( IBV; strain Beaudette [49] ) , and SARS- CoV ( strain Frankfurt-1 [50] ) , suggesting that K22 targets a broad range of coronaviruses . Furthermore , there was no cytotoxicity detectable in cells of feline ( FCWF cells ) , murine ( L929 cells ) , and primate ( Vero cells ) origin in the K22 concentration range assessed , and analysis of K22 cytostatic activities in the cell proliferation assay revealed CC50 values ≥40 µM ( Table S1 ) , i . e . , the highest drug concentration used in antiviral assays . Notably , the efficacy of K22-mediated inhibition varied amongst different coronaviruses , however whether this is related , as in HCoV-229E , to nsp6 function would require generation and analysis of K22 resistant variants for all coronaviruses tested . In contrast , K22 exhibited little or no effect on replication of poliovirus ( Figure S6 ) , a pathogen that like coronaviruses induces rearrangement of cellular membranes to assist RNA replication . Finally , we assessed the efficacy of K22 inhibition in the primary target cells of respiratory virus infection , the human airway epithelium . Fully differentiated primary human airway epithelia ( HAE ) cultures [15] , [51] derived from three different donors and grown under air-liquid interphase conditions were infected with a recombinant HCoV-229E expressing Renilla luciferase as marker for virus replication [52] , and with MERS-CoV [8] , [51] . MERS-CoV was first described in 2012 and was isolated from a 60-year old man with acute pneumonia , renal failure and fatal outcome in Saudi Arabia [8] . The virus is most likely of zoonotic origin [7] , [53] and by February 2014 the number of laboratory-confirmed cases of MERS-CoV infection reported to the World Health Organization exceeded 182 , including more than 79 cases with fatal outcome . We have previously shown that MERS-CoV can readily replicate on primary HAE cells [51] by infecting non-ciliated cells expressing the cellular receptor dipeptidyl peptidase 4 [14] . As shown in Figure 6 , HCoV-229E and MERS-CoV infections were inhibited by K22 treatment with remarkable efficacy , illustrated by reduction of viral replication by several orders of magnitude ( Figure 6E-F ) and substantial reduction of dsRNA in MERS-CoV-infected primary HAE cultures ( Figure 6G-H ) . This result demonstrates that the broad anti-coronaviral activity of K22 makes this compound particularly promising for the development of efficacious treatment options for emerging coronaviruses , such as MERS-CoV .
Here we describe the discovery of a novel class of inhibitor and propose a mode-of-action that targets membrane-bound viral replication . Like all positive strand RNA viruses , coronaviruses employ host cell membranes to assemble the viral replicase complex . This evolutionary conserved strategy provides a compartment for viral RNA synthesis that is enriched in replicative viral and host cell-derived proteins and believed to protect from antiviral host cell defense mechanisms . The remarkable efficacy of K22-mediated inhibition of coronavirus replication confirms that the employment of host cell membranes for viral RNA synthesis is a crucial step in the coronavirus life cycle , and importantly , demonstrates that this step is extremely vulnerable and also druggable for antiviral intervention . The observation that K22 resistance is mediated through mutations in nsp6 defines transmembrane domain-containing nsps implicated in anchoring viral replicase complexes to host cell-derived membranes , as novel targets for anti-coronaviral intervention . Moreover , we expect this mode-of-action to serve as a paradigm for the development of similar antiviral drugs to combat infections caused by many other positive strand RNA viruses . Notably , resistance conferring mutations in nsp6 emerged only after 10–13 consecutive passages of HCoV-229E under K22 selection , and we were so far not successful in obtaining K22-resistant MHV-A59 mutants ( data not shown ) . This suggests that escape mutations in membrane domain-containing coronavirus nsps compatible with maintaining efficient RNA synthesis are limited . In addition , the nsp6 escape mutants we have obtained for HCoV-229E display a remarkable reduction of specific infectivity . Thus , although RNA synthesis appears to be unaffected and viral RNA detected in preparations of extracellular virus was ribonuclease insensitive implying its adequate package in viral particles , mutations in nsp6 seem to reduce virus fitness . Thus , it is conceivable that the nsp6 mutants may be functionally impaired during an early step in the viral life cycle . Since dsRNA is localized in DMVs and nsp6 escape mutants induced decreased number of DMVs that are structurally impaired , it is possible that the reduced specific infectivity of these viruses could be related to dsRNA-triggered innate immune responses . SARS-CoV nsp6 was recently found to contribute to the establishment of the virus-induced RVN by promoting vesicle formation in transfected cells [39] , and our observation that K22 resistant mutants generated decreased number of DMVs implies that specific alterations may adversely affect the vesicle-forming capability of nsp6 . Nsp6 of HCoV-229E ( this report ) , MHV , and SARS-CoV [36] , [37] is predicted as a hexaspaning protein comprising a conserved C-terminal cytoplasmic tail . The latter domain may serve as a wedge-like amphipathic helix which upon insertion into the lipid membrane can trigger its bending due to induction of positive membrane curvature ( reviewed in [54] ) . The vesicle formation would also require a putative ion channel activity that depolarizes curved membranes thus facilitating their fusion and vesicle scission . The question as to whether nsp6 or other components of the coronavirus replicase complex exhibit such activities would require further investigation . Although our data reveal that the K22 escape mutations occur in nsp6 , further binding experiments are required to clarify whether K22 targets nsp6 directly . We observed that K22 is most active in inhibiting replication of the tested α-coronaviruses ( HCoV-229E , FCoV ) and the γ-coronavirus IBV , whereas amongst β-coronaviruses K22 was highly active in inhibiting MERS-CoV , but only moderately against MHV or SARS-CoV ( Figure 6 ) . It is conceivable that K22 may strong inhibit α-coronaviruses , since K22 has been identified by screening for anti-HCoV-229E activity . However , the limited nsp6 sequence similarity between coronaviruses ( Figure 2 ) does not allow predicting the strength of K22-mediated inhibition of replication based on nsp6 homology . We also like to address in future studies a question of how the moderately resistant virus variant L ( containing mutations in nsp15 and nucleocapsid ) can escape K22-mediated inhibition of replication . This variant , in contrast to these containing resistance mutations in nsp6 , exhibited only moderate resistance to K22 ( ∼2-3-fold ) and was not consistently selected in separate selection experiments . Although nsp15 and nucleocapsid protein have not yet been described as being directly involved in DMV formation , these proteins are components of the replicase complex that may somehow affect/modulate nsp6 functions , and compensatory mutations in these proteins may partially relieve K22 blockade of nsp6 . An alternative possibility is that the actual K22 target may be a cellular protein or a process of recruitment of a cellular protein that participates in coronavirus-induced membrane rearrangements by interacting with nsp6 . While we could not observe any detectable impact of K22 on the formation of autophagosomes , further studies are required to address if K22 may target similar vesicles , such as EDEMosomes [41] . Both possibilities are compatible with the observed phenotype of DMV impairment and the detection of resistance mutations at regions of HCoV-229E nsp6 that are structurally conserved while displaying only limited sequence similarity . It is thus conceivable that membrane domain-containing nsp3 and nsp4 may represent additional drug targets . Similar as described for the related arteriviruses , where co-expression of membrane-spanning nsp2 and nsp3 results in membrane alterations and DMV formation similar to those observed during arterivirus infection [55] , [56] , co-expression of coronavirus nsp3 , nsp4 and nsp6 is required to produce coronavirus-like membrane rearrangements including DMVs [39] . Expression of nsp3 , nsp4 or nsp6 alone or in combinations of two induces aberrant membrane rearrangements that only partially mimic membrane structures known from coronavirus infection [39] . Thus , there is growing evidence that nsp3 , nsp4 , nsp6 , and possibly ER membrane-resident host cell proteins [41] , [57] , orchestrate critical events that lead to the development of suitable membrane structures facilitating coronavirus RNA synthesis . Since K22 apparently interferes with these processes , inhibitors like K22 and corresponding escape mutants will likely become valuable tools to further our understanding on the induction of membrane alterations and DMV formation that take place during the early phase of the coronavirus life cycle . For example , co-expression of nsp3 , nsp4 and native or mutated nsp6 in the absence of virus replication , similar as described by Angelini and colleagues [39] , may help to clarify whether presence of K22 would affect formation of DMV by directly targeting nsp6 or cellular protein ( s ) required and recruited for DMV formation . We emphasize that the identification of K22 and its proposed mode-of-action is only the very first step towards an approved drug for therapeutic use in animals or humans . Specifically , we are currently focusing on the structure-activity relationship analysis of K22 analogs , with the aim to identify compounds with improved antiviral and cytotoxic profiles prior to their assessment in vivo . However , one important lesson of the past SARS-CoV and recent MERS-CoV outbreaks is that zoonotic transmission of coronaviruses into the human population can pose considerable threat to human health and that it is warranted to eventually invest significant efforts to developing efficacious and approved drugs to increase preparedness and combat coronavirus infections . The antiviral activity against a number of diverse coronaviruses makes K22 an ideal candidate for further development towards an efficacious “pan-coronavirus inhibitor” . Broad anti-coronaviral activity has been proposed for inhibitors targeting highly conserved enzymatic functions , such as coronavirus proteinase activities [26] , [58] , or more recently , for compounds targeting host cell factors required for efficient replication , such as cyclophilins [59] , [60] . The concept of targeting multiple key functions of viral replication led to the development of efficacious treatment regimens against HIV and hepatitis C virus by combining multiple antiviral drugs [61] , [62] and it is tempting to speculate that this concept will be applicable to combat coronavirus infections in the future . Moreover , with the identification of K22 , we demonstrate that there are yet additional critical steps in the life cycle of positive strand RNA viruses to explore as targets for antiviral intervention .
Human bronchial epithelial cells were isolated from patients ( >18 years old ) who underwent bronchoscopy and/or surgical lung resection in their diagnostic pathway for any pulmonary disease and that gave written informed consent . This was done in accordance with local regulation of the Kanton St . Gallen , Switzerland , as part of the St . Gallen Lung Biopsy Biobank ( SGLBB ) of the Kantonal Hospital , St . Gallen , which received approval by the ethics committee of the Kanton St . Gallen ( EKSG 11/044 , EKSG 11/103 ) . Human embryonic lung diploid fibroblasts ( MRC-5 ) , African green monkey kidney cells ( Vero ) , baby hamster kidney cells ( BHK-21 ) , felis catus whole fetus 4 cells ( FCWF-4 ) , were purchased from the American Type Culture Collection ( ATCC ) , murine fibroblast cells ( L929 ) , African green monkey kidney cells ( CV-1 ) were purchased from the European Collection of Cell Cultures . D980R cells were a kind gift from G . L . Smith , Imperial College , London , United Kingdom . African green monkey kidney ( GMK AH1 ) cells were obtained from the Swedish Institute for Infectious Disease Control , Stockholm . Cells were grown in Eagle's minimum essential medium ( EMEM ) ( MRC-5 , CV-1 , D980R , L929 , BHK-21 , GMK AH1 cells ) or in Dulbecco's modified EMEM ( DMEM ) ( FCWF-4 , Vero cells ) , supplemented with 5–10% heat-inactivated fetal calf serum , ( HI-FCS ) , 1% L-glutamine , penicillin ( 60 µg/ml ) and streptomycin ( 100 µg/ml ) ( PEST ) . Isolation and cultivation of primary human bronchial epithelial cells to form pseudostratified/differentiated human airway epithelial ( HAE ) cultures was performed as described previously [15] , [63] . Human CoV strain 229E [4] ( HCoV-229E ) was obtained from ATCC ( VR-740 ) . HCoV-229E stocks were prepared from virus passages 6–8 in MRC-5 cells growing in EMEM supplemented with 2% HI-FCS , 1% L-glutamine , HEPES ( 10 mM ) and PEST ( EMEM-FP ) . In some experiments , the virus was concentrated by centrifugation of infectious culture fluid of MRC-5 cells over a 1 . 5 ml cushion of 20% sucrose for 2 h at 22000 rpm ( SW28 . 1 rotor , Beckman ) . The pellet was covered with PBS ( 137 mM NaCl , 2 . 7 mM KCl , 8 . 1 mM Na2HPO4 , 1 . 5 mM KH2PO ) , left overnight at 4°C , and then gently suspended by pipetting . The following viruses and their propagation were described previously: recombinant HCoV- 229E [64] , recombinant HCoV-229E-Ren expressing Renilla luciferase [52] , recombinant feline coronavirus ( strain Black ) expressing Renilla luciferase ( recFCoV-RL ) [48] , SARS-CoV strain Frankfurt-1 [50] , recombinant avian infectious bronchitis virus ( IBV , strain Beaudette ) [49] , MERS-CoV [8] , [51] . Recombinant MHV strain A59 expressing Gaussia luciferase ( MHV-Gluc ) was generated based on the previously described reverse genetics system [47] , [65] . Briefly , the MHV-A59 accessory gene 4 was replaced by the gene encoding the codon-optimized Gaussia luciferase [66] ( hGLuc ) using vaccinia-virus-mediated homologous recombination essentially as described for the generation of MHV-GP33-GFP [67] . The plasmid DNA used for recombination contained MHV-A59 nucleotides ( nts ) 27500–27967 , the hGLuc Gaussia luciferase gene , and MHV-A59 nts 28265–28700 . Recombinant HCoV-229E containing mutations conferring K22 resistance in nsp6 were generated based on the previously described reverse genetics system [64] , [65] . Briefly , vaccinia virus HCoV-inf1 ( containing the full-length HCoV-229E cDNA ) [64] was used to recombine with a plasmid based on pGPT1 [68] where the Escherichia coli guanine phosphoribosyltransferase ( GPT ) gene was flanked by HCoV-229E nts 9398–10098 and 10930–11580 . The resulting GPT-positive vaccinia virus was then used to recombine with plasmids containing the HCoV-229E nts 9398–11580 with modification of nucleotide 10455 ( A to T; HCoV-229EH121L ) , or nt 10568 ( A to G; HCoV-229EM159V ) , or both nts 10455 and 10568 ( HCoV-229EH121L/M159V ) . The resulting vaccinia viruses were then used to rescue HCoV-229EH121L , HCoV-229EM159V , and HCoV-229EH121L/M159V as described previously [64] , [65] . The identity of plasmid DNA and recombinant vaccinia viruses and recombinant coronaviruses was confirmed by sequencing . In some experiments poliovirus 1 strain Sabin ( obtained from the Swedish Institute for Infectious Disease Control , Stockholm ) was used . The ChemBioNet diversity library of 16671 compounds was obtained from the Leibniz Institute for Molecular Pharmacology ( Berlin , Germany ) . Library was provided in a 384 well plate format , each well containing 5 µl of a compound solubilized in DMSO to a final concentration of 10 mM . Hit compound K22 was purchased from ChemDiv ( San Diego , CA; catalog number 4295–0370 ) . The correct structure and purity of K22 ( >95% ) was confirmed in our laboratory by NMR and LCMS analyses . MRC-5 cells were infected at a multiplicity of infection ( moi ) of 0 . 05 with wtHCoV-229E and K22-resistant recombinants HCoV-229EH121L , HCoV-229EM159V , and HCoV-229EH121L/M159V with or without the presence of K22 ( 4 µM ) . The cells were fixed at 18 h p . i . with 4% paraformaldehyde ( PFA ) and immunostained [69] using the mouse monoclonal anti-dsRNA ( J2 , English & Scientific Consulting Bt . ) and rabbit anti-HCoV-229E nsp8 [70] ( kindly provided by John Ziebuhr , University of Giessen , Germany ) as primary antibodies for detection of double-stranded ( ds ) RNA and viral replication complexes . Donkey derived , Dylight 488 labeled , anti-mouse IgG ( H+L ) and Dylight 647 labeled , anti-rabbit IgG ( H+L ) ( Jackson Immunoresearch ) were applied as secondary antibodies . Cells were counterstained with DAPI ( 4' , 6-diamidino-2-phenylindole; Invitrogen ) to visualize nuclei . HAE cell cultures were inoculated with 40000 plaque forming units ( PFU ) , with or without the presence of K22 ( 50 µM ) and fixed with 4% PFA 48 h p . i . Staining was performed with the mouse monoclonal antibody directed against dsRNA ( J2 ) and goat polyclonal anti-ZO1 ( tight junctions; ab99462 , Abcam ) as primary antibodies . Dylight 488-labeled donkey anti-mouse IgG ( H+L ) , Dylight 546-labeled donkey anti-goat IgG ( H+L ) ( Jackson Immunoresearch ) were applied as secondary antibodies , followed by two separate incubation steps with Alexa Fluor647-conjugated rabbit monoclonal anti-beta-Tubulin antibody ( ciliated cells; 9F3 , Cell Signal ) and DAPI ( Invitrogen ) . Images were acquired using EC-plan Neofluar 20x/50 M27 or EC Plan-Neofluar 40x/1 . 30 Oil DIC M27 objectives on a Zeiss LSM 710 confocal microscope . Image capture , analysis and processing were performed using the ZEN 2010 ( Zeiss ) and Imaris ( Bitplane Scientific Software ) software packages . The screening assay was performed as described previously for respiratory syncytial virus [71] . Briefly , MRC-5 cells were seeded in 384 well plates ( CLS-3701; Costar-Corning , NY , USA ) to become ∼70–90% confluent after one day of culture . The growth medium was removed , and the cells supplemented consecutively with 25 µl of EMEM-FP medium , 1 µl volumes of library compounds at 1 mM concentration , and ∼350 PFU of HCoV-229E in 25 µl of EMEM-FP . The last two columns of the 384 well plate received either virus or EMEM-FP medium to serve as controls . The cells were observed under the microscope for their protection from the virus-induced cytopathic effect after 3 and 6 days of incubation at 37°C . Plaque reduction assay to determine the antiviral effect of K22 on HCoV-229E was done as follows . MRC-5 cells were seeded in 12-well plates to become nearly confluent after one day of culture . Serial fivefold dilution of K22 ( 0–100 µM ) and 100 PFU of HCoV-229E virus in 0 . 5 ml of EMEM-FP medium were added to and incubated with cells for 3 h at 37°C , 5% CO2 . Subsequently , the virus-compound mixtures were removed from cells , and 1 . 5 ml volumes of 1% methylcellulose ( MC ) solution in EMEM-FP medium supplemented with the same concentration of K22 were added . The plates with cells were further incubated at 37°C , 5% CO2 for 2–3 days , and then stained with 0 . 2% solution of crystal violet to visualize the viral plaques . Viral yield reduction assays were done to determine the antiviral effect of K22 on HCoV-229E-Ren , recFCoV-RL , MHV-Gluc , SARS-CoV , IBV , MERS-CoV , and poliovirus replication . Briefly , K22 or its DMSO solvent in medium was added at the indicated concentrations to nearly confluent monolayers of corresponding cell lines or to HAE cultures at the basolateral side and incubated for 4 h at 37°C , 5% CO2 . The cells were then inoculated with recFCoV-RL ( moi = 0 . 1 on FCWF-4 cells ) , MHV-Gluc ( moi = 0 . 001 on L929 cells ) , SARS-CoV ( moi = 0 . 001 on Vero cells ) , IBV ( moi = 1 on Vero cells ) , HCoV-229E-Ren ( 4×103 PFU on HAE cultures apically ) , MERS-CoV ( 4×103 PFU on HAE cultures apically ) or poliovirus ( moi = 0 . 001 on GMK AH1 cells ) . After 2 h the viral inoculum was removed , cells were rinsed three times with PBS , and fresh medium containing the same concentrations of K22 or DMSO was added . Coronavirus replication was assessed from cell culture supernatant by determining titer as TCID50 ( tissue culture infectious dose that will produce pathological change in 50% of cell cultures inoculated ) for IBV or poliovirus at 48 h p . i . , by determining the amount of viral genome RNA produced by qRT-PCR specific for SARS-CoV and MERS-CoV at 48 h p . i . as described previously [51] , or by determining the level of Renilla expression at 48 h p . i . ( HCoV-229E-Ren ) or 72 h p . i . ( recFCoV-RL ) using Renilla Luciferase Assay System ( Promega , E2820 ) , or Gaussia luciferase expression ( MHV-Gluc ) at 24 h p . i . using the BioLux Gaussia Luciferase Assay Kit ( NEB , E3300 ) , respectively . For the virucidal assay , 200 µl of HCoV-229E suspension ( ∼3×104 PFU ) in EMEM-FP medium was mixed with 50 µM K22 and incubated for 15 min at 37°C . In the control sample , virus was incubated with the DMSO solvent at a final concentration corresponding to that present in the test compound . Then , both mixtures were diluted serially tenfold in EMEM-FP medium and the residual virus infectivity determined by the viral plaque assay . The toxicity of K22 or its solvent ( DMSO ) for MRC-5 cells was evaluated using the tetrazolium-based CellTiter 96 AQueous One Solution cytotoxicity assay ( Promega; G3580 ) . The effect of K22 or its solvent on proliferation of MRC-5 cells was studied as follows . The cells were seeded in 48 well plates to become ∼50% confluent after one day of culture . The growth medium was removed , and cells incubated with specific concentrations of K22 or its solvent in EMEM-FP medium for 72 h at 37°C . The cells were then dissociated with trypsin/EDTA solution and counted . The effect of K22 or DMSO on viability of Vero , L929 , and FCFW-4 cells was assessed using the CytoTox-Glo Cytotoxicity Assay kit ( Promega , G9291 ) while the toxicity of test compound for differentiated HAE cultures was evaluated with CellTiter-Glo Luminescent Cell Viability Assay kit ( Promega , G7571 ) . MRC-5 cells growing in 12 well plates were precooled for 15 min at room temperature and for another 15 min at 4°C . The cells were rinsed once with 500 µl of cold EMEM-FP and inoculated with HCoV-229E at moi of 0 . 05 . Following virus adsorption to cells for 45 min at 4°C , the cells were rinsed twice with 500 µl of cold EMEM-FP , and 990 µl of warm EMEM-FP medium was added . Subsequently 10 µl of 1 mM K22 was added at specific time points relative to the end of the virus adsorption period , and the infectious cell culture medium and cells harvested at the time point 24 h . The cell culture supernatant medium was clarified by centrifugation at 1000×g for 5 min while the pelleted cells were suspended in RNase-free water and stored at −80°C until quantification in RT-PCR assay . To study the effect of K22 on early virus-cell interaction the “time-of-addition” assay was modified as follows . MRC-5 cells were rinsed once with 1 ml of EMEM-FP and 500 µl of EMEM-FP supplemented with 4 µM K22 was added . The compound was incubated with cells for 2 h at 37°C either prior to , during or after a 2 h period of infection of cells with ∼100 PFU of 229E virus in 500 µl of EMEM-FP . The cells were washed once with 1 ml of EMEM-FP after each 2 h period of their incubation with compound and/or virus . Finally , the cells were overlaid with the MC solution , and after incubation for 2 days at 37°C stained with crystal violet to visualize the viral plaques . The RT TaqMan PCR was carried out as described by Brittain-Long et al . [72] . Briefly , the extraction of RNA was conducted in the Magnapure LC robot using the MagNA Pure LC Total Nucleic Acid Isolation Kit ( Roche Applied Science , Mannheim , Germany ) , and amplification was performed using a TaqMan 7300 Real Time PCR system ( Applied Biosystems , Foster City , CA ) , with a pair of forward 5′-CAGTCAAATGGGCTGATGCA-3′ and reverse 5′-AAAGGGCTATAAAGAGAATAAGGTATTCT-3′ primers as well as a probe 3′CCCTGACGACCACGTTGTGGTTCA 5′ specific for HCoV-229E genome fragment coding for nucleocapsid protein [73] . The number of HCoV-229E RNA copies was determined by relating the detected cycle threshold values to a standard curve prepared based on five tenfold dilutions of the specific plasmid ( pUC57 ) comprising a 94 bp insert from the nucleocapsid sequence of HCoV-229E . qRT-PCR assays to quantify SARS-CoV and MERS-CoV genomic RNA have been described previously [51] . A procedure described previously for respiratory syncytial virus [71] was used . Briefly , plaque purified HCoV-229E was subjected to 10–13 consecutive passages in MRC-5 cells in the presence of increasing concentrations ( 2–16 µM ) of K22 . For control purposes , the same virus was also passaged in MRC-5 cells in the absence of inhibitor . The virus was then subjected to two rounds of plaque purification in the presence of inhibitor , and its relative drug-resistance tested using the viral plaque reduction assay . Genomic RNA of original , mock-passaged , and the K22-resistant virus from passage 10–13 was extracted from extracellular fluid of the 229E-infected MRC-5 cells using the QIAamp viral RNA purification kit ( Qiagen ) . Overlapping DNA fragments covering the entire coding sequence were produced by reverse transcription PCR and subjected to nucleotide sequencing using the ABI PRISM Big Dye Terminator v3 . 1 Cycle Sequencing Ready Reaction kit ( Applied Biosystems ) . Nucleotide sequence analysis was performed using Sequencher 4 . 9 software ( Gene Codes Corporation ) . MRC-5 cells growing in 12 well plates were precooled for 15 min at room temperature and for another 15 min at 4°C . The cells were rinsed once with 500 µl of cold EMEM-FP and inoculated with concentrated preparation ( see the Cells and Viruses section ) of HCoV-229E ( moi = 0 . 05 ) . Following virus adsorption to cells for 1 h at 4°C , the cells were rinsed thrice with 500 µl of cold EMEM-FP , and 500 µl of warm EMEM-FP medium was added . The supernatant fluid and infected cells were harvested at specific time points relative to the end of the virus adsorption period , and processed for determination of viral RNA and infectivity as described under the “time-of-addition” assay . The infectious culture medium comprising HCoV-229E or recombinant nsp6 mutant HCoV-229E M159V were clarified by centrifugation at 1000×g for 5 min , and then 100 µl volumes of the supernatant were supplemented with 2 µl ( 20 µg ) of ribonuclease A ( Thermo Fisher Scientific; EN0531 ) or its solvent . All samples were spiked with ∼7 µg of RNA purified from human respiratory syncytial virus ( RSV ) to serve as an internal control of ribonuclease activity . Following incubation of the virus-enzyme mixture for 30 min at 37°C , the coronaviral and RSV RNA were quantified by RT TaqMan PCR as described by Brittain-Long et al . [72] while coronavirus infectivity was determined by plaque titration . To assess the time-frame where autophagy vesicle formation occurs we seeded Huh-7 cells ( 100 . 000 cells ) on glass bottom 12-well cluster plates ( MatTek ) . Forty-eight hours prior to stimulation cells were transfected with LC3B-GFP plasmid [74] using lipofectamine2000 ( Invitrogen ) , according to manufactures protocol . Hereafter cells were exposed to 100 nM of rapamycin ( Invivogen ) alone or in presence of either 20 µM of K22 or an equal volume of DMSO for the duration of 18 hours at 37°C . Fluorescent and differential interference contrast ( DIC ) images were acquired with 30 minute interval using EC Plan Neo-fluar 40x/1 . 30 Oil DIC M27 objective on a Zeiss LSM 710 confocal microscope . Image capture , analysis and processing were performed using the ZEN 2010 ( Zeiss ) . To determine whether K22 inhibits endogenous autophagy vesicle formation we stimulated Huh-7 cells ( 40 . 000 cells ) with 100 nM of rapamycin alone or in presence of either 20 µM of K22 or an equal volume of DMSO for duration of six hours at 37°C . Unstimulated cells were used as mock control . Cells were fixed and immunostained as previously described [69] . Rabbit polyclonal anit-LC3B ( L7543 , Sigma Aldrich ) was applied as primary antibody for the detection of autophagy vesicles . Goat derived , Cy3 labeled , anti-rabbit IgG ( H+L; Jackson ImmunoResearch ) was applied as secondary antibody . Thereafter cells were counterstained with DAPI ( Invitrogen ) . Fluorescent images were acquired using a PLAPON 60xO/1 . 42 objective on an Olympus FV-1000 confocal microscope . Image capture , analysis and processing were performed using the Olympus Fluoview software . MRC-5 cells growing on a Melinex polyester film ( Agar Scientific Ltd . , Stansted , U . K . ) in 24 well cluster plates were infected with HCoV-229E ( moi = 0 . 04 ) in the presence of 10 µM of K22 . After 18 h of infection at 37°C , the culture medium was removed , the cells rinsed twice with Eagle's medium , and a fresh Eagle's medium supplemented with 2 . 5% glutaraldehyde was added and incubated for 45 min at 37°C . The cells were washed twice with 0 . 05 M Tris-HCl buffer ( pH 7 . 4 ) supplemented with 2 mM CaCl2 , and further processed for electron microscopy as described [75] . Experiments with recombinant nsp6 mutant viruses and original virus were carried out in a similar manner except that the cells were inoculated at a moi of ∼0 . 25 and incubated with or without the presence of 4 µM K22 .
|
Viruses that replicate in the host cell cytoplasm have evolved to employ host cell-derived membranes to compartmentalize genome replication and transcription . Specifically for positive-stranded RNA viruses , accumulating knowledge concerning the involvement , rearrangement and requirement of cellular membranes for RNA synthesis specify the establishment of the viral replicase complex at host cell-derived membranes as an evolutionary conserved and essential step in the early phase of the viral life cycle . Here we describe a small compound inhibitor of coronavirus replication that ( i ) specifically targets this membrane-bound RNA replication step and ( ii ) has broad antiviral activity against number of diverse coronaviruses including highly pathogenic SARS-CoV and MERS-CoV . Since resistance mutations appear in an integral membrane-spanning component of the coronavirus replicase complex , and since all positive stranded RNA viruses have very similar membrane-spanning or membrane-associated replicase components implicated in anchoring the viral replication complex to host cell-derived membranes , our data suggest that the membrane-bound replication step of the viral life cycle is a novel , vulnerable , and druggable target for antiviral intervention of a wide range of RNA virus infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases",
"veterinary",
"diseases",
"zoonoses",
"medicine",
"and",
"health",
"sciences",
"respiratory",
"infections",
"sars",
"veterinary",
"virology",
"common",
"cold",
"biology",
"and",
"life",
"sciences",
"viral",
"diseases",
"pulmonology",
"veterinary",
"science"
] |
2014
|
Targeting Membrane-Bound Viral RNA Synthesis Reveals Potent Inhibition of Diverse Coronaviruses Including the Middle East Respiratory Syndrome Virus
|
The complement C3-like protein TEP1 of the mosquito Anopheles gambiae is required for defense against malaria parasites and bacteria . Two forms of TEP1 are present in the mosquito hemolymph , the full-length TEP1-F and the proteolytically processed TEP1cut that is part of a complex including the leucine-rich repeat proteins LRIM1 and APL1C . Here we show that the non-catalytic serine protease SPCLIP1 is a key regulator of the complement-like pathway . SPCLIP1 is required for accumulation of TEP1 on microbial surfaces , a reaction that leads to lysis of malaria parasites or triggers activation of a cascade culminating with melanization of malaria parasites and bacteria . We also demonstrate that the two forms of TEP1 have distinct roles in the complement-like pathway and provide the first evidence for a complement convertase-like cascade in insects analogous to that in vertebrates . Our findings establish that core principles of complement activation are conserved throughout the evolution of animals .
The mosquito Anopheles gambiae is the main vector of Plasmodium falciparum malaria in sub-Saharan Africa and hence directly responsible for the death of hundreds of thousands of people every year and for a devastating socioeconomic burden especially in endemic countries . Mosquitoes launch a potent immune attack leading to the killing of the majority of invading Plasmodium parasites . Multiple mechanisms are thought to participate in these anti-Plasmodium reactions , amongst them a latent pathway resembling vertebrate complement [1] . RNAi knockdown ( kd ) studies , based on the injection of double stranded RNA ( dsRNA ) into adult A . gambiae mosquitoes , have revealed important roles of components of the complement-like pathway in defense against the murine malaria parasite Plasmodium berghei [2]–[6] . There is also significant evidence for a role of this pathway in defense against the human parasite , P . falciparum , in laboratory infections of A . gambiae [3] , [7]–[9] . Recent studies with natural A . gambiae populations revealed that the gene encoding the C3-like protein TEP1 , a key player of the complement-like pathway , and the genomic locus encoding its interacting partner APL1C are under strong directional selection in an M form population but subject to balancing selection in another S form population [10] , [11] . Despite the fact that distinct TEP1 alleles have been associated with resistance to Plasmodium parasites [2] , [8] , [11]–[13] , the selective pressure on TEP1 is hypothesized to be driven by pathogens in larval habitats rather than those encountered by adults . This is further supported by the rather generic immune specificity of TEP1 that functions also in anti-bacterial [3] , [14] and anti-fungal defense [15] . The polymorphic nature of TEP1 also suggests that the different alleles might follow different kinetics in interacting with LRIM1/APL1C as well as other TEP1 regulatory proteins , which could influence the efficiency of parasite killing or microbial clearance . Therefore , a better understanding of the mechanisms regulating complement activation and identification of the proteins involved will permit deciphering the functional relevance to Plasmodium of allelic interactions within this immune module on resistance . The hallmark of activation of the mosquito complement-like pathway is the binding of TEP1 to microbial surfaces through a thioester bond , a reaction that is tightly linked to microbial killing [14] . TEP1 circulates in the mosquito hemolymph in two forms: the full-length form TEP1-F and the proteolytically processed form TEP1cut , corresponding to pro-C3 and the mature C3 protein after processing in the ER , respectively [14] , [16] . Unlike C3 , TEP1 lacks an anaphylatoxin domain and the exposed thioester bond of TEP1cut is unstable [17] . TEP1cut is stabilized in the hemolymph through interactions with a heterodimer of the leucine-rich repeat ( LRR ) proteins LRIM1 and APL1C , which seems to confer specificity upon TEP1 activity [5] , [16] . While the structure and function of TEP1 and its C3 homolog are largely conserved from insects to mammals , LRIM1 and APL1C are thought to be specific to mosquitoes [18] raising interesting questions about the degree of structural and/or functional conservation between other modules of the complement pathway such as those that stabilize or amplify complement on microbial surfaces . The research presented here aimed to address these questions and provide novel mechanistic insights into the activation of the mosquito complement pathway during infection .
To identify novel components of the mosquito complement pathway , we searched for genes that exhibited significant co-regulation with LRIM1 in a developmental transcriptome dataset of Expressed Sequence Tags ( ESTs; [19] ) . Pearson correlation coefficient ( PCC ) identified 4 EST clusters showing similarity to LRIM1 developmental expression greater than 0 . 95 . Importantly , 3 of the 4 clusters were found to encode proteins that had been previously shown to physically interact with LRIM1 , including APL1C ( PCC 0 . 964 ) , TEP1 ( PCC = 0 . 978 ) and TEP4 ( PCC = 0 . 965 ) [5] , [16] , [20] . The fourth EST cluster ( PCC = 0 . 980 ) did not correspond to any gene model in the A . gambiae genome . It encodes a protein with CLIP and serine protease domains , previously identified as SPCLIP1 and shown to be involved in defense against P . falciparum , P . berghei , Escherichia coli and Staphylococcus aureus [3] . SPCLIP1 maps within a genomic region encompassing 12 additional genes encoding proteins with CLIP and serine protease domains ( Figure S1A ) . All residues corresponding to the serine protease catalytic triad ( Asp-His-Ser ) are substituted in SPCLIP1 indicating that it is non-catalytic ( Figure S1B ) . Phylogenetic analysis places SPCLIP1 in the highly divergent CLIPE subfamily of non-catalytic CLIP-domain serine protease homologs ( SPHs; Figure S1C ) . Co-regulation with LRIM1 and the previously reported knockdown phenotypes [3] were suggestive of SPLCLIP1 involvement in the A . gambiae complement-like pathway . To characterize SPCLIP1 , we raised a polyclonal antibody against the entire protein and used it in western blots of adult mosquito hemolymph separated by non-reducing SDS-PAGE . The results showed that SPCLIP1 migrates at approximately 45 kDa , near its predicted 42 kDa molecular weight ( Figure 1A ) . We examined whether the steady state levels of SPCLIP1 in the hemolymph are affected by silencing LRIM1 or TEP1 . While TEP1 kd had no effect on SPCLIP1 levels , these were markedly reduced in LRIM1 kd ( Figure 1B ) . This decrease of SPCLIP1 parallels the near complete loss of TEP1cut from the hemolymph of LRIM1 or APL1C kd mosquitoes due to its accumulation on self-tissues ( Figure 1B ) [5] , [16] . To determine if the reduction of SPCLIP1 in LRIM1 kd is dependent on TEP1 , we silenced LRIM1 and TEP1 simultaneously . Under these conditions , SPCLIP1 was restored to its baseline levels ( Figure 1C ) . In contrast , silencing LRIM1 and SPCLIP1 together did not restore TEP1cut levels , suggesting that SPCLIP1 functions downstream of TEP1cut , and that in LRIM1 kd mosquitoes SPCLIP1 is likely to be sequestered on self-tissues together with TEP1cut . We investigated the role of SPCLIP1 in TEP1 binding to P . berghei . It has been previously established that TEP1 binds to the surface of P . berghei ookinetes as they traverse the mosquito midgut epithelium and come into contact with the hemolymph [2] . In SPCLIP1 kd mosquitoes , TEP1 staining on the ookinete surface was inhibited ( Figure 2A ) . This , together with the TEP1-dependent reduction of SPCLIP1 from the hemolymph following LRIM1 kd , led us to hypothesize that SPCLIP1 is recruited to the parasite surface during infection . To test this , SPCLIP1 was immunolocalized in midgut epithelium 26 h after infection . We observed robust SPCLIP1 signal on dead ookinetes , judged by the loss of their cytoplasmic GFP signal ( Figure 2B ) . Given that TEP1 is also highly prevalent on dead ookinetes , this result indicates that SPCLIP1 and TEP1 likely co-localize to the same ookinetes; however , we could not simultaneously assay their distribution since both antibodies were raised in the same host species . No SPCLIP1 staining was observed in midgut epithelia dissected from SPCLIP1 kd mosquitoes , showing that the antibody is specific . Importantly , SPCLIP1 staining on the ookinete surface was inhibited after TEP1 kd . This suggests that the localization of TEP1 and SPCLIP1 to ookinetes is mutually dependent ( Figure 2B ) . TEP1 present on microbial surfaces during infection may originate either from the TEP1cut or the TEP1-F pools . To clarify this point and investigate further the functional relationship between the two forms of TEP1 and SPCLIP1 , we developed an alternative infection model that allowed us to monitor temporally and quantitatively the dynamics of the examined proteins after injection of E . coli bioparticles ( chemically killed bacteria ) into the hemocoel . This infection model offers the advantage of tight temporal monitoring of rapid immune responses such as those of complement , which occur within minutes of microbial exposure to the hemolymph . Hemolymph was collected from groups of mosquitoes at 15 , 60 , 120 , 240 and 360 minutes post injection with bacteria or PBS ( i . e . control ) and proteins were analyzed by western blot . The results showed strong reduction in SPCLIP1 , the LRIM1/APL1C complex , and TEP1-F levels in mosquito hemolymph after injection of E . coli bioparticles ( Figure 3A ) . A marked reduction of these proteins was already observed at 60 min after injection and persisted up to 240 min when LRIM1/APL1C and TEP1-F levels began to rise . The kinetics of TEP1-F reduction demonstrate that this form of TEP1 is consumed quickly in the immune response to infection , in contrast to TEP1cut , which does not seem to vary significantly during that process , at least within the examined timeframe . In addition to the well-defined TEP1-F and TEP1cut bands , we also observed a broadly stained TEP1-specific smear at 50–60 kDa exhibiting depletion kinetics following bioparticle challenge similar to that of TEP1-F ( Figure 3A ) . These C-terminal TEP1 fragments have been previously described [14]; whether they represent functional forms of TEP1 or are products of TEP1-F turnover remains to be determined . LRIM1/APL1C and SPCLIP1 exhibited similar depletion kinetics as TEP1-F following bioparticle injections ( Figure 3A ) , suggesting that these proteins are either required for TEP1-F utilization or are independently consumed in the immune reactions . To address this , we monitored the effect of SPCLIP1 silencing on the infection-dependent depletion of TEP1-F . Western blot analysis of hemolymph collected from SPCLIP1 and control LacZ kd mosquitoes challenged with E . coli bioparticles demonstrated that the loss of TEP1-F is abolished in SPCLIP1 kd mosquitoes compared to controls ( Figure 3B ) , indicating that SPCLIP1 acts upstream of TEP1-F and is indeed required for the infection-induced loss of this protein . In contrast , the depletion of LRIM1/APL1C was not restored in the hemolymph of SPCLIP1 kd mosquitoes . Together , these data suggest that activation of mosquito complement by the LRIM1/APL1C/TEP1cut complex is a separate event upstream of the SPCLIP1-dependent complement amplification process that is poised to transform initial pathogen recognition into a robust attack . An important aspect of the complement system is its specific activation on microbial surfaces . In order to address whether the observed reduction in SPCLIP1 and TEP1-F levels in the hemolymph after injection of E . coli bioparticles is due to their sequestration on bioparticle surfaces , we designed an assay that allows quantitative assessment of E . coli-bound versus hemolymph soluble pools of these proteins . E . coli bioparticles were injected into mosquito hemocoel , and hemolymph was extracted 15 min after injection . Bioparticles were separated from the hemolymph by centrifugation , washed extensively and their surface-bound proteins eluted for western blot analysis ( Figure 4A ) . The results showed that SPCLIP1 was present in the E . coli-bound fraction in dsLacZ control mosquitoes ( Figure 4B ) , which explains its reduced levels in the hemolymph after bacterial challenge and is consistent with its localization to ookinetes . In TEP1 kd mosquitoes , SPCLIP1 was lost from the E . coli-bound fraction and became enriched in the soluble fraction , indicating that TEP1 is required for SPCLIP1 recruitment to bacterial surfaces . This assay also allowed us to monitor which of the two forms of TEP1 associates with the bacterial surface . In dsLacZ treated mosquitoes , TEP1-F was not detected in the E . coli-bound fraction , despite being almost fully depleted from the soluble material , in contrast to TEP1cut , which was clearly present . These data are consistent with those reported previously using a cell culture assay and showing that bacteria only bound TEP1cut when incubated with the conditioned medium of a hemocyte-like cell line that contained both forms of TEP1 [14] . Importantly , TEP1cut signal in the bound material was dramatically reduced by SPCLIP1 kd , concomitant with the detection of TEP1-F in the soluble fraction . These data indicate that TEP1cut accumulating on the surface of E . coli is generated from TEP1-F and that its conversion requires recruitment of SPCLIP1 and a yet unidentified protease to the bacterial surface . The functional association between SPCLIP1 and TEP1 including their cooperative recruitment to microbial surfaces suggested that these two proteins might physically interact . To examine this possibility , we performed an immunoprecipitation ( IP ) assay on hemolymph samples collected from mosquitoes following challenge with E . coli bioparticles using beads cross-linked to an affinity purified SPCLIP1 antibody . IP beads lacking antibody and mock bioparticle challenge ( PBS injection ) served as controls . The results revealed that SPCLIP1 was less abundant in the unbound fraction and significantly enriched in the bound fraction ( Figure 5 ) . In contrast , SPCLIP1 was not detected on control beads and the protein remained highly abundant in the unbound fraction . When samples were probed for TEP1 , a signal for TEP1cut and a faint but clear TEP1-F signal were observed in the SPCLIP1 IP bound fraction . These bands were detectable only in samples collected from bioparticle challenged mosquitoes . These data indicate that SPCLIP1 and TEP1 can interact and that this interaction is induced by infection . These data raise the possibility that these proteins interact first in the hemolymph prior to their localization on microbial surfaces . Alternatively , membrane-bound complexes containing TEP1 and SPCLIP1 may leach off the surface during sample preparation . Whether this interaction is direct or mediated by another factor remains to be determined . It has been previously shown that bacterial inoculation into the mosquito hemolymph leads to rapid activation cleavage of CLIPA8 , a key SPH regulator of bacteria [21] fungi [15] , and Plasmodium melanization [22] . We examined whether SPCLIP1 is required for CLIPA8 activation in the mosquito hemolymph following E . coli bioparticle injection . As shown in Figure 6A , silencing SPCLIP1 inhibited completely CLIPA8 cleavage , suggesting that SPCLIP1 is required for activation of the melanization cascade . The final steps of melanization are catalyzed by phenoloxidase ( PO ) which is secreted as a pro-enzyme ( PPO ) and activated by proteolytic cleavage in response to infection . We directly examined whether SPCLIP1 is essential for PPO activation by monitoring PO activity in the mosquito hemolymph after bacterial injection . Indeed , SPCLIP1 kd resulted in a strong decrease in PO activity relative to dsLacZ-injected controls , which is comparable to that observed in CLIPA8 kd mosquitoes ( Figure 6B ) . Similar to SPCLIP1 kd , silencing TEP1 also resulted in strong inhibition of both CLIPA8 cleavage and PPO activation ( Figure S2 ) . These data demonstrate that activation of the melanization cascade is dependent on SPCLIP1-mediated TEP1 accumulation on the bacterial surface . We next tested the function of SPCLIP1 in P . berghei melanization using as a model CTL4 kd mosquitoes which melanize nearly all ookinetes soon after they traverse the mosquito midgut and before they develop into oocysts [4] . Indeed , silencing CTL4 alone resulted in a marked decrease of the oocyst numbers and a reciprocal increase in melanized ookinetes , but concomitant silencing of SPCLIP1 completely blocked ookinete melanization and led to an increase in oocysts comparable to that of SPCLIP1 kd alone ( Figure 6C ) . A similar inhibition of parasite melanization has been observed after silencing TEP1 or LRIM1/APL1C [2] , [4] , [5] . These data reveal that , as with bacterial melanization , SPCLIP1-mediated accumulation of TEP1 on the ookinete surface is required for parasite melanization .
Here we characterize SPCLIP1 , a non-catalytic CLIP-domain serine protease of the malaria vector mosquito A . gambiae , which localizes to the surface of P . berghei ookinetes and E . coli promoting rapid accumulation of the complement C3-like protein TEP1 . Our results demonstrate that SPCLIP1 regulates a complement convertase-like activity henceforth referred to as TEP1 convertase . The TEP1 convertase is functionally analogous to the vertebrate C3 convertase , the formation of which is triggered by binding of antibodies or innate pattern recognition proteins on the microbial surfaces , or by spontaneous activation of C3 following hydrolysis of its thioester . The trigger for the formation of the TEP1 convertase is thought to be the binding on the microbial surface of TEP1cut which circulates in the mosquito hemolymph together with the LRIM1/APL1C complex ( Figure 7 ) . LRIM1 and APL1C possess LRR domains , a feature that is versatile in its binding properties and common in pattern recognition receptors involved in host defense in animals and plants [23] . Therefore , the LRIM1/APL1C complex may play a dual role in the mosquito complement-like pathway by stabilizing TEP1cut in the hemolymph and delivering it to the microbial surface upon infection . Given that the LRIM1 and APL1C belong to a mosquito-specific family of LRR proteins [5] whereas TEPs are widely conserved [24] , different triggers of complement activity are likely to exist in other insects . A number of different putative pattern recognition receptors have been identified to play a role in TEP1-dependent defense against bacteria and malaria parasites [4] , [6] , [25]–[27] raising the possibility that mosquitoes may also have multiple recognitions systems that can activate the TEP1 convertase . It has been proposed that nitration of malaria parasites during their passage through the mosquito midgut epithelium is required for TEP1 binding [28] . Whether microbe nitration can trigger recognition by LRIM1/APL1C or other putative recognition receptors remains to be determined . A study using recombinant proteins and an allele of TEP1 from mosquitoes that are refractory to Plasmodium has shown that the LRIM1/APL1C complex binds TEP1cut lacking an intact thioester , and that TEP1cut precipitates out of solution in the absence of LRIM1/APL1C [17] . A more recent study using a TEP1cut allele from susceptible mosquitoes has revealed that the LRIM1/APL1C complex can interact with TEP1cut with an active thioester [29] . These in vitro studies have led the authors to speculate that a complex between LRIM1/APL1C and TEP1cut may function in vivo as a TEP1 convertase . It remains unknown whether TEP1cut lacks an intact thioester in vivo , and whether its localization on mosquito tissues in the absence of LRIM1/APL1C is the result of protein precipitation or autoimmune attack by an active thioester motif [5] , [16] . The TEP1cut dependent SPCLIP1 depletion favors the hypothesis of an autoimmune attack that is tightly regulated to prevent collateral damage to host tissues . Indeed , SPCLIP1 loss from the hemolymph following artificial induction of TEP1cut attack of self-tissues is not accompanied by TEP1-F depletion , suggesting that downstream negative regulators prevent the full formation of the TEP1 convertase and/or that additional positive factors similar to vertebrate properdin may be required to stabilize the convertase on microbial surfaces . SPCLIP1 lacks catalytic serine protease activity and likely acts as a regulatory component of the TEP1 convertase . Hence , an unidentified protease and possibly other factors are expected to also contribute to the mature convertase , catalyzing the activation cleavage of TEP1-F . The role of non-catalytic serine proteases as cofactors for active proteases is well documented in insects with examples from Holotrichia diomphalia [30] , Manduca sexta [31] and Drosophila melanogaster [32] . The SPCLIP1-dependent rapid loss of TEP1-F from the hemolymph of bioparticle injected mosquitoes and the observation that SPCLIP1 kd in naive mosquitoes does not alter TEP1-F levels , suggests that the TEP1cut cargo circulating as a complex with LRIM1/APL1C is generated through a different mechanism than that produced by the TEP1 convertase . Of note , while bioparticle injection almost depletes TEP1-F from the hemolymph , only a minor reduction in TEP1cut levels is observed most significantly at 60 min post injection . A plausible explanation for this observation is that TEP1-F is converted to TEP1cut prior to binding the bacterial surface , a fraction of which remains soluble in the hemolymph throughout the timeframe of the experiment . Regardless of the activation mechanism , the C3 and TEP1 convertases function in very similar ways to recruit additional C3 and TEP1 , respectively , from precursor pools onto the microbial surface , and to initiate diverse effector cascades . In vertebrates , accumulation of the C3 cleavage product , C3b , on microbial surfaces triggers phagocytosis as well as assembly of the membrane attack complex that causes microbial lysis . In mosquitoes , in addition to triggering phagocytosis of bacteria [14] , [33] and lysis of malaria parasites [2] , [3] , TEP1 accumulation on microbial surfaces triggers the PO cascade leading to melanization . Therefore , the strategy of complement driving diverse effector functions is ancient and not specifically co-opted by vertebrates . It remains to be further investigated whether this system is indeed an example of convergent evolution rooted to the functional conservation of thioester-containing proteins , a hypothesis consistent with our earlier findings that this pathway appears to have evolved de novo in each mosquito species by “bricolage” assemblages of the most suitable available components [34] .
This study was carried out in strict accordance with the United Kingdom Animals ( Scientific Procedures ) Act 1986 . The protocols for maintenance of mosquitoes by blood feeding and for infection of mosquitoes with P . berghei by blood feeding on parasite-infected mice were approved and carried out under the UK Home Office License PLL70/7185 awarded in 2010 . The procedures are of mild to moderate severity and the numbers of animals used are minimized by incorporation of the most economical protocols . Opportunities for reduction , refinement and replacement of animal experiments are constantly monitored and new protocols are implemented following approval by the Imperial College Ethical Review Committee . A . gambiae G3 strain was maintained and assayed for infection with P . berghei CONGFP strain as described previously [20] . Single and double knockdown experiments and parasite counts in dissected midguts were performed as described previously [5] . Primers used for synthesis of double stranded RNA have been reported elsewhere LRIM1 , TEP1 , CTL4 [4] , [35]; SPCLIP1 [3] . The entire SPCLIP1 open reading frame lacking the endogenous signal peptide and stop codon was cloned into the pIEx10 insect cell expression plasmid ( Novagen ) incorporating a C-terminal 10× HIS-tag using the primers: For: GACGACGACAAGATGAACTTCCCCGTTGGGAAATTTC Rev: GAGGAGAAGCCCGGTTTATCGAAGCTGATCGGATCGGG The underlined sequences are extensions to allow ligase-independent cloning [5] . Sf9 cells adapted for growth in serum-free medium ( Invitrogen ) stably secreting SPCLIP1HIS were generated by selection with 1 mg/mL G418 following co-transfection using Escort IV ( Sigma ) of pIEx10-SPCLIP1HIS and pIE1-neo ( Novagen ) . Clones of resistant cells were analyzed by western blot for the presence of SPCLIP1HIS in their conditioned medium and the line with the highest expression was chosen for protein production . SPCLIP1HIS was purified from 500 mL of conditioned medium using a 1 mL HisTrap column attached to an ÄKTA purifier ( GE Healthcare ) . Bound protein was eluted in 15 mL of PBS containing 500 mM imidazole pH 8 . 0 . Purified SPCLIP1HIS was quantified by Bradford assay and by coomassie staining of SDS-PAGE gels . The purified protein was used to generate a rabbit polyclonal antibody ( Eurogentec ) . SPCLIP1 antibody was affinity purified from the positive immune serum by passage over an AminoLink column ( Pierce ) containing covalently bound SPCLIP1HIS . A 20 mg/mL suspension of fluorescein or pHrodo labeled E . coli K-12 strain bacterial bioparticles ( Invitrogen ) in sterile PBS was injected into the mosquito hemocoel ( ∼4×105 bacteria in 69 nL ) . Hemolymph was collected directly into non-reducing SDS-PAGE sample buffer from groups of 30–40 mosquitoes 15 , 60 , 120 , 240 and 360 min after the challenge and analyzed by reducing and non-reducing western as described previously [5] . Bioparticles surface extraction was performed by collecting in protein LoBind tubes ( Eppendorf ) hemolymph from 60 mosquitoes into 60 µL of 15 mM Tris ( pH 8 . 0 ) containing 1× protease inhibitor cocktail ( complete EDTA free , Roche ) 15 min after bacterial injection . The soluble ( unbound ) fraction was collected after pelleting the bacteria by centrifugation for 4 min at 6000 g at 4°C and then supplemented with SDS-PAGE buffer . The bacterial pellet was washed with 400 µL of 15 mM Tris ( pH 8 . 0 ) and the bound fraction was extracted with 25 µL SDS-PAGE sample buffer . Western blot analysis was performed using 25 µL of each sample . Western blot analysis for TEP1 , LRIM1/APL1C , SRPN3 , CLIPA8 and PPO6 was performed as previously described [5] , [21] . The affinity purified rabbit α-SPCLIP1 antibody was used to probe western blots at a 1∶1000 dilution of antibody in PBS containing 0 . 05% Tween 20 and 3% milk for 1 h at room temperature using . Co-immunoprecipitation reactions were performed using the Pierce Co-IP kit according to the manufacturer's protocol ( ThermoScientific ) . Hemolymph was collected from 100 mosquitoes into 200 µL ice-cold PBS containing 0 . 05% Triton X-100 , supplemented with 1× protease inhibitor cocktail 15 min after PBS or E . coli bioparticle injection ( 69 nL of 4 mg/mL; ∼8×104 particles ) . The samples were centrifuged at 4000 g for 5 min to remove mosquito and bacterial cells . 40 µL of a 1∶1 slurry of PBS and agarose beads containing crosslinked affinity purified α-SPCLIP1 antibody or control beads were added to the cleared hemolymph samples and mixed overnight at 4°C on a rotating wheel . The unbound fraction was collected and supplemented with SDS-PAGE buffer . Then the beads were washed five times with collection buffer and bound material was eluted two times with 100 µL of elution buffer ( 0 . 2% SDS and 0 . 1% Tween-20 in 50 mM Tris pH 8 . 0 ) . The eluents were pooled and supplemented with SDS-PAGE buffer . Western blot analysis was performed by loading 40 µL of each sample . Reducing samples were made by addition of 2-mercaptoethanol to a final concentration of 2 . 5% . Cleavage of CLIPA8 was assayed in samples of hemolymph analyzed under reducing conditions as described previously [21] . PPO activation was determined assaying the conversion of L-DOPA to Dopachrome in samples of mosquito hemolymph collected after bacterial challenge [36] . TEP1 and SPCLIP1 were immunolocalization to ookinetes 26 h after P . berghei infection . Mosquito midguts were prepared and analyzed as previously described [5] . The SPCLIP1 antibody was used at a 1∶250 dilution . Images were acquired on a Zeiss LSM 710 META confocal . LRIM1 , AGAP006348; APL1C , AGAP007033; TEP1 , AGAP010815; TEP4 , AGAP010812; CLIPA1 , AGAP011791; CLIPA2 , AGAP011790; CLIPA4 , AGAP011780; CLIPA5 , AGAP011787; CLIPA6 , AGAP011789; CLIPA7 , AGAP011792; CLIPA8 , AGAP010731; CLIPA9 , AGAP010968; CLIPA12 , AGAP011781; CLIPA13 , AGAP011783; CLIPA14 , AGAP011788; CLIPB2 , AGAP003246; CLIPB3 , AGAP003249; CLIPB4 , AGAP003250; CLIPB8 , AGAP003057; CLIPB9 , AGAP013442; CLIPB10 , AGAP003058; CLIPB13 , AGAP004855; CLIPB14 , AGAP010833; CLIPB15 , AGAP009844; CLIPC1 , AGAP008835; CLIPC2 , AGAP004317; CLIPC3 , AGAP004318; CLIPC5 , AGAP000571; CLIPC6 , AGAP000315; CLIPC9 , AGAP004719; CLIPC10 , AGAP000572; CLIPD4 , AGAP002811; CLIPD6 , AGAP002813; CLIPD7 , AGAP008998; CLIPD8 , AGAP002784; CLIPE2 , AGAP011782; CLIPE4 , AGAP010530; CLIPE5 , AGAP010547; CLIPE6 , AGAP011785; CLIPE7 , AGAP011786; PPO6 , AGAP004977; CTL4 , AGAP005335; SRPN3 , AGAP006910 .
|
Mosquitoes are vectors of numerous human diseases including malaria . Disease transmission requires that microbes overcome the robust mosquito immune system . In the African malaria mosquito , the TEP1 protein that is homologous to mammalian complement factor C3 is shown to play a central role in mosquito immunity to malaria parasites and bacteria . In this study , we report that another mosquito protein belonging to a class of non-catalytic enzymes that are specific to arthropods is a core component of the mosquito complement-like immune pathway . We found that this new protein , named SPCLIP1 , regulates the accumulation of TEP1 on malaria parasites and bacteria , and show that this can lead to distinct defense reactions including lysis and melanization of the pathogen . This work is valuable because it reveals novel insight into the regulation of mosquito complement on microbial surfaces such as those of the malaria parasites . Unraveling the molecular mechanisms regulating these defense responses may ultimately lead to the design of novel disease blocking strategies in the vector .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"complement",
"system",
"immunity",
"vector",
"biology",
"innate",
"immunity",
"anopheles",
"immune",
"defense",
"immunology",
"biology",
"microbiology",
"parasitology",
"immune",
"system"
] |
2013
|
The CLIP-Domain Serine Protease Homolog SPCLIP1 Regulates Complement Recruitment to Microbial Surfaces in the Malaria Mosquito Anopheles gambiae
|
Disruption of gene regulation is known to play major roles in carcinogenesis and tumour progression . Here , we comprehensively characterize the mutational profiles of diverse transcription factor binding sites ( TFBSs ) across 1 , 574 completely sequenced cancer genomes encompassing 11 tumour types . We assess the relative rates and impact of the mutational burden at the binding sites of 81 transcription factors ( TFs ) , by comparing the abundance and patterns of single base substitutions within putatively functional binding sites to control sites with matched sequence composition . There is a strong ( 1 . 43-fold ) and significant excess of mutations at functional binding sites across TFs , and the mutations that accumulate in cancers are typically more disruptive than variants tolerated in extant human populations at the same sites . CTCF binding sites suffer an exceptionally high mutational load in cancer ( 3 . 31-fold excess ) relative to control sites , and we demonstrate for the first time that this effect is seen in essentially all cancer types with sufficient data . The sub-set of CTCF sites involved in higher order chromatin structures has the highest mutational burden , suggesting a widespread breakdown of chromatin organization . However , we find no evidence for selection driving these distinctive patterns of mutation . The mutational load at CTCF-binding sites is substantially determined by replication timing and the mutational signature of the tumor in question , suggesting that selectively neutral processes underlie the unusual mutation patterns . Pervasive hyper-mutation within transcription factor binding sites rewires the regulatory landscape of the cancer genome , but it is dominated by mutational processes rather than selection .
Most large-scale surveys of somatic mutation in cancer have focussed on protein-coding sequences , and catalogues of genes that carry recurrent mutations already number in the hundreds [1–3] , but it has long been speculated that driver mutations are likely to exist in the 98% of the genome sequence outside protein-coding exons [4] . The landscape of somatic mutation in cancer is complex , whole genome sequencing ( WGS ) data have revealed variable mutational spectra across cancers , some associated with particular mutagens , some with defects in DNA repair or replication fidelity , and others with unknown etiology [5] . In spite of this , cancers can be classified based upon the constellations of genomic , epigenomic and transcriptomic features they possess , indicating broad changes in regulation during tumour evolution [6] . Over the past decade , our view of transcriptional regulation in the human genome has changed radically as large consortia have profiled chromatin features across multiple cell types [7] , including extensive catalogues of active regulatory elements [8] . At the same time , new technologies have allowed the exploration of chromatin conformation within nuclei , revealing maps of three-dimensional nuclear architecture , e . g . Rao et al . [9] . The most recent studies of WGS data derived from tumours have made use of these new perspectives , studying patterns of recurrent mutations in putatively functional regulatory sites [10–12] . However , accurately detecting elevated rates of mutation at relatively small numbers of regulatory sites presents major challenges for analysis . Firstly , there are wide variations in the mutational spectra experienced by different cancer types and individual tumours [2] . Secondly , the success of searches for recurrently mutated genomic regions is heavily dependent upon the number of samples available , and even large studies have proved under-powered to detect known hotspots at regulatory loci [11] . Thirdly , the reliable detection of elevated mutation at particular sites requires careful comparisons with control sites , accounting for the features associated with the sites under scrutiny , such as nucleotide composition , fine scale chromatin accessibility and replication timing [11 , 13] . Some studies of mutation at regulatory sites have suffered from low sample sizes per cancer type but were still able to identify a number of recurrently mutated promoters [14] , for example the telomerase reverse transcriptase ( TERT ) gene in melanomas [15] . Predicting the functional impact of mutations occurring within noncoding regions also remains challenging . Studies of coding sequence variation in cancers have often sought evidence for variants subject to positive selection as a proxy for functional significance [3] . However , this is complicated by a widespread increase in functional ( nonsynonymous ) mutations , reflecting the relaxation of purifying selection in cancers relative to the germline [16] . Current strategies include the use of regions annotated as functional based upon ChIP-seq data that is restricted to a small fraction of DNA binding proteins [10] , and the use of regulatory compendia scores [11] . Robust measures of selection traditionally use comparisons of putatively functional and non-functional sites ( e . g . nonsynonymous and synonymous sites ) , but this has been lacking in studies of selection at regulatory sites in cancer . Here , we exploit the unprecedented volumes of data produced recently by cancer WGS projects [5 , 17] and examine the likely functional consequences of mutations at regulatory sites . We develop novel approaches to explore the strength and directionality of selection exercised at these sites , controlling for the mutational spectra seen across cancer types and the variation in mutation rates across the human genome . Significant enrichments of somatic mutations are evident at the binding sites of several transcription factors , particularly CTCF , pointing to elevated mutation rates or suppressed surveillance and repair . These enrichments disproportionately involve mutations predicted to weaken or abolish binding at functional regulatory sites , and we find little evidence for selection preserving binding sites in cancer . However , we discover mutational foci across cancers that are predicted to alter chromatin organisation , and intriguing differences emerge in the patterns and extent of regulatory disruption seen between cancer types .
We compiled a total of 9 , 958 , 580 somatic single base substitutions across 1 , 574 tumour samples from 11 different tumour types; consistent with previous studies [2 , 5] , there was a high degree of variation in substitution rates amongst tumour types ( Table 1 ) . DNase hypersensitive sites containing sequence-specific transcription factor ( TF ) binding motifs have previously been shown to closely match signals obtained from Chip-Seq data and can hence be used as a proxy for TF occupancy [18–20] . We established the genomic locations for constitutive DNase hypersensitive sites , active in most cell types , spanning a total of 3 . 92MB in the human reference genome ( see Methods section ) . Next , we scanned the genome for matches to 118 known binding motifs of 81 transcription factors , and those motif matches inside constitutive DNase regions were labeled as “putatively functional” TFBSs . We found a total of 197 , 374 functional TFBSs ( S1 Dataset ) , spanning 1 . 39MB of the genome and containing a total of 4 , 782 somatic mutations across the 11 cancer types ( Table 1 ) . For each motif matrix , we also compiled a list of control TFBSs , i . e . sequences that match a given TF binding motif , but are located outside any regions of open chromatin or genic regions , and are therefore unlikely to be bound , functionally active TFBSs ( see Methods section ) . For each matrix , we compiled the same number of functional and control TFBSs ( listed in S1 Dataset ) . The median distance between functional and control motifs was 10 . 6KB , with 90% of functional-control sites being less than 55KB apart . Functional motifs showed significantly higher conservation scores across 35 mammals than control motifs , consistent with their differing importance in biological fitness ( see Methods ) . Considering each TFBS matrix separately , the total number of mutations increased linearly with the length of sequence encompassed by the TFBSs as expected ( S1 Fig ) . This was also true for control TFBSs in cancer and for high frequency germline variants , i . e . 1000 Genomes Project ( 1KG ) polymorphisms at both functional and control TFBSs ( S1 Fig ) . However , in the combined dataset across cancer types , we found a marked genome-wide excess of somatic mutations at functional TFBSs . This excess was seen relative to control motifs and compared with 1KG polymorphism rates ( Fig 1A and 1B and S1 Table; χ2-test with Yate’s correction: χ2 = 298 . 2; p < 10−4 ) . Stratifying the data by the type of binding motif , the vast majority of TFBSs ( 78% , 92/118 matrices ) showed an excess of substitutions at functional binding sites compared to control sites ( Fig 2 ) , with 27 TFBSs showing significant enrichment for mutations ( Fisher’s exact test p < 0 . 05 ) , and none with significant depletion . Accordingly , putatively active TFBSs are common targets for mutations in cancer and , on average , these sites mutate at higher rates than inactive control sites . We also observed an increase of somatic mutations at functional TFBSs compared to the regions of open chromatin that they occur within: functional TFBSs mutated at significantly higher rates than constitutively open DNase regions ( S2 Fig; 0 . 00348 versus 0 . 00336 mutations bp-1; χ2 = 4 . 35 , p < 0 . 05 ) . This increase is seen in spite of the fact that constitutively DNase accessible regions suffered higher mutation rates than both the mappable portion of the genome as a whole ( 0 . 00321 mutations bp-1; S2 Fig; χ2 = 25 . 26 , p < 10−6 ) , and the ENCODE DNase master sites , which are regions that are accessible in any of the 125 ENCODE cell lines ( 0 . 00301 mutations bp-1; S2 Fig; χ2 = 152 . 89 , p < 10−15 ) . Thus , TFBSs within DNase regions suffer unusually high mutation rates , even relative to the generally elevated mutation rates seen at regions of accessible chromatin , consistent with a mutational cost of factor binding . To quantify the deleteriousness of somatic mutations in TFBSs , we calculated the reduction in the position weight matrix ( PWM ) score caused by a substitution [21] . Specifically , we calculated the PWM-score for each mutated binding site and compared this to the PWM-score for the reference sequence from the human genome build ( hg19 ) , i . e . we calculated the statistic PWM-score ( ALT/REF ) . On average , 1KG polymorphisms reduced the PWM-score to a greater extent at control sites than at functional TFBSs ( Fig 1C ) , as expected if purifying selection in extant human populations often acts to remove deleterious variants at functional sites . In stark contrast , the PWM-score ( ALT/REF ) values generated by somatic mutation in cancer are statistically indistinguishable between functional and control TFBSs ( Fig 1C ) , suggesting a widespread loss of selective constraint at these sites in cancer . Next , we calculated the ratio of the PWM-score ( ALT/REF ) in functional , relative to control binding sites for all 118 motifs in both cancer and 1KG; for 68 motifs , the reduction in the PWM-score was greater in cancer than in 1KG ( Fig 2 ) , with 4 motifs attaining statistical significance . Hence , in cancer , functional binding sites do not only acquire an excess of mutations , but the changes introduced by these mutations often lead to PWM-scores that are predicted to be more deleterious than substitutions tolerated as polymorphisms . Intriguingly , two TFBS motifs ( ZNF263 and NRF1 ) had significantly increased relative PWM-scores in cancer compared to 1KG ( S1 Dataset ) , suggesting binding is enhanced in cancers , and raising the possibility of adaptive evolution at these particular classes of binding sites in cancer . CTCF binding sites are among the most common TFBSs in the genome ( S1 Dataset ) , and we found the CTCF-motif to be recurrently mutated at position 9 across cancer types ( Fig 3A ) , a pattern that was previously seen in CTCF-TFBSs identified via Chip-exo of CTCF in a colorectal cell line [10] . Note that the majority of our constitutive CTCF-TFBSs ( 8 , 795 out of 10 , 763 ) overlap with those identified by Katainen et al . [10] . The distribution of mutations within functional CTCF TFBSs in our dataset was significantly different from that of 1KG polymorphisms ( Fisher’s exact test , p < 10−5; S2 Dataset ) , with the central nucleotide known to be constrained at the population level but highly mutated in cancer ( Fig 3A ) [10] . Most substitutions at position 9 of the CTCF-motif are T>G , T>C and T >A in cancer ( Fig 3A ) , and mutations away from T at this information-rich central motif position are expected to lead to reduced binding of CTCF [22] . Overall , we observe an exceptionally high mutational burden at functional CTCF binding sites in cancer ( 3 . 31-fold excess ) relative to control sites , and we demonstrate that this effect is seen across cancer types ( Fig 2 ) . This unusual accumulation of substitutions could conceivably be the result of selective processes or mutational bias during cancer evolution . In either case , the mechanisms that lead to a specific site of the motif being subject to high rates of substitution , remain elusive . We stratified our samples into five mutational spectra ( S3 Fig and S2 Table ) , based upon the genome-wide occurrence of substitutions in their trinucleotide context , consistent with previous studies ( see Methods ) . Since we subdivide the data into only five signatures , a one-to-one comparison with the 21 mutational signatures of Alexandrov et al . [5] is not possible . However , we observe a similar grouping of lung adenocarcinoma samples ( in mutational group 1 , characterized by C>A mutations; Alexandrov et al . ’s signatures 4 and 5 ) , and observe an overrepresentation of C>T changes across most cancer samples . Interestingly , the excess of T>G/C/A mutations at position 9 of the CTCF-motif was only seen in mutational spectra 3 and 5 ( S4 Fig ) , and it was strongest in spectrum 3 which also shows the strongest T>C signature . In contrast , tumours in spectrum 1 do not show the elevated substitution rate at position 9 . Similarly , the total number of mutations in functional motifs , relative to control motifs , is not elevated in spectrum group 1 , as it is for samples in spectra 2 , 3 and 5 ( S3 Table ) . Thus , the increase in mutation at CTCF binding sites is driven by mutations at position 9 , which is heavily mutated in particular subsets of samples with a common mutational signature and indicative of the dominant underlying mutational process . It has recently been shown that liver cancer is particular prone to asymmetries of A>G/T>C mutations in relation to the transcribed and untranscribed DNA strands [23] , and we observe a similar genome-wide trend for the liver cancer samples ( S4 Table ) here . A:T nucleotides were more prone to mutate to G:C when the ‘A’ nucleotide occurred on the non-transcribed strand and the ‘T’ was on the transcribed strand . Interestingly , the same trend was also seen for the subset of functional CTCF sites that fall into transcribed genomic regions , and these sites mutated at much higher rates than the genome wide average ( S4 Table ) ; this further supports the notion that mutations at CTCF-TFBSs follow genome-wide trends in mutational bias . CTCF has long been known to have important architectural roles in chromatin structure [24 , 25] . Rao et al . [9] found that CTCF binding sites delineate a hierarchy of chromatin loops ( indicating peaks of Hi-C contact frequencies ) , and regulatory domains ( median size 185KB ) that compartmentalize the genome into self-interacting units . The majority of points in the genome marking the beginnings and ends of chromatin loops ( loop anchor points ) are bound by CTCF , and are thought to link regulatory sites to target promoters . The majority ( 55–75% ) of loop anchor points are conserved across human cell types , and across mammals; many of these loops also demarcate the boundaries of self-interacting regulatory domains [9] . Using a sliding window approach , we found the number of functional CTCF motif instances to increase sharply at chromatin loop anchor points and domain boundaries ( Fig 4A and 4C ) . Functional CTCF motifs were strikingly prone to mutation if they were located within chromatin loop anchor points ( Fig 4B and S5 Table ) , with a similar ( though non-significant ) trend evident at domain boundaries ( Fig 4D ) , whereas there was no significant enrichment of mutated control motifs ( S5 Table ) . Further , position 9 of the CTCF-motif was more highly mutated when the binding site was located inside a loop anchor point . Inside loop anchor points , 204 out of 792 observed substitutions ( 26% ) were at position 9 of the motif , compared with 15% ( 83/539 ) in functional motifs outside loop anchors , despite the motifs having very similar sequence composition inside and outside loop anchor points ( S5 Fig ) . The mutation rate was approximately three-fold higher within CTCF sites within loop anchor points , compared to the rate observed within anchor points in general ( S2 Fig; χ2 = 1242 . 00 , p < 10−15 ) , supporting the idea that the CTCF-motif is a hotspot of mutation within this specific chromatin context . Given the limited numbers of mutations recorded in some tumour samples , we could not rigorously determine if CTCF motifs were highly mutated inside chromatin anchor loops across all tumour types . However , an excess of mutations inside loop anchor motifs was observed in all cancer types with a sufficiently high number of CTCF mutations , i . e . whenever the power to detect this difference in mutation rates at alpha = 0 . 05 was 80% or greater ( S6 Fig ) . Thus , CTCF sites involved in higher order chromatin structures appear to suffer the highest mutational burden , and chromatin organization may be affected by this increased mutational input across several cancer types . S6 Table lists the number of CTCF-mutations for each cancer type and shows that the highest mutation rates at functional CTCF sites per individual are suffered by liver and lung tumours , with substantial mutational loads also seen for breast , pancreas and lymphoma samples . In contrast , the relatively numerous ( Table 1 ) medulloblastoma and astrocytoma samples show orders of magnitude lower rates per individual , suggesting that different cancer types experience very different degrees of CTCF binding site disruption ( S6 Table ) . Using the GREAT tool [26] with default parameters , we tested for enrichments of functional annotations at genomic regions associated with mutated functional CTCF-sites . We found modest over-representation of certain functional categories , including biological processes associated with the regulation of cellular secretion , and several cancer-associated MSigDB entries , such as down-regulated genes predicting poor survival of patients with thyroid carcinoma ( S7 Table ) . We further explored the chromatin context of mutated TFBS instances , examining whether particular functional chromatin states were associated with the propensity of a particular TFBS to undergo mutation ( see Methods ) . Among the 118 TFBSs tested , the mutational load of only five TFBSs ( E2F1_MA0024 . 2; CTCF_MA0139 . 1 , CTCFL_MA0531 . 1; E2F4_MA0541 . 1 and YY1_MA0095 . 2 ) showed an uneven distribution among chromatin states ( Chi-Squared Test , p < 10−3 ) . In each case , there was an excess of mutations in insulator regions ( S3 Dataset ) . In particular , 16–17% of the CTCF functional binding sites allocated to the “insulator” chromatin state carried a mutation in at least one sample , whereas CTCF TFBSs in “promoter” , “enhancer” and “transcription” regions were mutated less often ( 5–10% of functional sites ) . This suggests that CTCF binding sites are particularly prone to mutation when they are involved in specific chromatin contexts . This appears to reflect variation in the rates of somatic mutation in DNAse hypersensitive sites in general , which was 0 . 0039 per base pair in accessible regions classified as “insulator” , but only 0 . 0032 in regions classified as “promoter” , “enhancer” and “transcription” ( χ2 = 128 . 61 , p < 10−15 ) . We used logistic regression to assess which genomic parameters were prominently associated with a high rate of substitution across the 118 TFBSs . Factors , which significantly affected the propensity of a binding site to undergo mutation in cancer , included replication timing , the identity of the TFBS matrix , the functionality ( i . e . DNase status ) of sites and whether sites were present at loop anchor positions ( S4 Dataset ) . Logistic regression analysis confirmed that functional binding sites consistently mutate more often than control sites , that the positioning within loop anchor points increases a binding site’s chance of mutation , and that different binding motifs mutate at distinct rates . In addition , late replication was significantly associated with higher rates of mutation in the regression model , consistent with a general role for replication timing in the nucleotide substitution rate [27 , 28] . In fact , when we correct for replication timing , the difference in mutation rates between CTCF motifs inside and outside chromatin loop anchor points diminishes ( S4 Dataset and S7 Fig ) . These CTCF binding sites might otherwise have been regarded as candidates for the apparent action of selection in cancer , given their specialized roles as well as the elevated frequencies and specific patterns of mutation observed . It is therefore striking that even for these sites mutational bias emerges as a convincing explanation for the patterns observed . Motivated by the patterns of site-specific mutation accumulation in CTCF , we investigated the pattern of substitutions on a per-site basis for all 118 TFBSs , but found few examples of selection acting to preserve motif integrity . For example , ZBTB33 , a regulator of the Wnt signaling pathway , binds to methylated 5'-CGCG-3' , and showed evidence for preservation of its target TFBSs in 1KG data ( Fig 3C ) . By contrast , in cancer , ZBTB33 binding sites were highly mutated at positions 5 and 8 , reflecting the high mutational input evident at ZBTB33 control motifs ( Fig 3C ) . The significantly elevated numbers of mutations at these motifs were accompanied by a reduced PWM-score for the ZBTB33 motif in cancer ( S1 Dataset ) . Examination of most TFBSs suggests a similar situation , but the USF1 binding motif ( MA0093 . 2 ) was a rare exception . Functional USF1 TFBSs showed a depletion of substitutions compared to flanking regions—in the 1KG polymorphism as well as the cancer dataset—but this depletion was absent at control sites ( Fig 3B ) . In addition , mutations at functional USF1 binding sites reduced the PWM-score to a much lesser degree than control sites in cancer ( Fig 2 and S1 Dataset ) . Due to the relatively modest number of mutations present at USF1 sites in the current data , the comparison with 1KG PWM-scores was not statistically significant , but these observations are consistent with motif preservation at USF1 binding sites in cancer . The complete dataset for each of the 118 matrixes , their controls sites , flanking regions and 1KG comparison , are provided in S7 Fig . We found no evidence that significantly mutated binding motifs are more likely to be bound by transcription factors which have been reported to suffer recurrent protein coding sequence mutations , i . e . genes that are found in the Cancer5000 gene set of Lawrence et al . [2] ( S8 Table; Fisher’s test N . S . ) . This suggests that mutations at TFBSs and those within coding regions have largely independent impacts on regulatory dysfunction in cancer . Further , we found little recurrence of mutations at individual functional binding sites: the most highly mutated positions inside motif instances were mutated in only five out of the 1 , 574 tumor samples each , at chr6:73122103 , chr2:49173806 and chr2:49173798 , affecting the binding motifs of CTCF/YY1 and CTCF/CTCFL , respectively . The chr6:73122103 site was also previously found to be mutated in 3 . 5% of colorectal cancer samples [10] . In contrast , the two most highly mutated sites across cancer genomes in protein coding sequence are a known mutational hotspot in codon 12 of the KRAS gene; these sites carried substitutions in 257 and 67 tumors , respectively . Thus , in contrast to coding sequences , where specific loci suffer detectably higher mutation rates , the mutational burden at regulatory sites requires a genome-wide perspective , encompassing many individual sites that belong to a given class of TFBS . In spite of the broad loss of constraint seen across TFBSs in cancer , it was possible to discern differences among cancer types , even with the limitations and caveats of the current data . We found that the particular binding motifs mutated in functional , relative to control sites and 1KG polymorphisms differed markedly over different cancer types ( Fig 5; complete dataset in S5 Dataset ) . Stratifying the data by cancer type reduces the mutation counts in each category , but suggests that lung adenoma tumours ( which also possess a distinctive mutational profile; S2 Table ) may accumulate more mutations at functional TFBSs compared to other cancer types , with the notable exception of CTCF binding sites . Within cancer types , we observe large variation in the numbers of mutations on a per-patient basis ( Fig 5 ) . The high rate of TFBS mutations in liver cancer is in part driven by a small number of outlier patients with exceptional biases to mutation in functional rather than control motifs ( Fig 5 ) . With larger cancer sequencing datasets it is likely that such variation among cancer types will become clearer , promising a new perspective on cancer genomics .
We have shown that functional regulatory elements suffer elevated rates of somatic mutations in cancer that based upon the accumulation of substitutions relative to matched control sites appear deleterious to regulatory protein binding . These striking patterns of mutation differ across TFBSs and cancers , and yet a high attrition of CTCF sites is a notably general feature . The unusual patterns of mutation seen at CTCF sites suggest widespread alterations to regulatory chromatin architectures across the genome , underpinned by strong mutational biases rather than selective processes . This raises the possibility that regulatory ‘driver’ mutations in cancers may arise as a byproduct of such biases superimposed upon a genome-wide relaxation of selective constraint at regulatory sites . The strongest impact of mutation on functional CTCF sites in the current data was observed in liver cancer samples , which showed the most dramatic increase in numbers of mutations observed ( S2 Table ) . We have shown that , by examining aggregated sites across the genome , it is possible to detect these patterns rigorously , while controlling for the influences of sequence composition and regional variation in mutation rates . However , it is important to note that these patterns will remain undiscovered by conventional approaches , most of which are based upon identifying individual genomic regions subject to recurrent mutations , and make it difficult to correct for compositional bias . This is exemplified by a recent publication describing the liver samples studied here , which assessed mutation rates within 500bp genomic windows , did not correct for compositional bias , and was therefore unable to detect the genome-wide increase in mutation rates at CTCF sites [29] . Regions of open chromatin have previously been shown to mutate at a decreased rate [13 , 28 , 30 , 31] , presumably as such regions are more accessible to the DNA repair machinery . However , these analyses were based on sections of large , often multi-megabase regions , rather than the short binding motifs , about 10-20bp in size , examined here . Michaelson et al . [32] found DNAse I sites often to be de novo mutated in the germline , especially when the applied window sizes were small , i . e . 10 or 100bp . Recent studies [10 , 33–35] have suggested possible mechanisms for increased mutation rates at TFBSs , including the perturbation of lagging-strand replication at strong binding sites , and differential accessibility of binding sites to the nucleotide excision repair machinery . An emerging theme here is that there may be a general mutational burden to regulatory function , where the action of sequence specific binding to DNA interferes with normal replication , damage , surveillance and repair processes . The breadth of effects we observe genome wide , across many transcription factors and tissues of origin , suggests that these are pervasive influences on the mutagenicity of the genome . As the net effect is one of increased mutation rate specifically at functional regulatory sites , it will be important in future studies to explore the mechanistic nature of these interactions and the relative importance of replication , repair and exogenous mutagenesis to the locally elevated mutation rates . We have shown that the mutation mediated decay of TFBSs can be observed across cancer types and binding motifs , and there appears to be no widespread purifying selection to counteract this . Among 118 motifs tested , not a single motif was significantly depleted for mutations at functional sites , relative to comparisons with control sites or population variation ( 1KG ) , suggesting that most binding sites for most known transcription factors are dispensable for tumor survival . Further , considering the per-site mutation rates within motifs , we often observe the same patterns of substitutions at control and functional sites , e . g . CpG mutations , suggesting that the accumulation of substitutions at TF binding sites is mostly driven by mutational rather than selection processes . Finally , the recurrence of mutations in functional TFBSs was two orders of magnitude lower than at sites of recurrent mutation in protein coding regions , consistent with the notion that no individual TF binding site in our dataset is likely to be a major driver of tumorigenesis . However , this does not mean that the aggregated , genome-wide impact of mutations across many TF binding sites is negligible . For example , the widespread disruption of CTCF-binding sites may have drastic consequences for the chromatin organisation and hence regulation of tumour gene expression [36] , and possibly for the stable transmission of DNA in subsequent cell divisions [37] . Cancers with a strong A:T>G:C mutational signature were particularly affected by CTCF binding site mutations , and such cancers may show higher degrees of regulatory instability . Consistent with our results a recent study showed that the disruption of chromatin boundary sites may activate proto-oncogenes in T-cell acute lymphoblastic leukemia , and observed a similar excess of mutations at CTCF sites [38] . Many previous studies ( e . g . [29] ) have used comparisons between binding sites and their flanking regions to assess the relative somatic mutation rates at such sites . Given the inevitable differences in sequence composition between binding sites and flanks , and the large literature supporting the role of compositional bias in mutation rates [2 , 11] , this is a challenging strategy . In addition , since TFBSs are highly clustered in the genome , the neighbouring regions of any given motif may also act as binding sites for other factors , potentially affecting flanking rates of mutation . Third , it has also recently been shown that immediately flanking regions per se may undergo increased rates of mutation [33] , which is consistent with the mutational input observed at CTCF TFBSs ( Fig 3 ) . In this study , we use a metric comparing the rates of mutation in functional versus control motifs of matched length and composition , circumventing biases introduced by differences in nucleotide sequence composition of the binding site or its flanks . Nevertheless , for comparison with prior studies in S1 Dataset , we compare the number of mutations in functional and control sites seen for each binding motif , relative to their 100bp flanking regions . One should note that our global analysis , in common with others to date , was limited by the heterogeneity of substitution rates across tumour types and by the numbers of mutations found within TF binding sites , which bounded the statistical power of our analyses; further , all p-values shown are uncorrected for multiple testing of 118 binding motifs . Thus , it was not always possible to meaningfully stratify results by mutational signature group or tissue of origin . Considering each tumour type separately , it appears that some cancer samples have a reduced proportion of mutations in functional motifs compared to control sites ( Fig 5 ) . However , the number of samples and/or the overall rate of mutation within these cancers are relatively low , which increases sampling bias . In our genome-wide pan-cancer analyses , the weaker patterns seen in these tumours is overridden by cancers such as lung adenoma and liver cancer , which show an excess of mutations at functional sites ( Table 1; Fig 5 ) . Thus , with additional cancer WGS data to explore , many new insights into the regulatory genomics of cancers should be possible .
To detect functional regulatory binding sites in the genome , we used a combination of computational prediction and experimental data: Position weight matrices for 118 transcription factor binding motifs ( 85 from ensemble Biomart at http://grch37 . ensembl . org/biomart/martview/9620562a1888b791f43eb69ee9adcaf0 and 33 additional motifs from Jaspar [39] at http://jaspar . genereg . net/ ) were used as input to FIMO ( of the MEME suite [40] ) , to find predicted motif matches in the genome . The maximum p-value for a motif match was set as the default ( p < 4 . 4e-05 ) ; if more than 300 , 000 motif instances were found , the motifs with the largest p-values were iteratively dropped . We intersected these motif matches with experimentally defined open chromatin regions: UCSC DNase master sites were downloaded from the UCSC genome browser ( http://genome . ucsc . edu/cgi-bin/hgTrackUi ? db=hg19&g=wgEncodeAwgDnaseMasterSites ) , and DNAse footprints came from Thurman et al . [8] , with footprints calculated as in Neph et al . [19] . In order to avoid the erroneous classification of binding sites as active in tumour tissue , we only considered putative binding sites in constitutively open chromatin , i . e . in UCSC chromatin regions that were DNAseI accessible in at least 113 out of 125 ENCODE cell types , or within DNAse footprints that were found in at least 39 out of 41 tissues . We conservatively limited our analysis to these putatively functional binding sites in constitutively DNAseI hypersensitive sites , and accordingly , expect a relative underrepresentation of tissue-specific binding sites in our dataset . The aim was to enrich our ‘functional’ sites for active TF binding relative to control sites . Note that , due to partial positional overlap of motifs , 44% ( 2 , 123 out of 4 , 782 ) of the somatic substitutions found within functional sites affected more than one TFBS , supporting the functional significance of these sites . As control motifs , we chose FIMO motif matches that were located outside open chromatin regions/DNAseI sites in any tissue of the ENCODE and Thurman datasets; in addition , control motifs had to be in the mappable regions of the genome ( i . e . outside DUKE and Dac excluded regions [41] ) and more than 2kb upstream of known genes . To minimize the difference in the mutation rate among functional and control TFBSs , we position matched each functional motif instance with a nearest control motif , choosing , for each functional TFBS , the closest motif from the pool of possible control sites . Functional and controls TFBSs both had high and comparable uniqueness scores ( S9 Table ) , suggesting that mutations can be detected in both regions . We note that the GERP conservation score [42] across whole genome alignments of 35 mammals ( http://genome . ucsc . edu/ ) is , on average , higher for functional TFBSs than for control motifs ( S9 Fig ) ; this is expected if functional motifs are under purifying selection , and has no impact on our analysis . Functional motifs match the input position weight matrices slightly better than control motifs , with median PWM-scores of 8 . 73 and 8 . 33 , respectively ( S9 Fig ) . However , since we measure the reduction in score relative to the reference allele , this should have negligible consequences for our analysis , and , consistent with this , the reduction in score is lower for functional TFBSs in the 1KG data , even though functional motifs start off with slightly higher scores ( see Results section ) . We downloaded whole genome mutation annotation format ( maf ) files for 11 tumour types from public data resources: 507 samples came from Alexandrov et al . [5] , and a further 1 , 067 non-embargoed samples ( free of all publication moratoria ) came from Release_17 of the ICGC [17] , including the projects LINC-JP , BRCA-UK , LIRI-JP , CLLE-ES , MALY-DE , PBCA-DE , EOPC-DE , PRAD-CA , PRAD-UK , PACA-AU , LICA-FR and PACA-CA . The maf files had previously been filtered for germline variants , i . e . they only included somatic mutations . 1KG polymorphism data ( vcf files ) were from EBI ( ftp://ftp . 1000genomes . ebi . ac . uk/vol1/ftp/release/20130502/ ) . Somatic point mutations and 1KG common SNPs with a frequency of >5% were intersected with our set of functional binding sites and control motif sites . PWM-scores [21] were calculated for each motif site that carried somatic substitutions or polymorphisms , and this score was compared to the reference allele , i . e . the motif instance in the human reference assembly ( hg19 ) . The relative reduction or increase in PWM-score for each binding site was calculated as PWM-score ( ALT ) / PWM-score ( REF ) , thereby controlling for variation in information content between motifs . To assess the impact of mutations in cancer with regards to the number of mutations per motif site and the predicted change in PWM-score , we divided the data into four separate categories: 1 ) somatic mutations at functional sites; 2 ) 1KG polymorphisms at functional sites; 3 ) somatic mutations at control sites; 4 ) 1KG polymorphisms at control sites . Variants with a frequency > 5% in the 1KG dataset may be neutral , advantageous or mildly deleterious , but are unlikely overall to be under strong purifying selection . Accordingly , the level of 1KG polymorphism at functional sites , relative to control sites for the same motif , gives an indication of the level of constraint for a given class of binding sites [43] and can be compared to the patterns of mutation seen in cancers . The significance of enrichment or depletion of mutations inside functional TFBSs in cancer was assessed using Fisher’s exact test for mutation counts in the four classes of sites: functional and control sites in cancer and 1KG , respectively . To assign a p-value to the reduction in the PWM-score , we used the methods of Price and Bonett [44] and calculated , for each binding motif , the confidence intervals for the ratios of median relative PWM-scores in cancer ( functional/control ) and 1KG ( functional/control ) separately , and assessed the extent to which they overlapped . Aggregate mutation/polymorphism counts were produced for each binding motif and sample; the shape of the distribution between cancer and 1KG samples ( visualized as barplots in S8 Fig ) was compared using Fisher’s exact test . Mutational spectra were calculated by counting the number of each of the 96 possible substitution types for each cancer sample , and dividing this vector by the expected number of substitutions , which was based on the trinucleotide count in the human reference sequence and assuming that a substitution from any nucleotide to any other is equally likely [5] . The Manhattan distance between each sample-specific mutational spectrum ( scaled to a total sum of one ) was calculated , with a dendrogram based on hierarchical clustering to relate samples . To avoid errors due to sampling of low mutation counts , the dendrogram shown in S3 Fig only included samples with at least 7000 mutations . Samples were allocated to five different spectra based on their clustering in the dendrogram . We divided CTCF-binding regions of the genome , which also overlap transcribed regions , into two groups , based on whether DNA is transcribed from the reference strand or its complement according to the ENSEMBL annotation of hg19 . A total of 44 , 072 and 40 , 507 basepairs overlap functional CTCF motifs and are transcribed from the reference and complement strands respectively , excluding sites that are transcribed bi-directionally . Next , we counted the number of A>G and T>C changes at CTCF sites in liver cancers; we assessed whether the reference “A” nucleotide was on the transcribed or the non-transcribed strand of DNA ( with its complement , “T” , being on the other strand ) , and calculated the strand bias of these mutation classes as in Haradhvala et al . [23] . We repeated the same procedure for all liver somatic mutations that fell into unidirectionally transcribed regions of the genome ( 612MB and 587MB of DNA for reference and complement strands respectively ) . Chromatin loop anchor positions and chromatin domain boundaries based on the Hi-C data of GM12878 ( the cell line with the highest resolution of 950bp from Rao et al . [9] ) were obtained from NCBI GEO ( Accession GSE63525 ) . Across domain boundaries and loop anchor points reported by Rao et al . [9] , we counted the number of somatic mutations and the number of CTCF motif instances . We do not have Hi-C data for the tumour samples in this study; however , to assess if an increase in mutations at CTCF-TFBSs inside loop anchor points is seen across different cell lines , we repeated the analysis with loop anchor points called in IMR90 , HMEC , NHEK , K562 , HUVEC , HeLa , and KBM7 cell lines [9] . ChromHMM tracks [45] were downloaded from the UCSC Genome Bioinformatics site ( http://genome . ucsc . edu/ ) for GM12878 , H1-hESC and K562 cell lines . These datasets were intersected with the genomic location of all functional motifs , classifying each motif into falling into one of six chromatin “colors” , i . e . “promoter” ( red ) , “enhancer” ( yellow ) , “insulator” ( blue ) , “transcription” ( green ) , “repressed” ( grey ) and “low signal” ( white ) . For each Matrix , we counted the number of mutated and intact functional binding sites , using a Chi-Squared test to assess if different chromatin states showed different propensities for mutation . A logistic regression model was constructed , modeling the binary outcome variable “mutated/not mutated” in the combined cancer dataset; this variable describes if a given binding site at a particular genomic location is mutated in any of the cancer samples . As predictor variables , we used the replication timing data of Chen et al . [46] , “Matrix” as a factor with 118 different levels representing the different TFBS motifs included , a binary “Functionality” ( i . e . functional vs . control ) variable and the binary classifier of whether the binding motif was inside or outside a chromatin loop anchor point [9] . The Wald test was used to test for the significance of individual predictor variables within the model . The fraction of predicted mutated motif positions was calculated for each functional matrix inside or outside loop anchors respectively , keeping replication time constant .
|
Regulatory regions of the genome are important players in cancer initiation and progression . Here , we study the patterns of mutations accumulating at short DNA segments bound by regulatory proteins ( transcription factor binding sites ) across many cancer types and in the human population . We find strikingly high rates of mutation at active regulatory sites across different cancers , relative to matched control sequences . This excess of mutations disrupts the binding sites of particular factors , such as CTCF , and is likely to be driven by selectively neutral processes , such as the replication timing of the genomic regions concerned . However , binding sites involved in regulatory chromatin structures suffer particularly high levels of mutation , suggesting the frequent disruption of such structures in cancers .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cancer",
"genomics",
"sequencing",
"techniques",
"medicine",
"and",
"health",
"sciences",
"basic",
"cancer",
"research",
"oncology",
"substitution",
"mutation",
"mutation",
"sequence",
"motif",
"analysis",
"epigenetics",
"molecular",
"biology",
"techniques",
"chromatin",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"chromosome",
"biology",
"gene",
"expression",
"molecular",
"biology",
"somatic",
"mutation",
"point",
"mutation",
"cell",
"biology",
"gene",
"identification",
"and",
"analysis",
"genetics",
"mutation",
"detection",
"biology",
"and",
"life",
"sciences",
"genomics",
"genomic",
"medicine"
] |
2016
|
Mutational Biases Drive Elevated Rates of Substitution at Regulatory Sites across Cancer Types
|
In Arabidopsis , micro ( mi ) RNAs and trans-acting ( ta-si ) RNAs synthesized directly or indirectly through the DICER-LIKE-1 ( DCL1 ) ribonuclease have roles in patterning and hormonal responses , while DCL2 , 3 , 4-dependent small-interfering ( si ) RNAs are mainly involved in silencing of transposable elements and antiviral defense . Viral suppressors of RNA silencing ( VSRs ) produced by phytoviruses to counter plant defense may perturb plant developmental programs because of the collision of their inhibitory effects with the regulatory action of endogenous miRNAs and ta-siRNAs . This could explain the similar developmental aberrations displayed by Arabidopsis miRNA/ta-siRNA pathway mutants , including dcl1 , and by some VSR-expressing plants . Nonetheless , the molecular bases for these morphological aberrations have remained mysterious , and their contribution to viral disease symptoms/virulence unexplored . The extent of VSR inhibitory actions to other types of endogenous small RNAs remains also unclear . Here , we present an in-depth analysis of transgenic Arabidopsis expressing constitutively HcPro , P19 and P15 , three unrelated VSRs . We show that VSR expression has comparable , yet modest effects on known miRNA and ta-siRNA target RNA levels , similar to those observed using an hypomorphic dcl1 mutation . However , by combining results of transcriptome studies with deep-sequencing data from immuno-precipitated small RNAs , additional , novel endogenous targets of miRNA and ta-siRNA were identified , unraveling an unsuspected complexity in the origin and scope-of-action of these molecules . Other stringent analyses pinpointed misregulation of the miR167 target AUXIN RESPONSE FACTOR 8 ( ARF8 ) as a major cause for the developmental aberrations exhibited by VSR transgenic plants , but also for the phenotypes induced during normal viral infection caused by the HcPro-encoding Turnip mosaic virus ( TuMV ) . Neither RNA silencing , its suppression by VSRs , nor the virulence/accumulation of TuMV was altered by mutations in ARF8 . These findings have important implications for our understanding of viral disease symptoms and small RNA-directed regulation of plant growth/development .
RNA silencing in Arabidopsis entails the activities of four distinct paralogs of the RNaseIII Dicer , producing small RNAs with specialized functions [1] . DICER-LIKE 1 ( DCL1 ) predominantly synthesizes microRNAs ( miRNAs ) , 19-to-24-nucleotide ( nt ) in length , from non-coding primary transcripts called pri-miRNAs containing imperfect stem–loop structures . Stepwise nuclear pri-miRNA processing produces mature miRNAs that are then 2′-O methylated by HUA ENHANCER 1 ( HEN1 ) and exported to the cytoplasm [2] , [3] . One miRNA strand is stabilized in an RNA-induced silencing complex ( RISC ) containing , chiefly , the ARGONAUTE 1 ( AGO1 ) silencing effector protein , whereas the passenger miRNA strand , or miRNA* , is degraded . The miRNA-loaded AGO1 then guides post-transcriptional gene silencing ( PTGS ) of complementary or partially complementary mRNAs by inhibiting their stability and/or translation [4] . Hypomorphic mutations in DCL1 , HEN1 or AGO1 cause severe developmental abnormalities , highlighting the important role for miRNAs in plant development . Accordingly , many miRNA targets are mRNAs encoding transcription factors required for patterning , control of cell identity and elongation , including transcripts for AUXIN RESPONSE FACTORs ( ARFs ) , which modulate plant responses to the hormone auxin [5] . Nonetheless , other classes of miRNAs regulate non-developmental processes including basal metabolism and plant adaptation to biotic or abiotic stress [4] . Unlike miRNAs , populations of cis-acting , 24nt-long siRNAs produced by DCL3 direct cytosine methylation and other chromatin modifications at the endogenous loci that generate them , including transposable elements , DNA repeats , and complex gene arrays [6] . DCL4 generates 21nt-long siRNA populations that guide PTGS of endogenous transcripts , including trans-acting siRNAs ( ta-siRNAs ) , the biogenesis of which is initiated by miRNA-directed cleavage of specific , often non-coding precursor transcripts . This promotes complementary strand synthesis mediated by the RNA-DEPENDENT RNA POLYMERASE RDR6 that generates long dsRNA processed by DCL4 [7] , [8] . The ta-siRNAs then guide AGO1 to repress target mRNAs including those of ARF3 and ARF4 , which are important determinants of leaf development during post-embryonic growth [9] , [10] . Other classes of endogenous siRNAs are similarly loaded into AGO1 , presumably also to direct endogenous PTGS . These include DCL4-dependent , 21nt-long , and DCL2-dependent , 22nt-long , siRNA populations that are produced from small hairpins or extensively base-paired RNA formed upon transcription of inverted-repeat ( IR ) loci . These hairpin and IR loci may also attract DCL3 activity , leading to the accumulation of corresponding 24nt-long siRNAs [11] . DCL4 , and to a lesser extent DCL2 and DCL3 , additionally has a key role in antiviral defense by dicing dsRNA produced during replication of phytovirus genomes ( reviewed in [12] ) . The resulting siRNAs are methylated by HEN1 and incorporated into one or several AGO proteins directing PTGS of viral RNA as part of antiviral RISCs . AGO1 and AGO7 are good candidates as antiviral RISC effectors because hypomorphic ago1 and null ago7 mutants are hyper-susceptible to several viruses [13] , [14] . As expected from the never-ending molecular arms race that characterizes nearly all host-parasite interactions , phytoviruses have evolved a vast array of proteins , called viral suppressors of RNA silencing ( VSRs ) , in order to multiply and invade plants systemically [12] . Studies in transgenic plants expressing RNAi constructs ( as a surrogate to virus infection ) have shown that VSRs may target many steps of antiviral silencing , including small RNA processing , stability and activity via AGO effectors ( reviewed in [15] ) . For instance , homo-dimers of the tombusviral P19 protein sequester viral- or hairpin-derived siRNA duplexes in a size-dependent manner to prevent their effective loading into antiviral RISCs [16] . Many antiviral silencing factors are components of cellular pathways regulating host gene expression , including , and of note , HEN1 , which methylates and protects all endogenous classes of small RNAs , as well as AGO1 and AGO7 , effectors of miRNAs , ta-siRNAs and IR-derived siRNAs . Consequently , some VSRs are expected to interfere with endogenous silencing pathways as part of their counter-defensive action and , thus , to perturb plant developmental programs . This hypothesis has been supported by various studies of Arabidopsis plants expressing constitutively distinct types of VSRs: in many cases , such plants display morphological abnormalities in leaves and inflorescences , reduced stature and fertility reminiscent of defects exhibited by hypomorphic miRNA mutants [17] , [18] , [19] . Furthermore , transgenic plants expressing VSRs show alterations of ta-siRNA/miRNA and ta-siRNA/miRNA target levels . For instance , P19 sequesters and thereby stabilizes host miRNAs/miRNA* duplexes , preventing the activity of the mature miRNA strand [18] . Other transgenically expressed VSRs , such as the potyviral HcPro , cause a consistent elevation in mature miRNA steady state levels , possibly as a consequence of perturbed HEN1 activity [17] , [18] , [19] . Arabidopsis plants stably expressing the P15 protein of pecluviruses , by contrast , do not display altered mature miRNA levels , but , like HcPro and P19 transgenics , they accumulate ectopically miRNA and ta-siRNA target transcripts , suggesting a general perturbation in miRNA-RISC activity [18] . The above and other studies have prompted the popular assumption that the developmental phenotype of VSR transgenic plants is an unintended consequence of the primary inhibition of the antiviral silencing machinery at some steps colliding with the host miRNA/ta-siRNA pathways . This assumption , however , may be only partly true because it assumes that the miRNA pathway does not contribute actively to antiviral defense , and that , as a corollary , plant viruses do not rewire endogenous silencing pathways in order to thrive in their hosts . However , miRNAs and other cellular small RNAs have recently emerged as key regulators of Arabidopsis basal and race-specific resistance against many pathogens , including viruses ( reviewed in [12] , [20] ) . Therefore , inhibition of endogenous small RNA pathways by VSRs might also reflect a deliberate viral strategy to inhibit such immune systems . By extension , it could be argued that the onset of developmental or hormonal defects as a consequence of suppressed miRNA or endogenous siRNA activities might optimize the replication and spread of at least some viruses . Conversely , suppression of endogenous silencing pathways may be inconsequential to other virus types , and this may explain why some VSRs have narrower impacts in transgenic Arabidopsis , merely inhibiting RNAi and antiviral defense . For instance , the P6 protein of Caulimoviridae targets the DCL4-interacting protein DRB4 during siRNA biogenesis , without noticeable incidence on miRNA regulation in transgenic plants [21] . A related issue is whether the inhibition ( targeted or fortuitous ) of endogenous small RNA functions observed with certain VSR transgenes recapitulates some of the disease symptoms normally elicited by viruses during authentic infections . Indeed , those studies have mostly involved , so far , constitutive or inducible VSR expression in a much broader tissue range than is expected from natural infections ( discussed in [12] , [22] ) . An additional question pertains to the exact molecular underpinnings of the morphological abnormalities induced by transgenic expression of P19 , HcPro , P15 or other VSRs in Arabidopsis . The broad ectopic accumulation of miRNA targets seen in those plants would intuitively argue in favor of pleitropy owing to many compromised regulatory and developmental pathways . This idea is challenged , however , by the surprising recurrence and discrete nature of the observed defects , independent of the VSR under study ( though their strength may vary depending on VSR expression levels ) . Hence , rosette leaves are invariably narrow , serrated and curled , the rosette diameter and leaf area are reduced , as are the weight of total aerial tissue and the length of primary bolts . P19 , HcPro and P15 plants also display inflorescences with typically narrow and unusually long sepals; organs within internal whorls are usually exposed prior to opening , and flowers fail to release pollen , resulting in male sterility [17] , [18] , [19] . These recurrent and discrete anomalies thus suggest that misregulation of only a discrete number of endogenous genes accounts for the VSR phenotype . The identity of these targets remains unknown , however , as does the nature of the possible endogenous small RNA pathway ( s ) ( i . e . miRNA , ta-siRNA , endogenous IR-derived siRNAs ) involved . Moreover , although an effect of VSRs at the level of AGO action is usually invoked to unify these observations , additional actions of VSRs on chromatin or primary miRNA/ta-siRNA transcription have never been formally ruled out . For instance , histone acetylation/deacetylation was recently identified as a broad-spectrum chromatin-based mechanism regulating miRNA production in Arabidopsis [23] . This overall lack of understanding of the VSR effects in transgenic settings has limited the use of these factors as tools for the identification of potentially novel endogenous small RNAs and their associated targets , both in Arabidopsis and other plant species . It was indeed anticipated that VSRs could be possibly used as weak alleles of RNA silencing mutations , but with a broader output because of the likely simultaneous interference of these factors with multiple endogenous silencing pathways [24] . Through a systematic , comparative analysis of Arabidopsis lines over-expressing the tombusviral P19 , potyviral HcPro or pecluviral P15 VSRs , the present study addresses many of the outstanding issues raised above . This analysis notably uncovers the as yet unexplained molecular feature that underlies the post-embryonic developmental phenotype exhibited in common by the three VSR transgenic plants . Moreover , this study establishes that the same molecular bases account for the developmental , but not metabolic , symptoms normally elicited by an authentic virus infection . Finally , our work demonstrates that virus-induced developmental aberrations , on the one hand , and pathogen virulence as a consequence of antiviral silencing suppression , on the other , can be uncoupled . These findings not only shed light on hitherto unsolved issues of viral diseases , but they also challenge current views on the roles and impact of endogenous small RNAs on plant growth and development .
The systematic analysis reported in this study involved previously characterized Arabidopsis lines expressing the potyviral HcPro , tombusviral P19 and pecluviral P15 VSRs under the constitutive 35S promoter from Cauliflower mosaic virus [18 , material and method] . These lines contain an additional transgene encoding an RNAi inverted-duplication of the CHALCONE SYNTHASE gene ( CHS ) , which prevents pigmentation of the seed coat . The VSR transgenics , by contrast , have a brown seed coat owing to RNAi suppression [18] . We first investigated the possibility that VSRs could affect chromatin-level silencing of repeat elements mediated by small RNAs , or accumulation of known primary miRNA transcripts ( pri-miRNAs ) . To this end , transcript levels and two histone modifications were analyzed along the Arabidopsis chromosome 4 using a custom-made tiling array ( GSE24692; [25] ) . One percent or less of the 21000 probes on the tiling array reported statistically significant differences in transcript accumulation in leaves or inflorescences between WT plants and VSR transgenic plants ( Figure S1 ) . Likewise , histone marks were largely unaffected by VSR expression indicating that these proteins interfere with RNA silencing at the post-transcriptional level , consistent with previous studies showing that none of the three VSRs prevent accumulation of mature miRNAs [17] , [18] , [19] . We conclude that these factors likely interfere with Arabidopsis silencing pathways downstream of Dicer , presumably by inhibiting RISC-mediated repression of target transcripts , which may occur , at least partly , at the mRNA stability level . Consequently , we decided to analyze the changes in mRNA accumulation observed between WT and VSR-expressing plants , using a microarray approach ( Data deposited at the Gene Expression Omnibus [GEO] , accession GSE24693 ) . In order to define a threshold value for such changes , we first examined , in inflorescences , stems , leaves and roots of the VSR transgenic plants , the average expression changes of all known Arabidopsis miRNA and ta-siRNA target transcripts , as available in the miRbase ( http://www . mirbase . org ) and ASRP ( http://asrp . cgrb . oregonstate . edu; [26] ) depositories . We found that more than 90% of all known miRNA and tasiRNA target transcripts did not differentially accumulate in WT versus VSR plants: their accumulation was within the 0 . 8–1 . 2 fold range in all four organs of the VSR transgenic plants ( Figure S2 ) . A similar value was obtained upon analysis of dcl1-9 plants , which display vastly reduced miRNA levels ( Figure S2 ) . Strikingly , in leaves , only 30% of all target transcripts were found to over-accumulate in at least one VSR transgenic line , as compared to WT plants , and this figure was reduced to 11% in the dcl1-9 mutant ( Figure S3; results for the other organs are presented in Figure S4A-S6A ) . Moreover , for those over-accumulating target mRNAs , expression changes were mostly in the 1 . 5-2 fold range ( Figure 1A; Figure S4B-S6B ) . These results are in line with those of two separate microarray studies involving additional alleles of the dcl1 mutation in at least two distinct Arabidopsis ecotypes [27] , [28] . We conclude that expression of P19 , P15 or HcPro , like the dcl1-9 mutation , incurs only modest changes to the accumulation of some miRNA and ta-siRNA target transcripts . We further propose from this analysis that variations in gene expression above the 1 . 5 fold threshold can be ascribed to putative effects of VSRs interfering with endogenous PTGS pathways . Beside their effect on ta-siRNA and miRNA activities , VSRs might also compromise the action of additional species of AGO1-bound small RNA , including endogenous siRNAs , natural antisense ( nat- ) or long siRNAs [29] , or even heterochromatic small RNAs , and this may contribute to the developmental phenotype displayed by HcPro , P15 and P19 transgenic plants . To investigate this aspect exhaustively and in an unbiased manner , we exploited available small RNA deep-sequencing data from AGO1-immno-precipitates ( IPs ) obtained from a mixture of Arabidopsis tissues including those investigated in the present study [30] . In each organ , we selected mRNA ( i ) displaying ≥1 . 5 fold expression changes compared to WT in at least one of the three VSR lines and ( ii ) exhibiting high complementarity ( not more than three authorized mispairs ) to one or more AGO1-loaded small RNA ( Figure 1B , step 1-2 ) . We found that more than half of the transcripts that are up-regulated in at least one VSR have at least one matching AGO1-IP small RNA in the various organs analyzed ( Figure 1C ) . This approach was further refined by taking into account the number of unique small RNA reads from AGO1-IP deep-sequencing data ( [30]; Figure 1B , step 2–3 ) . Based on an analysis of all AGO1-loaded sRNAs mapped on all their predicted targets , a conservative threshold of ≥20 AGO1 reads was chosen in order to identify small RNAs that might reliably engage the transcripts identified in step 1–2 into regulatory interactions ( Figure S7 ) . Some of the results of this refined study are presented in Figure 2 , 3 and Figure S8 ( showing mostly small RNAs mapping to unique genomic regions ) and were all validated by two independent qRT-PCR analyses of RNA extracted from the VSR transgenic versus WT tissues ( Table S1 ) . The reader is referred to Table S2 and Text S1 for the complete list of putative target transcripts , their matching small RNAs , and corresponding AGO1-IP read values . This analysis notably uncovered that VSR expression enhances the accumulation of several potential trans-targets of AGO1-bound siRNAs , 21–22nt in size , that originate from long dsRNA formed upon transcription of inverted gene-duplications ( i . e . IRs ) . Although IRs are commonly detected along the Arabidopsis genome and frequently associated to siRNA production [31] , their targets ( if any ) are difficult to identify because of the shear amount and diversity of siRNAs generated at these loci . Figure 2A shows , for instance , that VSR expression elevates the levels of a putative target ( At1g12320 , encoding an unknown protein ) of a 21nt-long siRNA mapping to IR5334 , which is on chromosome 3 and produces heterogeneous populations of 21nt , 22nt and 24nt siRNAs . Similar findings were made for At4g08390 ( encoding a stromal ascorbate peroxidase; Figure 2B ) , a putative target of a 20nt siRNA derived from the >7kb-long IR71 ( Chromosome 3 ) , and for At4g28490 ( encoding a receptor-like protein kinase 5 precursor ) , which is likely regulated by a 21nt siRNA derived from IR6735 ( Figure 2C–D ) . The analysis also revealed that VSR expression enhances the accumulation of a putative novel target of a TAS3-derived small RNAs ( At2g38120 , Figure 3E ) . TAS loci typically produce populations of phased , 21nt-long siRNAs that are loaded into AGO1 , many of which have as yet unidentified functions . Figure 3A–B illustrates additional striking cases in which VSRs cause increased accumulation of transcripts that are likely regulated via miRNA* strands upon their efficient loading into AGO1 . This is the case of the MADS box gene SHATTERPROOF 1 ( SHP1 ) , involved notably in seed dispersal through regulation of valve dehiscence and also lateral root initiation [32] , [33] . The SHP1 open-reading frame displays near-perfect complementarity to miR159b* , which is nearly as abundant as miR159b itself ( Figure 3A ) . Similarly , VSR transgenic plants displayed elevated levels of the At2g47020 transcript , which is antisense and , therefore , perfectly complementary to miR408* ( Figure 3B ) . This configuration likely allows cis regulation of At2g47020 expression by miR408* , reminiscent of several natural-antisense transcripts/miRNA pairs that have been documented in rice [34] , but , as yet , not in Arabidopsis . Consistent with regulatory roles for both miR159b* and miR408* and with their interference by VSR expression , SHP1 and At2g47020 levels were similarly up-regulated in corresponding organs of dcl1-9 mutant plants ( http://urgv . evry . inra . fr/CATdb/; Project: GEN-107 ) . The sulphate transporter mRNA At5g13550 was also up-regulated in VSR transgenic plants ( Figure 3C ) and was identified as a likely target of miR843 , an Arabidopsis-specific miRNA with previously unassigned targets or functions . These and additional examples presented in Figure S8 show that VSR expression interferes with AGO1-dependent regulatory functions that extend beyond conventional miRNA-mediated repression and may involve a large variety of endogenous small RNA species including possible trans-acting siRNAs derived from repeats and transposable elements . Consequently , applying the microarray/AGO1-IP approach to individual VSR lines could not singularize alterations to one specific RNA silencing pathway , which could have shed light on the developmental phenotype shared by P15 , HcPro and P19 transgenic plants . We thus sought to design an alternative method to address this issue independently of AGO1-IP small RNA read values . We reasoned that the recurrent phenotypic abnormalities observed in VSR plants are mostly manifested in leaves and , therefore , likely accounted for by the ectopic expression of one or several silencing-regulated genes up-regulated in common in the three VSR lines . Based on this hypothesis , we found that only a subset of 20 transcripts had this stringent attribute in VSR leaves ( Figure 4A , diagram; Table S3 ) , among which approximately half were involved in basic metabolism or enzymatic processes that were unlikely to account for the leaf developmental phenotype ( Table S3 ) . Among the remaining nine candidate transcripts , six were direct or indirect targets of known miRNAs ( Figure 4A , table ) , of which four were also up-regulated in leaves of the dcl1-9 mutant plants . Given the importance of miRNAs in plant development , we decided to focus on this subset of candidates , which was further refined using a final filter based on organ-specific analyses of the hen1-1 mutant ( Figure 4A , table ) . Because HEN1 methylates and thereby protects all plant small RNA classes from degradation , hen1 mutants accumulate miRNAs to low levels [3] . Applying the same procedure to the other organs of VSR transgenic plants ( Table S4 ) identified gene sets that , as in leaves , were enriched for transcripts targeted by the miR398 family , involved in copper/zinc homeostasis , and for mRNAs encoding the Auxin response factors ARF8 ( targeted by miR167; [35] ) , ARF4 and ARF3/ETTIN ( both targeted by miR390-dependent TAS3; [9] , [10] ) . Based on the role of auxin in plant organogenesis [36] , the three ARFs ectopically accumulating in the VSR lines were further investigated . We reasoned that a key contribution of those factors to the developmental defects of VSR lines would be diagnosed by an attenuation of the phenotype following introgression of either the arf8 , arf4 or arf3 mutations . In other words , it was predicted that some of the above mutations would act as general , second-site suppressors of the VSR phenotype . As for most miRNA target genes ( Figure 1A ) , expression changes for ARF8 and ARF4 were within the 1 . 5–2 fold range in the leaves of the three VSR lines , while those of ARF3 were below the 1 . 5 fold threshold in leaves of P15 and HcPro plants ( Figure S9A ) . It was thus anticipated that the effects of mutations in at least arf8 or arf4 would be possibly manifested in the heterozygous state . Analysis of F1 progenies from the respective crosses to VSRs ( in the CHS RNAi background ) did not reveal any effect of the arf4–2 or arf3–2 heterozygous mutations ( Figure S9B-D and data not shown ) . VSR transgenic plants with the heterozygous arf8–6 background [37] , by contrast , displayed dramatically attenuated developmental defects ( Figure 4B , 4D and 4F ) , which could not be attributed to changes in expression levels of the cognate silencing suppressor mRNAs as compared to those found in the parental VSR lines ( Figure 4C , 4E and 4G ) . In addition , as expected , ARF8 expression levels were reduced in these F1 heterozygous mutant plants ( Figure S9E and data not shown ) . This arf8-dependent phenotype attenuation was not only observed in leaves , but also in inflorescences ( Figure 4B ) such that fertility of all three VSR lines was restored to near WT levels . While those VSRs with initially strong phenotypes in parental lines ( HcPro and P19 ) still exhibited a low degree of leaf serration in the arf8–6 heterozygous background ( Figure 4B , 4F , arrows ) , they were essentially undistinguishable from WT plants when the arf8–6 mutation was brought to homozygocity , as exemplified with the independently genotyped [P19 x arf8–6-/-] plants presented in Figure 4H–I . All these effects were highly specific for arf8 because they were not observed with mutations in ARF6 , a close paralog of ARF8 also regulated by miR167 , which has been implicated in similar developmental processes ( Figure S9C–D ) . We conclude that heterozygous or homozygous arf8 is sufficient to respectively attenuate or abolish the developmental defects caused by the three VSRs , strongly suggesting that all these defects have a sole and common ARF8-dependent origin . A possible cause of the effects of arf8 on the VSR phenotype is that ARF8 might itself influence small RNA biogenesis or activity . We ruled out this possibility , however , for three reasons . First , the protein levels of the miRNA-processing enzyme DCL1 were not changed dramatically in arf8–6-/- mutant as compared to WT plants , as were the levels of AGO1 , the main effector of miRNA and siRNA actions ( Figure 5A ) . Likewise , inspection of available transcriptome data for arf8–3-/- arf6–2-/- double mutant plants did not reveal any significant changes in the transcript levels of major PTGS effector proteins and endogenous suppressors of silencing , as compared to WT plants , with the notable exception of AGO7 ( Table S5 ) . Second , accumulation of a variety of miRNAs -including miR162 and miR168 regulating , respectively , the levels of AGO1 and DCL1 transcripts- was nearly the same in arf8–6-/- mutant plants as it was in WT plants ( Figure 5B ) . Third , accumulation of the endogenous targets of those miRNAs was largely unaffected in arf8–6-/- mutant compared to WT plants ( Figure 5C ) . Using crosses to the CHS RNAi line [18] , we also confirmed that the arf8–6 mutation did not affect PTGS mediated by siRNAs derived from long dsRNA , as the seed coat of all progeny plants remained pale , an indicator of CHS silencing ( Figure 5D; [18] ) . Suppression of CHS RNAi , manifested as brown seed coats , was , however , still observed in the VSR lines with the arf8–6 heterozygous mutation , which nonetheless exhibited strongly attenuated developmental phenotypes ( Figure 4B , 4D and 4F; Figure 5E ) . Moreover , the known effects of VSRs on CHS siRNA and endogenous miRNA accumulation were still observed in those crosses: as expected , both P15 and HcPro caused a strong reduction in 21nt CHS siRNA levels , while these remained unaffected by P19 ( Figure 5E ) . Also as reported previously [18] , HcPro and P19 ( but not P15 ) caused respectively an increased accumulation and a slight mobility shift of endogenous miRNAs ( Figure 5E ) . qRT-PCR analyses confirmed , additionally , that VSRs in both the heterozygous and homozygous arf8–6 mutant background still displayed enhanced accumulation ( a 1 . 5–2 fold range on average ) of several miRNA target transcripts , as observed in the parental VSR lines ( Figure 5F and data not shown ) . We conclude that suppression of developmental defects by the arf8–6 mutation in the VSR transgenic plants is merely accounted for by the correction of ARF8 transcript levels , independently of any other effects on RNA silencing . Therefore , ectopic ARF8 accumulation , diagnosed by a ∼2 fold elevation in transcript levels , is responsible for many of the severe developmental anomalies exhibited by the VSR transgenic plants . As a further test of the specificity of the arf8 effects , we used transgenic plants expressing the P6 VSR from Cauliflower mosaic virus ( CaMV ) . We previously showed that , unlike HcPro , P15 and P19 , the P6 protein does not compromise the miRNA pathway in Arabidopsis but targets the nuclear dsRNA-binding protein DRB4 , an accessory factor of DCL4 , the main dicer required for RNAi and antiviral defense [21] . Nonetheless , P6 transgenic plants exhibit developmental ( i . e . dwarfism , pointy leaves ) as well as metabolic ( i . e . chlorotic sectors ) anomalies that do not overlap with those of HcPro , P19 or P15 plants ( Figure 6A ) . We used an arf8–4 null mutation in the Ler ecotype and analyzed the phenotype of progenies from crosses to the P6 reference transgenic line , also in the Ler ecotype . We found that expression of P6 was unchanged in the crosses compared to the parental lines , as were the developmental anomalies incurred by P6 , suggesting that arf8 only suppresses those developmental phenotypes that are caused by VSRs targeting miRNA pathway components ( Figure 6A–B ) . As a final proof of the biological relevance of ARF8 during compromised miRNA-directed gene regulation , we used Turnip mosaic virus ( TuMV ) , which unlike tombusviruses ( producing P19 ) or pecluviruses ( producing P15 ) is known to infect Arabidopsis . TuMV is the potyvirus that naturally encodes the HcPro allele expressed in the VSR transgenic plants employed in the present study . We and others have previously shown that in addition to chlorosis , TuMV infection causes leaf serration and defects in flower architecture highly reminiscent of those found in stable transgenic HcPro plants [18] , [19] . Such morphological changes are , in fact , commonly associated to phytovirus infections but their molecular bases have remained poorly understood . Based on the results implicating ARF8 ectopic expression as a major cause for this phenotype in the VSR lines , we predicted that arf8–6-/- plants would sustain normal TuMV infection but would fail to display the developmental anomalies normally associated to the disease . The results of several independent infections were consistent with this prediction: while infected arf8–6-/- plants remained as chlorotic and accumulated as much TuMV RNA as WT plants , leaf serration was hardly discernable ( Figure 6C–D ) . We conclude that ARF8 ectopic accumulation , presumably as a result of HcPro-mediated suppression of miR167 underlies most , if not all , of the developmental symptoms associated to the authentic TuMV infection .
The present analysis indicates that up-regulation of small RNA targets at the post-transcriptional level , incurred in common by VSR expression and/or by the dcl1–9 mutation , concerns only a discrete subset of transcripts in Arabidopsis , with strikingly modest effects , mostly in the 1 . 5–2 fold range . This was not only observed for experimentally established ( Figure 1A; Figure S4–S6 ) , but also newly identified , putative targets . Although , the selection against high VSR expression and the hypomorphic nature of dcl1–9 might contribute to these effects , they are unlikely to form their sole basis . Indeed , modest changes in silencing target transcript levels were also noticed in studies of distinct alleles of dcl1 in various ecotypes , displaying developmental alterations ranging from moderate to severe; the same was observed in comparative analyses of transgenic Arabidopsis expressing other types of VSRs that also impinge on miRNA and siRNA functions [27] , [28] . More compellingly , a recent study of miRNA target mimics expressed under the strong 35S promoter also revealed a generally modest effect on miRNA target transcript levels , despite the generation of sometimes dramatic developmental phenotypes [28] . Collectively , these observations highlight an apparent discrepancy between the expected or observed biological outcome of miRNA action on the one hand , and the overall level of variation of target transcripts , on the other , which is in most cases within the range of haplo-sufficiency . One aspect that could help reconcile , at least in part , this apparent discrepancy is the tissue- or even cell-type specific expression of small RNAs and/or their targets . In situ-hybridization and reporter gene fusion analyses indeed show that several , perhaps many , plant miRNAs display exquisitely defined expression patterns [38] , [39] . However , the above-mentioned analyses and the present one employed RNA extracted from whole organs , and this may artificially dilute spatially restricted , yet biologically highly significant , effects of some miRNAs on some target transcripts . According to this idea , a much higher spatial , and even temporal resolution might be required in future microarray-based analyses of plant small RNA action [4] . A second , non-mutually exclusive possibility is that plant miRNA- and siRNA-mediated gene regulation entails a much wider translational inhibition component than is usually thought , such that only modest small RNA effects are manifested at the transcript level . Indeed , use of appropriate genetic background indicates that most , if not all , plant miRNAs ( and , possibly , siRNAs ) regulate their targets through a combination of slicing-based or translation-based inhibitory mechanisms whose respective prevalence is essentially unpredictable based on the position ( 5′ UTR , CDS , 3′ UTR ) , pairing degree , or multiplicity of small RNA binding sites [40] . In support of this idea , many Arabidopsis miRNAs are found on polysomes in association with AGO1 [41] . It is , in fact , striking that the amplitude of target mRNA expression changes ( 1 . 5–2 . 5 fold ) uncovered in this and other studies of Arabidopsis small RNAs falls within the range of variations typically observed for miRNA-repressed transcripts in metazoans . This modest , yet quantifiable reduction of transcript accumulation by metazoan small RNAs is not accounted for by slicing but , rather , by mRNA decay following deadenylation and decapping , which is coupled to translational repression [42] , [43] , [44] . In plants , the bulk of target mRNA degradation is commonly ascribed to slicing , typically diagnosed by 5′ RACE analyses [45] . Yet , hardly ever is this technique used quantitatively , so that the real contribution of slicing as opposed to other mechanisms of miRNA-induced transcript turnover ( i . e . mRNA decay ) is difficult to evaluate . mRNA decay as a consequence of small RNA-directed translational repression is yet to be described in plants , but it certainly deserves careful attention in future investigation of small RNA/target interactions in those organisms . This study incidentally unraveled that combining comparative microarray analyses of individual VSR transgenic plants and target site predictions from AGO-IP reads is an original approach to the discovery of endogenous transcripts regulated via small RNAs at the post-transcriptional level . The approach was notably useful in uncovering somewhat poorly predictable instances of PTGS-based regulations , emphasizing the flexibility and intricate nature of the various RNA silencing pathways in Arabidopsis . For instance , some heterochromatic loci normally associated to the production of 24-nt siRNAs , might be sources of AGO1-loaded trans-acting siRNAs , 21–22-nt in length ( Figure 2C , Figure S8 ) while 5′-A- or 5′-G-terminal miRNA passenger strands may exert cis or trans regulatory effects upon their association with AGO1 , which is prominently loaded with 5′-U-terminal small RNAs [30] , [46] , [47] . Hence , our observation with miR159b* and SHP1 ( Figure 3A ) possibly extends the range of transcription factors controlled by the MIR159b locus ( at least in Arabidopsis ) , which normally targets MYB-related genes through the mature miR159 species . The prospect of miRNA passenger strands being used for regulatory purposes has not received much attention so far in plants , yet this phenomenon appears to be common in metazoans . In Drosophila , developmentally regulated mechanisms seem to determine the selection/usage of one or the other miRNA strand , and to engage them into distinct regulatory networks , possibly in a cell- or tissue-specific manner [48] , [49] . Finally , the AGO1-IP approach applied to single VSR lines could also identify potential trans-targets of IR-derived siRNAs . In particular , we recently showed that IR71-derived siRNA populations can move between distant tissues through the vasculature , presumably to orchestrate gene regulation at a distance both at the transcriptional and post-transcriptional levels [11] . At4g08390 , encoding a stromal ascorbate peroxidase , is obviously a strong candidate for this type of regulation; moreover , its presumed function -detoxifying hydrogen peroxide , a molecule involved in defense reactions- is consistent with our recent finding that IR71 transcription and ensuing siRNA production are strongly induced by viral and bacterial pathogens [11] . Undoubtedly , many additional occurrences will be uncovered through analysis of the non-exhaustive depository found in Figure S7 and Figure S8 such that the approach and its possible refinements ( Text S2 ) will likely complement the tools already available for the discovery or validation of endogenous silencing targets and associated small RNAs in Arabidopsis . Although the method was restricted here to the analysis of sequencing reads from AGO1-IPs [30] , it could , in principle , be adapted to small RNAs that are loaded into other types of AGOs with demonstrated or suspected functions in PTGS , and whose action is also likely inhibited by VSRs . These include Arabidopsis AGO10 and AGO5 , which belong to the same genetic clade as AGO1 , as well as AGO7 , which directs cleavage of specific non-coding RNAs to initiate phased TAS3 ta-siRNA production [50] . One advantage of the method is that it does not rely on specific mutations in RNA silencing pathway components ( i . e AGO1 or DCL1 ) but , rather , on the broad-spectrum inhibitory effects of VSRs upon the activity of PTGS-associated small RNAs , independently of their origin and of their AGO effector proteins . This likely explains our finding that introgression of the arf8–6-/- or arf8–6+/− mutation into hypomorphic ( ago1–27 ) or null ( ago1–36 ) mutant alleles of AGO1 has no detectable effects on the developmental abnormalities exhibited by those plants ( data not shown ) . Presumably , miR167 regulatory functions are , in this case , rescued by the function of an alternative AGO ( e . g . AGO10 ) that is also affected by VSRs . This hypothesis predicts that the developmental defects of mutants in DCL1 , which fail to accumulate most miRNAs , should , by contrast , be sensitive to arf8-/- . Indeed , introducing the arf8 homozygous mutation into the dcl1–7 hypomorphic allele ( ecotype Col-0 ) was reported to rescue the pleitropic phenotype and viability of this allele , although the molecular bases for this phenomenon was not explained at the time [29] . We show , in this study , that the post-embryonic developmental anomalies of VSR plants can be largely ascribed to the misregulation of ARF8 , presumably via an effect on miR167 activity . In support of this result , arf8–6 mutant plants expressing ectopically a miR167-resistant allele of ARF8 ( mARF8 ) are hardly viable , and the few T1 individuals that survive transformation , presumably because of low transgene expression levels , display strong sterility reminiscent of that seen in HcPro , P19 and P15 plants [51 , Jason Reed , personal communication] . Moreover , and as explained in the previous section , the arf8 mutation also attenuates the pleiotropy and fertility defects of dcl1–7 mutant Arabidopsis [29] . Regulation of ARF8 by miR167 appears , therefore , central to Arabidopsis developmental biology . Recently , a mutation in an ethylene-induced transcription factor , RAV2 , was also shown to partially suppress the developmental phenotype of HcPro transgenic Arabidopsis plants [52] . Unlike in arf8 mutant plants , however , this effect was only evident in homozygous rav2 mutants , and it was accompanied by a strong inhibition of RNAi suppression by HcPro . While ARF8 was not part of the set of genes previously found to be up-regulated in rav2 mutant plants , analyses of available transcriptome data for the Arabidopsis arf8–3-/- arf6–2 -/- double mutant revealed that RAV2 expression is induced , rather than repressed , in the tissues analyzed ( Table S6 ) . Therefore , the developmental anomalies of HcPro transgenic plants may result from defects in at least two parallel pathways with distinct molecular bases . Abrogation of the VSR or dcl1–7 phenotypes by the arf8 mutation echoes previous findings that most developmental abnormalities of mutant plants deficient for SERRATE ( a gene involved in maturation of some , albeit not all Arabidopsis miRNAs ) can be rescued by mutations in only two targets of miR-165/miR-166 , PHABULOSA and PHAVOLUTA , which encode HD-ZIPII transcription factors specifying adaxial cell fates [53] . Thus , the establishment of key developmental programs might require the action of only a small subset of miRNAs and of their targets in Arabidopsis , raising the important issue of the biological significance of additional targets predicted for these and other miRNAs . An in-depth meta-analysis of the transcriptome and protein outputs of over-expressed miRNAs in various mammalian cell cultures similarly raised the question of whether metazoan miRNA-directed regulation of most predicted targets might be biologically neutral [54] . While the neutrality hypothesis certainly deserves attention in plants , an alternative idea holds that many plant miRNAs ( and thus their targets ) might mainly confer robustness to redundant , miRNA-independent gene repression programs based on transcriptional or epigenetic control , for instance . According to this idea , the function of such miRNAs would only become apparent under at least two conditions . The first condition would entail the prior genetic ablation of the redundant layers of gene expression control [55] . The second circumstance that might reveal functions of plant miRNAs in safeguarding unwanted gene expression is stress . Indeed , most miRNA studies in Arabidopsis have been conducted so far under ideal laboratory growth conditions , where the environmental cues or stimuli that might be required to induce unstable transcriptional patterns are usually nonexistent . Stress application and genetic inactivation of major transcriptional/epigenetic ‘hubs’ in VSR plants , miRNA pathway mutants , or individual MIRNA gene knockouts , are thus attractive prospects in future studies of Arabidopsis small RNAs and of their targets . One important aspect that had remained unclear from previous studies of antiviral silencing is whether hindrance of the host miRNA pathway is actually a mere consequence of the primary inhibition of antiviral silencing by VSRs or , on the contrary , a deliberate attempt of plant viruses to perturb plant developmental or hormonal pathways to optimize their replication and/or spread . This question is of particular pertinence in the frame of auxin signaling ( which is modulated by ARF8 ) , as this hormone has been previously implicated as a negative regulator of basal defense in plants [56] . Moreover , the interaction of the Tobacco mosaic virus ( TMV ) replicase protein , which displays VSR activities , with the PAP1 Aux/IAA protein correlated with viral disease symptoms [57] . The results of TuMV infections in arf8-/- mutant Arabidopsis , however , show that neither the virus replication nor the chlorotic symptom intensity was altered in those plants , despite a strong reduction of the developmental anomalies normally linked to the infection . These experiments therefore demonstrate in an authentic infection context , that the onset of morphological symptoms often associated with viral diseases , on the one hand , and pathogen virulence as a consequence of antiviral silencing suppression , on the other , can be uncoupled . Given the high evolutionary conservation of ARF8 and of its riboregulator , miR167 , the question thus arises of whether leaf serration and flower defects seen in Arabidopsis are an expected , generic outcome of virus infection in other plant species . It might not be the case for at least three reasons . First , miR167 and its targets may not have a similar weight in shaping organ morphology as they do in Arabidopsis , given the differences in stature and physiology of many plants . Second , the contribution of small RNAs to ARF8 regulation , as opposed to transcriptional control programs ( as evoked in the previous section ) , may vary between species . Third , paralogous proteins not necessarily regulated by small RNAs might ensure redundant ARF8 functions in some species . Supporting these ideas , expression of the same or related VSR alleles as those used in the present study induces developmental phenotypes in tobacco that do not necessarily overlap with those seen in Arabidopsis [58] . A last puzzling observation is that the arf8 mutation did not suppress the chlorotic symptoms associated with TuMV infection , leaving open the question of whether chlorosis , a widespread yet very poorly understood outcome of virus infection , is indeed related to virulence through VSR function . Accumulation of VSR-deficient viruses , including HcPro-deficient TuMV , can be rescued in Arabidopsis dcl2-dcl4 double-mutants . Thus , incorporating the arf8 mutation in this background might provide an interesting ground to study the potential VSR-dependency of chlorosis without the complication of developmental symptoms caused by viruses .
P15 , P19 and HcPro expressing lines ( in the CHS RNAi background ) were described previously [18] , as were the P6 transgenic line in the WT background [21] . P15 , P19 and HcPro lines are moderate expressors and carry the corresponding VSR transgenes in the heterozygous condition , as previously described [18] . The dcl1–9 , hen1-1 , hen1–6 and arf8–6 mutants were as described [37] , [59] , [60] . The arf8–4 ( WISC DsLox 324F09 ) , arf4–2 ( Salk_070506 ) , arf6 ( GABI_859B08 ) and arf3–2 ( SALK_005658 ) mutants were as reported in [37] . For microarray analyses all plants were grown in vitro in sterile Magenta glass boxes containing 1x MS medium ( Duchefa ) , 1% sucrose and 0 . 8% agar . Homozygous mutant plants were selected based on their developmental phenotypes and grown at 21–22°C with an 8 h photoperiod ( 60 µE m−2 sec−1 ) . All tissues ( inflorescences , stems , leaves and roots ) were harvested at once at the flowering stage . TuMV sap was extracted from 10 dpi infected turnip leaves ( 1 g tissue/2 mL 5 mM NaP pH 7 . 5 ) and used to inoculate three-week-old Arabidopsis rosettes as described previously [18] . TuMV-infected systemic leaves were collected at 14 dpi and subjected to molecular analyses . Total RNA was extracted from Arabidopsis tissues using Tri-Reagent ( Sigma , St . Louis , MO ) according to the manufacturer's instructions . Northern analyses of low molecular weight RNA were performed with 30 µg of total RNA , as described previously [18] . DNA oligonucleotides complementary to miRNA sequences were end-labelled with [γ-32P]ATP using T4 PNK ( New England Biolabs , Beverly , MA ) . Northern analyses of high molecular weight RNA were performed with 5–10 µg of total RNA . Probes were DNA fragments labelled by random priming incorporation of [α-32P]dCTP ( Amersham ) . RNA gel blots were subsequently exposed to x-ray films . For DCL1 , protein extraction was performed as previously reported [61] . For AGO1 , analyses were carried out using protein crude extracts in Tris-HCl 25M , pH 7 . 5 . In both cases , 100 to 200 µg of proteins were resolved on a 8% SDS-polyacrylamide gel , and subjected to western blotting . Antibodies for AGO1 and DCL1 were described previously in [62] . Total RNA was extracted using the RNeasy Plant Mini kit ( Qiagen ) according to the manufacturer's instructions . RNA samples were reverse transcribed into cDNA using SuperScript III reverse transcriptase ( Invitrogen ) after DNase treatment with RQ1 RNase-freeDNase ( Promega ) . The cDNA was quantified using LightCycler 480 SYBR Green I Master mix ( ROCHE ) and gene-specific primers ( see table below ) . PCR was performed in 384-well optical reaction plates heated at 95°C for 10min , followed by 45 cycles of denaturation at 95°C for 15s , annealing at 60°C for 20s , and elongation at 72°C for 40s . A melting curve was performed at the end of the amplification by steps of 1°C ( from 50°C to 95°C ) . The reference gene set was defined using the NormFinder algorithm ( http://www . mdl . dk/publicationsnormfinder . htm ) . These were Actin2 ( At3g18780 ) , At4g34270 and At4g26410 in stems; At4g34270 in leaves; Actin2 and At4g26410 in inflorescences . The sequences of DNA oligonucleotides used for qPCR validations were as shown in Table 1 . Microarray analysis was carried out at the Unité de Recherche en Génomique Végétale ( Evry , France ) , using the CATMA gene arrays containing 24576 gene-specific tags corresponding to 22089 genes from Arabidopsis [63] , [64] and a custom-made tiling array covering chromosome 4 at 1 kb resolution [25] . Two independent biological replicates were produced . Total RNA was extracted using trizol according to the supplier's instructions . For each comparison , one technical replication with fluorochrome reversal was performed for each biological replicate ( i . e . four hybridizations per comparison ) . Labelling of cRNAs with Cy3-dUTP or Cy5-dUTP ( Perkin-Elmer-NEN Life Science Products ) , hybridization to the slides , and scanning were performed as described in [65] . Experiments were designed with the statistics group of the Unité de Recherche en Génomique Végétale . Normalization and statistical analysis was based on two-dye swap method ( i . e . four arrays , each containing 24576 GSTs and 384 controls ) as described in [66] . To determine differentially expressed genes , a paired t-test was performed on the log ratios , assuming that the variance of the log ratios was the same for all genes . Spots displaying extreme variance ( too small or too large ) were excluded . The raw p-values were adjusted by the FDR method , which controls the Family Wise Error Rate , ( with a type I error equal to 5% ) in order to keep a strong control of the false positives in a multiple-comparison context ( as described in [67] . ) We considered as being differentially expressed the genes with a pFDR ≤0 . 05 , as described in [66] . An exhaustive description of the statistical procedures used for microarray analyses can be found in Text S3 . Chromatin was extracted from leaves of three weeks old plants and chromatin immupoprecipitation was performed using two biological replicates , as described previously [68] . H3K4me2 and H3K9me2 antibodies were purchased from Millipore ( Ref . 07-030 and 07-441 , respectively ) . Immunoprecipitated samples were differentially labeled and hybridized onto a custom made tiling array covering Arabidopsis chromosome 4 and the results were analyzed as described previously [25] . AGO1 associated siRNA sequences were downloaded from GEO ( www . ncbi . nlm . nih . gov/geo/ ) , accession number GSE10036 , and were mapped to Arabidopsis thaliana genome ( TAIR8 release ) with Vmatch ( www . vmatch . de ) . mRNA sequences were calculated from the MIPS Arabidopsis thaliana Genome Database ( MAtDB ) , based on TAIR8 release . Each AGO1 associated siRNA was then subjected to BLAST analysis against a given set of mRNA sequences . The results were parsed by a python script , using the Biopython library . A transcript is considered as a putative target when its reverse complement sequence presents ( i ) ≤three mismatches with an AGO1-IP sRNA and ( ii ) no more than two mismatches between position one and 12 . All the transcripts for one gene were searched for target sites independently . The abundances of all siRNAs matching each target site were then summed for each mRNA . The datasets corresponding to the gene expression profiling experiments in VSR transgenics , hen1 and dcl1 mutants of Arabidopsis are accessible at the Gene Expression Omnibus [GEO] under accession number GSE24693 . The datasets corresponding to the Arabidopsis chromosome 4 TILLING array experiments are accessible at the Gene Expression Omnibus [GEO] under accession number GSE26739 for transcript analysis and GSE24692 for chromatin modifications . Both datasets are also accessible at CATdb ( http://urgv . evry . inra . fr/CATdb/; Project: GEN107 ) according to the “Minimum Information About a Microarray Experiment” standards .
|
In the plant and animal RNA silencing pathways , small RNA molecules known as micro ( mi ) RNA and short-interfering ( si ) RNAs have key roles in development and antiviral defense , respectively . In turn , viruses counteract this defense by deploying specific virulence factors , referred to as Viral Suppressors of RNA silencing ( VSRs ) , which target distinct steps of the host silencing machinery . In the model plant species Arabidopsis thaliana , transgenic expression of distinct VSRs often incurs a set of strikingly recurrent developmental anomalies that resemble those triggered by viral infections . While these defects have been assumed to result from a general interference of VSRs with silencing-based mechanisms controlling cellular growth , their exact molecular basis has remained largely elusive . Here , we address this issue by demonstrating that misregulation of a single transcript encoding the AUXIN RESPONSE FACTOR 8 , a target of miR167 , underlies most , if not all , of the defects caused by VSR expression , both in transgenic and in an authentic infection context . Our study also highlights the value of VSRs as generic tools for the discovery or validation of endogenous RNA silencing targets . These results also have implications for our understanding of small RNA-based regulations in plants , and shed light on the possible origin of some of the symptoms elicited by viral diseases .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"science",
"plant",
"biology",
"biology",
"molecular",
"cell",
"biology"
] |
2011
|
Misregulation of AUXIN RESPONSE FACTOR 8 Underlies the Developmental Abnormalities Caused by Three Distinct Viral Silencing Suppressors in Arabidopsis
|
Cysteine ( Cys ) residues often play critical roles in proteins , for example , in the formation of structural disulfide bonds , metal binding , targeting proteins to the membranes , and various catalytic functions . However , the structural determinants for various Cys functions are not clear . Thiol oxidoreductases , which are enzymes containing catalytic redox-active Cys residues , have been extensively studied , but even for these proteins there is little understanding of what distinguishes their catalytic redox Cys from other Cys functions . Herein , we characterized thiol oxidoreductases at a structural level and developed an algorithm that can recognize these enzymes by ( i ) analyzing amino acid and secondary structure composition of the active site and its similarity to known active sites containing redox Cys and ( ii ) calculating accessibility , active site location , and reactivity of Cys . For proteins with known or modeled structures , this method can identify proteins with catalytic Cys residues and distinguish thiol oxidoreductases from the enzymes containing other catalytic Cys types . Furthermore , by applying this procedure to Saccharomyces cerevisiae proteins containing conserved Cys , we could identify the majority of known yeast thiol oxidoreductases . This study provides insights into the structural properties of catalytic redox-active Cys and should further help to recognize thiol oxidoreductases in protein sequence and structure databases .
Compared to other amino acids in proteins , cysteine ( Cys ) residues are less frequent , yet often more conserved and found in functionally important locations . Protein-based Cys thiols can be divided into several broad categories wherein these residues ( i ) are engaged in structural disulfide bonds , ( ii ) coordinate metals , ( iii ) carry out catalysis , ( iv ) serve as sites of various posttranslational modification , or ( v ) are simply dispensable for protein function . Structural disulfide bonds are typically observed in oxidizing environments such as periplasm in prokaryotes , and extracellular space and the endoplasmic reticulum ( ER ) in eukaryotes . Structural disulfides are formed by designated systems for oxidative protein folding , for example DsbA and DsbB in bacteria and protein disulfide isomerase and Ero1 in the eukaryotic ER . In addition , disulfides as stabilizing or regulatory elements may occur intracellularly . However , there are also situations when the introduced intraprotein disulfide leads to a decreased protein stability [1] . Structural stability may also be achieved when Cys residues are linked by metal ions , such as zinc and iron . In addition , Cys-coordinated metal ions may serve catalytic functions; for example , when the metal is zinc , copper , nickel , molybdenum or iron . Metal-coordinating thiols are typically found intracellularly [2] , [3] , but may also occur in the extracellular space . Another important functional category of Cys residues involves catalytic Cys that act as nucleophiles . This situation occurs , for example , in Cys proteases and tyrosine phosphatases where Cys does not change redox state during catalysis , and in thioredoxins and glutaredoxins where Cys undergoes reversible oxidation and reduction . In the latter case , thiol oxidation may result in the formation of an intermediate disulfide bond with another protein thiol . In the absence of nearby Cys residue , thiol oxidation may lead to sulfenic acid ( -SOH ) , sulfinic acid ( -SO2H ) , S-nitrosothiol ( -SNO ) , or S-glutathionylation ( -SSG ) . In the majority of these intermediates ( with the exception of sulfinic acids ) , the oxidized forms of Cys can be reduced by thiol oxidoreductases , such as thioredoxin and glutaredoxin , by glutathione , or by other protein and low molecular weight reductants [4] , [5] . Even sulfinic acids can be reduced in a select class of proteins , for example , in peroxiredoxins by a protein known as sulfiredoxin [6] . Since these oxidized thiol forms are often reversible , they constitute a facile switch for modulating protein activity and function . Reversible thiol oxidation has received considerable attention in recent years due to its ability to regulate proteins , protect them against stress and influence signaling . For example , sulfenic acid formation is often an intermediate step in generating disulfides [7] . Recent work has analyzed Cys-SOH formation in a set of test proteins by examining their functional sites and electrostatic properties [8] . The authors characterized several features of these proteins including significant underrepresentation of charged residues and occurrence of polar uncharged residues in the vicinity of modified Cys . Nevertheless , at present little is known about the sequence or structural features that can be employed to predict these proteins in sequence or structure databases . Much recent work has focused on S-glutathionylation [9] , but common features of these modification sites are also unclear , especially as tools to identify other glutathionylation sites . Similarly , the determinants of S-nitrosylation are poorly understood . In the latter case , previously reported features include the presence of acid-base motifs flanking the modified Cys [10] , and , in contrast to the Cys-SOH-containing proteins , higher frequency of charged residues . In addition , attempts have been made to examine sites of Cys oxidation at a structural level . One study evaluated simple structural properties and aimed at identifying common features of the environment in the vicinity of Cys residues that undergo reversible redox changes [11] . Parameters that positively correlated with the occurrence of these Cys included ( i ) proximity to another Cys residue; ( ii ) low pKa ( lower than ca . 9 . 06 ) ; and ( iii ) significant exposure ( greater than 1 . 3 Å2 ) of the sulfur atom to solvent . Additional parameters reported were spatial proximity of both proton donor and proton acceptor to the redox Cys . However , this generic approach combined the analysis of catalytic and regulatory Cys , which by nature , are different . In addition , with this approach , almost all protein tyrosine phosphatases , ubiquitin-activating E1-like enzymes , thymidylate synthases and other enzymes with catalytic non-redox Cys could be detected , mainly because of their reactive ( i . e . , low pKa and high exposure ) catalytic Cys . Although Cys residues often serve roles critical to protein function and regulation , the presence of a Cys per se by no means implies any of these features . Analyses of Cys conservation may help identify some catalytic and functional Cys , but mostly for proteins with already known functions . Nevertheless , at present , sequence-based methods provide the most straightforward approach to analyze Cys function . For example , many catalytic redox Cys can be efficiently identified by searching for Cys-selenocysteine ( Sec ) pairs in homologous sequences [12] . This idea stems from the observations that known functions of Sec are limited to redox functions and that most selenoproteins have homologs in which Sec is replaced with a conserved Cys ( implicating this Cys in redox catalysis ) . We hypothesized that identification of Cys function may be assisted by examining unique features of each Cys function in proteins . In this work , we analyzed general features of catalytic redox-active Cys via functional profiles of active sites and structural analyses of reaction centers . When integrated with the tools for enzyme active site prediction and titration properties of active site residues , this approach allowed efficient prediction of thiol oxidoreductases in protein structure databases .
To examine common features of thiol oxidoreductase active sites , we first built a protein dataset containing previously described thiol oxidoreductases . It included representative members of protein families with known three-dimensional structures . We paid particular attention to balance the representation of thioredoxin fold ( which is the most common fold found in thiol oxidoreductases ) and non-thioredoxin fold oxidoreductases . The resulting dataset consisted of 75 structures in which none of the protein domains , as defined by SCOP classification , was represented by more than 7 structures . Of these 75 proteins , 40 had thioredoxin-fold , including homologs of glutathione peroxidase ( 10 representatives ) , thioredoxin ( 7 ) , glutaredoxin/thioltransferase ( 13 ) , protein disulfide isomerase ( 3 ) , DsbA ( 2 ) , C-terminal domain of DsbC/DsbG ( 2 ) , selenoprotein W ( 2 ) and ArsC ( 1 ) . The non-thioredoxin fold proteins of our redox dataset included 35 proteins organized in 10 structural folds ( thirteen protein families ) , including FAD/NAD-dependent reductase ( 9 representatives ) , Ohr/OsmC resistance protein ( 6 ) , methionine-S-sulfoxide reductase ( 3 ) , reductase with the protein tyrosine phosphatase fold ( 3 ) , GAF-domain methionine sulfoxide reductase fRMsr ( 2 ) , FAD-dependent thiol oxidase ( 2 ) , methionine-R-sulfoxide reductase ( 2 ) , antioxidant defense protein AhpD ( 2 ) , Ero1 ( 1 ) , and thiol-disulfide interchange protein DsbD ( 1 ) . The complete dataset is shown in Table S1 . Our initial analyses suggested that the most challenging problem in characterizing the general features of redox-active Cys is distinguishing them from other catalytic Cys residues . Clearly , these two Cys types share active-site location and high reactivity ( e . g . , both redox and non-redox Cys are often strong nucleophiles ) . To ascertain differences between these protein classes , we built a separate control dataset of proteins containing catalytic non-redox Cys ( Table S2 ) . This set was composed of 36 proteins ( organized in the form of 17 families/9 folds ) including papain-like ( 9 representatives ) , penta-EF-hand ( 2 ) , ubiquitin carboxyl-terminal hydrolase UCH-13 ( 1 ) , FMDV leader protease ( 1 ) , caspase catalytic domain ( 3 ) , gingipain R ( 1 ) , adenain-like ( 2 ) , pyrrolidone carboxyl peptidase ( 1 ) , hedgehog C-terminal autoprocessing domain ( 1 ) , high molecular weight phosphotyrosine protein phosphatase ( 4 ) , dual specificity phosphatase-like ( 2 ) , thymidylase synthase/dCMP hydroxymethylase ( 2 ) , low molecular weight phosphotyrosine protein phosphatase ( 1 ) , calpain large subunit , catalytic domain ( domain II ) ( 1 ) , dipeptidyl peptidase I ( cathepsin C ) domain ( 1 ) , viral Cys protease of trypsin fold ( 2 ) , Ulp1 protease family ( 1 ) , and ubiquitin-activating enzyme ( 1 ) . The method further presented in this work is divided into two parts ( Figure 1A ) : the first employs knowledge-based information for detection of thiol oxidoreductases by analyzing structural and compositional similarity to the active sites of known thiol oxidoreductases; and the second makes use of energy-based methods to assess properties of the catalytic redox-active Cys . For simplicity we refer to the first part as Active Site Similarity , and to the second as Cys Reactivity . The Active Site Similarity analysis included three independent steps: ( i ) amino acid composition of active sites at two distances from the catalytic Cys; ( ii ) structural profiles of active sites; and ( iii ) secondary structure profiles . Each of these steps contributed to the scoring function ( SF ) . To analyze amino acid composition of the region surrounding catalytic Cys in known thiol oxidoreductases , we determined the occurrence of amino acids within a sphere centered at the sulfur atom of the catalytic Cys with two radii , 6 Å and 8 Å ( Figure 1B ) . For this , we separately examined thioredoxin-fold , FAD-containing , and other non-thioredoxin fold thiol oxidoreductases . For comparison , we analyzed two sets of randomly chosen Cys-containing proteins ( 800 and 1000 proteins , respectively ) , from which any proteins present in the thiol oxidoreductase and control datasets were excluded . Cys residues present in randomly chosen proteins represented an average composition of amino acids in the vicinity of Cys in protein structures . For each of the six so-defined groups of proteins ( i . e . , three groups of thiol oxidoreductases , a group containing catalytic non-redox Cys , and two groups of randomly chosen proteins ) an average amino acid composition was calculated for 6 Å and 8 Å distances from the sulfur atom of Cys ( Figure 2 ) . Interestingly , each group of proteins with catalytic Cys showed unique amino acid occurrence that was also different from those of the two sets of randomly chosen proteins . This was particularly evident in the 6 Å datasets . However , statistical analysis of these data ( standard deviations are given in Figure 2 and the p-values for frequency counts are listed in Figure 3 ) showed that some differences observed were not significant . Thus , a complete definition of thiol-oxidoreductases based only on amino acid frequency is not possible . Nevertheless , these data can be used , in a multi-parameter approach like the one presented here , to contribute to the description and predictability of these enzymes . Thus , we proceeded in our analyses considering the average values as shown in Figure 2 . We further employed the average occurrences of each amino acid in the vicinity of Cys as profiles ( or dictionaries , to avoid confusion with the structural profiles described later on ) , specific for each set , in which every amino acid had its protein function-specific occurrence . The use of these dictionaries as predictive tool is straightforward: for a given protein , occurrences of amino acids located within 6 Å and separately within 8 Å of each Cys sulfur atom are calculated , compared with the dictionaries of each reference protein class , and scored . The occurrence that receives the highest score is assigned to the corresponding protein class . For example , when a score is closest to those of thiol oxidoreductase dictionaries , it is considered positive , and in all other cases it is considered negative . In the former case , a positive value ( 0 . 375 from each of the 6 Å and 8 Å distance calculations ) is given to the final SF while in other cases a null value is given . Thus , the dictionary component of the Compositional analysis can give an overall contribution of up to 0 . 75 to the SF . These analyses detected differences in amino acid occurrence around catalytic Cys between thiol oxidoreductases and proteins containing catalytic non-redox Cys residues . In addition , within thiol oxidoreductases , the amino acid composition of FAD-containing enzymes was unique . For example , thioredoxin-fold thiol oxidoreductases showed an overall high representation of aromatic residues near the catalytic Cys , whereas FAD-containing thiol oxidoreductases showed lower occurrences of these residues . Thus , for this step of the procedure , FAD-containing thiol oxidoreductases were not considered . It should be noted that this did not affect the overall analysis as other steps of the method performed well with these enzymes and they could still be identified by the overall method . With this restriction , we found that several amino acids , including Pro , Cys , Trp , Tyr and Phe , were overrepresented in thiol oxidoreductases ( Figure 2 ) . At the same time , Met , His , Gly , and Glu were found to be less frequent in these proteins . Based on this information , we empirically defined the following formula that allowed separation of thiol oxidoreductases and other Cys-containing proteins: ( W+Y+F+1 . 5C+0 . 5P ) / ( G+H+Q+2M ) , where letters correspond to abundances of amino acids ( in single letter code ) and the numbers are coefficients . In developing this formula , we sampled different coefficients and applied the formulae to true positive and control ( S1 and S2 ) datasets . The coefficients most efficiently separating thiol oxidoreductases from other proteins were kept . The ratio in the formula reflected common features of thiol oxidoreductases , distinguishing them from enzymes containing non-redox catalytic Cys . For example , active sites of thiol oxidoreductases preferred non-polar aromatic residues . While all aromatic amino acids were overrepresented ( compared to their average values in control sets , see Random Cys in Figure 2 ) , histidine was less frequent ( but it had high frequency in non-redox proteins with catalytic Cys ) . Consequently , all aromatic residues appeared in the numerator of the formula , but histidine was placed in the denominator . Other features of catalytic Cys were also included in the formula such as the well known preference for a second Cys ( often a resolving Cys ) in the proximity of the catalytic Cys , while the enzymes containing non-redox catalytic Cys showed a significant underrepresentation of additional Cys in the active sites . Proline is also often observed in thiol oxidoreductases , but is less frequently found in other enzymes ( Figure 2 ) . Although the chemical basis for differences in the use of amino acid in the vicinity of Cys is not fully clear , the application of this formula was found to be quite effective . Generally , values higher than 1 . 0 corresponded to thiol oxidoreductases . For example , 79% thiol oxidoreductases ( Table S1 ) had scores higher than 1 . 0 , whereas in the control dataset ( Table S2 ) , 88% proteins had a score lower than 1 . 0 . When representatives of the Random Cys sets were screened with the formula , the ratio of false positive prediction ( i . e . , non thiol oxidoreductases scoring higher than 1 . 0 ) somewhat increased , e . g . , among 100 analyzed proteins from the Random Cys set 1 , 22% scored above 1 . 0 . Interestingly , many of these scoring proteins contained metal-binding Cys . This was mainly because Cys residues clustered in these proteins ( e . g . , in zinc finger or iron-sulfur cluster-containing proteins ) . Thus , the contribution to the SF from this last component of the Compositional analysis was lower than that of the dictionaries , adding a value of up to 0 . 25 to the SF . Finally , when the three components of the Compositional analysis ( analysis of dictionaries for 6 Å and 8 Å and the application of the formula ) were considered , the contribution to the SF ranged from 0 to 1 . 0 ( Figure 1 ) . A previous study assessed structural similarity of reaction centers by profiling functional sites in proteins [13] . It built a signature sequence of amino acids located in the active sites . In our work , segments of amino acids in the active sites were extracted from the structure and combined into a single contiguous sequence ( called either structural profile or active site signature ) . A similar approach was recently employed to examine proteins with Cys oxidized to sulfenic acid [8] , in which active sites were defined as an area located within 10 Å from the oxidized Cys . This study [8] proposed that pairwise alignments between signatures can be effective in predicting protein function by analyzing an unknown profile against a set of known profiles . We used this idea and employed the 8 Å active site signatures derived from each thiol oxidoreductase in our dataset ( Table S1 ) as the set of known profiles . It should be noted that , compared to the original procedure [13] , the parameters for weighting pairwise alignments ( i . e . , relative weights for similarities , gaps and identities ) were empirically optimized to achieve the best separation of thiol oxidoreductases and reference datasets ( Figures S1 and S2 ) . The optimized parameters for equation 1 are described in detail in the Methods section . The ability of this procedure to separate thiol oxidoreductases from other proteins is remarkable; using an appropriate cut off for the output of equation 1 ( for example , 0 . 4 in Figure S1 ) as described in the Methods section , no false positives were detected . This feature ( i . e . , very low false positive rate ) opened up an opportunity , based on the structural profile analysis , to assign a wider range of values as contributing to the SF . In particular , values higher than 1 . 0 could be given to the SF when the output of equation 1 is sufficiently high . However , values higher than 1 . 0 were appended to the SF only under the conditions where the probability of false positive predictions was either null or very low . The contribution of this procedure to the SF ranged from 0 to 2 . 5 with the latter occurring only when the profile of a putative protein under examination was almost identical to that of a known thiol oxidoreductase . Further details on this part of the procedure are given in the Methods section . We analyzed secondary structure composition within 6 Å from the catalytic Cys for all proteins in our datasets ( Figure S3 ) . A marked preference for alpha helical and loop geometries around the Cys was found in thiol oxidoreductases . In turn , beta strands were infrequent ( with notable exception of MsrBs ) . We implemented these observations with a simple function requiring helical composition exceeding 35% and loops exceeding the composition of strands . As alluded above , some thiol oxidoreductases ( MsrBs , fRMsrs and arsenate reductases ) were missed at this step of the analysis . Since this procedure could potentially miss other candidate thiol oxidoreductases , its contribution to the SF ranged from 0 to 0 . 5 . When the three steps of the procedure ( i . e . , amino acid composition , structural profile and secondary structure composition of the active sites ) were applied together to thiol oxidoreductase and control datasets , a nearly complete separation of thiol oxidoreductases and other proteins was achieved ( Figure S4 ) . Each thiol oxidoreductase ( Table S1 ) received scores higher ( ≥1 . 5 ) than any control protein ( Table S2 and a representative subset of the randomly chosen proteins ) , with a single exception: a low molecular weight tyrosine phosphatase ( PDB code 1D1P ) scored as high as some of the low scoring thiol oxidoreductases . However , this phosphatase showed marked analogy to thiol oxidoreductases ( e . g . , some proteins annotated as low molecular weight tyrosine phosphatases are in fact arsenate reductases ) . We discuss this feature in greater detail later in the text ( see results of the Yeast Analysis ) . We hypothesized that properties of redox-active catalytic Cys could also be suitable for distinguishing thiol oxidoreductases from proteins with other Cys types . In addition , proteins with catalytic Cys could potentially be distinguished from those with non-catalytic Cys by virtue of thiol oxidoreductases being enzymes . Thus , we examined available active site prediction programs with respect to recognition of Cys active sites in thiol oxidoreductases . These programs included Q-site finder ( http://www . modelling . leeds . ac . uk/qsitefinder/ ) , Pocket finder ( http://www . modelling . leeds . ac . uk/pocketfinder/ ) , THEMATICS ( http://pfweb . chem . neu . edu/thematics/submit . html ) , SARIG ( http://bioinfo2 . weizmann . ac . il/̃pietro/SARIG/V3/index . html ) and FOD ( http://bioinformatics . cm-uj . krakow . pl/activesite/ ) . All of these programs are freely accessible via web service , but some calculations could be slow ( e . g . , THEMATICS ) . For each program , we examined randomly chosen 15 thioredoxin fold and 15 non-thioredoxin fold thiol oxidoreductases ( Figure 4 ) . Two programs , FOD and SARIG , were ineffective in predicting catalytic sites of thiol oxidoreductases . Pocket Finder performed slightly better but still clearly missed many active sites with catalytic redox-active Cys . The best methods for thiol oxidoreductase prediction proved to be Q-site finder and THEMATICS . The use of THEMATICS is limited by its speed . Thus , Q-site finder was further employed . Scoring of this method is detailed in the Methods section . Briefly , if a catalytic Cys ranked within the first 3 sites , a positive value ( 1 . 0 ) was given to the SF , and a zero value was given if the sulfur atom of Cys was not predicted in any of the 10 ranked sites . Intermediate situations resulted in the contributions to the SF , declined in the range between 0 and 1 , as detailed in the Methods section . The final step of our algorithm examined Cys titration curves . As discussed in the Introduction , pKa and exposure have recently been proposed as parameters that distinguish redox-regulated Cys from other Cys types [11] . However , when applied to our dataset , they proved to be ineffective in detecting differences between redox and non-redox catalytic Cys residues ( Figure S5 ) . This is indeed not surprising , as sulfur exposure and a reasonably low Cys pKa should be necessary features for both thiol oxidoreductases and enzymes with other nucleophilic catalytic Cys . Thus , we examined other properties and methods that could account for accessibility and reactivity of catalytic redox Cys . While Q-site finder may possibly account for effective accessibility of Cys to small molecular probes [14] , it provides no information on Cys chemistry . An alternative was to directly employ theoretical titration curves of active site Cys residues . Indeed , the main idea of THEMATICS is based on the observation that theoretical titration curves and their deviation from standard Henderson-Hasselbach ( HH ) behavior can inform on the location of active site residues ( if they are titrable ) . Analysis of the theoretical titration curve of a titrable residue is often more informative than simple calculations of its pKa [15]–[18] . In this work , we employed the web accessible H++ server [19] to calculate Cys titration curves and developed in-house tools for analyzing the output ( details are in the Methods section ) . Briefly , we examined theoretical titration curves of each candidate Cys and compared them with the standard HH behavior . The two curves were superimposed and numerically compared ( Figure 5 ) . Greater deviation between the two curves ( Figure 5A ) implied a higher probability of the Cys being part of the active site and was given a positive contribution ( up to 1 . 0 ) to the SF , whereas small deviation or no deviation ( Figure 5B ) was given a zero contribution . We combined the methods discussed above in a single algorithm shown in Figure 1A . For the initial test of the algorithm , we selected a set of randomly chosen proteins ( Test Case ) not included in the datasets used to develop the method , which consisted of 22 thiol oxidoreductases ( 13 thioredoxin-fold proteins , 4 FAD-binding proteins and 5 other non-thioredoxin fold enzymes ) , 13 proteins with catalytic non-redox Cys and 21 proteins with non-catalytic Cys known to be redox-regulated through nitrosylation or glutathionylation ( Table S3 ) . Several Test Case proteins were homology models . We deliberately included them as structural models ultimately represent application of the program to proteins with unknown structures . The Test Case was also used to analyze weight distribution for each parameter of the algorithm; this process supported parameter weights shown in Figure 1A ( values in brackets ) . Details of these calculations are shown in Figure S6 , available as supporting information . We also assessed method performance upon changes in weights , and this is shown in Figure 6 ( details are given in the figure legend ) . The output of the algorithm with optimized parameter weights ( Figure 1A ) , applied to the Test Case , is shown in Figure 7 . Complete separation of thiol oxidoreductases ( shown by blue circles ) from proteins with other Cys functions ( green circles ) was achieved with a cutoff value of 2 . 75 . Details of the calculations for each protein in the Test Case are shown in Table S3 . To validate the algorithm on a genome-wide level , without any bias in the selection of proteins , we applied the method to the Saccharomyces cerevisiae proteome . Initially , we selected a subset of yeast proteins by including ( i ) all known thiol oxidoreductases found by literature search and detected by PSI-BLAST searches using known thiol oxidoreductases as queries; and ( ii ) all other proteins in the yeast proteome containing at least one highly conserved Cys ( conserved in ≥90% homologs ) . From this set , proteins containing metal-binding Cys residues were filtered out using Prosite patterns . The resulting set of 292 proteins was subjected to homology modeling via Swiss Model ( http://swissmodel . expasy . org/ ) or HOMER ( http://protein . cribi . unipd . it/Homer/ ) , which generated 149 structural models ( Table S4 ) . Among these proteins , 42 were predicted by our algorithm as thiol oxidoreductases ( i . e . , scored≥the cutoff value of 2 . 75 ) ( Figure 8 and Table S5 and Table S6 ) . Interestingly , 33 of the 42 predicted proteins were indeed known thiol oxidoreductases , and the remaining 9 proteins likely included candidate thiol oxidoreductases and false positives . The correctly predicted thiol oxidoreductases were ( Table S6 ) 6 glutaredoxin/glutaredoxin-like proteins ( >gi|6320720 , >gi|6323396 , >gi|6320492 , >gi|6319814 >gi|6320193 , >gi|6321022 ) , 4 thioredoxins/thioredoxin-like ( >gi|6319925 , >gi|6321648 , >gi|6323072 , >gi|6322186 ) , 1 glutathione reductase ( >gi|6325166 ) , 2 thioredoxin reductases ( >gi|6321898 , >gi|6320560 ) , 1 Ero1 ( >gi|6323505 ) , 1 Erv1 ( >gi|6681846 ) , 1 Erv2 ( >gi|6325296 ) , 5 peroxiredoxins/peroxiredoxin-like ( >gi|6323613 , >gi|6320661 , >gi|6320661 , >gi|6322180 , >gi|6319407 ) , 2 glutathione peroxidases ( >gi|6322228 , >gi|6322826 ) , 1 alkyl hydroperoxidase ( >gi|6323138 ) , 1 methionine-S-sulfoxide reductase ( >gi|6320881 ) , 1 methionine-R-sulfoxide reductase ( >gi|6319816 ) , 4 protein disulfide isomerases ( >gi|6319806 , >gi|6324484 , >gi|6324862 , >gi|6320726 ) , and 1 dihydrolipoamide dehydrogenase ( >gi|14318501 ) . The results are further illustrated in Figure 8 where all 149 yeast proteins for which models have been generated are represented ( green circles correspond to known thiol oxidoreductases ) . One of the candidate thiol oxidoreductases was 6-O-methylguanine-DNA methylase . Interestingly , in addition to this algorithm , this protein was predicted as thiol oxidoreductase by a method based on Cys/Sec pairs in homologous sequences [12] . As the structure of E . coli 6-O-methylguanine-DNA methylase is known ( PDB code 1sfe ) , we separately subjected this protein to our algorithm . For Cys135 of this protein , the score was 3 . 75 , a value above the cutoff . The same Cys was predicted by the Cys/Sec method . Overall , the data suggest that yeast 6-O-methylguanine-DNA methylase is a strong candidate for a novel thiol oxidoreductase . Other predictions included ( i ) >gi|6325330| homologous to mammalian PTP ( LTP1 ) , ( ii ) >gi|6321631| glyceraldehyde-3-phosphate dehydrogenase 1 ( GAPDH-1 ) ; ( iii ) >gi|6322409| glyceraldehyde-3-phosphate dehydrogenase 2 ( GAPDH-2 ) ; ( iv ) >gi|6324268| similar to tRNA and rRNA cytosine-C5-methylase ( NOP2 ) ; ( v ) gi|14318558| ubiquinol-cytochrome c oxidoreductase subunit 6 ( QCR6 ) ; ( vi ) >gi|6322155|ref|NP_012230 . 1| capping - addition of actin subunits ( Cap2p ) ; ( vii ) >gi|6321388|ref|NP_011465 . 1| hypothetical ORF ( Ygl050wp ) ; and ( viii ) >gi|6322921|ref|NP_012994 . 1| hydrophilic protein implied in targeting and fusion of ER to Golgi transport vesicles ( BET3 ) . While the functions of some of these proteins are not known , the first three are worth a comment . GAPDH proteins are known to have a catalytic nucleophilic Cys in the active site which is highly sensitive to redox regulation by both thiols and reactive oxygen species [20]–[22] . Oxidized GAPDHs were also found to recover full activity in the presence of thioredoxin [23] or DTT [24] . It appears that these proteins share properties with thiol oxidoreductases , and their active site Cys showed common features with catalytic redox Cys in other enzymes . Low molecular weight protein tyrosine phosphatases ( lwPTP ) share the phosphotyrosine protein phosphatase I-like fold with arsenate reductase ( ArsC ) of gram-positive bacteria and archaea [25] , which are thiol oxidoreductases . These enzymes ( lwPTP and ArsC ) belong to the same superfamily ( phosphotyrosine protein phosphatases I ) . In our original dataset , there were two ArsC proteins ( PDB coded 1LJL and 1Y1L ) , and recognition of their nucleophilic catalytic Cys as redox-active residues may reflect such similarity . With regard to other predictions , no strong evidence to support or reject them as thiol oxidoreductases was obtained , so at least some of these proteins could indeed be thiol oxidoreductases . Finally , one known thiol oxidoreductase among the 149 modeled yeast proteins was not correctly detected by our method . This protein was a monothiol glutaredoxin ( >gi|6319488 , GRX7 ) , which corresponds to the single green circle in Figure 8 located slightly below the cut off value . However , the only contribution to the score for this protein came from the Active Site Similarity method , whereas the Cys Reactivity contribution was zero: Q-site finder did not predict its catalytic Cys in any one of the 10 ranked sites , and the Cys titration curve strictly followed HH behavior . We also submitted the protein to the THEMATICS server , but its catalytic Cys was not predicted as an active site residue . The fact that these independent structure-based calculations , which proved to be quite effective in other analyses , did not recognize the active site and its catalytic Cys could potentially be explained by poor quality of the homology model . It can be argued , that the Similarity part of our algorithm should work better than the Cys reactivity part with scarcely refined ( but still reasonable ) structural models , due to its lesser dependence ( especially for secondary structure and compositional analysis ) on the accuracy of predicted atomic positions; these , in turn , determine titration curves and all types of docking-like calculations ( e . g . , Q-site finder predictions ) . Therefore , poorly refined structural models should affect predictions of the energy-based calculations of the Cys reactivity part of the method to a greater extent . Finally , it should be noted that all other glutaredoxins and glutaredoxin-like proteins could be confidently predicted , which is consistent with the idea that the low score for Cys reactivity in GRX7 may be related to the quality of the structural model rather than inability of the procedure to detect this specific protein . Overall , the method presented in this study showed very good selectivity and specificity . It should find applications in examining protein structures and identifying new thiol oxidoreductases and catalytic redox-active Cys residues in these proteins . During the review of our study , another paper was published [26] that analyzed performance of active site prediction and employed multiple and independent parameters . The authors observed improved performance when the analyses included theoretical titration curves , residue exposure and sequence alignment-based conservation scores . This study and our work suggest that implementing different chemical ( e . g . , titration curves ) , physical ( e . g . , solvent accessibility ) , and biological ( e . g . , sequence alignment ) parameters offers a promising approach to develop efficient tools for protein structure-function predictions . Such approaches may allow the user to achieve specific biologically meaningful insights , a feature often missing in predictive bioinformatics tools . Finally , we suggest that the use of similar approaches may address the challenging issue of prediction of Cys-based modification sites in proteins .
A set of known thiol oxidoreductases present in Saccharomyces cerevisiae was collected by searching literature , analyzing homology to known thiol oxidoreductases from other organisms , and similarities to Sec-containing proteins [12] . Sequence alignments were prepared with PSI-BLAST against the NCBI nonredundant protein database with the following search parameters: expectation value 1e-4 , expectation value for multipass model 1e-3 , and maximal number of output sequences 5 , 000 . Cys conservation for yeast Saccharomyces cerevisiae proteins was determined using an in-house Perl-script by parsing the PSI-BLAST output . Models were built via Swiss Model ( http://swissmodel . expasy . org/ ) and HOMER ( http://protein . cribi . unipd . it/Homer/ ) . VegaZZ 2 . 2 . 0 molecular modeling package was used to check for missing residues , and for minimization runs ( with CHARMM22 force field ) , fixing planarity problems , editing multiple sidechain conformations , adjustment of incorrect geometries , and residue renumbering . Most of these operations were required for successful submission to a server , such as SARIG and H++ . With HOMER analyses , the selection of template for modeling was done using PDB Blast . Calculations of pKa values for dataset proteins were made with H++ server and with PropKa implementation in VegaZZ ( only for calculations shown in Figure S5 , for consistency with the previously published procedure [11] ) . Calculations of accessible surface area were performed with a standalone program , Surface 4 . 0 , downloaded from http://www . pharmacy . umich . edu/tsodikovlab/ . The overall procedure was based on observations of unique properties of active sites and catalytic Cys in thiol oxidoreductases . Each parameter of the method ( Figures 1 ) was optimized for the ability to separate thiol oxidoreductases from other proteins . Optimization of the parameters was carried out on an empirical basis: separately for each subpart of the method we tested different parameters and calculations were then performed against the dataset . The parameters which permitted better resolution of the dataset ( i . e . , better separation of thiol oxidoreductases from set 1 against other reference proteins – set S2 and representatives of the Random Cys set ) were kept and used in the composite procedure . A representative example is given in Supporting information , Figure S2 . To analyze the relative weight distribution for each parameter of the algorithm and how the algorithm performance depends on them , we carried out calculations of a set of proteins ( Test Case , described in the Results section ) not belonging to the dataset . This analysis supported the arrangements of parameter weights shown in Figure 1A ( values in brackets ) . Details of these calculations are shown in Figure S6 , Figure 6 , and Figure 7 . The analysis of the Test Case also allowed us to identify a cut-off value for the scoring function ( described later on in this section ) to efficiently discriminate thiol oxidoreductases form other proteins . The final scoring function , SF , was made up of contributions from each part of the method , as detailed further in this section . The overall method was divided into 2 parts: the first , Active Site Similarity , analyzed structural similarity of test proteins to known thiol oxidoreductases . The second , Cys Reactivity , employed external software for energy-based calculations of Cys properties . Both parts were further subdivided into subparts , as shown in the scheme of the algorithm in Figure 1 , and each is further discussed separately here in the Methods section . Analysis of amino acid composition around Cys was carried out with in-house tools written in Python ( v2 . 4 ) . Detection of amino acids within a cutoff distance ( 6 Å or 8 Å ) from the catalytic Cys sulfur was made considering all residues with one or more of their atoms at a distance equal or lower than the cutoff . A simple graphical representation is shown in Figure 1B . We employed this procedure for all proteins in the dataset ( Table S1 and Table S2 ) , divided into 4 categories: ( i ) thioredoxin fold thiol oxidoreductases ( Trx OxR ) ; ( ii ) non-thioredoxin fold thiol oxidoreductases ( Non Trx OxR ) ; ( iii ) FAD-binding thiol oxidoreductases ( FAD OxR ) ; and ( iv ) proteins with catalytic non-redox Cys ( Non OxR ) . For each protein category , we computed an average amino acid composition . This is shown in graphical form in Figure 2 . Frequency of amino acid occurrence was associated with each amino acid ( the Y value in Figure 2 ) . Consequently , four separate sets of amino acid compositions were built for Trx OxR ( blue bars in Figure 2 ) , Non Trx OxR ( pink bars ) , FAD OxR ( red bars ) , and Non OxR ( green bars ) . We stored information for each protein category in the form of specific dictionaries ( after the Python 2 . 4 datatype actually employed ) , wherein each amino acid received a value of its frequency . In addition , two other sets of non-overlapping randomly selected proteins , one made of 800 PDB structures and the other of 1000 structures , were built . These sets were designated Random Cys set 1 and Random Cys set 2 and represented an average composition of amino acids in the vicinity of Cys in protein structures . Combined together these two sets made up the Random Cys set ( bright yellow bars in Figure 2 ) . We required that these sets have no overlap with datasets S1 and S2 . Also for these two sets , two specific dictionaries were built to store the set-specific amino acidic composition . The use of the six dictionaries to carry out compositional analysis is illustrated with the following example . Given the following short structural profile , i . e . , the amino acid sequence in the active site , Cys-Ala-Val-Glu , and the following dictionaries , When applying each dictionary separately to the profile , three different scores are received , each obtained by appending the average set-specific frequency value corresponding to an amino acid of the profile: In this example , the highest score is obtained with the “Set3” dictionary . If “Set3” corresponds , for instance , to the Trx OxR dictionary , the putative sequence resembles the composition of thiol oxidoreductases . In this case , a value of +0 . 375 is added to the final scoring function , SF . The same happens if the best scoring dictionary is that of Non Trx OxR . If instead the best scoring dictionary is one of non-thiol oxidoreductases , then a zero contribution is given to the SF . These dictionary-based calculations were done with 6 Å and 8 Å distance profiles , thus contributing a maximum value of 0 . 75 to the SF ( 0 . 375 for the 6 Å profile and 0 . 375 with the 8 Å profile ) . Another evaluation formula , limited in this case to the 6 Å distance ( because this distance shows the most significant difference among proteins in the dataset , see Figure 2 ) was based on the following ratio ( W+Y+F+1 . 5C+0 . 5P ) / ( G+H+Q+2M ) , where letters correspond to the single letter code for amino acids and numbers are coefficients . This empirical ratio was chosen as discussed in the Results session . We sampled different coefficients ( 0 . 5 , 1 , 1 . 5 , 2 ) for the amino acid composition in this formula: in each case the same datasets ( S1 and S2 ) were used . The coefficients most efficiently separating thiol oxidoreductases from other proteins were kept . When the formula was applied to a profile for a putative active site , the result ( x ) was analyzed as follows . If x≥1 . 5 , a value of 0 . 25 was given to the SF . If it was between 1 . 5 and 1 . 1 , a value of 0 . 125 was given . Otherwise a zero value was given . For this step in the procedure , we followed a previously published procedure of functional site profiling [13] . Accordingly , we employed ClustalW ( http://www . ebi . ac . uk/Tools/clustalw2/index . html ) standalone version 2 . 0 . 3 for pairwise alignment calculations between a putative profile and each reference profile extracted from our dataset of known thiol oxidoreductases ( Table S1 ) . The evaluation function was carried out with Equation 1 ( 1 ) where SI represents identities ( n is the total number of identities in the alignment ) , Ss strongly conserved residues ( m is the total number of Ss in the alignment ) , Sw weakly conserved residues ( K is the total number of Sw ) , Sg gaps ( j is the total number of Sg ) and N is the number of paired residues in the alignment . Modified parameters were used for Equation 1 ( in parenthesis are the original values , also derived empirically ) : SI = 1 . 0 ( 1 . 0 ) , Ss = 0 . 3 ( 0 . 2 ) , Sw = 0 . 1 ( 0 . 1 ) , Sg = 0 ( −0 . 5 ) . Starting from the original parameters , we sampled different values to determine if it was possible to improve the performance of Equation 1 against our datasets ( S1 , S2 and representatives of the Random Cys sets ) . An example of the performance with modified parameters is given in Figure S2 . We found that an improvement can be reached by underweighting the gaps , and we obtained the best results when the gaps were treated like “non similar” paired residues . Our parameters were more permissive than the original parameters , which were developed and optimized to address a different biological question . It must be stated that the original parameters performed better if the purpose was to detect similarities between more related protein sets ( for example , functional families ) . For the analysis of distantly related proteins , a relaxation of parameters was necessary , and we obtained the best results with our more permissive ad hoc optimized parameters ( Figure S2 ) . The flow of our structural profile analysis was as follows: given a putative active site , pairwise alignments were made with ClustalW between the putative profile and each of the profiles extracted from the known thiol oxidoreductases in our dataset ( Figure 1B ) . Each pairwise alignment was evaluated with Equation 1 . The highest scoring alignment was selected and its score value ( x ) was kept for further analysis . If the best result ( x ) of Equation 1 was lower than 0 . 35 , a null value was given to the SF . If 0 . 35≤x<0 . 4 , a value of 0 . 5 was given . If 0 . 4≤x≤0 . 5 , a value of 1 was given . If 0 . 5<x≤0 . 6 , a value of 1 . 5 was given . If 0 . 6<x≤0 . 75 , a value of 2 was given . Finally , if x>0 . 75 , a value of 2 . 5 was given to the SF . In the latter case , a x value higher than 0 . 75 actually meant that this profile was almost identical to that of a known thiol oxidoreductase . We analyzed the secondary structure content of active sites of each thiol oxidoreductase in our dataset and then compared them with proteins in the control sets . A three-state secondary structure classification ( helix , strand , or coil ) was assigned to each amino acid within 6 Å from the Cys sulfur atom . The evaluation was made as following: ( i ) if the helical content was higher or equal to 35% and the coil content was higher than the strand content , a value of +0 . 5 was given to the SF . ( ii ) If helical content was equal to or higher than 10% and both the coil content and the helix content were higher than the strand content , a value of +0 . 25 was given to the SF . In all other cases , this part of the method received a zero contribution . Thus , the overall contribution to the SF from the Active Site Similarity part of the method ranged from 0 to 4 . 0; once again it must be clearly stated that the latter value occurred only when a putative active site was nearly identical to that of a known thiol oxidoreductase . This part of the method was based on , but not limited to , calculations from two publicly available external servers , Q-site finder ( http://www . modelling . leeds . ac . uk/qsitefinder/ ) and H++ ( http://biophysics . cs . vt . edu/H++/index . php ) . We first discuss the use of Q-site finder . For an overview of this program , we refer the reader to the original paper [14] . To automate the analysis , the predictions of Q-site finder were parsed in html format with an in-house Python tool . We developed an ad hoc scoring of 10 differently ranked sites in the Q-site finder output , derived on an empirical basis ( i . e . , by testing against all dataset proteins ) . A value of 1 . 0 was given to the SF if a Cys was predicted with its sulfur atom among the first 3 sites , as ranked by Q-site finder . A value of 0 . 5 was given to the SF if the sulfur atom was predicted in the 4th , 5th or 6th site . A value of 0 . 25 was given if the sulfur atom was predicted in one of the remaining sites . If a residue was predicted in more than one site , only the highest ranked site was considered . H++ server calculations were performed by choosing the following parameters: the interior dielectric constant ( protein ε ) was set to 20 while the solution dielectric constant was set to 75 . Salinity ( sodium chloride ) of the medium was set to 150 mM . Of the H++ server output files , we considered only the * . pkaout files , which contained a list of all titrable residues with their pKa values . In addition , the files contained two-dimensional coordinates of theoretical titration curves for each residue . Parsing the H++ output file with an ad hoc Python tool , the values for the residue ( in our case , Cys ) were extracted , as well as its calculated pKa . We further considered the Henderson-Hasselbach ( HH ) equation: ( 2 ) Equation 2 can be rewritten to show the charge on the titrable residue ( 3 ) where C− indicates a negative charge on the sulfur atom . Equation 3 is valid for acidic residues , which acquire negative charge upon titration ( e . g . , Cys ) . Substituting H++ pKa-calculated value in Equation 3 and varying the pH between 0 and 18 , the HH behaving curve for an acidic residue was then obtained . Figure 5 shows two examples of superimposition of theoretical titration curves obtained by the H++ server ( red curves ) and the corresponding HH behavior curves ( blue curves ) . The HH behavior curves were viewed as standard behavior of the residue if no perturbations due to other nearby titrable residues occurred [15] . Thus , deviation of the red curve from the blue curve in Figure 5 ( in the titrable range around the pKa ) pinpointed the active site residue [16] , [17] . Automatic evaluation of the deviation between the two curve behaviors could be a challenge [27] . In the present work , we were only interested in a simple way to perform a quick quantification of the deviation between the two curves . Thus , point by point subtraction ( for each pH value ) between the two curves was carried on . These values were integrated over the entire pH range , resulting in the overall difference absolute value ( Σ Δ ) for the deviation between the two curves . Σ Δ was next evaluated to give a contribution to the SF . Cutoff values employed were as follows: if |Σ Δ|≥2 . 0 , then a value of 1 . 0 is given . If 2 . 0>|Σ Δ|≥1 . 5 , a value of 0 . 75 is given . If 1 . 5>|Σ Δ|≥1 . 0 , a value of 0 . 5 is given . If 1 . 0>|Σ Δ|≥0 . 5 , value of 0 . 25 is given . Values below 0 . 5 correspond to a small or null deviation from the typical HH titration behavior ( Figure 5B ) , and consequently a zero value is given to SF . The overall contribution of the Cys Reactivity method to the SF ranged from 0 to 2 . 0 . Finally , in the complete algorithm , the resulting value of the SF ranged from 0 to 6 . 0 ( Figure 1A ) . We found that a value of 2 . 75 was a minimum cutoff value that positively discriminated catalytic redox-active Cys residues ( Figure 7 and Figure 8 ) .
|
Among the 20 amino acids commonly found in proteins , cysteine ( Cys ) is special in that it is present more often than other residues in functionally important locations within proteins . Some of these functions include metal binding , catalysis , structural stability , and posttranslational modifications . Identifying these functions in proteins of unknown function is difficult , in part because it is unclear which features distinguish one Cys function from the other . Among proteins with functionally important Cys , a large group of proteins utilizes this residue for redox catalysis . These proteins possess different folds and are collectively known as thiol oxidoreductases . In this work , we developed a procedure that allows recognition of these proteins by analyzing their structures or structural models . The method is based on the analyses of amino acid and secondary structure composition of Cys environment in proteins , their similarity to known thiol oxidoreductases , and calculations of Cys accessibility , reactivity , and location in predicted active sites . The procedure performed well on a set of test proteins and also selectively recognized thiol oxidoreductases by analyzing the Saccharomyces cerevisiae protein set . Thus , this study generated new information about the structural features of thiol oxidoreductases and may help to recognize these proteins in protein structure databases .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"biochemistry/biocatalysis",
"biochemistry/bioinformatics",
"biochemistry/structural",
"genomics"
] |
2009
|
A Structure-Based Approach for Detection of Thiol Oxidoreductases and
Their Catalytic Redox-Active Cysteine Residues
|
Electron microscopy ( EM ) achieves the highest spatial resolution in protein localization , but specific protein EM labeling has lacked generally applicable genetically encoded tags for in situ visualization in cells and tissues . Here we introduce “miniSOG” ( for mini Singlet Oxygen Generator ) , a fluorescent flavoprotein engineered from Arabidopsis phototropin 2 . MiniSOG contains 106 amino acids , less than half the size of Green Fluorescent Protein . Illumination of miniSOG generates sufficient singlet oxygen to locally catalyze the polymerization of diaminobenzidine into an osmiophilic reaction product resolvable by EM . MiniSOG fusions to many well-characterized proteins localize correctly in mammalian cells , intact nematodes , and rodents , enabling correlated fluorescence and EM from large volumes of tissue after strong aldehyde fixation , without the need for exogenous ligands , probes , or destructive permeabilizing detergents . MiniSOG permits high quality ultrastructural preservation and 3-dimensional protein localization via electron tomography or serial section block face scanning electron microscopy . EM shows that miniSOG-tagged SynCAM1 is presynaptic in cultured cortical neurons , whereas miniSOG-tagged SynCAM2 is postsynaptic in culture and in intact mice . Thus SynCAM1 and SynCAM2 could be heterophilic partners . MiniSOG may do for EM what Green Fluorescent Protein did for fluorescence microscopy .
The most general techniques for imaging specific proteins within cells and organisms rely either on antibodies or genetic tags . EM is the standard technique for ultrastructural localization , but conventional EM immunolabeling remains challenging because of the need to develop high-affinity , high-selectivity antibodies that recognize cross-linked antigens , and because optimal preservation of ultrastructure and visibility of cellular landmarks requires strong fixation that hinders diffusibility of antibodies and gold particles . Thus the target proteins most easily labeled are those exposed at cut tissue surfaces . Replacement of bulky gold particles by eosin enables catalytic amplification via photooxidation of diaminobenzidine ( DAB ) , but eosin-conjugated macromolecules still have limited diffusibility and need detergent permeabilization to enter cells [1] . Genetic labeling methods should overcome many of these shortcomings , just as fluorescent proteins have revolutionized light microscopic imaging in molecular and cell biology [2] . However , no analogous genetically encoded tag for EM contrast has yet proven widely applicable . Metallothionein has been proposed as a genetic tag that can noncatalytically incorporate cadmium or gold [3] , but its main applications to intact cells have been to Escherichia coli conditioned to tolerate 0 . 2 mM CdCl2 for 18 h [4] or 10 mM AuCl for 3 h [4] , [5] . Such high concentrations of heavy metal salts would not seem readily transferable to most multicellular organisms or their cells . Also many higher organisms express endogenous metallothionein , which would contribute background signals unless genetically deleted or knocked down [5] . Horseradish peroxidase can be a genetic label in the secretory pathway but is greatly limited by its requirements for tetramerization , glycosylation , and high Ca2+ , so that it is not functional when expressed in the cytosol [6] . Furthermore , its DAB reaction product tends to diffuse from sites of enzymatic generation , resulting in poorer resolution than immunogold or the reaction product of photogenerated singlet oxygen ( 1O2 , the metastable excited state of O2 ) with DAB [1] , [7] , [8] . The best previous genetically targetable generator of 1O2 was the biarsenical dye ReAsH , which binds to genetically appended or inserted tetracysteine motifs [9] . However , ReAsH has modest 1O2 quantum yield ( 0 . 024 ) ( Figure S1 ) , requires antidotes to prevent cell toxicity , needs careful precautions to reduce nonspecific background signal , and has been difficult to apply to multicellular tissues and organisms [10] . Although fluorescence photooxidation using GFP has been reported [11] , [12] , the 1O2 quantum yield of the naked GFP chromophore is extremely low ( 0 . 004 ) , and the 1O2 quantum yield of the intact protein was yet lower and unquantifiable [13] , presumably because the beta-barrel of the protein shields the chromophore from oxygen . The phototoxic fluorescent protein “Killer Red” [14] is now acknowledged not to work through 1O2 [15] , and we have confirmed that its 1O2 quantum yield is negligible ( Figure S1 ) . Here , we introduce miniSOG , a small , genetically encodable protein module that needs no exogenous cofactors to fluoresce and photogenerate 1O2 with a substantial quantum yield . MiniSOG provides major improvement in correlated light and electron microscopy in cells and multicellular organisms via photooxidation techniques .
The LOV ( light , oxygen , and voltage ) domain of phototropin ( a blue light photoreceptor ) binds flavin mononucleotide ( FMN ) [16] , [17] , which by itself is an efficient singlet oxygen photosensitizer [18] . FMN is ubiquitous in cells and performs indispensable biological functions such as mitochondrial electron transport , fatty acid oxidation , and vitamin metabolism [19] . In phototropin , the excited state energy of FMN is consumed to form a covalent bond with a cysteine [20] . To divert this energy into 1O2 generation , we carried out saturation mutagenesis of the relevant cysteine ( Cys426 ) of the LOV2 domain of Arabidopsis thaliana phototropin 2 ( AtPhot2 ) . To screen for optimal 1O2 production , these site-specific mutants were fused to an infrared fluorescent protein , IFP1 . 4 , which is readily bleached by 1O2 ( Figure S2 ) [21] . Colonies of E . coli expressing the fusion proteins were imaged in the IFP channel ( ex 684/em708 nm ) before and after blue light ( 488 nm ) illumination ( Figure 1A ) . Several colonies showed a decrease of IFP fluorescence from wild-type colonies and two with the largest decrease ( ∼70% ) had the single site substitution of Cys426 to Gly . The small side chain of the glycine residue may provide space around the cofactor that would allow O2 close apposition to FMN for efficient energy transfer . To increase the brightness of the C426G mutant , we also performed saturation mutagenesis of other residues surrounding the chromophore binding site . DNA shuffling of the improved mutants plus random mutagenesis led to a new protein , miniSOG ( 106-residue ) ( Figure 1B and C , Figure S3 ) , which absorbs maximally at 448 nm with a shoulder at 473 nm with extinction coefficients ( 16 . 7±0 . 7 ) ×103 and ( 13 . 6±0 . 5 ) ×103 M−1cm−1 , respectively ( Figure 1D ) . Excitation of miniSOG leads to green emission with two peaks at 500 and 528 nm ( Figure 1D ) . The 1O2 quantum yield of miniSOG ( 0 . 47±0 . 05 ) was measured using anthracene-9 , 10-dipropionic acid ( ADPA ) as 1O2 sensor ( Figure 1E ) [22] . Free FMN was used as the standard for the measurement of 1O2 generation ( quantum yield 0 . 51 ) [10] . MiniSOG was determined by light scattering to be monomeric in solution , with a molecular weight of 13 . 9±0 . 4 kDa , close to the theoretical value of 15 . 3 kDa . Absence of oligomerization was further supported by the good separation by gel filtration of miniSOG from its tandem dimer ( td-miniSOG ) ( Figure S4 ) . Mass spectrometry confirmed that the flavin cofactor is FMN ( Figure S5 ) . Equilibrium dialysis reported a dissociation constant of 170±8 pM ( Table S2 ) , similar to values for some flavoproteins ( e . g . 260±60 pM for a flavodoxin [23] ) and consistent with the crystal structures of LOV domains , which show FMN deeply buried inside the protein core [24] . Furthermore , overexpression of miniSOG in HEK293 cells caused the FMN content to increase ∼3-fold , presumably to keep miniSOG nearly saturated with FMN ( Figures S6–S8 ) , but caused no obvious toxicity in the absence of light ( Table S1 ) . Feedback pathways involving enzymes such as riboflavin kinase ( EC 2 . 7 . 1 . 26 ) and FAD ( flavin adenine dinucleotide ) diphosphatase ( EC 3 . 6 . 1 . 18 ) probably regulate intracellular FMN to titrate endogenous flavoproteins and miniSOG [25] . Riboflavin kinase phosphorylates riboflavin into FMN , while FAD diphosphatase catalyzes the production of FMN from FAD . We used the fluorescence from miniSOG fusion proteins to successfully localize a wide variety of proteins and organelles in cultured mammalian cells ( Figure 2 ) . Its green fluorescence , while modest compared to GFP ( quantum yield of 0 . 37 versus 0 . 6 ) , revealed that labeled components appeared to have correct localizations ( Figure 2A–H ) . Figure 2A shows ER-targeted miniSOG , indicating that miniSOG can work within the secretory pathway . Figure 2B–F show Rab5a , zyxin , tubulin , β-actin , and α-actinin as examples of proteins tagged in cytosolic compartments . Mitochondrial targeting and nuclear histone 2B-fusions ( Figure 2G , H ) show that miniSOG expresses within those organelles . Using the fluorescence and photo-generated 1O2 from miniSOG for fluorescence photooxidation of DAB ( Figure 3A ) , correlated confocal and EM imaging could be performed with several miniSOG fusion proteins ( Figure 3B–E ) , producing excellent EM contrast , efficient labeling , and good preservation of ultrastructure .
The successful localization of a variety of proteins by light and EM in cultured cells as well as mitochondria in C . elegans and SynCAM2 in intact mouse brain demonstrates the value of miniSOG for correlated light and EM localization of specific proteins in cells and multicellular organisms . MiniSOG is advantageous over conventional immuno-gold staining because the protein of interest is genetically tagged before fixation and all subsequent components ( O2 , DAB , and OsO4 ) are small molecules that easily permeate tissues . Tissues or cells can be fixed using established methods for good preservation of ultrastructure without concern for retention of antigenicity . Thus , permeabilizing detergents such as Triton X-100 that degrade membranes to facilitate the diffusion of bulky antibodies and secondary labels are unnecessary . This is demonstrated by the well-preserved ultrastructure in SynCAM-miniSOG labeled mice where unlabeled synapses ( arrowhead ) , nonsynaptic plasma membrane , and synaptic vesicles are clearly observed ( Figure 5 ) . Such landmarks were essential to assign the precise location of the SynCAMs . While super-resolution fluorescence techniques [38]–[40] could provide improved localizations , each landmark of interest would need to be labeled with fluorophores emitting at different color . MiniSOG probes have several advantages over other correlated LM/EM probes . MiniSOG needs no exogenous cofactors and produces 1O2 with about 20 times higher quantum efficiency than ReAsH on a tetracysteine motif . Therefore , miniSOG photooxidation has considerably better sensitivity and lower background than ReAsH labeling . MiniSOG is much smaller than GFP , and unlike GFP can mature and become fluorescent in the absence of O2 . GFP-based photooxidation is very difficult due to its extremely low 1O2 quantum yield [13] . Genetically encoded horseradish peroxidase is tetrameric and far larger than GFP , only becomes functional inside the secretory pathway [6] , and produces relatively diffuse precipitates [1] , [7] , [8] . Metallothionein fusions would seem most appropriate for purified macromolecules [3] , because imaging of intact cells requires them to survive prolonged incubation in high concentrations of Cd2+ or Au+ [4] , [5] and not to express endogenous metallothionein . Our results with miniSOG fusions demonstrate that SynCAM1 and SynCAM2 are localized to pre- and post-synaptic membranes , respectively , and these observations are consistent with the reported strong heterophilic interaction between SynCAM1 and SynCAM2 in the formation of trans-synaptic structures [41] . The presynaptic membrane localization of SynCAM1 is also consistent with the recent report that SynCAM1 is expressed in growth cones in the early developmental stages of mouse brain and is involved in shaping the growth cones and the assembly of axo-dendritic contact [41] . Analogous trans-synaptic pairs include neurexin/neuroligin [42] , EphrinB/EphB , and netrinG/netrin-G ligand ( NGL ) . New synaptic proteins continue to be reported , such as leucine rich repeat transmembrane proteins ( LRRTMs ) , NGL-3 , and leukocyte common antigen-related ( LAR ) [43] , [44] . The large variety of these molecules may be necessary to establish and support the great diversity of neuronal synapses; dissecting their locations within synapses will be a complex task . As demonstrated here , our miniSOG-based photooxidation technique provides a method to determine the detailed distribution of these and other important macromolecules . In combination with SBFSEM , miniSOG fusion proteins should find wide applications in the ultrastructural localization of proteins , including 3-d reconstruction of neuronal circuits by large scale automated SBFSEM to mark cells of interest and trace them across large numbers of sections ( Figure S13 ) [37] . Additionally , a logical next step will be to further enhance the preservation of cellular ultrastructure in these types of specimens by combining chemical fixation and high pressure freezing [45] with photooxidation using miniSOG . Spatiotemporally controlled local photogeneration of 1O2 should also be useful for rapidly inactivating proteins of interest [46] , reporting protein proximities over tens of nanometers [47] by 1O2 transfer from a SOG to a 1O2 sensitive fluorescent protein ( e . g . IFP1 . 4 ) and ablating cells by photodynamic damage . Thus , further development and application of miniSOG using 1O2 generation should greatly expand its utility in imaging and functional studies .
A gene encoding LOV2 domain of Phototropin 2 with codons optimized for E . coli was synthesized by overlap extension PCR [48] . Genetic libraries were constructed by saturation and random mutagenesis and DNA shuffling [21] . Mutants were fused to IFP1 . 4 by overlap extension PCR and cloned into a modified pBAD vector containing the heme oxygenase-1 gene from cyanobacteria [21] . Libraries were expressed in E . coli strain TOP10 and screened by imaging the agar plates with colonies in the IFP channel before and after blue light illumination [21] . Protein purification and spectroscopic characterization experiments were done as described [49] . DNA encoding miniSOG with codons optimized for mammals was synthesized by overlap extension PCR [48] . MiniSOG fusions were cloned into pcDNA3 . 1 vector . HEK293 and HeLa cells were transfected with miniSOG or chimera cDNAs using Fugene , then imaged 24–48 h later . Cultured cortical neurons were transfected by Amaxa electroporation ( Lonza AG , Germany ) and imaged 1–2 wk later . Transfected cells cultured on glass bottom culture dishes ( P35G-0-14-C , MatTek Corp . , Ashland , MA ) were fixed with 2% glutaraldehyde ( Electron Microscopy Sciences , Hatfield , PA ) in pH 7 . 4 0 . 1 M sodium cacodylate buffer ( Ted Pella Inc . , Redding , CA ) for 30–60 min , rinsed several times in chilled buffer , and treated for 30 min in blocking buffer ( 50 mM glycine , 10 mM KCN , and 5 mM aminotriazole ) to reduce nonspecific background reaction of diaminobenzidine ( DAB ) . Confocal images were taken with minimum exposure using a BioRad MRC-1024 inverted confocal microscope or similar inverted fluorescence microscope to identify transfected cells and for correlative light microscopic imaging . Detailed protocols for performing fluorescence photooxidation of DAB have been published [2] , [6] . It is important to use an inverted microscope to ensure direct open access to the DAB solution . An objective of numerical aperture ≥0 . 7 is desirable to maximize illumination intensity . For photooxidation , diaminobenzidine tetrahydrochloride ( Sigma-Aldrich , St . Louis , MO ) was freshly diluted to 1 mg/ml in 0 . 1 M sodium cacodylate buffer , pH 7 . 4 , filtered through a 0 . 22 micron syringe filter ( Millipore ) , and placed on ice and added to the cells . The region of interest was identified by the fluorescence and an image recorded with care not to bleach the area . A small tube attached to an oxygen tank was placed near the top of the dish and a stream of pure oxygen was gently blown continuously over the top of the solution . Alternately , the DAB solution on ice was bubbled with oxygen and the solution in the dish refreshed every few minutes . The samples were then illuminated using a standard FITC filter set ( EX470/40 , DM510 , BA520 ) with intense light from a 150W xenon lamp . Illumination was stopped as soon as a very light brown reaction product began to appear in place of the green fluorescence as monitored by transmitted light ( typically 2–10 min , depending on the initial fluorescence intensity , the brightness of the illumination , and the optics used ) . Care was taken to avoid overreacting the samples , as this can lead to overstaining and the degradation of ultrastructure in the region of photooxidation . Multiple areas on a single dish could be reacted if the solution was refreshed every few minutes . The cells were then removed from the microscope and washed in chilled buffer ( 5×2 min ) and post-fixed in 1% osmium tetroxide ( Electron Microscopy Sciences ) in 0 . 1 M sodium cacodylate buffer for 30 min on ice . Cells were washed in chilled buffer twice and rinsed in distilled water , then en bloc stained with 2% aqueous uranyl acetate ( Ted Pella Inc . ) for 1 h to overnight at 4°C . The samples were then dehydrated in a cold graded ethanol series ( 20% , 50% , 70% , 90% , 100% , 100% ) 2 min each , rinsed once in room temperature anhydrous ethanol , and infiltrated in Durcupan ACM resin ( Electron Microscopy Sciences ) using 1∶1 anhydrous ethanol and resin for 30 min , then 100% resin 2×1 h , then into fresh resin and polymerized in a vacuum oven at 60°C for 48 h . Transgenic worms were made by injection of cDNAs of mitochondrially targeted miniSOG driven by myo-3 promoter at 50 ng/µl . The worms were chemically fixed with 2% glutaraldehyde , washed , and blocked as described above . The cuticle was sharply cut to allow diffusion of DAB into the inner body for photooxidation . After confocal imaging and fluorescence photooxidation , the worms were processed for EM imaging as described above . Endotoxin-free DNA ( ∼3 µg ) of the SynCAM2-miniSOG fusion construct was delivered into the lateral ventricle of embryos by in utero electroporation [50] . The offspring at p7 or p21 were anesthetized and fixed by vascular perfusion as previously described [51] with Ringer's solution followed by 4% formaldehyde made fresh from paraformaldehyde ( Electron Microscopy Sciences ) in 0 . 15 M cacodylate buffer . Brains were removed and placed in the same fixative at 4°C for 1 h for p21 and overnight for p7 . In this case we avoided glutaraldehyde in combination with paraformaldehyde due to the increased autofluorescence that occurs with glutaraldehyde . The autofluorescence obscured miniSOG fluorescence and made it impossible to locate transfected neurons in the brain slices for photooxidation . Brains were then sliced to 100 µm sections using a vibratome ( Leica ) . Areas of interest were identified by confocal microscopy . The sections were then postfixed with 2% glutaraldehyde for 30 min , rinsed in cold buffer , blocked , and then photooxidized as described above . Subsequent procedures for EM processing were similar to those described above except the vibratome sections were resin embedded between two liquid release agent coated glass slides ( Electron Microscopy Sciences ) . Photooxidized areas of embedded cultured cells were identified by transmitted light and the areas of interest were sawed out using a jeweler's saw and mounted on dummy acrylic blocks with cyanoacrylic adhesive . The coverslip was carefully removed , ultrathin sections were cut using an ultramicrotome , and electron micrographs recorded using a 1200 TEM ( JEOL ) operating at 80 keV . For tissue sections , one of the glass coverslips was removed using a razorblade and the area of interest identified by transmitted light microscopy . The tissue was removed from the slide , mounted , sectioned , and imaged as above . For electron tomography , 0 . 5 micron thick sections of cells expressing photooxidized H2B-miniSOG were cut and imaged using a 4000 IVEM ( JEOL ) operated at 400 keV . Images were tilted and recorded every 2° from ±60° to −60° . The image stack was aligned and reconstructions were obtained using R-weighed back projection methods with the IMOD tomography package . For serial block face scanning electron microscopy , a 3View system ( Gatan Inc . , Pleasanton , CA ) mounted in a Quanta FEG scanning electron microscope ( FEI Company , Eindhoven , The Netherlands ) was employed . Imaging was performed as previously described [37] . Individual image planes were hand segmented to outline the plasma membrane of the target neuron and denote labeled post-synaptic densities , then thresholded and projected using Amira ( Visage Imaging , Germany ) .
|
Electron microscopy ( EM ) once revolutionized cell biology by revealing subcellular anatomy at resolutions of tens of nanometers , well below the diffraction limit of light microscopy . Over the past two decades , light microscopy has been revitalized by the development of spontaneously fluorescent proteins , which allow nearly any protein of interest to be specifically tagged by genetic fusion . EM has lacked comparable genetic tags that are generally applicable . Here , we introduce “miniSOG” , a small ( 106-residue ) fluorescent flavoprotein that efficiently generates singlet oxygen when illuminated by blue light . In fixed tissue , photogenerated singlet oxygen locally polymerizes diaminobenzidine into a precipitate that is stainable with osmium and therefore can be readily imaged at high resolution by EM . Thus miniSOG is a versatile label for correlated light and electron microscopy of genetically tagged proteins in cells , tissues , and organisms including intact nematodes and mice . As a demonstration of miniSOG's capabilities , controversies about the localization of synaptic cell adhesion molecules are resolved by EM of miniSOG fusions in neuronal culture and intact mouse brain .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology",
"bioengineering",
"biochemistry",
"biology",
"molecular",
"cell",
"biology",
"neuroscience",
"engineering"
] |
2011
|
A Genetically Encoded Tag for Correlated Light and Electron Microscopy of Intact Cells, Tissues, and Organisms
|
Glycolytic potential ( GP ) in skeletal muscle is economically important in the pig industry because of its effect on pork processing yield . We have previously mapped a major quantitative trait loci ( QTL ) for GP on chromosome 3 in a White Duroc × Erhualian F2 intercross . We herein performed a systems genetic analysis to identify the causal variant underlying the phenotype QTL ( pQTL ) . We first conducted genome-wide association analyses in the F2 intercross and an F19 Sutai pig population . The QTL was then refined to an 180-kb interval based on the 2-LOD drop method . We then performed expression QTL ( eQTL ) mapping using muscle transcriptome data from 497 F2 animals . Within the QTL interval , only one gene ( PHKG1 ) has a cis-eQTL that was colocolizated with pQTL peaked at the same SNP . The PHKG1 gene encodes a catalytic subunit of the phosphorylase kinase ( PhK ) , which functions in the cascade activation of glycogen breakdown . Deep sequencing of PHKG1 revealed a point mutation ( C>A ) in a splice acceptor site of intron 9 , resulting in a 32-bp deletion in the open reading frame and generating a premature stop codon . The aberrant transcript induces nonsense-mediated decay , leading to lower protein level and weaker enzymatic activity in affected animals . The mutation causes an increase of 43% in GP and a decrease of>20% in water-holding capacity of pork . These effects were consistent across the F2 and Sutai populations , as well as Duroc × ( Landrace × Yorkshire ) hybrid pigs . The unfavorable allele exists predominantly in Duroc-derived pigs . The findings provide new insights into understanding risk factors affecting glucose metabolism , and would greatly contribute to the genetic improvement of meat quality in Duroc related pigs .
In past decades , thousands of quantitative trait loci ( QTLs ) have been detected for economically important traits in livestock through genetic linkage studies [1] . The recent availability of livestock genome sequences and high-density SNP chips has allowed detection of significant association of nucleotide polymorphisms with complex traits , and effective identification of causal mutations for some monogenic traits [2]–[4] . Despite these progresses , uncovering the quantitative trait genes ( QTGs ) or nucleotides ( QTNs ) for complex traits remains a challenging task . Only a handful of QTNs have been convincingly identified in livestock [5]–[7] . More recently , several studies in human , mouse and Drosophila have shown that the integration of phenotypic traits , genetic and gene transcript data enables researchers to identify expression QTL ( eQTL ) , untangle gene-based regulatory networks , infer relationship between gene expression levels and phenotypic traits , and thereby detect novel trait-causing genes [8]–[10] . Therefore , the integrative analysis would play a key role in acquiring the knowledge of mechanisms responsible for livestock complex traits . Indeed , some researchers have identified a number of promising candidate genes for muscle traits and blood lipid traits of pig by integrative analyses of GWAS ( or linkage mapping ) , eQTL and trait-correlated expression [11]–[14] . Glycogen storage diseases ( GSD ) characterized by defects in glycogen metabolism and excess glycogen stored in liver and muscle are multifactorial disorders . Both human and animals suffer from GSD . Agricultural researchers often measure the glycogen content or glycolytic potential [GP = 2× ( glucose + glycogen + glucose-6-phosphate ) + lactate] in skeletal muscle of farm animals at slaughter . However , instead of the GSD diagnostic indicator , the GP value is mainly used for the prediction of meat quality development during the conversion of muscle to meat , because GP is a determinant of multiple meat quality characteristics , such as pH , color , water holding capacity ( drip loss ) , tenderness and processing yields [15] , [16] . GSD or extreme GP phenotype can be caused by genetic variation of various enzymes or transporters , which are involved either directly in the synthesis or breakdown of glycogen or in the utilization of its catabolite , glucose-1-phosphate [17] . To date , only one responsible gene , PRKAG3 , has been elaboratively evidenced to impact glycogen and GP levels in Hampshire and its related synthetic lines [18] , [19] . Although more than 10 different QTLs for the trait have been reported ( http://cn . animalgenome . org/cgi-bin/QTLdb/index ) , QTGs or QTNs underlying these QTLs remain unexplored . We have previously identified a major QTL for GP and pH values at 42 cM on chromosome 3 in a large scale White Duroc × Erhualian F2 intercross [20] . To decipher the molecular basis of the GP QTL , we herein performed an integrative genetic analysis by utilizing extensive data sets of GP-related traits , high-density genotypes and gene expression profiling from three experimental populations . We show compelling evidence that a splice mutation in the PHKG1 gene is the QTN underlying the major QTL effect on GP and its related traits .
We first performed a genome-wide association study ( GWAS ) for GP and its components including residual glycogen & glucose ( RG ) , glucose-6-phosphate ( G-6-P ) and lactate on the White Duroc × Erhualian F2 intercross , in which 877 phenotyped F2 individuals and its parents/grandparents were genotyped by using Illumina Porcine SNP 60K Beadchips [21] . The quality control filtering and data processing of the GWAS data are described in the Methods . Quantile-quantile plots with genome control λGC values are shown in Figure S1 . We found no evidence of systematic inflation of association test results . Consistent with our previous QTL results [20] , the GWAS results demonstrated that Sus Scrofa chromosome 3 ( SSC3 ) contained the most genome-wide significant locus ( P = 5 . 85×10−22 ) for both GP and RG with the top SNP ss131031160 ( pSNP ) at 17 . 09 Mb ( Figure 1 ) . However , this lead SNP was not associated with the glycolysis intermediate product G-6-P and end-product lactate ( Figure S2 ) . These results suggest that the underlying QTG likely influences the conversion between glycogen and glucose ( or G-6-P ) rather than the conversion between G-6-P to lactate . The pSNP ss131031160 explains 19 . 6% of the phenotypic variance in RG of the F2 population . To validate and fine map the SSC3 QTL for RG , we conducted a second GWAS on 433 Sutai pigs , a Chinese synthetic line derived from a cross between Duroc and Taihu including Erhualian and Meishan after more than twenty-year selection . Besides 62163 SNPs on the Illumina Porcine SNP 60K Beadchip , 53 SNPs derived from DNA sequence comparison between Erhualian and Duroc ( see Materials and Methods ) within a 1-Mb region surrounding the top pSNP were genotyped for these Sutai pigs . As expected , we confirmed the strong association signal on SSC3 in the Sutai population . The pSNP ss131565361 ( P = 9 . 06×10−19 ) at 16 . 92 Mb ( Figure 1 ) explains 53 . 6% of the RG variance . This locus also significantly influenced ultimate pH ( measured 24 hours after slaughter ) and drip loss ( Figure S2 ) . Based on the LOD drop off 2 , the empirical confidence intervals of the QTL in the F2 and Sutai populations was 920 kb ( 16 . 92–17 . 84 Mb ) and 630 kb ( 16 . 47–17 . 10 Mb ) respectively ( Figure 2A ) . Therefore , the most likely QTL interval was their overlapping region of 180 kb ( 16 . 92–17 . 10 Mb ) . This interval contains 7 annotated genes: GUSB , VKORC1L1 , NUPR1L , CHCHD2 , PHKG1 , SUMF2 and CCT6A ( Figure 2A ) . Using the data of digital gene expression profiles ( DGE ) tested in longissimus muscle samples from 497 F2 animals , we identified genome-wide eQTL for the 7 annotated genes in the critical region . We operationally defined cis-eQTL as any association between a gene expression and SNPs within 2 Mb of the gene location . We found 3 cis-eQTL each for PHKG1 , SUMF2 and GUSB ( Figure 2B ) . Intriguingly , the lead SNP for the cis-eQTL affecting PHKG1 expression was identical to the top pSNP ( ss131031160 ) for GP in the GWAS on the F2 population . The major allele ( G ) at this SNP was associated with lower residual glycogen and higher expression of PHKG1 ( Table 1 and Figure 2C ) . PHKG1 encodes a catalytic subunit of the phosphorylase kinase ( PhK ) , which can mediate glycogen breakdown . Therefore , the co-localization of the top SNP in both GWAS and eQTL mapping coupled with the biological function highlights PHKG1 as the most likely QTG underlying the major locus on SSC3 . To search for coding variants in the PHKG1 gene , we isolated and sequenced PHKG1 cDNA from muscle samples of 6 F2 individuals representing three genotypes at the pSNP ss131031160 ( 2 GG , 2 GA and 2 AA animals ) . In total , we detected 14 polymorphisms ( Table S1 ) . Of note , we found a 32-bp deletion/insertion ( c . del/ins32; Figure 3A&B ) polymorphism at exon10 that alters the open-reading frame and causes a premature stop codon , leading to a truncated and nonfunctional protein product . To test if the 32-bp deletion was also present in the genomic DNA ( gDNA ) , we sequenced the 140 bp genomic region encompassing the deletion using gDNA samples of the above-mentioned 6 F2 animals . We found only one single nucleotide substitution ( C>A ) in the region . This SNP ( g . 8283C>A ) lies 5 bp upstream of the c . del/ins32 ( Figure 3C&D ) , where the pyrimidine ( C or T ) is highly conserved among vertebrates , including chicken , mouse , dog , cow , sheep and human . The C→A nucleotide transvertion may weaken the strength of the pyrimidine-rich signal near the 3′ end of the PHKG1 intron 9 , which is known to correlate with splicing efficiency [22] . Using a web-available tool Alternative Splice Site Predictor ( ASSP , http://wangcomputing . com/assp/index . html ) , we found that the splice site score ( 1 . 652 ) of the mutant sequence was much lower than the wild-type counterpart ( 3 . 659 ) , and even lower than the default cutoff value ( 2 . 2 ) for acceptor sites set in the predictor . Therefore , the mutation appears to attenuate or inhibit the role of the constitutive acceptor splice site and this consequently evokes another cryptic acceptor at 32 bp downstream of the mutation , which results in a loss of 32 bp in mature mRNA during PHKG1 transcription ( Figure 3E ) . To test if the 32-bp deletion in exon 10 was directly caused by the SNP g . 8283C>A , the effect of the variant on splicing was assessed using a minigene splicing assay ( Figure S3 ) . Two minigene expression vectors carrying either the wild-type or the mutant PHKG1 g . 8283C>A segment were constructed and transiently transfected into HeLa cells and 293T cells ( Figure S3A ) . The minigene transcripts in these transfected cells were analyzed by RT-PCR , using specific primers complementary to exon 9 and exon 10 of the minigene . We found two amplicons of 78 bp and 62 bp from the mutant construct and only one amplicon of 94 bp from the wild-type construct ( Figure S3B ) . Sanger sequencing analysis revealed that the two truncated amplicons corresponded to two aberrant splicings of the first 16 and 32 nucleotides ( nt ) at 5′ end of exon 10 ( Figure S3C-E ) . The presence of novel aberrant splicing of 16-nt may be due to that the minigene constructs only contain partial PHKG1 sequence or there is a special splicing factor in the transfected cells . Anyway , the result clearly demonstrates that the variant PHKG1 g . 8283C>A is responsible for the aberrant splicing of 32-nt observed in vivo . To obtain further evidence for the causality of the candidate QTN ( SNP g . 8283C>A ) , we conducted the concordance test between the SNP genotypes and the QTL genotypes on 9 parental boars ( 6 F1 boars and 3 Sutai boars ) . The QTL genotypes of these boars were determined by the marker-assisted segregation analysis ( see Materials and Methods ) . We found that the SNP genotypes were completely concordant with the QTL genotypes in these boars ( Table S2 ) . In contrast , the two top pSNPs ss131031160 and ss131565361 in the GWAS exhibited disconcordance with the QTL genotypes in the 9 parental sires . Concordantly , the association of the g . 8283C>A SNP with RG phenotype was strongest among all SNPs genotyped in Sutai pigs , and was at the same significance level as that of the top GWAS SNP ss131031160 in the F2 population due to their complete linkage disequilibrium ( Table S3 ) . In addition , we re-sequenced a 10-kb segment covering 1 kb upstream of the PHKG1 gene to its 3′ end on all 9 sires ( 6 F1 and 3 Sutai sires ) with deduced QTL status . A total of 142 variants were identified ( Table S4 ) . We found that 7 Q chromosomes of these boars shared the same haplotype while 11 q chromosomes corresponded to multiple divergent haplotypes ( Figure S4 ) . Surprisingly , a q haplotype from Sutai boars was nearly identical to the Q haplotypes except for three variants , of which only one ( g . 8283C>A ) showed co-segregation with QTL genotypes across all the 9 sires ( Figure S5 ) . This strongly supports the causality of the g . 8283C>A mutation . Haplotype analysis showed that no other variants within the PHKG1 region were in complete LD with the SNP g . 8283C>A across all experimental populations . Based on that , we tried to determine whether other variants can also result in partial QTL effect . When the SNP g . 8283C>A was included as a fixed effect in the model , the QTL effects on PHGK1 expression and RG trait vanished in these populations ( Figure S6A ) . Furthermore , we divided the Sutai pigs into three genotype groups ( AA , CA , CC ) . No eQTL effect was detected within each group ( Figure S6B ) . It thus suggests that even there is another regulatory SNPs , their effects are likely negligible . Aberrant mRNA , like the truncated PHKG1 transcript caused by the g . 8283C>A SNP , tend to be degraded by a known mechanism of nonsense-mediated mRNA decay ( NMD ) in the cell . To analyze whether the mutation interferes with PHKG1 mRNA expression levels , qRT-PCR experiments were performed on total RNA isolated from 293T cells transiently transfected by the wild-type and mutant PHKG1 minigenes . The mutant minigene produced nonsense mRNAs at 56% level of normal expression ( Figure S7 ) . The finding indicates that the PHKG1-32del mRNA bearing the premature termination codon was most likely degraded by NMD . In fact , electropherogram of RT-PCR products amplified from PHKG1 mRNA in homozygous animals showed that the intensity of the mutant DNA band of 114 bp was much lower than the normal band of 146 bp ( Figure 3A ) , implying NMD of the mutant PHKG1 mRNA . Accordingly , the PHKG1 cDNA sequence chromatograms illustrated that the fluorescence intensity of wild-type allele ( Wt or q ) were 2–3 fold stronger than that of the mutant allele ( Mt or Q ) in animals heterozygous for the g . 8283C>A SNP ( Figure 3F ) . To more accurately estimate the difference in abundance between Wt and Mt transcripts , we designed two pairs of primers: one ( Common-5′-FP/RP ) for amplification of both transcripts , and the other ( Wt-3′-FP/RP ) for the specific amplification of Wt transcript ( Figure 4A ) . After performing qRT-PCR with the two primer sets , we quantified the levels of total mRNA transcripts relative to wild-type transcripts . In heterozygotes , the ratio of ( Mt+Wt ) to Wt transcripts was 1 . 4∶1 ( Figure 4B ) , suggesting that the 60% of Mt transcripts were degraded by NMD . Interestingly , we found that mutant homozygotes ( AA or QQ ) had PHKG1 Wt , as RT-PCRs using the primers specific for the Wt generated amplicons corresponding to Wt in these mutant homozygotes ( Figure 4C ) . We further showed that , only about one-eighth of PHKG1 transcripts was Wt ( Figure 4B ) . The result suggests that the g . 8283C>A mutation could strongly decrease but not completely abrogate the original splicing form . Consistently , the PHKG1 Wt transcript level is highest in muscle samples from CC animals , followed by AC and AA individuals ( Figure 4C ) . Similar tendency was observed for the PHKG1 Wt protein level in the three genotypes by Western-blot analysis ( Figure 4D ) . Thus , it is evident that the g . 8283C>A mutation affects the expression of PHKG1 at both transcription and translation levels . PHKG1 is a critical enzyme in the glycogen metabolism . We expected that the PHKG1 mRNA expression level would be significantly associated with the RG phenotype . However , we did not observe such strong correlation ( r = −0 . 08 , P = 0 . 106; Figure 5B ) using the DGE data in the F2 population . We then made a close examination on the DGE data . We found that the DGE tag for PHKG1 was located in a region upstream of the 32-bp deletion , which therefore can not distinguish Wt from Mt transcripts . To correct for the biased effect of the abnormal Mt transcripts , we further used qRT-PCR to measure the Wt level on 117 F2 individuals and 104 Sutai pigs , of which the number of CC , CA and AA animals at the g . 8283C>A locus are nearly identical ( Figure 5A ) . We then examined the correlation between the qPCR-data and the RG phenotypes . As a result , the PHKG1 Wt ( functional ) transcript level was significantly correlated with RG phenotype ( r≤−0 . 4 , P<10−5 ) in the two populations ( Figure 5B ) . Such strong correlation were not detected for any other cis-regulated genes within the critical region of the SSC3 QTL ( Figure S8 ) , strengthening the causal relationship between PHKG1 and RG . PHKG1 is a catalytic subunit of the phosphorylase kinase ( PhK ) . The g . 8283C>A splice mutation in the PHKG1 gene thus likely influence the enzymatic activity of PhK and glycogen phosphorylase . To verify the assumption , we tested the enzymatic activity of PhK in 18 muscle samples―6 per genotype group ( CC , AC , and AA ) . As expected , the AA group showed>6-fold reduction in enzyme activity as compared to the CC and AC groups ( Figure 6 ) . It is reasonable to speculate that reduced PhK enzyme's activity would lead to slow breakdown of glycogen in muscle , which in turn cause excess accumulation of glycogen in the tissue . This is consistent with the SSC3 QTL effect on GP or RG trait . Considering the inter-relationship of GP with other meat quality attributes , we evaluated the effects of the PHKG1 g . 8283C>A mutation on all meat quality traits measured in the 864 F2 individuals from the White Duroc × Erhualian intercross , 431 Sutai pigs and 140 three-way hybrid DLY [Duroc × ( Landrace × Yorkshire ) ] pigs . In the F2 population , there was a tendency towards lower ultimate pH and higher drip loss in AA pigs with higher GP compared to CA and CC individuals ( the mean values of pH 24h in AA , CA and CC groups were 5 . 70 , 5 . 72 and 5 . 77 , respectively; for drip loss: 1 . 01% , 0 . 85% and 0 . 92% , respectively ) , although the mean differences did not reach statistical significance , partially due to a low frequency ( 5% ) of the AA genotype in the population . In Sutai pigs , each genotype group ( AA , AC or CC ) at the PHKG1 g . 8283C>A site has more than 100 individuals . Significant effects of the causal mutation were observed on almost all meat quality traits in this population ( Tables 2 and S5 ) . Especially , the RG level in the longissimus muscle ( LM ) of AA animals was 4 times higher ( P = 9 . 03×10−54 ) than those in CC animals . Coincidently , drip loss , rate of pH decline and Minolta a* and b* were higher ( P<0 . 01 ) in AA pigs than CC pigs . AA pigs also had lower ( P<0 . 001 ) intramuscular fat content ( IMF ) and marbling score compared to CC pigs . In the DLY hybrid commercial population , all 140 individuals were genotyped for the PHKG1 g . 8283C>A mutation and 53 surrounding SNPs using the OpenArray platform ( see Materials and Methods ) . Again , we observed the significant effects of the g . 8283C>A mutation on RG , pH and drip loss ( Table 2 ) . Moreover , this mutation showed stronger associations with these traits than any other surrounding SNPs ( Figure S9 ) . These results indicate that the A allele has unfavorable effects on these meat quality traits . To reveal the allele frequency of the PHKG1 g . 8283C>A mutation in diverse pig breeds , we genotyped this mutation in a broad panel of 629 animals representing 5 European commercial breeds , 2 Chinese domestic breeds , and wild boars from China and Europe . The A allele causing excess glycogen content occurred at high frequency ( 0 . 70 ) in White Duroc and at medium frequency ( 0 . 32 ) in Red Duroc , but it was nearly absent in other domestic and wild breeds ( <0 . 03; Table 3 ) . The PHKG1 mutant allele was absent in wild boars , suggesting that the mutation likely happened after domestication . However , due to limit number of wild boars examined in this study , we cannot rule out the possibility that it is a standing variation .
To date , only a handful of QTG and QTN have been identified for complex traits in farm animals . To the best of our knowledge , this is the first study that has used a system genetics approach including GWAS , eQTL mapping and causality modeling to identify QTG and QTN for complex traits in pigs . Our study supports the PHKG1 gene as a QTG for GP-related traits based on the following findings: ( 1 ) GWAS on the F2 and Sutai populations enable us to define the major QTL for GP within an interval of 180-kb on SSC3 , which contains only 7 genes including PHKG1 . ( 2 ) Of three positional candidate genes with cis-eQTLs signals , only PHKG1 has the cis-eQTL peak SNP that is identical to the pQTL peak SNP . ( 3 ) PHKG1 is a catalytic subunit of the phosphorylase kinase ( PhK ) , which is critical to glycogen degradation . ( 4 ) The wild-type transcript level of PHKG1 was significantly correlated to glycogen content in muscle . Furthermore , our study shows the following evidences for the PHKG1 g . 8283C>A mutation as QTN underlying the SSC3 QTL effect: ( 1 ) The mutation caused abnormal splicing of PHKG1 mRNA , resulting in a shift in the reading frame with a premature stop codon . ( 2 ) The aberrant mRNA transcripts were diminished by NMD , which reduced the PHKG1 protein level and led to PhK enzyme deficiency . ( 3 ) The mutation shows the complete concordance between their genotypes and the deduced QTN genotypes across all parental boars . No other variants in the PHKG1 gene exhibited such concordance . ( 4 ) This mutation has a consistent and significant effect on GP-related traits across all tested populations . Here , we illustrate that the QTN ( g . 8283C>A ) is a splice site mutation affecting both transcription and translation levels of the PHKG1 gene , which has at least three implications . One is that cis-eQTL mapping for annotated genes residing the QTL region can not only contribute to identification of regulatory QTNs , but also benefit characterization of protein-altering QTNs including splice and nonsense mutations that affect transcript levels by NMD , just like our identified QTN . Another implication is that if a gene is subjected to alternative splicing , it is necessary to determine the levels of its different transcripts ( instead of only the total amount of these transcripts ) by deep RNA sequencing and then examine their individual relationship with phenotypic traits . The third one is that we could identify a cis QTL for PHKG1 protein level that overlaps with the mapped cis-eQTL and pQTL on SSC3 if a big data set on protein abundance was available , and find a strong relationship between protein level and GP-related traits . This information could add a new dimension for the search of QTG . Several studies have recently demonstrated the feasibility of high-throughput proteome quantification and revealed the variation and genetic control of protein abundance in humans and mice [23] , [24] . Hopefully , whole proteome analysis will be more efficient and routinely added to integrative genomic analysis to accelerate the identification of QTG and QTN for complex traits in livestock . Phosphorylase kinase ( PhK ) is comprised of four different subunits with a stoichiometry of ( αβγδ ) 4; α , β , and δ are regulatory , while γ is catalytic . Each of these subunits has isoforms or splice variants differentially expressed in different tissues . Mutations in 4 PhK subunit genes ( PHKA1 , PHKA2 , PHKB and PHKG2 ) have been implicated in low PhK activity in liver and/or muscle [25]–[29] . No variant in the muscle isoform of the PhKγsubunit ( PHKG1 ) has been reported for muscle PhK deficiency [17] . To our knowledge , this study is the first one to confirm the association of the PHKG1 mutation with PhK deficiency , muscle glycogenosis and meat quality traits in pigs . Pork with high GP ( >180 µmol/g ) often has low ultimate pH and water holding capacity , and is therefore called “acid meat” . The R225Q mutation in PRKAG3 gene was the first identified causal mutation for acid meat [19] . This gain-of-function mutation causes an increased glucose uptake and glycogen synthesis in skeletal muscle [30] , [31] . Its unfavorable allele ( 225Q ) is dominant and specifically present in Hampshire and related breeds [19] . In contrast , the PHKG1 g . 8283C>A mutation that we identified is a loss-of-function mutation causing the defect in glycogen degradation . This variant occurs predominantly in Duroc or Duroc-crossed pigs . The mutant allele A appears to be partially recessive , since the average RG value of AC heterozygotes approximates to that of CC homozygotes rather than AA homozygotes ( Table S3 ) . Costa et al . [32] have reported that 9 . 8% of DLY hybrid pigs free of the PRKAG3 225Q allele still show the acid meat phenotype with GP higher than 180 µmol/g . In this study , we found that the PHKG1 QTNs are segregating in DLY hybrid pigs with a frequency of 1 . 7% ( 9/540 ) for the homozygous mutant with GP beyond 180 µmol/g . Therefore , we speculate that a substantial proportion of acid meat is likely caused by the PHKG1 g . 8283C>A mutation . It was observed that the mutation had negative effects on almost all meat quality traits but did not impact any growth traits ( e . g . carcass weight; see Table S6 ) in the F2 , Sutai and DLY populations . However , Duroc and two Duroc-derived lines carry the mutation at relatively high frequencies ( Table 3 ) . The result may suggests that meat quality has not been the primary breeding goals in these pig populations . In conclusion , we identified a causal mutation in the PHKG1 gene associated with excess glycogen content in Duroc and its related pigs . The finding highlights the important role of genes encoding PhK subunits in the formation of the GP-related traits . More intriguingly , our finding would be of considerably importance for the pig industry as we can develop a diagnostic DNA test to effectively eliminate the PHKG1 undesirable allele from nucleus herds and consequently improve meat quality .
All procedures involving animals followed the guideline for the care and use of experimental animals established by the Ministry of Agriculture of China . The ethics committee of Jiangxi Agricultural University specifically approved this study . Three experimental populations were involved in this study: a White Duroc × Erhualian F2 intercross , a Chinese Sutai half-sib population and a commercial DLY hybrid population . The F2 population was established as described previously [33] . Briefly , two White Duroc boars were mated to 17 Erhualian sows . Nine F1 boars and 59 F1 sows were then intercrossed to produce a total of 1912 F2 animals in 6 batches . Sutai is a Chinese synthetic line that is derived from Chinese Taihu ( 50% ) and Western Duroc ( 50% ) after over 18 generations of artificial selection . The Sutai population comprised offspring of 4 sires and 55 dams . A total of 930 F2 individuals , 434 Sutai pigs and 540 DLY pigs were used in this study . The F2 and Sutai pigs were weaned at day 46 and 28 respectively , and males were castrated at day 90 and 18 respectively . The two populations were raised at an experimental farm of Jiangxi Agricultural University in Nanchang city during their fattening period and were slaughtered for phenotype recording at the age of 240±3 days . The DLY pigs grew up at a farm of Xiushui city ( about 110 miles away from Nanchang ) until the slaughter weight of 90–100kg . All pigs were transported and slaughtered at the same commercial abattoir in Nanchang where the pigs were fasted for 15–20 hours with water available ad libitum . After slaughter , muscle samples were removed within 30 minutes postmortem from the longissimus ( LM ) and semimembranosus ( SM ) muscles for RNA isolation and the measurement of meat quality traits . The meat characteristics including the ultimate pH ( or pH 24h , measured at 24h postmortem ) , drip loss , Minolta color parameters ( L* , a* , b* ) , subjective scores of color and marbling , intramuscular fat content ( IMF ) , glycolytic potential ( GP ) , residual glycogen ( RG ) , glucose-6-phosphate ( G-6-P ) and lactate were measured as described previously [20] , [34] . Genomic DNA was isolated from ear , blood or spleen tissues with a standard phenol/chloroform method . A total of 1020 animals from the F2 population were genotyped for 62163 SNPs on the Illumina PorcineSNP60 BeadChip [21] according to the standard manufacture's protocol . The 60K Beadchip has 62 , 163 SNP , of which 54 , 920 can be mapped to the current pig genome assembly ( Sus Scrofa Build 10 . 2 ) [35] . The quality control ( QC ) procedures were carried out by Plink v 1 . 07 [36] . Briefly , animals with call rate>0 . 9 and Mendelian error rate <0 . 05 , and SNP with call rate>0 . 9 , minor allele frequency>0 . 05 , P value>10−5 for the Hardy-Weinberg equilibrium test were included . A final set of 39414 informative SNPs on 930 F2 pigs were used for subsequent analyses . A total of 434 Sutai pigs were also genotyped using the Illumina PorcineSNP60 BeadChip . To fine map the SSC3 QTL , we increased the marker density in this QTL region with additional 53 SNPs ( Table S7 ) , which were identified through comparison of our own whole-genome sequence data from 4 F0 Erhualian sows and the Duroc reference genome sequence ( Sus scrofa Build 10 . 2 ) . All Sutai pigs were further genotyped for the 53 SNPs by using the TaqMan OpenArray Genotyping System ( Life Technologies ) . After QC filtering as described above , 44560 SNPs were included for further analysis . We also genotyped 140 DLY pigs using our developed OpenArray 53-SNP panel . Out of the 53 SNPs , 28 passing QC were included in association analysis . These genotype data are deposited in the Dryad repository ( http://dx . doi . org/10 . 5061/dryad . 7kn7r ) . The allelic effect of each SNP on phenotypic traits was tested using a general linear mixed model [37] . The model included a random polygenic effect , and the variance-covariance matrix was proportionate to genome-wide identity-by-state [38] . The formula of the model is given in a mathematic expression: , where Y is the vector of phenotypes; µ is the overall mean; b is the vector of fixed effects including sex and batch effects; w is the vector of slaughter weight of individuals considered as covariate; c is the vector of SNP effects with Erhualian allele substitute to White Duroc allele; a is the vector of random additive genetic effects with α∼N ( 0 , Gσα2 ) , where G is the genomic relationship matrix calculated from the corrected pedigree and σα2 is the polygenetic additive variance; k is the regression coefficient of slaughter weight and e is the vector of residual errors with e∼N ( 0 , Iσe2 ) , where I is the identity matrix and σe2 is the residual variance . X , S and Z are incidence matrices for b , w and c respectively . All single-marker GWAS were conducted by GenABEL packages [39] . The genome-wide significance threshold was determined by the Bonferroni method , in which the conventional P-value was divided by the number of tests performed [40] . A SNP was considered to have genome-wide significance at P<0 . 05/N and chromosome-wide significance at P<1/N , where N is the number of SNPs tested in the analyses . The genome-wide and chromosome-wide significant thresholds were respectively 1 . 27e-6 ( 0 . 05/39414 ) and 2 . 54e-5 ( 1/39414 ) for the F2 population , and 1 . 12e-6 ( 0 . 05/44560 ) and 2 . 24e-5 ( 1/44560 ) for the Sutai population . The phenotypic variance explained by the top SNPs was estimated by ( Vreduce– Vfull ) /Vreduce , where Vfull and Vreduce are residual variances of models for association analysis with and without SNP term , respectively . The influence of population stratification was assessed by examining the distribution of test statistics generated from thousands of association tests and assessing their deviation from the null distribution ( that expected under the null hypothesis of no SNP associated with the trait ) in a quantile-quantile ( Q-Q ) plot [41] . The Q-Q plot was constructed using R software . Linkage disequilibrium ( r2 ) was estimated for SNPs around the QTL region in the two populations by using PLINK v1 . 07 [36] . Total RNA was extracted from longissimus dorsi muscle samples of 497 F2 animals using Trizol ( Invitrogen ) . RNA quantity and integrity were assessed using a NanoDrop ND-1000 Spectrophotometer ( Thermo Fisher Scientific ) and a 2100 Bioanalyser ( Agilent ) . Genome-wide transcripts were assayed by digital gene expression ( DGE ) system and data processing was conducted as described previously [11] , [42] . In brief , the raw tags were first filtered to produce the clean tag data . For mapping clean tags to reference transcript sets or to the pig reference genome ( Sus Scrofa Build 10 . 2 ) [35] , we created virtual libraries containing all the possible 17-base length sequences of these resources located next to an NlaIII restriction site . The reference transcript sets were downloaded from the database of PEDE ( Pig Expression Data Explorer; http://pede . dna . affrc . go . jp/ ) and pig unigene in NCBI ( ftp://ftp . ncbi . nih . gov/repository/UniGene/Sus_scrofa/ ) . The redundant transcripts overlapped between the two databases were removed from the reference transcript set . For monitoring the mapping events on both strands , virtual sense and antisense tag sequence databases were generated for both full gene and cDNA sequences using in-house Perl scripts . The clean tag sequences were then mapped using SOAP2 [43] allowing up to one mismatches in 21-bp tag sequences . Sense and antisense tag sequences that unsuccessfully mapped to reference transcripts or mapped to multiple genes were filtered . The number of clean tags that uniquely mapped to the reference transcript sequence of each gene was calculated and then normalized to TPM ( number of tags mapped to each gene per million clean tags ) as expression level of transcript . The DGE data of 497 F2 animals were adjusted for gender , batch and kinship using a robust linear regression model [44] . Associations between gene expression levels and the RG phenotype were evaluated with Pearson correlation coefficient by R software . eQTL mapping was performed for the DGE profiles in 497 F2 animals using mixed linear model implemented by mmscore function of GenABEL in R package . Sex and batch were considered as fixed effects , and the genetic co-variances among samples were also taken into account by fitting kinship matrix derived from whole genome SNP genotypes . Bonferroni correction was applied to adjust the multiple tests . All the above mentioned analyses were carried out with R software . The entire cDNA sequence of PHKG1 were determined by RT-PCR ( reverse transcriptase-polymerase chain reaction ) and RACE ( rapid amplication of cDNA ends ) analysis . First , RNA was extracted from skeletal muscle of 6 F2 pigs ( 2 of each QTL genotype ) using Trizol ( Invitrogen ) , then cDNA was synthesized using the PrimerScript RT reagent Kit With gDNA Eraser ( Takara ) for RT-PCR or the 5′- & 3′- Full Race Kits ( Takara ) for RACE . The corresponding primer pairs are listed in Table S8 . To get full-length gene sequence , we amplified 14 overlapping segments from genomic DNA , using standard PCR condition and primers reported in Table S9 . All PCR products were purified using the QIAquick PCR Purification Kit ( Qiagen ) and sequenced on both strands using the same primers and BigDye Terminator v3 . 1 Cycle Sequencing kits ( Applied Biosystems ) and a 3130 DNA Analyzer ( Applied Biosystems ) . The sequence traces were assembled and analyzed for polymorphisms using the SeqMan program ( DNASTAR ) . A 140-bp fragment ( Figure 3C ) encompassing the g . 8283C>A mutation was amplified by PCR from genomic DNA using primers ( PHKG1-F1: 5′-ATC CCT GTG CTT GCT GGT G-3′; PHKG1-R1: 5′-CCC GGC GGT ACT GGT AAT-3′ ) , digested using enzyme TaqαI and size fractionated by 2% agarose gel electrophoresis . The A allele was represented by two fragments of 78 and 62 bp , and the C allele by uncut amplicons . Association between the PHKG1 g . 8283C>A polymorphism and meat quality traits was calculated using the least square means method of GLM ( General Linear Model ) procedure in R software . For the F2 and Sutai populations ( n = 930 and 434 respectively ) , sex and batch was included in the model as fix effects , carcass weight as a covariate . A total of 540 DLY pigs were genotyped for this mutation . The residual glycogen content and other meat quality traits were determined for muscle samples from 140 DLY pigs . The model for DLY included sex and harvest batch as fix effects , and carcass weight as a covariate . The associations between SNP genotypes ( i . e . ss131031160 SNP and PHKG1 g . 8283C>A ) and expression levels of three genes ( PHKG1 , GUSB and SUMF2 ) were established by One-Way ANOVA analysis in R software . The relationship between the transcript level of PHKG1 and the RG content was calculated using Pearson correlation in R software . QTL genotypes of 6 F1 boars in the F2 population and 3 Sutai F0 boars were determined by marker-assisted segregation analysis as described previously [45] . Briefly , a Z-score was calculated for each sire; the score is the log10 of the H1/H0 likelihood ratio where H1 assumes that the boar is heterozygous at the QTL ( Qq ) , while H0 postulates that the boar is homozygous QQ or qq . Boars were considered to be Qq when Z>2 , QQ or qq when Z <−2 , and of undetermined genotype if −2<Z<2 . Quantitative RT-PCR ( qRT-PCR ) reactions were performed in a final volume of 10 µl containing 1 µl of 2 . 5-fold diluted cDNA ( corresponding to 20 ng of starting total RNA ) , 5 µl Power SYBR Green PCR Master Mix ( Applied Biosystems ) , forward and reverse primers ( 2 pM each ) and 3 . 6 µl free water . PCRs were conducted on an ABI7900HT instrument ( Applied Biosystems ) under the following cycling conditions: 10 min at 95°C followed by 40 cycles at 95°C for 15 sec and 60°C for 50 sec . Two primer sets Common-5'-FP/RP and Wt-3'-FP/RP ( Figure 4A; Table S10 ) were used to respectively test total and wild-type transcript ( Wt ) levels of PHKG1 . Beta Actin ( ACTB ) was included as endogenous controls . Expression of all assays was measured in triplicates and average values of the triplicates were used for the analysis . The quantification of transcripts was performed by the comparative Ct ( 2-ΔΔCt ) method . The presence of PHKG1 Wt transcript in animals with three QTL genotypes was assayed by RT-PCR using the primers 5′-CAC CCC AAC ATC ATA CAG CT-3′ and 5′-ACA GAA GCC AGC ACC GTC-3′ ( RT-3'-RP ) . PCR products of 698-bp were electrophoresed on 1% agarose gel and visualized by UV illumination ( Figure 4C ) . Total protein from pig muscle tissue was extracted using a Protein Extraction Kit ( Applygen ) . Protein samples separated on SDS-PAGE were transferred onto polyvinylidene difluoride membranes and incubated with rabbit anti-PHKG1 ( Proteintech ) and rabbit anti-mouse β-Actin ( as loading control; Beijing Zhong Shan-Golden Bridge Biological Technology ) antibodies . Anti-mouse or anti-rabbit secondary antibodies conjugated with horseradish peroxidase were used and visualized using chemiluminescent substrate ( Tiangen Biotech ) . Phk activity of 18 F2 animals were determined on their frozen muscle samples using Phk Colorimetric Assay kit ( Genmed Scientifics ) according to the manufacturer's instructions .
|
Glycogen storage diseases ( GSD ) are a group of inherited disorders characterized by storage of excess glycogen , which are mainly caused by the abnormality of a particular enzyme essential for releasing glucose from glycogen . GSD-like conditions have been described in a wide variety of species . Pigs are a valuable model for the study of human GSD . Moreover , pigs affected by GSD usually produce inferior pork with a lower ultimate pH ( so-called “acid meat” ) and less processing yield due to post-mortem degradation of the excess glycogen . So far , only one causal variant , PRKAG3 R225Q , has been identified for GSD in pigs . Here we reported a loss-of-function mutation in the PHKG1 gene that causes the deficiency of the glycogen breakdown , consequently leading to GSD and acid meat in Duroc-sired pigs . Eliminating the undesirable mutation from the breeding stock by a diagnostic DNA test will greatly reduce the incidence of GSD and significantly improve pork quality and productivity in the pig .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"biology",
"and",
"life",
"sciences",
"animal",
"genetics"
] |
2014
|
A Splice Mutation in the PHKG1 Gene Causes High Glycogen Content and Low Meat Quality in Pig Skeletal Muscle
|
Germline mutations of the Liver Kinase b1 ( LKB1/STK11 ) tumor suppressor gene have been linked to Peutz-Jeghers Syndrome ( PJS ) , an autosomal-dominant , cancer-prone disorder in which patients develop neoplasms in several organs , including the oviduct , ovary , and cervix . We have conditionally deleted Lkb1 in Müllerian duct mesenchyme-derived cells of the female reproductive tract and observed expansion of the stromal compartment and hyperplasia and/or neoplasia of adjacent epithelial cells throughout the reproductive tract with paratubal cysts and adenomyomas in oviducts and , eventually , endometrial cancer . Examination of the proliferation marker phospho-histone H3 and mammalian Target Of Rapamycin Complex 1 ( mTORC1 ) pathway members revealed increased proliferation and mTORC1 activation in stromal cells of both the oviduct and uterus . Treatment with rapamycin , an inhibitor of mTORC1 activity , decreased tumor burden in adult Lkb1 mutant mice . Deletion of the genes for Tuberous Sclerosis 1 ( Tsc1 ) or Tsc2 , regulators of mTORC1 that are downstream of LKB1 signaling , in the oviductal and uterine stroma phenocopies some of the defects observed in Lkb1 mutant mice , confirming that dysregulated mTORC1 activation in the Lkb1-deleted stroma contributes to the phenotype . Loss of PTEN , an upstream regulator of mTORC1 signaling , along with Lkb1 deletion significantly increased tumor burden in uteri and induced tumorigenesis in the cervix and vagina . These studies show that LKB1/TSC1/TSC2/mTORC1 signaling in mesenchymal cells is important for the maintenance of epithelial integrity and suppression of carcinogenesis in adjacent epithelial cells . Because similar changes in the stromal population are also observed in human oviductal/ovarian adenoma and endometrial adenocarcinoma patients , we predict that dysregulated mTORC1 activity by upstream mechanisms similar to those described in these model systems contributes to the pathogenesis of these human diseases .
The embryonic Müllerian ducts , which are composed of a simple columnar epithelium surrounded by mesenchymal cells , differentiate into the oviducts , uterus , cervix , and anterior portion of the vagina [1] . During differentiation , epithelial-mesenchymal communication plays an important role in specification of the Müllerian duct epithelium into ciliated and secretory ( oviduct ) , columnar ( uterus ) , and squamous ( cervix ) epithelium [2] . Confirmation of the control exerted by the stroma on differentiation , shown using tissue recombination studies mixing uterine or vaginal stroma and epithelia , have revealed that the fate of epithelial cells depends on stromal/mesenchymal signaling [2] , [3] . In the uterus , epithelial-mesenchymal crosstalk also plays an important role in development of epithelial cancer . For example , in our recent study , we showed that conditional deletion of Adenomatous Polyposis Coli ( APC ) in endometrial stromal cells results in their conversion to a myofibroblast phenotype , which was sufficient to initiate endometrial hyperplasia that could lead to endometrial cancer in mice [4] . The physiological relevance of the endometrial stroma cell conversion was confirmed when a myofibroblast stromal phenotype was also observed in human endometrial epithelial cancer patient tissue samples [4] . Peutz-Jeghers syndrome ( PJS ) is a hereditary cancer-prone disorder linked to mutation of LKB1 ( also known as Serine/Threonine Protein Kinase 11; STK11 ) [5] . Patients with PJS are at high risk of developing cancerous lesions in various organs including testis , ovary , endocervix , breast , and colon [6] . LKB1 encodes an evolutionarily conserved serine/threonine kinase that phosphorylates and activates a family of related AMP kinases ( AMPK ) in response to a decline in the cellular ATP:AMP ratio , acting as a metabolic rheostat to maintain energy homeostasis [7] . One of the best studied targets of AMPK is mammalian target of rapamycin complex 1 ( mTORC1 ) , a master regulator of proliferation , which is inhibited indirectly by maintaining the TSC1/TSC2 tumor suppressor complex and directly by phosphorylation of regulator-associated protein of mTOR ( Raptor ) , a substrate binding component of the rapamycin-sensitive mTORC1 [5] . LKB1-AMPK tumor suppressor activity has also been associated with another of its major functions , controlling cell polarity , which appears to be the central mechanism suppressing tumorigenesis in a pancreatic cancer model with loss of LKB1 [8] . Adenoviral-delivered Cre-mediated deletion of Lkb1 in murine endometrial epithelium can drive development of highly invasive endometrial adenocarcinoma [9] showing that LKB1 is an important tumor suppressor in endometrial carcinogenesis . Mutations in LKB1 are also detected in human cervical cancer patients , and PJS patients also develop endocervical cancer known as adenoma malignum/minimum deviation of adenocarcinoma [10] . Although most reports of tumorigenesis are from mutated epithelial cells , loss of LKB1 in mesenchymal cells using Smooth Muscle 22-cre has been shown to lead to the development of polyps with features similar to those found in PJS patients [11] . Of note , gastrointestinal polyps from PJS patients contain more myofibroblastic stromal cells , which is similar to the phenotype mice develop after deletion of endometrial stromal APC [4] . LKB1 is highly expressed in the mesenchymal cells of human gonads and patients with PJS develop ovarian and testicular stromal tumors [12]–[14] , suggesting that LKB1 might be an important tumor suppressor in the stromal cells of reproductive organs . This hypothesis is supported by the recent findings that , whereas , heterozygous deletion of LKB1 in both epithelium and stroma results in endometrial cancer [9] , heterozygosity of LKB1 in the epithelium alone does not [15] . In order to investigate whether deletion of LKB1 from reproductive tract and gonadal stromal cells leads to the gynecological abnormalities observed in PJS patients , we generated mice with conditional deletion of LKB1 in the stromal cells of the female reproductive tract using Müllerian inhibiting substance receptor 2-driven Cre ( Misr2-Cre ) [16] . A significant proportion of PJS patients harbor mutations that encompass whole or partial LKB1 gene deletions , make this mouse model appropriate for studying this disease . We observed expansion of the myofibroblast population accompanied by hyperplasia and/or neoplasia of the epithelia of both oviduct and uterus . Loss of TSC1 or TSC2 using the same Cre is able to phenocopy some of the reproductive pathologies of Lkb1-deleted mice , suggesting that their common downstream target , mTORC1 , plays a role in their pathogenesis when dysregulated . These results show the importance of mesenchymal LKB1/TSC1/TSC2/mTORC1 signaling in the female reproductive tract and provide a compelling rationale for considering the therapeutic option of mTORC1 inhibitors for these patients .
No gross defects were observed in 5 week old control and Lkb1cko mutant ( N = 3/each ) oviducts ( Figure 1A and 1B ) . After 18 weeks , grossly visible cystic growths of various sizes were observed in the oviducts of mutant females ( N = 5/5; Figure 1D ) . Normal oviduct development was observed in age-matched control littermates ( N = 5/5; Figure 1C ) . Initial examination of ovaries from both groups of mice revealed the presence of corpora lutea , suggesting normal ovulation and ovarian functions ( data not shown ) . Histological examination of the control and mutant oviducts was performed to evaluate cellular changes after loss of LKB1 . At 5 weeks of age , H&E-stained sections of mutant oviducts showed increased thickness of the LKB1-deleted stromal compartment compared with controls ( N = 3; Figure 1E–1J ) . Stromal cells of the mutant oviducts were also more disorganized compared with age-matched controls and oviductal epithelial cells of mutant mice had a more irregular and vacuolated arrangement ( Figure 1G–1J ) and were often found occluding the lumen ( Figure 1J ) . Examination of the mesenchymal/smooth muscle cell markers , desmin and αSmooth Muscle Actin ( αSMA ) in the 5 week old oviducts by immunofluorescence confirmed expansion of αSMA+/desmin- or weakly desmin+ stromal cell population , indicating dysregulated proliferation of Lkb1-deleted stromal cells ( Figure 1M and 1N ) compared with controls ( Figure 1K and 1L ) . A similar expansion of αSMA+/desmin- myofibroblast cells was also observed in polyps from human PJS patients and other mouse models with loss of LKB1 [11] . By 18 weeks , histological examination of mutant oviducts showed massive expansion of the stromal compartment compared with controls ( Figure 1O and 1P ) . Co-staining with αSMA and desmin confirmed the increase in smooth muscle/myofibroblast cells in the stroma of Lkb1cko oviducts ( Figure 1Q and 1R ) . The extracellular matrix ( ECM ) plays an important role in determining epithelial cell integrity and polarity [24] . In the uterus , stromal cells secrete and deposit various components of ECM [25] , including collagen and laminin , which play an important role in endometrial remodeling [26] . Additionally , altered production of ECM components is observed in various endometrial pathologies [27] , [28] . For this study , we hypothesized that expansion of the stromal population in mutant oviducts affects the production and deposition of ECM components . To test this we performed Masson's Trichrome staining of control and mutant oviducts ( N = 3/each ) and observed a significant increase in blue staining , indicative of collagen in the stromal compartment of mutant oviducts ( Figure 1U–1V ) . By comparison , collagen-specific staining is limited to the basement membrane of the control oviducts ( Figure 1S ) . Next we examined expression of various cytoskeleton proteins ( cytokeratin , β-catenin , E-cadherin and Tight Junction Protein-1/Zona Occuldens1 ( TJP1/ZO1 ) to determine if there were any changes in oviductal epithelial cells due to the stromal expansion and alterations in ECM ( Figure S2 ) . No differences in the expression of cytokeratin , β-catenin , E-cadherin , and TJP-1 were observed between attached mutant and control oviductal epithelial cells . However , their expression did appear abnormal in detached epithelial cells present in the lumen of the mutant oviducts . To confirm that the normal differentiation of the oviductal epithelial cells was not affected by the changes in the mesenchymal cells of the mutant oviducts , we perform colocalization of paired box gene 2 ( PAX2 ) and αSMA in oviducts of both control and mutant mice ( Figure S2 ) . PAX2 is a marker of the murine reproductive tract epithelial cells and loss of the Pax2 gene is associated with dysgenesis of reproductive tract [29] . Normally PAX2 is not expressed in the epithelium of the distal segment of the mouse oviduct and no changes in the expression pattern of PAX2 were observed between control and mutant oviducts ( Figure S2 ) . PJS patients have been diagnosed with cystic growths in their Fallopian tubes that are either filled with translucent white fluid or pus ( pyosalpinx ) [17] . Figure 1D shows a typical large cyst in the Lkb1cko oviduct , and histological examination of Lkb1cko mutant oviducts revealed numerous smaller cystic growths as well ( N = 5/5 ) ( Figure 2 ) . The distended blind cysts in mutant mice were highly variable in size , often accompanied by stromal expansion ( Figure 2C ) , and often filled with either bloody or pale fluid similar to hematosalpinx , and pyosalpinx , respectively ( Figure 2D ) . We injected bromophenol blue dye into the lumen of mutant and control oviducts to determine whether the fluid accumulating in the cysts was derived from the lumen , which in normal oviducts should pass straight through [20] . In mutant oviducts , abnormal accumulation of dye in small cystic growths was observed , suggesting that the cysts were directly connected to the lumen or that the oviductal epithelial basement membrane had become permeable ( Figure 2G and 2H ) . Additionally , when dye was injected from the uterine side , no dye was observed in the oviductal lumen of control mice but was observed in the mutant oviducts ( Figure 2I and 2J ) , suggesting a defective uterotubular junction in mutants and consistent with loss of control of retrograde flow [20] . LKB1 plays an important role in various biological processes , including cell proliferation , by interacting with AMP kinases ( AMPKs ) and regulating mTORC1 activation [5] . We therefore examined expression of phospho-histone H3 ( pH 3 ) , a marker for mitotic cells , to determine the rate of cellular proliferation in control and mutant oviducts . Increased pH 3-positive cells in both epithelial ( arrow ) and stromal ( arrowheads ) compartments was observed in mutant oviducts compared to controls ( Figure 3A and 3B ) . Analysis of the expression of phosphorylated forms of mTOR and riboprotein S6 , a target of S6 Kinase that is downstream of activated mTORC1 , showed increased phosphorylation of both mTOR ( Ser2448 ) and S6 ( Ser235/236 ) in the mesenchymal cells of the mutant oviducts ( Figure 3C–3F ) . Since phosphorylation of S6 at Ser235/236 sites is regulated by both mTORC1 and mitogen-activated protein kinases [30] we confirmed mTORC1 involvement by western blot analyses and showed decreased expression of pRAPTOR ( Ser792 ) and increased phosphorylation of S6 ( Ser235/236; pS6/S6 ratio: 12 . 3±1 . 9 mutant/8 . 2±1 . 9 control ) and eukaryotic translation initiation factor 4E-Binding Protein 1 ( 4EBP1 , Thr37/46; p4EBP1/4EBP1 ratio: 0 . 8±0 . 0 mutant/0 . 5±0 . 1 control ) in the mutant oviducts ( n = 3 ) ( Figure 3G ) . LKB1 has also been shown to affect Wnt signaling , dysregulation of which causes defects in oviduct development and differentiation [5] , [22] , [31] . We measured β-catenin protein levels in oviducts by western blot and observed no change in expression of β-catenin between control and mutant oviducts ( Figure 3G ) , suggesting that defects observed in Lkb1 mutant oviducts are independent of canonical Wnt signaling . LKB1 is also an inhibitor of transforming growth factor β ( TGFβ ) signaling [32] , which can play an important role in fibroblast differentiation and fibrosis [33] and has been implicated in carcinogenesis of various organs [4] , [34] , [35] . In this study , we evaluated TGFβ signaling and observed an increase in expression and nuclear translocation of the phosphorylated and active form ( Ser465/467 ) of its downstream target , SMA and Mothers Against Decapentaplegic homolog 2 ( SMAD2 ) , in mesenchymal cells of both 5 week-old and adult mutant oviducts compared to controls ( Figure 3H–3O ) , which was confirmed by western blot analysis ( Figure 3G ) . Since stromal bone morphogenetic protein ( BMP ) signaling also plays a role in regulating the growth of intestinal epithelium and its inhibition leads to polyposis in mice [36] , we examined and found comparable pSMAD1/5/8 in Lkb1 mutant and control mice ( data not shown ) , suggesting BMP signaling is not affected in our model system . These results suggest that stromal expansion and increased ECM deposition in the mutant oviducts could both be the result of dysregulated TGFβ signaling . Because we observed increased mTORC1 activity in the stromal cells of Lkb1cko oviducts ( Figure 3 ) , we reasoned that deletion of other genes involved in the regulation of the mTORC1 pathway would phenocopy the defects observed in Lkb1cko oviducts . For example , TSC1 and TSC2 act together as a complex to modulate the activity of the mTORC1 signaling pathway and loss of TSC1 or TSC2 leads to hyperactivation of mTORC1 signaling [37] . To study the effects of TSC1 and TSC2 loss in mesenchymal cells of the oviduct , we developed mice with conditional deletion of Tsc1 ( Tsc1cko ) and Tsc2 ( Tsc2cko ) by using the same Misr2-Cre we used to generate the Lkb1cko mice . Deletion of Tsc2 in the female reproductive tract ( oviduct , ovary , and uterus ) was confirmed using genomic PCR ( Figure S1E ) . Gross examination of female reproductive tract revealed no obvious differences between control and Tsc2cko mutant mice ( data not shown ) . However , histological examination of 6 week old oviducts revealed moderate hyperplasia of epithelial cells in mutants compared with controls ( Figure S3 ) . By 18 weeks , the oviducts of Tsc2cko mice showed expansion of both stromal and epithelial compartments accompanied by abnormal cystic growth ( N = 5/5 ) ( Figure 4B , 4D , 4F ) compared to controls ( N = 4/4 ) ( Figure 4A , 4C , 4E ) . Similar to Lkb1cko and Tsc2cko mutants , abnormal cystic lesions were also observed in the oviducts of the older Tsc1cko mutant females ( N = 3/each ) ( Figure 4I–4K ) . Histological examination of the oviducts from Lkb1cko , Tsc1cko and Tsc2cko mice also revealed the presence of adenomyomas ( Figure 2 and Figure 4 ) , nodular lesions consisting of simple glandular , often hyperplastic epithelium with abnormal stromal cell expansion as a prominent feature ( Figure 1 and Figure 4 ) . In humans , adenomyomas are observed in various organs including the oviduct , ovary , uterus , and intestine [38]–[41] . Because we observed development of adenomyomas in the mutant animals with a significant myofibroblastic stromal cell population , we hypothesized that human oviductal/ovarian adenomyomas might also be the result aberrant stromal cell expansion and conversion to myofibroblasts . We analyzed expression of αSMA and desmin in normal human oviducts and oviductal adenomas to study changes in the stromal compartment ( Figure 4L–4O ) and found that expression of these markers was limited to the blood vessels and very little staining was observed in the stromal cells ( Figure 4N ) . In contrast , αSMA and desmin staining is increased in the stroma of the oviductal adenomyomas ( N = 8/10 ) ( Figure 4O ) , suggesting of expansion of myofibroblast/smooth muscle cell population . The mouse uterus is comprised of three different compartments: endometrial ( luminal and glandular ) epithelium , endometrial stroma , and myometrium ( smooth muscle cells ) [42] . In our previous study , we showed that deletion of APC in the stromal compartment is sufficient to induce endometrial cancer in mice and also observed comparable changes in human endometrial cancer patients suggesting that mesenchymal cells play an important role in the etiology of endometrial cancer [4] . The LKB1/mTORC1 signaling pathways have also been implicated in endometrial carcinogenesis [15] , [43] . We examined uteri from 9 week old control and Lkb1cko mutant mice and found evidence of endometrial epithelial hyperplasia and endometrial cancer with expansion of the myofibroblastic population in the Lkb1cko mice but not in the controls ( Figure 5A–5D ) . Colocalization of αSMA and cytokeratin 8 ( CK8; epithelial marker ) confirmed expansion of myofibroblast cell population in the stromal compartment adjacent to the CK8+ epithelial lining in mutant uteri ( Figure 5F and Figure S4 ) . In contrast , only αSMA-negative stromal cells are present close to CK8+ epithelial cells in control uteri ( Figure 5E ) . Examination of the reproductive tracts from older mutant animals ( N = 5/5 ) showed that their uteri were greatly enlarged ( Figure S4B ) and that endometrial epithelial glands had invaded the myometrial compartment , which is a hallmark of endometrial adenocarcinoma [44] ( Figure 5H , 5K , 5N ) . In contrast , control uteri ( N = 5/5 ) were much smaller and epithelial cells were limited to the endometrial/stromal compartment ( Figure 5G , 5J , 5M; Figure S4A ) . A previous study showed that approximately 30% of Lkb1+/− mice developed endometrial cancer and that biallelic uterine epithelial specific loss of Lkb1 using adenoviral Cre was sufficient to induce highly invasive endometrial adenocarcinoma [9] . To compare tumorigenesis in mice with stromal Lkb1cko alone with mice with epithelial loss of Lkb1 , we generated another mouse ( Lkb1cko/- ) in which one allele of Lkb1 is deleted in all cells , including the epithelial cells of the uterus , and the other allele is floxed only in the Müllerian duct mesenchyme-derived stromal cells ( Figure 5I , 5L , 5O; Figure S4C ) . Comparison of endometrial cancer formed in Lkb1cko and Lkb1cko/- using αSMA and CK8 immunostaining revealed that tumors in both model systems were very similar ( Figure 5N and 5O ) . Particularly noteworthy was the increased αSMA+ cell population adjacent to CK8+ cells observed in both models ( Figure 5N and 5O ) compared with controls . However , tumors formed in Lkb1cko/- were bigger , more aggressive and invasive compared to Lkb1cko mice , supporting the findings of the previous report [9] and showing the importance of epithelial LKB1 loss to endometrial carcinogenesis . Similar to Lkb1cko oviducts ( Figure 3 ) , we observed increased proliferation of uterine mesenchymal cells as confirmed by pH 3 staining in Lkb1cko mutants compared with controls ( Figure S4F and S4G ) . Examination of pmTOR , pS6 , and pSMAD2 expression revealed increased mTORC1 and TGFβ signaling activity in Lkb1cko uteri compared to controls ( Figure S4H–S4M ) . Because we observed increased mTORC1 activity in Lkb1cko uteri , we treated aged Lkb1cko mice ( >7 month old ) with rapamycin or vehicle ( N = 3/group ) as previously described [45] . After 3 weeks of treatment , we observed decreased uterine weight accompanied by reduced expression of pS6 in rapamycin-treated mice compared with controls ( Figure 6A–6E ) . Histological examination of rapamycin- and vehicle-treated uteri and oviducts showed suppression of endometrial carcinogenesis ( Figure 6F and 6G ) and inhibition of cyst formation ( Figure S5A ) , respectively , with rapamycin treatment confirming the involvement of mTORC1 in the pathogenesis of the Lkb1 mutant phenotype . We also analyzed uteri from Tsc1cko and Tsc2cko mice to determine whether deletion of these upstream regulators of mTORC1 activity resulted in phenotypes similar to those observed in the Lkb1cko uteri . Compared to controls , Tsc2cko and Tsc1cko uteri were enlarged and showed hyperplasia or neoplasia of the endometrial epithelium ( Figure 6H–6J ) . Immunolocalization of αSMA and CK8 revealed that , similar to Lkb1 mutant uteri , Tsc2cko and Tsc1cko uteri showed expansion of the αSMA+ and CK8+ cell populations ( Figure 6K–6M ) . In contrast to Lkb1cko or Lkb1cko/- endometrial cancers , myometrial invasion of epithelial cells ( Figure 6L and 6M ) and squamous metaplasia of endometrial epithelium ( Figure S5B ) was not observed in either Tsc2cko or Tsc1cko uteri . PJS patients can develop leiomyosarcomas [46] reinforcing the importance of LKB1 in smooth muscle function and differentiation . Also , deregulation of mTORC1 signaling and mutations in various components of this pathway are commonly observed in human smooth muscle tumors [47] , [48] . Paradoxically , loss of only PTEN , an upstream regulator of the mTORC1 pathway , in mesenchymal cells of the female reproductive tract is unable to induce carcinogenesis in either stromal cells or the adjacent epithelium [45] , [49] , [50] . Similarly , PTEN loss alone is unable to initiate polycystic kidney disease or kidney cancer in mice [51] . However , Pten deletion does enhance polycystic kidney disease and progression of the kidney cancer phenotype and decreases the lifespan of Tsc1 mutant mice by over activating the mTORC1 pathway [51] . In this study we examined whether PTEN loss in mesenchymal cells synergizes with LKB1 loss by developing another mouse model with conditional deletion of both Lkb1 and Pten genes ( Lkb1cko;Ptencko ) . Grossly , the female reproductive tracts of 5 week old Lkb1cko;Ptencko mice were enlarged and showed abnormal growths compared with Lkb1fl/fl;Ptenfl/fl controls ( Figure 7A and 7B ) . By 9 weeks , tumorous growths were observed projecting through the vaginal opening of Lkb1cko;Ptencko mice ( N = 8/10 ) but not in Lkb1cko/+;Ptencko or Lkb1fl/fl;Ptenfl/fl mice ( Figure 7C ) . Dissection of Lkb1cko;Ptencko double mutant mice revealed large tumorous growths in the uteri and in the cervix/vagina region ( N = 20/20 ) ( Figure 7D and 7E ) . Histological examination of Lkb1cko;Ptencko uteri showed development of endometrial intraepithelial neoplasia by 5 weeks ( N = 4/4 ) , which progressed to endometrial adenocarcinoma in 9 week old mice ( N = 10/10 ) ( Figure 7F–7M ) . In comparison , endometrial cancer development usually required approximately 24 weeks to be observed in Lkb1cko mice . Colocalization of αSMA and CK8 showed that , similar to Lkb1cko mice ( Figure 5 ) , expansion of αSMA+ cells adjacent to CK8+ epithelial cells was also observed in Lkb1cko;Ptencko mutant mice ( Figure 7N–7Q ) . Examination of oviducts from Lkb1cko;Ptencko mutants showed development of oviductal cysts and adenomas akin to Lkb1cko mice ( Figure S6A and S6B ) . However , oviductal abnormalities appeared much earlier in Lkb1cko;Ptencko mutants ( 12 weeks ) compared with Lkb1cko mice ( 18 weeks ) . Human cervical cancer and PJS patients show alterations in LKB1/mTORC1 signaling [10] , [18] , [52] . Even though Misr2-Cre causes recombination in stromal cells of the cervix and upper vagina ( Figure S1 ) , no tumor formation was observed in these organs of Lkb1cko , Tsc1cko , and Tsc2cko mice ( N = 5/each; data not shown ) . However , loss of both LKB1 and PTEN initiated tumor formation in cervices and vaginas of mutant animals ( N = 20/20 ) ( Figure S6C and S6D ) . Histological examination of the lower reproductive tracts ( endocervix , cervix and vagina ) of 5 week old mice showed expansion of the stromal compartment and hyperplasia of the adjoining epithelial cells ( Figure S6E and S6F ) . By 10 weeks , hyperplasia and/or neoplasia of cervical and vaginal squamous epithelial cells were observed in Lkb1cko;Ptencko mice ( N = 20/20 ) ( Figure S6H–S6J ) . No similar changes were observed in Lkb1fl/fl;Ptenfl/fl control mice ( N = 5 ) ( Figure S6G ) . Interestingly , massive expansion of mesenchymal cells or areas with mesenchymal only features were also observed in all cervical and vaginal tumors examined ( Figure S6K ) .
Mutations in LKB1 are frequently observed in PJS patients and associated with development of gastrointestinal , colorectal , pancreatic , breast , and gynecological and gonadal cancers [5] , [53] . LKB1 inhibits mTORC1 activity through AMPK , and loss of LKB1 is associated with increased mTORC1 activity in both human and murine tumors [5] , [54] , [55] . The mechanisms controlled by the LKB1 in reproduction and gynecological cancers have not been thoroughly investigated . However , recent studies have highlighted the importance of the genes involved in this signaling pathway in germ cell and reproductive tract biology . Oocyte-specific loss of TSC1 or TSC2 leads to premature ovarian failure and infertility in mice [56] . The deletion of Lkb1 in the murine uterine epithelium activates mTORC1 signaling and leads to the development of endometrial cancer [9] . Recently , we showed that conditional deletion of TSC1 in the female reproductive tract initiates oviductal epithelial cell dysplasia and causes blockage of embryo transport through the oviduct leading to infertility in mice [57] . In this report we have shown that conditional deletion of Lkb1 , Tsc1 , and Tsc2 in the mesenchymal cells leads to the development of oviductal and uterine pathologies such as endometrial cancer , indicating that dysregulated mTORC1 signaling downstream of LKB1 signaling plays an important role in pathogenesis of the observed defects ( Summarized in Table S1 ) . The activation of mTOR signaling by dysregulated LKB1 has been associated with smooth muscle development and associated pathologies [58] . For example , intestinal polyps in human PJS patients and an Lkb1 heterozygous mouse model show upregulation of the mTOR activity and expansion of smooth muscle compartment [58] . The deletion of Lkb1 using smooth muscle-specific cre mice affects smooth muscle cells and leads to hyperplasia of adjoining epithelial cells , causing development of polyps similar to those observed in human patients with PJS [11] . The upregulation of mTOR signaling is also observed in human smooth muscle tumors of the uterus known as leiomyomas and similar tumors were developed in Eker rat with defective TSC2 signaling confirming that the mTORC1 pathway plays an important role in the pathogenesis of these tumors [48] . In another example , the loss of TSC1 in cardiac smooth muscle cells results in cardiac hypertrophy and death [59] . The increase in cardiac muscle mass is associated with activation of mTORC1 signaling and rapamycin treatment of these mice rescues the phenotype and leads to prolonged survival [59] . In this study , we showed that inhibition of mTORC1 signaling by rapamycin significantly suppressed tumor burden in Lkb1 mutant mice ( Figure 6 ) , further highlighting the contribution of dysregulated mTORC1 signaling to development of Lkb1 mutant phenotype . We show that mutation of stromal Lkb1 induces proliferation of adjacent oviductal and uterine epithelium ( Figure 1 and Figure 5 ) accompanied by increased TGFβ signaling ( Figure 3 and Figure S4 ) , which is paradoxically known to mediate both tumor suppression and promotion [60] . Increased TGFβ signaling is associated with tumor promotion in pancreatic and breast cancer models [61] , [62] . In contrast , loss of TGFβ signaling leads to the development of prostate and gastric carcinomas [34] . In the intestine , loss of LKB1 in mesenchymal cells causes decreased TGFβ signaling , which is associated with polyp development , suggesting that LKB1 signaling promotes TGFβ signaling [11] . In contrast , a recent study showed that LKB1 inhibits TGFβ signaling and promotes epithelial differentiation [32] . We suspect that the role of TGFβ in carcinogenesis is highly context and/or tissue dependent [34] . LKB1 mutations have been observed in approximately 20% of human cervical cancer patients [10] and activation of mTORC1 , a downstream target of LKB1 signaling , has been observed in 54% of human cervical adenocarcinoma patients [63] . Inhibition of mTORC1 decreases proliferation and induces apoptosis in cervical cancer cell lines [52] . These studies indicate the critical role played by this pathway in cervical tumorigenesis . Human PJS patients also develop malignant tumors in the endocervix known as adenoma malignum [18] . However , tumor formation in the cervix has not been reported in Lkb1 mutant mouse models [9] , [19] . Because these previous studies mainly focused on the role of LKB1 signaling in epithelial cells , the contribution of dysregulated stromal LKB1 signaling in cervical carcinogenesis has been unappreciated . Examination of the lower female reproductive tracts ( cervix and vagina ) collected from Lkb1 , Tsc1 , and Tsc2 mutant mice showed no abnormal growth in these organs . However , cervical/vaginal epithelial hyperplasia and neoplasia were observed in Lkb1cko;Ptencko mice ( Figure 7 ) , indicating that loss or alterations in the activity of another tumor suppressor in combination with defective LKB1 activity is required for cervical carcinogenesis . We have shown that defective LKB1/TSC1/TSC2/mTORC1 signaling in mesenchymal cells is sufficient to cause epithelial hyperplasia , adenoma and paratubal cysts in oviducts , and uterine endometrial cancer in mice . A significant proportion of PJS patients harbor mutations that encompass whole or partial LKB1 gene deletions [64] , and comparative analyses of human oviductal/ovarian adenomas revealed similar changes in the stromal population , making this mouse model appropriate for studying this disease . Future studies will investigate human oviductal or ovarian adenomas and endometrial carcinoma associated mesenchymal cells for genetic mutations or alterations in this signaling pathway with the expectation of strong support for treating PJS patients with therapies targeting mTORC1 , such as rapamycin and its analogs .
All protocols involving animal experimentation are in compliance with the NIH Guide for the Care and Use of Laboratory Animals and were approved by the Institutional Animal Care and Use Committee at Massachusetts General Hospital . Mice used in this study were housed under standard animal housing conditions and maintained on a mixed genetic background ( C57BL/6;129/SvEv ) . The following mice strains: Amhr2tm3 ( cre ) Bhr ( also known as Misr2-Cre , obtained from Dr . Richard Behringer , [16] ) , and Stk11tm1Rdp ( Lkb1fl/fl , [19] ) , Tsc1fl/fl [65] , Tsc2fl/fl [66] , Ptentm1Hwu [67] were mated to produce Amhr2tm3 ( cre ) Bhr/+;Stk11Δ/Δ , Amhr2tm3 ( cre ) Bhr/+;Tsc2Δ/Δ , Amhr2tm3 ( cre ) Bhr/+;Tsc1Δ/Δ , Amhr2tm3 ( cre ) Bhr/+;PtenΔ/Δ and Amhr2tm3 ( cre ) Bhr/+;Stk11Δ/Δ; PtenΔ/Δ hereafter referred to as Lkb1cko , Tsc2cko , Tsc1cko , and Lkb1ckoPtencko respectively . Whenever possible , littermate control mice were used in all experiments . Misr2-Cre;Rosa26Laczfl/fl reporter mice were generated as previously described [4] . Tail biopsies were used to perform genotyping using standard PCR protocols as described for Misr2-Cre [22] and with the following primers and conditions to detect wt and flox alleles of Lkb1 5′-GGG CTT CCA CCT GGT GCC AGC CTG T , 5′-GAT GGA GAA CCT CTT GGC CGG CTC A-3′ and 5′-GAG ATG GGT ACC AGG AGT TGG GGC T and 35 cycles of 94 C 30 sec , 65 C 1 min , 72 C 1 min . PCR conditions for Tsc1 , Tsc2 , and Pten alleles are previously described in detail [45] , [57] , [66] . Gross pictures of were taken using a Nikon SMZ1500 microscope with an attached Spot camera ( Diagnostic Instruments , Sterling Heights , MI ) or with a Nikon D60 digital camera and macro lens . Bromophenol blue dye injections were performed as previously described [20] . Briefly , 0 . 25% bromophenol blue solution was injected into the lumen of oviducts at the uterotubal junction or lumen of the uterus in adult control and Lkb1cko mutant oviducts ( N = 3/each ) . The oviducts were grossly examined under microscope . Lkb1cko mutant mice ( >7 month old , N = 3/group ) were given either rapamycin ( 250 ug by oral gavage , Rapamune , Wyeth , PA ) or an equivalent volume of vehicle control ( The American Lecithin company , Oxford , CT ) as previously described in [45] for five days per week for three weeks . After the treatment period , animals were euthanized and tissues were collected for further analyses . The female reproductive tracts from control and mutant animals were collected at different stages of development . For histological examination , tissues were fixed in 4% paraformaldehyde for 10–12 h at 4°C , processed as previously described [4] , and examined by an experienced human oviductal pathologist . Paraffin embedded tissue sections of human oviductal/ovarian adenomas were obtained from Department of Pathology , Brigham and Women's Hospital using Institutional Review Board-approved protocols . Detailed methods for IHC and IF are described elsewhere [4] , [68] . Tumors were graded using the FIGO staging system . The primary and secondary antibodies used in this study are: β-catenin ( BD Transduction Laboratories , San Jose , CA ) ; E-cadherin ( Santa Cruz Biotechnology , Inc . , Santa Cruz , CA ) ; αSMA ( Sigma , St . Louis , MO ) ; TJP-1/ZO-1 ( Developmental Studies Hybridoma Bank , Iowa City , IA ) ; phospho-riboprotein S6 , phospho-SMAD1 ( Ser463/465 ) /5 ( Ser463/465 ) /8 ( Ser426/428 ) , phospho-mTOR ( Cell Signaling Technology , Danvers , MA ) ; phospho-SMAD2 , phospho-Histone H3 ( Millipore , Billerica , MA ) ; cytokeratin , desmin ( Neomarkers , Fremont , CA ) ; cytokeratin 8 ( Developmental studies hybridoma bank , IA ) , PAX2 , AlexaFluor second antibodies ( Invitrogen , Carlsbad , CA ) ; and biotinylated donkey antimouse or antirabbit F ( ab ) 2 fragments ( Jackson ImmunoResearch , West Grove , PA ) . Photos were taken with a Nikon TE2000S with an attached Spot camera ( Diagnostic Instruments ) or Nikon Eclipse Ni fitted with Nikon DSF12/DS-Q1MC camera . For measurements , images were analyzed from minimum of three different animals per group using Nikon NIS elements imaging or ImageJ ( National Institute of Health , Bethesda , MD ) software . For β-galactosidase staining , female reproductive tract from Misr2-Cre;Rosa26Laczfl/+ and Rosa26Laczfl/+ reporter mice were collected at 5–6 weeks of postnatal . Tissues were fixed for 1 h at 4°C then washed and stained in X-gal solution at room temperature for 3–4 h . After a quick rinse with PBS , tissues were processed for histology . Masson's Trichrome staining was performed using a kit ( Sigma ) . Oviducts ( N = 3/each ) from Lkb1 control and mutant animals were collected and protein extracts were prepared using RIPA buffer as described in [4] . Protein concentration was determined using the Bradford assay and equal amounts protein was loaded in gels . The following antibodies are used: S6 , pS6 , pRAPTOR , 4E-BP1 , p4EBP1 ( Cell Signaling Technology ) ; β-catenin ( Sigma ) ; pSMAD2 ( Millipore ) ; β-actin ( Neomarkers ) . Western blot films were scanned and bands were analyzed by pixel density for statistical analyses . Statistical analyses were performed using Prism software ( GraphPad software , La Jolla , CA ) . The Student t test was used to calculate differences between the groups ( N≥3/group ) , and p values≤0 . 05 were considered statistically significant .
|
Peutz-Jeghers Syndrome patients have autosomal dominant mutations in the LKB1/STK11 gene and are prone to developing cancer , predominantly in the intestinal tract but also in other tissues , including the reproductive tracts and gonads . To elucidate the mechanisms disrupted by the loss of LKB1 in the reproductive tract , we have developed a mouse model with deletion of Lkb1 specifically in stromal cells of gynecologic tissues . These mice show stromal cell expansion and develop oviductal adenomas and endometrial cancer . Deletion of either Tsc1 or Tsc2 genes , which are mutated in patients with Tuberous Sclerosis Complex and whose protein products are indirect downstream targets of LKB1 signaling , resulted in some of the same defects observed in Lkb1 mutant mice . Activation of mammalian Target Of Rapamycin Complex 1 ( mTORC1 ) , a common effector of disrupted LKB1 , TSC1 , and TSC2 signaling , was observed in all mutant tissues examined , suggesting that uninhibited mTORC1 activity is necessary for the phenotypes . Suppression of mTORC1 signaling by rapamycin reduced tumor burden in Lkb1 mutant mice , confirming the link between dysregulation of mTORC1 to development of the Lkb1 mutant phenotype and suggesting that therapeutic targeting of LKB1/TSC1/TSC2/mTORC1 signaling would benefit human Peutz-Jeghers Syndrome and Tuberous Sclerosis patients with reproductive tract disease .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"gene",
"networks",
"cancer",
"genetics",
"genetic",
"mutation",
"obstetrics",
"and",
"gynecology",
"cancer",
"risk",
"factors",
"cancers",
"and",
"neoplasms",
"animal",
"models",
"oncology",
"model",
"organisms",
"biology",
"gynecological",
"tumors",
"mouse",
"autosomal",
"dominant",
"genetic",
"causes",
"of",
"cancer",
"genetics",
"human",
"genetics",
"gynecologic",
"cancers",
"genetics",
"and",
"genomics"
] |
2012
|
Stromal Liver Kinase B1 [STK11] Signaling Loss Induces Oviductal Adenomas and Endometrial Cancer by Activating Mammalian Target of Rapamycin Complex 1
|
Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates , their distribution across the genetic code and the resulting implications have received little attention . In general , studies of codon usage bias ( CUB ) assume that codons with higher tRNA abundance have lower missense error rates . Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics , we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code . Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera , we find a consistent positive correlation between tRNA abundances across the genetic code . This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB .
Protein production is the most energetically expensive metabolic process within a cell [1]–[4] . However , like all biological processes , protein translation is prone to errors . The biological importance of these translation errors and their impact on coding sequence evolution , especially the evolution of codon usage bias ( CUB ) , depends on both their effects on protein function and their frequencies . Translation errors fall into two categories: nonsense errors and missense errors . Nonsense errors , also referred to as processivity errors , occur when a ribosome prematurely terminates translating a coding sequence . Missense errors occur when the wrong amino acid is incorporated into a growing peptide chain . Although many possible factors such as mRNA stability and recombination likely contribute to the evolution of CUB , selection against translation errors and biased mutation are thought to be the primary forces [5]–[11] . Most researchers believe that CUB results primarily from selection against missense errors or , equivalently , for translational accuracy ( see [10] , [12]–[15] ) . In addition to limited empirical observations , the main evidence cited as supporting this belief includes the fact that preferred synonymous codons ( i . e . the codons over-represented in high expression genes ) have higher cognate tRNA abundances and that these codons are also favored at evolutionarily conserved sites [12] , [13] . While the preferred codons may indeed be ‘optimal’ in some limited sense , as we demonstrate below , the idea that they minimize missense error rates is based on an overly simplistic understanding of the relationship between tRNA abundances and missense error rates . The effect of missense errors on protein function is equivalent to a non-synonymous point mutation . Because amino acids with similar properties are clustered within the genetic code [16]–[19] , the genetic code is generally considered to be adapted to minimize the phenotypic effects of point mutations and missense errors . However , despite its importance , the adaptedness of tRNA abundances across the genetic code to reduce the rate of translation errors has received almost no attention . For instance , in E . coli the average nonsense and missense error rates are estimated to be on the order of to per codon , respectively [10] , [20]–[25] . This implies that for an average length gene of amino acids , about 3–26% of its protein products will contain at least one translation error . However , since the only available estimates of missense error rates are for specific amino acid misincorporations [20]–[22] , these rates are likely gross underestimates as they do not take into account all possible amino acid misincorporations at that codon . Currently , missense errors are thought to be the result of competition between tRNAs with the right amino acid ( cognates ) and the ones with the wrong amino acids ( near-cognates ) for the codon at the ribosomal A-site [25]–[27] . A near-cognate tRNA is characterized by a single codon-anticodon nucleotide mismatch and codes for an amino acid different from that of the A-site codon [28]–[30] . As a result of this competition , the rate of missense errors at a codon should be strongly affected by the abundances of both cognate and near-cognate tRNAs [25] . For example , an increase in cognate tRNA abundances is predicted to lead to a decrease in a codon's missense error rate . In contrast , an increase in near-cognate tRNA abundances is predicted to lead to an increase in a codon's missense error rate [25] . Previous studies of CUB have generally assumed that amongst a set of synonymous codons , the one with the correspondingly highest tRNA abundance is the one with the lowest missense error rate . However , because missense error rates are thought to be a function of both cognate and near-cognate tRNA abundances , if tRNA abundances are positively correlated across the genetic code this assumption may not hold . In this study we ask a fundamental question , “Are tRNA abundances correlated across the genetic code ? ” Finding that tRNA abundances are indeed generally positively correlated across a wide range of prokaryotes , we then ask , “How does the distribution of tRNA abundances affect the relationship between codon translation and error rates ? ” This question is of critical importance because the currently favored explanation of CUB , what we will refer to as the standard model , implicitly assumes that codons with the highest translation rates are also the ones with the lowest missense error rates . Our results indicate that this basic assumption only holds for a limited subset of amino acids . As a result , our work strongly suggests that missense errors play a smaller role in the evolution of CUB than currently believed and that the observed patterns of codon conservation observed by Akashi and others are likely due to other selective forces such as selection for translational efficiency or against nonsense errors .
Following [29] , our model of translation errors takes into account competition between cognate and near-cognate tRNAs for the ribosomal A-site during translation . We also consider the kinetics of tRNA selection within a ribosome [27] and the effect of codon-anticodon wobble on these kinetics [36] . During protein translation , when a ribosome waits at a given codon , one of three outcomes is likely to occur: ( a ) elongation by cognate tRNA , ( b ) elongation by a near-cognate tRNA leading to a missense error or ( c ) spontaneous ribosomal drop-off , frameshift or recognition by release factors , any of which will lead to a nonsense error ( Figure 2 ) . The relative frequency of each of these outcomes determines the rates of missense and nonsense errors at a particular codon . Assuming an exponential waiting process for a tRNA at codon , the codon specific missense and nonsense error rates , and respectively , can be calculated as follows , ( 1 ) ( 2 ) where is the codon specific cognate elongation rate , is the codon specific near-cognate elongation rate , and represents the background nonsense error rate ( see Methods for details ) . Using Equations ( 1 ) and ( 2 ) , we calculated codon-specific missense and nonsense error rates for each bacterial genome . In order to understand the effect of codon degeneracy on the relationship between error rates and codon elongation rates , we categorized amino acids based on the number of their synonymous codons as before . Given our model was parametrized from data on E . coli , we also checked for the sensitivity of our analysis to changes in these parameters when extending it to other prokaryotes ( Text S1 B ) . Using E . coli strain K12/DH10B ( K12 ) as an example , our estimates of codon-specific missense error rates ranged from with a median of . Six of the 61 sense codons have a predicted missense error rate of as these codons have no near-cognate tRNA species ( Table S2 ) . These rates are higher than recent empirical estimates of missense error rates in E . coli , which vary from with a median value of [25] . This is likely due to the fact that the missense error estimates in [25] were for specific amino acid misincorporations , whereas , the values predicted here indicate the rate of all possible missense errors at a given codon . Our predicted rates of codon-specific nonsense errors in E . coli ranged from with a median of ( Table S2 ) . We find that on average both missense and nonsense error rates decrease with an increase in cognate elongation rates ( Figure 3 ) . These results seem , on first glance , largely consistent with the standard model for inferring translation errors from tRNA abundances , which assumes that decreases with . However , because varies between synonymous codons , for about half of the amino acids ( 10 out of 21 ) is actually greater for the codon with the highest value . This holds even when empirical estimates of tRNA abundances in E . coli [31] are used instead of tRNA gene copy numbers ( see Figure S5 ) . This result is inconsistent with expectations under the standard model that implicitly assumes a codon-independent rate of elongation by near-cognate tRNAs , . If the abundance of a focal tRNA and its neighbors are uncorrelated , then the only factor that affects is . However , as shown earlier , and are positively correlated ( Figure 1 ) . Thus , the estimates of of synonymous codons of an amino acid depend not only on their individual but also on the slope of the relationship between and . If the rate of increase of with is higher than the relative increase in , then codons with higher cognate elongation rates are expected to have higher missense error rates ( Figure S2 ) . Interestingly , 8 out of the 10 amino acids in E . coli K12 showed a positive relationship between and . Specifically , we would expect to increase with whenever the condition is satisfied . Thus , among the synonymous codons of an amino acid in E . coli , the codon with the lowest is often not the codon with the highest . This points to a fundamental change in our understanding of the relationship between tRNA abundances and missense errors and which codons minimize their occurrence . Interestingly , these results are also consistent with the limited empirical estimates of codon-specific missense error rates . For instance , [22] used E . coli to estimate rates at which the asparagine codons AAC and AAU were mistranslated by . As expected , the authors found that the AAC codon , with a higher had a lower rate of mistranslation by than AAU , with a lower . Our model makes the same prediction when considering this specific subset of missense errors . However , when considering the overall missense error rates at AAC and AAU codons due to , , , , , and ( all one-step neighbors ) , we come to a very different prediction . Specifically we find that even though AAC has a higher than AAU , it also has a much higher rate . As a result , the overall missense error rate for AAC is actually predicted to be higher than AAU . This result illustrates how focusing on only a subset of possible missense errors at a codon , as all previous experiments have done , provides an incomplete and potentially misleading picture . In contrast to missense error rates , our model predicts will consistently decline with an increase in , suggesting that nonsense errors may be playing a larger role in driving CUB than commonly accepted [14] . In order to evaluate the relationship between cognate elongation rate , , and error rates , we looked across 73 bacterial genomes for inter-specific variation and 11 strains of E . coli for intra-specific variation . As before , we categorized amino acids based on the degeneracy of their synonymous codons for each genome . We calculated the fraction of amino acids within each category that showed a negative relationship between and error rates , and ( Figure 4 ) as expected under the standard model where the abundances of tRNAs are assumed to be uncorrelated . For both intra- and inter-specific datasets we find that synonymous codons with a higher have a lower nonsense error rate for all amino acids , irrespective of the degenerate class they belong to . However , in the case of missense errors , the relationship between and depends on the amino acid degeneracy as previously observed in E . coli K12 ( Figure 3 ) . Amino acids with two synonymous codons ( ) show a strong bias towards a positive relationship between and , both intra- and inter-specifically ( Binomial test , and , respectively ) . In the case of isoleucine , the only amino acid in , there exists no bias towards a positive or a negative relationship between cognate elongation and missense error rates ( Binomial test , intra-specific and interspecific ) . Interestingly 4-fold degenerate amino acids show a bimodal distribution of the fraction of genomes with a negative relationship , and the two 6-fold degenerate amino acids ( arginine and leucine ) show a strong bias towards negative correlation between and ( Binomial test , intra-specific and interspecific ) . The differences in the relationship between and across degenerate classes are similar to the differences in the correlation between and across these classes ( Figure 1 ) . Although the patterns we observe are complex and vary with amino acid degenerate classes , the assumption underlying the standard model that higher cognate tRNA abundance codons will have the lowest translation error rates is predicted to be clearly violated in the case of missense errors – a finding consistent both across bacterial genomes and across various E . coli strains . We also find that the positive relationship between missense error rates and observed within certain amino acids is insensitive to moderate changes in parameter estimates of background nonsense error rates , and wobble parameters ( Text S1 B ) .
For over 30 years , the standard model of translation errors has implicitly assumed that for any given amino acid , the translation error rates are lowest for the codons with the highest tRNA abundances [25] , [26] , [37] . With respect to missense errors , this prediction was based on the implicit and unstated assumption that the distribution of tRNA abundances across the genetic code are uncorrelated . Here we show a consistent positive correlation between the abundance of a tRNA and its one-step mutational neighbors across a wide array of prokaryotes . In order to understand the effects of this relationship on translation errors , we developed a simple model for estimating codon-specific error rates based on the distribution of tRNA gene copy number of a species . Our model takes into account tRNA competition , wobble effects , and intra-ribosomal kinetics of elongation to predict rates of missense and nonsense errors . To our knowledge , ours is the first model to integrate all these factors for estimating translation errors . Using our model , we find that on average , both missense and nonsense error rates of a codon decrease with an increase in its cognate tRNA elongation rate . This average behavior is consistent with expectations under the standard model of how codon specific error rates scale with cognate tRNA abundance [12] , [15] , [25] , [38] . However , the expected relationship between error rates and cognate tRNA abundances does not hold at finer scales of individual amino acids , the relevant scale for the evolution of CUB . For about half of the amino acids ( 10 out of 21 ) in E . coli K12 , synonymous codons that have higher cognate elongation rates also have higher missense error rates . This counterintuitive behavior is due to the fact that tRNA abundances within the genetic code are positively correlated , which leads to an increase in with , an important pattern that has been overlooked by previous researchers . We find a positive correlation between the abundance of a focal tRNA and that of its neighbors in 69 out of 73 genomes examined here . In addition , the 4 genomes that show a negative ( E . coli O157H7 , E . coli O157H7-EDL933 , Photobacterium profundum SS9 , Vibrio parahaemolyticus ) also show evidence of a high degree of horizontal gene transfer . Interestingly we also find that the differences in the relationship between and across amino acid degenerate classes is mirrored in the correlation between and . In contrast to , the nonsense error rates of synonymous codons decrease with an increase in for every amino acid across every genome we analyzed . This is due to the fact that increasing either or leads to a decrease in ribosomal wait time at that codon which , in turn , leads to a lower . Thus with respect to , a positive correlation between tRNA abundances actually accentuates the advantage of using codons with higher tRNA abundances . These results lend further support to the hypothesis that nonsense errors play an important but under-appreciated role in the evolution of CUB [11] , [39] . The role of tRNA competition has been recognized as an important factor in affecting translation error rates [25] , [26] , [29] . However , previous studies on the relationship between error rates and tRNA abundances have focused primarily on the effects of modifying cognate tRNA abundances and ignored the effects of near-cognate tRNA abundances . Consistent with our model behavior , [25] showed that when was over-expressed , it led to a decrease in the missense error rate at codons for which the tRNA was a cognate: AGA and AGG . However , if a higher expression level of reduces the frequency of at codons AGA and AGG , why is it not fixed in the population ? We argue that increasing the abundance of a given tRNA may not always be adaptive . For instance , over-expressing will also lead to an increase in at nearby non-synonymous codons - AAA , ACA , AUA , etc . , a testable prediction not considered by [25] . The trade-offs between reducing at one codon at the expense of increasing at nearby codons has not been explored . However , these trade-offs likely play an important role in shaping the evolution of tRNA gene copy number and force us to reconsider the evolutionary causes of CUB . Currently , many researchers believe that selection for translational accuracy , i . e . , against missense errors , is a primary force driving the evolution of CUB ( see [12] , [14] , [15] , [40] ) . This belief largely rests on the interpretation of two facts . Firstly , preferred codons are generally those with the highest corresponding tRNA abundances and secondly , sites that are highly conserved and thought to have large effects on protein structure and function , use preferred codons more often than their coding synonyms [12] . Selection for translational accuracy is usually tested using Akashi's test by identifying evolutionarily conserved sites in protein sequences and checking whether they are coded by preferred codons [10] , [12] , [15] , [41] . In light of the above results , we need to revisit the underlying assumptions of Akashi's test [12] . Although , our analysis predicts that a considerable number of amino acids have a positive relationship between missense error rates , and cognate elongation rates , many amino acids in are still predicted to conform to the standard model of lower with higher . Indeed , in the case of Drosophila species used in the original Akashi's paper [12] , only 4 out of 21 amino acids are predicted to have a positive relationship between and . Thus , we argue that the relationship between and are highly species and amino acid specific and that selection for translation accuracy cannot explain all of the observed CUB at conserved sites . In addition to selection for translational accuracy , selection against nonsense errors [11] , [39] , [42] , mRNA stability [6] and protein misfolding due to ribosome stalling [43] , [44] have been shown to affect CUB . In fact , recent evidence suggests that the speed of translating a codon also affects protein folding [43]–[45] . The presence of a codon with a low , increases the ribosomal waiting time at a codon potentially leading to alternate protein folds . This directly affects the functionality and stability of the protein . Thus , a codon with a higher at a conserved site , as observed by Akashi and others , could be under selection to prevent protein misfolding due to an entirely different mechanism unrelated to missense errors . Thus , we would like to stress that the definition of preferred codons used in the Akashis test is based on the genome-wide frequency of codon usage and not on any fundamental biological process . Although , we do not dispute the fact that certain codons are preferred over others at conserved sites , we simply point that the presence of these preferred codons at conserved sites cannot be explained entirely by selection against missense errors and that other selective forces must be responsible for the maintenance of these codons . CUB often increases with gene expression , such that highly expressed genes tend to use codons with a higher cognate elongation rate [11] , [35] , [46] . Thus , these genes would have lower nonsense error rates and wait times , but not necessarily lower missense error rates . This might appear paradoxical , as the failure to minimize missense error rate would presumably increase the probability that a translated protein would be rendered nonfunctional and be selected against . However , the deleterious effects of a high missense error rate can be mitigated by an increased robustness of highly expressed genes . According to [40] , [47] , [48] , highly expressed genes are expected to evolve at a slower rate and also be extremely functionally robust to missense errors . If this is the case , then missense errors in highly expressed genes may not have much of an effect on protein function . These genes maybe perfectly poised for trading off an elevated missense error rate for faster elongation and fewer nonsense error rates . When it comes to mitigating the effects of non-synonymous mutations and missense errors , the genetic code has been described as “one in a million” [17] . This is due to the fact that amino acids with similar chemical properties are in a genetic ‘neighborhood’ , thus reducing the phenotypic effect of any point mutation or missense error . However , unlike point mutations , the frequency of missense errors depends on the distribution of tRNA within the genetic code . The distribution of tRNA abundances is usually attributed to the coevolution between codon usage and tRNA abundances [49]–[51] . However , these studies have not taken into account how changes in tRNA abundances affect the rate of translation errors at neighboring codons . The degree to which the distribution of tRNA abundances within the genetic code is adapted to minimize translation errors remains largely unexplored . Our work suggests that understanding the trade-offs between missense and nonsense errors would provide significant insights into the evolution of tRNA abundances within the genetic code . We believe building mechanistic models of translation errors , as shown here , will help further our understanding of the evolution of tRNA abundances across the genetic code .
Assuming an exponential waiting process and simple diffusion , the rates at which cognate and near-cognate tRNAs enter the ribosomal A-site will be proportional to their abundances . As a result , translation error rates of a codon will depend , in part , on the relative abundances of its cognate and near-cognate tRNAs [25] . Following [8] , [31] , [32] , we use the GCN of a tRNA as a proxy for its abundance . Discrimination between cognate , near-cognate and non-cognate tRNAs takes place in the peptidyl transfer step of elongation . Since the underlying process is stochastic , there is a non-zero probability that when a cognate tRNA enters the A-site it will be rejected or a near-cognate tRNA will be accepted [27] . These probabilities are a function of the kinetic rate constants of various steps involved within the peptidyl transfer and translocation processes during tRNA elongation for both cognate and near-cognate tRNAs [27] , [52] , [53] ( Text S1 A ) . Based on the rate constants for cognate and near-cognate tRNAs from [27] and equations from [29] , we estimated the probability of elongation of a codon by a cognate and near-cognate tRNA per tRNA entry into the ribosomal A-site to be and , respectively ( Text S1 A ) . One of the factors affecting the rate constants in the intra-ribosome kinetic model described above , is the effect of codon-anticodon wobble . [27] proposed that a wobble mismatch between a codon and its cognate tRNA anticodon , will affect its kinetic rate constants ( Text S1 A ) and consequently reduce the probability of elongation by that tRNA . Based on [34] , [36] , we assume that a purine-purine or pyrimidine-pyrimidine wobble reduces the probability of a cognate tRNA being accepted , by 40% . This reduction in is consistent with estimates based on the kinetic rate constants estimated by [54] for codon that is recognized by through a pyrimidine-pyrimidine wobble . Similarly , based on [36] , we assume that a non-canonical purine-pyrimidine wobble ( GU/AC ) would reduce by 36% . In addition , some codons can be recognized by cognate tRNAs through a non-standard wobble as described by [55] , [56] . For instance , C-U and C-A anticodon-codon interactions are considered nonstandard owing to their stereochemistry and thermodynamic constraints . Hence , even though anticodon does not lead to a missense error when translating the codon , it is considered nonstandard translation due to its C-U wobble . We call these tRNAs ‘pseudo-cognates’ . We assume that the probability of elongation of a codon by pseudo-cognates is the same as that of near-cognate tRNAs , i . e . , . In order to predict per codon missense and nonsense error rates , we calculated the rates of elongation by cognate and pseudo-cognate tRNAs vs . near-cognate tRNAs at each codon . The cognate elongation rate for codon is given by ( 3 ) where is the set of cognate tRNAs for codon , represents the set of pseudo-cognate tRNAs , represents the gene copy number of tRNA species , and is the reduction in elongation probability due to wobble mismatch . Similarly , the rate at which near-cognate tRNAs elongate codon is given by ( 4 ) where is the set of near-cognate tRNAs with respect to codon . The parameter a represents a scaling constant between tRNA gene copy number GCN and elongation rate . For E . coli , we used a value of , so that the harmonic mean of elongation rates of all codons was [20] , [26] , [57] . We assume that nonsense errors occur primarily due to spontaneous drop-off of ribosomes at a given codon when it is waiting for a tRNA . As a result , the nonsense error rate due to spontaneous ribosomal drop-off , , is codon independent and occurs at a constant rate . [24] measured a nonsense error rate of per codons . If we assume , then the background rate of nonsense errors is .
|
Codon usage bias ( CUB ) is a ubiquitous and important phenomenon . CUB is thought to be driven primarily due to selection against missense errors . For over 30 years , the standard model of translation errors has implicitly assumed that the relationship between translation errors and tRNA abundances are inversely related . This is based on an implicit and unstated assumption that the distribution of tRNA abundances across the genetic code are uncorrelated . Examining these abundance distributions across 73 bacterial genomes from 20 different genera , we find a consistent positive correlation between tRNA abundances across the genetic code . We further show that codons with higher tRNA abundances are not always “optimal” with respect to reducing the missense error rate and hence cannot explain the observed patterns of CUB .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biochemistry/molecular",
"evolution",
"genetics",
"and",
"genomics/microbial",
"evolution",
"and",
"genomics",
"genetics",
"and",
"genomics/bioinformatics"
] |
2010
|
Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias
|
Schistosomiasis in humans along the lower Mekong River has proven a persistent public health problem in the region . The causative agent is the parasite Schistosoma mekongi ( Trematoda: Digenea ) . A new transmission focus is reported , as well as the first study of genetic variation among S . mekongi populations . The aim is to confirm the identity of the species involved at each known focus of Mekong schistosomiasis transmission , to examine historical relationships among the populations and related taxa , and to provide data for use ( a priori ) in further studies of the origins , radiation , and future dispersal capabilities of S . mekongi . DNA sequence data are presented for four populations of S . mekongi from Cambodia and southern Laos , three of which were distinguishable at the COI ( cox1 ) and 12S ( rrnS ) mitochondrial loci sampled . A phylogeny was estimated for these populations and the other members of the Schistosoma sinensium group . The study provides new DNA sequence data for three new populations and one new locus/population combination . A Bayesian approach is used to estimate divergence dates for events within the S . sinensium group and among the S . mekongi populations . The date estimates are consistent with phylogeographical hypotheses describing a Pliocene radiation of the S . sinensium group and a mid-Pleistocene invasion of Southeast Asia by S . mekongi . The date estimates also provide Bayesian priors for future work on the evolution of S . mekongi . The public health implications of S . mekongi transmission outside the lower Mekong River are also discussed .
Schistosomiasis in humans along the lower Mekong river ( specifically Cambodia and southern Laos ) was first recognized in 1957 [1] and has proven a persistent public health problem in the region [2] . The species involved is the parasitic blood fluke Schistosoma mekongi Voge , Buckner & Bruce 1978 , which uses the caenogastropod snail Neotricula aperta ( Temcharoen , 1971 ) ( Gastropoda: Pomatiopsidae: Triculinae ) as intermediate host . Published records identify the following foci of S . mekongi transmission: Ban Hat-Xai-Khoun , Khong Island , southern Laos [3] ; Kratié in Kratié Province , northeastern Cambodia , approximately 180 km downstream of Khong Island [4]; and San Dan , Sambour District , also in Kratié Province [5] ( Fig . 1A ) . Prior to 1994 up to 40% of the admissions to Kratié hospital were schistosomiasis-related and deaths were common place [5] . Following mass treatment with the anthelmintic Praziquantel , the prevalence in school children in Kratié Province fell from 40% in 1994 to 14% in 1995 [6] . In Laos , at Khong Island , a nine year Praziquantel intervention programme reduced the prevalence among village children from 51% to 27% [2] . There has been recent optimism regarding the possible complete control of S . mekongi infection [7] , [8]; however , this may be unfounded , not only because of the persistence of infection in reservoir hosts [9] , [10] , [11] , but also because the range of N . aperta ( and therefore the potential range of the disease ) has been underestimated . No new cases of severe morbidity have been reported in Cambodia since 2002 , but three new cases of human infection were reported in 2005 [12]; this highlights the resilience of transmission in the face of seven years of mass chemotherapy ( beginning 1996 ) . To date all published molecular studies on S . mekongi transmission , and much of the control efforts , have been restricted to little more than a 200 km stretch of the lower Mekong river . Recent surveillance of tributaries of the Mekong river , that drain the Annam highlands ( Fig . 1A ) , and of other river valley systems , have revealed new N . aperta populations . Recently 11 new N . aperta populations , involving six new river systems in Cambodia and Laos , were reported [13] . Many of the new populations lay outside the Mekong river valley , most were reported from the upper Xe Kong river valley . Prior to these studies the total population at risk was estimated to be 120 , 000 people [2]; however , after taking into account these new populations in areas beyond the lower Mekong river , the potential affected population rises to over 1 . 5 million . The findings also suggested that areas cleared of N . aperta by control efforts in the Khong Island area or in Kratié could be rapidly recolonized by snails from inaccessible populations in the tributaries draining the Annam mountains . In 2004 S . mekongi was detected in an N . aperta population at Sa Dao in the Xe Kong river of Cambodia ( Fig . 1A ) [13]; this was the first published direct evidence for the ongoing transmission of S . mekongi outside the Mekong river and further suggests that control of Mekong schistosomiasis will be problematic . Phylogeographies ( incorporating data on DNA-sequence variation ) have been used to study the evolutionary radiation of Asian Schistosoma Weinland , 1858 [14]–[16] , their relationships with other Schistosoma [17] , and their snail intermediate hosts [18]–[20] . Earlier studies suggested that Neotricula arrived in Laos after dispersing southwest from Hunan ( China ) via the Red river ( Fig . 1A ) [20]; this at a time when the Yangtze and Red rivers shared a common course some 400 km further West than at present ( prior to Pleistocene tectonic events affecting this region [21] ) . Davis ( 1992 ) [18] used snail phylogenies , and Attwood et al . ( 2002 ) [16] used DNA-sequence data for Schistosoma , to argue that Schistosoma japonicum Katsurada , 1904 and subsequently S . mekongi diverged from an antecedent resembling Schistosoma sinensium Bao , 1958 in the Shan region of China and Myanmar ( Fig . 1B ) . In this case S . mekongi would be expected to occur in northern and central Laos and even in Vietnam . Recent DNA-sequence based phylogenies show Schistosoma malayensis Greer et al . , 1988 as a sibling species of S . mekongi [22]–[24] . Indeed , the two species differ only in terms of intermediate host , life cycle parameters ( e . g . length of pre-patent period ) , and biogeography [25] . Examination of DNA-sequence variation between the intermediate hosts of S . malayensis and S . mekongi estimated their divergence at 5 Ma ( million years ago ) [26]; however , palaeogeographical models suggested that the two species were separated less than 1 . 5 Ma [26] . Després et al . [27] used an ITS2 molecular clock rate of 0 . 3–0 . 8% per Myr to date the divergence of S . japonicum from African species at 24–70 Ma . In contrast , Attwood et al . [28] estimated a divergence date of only 12 Ma on the basis of palaeogeography , available dispersal tracts and the radiation of definitive host groups . Després et al . [27] suggested that the divergence of S . haematobium in Africa , from other species infecting animals , was triggered by the colonization of savanna areas by hominids ( 1–10 Ma ) . Similarly , the wide host range of S . japonicum ( which is a true zoonosis ) has been explained as a result of very recent transfers from animals to modern humans [29] . In the present study samples of S . mekongi were taken from all published foci of infection and from a previously unknown population in Lumphat District of Northeast Cambodia; these enabled the first intraspecific study of S . mekongi . Surveys were performed in Lumphat because the region was accessible and there have been suggestions of past transmission in Rattanakiri Province [30] . The Lumphat taxon showed morphological differences ( larger eggs and cercariae ) from other populations . The work was undertaken to confirm the status of the Lumphat and Sa Dao taxa as S . mekongi , to provide the first divergence date estimates for the radiation of S . mekongi in Southeast Asia ( that can be used as priors in future studies ) , and to estimate a phylogeny for Southeast Asian Schistosoma which can be compared with phylogenies and historical biogeographical hypotheses for the intermediate hosts . The public health implications of the reported data are also considered .
Samples were taken in Cambodia , Laos and Pahang State , West Malaysia . Table 1 gives details of sampling sites , laboratory lines , dates of collection , sample codes , whilst Table 2 details other sources of DNA sequence data . Adult worms were obtained following published methods [16] using the hamster ( Mesocricetus auratus ) , as the laboratory definitive host , and cercariae from naturally infected snail intermediate hosts , but with the following exceptions . The MAL sample was obtained from field trapped rodents by perfusion [31] and the JAP sample was obtained from laboratory lines . Tegumental features ( tubercles , spines , etc . ) , gross internal anatomy and egg morphology were used to identify the worms . DNA was preferentially extracted from females or from separated worm pairs for which eggs had been observed and identified in corpo . Species identification followed relevant publications for S . japonicum [32]–[34] and for S . mekongi [32] , [33] , [35] . DNA was extracted from single adult worms using a standard method [36] . Sequence variation was assessed at two loci , being partial sequences of the mitochondrial ( mt ) cytochrome oxidase subunit I gene ( cox1 ) and the small ribosomal-RNA gene ( rrnS ) , here denoted as COI and 12S loci respectively . Sequences of the oligonucleotide primers used in the PCR for the amplification of rrnS locus are published elsewhere [16] . The rrnS region amplified corresponded approximately to positions 11433–11760 in the complete mt genome sequence of Schistosoma spindale Montgomery , 1906 ( see Littlewood et al . [37] ) . The COI locus was amplified using the HCO-2198 and LCO-1490 primer pair [38]; the region amplified using this primer pair corresponded approximately to positions 10224–10851 on the same complete mt sequence . Further details of the data set ( including sample sizes and GenBank accession numbers ) are given in Table 3 . The efficiency of the PCR varied considerably between populations and , in some cases , this effect and the small number of worms available to us , led to a low number of replicates for some populations . Two mt genes were selected because , with their maternal pattern of inheritance , and smaller effective population size , they were considered to represent potentially better recorders of phylogenetic events at the intra-specific to sibling species level . In addition , the loci targeted were those within regions previously shown to exhibit ideal levels of variation in Schistosoma for this type of study [16] , and those which had been used in earlier studies so that data were already available for the outgroup and for comparisons with related taxa . Total genomic DNA was used as a template for PCR amplification on a Progene thermal cycler ( MWG ) employing standard PCR conditions [39] . Unincorporated primers and nucleotides were removed from PCR products using the QIAQuick PCR purification kit ( QIAGEN ) . Sequences were determined bidirectionally , directly from the products by thermal-cycle-sequencing using Big Dye fluorescent dye terminators and an ABI 377 automated sequencer ( Perkin-Elmer ) , following procedures recommended by the manufacturers . DNA extracts were not pooled and one DNA sequence thus represented one worm . Sequences were assembled and aligned using Sequencher ( version 3 . 1 Gene Codes Corp . Ann Arbor , Michigan ) . DNA sequences for both strands were aligned and compared to verify accuracy . Controls without DNA template were included in all PCR runs to exclude any cross-over contamination . Consensus sequences for the populations sampled were grouped together into sets of aligned sequences of equal length ( one set for each locus ) , such that all taxa were represented in each set ( Table 3 ) . In addition , the COI and 12S sequences for each population were concatenated and aligned to form a combined data set . No intrapopulation variation was found among the sequences . Outgroup sequences were taken from the GenBank for Schistosoma incognitum Chandler , 1926 from Central Thailand . Phylogenetic analysis was conducted using both a solely maximum likelihood ( ML ) approach and a Bayesian method ( BM ) . The present data showed significant variation in the rate of substitution among sites , together with considerable bias among the six different types of nucleotide substitutions . In such cases , ML-based methods are considered more robust than most other commonly used phylogenetic methods , as they permit a better optimized model of substitution [40] . The three data sets were analysed separately by ML and BM . A suitable substitution model was selected using an hierarchical test of alternative models as implemented in Modeltest v . 3 . 06 [41] . A General Time Reversible model , with estimates for among site rate heterogeneity ( GTR+G ) , was the model selected for the COI data ( the-ln likelihood for this model was 2038 . 1306 , whereas the–ln likelihood for the next more complex model was 2037 . 0510; X2 = 2 . 1592 , P = 0 . 0709 ) . The Hasegawa , Kishino and Yano model , again with estimates for among site rate heterogeneity ( HKY+G ) , was the model selected for the 12S data ( the-ln likelihood for this model was 850 . 6237 , whereas the–ln likelihood for the next more complex model was 850 . 1796; X2 = 0 . 8882 , P = 0 . 1730 ) . The data were partitioned and the appropriate model applied to each partition during the analyses . The data were tested for substitution saturation using plots of the numbers of transitions and transversions against the ML genetic distance ( following DeSalle et al . [42] ) . The indications of these plots were further evaluated using the entropy-based test [43] as found in the DAMBE ( v . 4 . 5 . 29 ) software package [44] , which provides a statistical test for saturation . Statistics relating to polymorphism ( see Table 4 ) were computed using DNAsp ( v . 3 . 51 ) [45] . The incongruence length-difference ( ILD ) test [46] , as implemented in PAUP* ( v . 4 . 0b10; [47] ) , was used to test for homogeneity between the COI and 12S data partitions prior to combining them; the test was applied to informative sites only [48] . In all analyses , gaps were treated as missing data and all characters were run unordered and equally weighted . For the ML method heuristic searches were performed ( under the respective model and starting parameters indicated by Modeltest ) using PAUP* with random addition of sequences ( 10 replicates ) and tree-bisection-reconnection branch-swapping options in effect . Nodal support was assessed by bootstrap with 5000 replicates . Starting parameters for the BM were taken from Modeltest; these were then “optimized” using a ML method with the Brent Powell algorithm in the phylogenetics software suite P4 [49] . The values from these optimizations were used as starting parameters for the first Bayesian analyses . A Metropolis-coupled Markov chain Monte Carlo sampling process ( McMcMC ) [50] was used to search the parameter space of our evolutionary model and compute the posterior probability density . Although a direct ML method was used in this study this was mainly to afford comparisons with earlier work . The final inferences were made using a BM; this is in accordance with a growing opinion that Bayesian phylogenetic analysis is not only faster in terms of computing time ( for analyses with an equivalent level of confidence ) but also statistically superior to a solely ML method [51] . For example , such methods do not assume approximate normality or large sample sizes as would general ML methods [52]; they also allow the incorporation of prior information about the phylogenetic process into the analysis . In this study P4 was used to apply the BM; this employs the same method as MrBayes [53] but allows consideration of unresolved trees ( i . e . polytomies ) and provides an automated ( iterative ) procedure for tuning the McMC acceptance rates to acceptable levels . The McMC was thereby tuned to give proposal acceptance rates between 10 and 70% for each data partition ( this required over 5 , 000 replicates ) . The P4 analyses ( except for those using the polytomy prior ) were repeated in MrBayes ( 3 . 1 . 2 ) to reveal any topological disagreement . The priors specified for the BM generally followed the default values found in MrBayes; a flat Dirichlet distribution was set as the prior for the state frequency and for the rate set priors ( e . g . , revmat , tratio ) , the branch lengths were unconstrained . A polytomy proposal was set as either zero ( i . e . , no favouring of multifurcations ) or as e , e2 or 10 to examine the effect this has on the posterior probabilities of the clades found; this implements a move ( proposed by Lewis et al . , 2005 ) to counter the problem of the spuriously high posterior clade probabilities returned by MrBayes relative to corresponding ML analyses [54] . During the Bayesian analysis , model parameters and relative rates were set to be freely variable; there were four discrete rate categories for the Γ-distribution . Convergence of the McMC was assessed by plotting split support ( for the S . malayensis/mekongi partition ) for consensus trees over different generation time windows; the generation of convergence was considered to be that at which the support reached a plateau . In this way , a burnin of 400 , 000 generations was found to be adequate for all the analyses in this study . Posterior probabilities were then estimated over 900 , 000 generations beyond the assumed point of stationarity . Four simultaneous Markov chains were run ( one cold , three heated ) and trees were sampled every 10 generations , two such runs were performed simultaneously . After 900 , 000 generations ( post-stationarity ) the average standard deviation of the split frequencies ( between the two runs ) was checked; the McMC was considered complete if this SD was <0 . 01 . Likelihood ratio tests ( LRTs ) were performed to assess the applicability of a molecular clock across the whole phylogeny [55] . The program BEAST ( 1 . 4 . 3 ) [56] , [57] was used to estimate the rates . BEAST implements a Bayesian method for the simultaneous estimation of divergence times , tree topology and clock rates; this method is currently considered superior to other approaches ( e . g . , non-parametric methods such as NPRS [58] or penalized likelihood methods [59] , particularly for phylogenies with a low time depth , because it can allow for uncertainty in dates assigned to calibration points and does not require untested assumptions about the pattern of clock rate variation among lineages [60] . The procedure involves the user specifying both a phylogenetic model ( a model of evolutionary history; the tree model ) and a clock model ( of substitution and rate variation ) ; however , the likelihood calculation is based on the clock model only . Rate variation between adjacent branches is assumed to be uncorrelated , as these rates did not show autocorrelation in recent studies [61] . BEAST can implement several combinations of tree and clock models , but for several combinations it was not possible to obtain a stable result ( between replicate McMC chains ) or a sufficient effective sample size ( ESS ) for parameter estimates ( sufficient being >200 ) . The program TRACER ( 1 . 3 ) [62] was used to check convergence of the chains to the stationary distribution by visual inspection of plotted posterior estimates and to summarize parameter estimates , errors and confidence intervals . For those models which gave stable results , the ratio of the marginal likelihoods ( with respect to the prior ) of alternative models ( i . e . , the Bayes Factor ) was used to choose between them [63] ( who used importance sampling and the harmonic mean of the sampled likelihoods as an estimator ) ; this does not maximize the likelihoods but averages them over the parameters involved . The calculation was implemented using BEAST ( 1 . 5 alpha ) following [64] . Divergence dates ( Table 5 ) were taken from the Bayesian posterior distribution of the divergence of the taxa concerned . The greatest benefit of using a Bayesian method for dating is that the specification of prior distributions can be used to ensure that the analysis realistically incorporates the uncertainty associated with the calibration points used [65] . The models and the priors for the BEAST analyses were set as follows . The tree model prior assumed that divergence patterns followed a Yule process where symmetrical trees are considered more probable ( i . e . a simple uniform probability of speciation ) ; this prior and a basic coalescent model ( which assumed a constant population size over the time period concerned ) were used to obtain the starting tree for the analysis . The clock rates were drawn from either a log normal distribution or an exponential distribution , which were then used to specify the probability of a certain substitution rate on a particular lineage during the McMC . The GTR+G model was applied to the COI partition and HKY+G to the 12S ( GTR+ss ( ss , site specific rates ) could not be used owing to a paucity of polymorphic sites at the first codon position , which causes the BEAST analysis to stall ) . A normal clock rate prior was specified ( 0 . 035±0 . 0071 substitutions per site per Myr ) ; this was based on rates for S . mansoni and S . incognitum estimated elsewhere [66] ) . A normal prior ( 5 . 0±0 . 1 Ma ) was applied to the TMRCA for the ingroup; this corresponded to the second major Himalayan orogeny which could have isolated central Asian taxa from those of the Orient [28] . For the final parameter estimates three independent runs of 130 million generations were combined to give a final set of 390 million states; the burnin was set to 10% .
Table 4 provides basic statistics for the two loci and the combined data . The COI data appeared the most informative having a greater proportion of parsimony informative polymorphic sites ( 12 . 3% of the total number of aligned sites , excluding gaps , compared with 5 . 4% for 12S ) . Similarly , 34 . 6% of positions were polymorphic in the COI data set ( of these 35 . 5% were informative sites , the remaining 64 . 5% being singletons ) and only 23 . 8% in the 12S set ( of which 22 . 7% were informative ) . For the COI data 201 mutations were inferred of which 121 ( 60 . 2% ) were synonymous and 80 ( 39 . 8% ) were amino acid replacements . The test of Xia et al . [43] suggested that there were no significant levels of substitution saturation at either locus ( ISS<ISS . C , P<0 . 0001 , a lack of statistical significance here would imply a poor phylogenetic signal ) . Table 4 also shows that the nucleotide diversity ( D ) was greater for the COI data . The haplotype diversities for the full taxa set ( H , Table 4 ) show that not all taxa had unique haplotypes . In the COI set the HXK , SDN and SDO samples shared a common “lower Mekong river” haplotype . Among the 12S sequences SDN , SDO , LMP and S . malayensis shared a common haplotype; that S . malayensis was indistinguishable at this locus highlights its close relationship with S . mekongi . In the combined COI+12S data set each taxon was represented by a unique haplotype , except for SDN ( which was identical in state to SDO ) which was excluded from the Bayesian analysis . In all cases the test of Tajima ( 1989 ) [67] failed to refute the hypothesis of neutral evolution . LRTs for all data sets failed to support the hypothesis that the different lineages had been evolving at the same rate ( -ln likelihood with a clock enforced 2932 . 5967 , without clock 2921 . 57447; X2 = 22 . 04 , P = 0 . 0005 ) . Phylogenies estimated using ML showed the same topology with all three data sets , aside from differences due to the number of distinct haplotypes . An LRT comparing the GTR+G and GTR+ss models for the COI data indicated a significant difference between them ( X2 = 8 . 71 P = 0 . 0128 , d . f . = 2 ) favouring GTR+ss , consequently this model was used for the COI partition in the Bayesian analysis of the combined data set ( but GTR+G was used in the BEAST analyses , see METHODS final section ) . Figure 2 shows the tree resulting from phylogenetic estimation using BM and the COI+12S data set; this tree is identical to that of the ML analysis except that with ML there is an unresolved trichotomy for the three S . mekongi populations . Performing the BM with the polytomy prior turned off resulted in posterior probabilities >0 . 97 ( except for the HXK/SDO node at 0 . 39 ) ( Fig . 2 ) , increasing the prior to e led to a slight drop in the probabilities , further increases to e2 and 10 had little further effect . The topology and split support using MrBayes was very close to that of P4 with the polytomy prior turned off . Schistosoma malayensis is confirmed as a sibling species of S . mekongi and the S . mekongi populations form a monophyletic unit on the tree; the statistical support for these groupings is high ( 1 . 00 ) . The S . mekongi population of LMP appears as sister to a clade comprising the HXK and SDO populations , in the S . mekongi lineage , but this relationship is less well supported ( posterior probability only 0 . 39 ) . Aside from the Yule process several more complex models of past population dynamics can be implemented using BEAST ( e . g . past exponential , logistic or expansive growth and the Bayesian skyline model ) ; however none of these gave stable results ( after multiple runs of several 100 million states with tuning and prior-adjustments , or varying starting trees ) or they had very low likelihoods . LRT indicated that a strict molecular clock model was inappropriate for these data ( P = 0 . 0005 ) . Consequently the Yule model was used in the final analyses in this study and the log normal and exponential clocks were compared . Table 5 shows the results of a Bayesian estimate using a Yule tree model and an uncorrelated log normal relaxed clock . Comparison of the posterior log likelihood of this model with that for the next best model ( Yule process with an uncorrelated exponential clock ) gave a Bayes factor of 22 . 35 which strongly favoured the log normal model . The TMRCA values given in Table 5 are summarized from the Bayesian posterior distribution of the divergence times of the taxa involved in the partition . The exponential clock model gave much lower TMRCAs than the statistically “preferable” log normal model; for example , TMRCA ( mekongi ) 9 , 760 years before present ( YBP ) , TMRCA ( malayensis ) 45 , 512 YBP , TMRCA ( japonicum ) 242 , 690 YBP . Plots for the posterior distribution of estimates of mutation rate and the TMRCAs in the Yule/log normal analysis were bell-shaped and showed no cut-off at the upper or lower bounds; this suggested that the priors used were not restricting the range of values implied by the data [68] ( this restriction was found with other model/prior combinations ) . The wide range of the HPDs in for the divergence time estimates in Table 5 reflects the uncertainty inherent in all molecular date estimates; this is not unusual and is a realistic feature of this method of analysis .
The Schistosoma indicum to ingroup divergence date of around 4 . 6 Ma ( see Table 5 ) implies a 2 . 5% ( of sites varying per Ma ) clock for COI and a 2 . 0% clock for the 12S locus; these figures appear to be moderate values and compare well with published rates of 1–2% for African and South American Schistosoma at mt loci [27] , of 3% for S . indicum-group taxa [28] , and of 1% averaged across metazoan groups in general [69] . Attwood et al . [26] suggested a divergence date of 5 Ma for the intermediate hosts of S . mekongi/malayensis , whereas the TMRCA corresponding to this divergence for the parasites themselves in the present study was approximately 2 . 5 Ma . The S . D . of this estimate is only 4% but the confidence interval is wide , from c . a . , 200 KYBP ( thousand years before present ) to 5 Ma; these wide 95% confidence intervals are common for Bayesian date estimates , they are wider than those of ML based point estimates but this is only because other methods fail to account fully for the uncertainty in the estimation procedure . Attwood et al . [26] used a simple point estimate of divergence times based on pairwise genetic distances ( following [70] ) and relied on a general invertebrate clock for calibration . Such methodological differences may explain the incongruence between snail and parasite phylogeographies . The phylogeny in Figure 2 shows all of the Schistosoma mekongi populations , including that of LMP , as lying within a monophyletic clade and this hypothesis is well supported ( posterior probability = 1 . 00 ) . Consequently , it appears that the Schistosoma found in the Srepok river is indeed S . mekongi; this finding has implications for schistosomiasis surveillance in Vietnam . The Srepok river originates in Vietnam and flows westwards into Cambodia . Initial studies suggested that Neotricula aperta evolved in northern Laos/Thailand from a lineage dispersing from India , via Tibet and Yunnan ( China ) , along the Miocene extended upper Irrawaddy and Mekong rivers; the same historical biogeography was assumed for S . mekongi diverging from S . japonicum [71] . However , more recent work suggested an origin for both proto-S . mekongi and proto-N . aperta in Hunan or Guangxi Provinces , China , with a Yangtze-Red river radiation into Cambodia via Vietnam [2] . At least five species of Neotricula Davis , 1986 are known from Hunan but only one from Laos and none from Yunnan; therefore it is more likely that Neotricula and an antecedent of S . mekongi arrived in Vietnam and Cambodia directly from Hunan and not from Yunnan , via Thailand and Laos [20] . Palaeogeographical evidence appears to favour the Vietnam-Cambodia dispersal hypothesis . Much of the Annam mountain chain ( which today forms a barrier between Hunan and northern Laos and Vietnam ) is Mesozoic and at 1 . 3 Ma the only trans-Annam dispersal corridor would be the 900 km long valley of the Red river fault , which in the past ran up to 400 km closer to Laos than today [21] . The Pliocene Yangtze is also reported to have flowed along a common course with the Red river [72] . The present data yielded an estimated date for the radiation of S . mekongi in Cambodia of around 1 Ma; this is just before the uplift of ( volcanic ) highlands in Southeast Cambodia when it would have been possible for S . mekongi to enter Cambodia from Vietnam , just South of the Kontum range . The Srepok river population ( LMP ) in southern Cambodia is seen as a sister taxon to the other ( Xe Kong and lower Mekong river ) populations in Figure 2 and may have been early divergent . A phylogenetically basal Srepok river population would be in agreement with the idea of an S . mekongi radiation beginning in Southeast Cambodia; however , the support for this clade was low ( posterior probability = 0 . 39 ) and only three endemic geographical regions are available for comparison . The North to South tract , from Yunnan to northern Thailand/Laos and then Cambodia , as proposed in an earlier publication [71] cannot readily explain the absence of S . mekongi from suitable transmission habitats in central Laos . The only known foci of transmission are on the border with Cambodia , around Khong Island at the southern tip of Laos . In contrast , a South to North dispersal together with the Pleistocene ( i . e . , relatively recent ) divergence date estimated here , explains the current range of S . mekongi as a consequence of the limited time available for dispersal from Cambodia into Laos . The Dangrek escarpment lies immediately East of HXK ( Fig . 1A ) ; these Mesozoic hills are a likely effective biogeographical barrier between Cambodia and Laos . S . malayensis has been regarded as a geographical isolate derived from the S . mekongi radiation in Cambodia [2]; however , Figure 2 shows S . malayensis as sister to the S . mekongi clade and the divergence dates of 2 . 5 Ma estimated for S . malayensis/mekongi and around 3 . 8 Ma for S . japonicum/Southeast Asian Schistosoma suggest that S . malayensis is basal in the true phylogeny rather than a derivative of S . mekongi . The ancestral definitive hosts of Asian Schistosoma were probably rodents [20] . S . malayensis appears to have retained this ancestral condition , with S . mekongi showing derived character states , that is the ability to utilise humans and Neotricula aperta as definitive and intermediate hosts , respectively . N . aperta is a snail of larger faster rivers than the springs and primary streams to which S . sinensium and all other Neotricula spp . are restricted . The Pliocene Dong-Ngai-Mekong river could have introduced an S . malayensis/mekongi antecedent to the whole Sundaland drainage , with later range contraction , fragmentation and divergence . The divergence time of 2 . 5 Ma coincides with a major intensification of monsoon winds affecting rainfall and flow patterns in the rivers of the region [73]; this would have impacted on the distribution of the intermediate hosts and could have isolated Cambodian proto-S . mekongi from Malaysian S . malayensis . The mean date estimates obtained here agree well with palaeogeographical data and hypotheses based on snail phylogenies . For example , the radiation of S . mekongi in Cambodia ( dated at 1 . 3 Ma ) correlates well with Pleistocene tectonic upheavals in the region . The severity of late Cenozoic tectonic events in Sundaland strongly suggests that the lower Mekong river ( in the area of SDN and Kratié ) did not occupy its present course until 5–6 KYBP [74] . Consequently , all known extant S . mekongi populations must have been established mid- to late Pleistocene . The Pleistocene Mekong river itself flowed further west , along the Dangrek escarpment then southwards along the Tonlé Sap of today , and across the Sunda shelf from Kampot ( Cambodia ) to the present day West Malaysia [75] ( Fig . 1A ) . The divergence of the S . sinensium group from Central Asian lineages ( here represented by S . incognitum ) dated at 4 . 6 Ma agrees with the published hypothesis [20] , based on snail phylogenies , that the divergence of the S . sinensium group was triggered by isolating events linked to the second major Himalayan uplift ( 5 Ma ) . Consequently , the date estimates obtained here are useful priors upon which further studies based on independent data may be undertaken . The work has demonstrated that transmission at all of the known foci of human schistosomiasis in the lower Mekong Basin involves S . mekongi , including the apparent zoonotic focus in the Srepok river . The phylogeny and divergence dates estimated , although not conclusive , correlate well with the idea of a Vietnam to Cambodia entry of S . mekongi into the lower Mekong region , with a subsequent South to North radiation from Cambodia into Laos . The study also demonstrates the transmission of S . mekongi in the Srepok river close to Vietnam . Such observations and inferences have certain public health implications . The likelihood of finding S . mekongi in Vietnam is increased in the light of these results . The inferred South to North dispersal of S . mekongi implies that it is not ecology but history which is limiting the current distribution of Mekong schistosomiasis . Further work is required into this problem , as , if we have no reason to assume that ecological conditions in Laos are unsuitable for transmission , we may expect the future spread of this disease northwards into Laos . Recent work has already demonstrated that the range of N . aperta is far greater than previously thought ( particularly in Central Laos ) [13] . The loci used here were chosen for a population phylogenetic study , with no expected intra-population variation , and not for population genetic work . Consequently , the genetic divergence among the S . mekongi populations was relatively small . Further work should involve additional loci and possibly also microsatellites; however , microsatellites are costly to develop and use in endemic countries and are less ideal for dating because they rely on genetic distance estimates of less certain reliability . In spite of low divergence levels , the date estimates obtained were biologically reasonable in the context of independently derived time frames and will be useful priors in future studies .
|
Schistosomiasis is a disease caused by parasitic worms of the genus Schistosoma . In the lower Mekong river , schistosomiasis in humans is called Mekong schistosomiasis and is caused by Schistosoma mekongi . In the past , Mekong schistosomiasis was known only from the lower Mekong river . Here DNA-sequence variation is used to study the relationships and history of populations of S . mekongi . Populations from other rivers are compared and shown to be S . mekongi , thus confirming that this species is not restricted to only a small section of one river . The dates of divergence among populations are also estimated . Prior to this study it was assumed that S . mekongi originated in Yunnan , China , migrated southwards across Laos and into Cambodia , later becoming extinct in Laos ( due to conditions unsuitable for transmission ) . In contrast , the dates estimated here indicate that S . mekongi entered Cambodia from Vietnam , 2 . 5–1 Ma . The pattern of genetic variation fits better with a more recent , and ongoing , northwards migration from Cambodia into Laos . The implications are that Mekong schistosomiasis is more widespread than once thought and that the human population at risk is up to 10 times greater than originally estimated . There is also an increased possibility of the spread of Mekong schistosomiasis across Laos .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/helminth",
"infections",
"genetics",
"and",
"genomics/population",
"genetics",
"evolutionary",
"biology/evolutionary",
"ecology",
"evolutionary",
"biology/evolutionary",
"and",
"comparative",
"genetics"
] |
2008
|
DNA-Sequence Variation Among Schistosoma mekongi Populations and Related Taxa; Phylogeography and the Current Distribution of Asian Schistosomiasis
|
Post-transcriptional modifications of transfer RNAs ( tRNAs ) have long been recognized to play crucial roles in regulating the rate and fidelity of translation . However , the extent to which they determine global protein production remains poorly understood . Here we use quantitative proteomics to show a direct link between wobble uridine 5-methoxycarbonylmethyl ( mcm5 ) and 5-methoxy-carbonyl-methyl-2-thio ( mcm5s2 ) modifications catalyzed by tRNA methyltransferase 9 ( Trm9 ) in tRNAArg ( UCU ) and tRNAGlu ( UUC ) and selective translation of proteins from genes enriched with their cognate codons . Controlling for bias in protein expression and alternations in mRNA expression , we find that loss of Trm9 selectively impairs expression of proteins from genes enriched with AGA and GAA codons under both normal and stress conditions . Moreover , we show that AGA and GAA codons occur with high frequency in clusters along the transcripts , which may play a role in modulating translation . Consistent with these results , proteins subject to enhanced ribosome pausing in yeast lacking mcm5U and mcm5s2U are more likely to be down-regulated and contain a larger number of AGA/GAA clusters . Together , these results suggest that Trm9-catalyzed tRNA modifications play a significant role in regulating protein expression within the cell .
A striking feature of tRNA molecules is the large number of post-transcriptional modifications , representing up to 10% of the ribonucleoside content [1 , 2] . Ranging from simple base methylation to complex modifications involving multiple enzymatic steps , modified ribonucleosides are phylogenetically widespread and have long been recognized to play crucial roles in tRNA functions [1 , 3–5] . Modifications in or around the anticodon loop of tRNA affect translation rate and fidelity through stabilization of codon-anticodon pairing , while other modifications remote from the anticodon loop have specific roles in regulating tRNA stability and folding [1 , 3 , 4 , 6–10] . These observations fuel the hypothesis that tRNA modifications play a broader role in regulating global protein expression , with a focus here on wobble uridine modifications catalyzed by tRNA methyltransferase 9 ( Trm9 ) in budding yeast . Modification of the wobble uridine in tRNAArg ( UCU ) , tRNAGly ( UCC ) , tRNALys ( UUU ) , tRNAGln ( UUG ) and tRNAGlu ( UUC ) requires a number of key activities ( Fig 1 ) . The Elongator complex ( ELP1-ELP6 ) uses uridine as a substrate and catalyzes the formation of 5-carboxymethyluridine ( cm5U ) . In association with Trm112 , Trm9 will use cm5U as a substrate and catalyze the formation of 5-methoxycarbonyl-methyluridine ( mcm5U ) at the wobble position of tRNAArg ( UCU ) , tRNAGly ( UCC ) , tRNALys ( UUU ) , tRNAGln ( UUG ) and tRNAGlu ( UUC ) ( Fig 1 ) [11–14] . The wobble position of tRNALys ( UUU ) , tRNAGln ( UUG ) and tRNAGlu ( UUC ) is further thiolated by an enzyme cascade involving Urm1 , Uba4 , Ctu1 , Ncs2 and Ncs6 to yield mcm5s2U ( Fig 1 ) [11 , 12 , 14] . We and others have performed studies in budding yeast , which suggest that stress-induced reprogramming of wobble modifications in tRNA leads to enhanced translation of codon-biased mRNAs for critical stress response genes . [15–19] . For example , we showed that deficiencies in Trm9 and another anticodon loop tRNA methyltransferase , Trm4 , cause sensitivity to DNA alkylating agents ( methylmethane sulfonate , MMS ) and reactive oxygen species ( H2O2 ) , respectively [16 , 20–23] . The roles of the tRNA modifications catalyzed by Trm4 and Trm9 in the cell response were found to involve stress-induced increases in wobble m5C in tRNALeu ( CAA ) and wobble mcm5U in tRNAArg ( UCU ) and tRNAGln ( UUG ) , respectively . With Trm9 , these changes were directly linked , by Western blots , to enhanced translation of several stress response proteins enriched with AGA and GAA codons [20] . These results not only support the idea that dynamic changes in tRNA wobble modifications facilitate translation of critical stress response proteins [19 , 20] , but they also raise the possibility of an alternative or accessory genetic code involving selective use of degenerate codons as an adaptation for translational regulation by tRNA modifications . Although there are several examples of individual genes supporting this notion [8 , 10 , 17 , 20 , 24] , what is lacking in this model for translational control of stress response is the larger view of the role of tRNA modifications in regulating global protein expression . Regulation of protein expression occurs at a variety of different levels [25–27] , for example , by regulating transcription activity , splicing efficiency , and mRNA export and stability [25 , 28–33] . Moreover , different stages of protein synthesis are also subject to regulation to ensure efficiency and to preserve fidelity [25 , 26 , 34] . Among the variety of factors regulating gene expression , very little is known about the role of tRNA modifications as determinants of global protein translation . Recent studies have shown that loss of Ctu1 or ELP3 result in a moderate reduction in the global protein expression [10] , while urm1 and elp3 knockout impairs translation of proteins with high usage of AAA , CAA , and GAA codons [9] . Using ribosomal footprinting , two recent genome-based studies measured average ribosome occupancy on each codon type in several yeast U34 modification mutants [24 , 35] . While there were striking discrepancies between the two similar studies , the consistent results suggested that loss of wobble uridine modifications in ncs2Δ , ncs6Δ , elp3Δ and elp6Δ mutants leads to changes in ribosome occupancy for some codons associated with tRNAArg ( UCU ) , tRNAGly ( UCC ) , tRNALys ( UUU ) , tRNAGln ( UUG ) and tRNAGlu ( UUC ) . Of particular note , however , is that the effects caused by loss of U34 modifying enzymes on overall ribosome occupancy on each codon type were averaged over the genome and thus did not reflect codon usage patterns in individual genes , which greatly limits their regulatory conclusions . To address these problems and identify gene-specific regulatory rules , we performed an integrated analysis of proteome , transcriptome and gene-specific ribosome footprinting to investigate the role of Trm9-catalyzed tRNA modifications , mcm5U and mcm5s2U , in regulating global protein expression .
With the overall goal of assessing the effects of loss of Trm9 and its products mcm5U and mcm5s2U on global protein translation , we first verified that modified ribonucleosides mcm5U and mcm5s2U were absent in the trm9Δ cells ( S1A and S1B Fig ) while the abundance of the hypomodified tRNA species were not significantly affected ( S1C Fig ) under both normal and stress conditions . These results corroborate previous studies [4 , 11 , 12 , 16 , 20 , 36] and establish the trm9Δ cells as a well-controlled model system for analyzing the influence of tRNA modification on global protein expression . We then used a SILAC-based quantitative proteomic analysis to assess global protein expression in unexposed and MMS-exposed wild-type ( WT ) and trm9Δ yeast [37] . Proteins derived from lys1Δ yeast grown with [13C6 , 15N2]-L-lysine were used as an internal standard that was added to protein extracts in each sample , with quantitation of proteins relative to this standard accomplished by LC-MS/MS analysis of protein digests [37] . Protein coverage was maximized by extensive peptide fractionation using an off-gel isoelectric focusing system [38] . Using this approach , we achieved high-confidence identification of 2 , 408 proteins with a false-discovery rate of 0 . 46% ( S1 Table ) and good reproducibility for the three biological replicates analyzed for each cell type and treatment condition ( S1D and S1E Fig ) . Interestingly , protein expression patterns showed greater similarity between the same yeast strains under different treatment conditions than between different yeast strains under the same conditions , which indicates that loss of Trm9 has a stronger influence on global protein expression than MMS treatment . Altogether , we identified 231 proteins that were significantly down-regulated and 95 up-regulated proteins in trm9Δ cells compared with WT cells during normal growth ( p <0 . 05 , Student’s t-test and fold-change >1 . 2 ) ( S2 Table ) . We also identified 195 significantly down-regulated proteins and 137 significantly up-regulated proteins in trm9Δ cells in response to MMS treatment ( S2 Table ) . We first examined whether changes in protein expression are highly selective given the assumption that , after controlling for protein length , proteins with enhanced usage of codons dependent on these wobble modifications are more likely to be down-regulated in trm9Δ cells . In this case , we would expect to see genes enriched with mcm5U-dependent codons AGA and GGA , as well as mcm5s2U-dependent codons , CAA , GAA and AAA , to be selectively down-regulated . Moreover , it has been shown that the mcm5 side chain facilitates wobble decoding for G-ending codons [4] . Accordingly , proteins enriched with AGG and GGG codons may likewise be affected by loss of mcm5U . To this end , we analyzed gene-specific codon usage patterns for all 5886 genes in the yeast genome to determine groups of proteins that are significantly enriched with each codon . A Z-score was calculated to indicate whether a certain codon is over- or under-represented in each individual gene compared to the genome average . Hierarchical clustering analysis of Z-scores of all genes revealed clusters of codons with relatively similar patterns of usage across different genes ( Fig 2A; codon usage data for individual genes is presented in S3 Table ) . The heat map in Fig 2A shows clustering of CAA , AGA and GAA codons , which is distinguished from clustering of GGG , AGG and GGA codons , while the AAA codon was separated from the others . We then asked whether proteins enriched with these wobble modification-dependent codons were selectively down-regulated in trm9Δ cells . To this end , we calculated the number of significantly down-regulated proteins in each group of proteins enriched with one of the 61 codons . Moreover , to control for the size of different groups and the randomness of changes in protein expression , the percentage of down-regulated proteins , as well as the ratio of the number of down-regulated proteins to the number of up-regulated proteins ( D/U ) in each group were calculated . For example , in our proteomic dataset , 148 proteins overrepresented with AGA codon were identified and quantified , of which 54 ( 36 . 5% ) were significantly down-regulated , while only 10 were significantly up-regulated in trm9Δ cells ( D/U = 5 . 4 ) . Among the 196 proteins with high GAA usage , 45 ( 23 . 0% ) were significantly down-regulated and 10 were significantly up-regulated in trm9Δ cells ( D/U = 4 . 5 ) . In contrast , for all 2408 proteins identified , only 231 ( 9 . 6% ) were down-regulated while 95 were up-regulated ( D/U = 2 . 4 ) . As shown in Fig 2B and 2C , the percentage of down-regulated proteins and D/U ratios were significantly enhanced in AGA- and GAA-enriched groups as compared with the genome average . In addition , the CAA group showed a high D/U ratio but the percentage of down–regulated proteins showed no difference from the genome average . This suggested that proteins from genes enriched with AGA/GAA codons were preferentially down-regulated in trm9Δ cells . In contrast , we observed no evidence that expression of proteins from genes enriched with GGA , GGG , AGG or AAA were selectively inhibited in trm9Δ cells . One possible explanation for lack of effect is that these codons are all non-optimal codons with low overall usage in the genome ( see Discussion ) . However , several codons independent of the modifications were also associated with a high proportion of down-regulated proteins , which could be explained by co-enrichment of these codons with AGA and GAA . To investigate the influence of codon co-enrichment , we removed proteins enriched with both AGA and another codon from the group of proteins enriched with AGA , and vice versa . As shown in Fig 2D , this analysis revealed that high usage of the AGA codon , to the exclusion of any other codon , remained the single best predictor for protein down-regulation in trm9Δ cells . In contrast , as expected , the percentages of down-regulated proteins were reduced after removing proteins whose reduction could be better explained by co-enrichment of AGA codon . A similar result was observed for the GAA enriched group ( Fig 2E ) . In response to MMS treatment , changes in global protein expression in trm9Δ cells were likewise skewed as a function of high usage of AGA and GAA codons , but not the other codons dependent on the wobble modifications ( S2A–S2D Fig ) . Taken together , these results support a role for mcm5U and mcm5s2U modifications in regulating proteins enriched with AGA and GAA codons under both normal growth and stress conditions , establishing that Trm9-catalyzed tRNA modifications play a significant role in regulating protein expression . We then examined whether proteins enriched with AGA or GAA codons were more likely to be down-regulated than expected by chance in trm9Δ cells and whether the results could be better explained by , for example , changes in mRNA level or biased protein expression . To this end , for proteins enriched with AGA codon ( n = 148 ) , we performed 100 , 000 random samplings of 148 proteins from the proteins that are not enriched with AGA codon , and calculated the percentage of down-regulated proteins and D/U ratio for each sampling . This analysis demonstrated that groups of proteins from genes enriched with AGA were more likely to possess a higher proportion of down-regulated proteins ( Fig 3A ) as well as a greater D/U ratio ( Fig 3C ) than expected by chance . Similarly , proteins enriched with GAA codons ( n = 196 ) were more likely to be down-regulated than genome average in trm9Δ cells ( Fig 3B and 3D ) , but not for those enriched with the other codons dependent on the wobble modifications ( S3A–S3J Fig ) . Taken together , these results suggest that depletion of mcm5U and mcm5s2U represses expression of proteins enriched with AGA and GAA codons in a highly selective manner . However , this analysis could be misleading without controlling for changes in mRNA levels , which may be a major contributor to the changes in protein expression . To this end , we combined the proteomic data with our previous microarray data from trm9Δ cells [19] . We found that changes in protein level and changes in mRNA expression were not correlated , with only 4% ( 13 out of 326 ) of the significantly changed proteins explained by changes in mRNA level . We then repeated the analysis after removing these proteins from the dataset . As expected , proteins enriched with AGA and GAA codons were still preferentially down-regulated in trm9Δ cells ( S4A and S4B Fig ) . Another feature in question was a bias caused by protein abundance . As shown in S5A and S5B Fig , proteins from genes with high usage of AGA and GAA codons were skewed toward highly expressed proteins . Accordingly , these proteins may be more dramatically down-regulated because they were present at higher levels in WT cells . To control for this , we repeated the analysis by randomly selecting a group of proteins with the same expression level as proteins enriched with AGA or GAA codon , respectively , in each sampling . As shown in S5C and S5D Fig , after controlling for protein abundance , proteins from genes enriched with AGA or GAA were still more likely to be down-regulated in trm9Δ cells than expected by chance . We then examined the possibility that a specific protein is down-regulated in trm9Δ cells as a function of increased usage of AGA/GAA codons in all proteins , regardless of whether they are enriched with AGA/GAA codons or not . As shown in Fig 3E and 3F , we found that reduced protein expression in trm9Δ cells was significantly correlated with enhanced usage of AGA ( rs = -0 . 17 , p = 2 . 8E-09 ) and GAA ( rs = -0 . 17 , p = 7 . 4E-08 ) , respectively . Furthermore , we binned proteins into seven groups based on their usage of AGA and GAA codons and calculated the D/U ratio in each group . As shown in Fig 3G and 3H , increased usage of AGA and GAA codons additively enhanced the chance of down-regulation in trm9Δ cells on a genomic scale . These correlations held when we examined the data for MMS-treated cells ( S6 Fig ) . Together , these results establish that depletion of mcm5U and mcm5s2U selectively repressed expression of proteins with high usage of AGA and GAA codons . In addition to overall codon usage , certain features such as codon clustering ( i . e . , close spacing of codons along a gene sequence ) may also regulate the rate of translation along a transcript . We thus scanned each mRNA sequence with a sliding window searching for physical clustering of AGA and GAA codons . As shown in Fig 4A and 4B , for genes enriched with AGA and GAA codons , we observed non-random distributions of these codons along the transcripts . We then tested whether such clustering occurred more frequently than expected by chance . To this end , we counted the number of triplet runs ( 3-mer ) of AGA and GAA combinations in each gene . Maintaining codon composition , we shuffled the codons of each gene and counted the number of triplet runs . After performing this shuffling 10 , 000 times for each gene , we found that the actual number of codon runs observed was significantly higher than randomization ( Fig 4C , p = 2 . 5E-187 , Mann-Whitney U test ) . The results remained robust when quadruple or quintuple codon combinations were used ( S7A and S7B Fig ) . In the absence of mcm5U and mcm5s2U modifications , these codon runs may generate a local sequence unfavorable for translation by enhancing the chance of ribosomal pausing . In line with this notion , we showed that genes for down-regulated proteins in trm9Δ cells contained a significantly higher number of AGA and GAA runs than the other proteins ( Fig 4D , p = 7 . 4E-6 , Mann-Whitney U test ) . However , this could be potentially explained if genes for down-regulated proteins contained more AGA and GAA codons , and as a result , a higher number of codon runs . We controlled for this scenario by limiting our analysis to proteins from genes enriched with AGA and GAA codons . We found no significant difference in the usage of these codons between proteins with codon runs ( n = 144 ) and those without codon runs ( n = 154 ) ( mean frequency: with = 11 . 2% versus without = 11 . 0%; p = 0 . 84 , Mann-Whitney U test ) . Controlling for codon usage , we found that down-regulated proteins still had a significantly higher number of codon runs than the other proteins ( Fig 4E , p = 0 . 017 , Mann-Whitney U test ) . These results support the notion that clustering of certain codons imposes an additional layer of regulation on translation efficiency and provide independent evidence for selective inhibition of proteins from genes enriched with AGA and GAA codons in trm9Δ cells . Ribosome footprinting analysis provides an opportunity to quantify the rate of translation of specific mRNA sequences in vivo based on the assumption that the slower a ribosome travels along a specific region of a transcript , the more likely that the ribosomal density in that region will be enhanced . Zinshteyn and Gilbert [24] used ribosome footprinting to assess the effect of mcm5U and mcm5s2U on translation rates in elp3Δ yeast cells lacking these modifications and found ribosome accumulations at AAA , CAA , and GAA codons . However , their results were based on genome-average ribosomal occupancy on each codon type , and cannot be used to predict altered expression of individual proteins . We thus integrated this ribosomal footprinting data with our proteomic data to examine whether there is a link between ribosomal pausing and reduced protein expression in cells lacking mcm5U and mcm5s2U . After controlling for differences in sequencing depth and changes in mRNA expression , we calculated the changes in stringently mapped ribosomal densities that occur within a single transcript between elp3Δ cells and WT cells [24] . As shown in Fig 5A , proteins whose transcripts have enhanced ribosomal density ( pausing ) are preferentially down-regulated compared to those without increase in ribosomal density ( i . e . , no pausing ) ( p = 3 . 56E-05 , K-S test ) . Specifically , as shown in Fig 5B , 75 out of the 292 ( 26% ) transcripts with pausing were found among the significantly down-regulated proteins in trm9Δ cells , while only 156 out of the 930 ( 17% ) proteins without pausing were significantly down-regulated in our proteomics dataset ( p = 6 . 92E-4 , chi-square test ) . We then asked whether ribosomal pausing is associated with enhanced usage of AGA and GAA codons . We note that all genes with ribosome footprinting information were analyzed , regardless of whether they were identified in our proteomic study . As expected , groups of transcripts with pausing tended to contain a higher proportion of genes with high usage of AGA and GAA codons ( Fig 5C , p = 7 . 16E-11 , K-S test ) . Specifically , a significantly higher rate of genes enriched with AGA and GAA codons was observed in genes with pausing ( 226/1251 , 18 . 1% ) than in genes without pausing ( 598/4353 , 13 . 7% ) ( Fig 5D , p = 1 . 39E-4 , chi-square test ) . We further asked whether clustering of AGA and GAA codons could enhance ribosomal pausing . As shown in Fig 5E , the genes prone to pausing were skewed toward those with more runs of AGA and GAA codons ( p = 4 . 87E-13 , K-S test ) and the frequency of AGA and GAA codon runs in stalled genes is significantly higher than those without pausing ( Fig 5F , p = 2 . 62E-16 , Mann-Whitney U test ) . However , this bias toward codon runs could simply result from an association of ribosomal pausing with transcripts possessing high AGA and GAA codon usage . To control for this bias , we limited our analysis to proteins enriched with AGA and GAA codons in both groups . As shown in Fig 5G , genes prone to pausing are still skewed toward higher numbers of codon runs ( p = 6 . 86E-05 , K-S test ) and the number of codon runs is significantly higher in transcripts on stalled ribosomes ( Fig 5H , p = 3 . 17E-6 , Mann-Whitney U test ) . Taken together , these data provide independent evidence that loss of mcm5U and mcm5s2U selectively reduces translation of genes enriched with AGA and GAA codons by causing ribosomal pausing . The fact that loss of Trm9-catalyzed tRNA modifications disrupts expression of proteins from AGA- and GAA-enriched genes led us to explore the Trm9-dependent proteome for a molecular mechanism underlying the associated phenotype of MMS sensitivity . To this end , we analyzed the biological processes associated Trm9-dependent proteins , with comparison of normally growing and MMS-treated trm9Δ cells . Using the David program [36] , we find that most of the defects in protein expression occurring in response to MMS exposure are readily observed under normal growth conditions in trm9Δ cells ( S8 Fig; S4 and S5 Tables ) . Notably , down-regulated proteins with a unique codon usage pattern linked to Trm9 are heavily enriched in translation machinery . For example , 18 out of the 20 components of the 60S ribosomal subunit and all 15 components of the 40S ribosomal subunit are significantly down-regulated under normal and/or stress condition , indicating impaired function of this basic translation machinery ( Fig 6A ) . Paralleling the reduction in ribosomes , we also observed a down-regulation of proteins involved in different steps of translation ( Fig 6B ) , including eIF2 , eIF4A , eIF4g and DED1 involved in translation initiation , 15 out of 17 proteins involved in translational elongation , and SSB1 , YEF3 and RPL10 involved in translation termination . Moreover , six out of seven proteins involved in protein folding were significantly down-regulated ( Fig 6C ) . Notably , 11 of the 12 aminoacyl-tRNA synthetases were likewise significantly down-regulated . These results revealed an unexpected role for Trm9-catalyzed tRNA modifications in regulating translation , which is consistent with our previous observation that loss of Trm9 impaired expression of proteins involved in translation elongation ( YEF3 ) and DNA damage repair ( RNR1 and RNR3 ) , and leaded to translational infidelity , protein errors and activation of protein stress response pathways [19 , 20] . This is held up to explain the observation that some proteins without high usage of AGA and GAA codons were also down-regulated in trm9Δ cells . However , we also suggest that the effect , if any , could not far surpasses that induced by codon usage bias , otherwise we should not observe the selective repression of proteins enriched with AGA and GAA codons . In addition to translation components , we also observed significant down-regulation of proteins involved in DNA damage repair ( MPH1 , RPL40A and DEF1 ) and cell cycle control ( NBP1 , YRB1 , CMD1 and MYO1 ) pathways ( Fig 6D ) . This is consistent with our previous observations that trm9Δ cells display delayed transition into S-phase following DNA damage [19] .
The variety and conservation of modified ribonucleosides in tRNA support the idea that they must play an important role in regulating protein expression [2 , 3 , 8 , 17 , 19] , though the evidence remains largely circumstantial without testing their influence on a global scale in vivo . To this end , we integrated proteome , transcriptome and ribosome footprinting data to elucidate the role of mcm5U and mcm5s2U in regulating global protein expression . After controlling for various confounding factors , such as protein abundance , changes in mRNA levels , and potential influence of other codons , we found robust evidence that expression of proteins enriched with AGA and GAA codons , and to a lesser extent with CAA , are preferentially repressed in cells lacking mcm5U and mcm5s2U under both normal and stress conditions . Consistent with this result , we previously examined expression of several TAP-tagged endogenous proteins , and found that loss of Trm9 only affected expression of proteins overrepresented with AGA and GAA codons [20] . Moreover , we re-engineered a Trm9-depedent gene , ribonucleotide reductase 1 ( RNR1 ) , to replace all Trm9-dependent codons with Trm9-independent synonymous codons . In striking contrast to the wild-type gene , the mutant RNR1 gene was largely resistant to trm9Δ-induced repression of protein expression [19] . A combined consideration of the proteomic results presented here and previous genetic studies [39] reveal a highly important role of wobble uridine modifications in regulating global gene expression . Our data clearly revealed that loss of Trm9 and its wobble modifications causes a significant shift to reduced expression of AGA- and GAA-enriched genes . However , it is important to point out that this regulation is not an “all or none” effect—that is , the loss of Trm9 causes a significant shift in translation but not a complete down-regulation of all AGA- and GAA-enriched genes . The observation that not all AGA- and GAA-enriched genes are affected by loss of Trm9 illustrates the fact that gene expression in general and translation in particular are regulated by a complex interplay of different factors that control the efficiency and fidelity of different steps of protein synthesis . It is also important to point out that we compared groups of proteins enriched or not enriched with a single codon as an unbiased test of the hypothesis that the effects of Trm9 loss should be more pronounced for proteins enriched with Trm9-dependent codons . This proved to be the case , but does not imply that genes enriched with AGA and GAA codons are the only ones affected by loss of Trm9 , or that all genes enriched with AGA and GAA must be affected by Trm9 loss . However , we did not see any evidence that genes enriched with other Trm9-dependent codons , including GGA , GGG , AGG and AAA , were preferentially down-regulated in cells lacking Trm9 . This could be explained by , for example , lower usage of these codons in yeast genes relative to AGA and GAA codons , or that the effect was counterbalanced by poor usage of AGA , GAA and CAA codons , which is supported by the codon usage clustering result in Fig 2A . Nonetheless , the key point is that our results clearly established , as a proof of concept , that Trm9-dependent tRNA modifications play a significant role in regulating protein expression in vivo . An interesting feature of AGA- and GAA-enriched genes is the observation that the codons are more likely to cluster together than expected by chance . Such clustering has been found to affect local translation rate , which has emerged as a mechanism to fine-tune protein expression and minimize protein folding errors , thus providing an additional layer of translational control . For example , biased combinations of codon runs differ in their propensity to cause mistranslation or ribosome pausing [40–42] . Furthermore , large codon clusters could have a greater effect on protein production than an equivalent number of randomly scattered codons , while clustering of rare codons could play an important role in regulating tissue-specific protein expression [40 , 43 , 44] . Here we found that Trm9-dependent proteins from genes enriched with AGA and GAA codons showed a significantly increased frequency of AGA and GAA codon runs . Our results provide evidence that 1 ) proteins with AGA/GAA codon runs , after controlling for codon usage , are more likely to be down-regulated in trm9Δ cells than those without codon runs , and that 2 ) ribosomal pausing in yeast cells lacking mcm5U and mcm5s2U is more likely to occur with transcripts possessing a larger number of AGA/GAA codon runs . These results support the idea that codon clusters add another layer of translational control to protein production . Since our proteomic analyses provide new insights into the functional complexity of wobble uridine modifications in regulating translation , it is important to place our results in the context of published studies that address U34 modifications from other perspectives and reveal a highly complicated system of regulatory control . Here we compare our results for Trm9-dependent modifications with the genetic studies ( tRNA over-expression rescue ) of Bjork and coworkers in ncs6Δ and elp3Δ mutants [39] , as well as with ribosome footprinting studies of Zinshteyn and Gilbert [24] and , more recently , Nedialkova and Leidel [35] in ncs2Δ , ncs6Δ , elp3Δ and elp6Δ mutants . S6 Table summarizes these studies . Most notably , the footprinting data showed that the loss of ncs2Δ , ncs6Δ and elp3Δ caused ribosomal pausing on codons GAA , CAA , AAA and GAG , but not AGA , and the authors speculated that the effect was too small to influence protein production [24] . In addition to discordant conclusions based on the same yeast mutants [24 , 35] and misinterpretation of oxidative stress affects on U34 modifications [35] , we point to several problems with these footprinting studies in terms of the uncertainty of both RNA-seq technology and data analytics , as detailed in a recent review of ribosome profiling technology [45] , problems that obviate stringent comparisons of the ribosome footprinting data sets with the proteomic data . In terms of data analytics , the two studies analyzed the RNA-seq footprinting data in terms of genome-average effects of ribosomal pausing on each codon type and did not specify ribosomal pausing on individual genes at single-codon resolution [24 , 35] . Ribosomal pausing on the same codon can vary dramatically among genes and even along the same transcript , depending upon the structural and physiochemical properties of the local protein sequence . So the approach to data analysis used in the two ribosome footprinting studies precludes drawing conclusions about ribosomal pausing on individual transcripts or changes in expression of individual genes . To address these problems , we reanalyzed the elp3Δ ribosome footprinting data of Zinshteyn and Gilbert [24] in terms of individual genes and found a significant association between enhanced ribosomal pausing and high usage of AGA/GAA codons , as well as the number of AGA/GAA runs along the transcripts . Another feature of the footprinting data , which involves a focus on short mRNA fragments protected by a single ribosome , could explain the apparent absence of AGA codons among the codons associated with ribosome pausing . Close spacing of paused ribosomes has been shown to produce longer protected RNA fragments that are ignored in most ribosomal footprinting methods [45] . Such close spacing could occur by strong pausing at a high density of AGA codons , with a possible contribution from the drag produced when positively charged Arg residues ( coded by AGA ) interact with the negatively charged ribosomal exit tunnel [46] . This could explain why overall ribosomal occupancy on AGA codons actually decreased in elp6Δ cells in the studies of Nedialkova and Leidel [35] . Lastly , all mutants used in the footprinting studies have modification deficiencies that result in the presence of wobble U or s2U on specific tRNAs , while the trm9 mutant used here leaves wobble cm5U or cm5s2U and the nsc6 mutant used in Bjork et al . [39] leaves a wobble mcm5U . These different wobble modification structures further confound the comparison of the results of the various studies and highlight the complexity of U34 modification effects . Our analysis of proteins regulated by mcm5U and mcm5s2U modifications provides several insights into the molecular mechanisms underlying the Trm9-dependent alkylation stress response in budding yeast . First , our proteomic analysis revealed 153 of the proteins found to confer sensitivity to MMS in a phenotypic screening study [22] , with 30 of these down-regulated and 7 up-regulated by loss of Trm9 ( S7 Table ) . These proteins may thus play a role in the MMS stress response phenotype . An analysis of the functional categories of proteins down-regulated in trm9Δ cells provides insights into the molecular mechanisms . One striking feature is that a majority of down-regulated proteins in trm9Δ cells are ribosome related or involved in different steps of translation ( Fig 6 ) . This behavior has strong parallels with Trm4-dependent translation of ribosomal protein paralogs from TTG-enriched genes during the response to oxidative stress [17] . As one of the central control points for gene expression , protein synthesis is regulated at multiple levels for translation efficiency and error reduction [19 , 26] , with ribosomal protein variants allowing control of ribosome structure and function for plasticity in the cell response to environmental changes and stress [47] . So it is not surprising that loss of Trm9 causes in large-scale changes in protein expression as a result of perturbations of the translational machinery , even for proteins not enriched with AGA and GAA codons . The additional changes in expression of elongation factors could alter local translation rates , leading to mis-folding and impaired protein function [41] , which would be compounded by the down-regulation of chaperone proteins observed in trm9Δ cells . Consistent with the idea that cells lacking Trm9 suffer from translational inadequacy , loss of Trm9 was found to perturb polysome profiles of Trm9-dependent transcripts [20] , to cause a mis-folded protein stress due to multiple translational errors including mis-incorporations and frame shifts [19] , and to disrupt translation of AGA , GAA , CAA , GAG codons [19] . The sum of these dysregulations thus induces accumulation of mis-translated and mis-folded proteins that activates protein stress response pathways in trm9Δ cells , which is consistent with the fact that loss of Trm9 recapitulates the stress response associated with exposure to the protein- and nuclei acid-damaging agent , MMS . Another feature of the trm9Δ phenotype involves up-regulation of energy production . Since both protein synthesis and rescue of mis-folded proteins by chaperones are energy-dependent processes ( S8 Fig; S4 and S5 Tables ) [41] , it is likely that energy demands are elevated in trm9Δ cells to maintain translation activities and to activate degradation pathways for errors in protein translation and folding . This model is supported by our proteomics data and Gene Ontology analysis . In comparison with WT cells , we find that proteins involved in glucose metabolism and the tricarboxylic acid cycle are coordinately up-regulated in trm9Δ cells under both normal and MMS stress conditions ( S8 Fig; S4 and S5 Tables ) , possibly to keep up with the increased requirement for energy consumption due to translational errors caused by loss of Trm9 [19] . Oxidative stress response proteins were also activated in trm9Δ cells ( S8 Fig; S4 and S5 Tables ) , suggesting that loss of Trm9 confers a state of oxidative stress with elevated reactive oxygen or nitrogen species that are harmful to the cell . The observed proteomic changes all reflect a phenotype characterized by cell stress , which is consistent with the up-regulation of proteins involved in apoptosis and cell death in trm9Δ cells ( S8 Fig ) . Indeed , loss of Trm9 partially recapitulates the MMS-induced stress response in budding yeast [20] . In the absence of Trm9-catalyzed tRNA modifications , cells experience a dysregulated uncoupling of modified tRNAs from codon-biased translation , which leads to a highly regulated but unfavorable steady-state of altered protein synthesis , energy metabolism and cell death . In this regard , we propose a novel model in which regulation of the spectrum of modified ribonucleoside levels at wobble positions in the system of tRNAs fine-tunes global protein expression by codon-biased translation of mRNAs and reprogramming of translational machinery . Trm9 activity thus illustrates a systems-level mechanism for translational control of cell behavior , with mechanistic parallels in other tRNA modification enzymes .
Urea , sodium chloride , Tris , sodium fluoride , β-glycerophosphate , sodium orthovanadate , sodium pyrophosphate , dithiothreitol , iodoacetamide were purchased from Sigma Chemical Co . ( St . Louis , MO ) . Endoproteinase Lys-C was purchased from Wako ( Richmond , VA ) . All chemicals and reagents were of the highest purity available . All strains of S . cerevisiae BY4741 were purchased from American Type Culture Collections ( Manassas , VA ) . Yeast strain BY4741 was used in this study . WT and trm9Δ yeast cells were grown in yeast nitrogen base ( YNB ) liquid medium containing 30 mg/l normal L-lysine . MMS at a concentration of 0 . 0125% was used to treat log-phase yeast cells ( OD600 0 . 7 ) for 1 h , which caused a lethality of <5% . lys1Δ yeast cells were grown in YNB medium containing U-[13C6 , 15N2]-lysine ( Sigma ) at 30 mg/l for at least 10 generations to log-phase . Cells were harvested by centrifugation for 10 min at 1 , 500 × g at 4°C and washed twice with cold water . Modified ribonucleosides in cytoplasmic tRNA were identified and quantified as reported previously [16 , 17] . Briefly , WT and trm9Δ yeast cells were lysed by lyticase treatment in the presence of deaminase inhibitors ( 5 μg/ml coformycin , 50 μg/ml tetrahydrouridine ) and antioxidants ( 0 . 1 mM desferrioxamine , 0 . 1 mM butylated hydroxytoluene ) . Total RNA were extracted by the Trizol-chloroform method following manufacturer's instructions , and tRNA-containing small RNA species were enriched using the PureLink miRNA Isolation Kit ( Invitrogen ) . The quantity of tRNA was then determined by UV-vis spectrophotometer ( absorbance at 260 nm ) and Bioanalyzer analysis ( Agilent Bioanalyzer Small RNA Kit ) . Using identical quantities of tRNA from WT and trm9Δ cells , each tRNA sample was mixed with [15N]5-2-deoxyadenosine as an internal standard and the tRNA was enzymatically hydrolyzed with nuclease P1 and RNase A , followed by dephosphorylation by alkaline phosphatase [16 , 17] . Proteins and other large molecules were removed by ultrafiltration , and the digested ribonucleosides were then resolved by reversed-phase HPLC ( Agilent 1100 ) with a mobile phase of 1~100% acetonitrile in 8 mM ammonium acetate at a flow rate of 300 μl/min for 1 h . Eluted ribonucleosides were analyzed on an Agilent 6410 Triple Quadrupole mass spectrometer . Modified ribonucleosides were identified by HPLC retention time and collision-induced dissociation ( CID ) fragmentation pattern . The signal intensity for each ribonucleoside was normalized with the signal intensity of [15N]5-dA and abundance of the modified ribonucleosides was compared for WT and trm9Δ cells in the presence and absence of MMS . DNA probes complementary to 5sRNA ( 5'-TGGTAGATATGGCCGCAACC-3' ) , tRNAArg ( UCU ) ( 5'-CACGGCTTAGAAGGCCGTTG-3' ) , tRNAGlu ( UUC ) ( 5'-CTCCGCTACGGGGAGTCGAAC-3' ) , tRNAGln ( UUG ) ( 5'- GGTCGTACTGGGAATCGAACCCAGG-3' ) , tRNALys ( UUU ) ( 5'-CTCCCACTGCGAGATTCGAACTCGC-3' ) and tRNAGly ( UCC ) ( 5'-GTGTAGTGGTTATCATCCCACCCTTC-3' ) were end labeled with T4 polynucleotide kinase ( NEB ) in the presence of [32P]-ATP according to the manufacturer’s instructions . Total RNA ( 10μg ) extracted by the Trizol-chloroform method was separated on a 12% polyacrylamide/8M urea/1×TBE gel followed by semi-dry electroblotting onto Hybond N+ nylon membranes ( GE Healthcare ) . Membranes were cross-linked and pre-hybridized for 1 h in hybridization buffer ( 50% formamide , 0 . 5% SDS , 5×SSPE , 5×Denhardt’s solution , and 20 μg/ml sheared , denatured , salmon sperm DNA ) . Then the membrane was hybridized in the same solution containing 10 pmol radio labeled probes overnight at 42°C . The membrane was washed 3-times with 4×SSC at ambient temperature for 10 min . The membrane was wrapped in plastic wrap ( Saran ) and placed in a cassette with Kodak MS film at -80°C overnight . Light SILAC-labeled WT and trm9Δ yeast cells as well as heavy-labeled lys1Δ yeast cells were disrupted in an alkaline buffer ( 2 M NaOH , 8% v/v 2-mercaptoethanol ) , and proteins were isolated by TCA precipitation . Yeast proteins were pelleted by centrifugation for 15 min at 15 , 000 × g at 4°C , and resuspended in lysis buffer ( 8 M urea , 75 mM NaCl , 50 mM Tris , pH 8 . 2 , 50 mM NaF , 50 mM β-glycerophosphate , 1 mM sodium orthovanadate , 10 mM sodium pyrophosphate , 1 mM PMSF ) . Protein concentration was determined using the Bradford assay . This lys1Δ yeast protein extract was used as global internal standard and mixed ( 1:1 , w/w ) with WT and trm9Δ proteins separately . The protein mixture was reduced for 2 . 5 h at 37°C in 1 mM dithiothreitol ( DTT ) , alkylated for 40 min by 5 . 5 mM iodoacetamide ( IAA ) at ambient temperature in the dark , and then digested with 50:1 ( w/w ) endoproteinase lys-C overnight at 37°C . Peptide mixtures were fractionated into 24 fractions according to their isoelectric point using Agilent 3100 OFFGEL Fractionator ( Agilent ) . Each peptide fraction was acidified by adding 0 . 1% formic acid , and loaded onto a C18 trap column ( 200Å Magic C18 AQ 5μm , 150 μm × 10 mm ) at flow rate of 5 μl/min , with subsequent elution from a coupled analytic column ( 200Å Magic C18 AQ 5 μm , 75 μm × 150 mm ) at 200 nl/min using a 2–98% acetonitrile gradient ( 180 min ) in 0 . 1% formic acid . Eluted peptides were analyzed on a QSTAR-XL ( Applied Biosystems/MDS Sciex ) mass spectrometer . Three technical replicates were performed for each sample . Acquired MS/MS spectra were parsed by Spectrum Mill ( Agilent ) and searched against the Saccharomyces Genome Database ( SGD ) . SILAC peptide and protein quantitation was performed with DEQ ( Differential Expression Quantitation ) . SILAC protein ratios are determined as the average of all peptide ratios assigned to the protein , and the proteins quantified in at least two replicates of the sample are recruited for further study . Differential protein expression was determined by Student’s t-test between different samples . Using protein-coding sequences for 5886 Saccharomyces cerevisiae genes downloaded from the SGD database ( http://www . yeastgenome . org/ ) , we applied custom scripts to determine the gene-specific codon frequency in terms of the number of a particular codon per thousand codons in the open reading frame . Whether a gene was over- or under-represented with a specific codon relative to the genome average was determined by calculating a Z-score based on a hypergeometric distribution with a cut-off of p < 0 . 01 . Gene-specific codon usage data were analyzed by hierarchical clustering using Cluster 3 . 0 , and visualized as a heat map using Treeview [48] . Simulation and ORF shuffling were performed in R project using custom scripts . A spreadsheet containing the gene-specific codon usage data is presented in We investigated gene-specific clusters of AGA and GAA by calculating the frequency of AGA/GAA codons over a sliding window which was then subtracted the mean value of that gene . Similar to previous studies [49 , 50] , a window size of 15 nt was used in this study . The data were plotted as a histogram , with positive peaks indicating clusters of AGA and GAA codons in these regions . The number of short codon runs in the form of triplets of AGA , GAA or their combinations in each gene was counted using custom scripts in R project . Ribosomal footprinting data of the wildtype and elp3Δ cells as well as the RNA-seq data of the corresponding samples were obtained from a previous study ( GSE45366 ) [24] . The reads per kilobase per million mapped reads ( rpkms ) of ribosomal footprinting data ( FP ) and the matched RNA-seq data ( T ) were used for comparison after normalization for library size . FP/T ratio for each gene was calculated to indicate ribosomal density on each transcript . A cut-off of >1 . 2 fold increase in FP/T ratio was used to determine whether ribosomal density on a certain gene was enhanced in cells lacking mcm5U and mcm5s2U .
|
Here we present evidence for a more complicated role for transfer RNAs ( tRNAs ) than as mere adapters that link the genetic code in messenger RNA ( mRNA ) to the amino acid sequence of a protein during translation . tRNAs have long been known to be modified with dozens of different chemical structures other than the 4 canonical ribonucleosides , though the role of these modifications in controlling translation is poorly understood . By quantifying the expression of thousands of proteins in the yeast S . cerevisiae , we identified a mechanistic link between modified ribonucleosides located at the wobble position of two tRNAs , tRNAArg ( UCU ) and tRNAGlu ( UUC ) , and the translation of proteins derived from genes enriched with codons read by these tRNAs: AGA and GAA . In cells lacking the enzyme that inserts these modifications , tRNA methyltransferase 9 ( Trm9 ) , we found a significant reduction in proteins from genes enriched with AGA and GAA codons and with runs of these codons . Also , mRNAs enriched with runs of AGA and GAA codons are subject to stalled translation on ribosomes in yeast lacking mcm5U and mcm5s2U . Together , these results reveal a distinct role for Trm9-catalyzed tRNA modifications in selectively regulating the expression of proteins enriched with AGA and GAA codons .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Trm9-Catalyzed tRNA Modifications Regulate Global Protein Expression by Codon-Biased Translation
|
Respiratory syncytial virus ( RSV ) RNA synthesis occurs in cytoplasmic inclusion bodies ( IBs ) in which all the components of the viral RNA polymerase are concentrated . In this work , we show that RSV P protein recruits the essential RSV transcription factor M2-1 to IBs independently of the phosphorylation state of M2-1 . We also show that M2-1 dephosphorylation is achieved by a complex formed between P and the cellular phosphatase PP1 . We identified the PP1 binding site of P , which is an RVxF-like motif located nearby and upstream of the M2-1 binding region . NMR confirmed both P-M2-1 and P-PP1 interaction regions in P . When the P–PP1 interaction was disrupted , M2-1 remained phosphorylated and viral transcription was impaired , showing that M2-1 dephosphorylation is required , in a cyclic manner , for efficient viral transcription . IBs contain substructures called inclusion bodies associated granules ( IBAGs ) , where M2-1 and neo-synthesized viral mRNAs concentrate . Disruption of the P–PP1 interaction was correlated with M2-1 exclusion from IBAGs , indicating that only dephosphorylated M2-1 is competent for viral mRNA binding and hence for a previously proposed post-transcriptional function .
Human respiratory syncytial virus ( RSV ) is the leading cause of severe respiratory tract infections in infants worldwide and the primary cause of infant hospitalization for respiratory infections [1] . In addition , RSV is increasingly recognized as a significant cause of disease in the elderly population and can often be fatal for patients with a compromised immune system [2] . The virus belongs to the Orthopneumovirus genus of the Pneumoviridae family , order Mononegavirales [3] . The RSV genome is a single strand , negative sense RNA of about 15 kb that is packaged by the nucleoprotein ( N ) and maintained as a left-handed helical N-RNA ribonucleoprotein complex ( RNP ) [4–6] . This RNP is the template for two distinct activities: RNA replication that generates genomic and antigenomic RNA , which is encapsidated by N immediately after synthesis [7 , 8] , and RNA transcription that generates 10 capped and poly-adenylated mRNAs , which are not encapsidated by N . Both activities are carried out by the viral RNA-dependent RNA polymerase complex ( RdRp ) [9] . The viral N , P ( phosphoprotein ) and L ( large polymerase ) proteins are the essential components of the RdRp . RSV P is the main cofactor of the large polymerase L protein . In particular , by interacting with L and the RNP , P is essential to properly position the L protein for RNA synthesis [10] . RSV transcription is dependent on a fourth viral protein , M2-1 [11] . The transcriptase complex first engages promoter sequences that lie at the 3’ end of the genome [12] . Transcription proceeds through sequential stop-and-restart events , in which the RdRp recognizes gene start ( GS ) and gene end ( GE ) sequences , that flank each gene and direct initiation and termination of transcription , respectively [13] . The transcriptase complex has the propensity to dissociate from the RNP template , but cannot reinitiate at a downstream gene after a premature termination . This leads to a decreasing gradient of mRNA from the 3’ to the 5’ end of the genome [14] . In contrast , the highly processive replicase bypasses GS and GE signals to produce complete genomic and antigenomic RNAs [15] . The exact mechanism of how RdRp differentiates between transcription and replication still remains unknown . By increasing the processivity of the RdRp complex , RSV transcription antiterminator protein M2-1 prevents premature transcription termination [16 , 17] . For this activity , M2-1 has to be recruited to cytoplasmic inclusion bodies ( IBs ) , which contain other components of the RdRp complex , notably N , P and L , and [18–20] , [21] , [22] . Moreover we recently showed that IBs are a place of viral RNA synthesis and that M2-1 and viral mRNAs concentrate in IB substructures called IB associated granules ( IBAGs ) , from which N , P , L and genomic RNA are absent [20] . M2-1 is a 22 kDa basic protein that forms stable tetramers in solution [23 , 24] . Each protomer features an N-terminal zinc finger domain , an α-helical tetramerization motif , and a C-terminal α-helical core domain [24] . M2-1 is an RNA binding protein [25] that binds preferentially to RSV mRNAs and A-rich sequences [26] . RSV M2-1 can also interact with RSV P . We showed previously that substitution of M2-1 residues involved in the M2-1–P interaction prevented the recruitment of M2-1 to IBs , suggesting that formation of a P–M2-1 complex is critical for M2-1 recruitment to IBs [19] . Since M2-1 interacts with RNA and P in a competitive manner through the core domain [19 , 23] , it is expected that these interactions are regulated in a cyclic manner . In RSV-infected cells M2-1 exists in different phosphorylation states , resulting in its migration as two major bands in SDS-PAGE [27–29] . The slower-migrating species contains phosphorylated M2-1 , whereas the faster-migrating species lacks significant phosphorylation [27] . In RSV infected cells or when co-expressed with P , M2-1 protein remains mainly unphosphorylated , whereas M2-1 is mainly phosphorylated when expressed alone [25] . Using recombinant ( unphosphorylated ) M2-1 produced in E . coli , it has also been shown that M2-1 can be phosphorylated in vitro by casein kinase I on serines S58 and S61 [26] . Abolishing phosphorylation of these residues by alanine substitution impaired the antitermination function of M2-1 [26] . However , the P–M2-1 interaction appears to be independent of the phosphorylation status of M2-1 [23] . On the other hand , phosphorylated M2-1 has reduced RNA binding capacities [25] . All these data point to the critical role of dynamic and reversible M2-1 phosphorylation for its function in transcription . Neither P nor M2-1 produced in E . coli are phosphorylated [23 , 30 , 31] . These two unphosphorylated proteins interact together and have been used previously to study the P–M2-1 interactions in vitro [23 , 32] . In P , the region encompassing residues 100–120 and more specifically residues L101 , Y102 , and F109 were reported to be critical for the M2-1–P interaction and for efficient transcription [33] . It was also shown that P residue T105 is probably involved in M2-1 binding [34] . P can be phosphorylated on several serine and threonine residues with different turnover rates [34–39] . In particular phosphorylation of T108 , which occurs with a high-turnover , would prevent M2-1 binding . However , the role of P phosphorylation remains unclear , since phosphorylation is not required for viral transcription or replication [38 , 40 , 41] . Here we further investigated structural and functional aspects of the M2-1–P interaction . We show that a region encompassing residues 93–110 of P is required for the presence of M2-1 in IBs . We further identified another element , located upstream of this region which is responsible for M2-1 dephosphorylation . We show that this region is involved in the binding of the cellular protein phosphatase-1 ( PP1 ) to P , but not in M2-1 binding , and that the complex formed by P and PP1 is responsible for M2-1 dephosphorylation , a key process for efficient viral transcription .
We previously mapped the interaction surface of RSV P on the core domain of M2-1 ( M2-1core , residues 58–177 ) by NMR [19] , by observing spectral perturbations , at a residue-specific level , induced by unlabeled P on 15N-labeled M2-1core . RSV P forms highly stable tetramers [31 , 42 , 43] , with large N- and C-terminal intrinsically disordered regions ( IDRs ) flanking the oligomerization domain ( residues 126–163 ) [31 , 32] . We recently analyzed the propensities of these IDRs to form transient secondary structures and to transiently associate , either with each another or with the N protein , also by NMR [44] . Here we proceeded to determine the M2-1 binding region in P . Both P and M2-1 , produced in E . coli , were unphosphorylated . We compared 1H-15N spectra of 15N-labeled P in the absence and presence of unlabeled M2-1core . The presence of M2-1core induced a significant decrease of NMR signal intensities , or line broadening , in a region spanning residues 90–120 in the N-terminal IDR of P , upstream of the oligomerization domain ( Fig 1A ) . This finding is in agreement with the previous localization of residues critical for M2-1 binding [33 , 34] . The binding region includes an extremely transient α-helix detected in free P ( αN2 in Fig 1A ) [44] . It is expected that in the M2-1–P complex , the αN2 region adopts the molecular tumbling properties of the globular M2-1core , which results in increased transverse relaxation and hence line broadening . But this cannot explain that the signal is fully broadened out . A Kd of 3 μM was previously determined for the M2-1–P complex by isothermal titration calorimetry ( ITC ) [19] . It is compatible with exchange on a μs-ms timescale between free and M2-1core-bound P , which contributes to line broadening . Additional broadening probably arises from conformational exchange taking place between partially folded states of the αN2 helix , which may all contribute to M2-1core binding . We also carried out NMR interaction experiments between M2-1core and two 15N-labeled P fragments , P[1–126] and P[1–163] , which were designed for previous characterization and interaction experiments with N by NMR [44] . They both comprise the 90–120 region . P[1–126] is a monomeric fragment that represents the N-terminal IDR of P . P[1–163] additionally contains the oligomerization domain of P and displays a similar behavior to full-length P , with nearly complete line broadening in the αN2 region ( Fig 1B ) . Surprisingly , in P[1–126] a second region is perturbed at the N-terminus of P ( residues 23–37 ) at a lesser extent . This region overlaps with the N0-binding site of P , which contains another transient α-helix ( αN1 ) [44 , 45] . Notably , in N0-P interaction experiments using RNA-free N , we had observed the symmetrical scenario: N not only induced line broadening in the N0-binding region , but also to a lesser extent in the M2-1-binding region [44] . We cannot rule out that a direct interaction takes place in both cases at a second binding site . However , since we evidenced transient contacts between these two regions in free P [44] , the perturbations observed at the second site may indirectly arise from breaking of internal contacts to expose the primary binding site [44] . Finally , from the interaction experiment with P[1–126] , it appears that the primary interaction region is probably restricted to residues 90–112 , since residues 113–120 are no longer completely broadened out ( Fig 1C ) . The presence of the oligomerization domain in full-length P and P[1–163] can affect nuclear relaxation in this region by restricting motions due to steric hindrance or by promoting an extension of either αN2 or the coiled-coil helices of the oligomerization domain . To validate our NMR results , we performed GST pulldown assays . Full-length and truncated forms of RSV P were produced as GST-fusion proteins ( Fig 2A ) and incubated with recombinant His-tagged M2-1 protein . All proteins were expressed in E . coli . After extensive wash , the complexes were analyzed by SDS-PAGE and Coomassie blue staining . As shown in Fig 2B , M2-1 and P constructs were purified to > 90% homogeneity , except for GST-P[1-126] and GST-P[1-90] , for which faster migrating bands were observed in a reproducible manner . Mass spectrometry analysis revealed that these bands correspond to degradation of these P fragments . The results clearly show that M2-1 binding was retained for GST-P , GST-P[1-126] , GST-P[90-126] and GST-P[93-110] . However , no M2-1 binding was seen for GST-P[161-241] , GST-P[127-160] or GST-P[1-90] . These results , which are in agreement with previous data by Mason et al . [33] , demonstrate that P region P93-D110 is sufficient for binding M2-1 in vitro . In order to identify the P residues critical for P–M2-1 interaction , we used a functional assay based on a firefly luciferase ( Luc ) reporter RSV minigenome . In this system transcription of the second gene coding for Luc is absolutely dependent on the P–M2-1 interaction [19 , 23] . Site-directed mutagenesis was performed on residues V85 to E115 , encompassing the P93-D110 region . Ala substitution of seven mainly hydrophobic residues , F87 , F98 , L101 , Y102 , T105 , I106 and F109 , had a drastic effect on RSV transcription ( Fig 3A ) . Western blot shows that the drop in transcription efficiency was not due to a defect in expression of the P variants ( Fig 3B ) . Among these , L101 , Y102 , T105 and F109 had been shown previously to be involved in the P–M2-1 interaction [33 , 34] . The phosphomimetic T108D variant impaired transcription , in contrast to T108A . This is in line with the results of Asenjo et al . who had suggested that phosphorylation of T108 could negatively regulate the P–M2-1 interaction [34] . Our results are thus in agreement with previous data , but highlight the critical role of newly identified residues F87 , F98 and I106 . Mutations of P impairing transcription are located in the P93-D110 region , except for F87 . The ( i , i+3; i , i+4 ) periodicity of the critical residues F98-F109 of P identified here suggests that M2-1 binding stabilizes the transient α-helix formed in free P [44] . Helical representation of this domain reveals that critical residues F98 , L101 , Y102 , T105 , I106 and F109 are located on the same side of the putative helix and form a contiguous surface ( Fig 3C ) . When co-expressed in the absence of other viral proteins , RSV P and N proteins induce the formation of cytoplasmic IBs similar to those observed during RSV infection , where N and P co-localize [18] . When co-expressed with P and N , M2-1 also localizes preferentially in these IBs , which has been linked to its interaction with P [19] . We thus analyzed the impact of the P mutations identified as critical for RdRp activity on the intracellular localization of M2-1 by fluorescence microscopy . Cells were cotransfected with expression vectors encoding P ( WT and variants ) , N and M2-1-mCherry . All tested P variants were able to induce the formation of IBs ( Fig 4 ) . The M2-1-mCherry fusion protein accumulated in IBs in the presence of wild type ( WT ) P . M2-1 was also present in the IBs in the presence of P variant T108A , which did not impact transcription in the minigenome assay . In contrast , M2-1 was absent from the IBs for P variants that were defective for RdRp activity , F98A , L101A , Y102A , T105A , T105D , I106A , T108D and F109A , with the notable exception of F87A . It must be specified that mCherry fusion at the C-terminus of M2-1 does not affect the polymerase activity in the context of the minigenome , since ~ 70% of activity was recovered , as compared to WT M2-1 ( S1 Fig ) . These results show that there is a good correlation between the presence of M2-1 in IBs and RdRp activity , except for F87A . They also point to the potential role of T108 phosphorylation for the presence of M2-1 in IBs . To determine whether point mutations affecting RSV transcription and M2-1 localization directly impact the P–M2-1 interaction , we performed GST pulldown assays using recombinant , non-phosphorylated GST-P and M2-1 proteins produced in E . coli . Fig 5A shows that substitutions F98A , L101A , Y102A , T105A , T105D , T108D and F109A were sufficient to impair P–M2-1 interaction in vitro , while M2-1 still interacted with the T108A and F87A variants . We hypothesized that the M2-1 binding region in P , which displays helical propensity in solution folds into a stable helix upon M2-1—P complex formation , and we docked a structural model of the P helix ( Fig 5B , green ) onto the structure of M2-1core under constraints obtained by mutagenesis and NMR interaction data . We have shown previously that the P binding site on M2-1 forms a groove between helices α4 and α6 and that the interaction surface on M2-1 is composed of hydrophobic residues ( V127 , L152 , V156 ) , neutral ( N129 , T130 , S133 ) and basic residues ( R126 , R151 ) [19] . M2-1 R126D and L148A variants completely impaired P binding as well as its recruitment to cytoplasmic IBs . Critical P residues determined in the present study are rather hydrophic or neutral . However a 50% decrease in minigenome activity was observed for P variants D95A and D110A . These two acidic residues are at the edge of the P region involved in the interaction with M2-1 and could thus also play a role in this interaction ( see Fig 5B ) . Altogether our observations strongly suggest that the binding surfaces of P and M2-1 involve both hydrophobic and electrostatic interactions . To clarify the differences observed between F87A and the mutations affecting the P–M2-1 interaction , we performed immunoprecipitation after co-transfecting BSRT7 cells with plasmids encoding N , M2-1 and HA-P ( WT and variants impairing in vitro transcription ) and by precipitating with an anti-HA monoclonal antibody . The precipitated complexes were analyzed by Western blot using anti-P and anti-M2-1 polyclonal sera . As expected [29] [28] , two main bands , corresponding to phosphorylated ( upper band ) and unphosphorylated ( lower band ) M2-1 , were observed in cell extracts ( Fig 5C ) . However , whereas M2-1 in the complex with WT P was mainly unphosphorylated , M2-1 was almost exclusively phosphorylated in the presence of all the P variants tested . Even more surprisingly , whereas only the unphosphorylated form of M2-1 co-precipitated with WT P , the F87A mutant was able to precipitate phosphorylated M2-1 as well . M2-1 remained phosphorylated with F98A , L101A and T105A P variants , which do not bind any form of M2-1 , suggesting that the M2-1–P interaction is involved in M2-1 dephosphorylation . Taken together , these observations indicate that both unphosphorylated and phosphorylated forms of M2-1 can interact with P , and that the interaction between P and M2-1 favors M2-1 dephosphorylation . They also reveal that the F87A mutation impairs M2-1 dephosphorylation without impeding P–M2-1 binding . Since RSV P is required for M2-1 dephosphorylation , we hypothesized that P could associate with a cellular phosphatase , that in turn would be responsible for M2-1 dephosphorylation . For Ebola virus , which belongs to the Filoviridae family in the Mononegavirales order , it was recently shown that VP30 , which shares functional and structural similarities with RSV M2-1 , is dephosphorylated by PP1 [46] , and that VP30 dephosphorylation is critical for viral transcription . PP1 does not recognize specific sequences on its target protein . Instead , substrate binding depends on its association with PP1-interacting proteins ( PIPs ) that function as targeting subunits [47] . A majority of known PIPs contain a short PP1-binding motif "RVxF" ( R/K-K/R-x ( 0 , 1 ) -V/I-x-F/W/Y ) . RSV P contains a 81RKPLVSF87 sequence , which conforms to the "RVxF" motif . Sequence alignment of Pneumoviridae P shows high conservation of a "R/x-K-x-x-V-T/S-F" motif , which reduces to "R-K-P-x-V-T/S-F" for pneumoviruses ( Fig 6A ) . RSV P thus harbors a degenerate "RVxF" motif containing the residue F87 and is most likely a PIP . To determine whether P could associate with endogenous PP1 , cells were co-transfected with pHA-P and p-N , and P was immunoprecipitated from cell lysates using an anti-HA antibody . The presence of cellular phosphatases was then analyzed by Western blot . The presence of PP1 was clearly revealed in the precipitated products using WT P ( Fig 6B ) . With the P F87A variant , PP1 was no longer precipitated ( Fig 6B ) , emphasizing the role of this residue . Of note , for unclear reasons , the F87A P variant was overexpressed as compared to WT P . We then investigated whether RSV P could directly interact with PP1 by using NMR interaction experiments . We observed the perturbations in 1H-15N correlation spectra ( BEST-TROSY ) of 15N-labeled P[1–126] in the presence of unlabeled GST-PP1α . GST-PP1α induced line broadening of NMR signals , i . e . a decrease of intensity , notably in a region spanning residues K76-D90 ( Fig 6C and S2 Fig ) . Control experiments in the presence of GST alone did not reveal any intensity perturbation ( S2 Fig ) . The 76–90 region contains the degenerate "RVxF" motif identified above . It is adjacent to the M2-1 binding site , but was not perturbed by M2-1core in P[1–126] ( Fig 1C ) . The 76–90 region had already drawn our attention owing to more efficient 15N transverse relaxation than in adjacent IDRs and to its β-strand propensity in free P [44] . Since PPI RVxF" motifs adopt an extended β-strand conformation in complex with PP1 , it was tempting to hypothesize that 76–90 region forms a primary PP1 binding site [48] . Similarly to M2-1core , GST-PP1α also perturbed the N0-binding region in P[1–126] . In contrast to M2-1core , when we performed interaction experiments with full-length P ( Fig 6C and S2 Fig ) , perturbations in the vicinity of αN1 were still observed , so that we cannot rule out that they reflect direct binding to a second binding site [48] . The presence of GSH in the buffer did not affect intensities . The ability of PP1 to interact specifically with P was thus investigated by GST pulldown using GST-PP1α and recombinant P , WT or F87A mutant , all produced in E . coli . As shown in Fig 6D , only WT P was efficiently pulled down by GST-PP1 . In summary , these results demonstrate that the P–PP1 interaction is direct and that residue F87 of P plays a pivotal role in this interaction . The presence of PP1 in IBs was analyzed by confocal microscopy . BSRT7/5 cells were co-transfected with plasmids expressing PP1-GFP , L , P-BFP , N , M2-1–mCherry proteins together with the pM/Luc vector expressing a firefly luciferase-reporter RSV minigenome , then fixed 24 hours post-transfection . Of note , BFP insertion between residues 73–74 of P , in a naturally disordered and poorly conserved region among Pneumoviridae [44] , only moderately affected the polymerase activity in the context of the minigenome , since ~ 80% of activity was recovered , as compared to WT P ( S1 Fig ) . As shown in Fig 7 , PP1 fluorescence clearly overlapped with the WT P fluorescence , indicating that PP1 was significantly targeted to the IBs . In contrast , PP1 was no longer detected in IBs when expressed in the presence of the F87A P variant . These results revealed that RSV P recruits PP1 to IBs and that F87 plays a critical role in this process . By studying the ultrastructure of IBs , we recently found that M2-1 colocalizes with viral neo-synthesized mRNA in IBAGs , revealed by a poly ( dT ) probe , and from which genomic viral RNA , N , P and L proteins are excluded [20] . We thus wondered if the absence of a P-PP1 complex could affect the localization of M2-1 in IBs . As the formation of IBAGs requires viral mRNA synthesis , we first verified that viral transcription can occur in the absence of M2-1 activity in our system . For that purpose , we engineered a new minigenome in which the first gene was replaced by the Gaussia luciferase coding sequence , upstream from the firefly luciferase gene . As shown in S3 Fig , whereas no Firefly luciferase activity was detected in the absence of M2-1 , the Gaussia luciferase activity was still detectable although reduced to ~15% . This confirmed that M2-1 is not absolutely required for expression of the first gene but increases expression of this gene . Based on this result , transfected cells were prepared for FISH using poly ( dT ) probes and analyzed by confocal microscopy . Fig 7 shows that , in contrast to what was observed with WT P , in the presence of the F87A P mutant M2-1 was present throughout the IBs , where it colocalized with P , but absent from IBAGs as revealed by a poly ( dT ) probe . These results indicate that phosphorylated M2-1 , which is still competent for P-binding , cannot associate with neo-synthesized viral poly-adenylated mRNAs . In a previous report we observed that IBAGs are not detected when using an oligo ( dT ) probe in the absence of M2-1 [20] . These results suggested that either M2-1 is needed for the formation of IBAGs , or that M2-1 binds to mRNAs and is carried to the IBAGs as a passenger , not as a required chaperone . To clarify this point , we used two different probes , an oligo ( dT ) and probes targeting the first transcription unit of the M/Luc minigenome ( the NS1-M chimeric mRNA ) , and compared the presence of IBAGs in the absence or presence of either P WT or P F87A . Some pictures representing the trend of what we observed are shown in Fig 8; in the absence of M2-1 , some IBAGs were detected when using NS1/M probes but not with an oligo ( dT ) probe . Similar results were observed with either WT or F87A P . Thus these results indicate that ( i ) transcription of the first gene can occur either in the absence of M2-1 or in presence of phosphorylated M2-1 , as revealed by NS1 probes; ( ii ) poly-adenylation is affected in the absence of M2-1 but not in the presence of phosphorylated M2-1; and ( iii ) IBAGs revealed by either NS1 or oligo ( dT ) probes can form in the absence of M2-1 or in the presence of phosphorylated M2-1 which is excluded from them . In conclusion these results suggest that M2-1 is not essential for the formation of RNA aggregates calles IBAGs , and could be involved in mRNA poly-adenylation . They also suggest that a defect in M2-1 dephosphorylation does not affect mRNA poly-adenylation but binding of M2-1 to poly ( A ) RNAs after their synthesis . A previous report suggested a requirement for cyclic phosphorylation/dephosphorylation of M2-1 for efficient antitermination function [24] . To further demonstrate that PP1 is involved in M2-1 dephosphorylation in cellula , PP1 was overexpressed in BSRT7/5 cells in the context of the RSV minigenome . Fig 9A shows that RSV RdRp activity , as revealed by Luc activity , significantly decreased in a dose-dependent manner with pEGFP-PP1 plasmid addition , while P and N expression levels were not affected ( Fig 9B ) . However , although the expression level of unphosphorylated M2-1 was not or poorly affected ( Fig 9B ) , overexpression of PP1 significantly induced a decrease in phosphorylated M2-1 , and thus a decrease of the ratio of phosphorylated versus unphosphorylated M2-1 ( Fig 9B and 9C ) , confirming that PP1 is involved in M2-1 dephosphorylation in living cells .
The efficient activity of the RSV RdRp complex depends on regulated and highly specific protein-protein interactions , which are potential targets for antiviral therapy [49] . P plays a pivotal role through multiple interactions with L , N and M2-1 , mediated by its high structural plasticity linked to its disordered regions [44 , 50] . The M2-1 binding region has been mapped previously to P residues 100–120 , using proteins from two RSV strains ( A2 and Long ) , and the role of specific residues L101 , Y102 , F109 , T105 and T108 was highlighted [33] , [34] . By combining NMR , biochemical and functional approaches based on an RSV minigenome and microscopy , we precisely mapped the M2-1 binding region of P to a stretch encompassing residues 93–110 . We identified 7 residues of P that are directly involved in this interaction , summarized in Fig 10A . These include two newly identified residues F98 and I106 and validate the major role of hydrophobic P residues in the P–M2-1 interaction [33] . Furthermore , we found a perfect correlation between the capacity of P to interact with M2-1 , RdRp activity and the presence of M2-1 in IBs . These results indicate that M2-1 cannot reach IBs without P , P acting as a recruiter for M2-1 , and are in agreement with previous observations obtained with M2-1 variants unable to interact with P [19] . M2-1 is mainly unphosphorylated in the context of an RSV infection , whereas the phosphorylated state is predominant when M2-1 is expressed alone in cells , S58 and S61 being the main sites of phosphorylation [26] . Previous experiments showed that phosphoablatant substitutions S58A/S61A as well as phosphomimetic substitutions S58D/S61D reduced RSV transcription activity to less than 20% and to ∼40% as compared to WT M2-1 , respectively [24 , 26] . These data suggest that a cyclic turnover of phosphorylation-dephosphorylation of M2-1 is required for efficient RSV transcription . Here we observed that unphosphorylated M2-1 was predominant in cell lysates when co-expressed with WT P . A reverse situation was observed when M2-1 was co-expressed with P variants F98A , L101A , T105A that do not interact with M2-1 , M2-1 being mainly phosphorylated , suggesting that P binding induces M2-1 dephosphorylation ( Fig 5C ) . The finding that M2-1 is predominantly phosphorylated in the presence of another P variant F87A , which efficiently pulled down M2-1 , confirmed that P is capable of interacting with both phosphorylated and unphosphorylated forms of M2-1 [23] . Altogether these results indicated that ( i ) P mediates M2-1 dephosphorylation or prevents M2-1 phosphorylation and that ( ii ) a P region adjacent to the M2-1 binding region comes into play for this activity . Previous studies suggested that RSV P could be a target of cellular phosphatases PP1 and PP2A in cultured cells [38 , 51] . PP1 is a well-characterized and conserved Ser/Thr phosphatase holoenzyme . It is composed of a variable regulatory subunit that determines the localization , activity , and substrate specificity of the phosphatase and of one of three highly homologous catalytic phosphatase subunits PP1α , PP1γ , or PP1β/δ ( reviewed in [47 , 48] ) . PP1 is the most widely expressed and abundant Ser/Thr phosphatase and is estimated to catalyze about one third of all protein dephosphorylations in eukaryotic cells . It dephosphorylates hundreds of key biological targets by associating with nearly 200 regulatory proteins to form highly specific holoenzymes . Of note , many of the > 200 established PIPs are predicted to be intrinsically disordered like RSV P . The defect in M2-1 dephosphorylation observed for the P F87A variant mainly argued in favor of the hypothesis of the recruitment by P of the PP1 cellular phosphatase through a RVxF-like motif , upstream of the M2-1 binding site . This hypothesis was consolidated by several complementary approaches showing that ( i ) WT P , but not the F87A variant , could bind PP1 in vitro and in cellula; ( ii ) PP1 colocalized with WT P , but not with the F87A variant , in IBs; and ( iii ) overexpression of PP1 increased the unphosphorylated/phosphorylated M2-1 ratio . Altogether , our data show that RSV P can be considered as a PP1-interacting protein ( PIP ) , targeting PP1 to the M2-1 substrate . The degenerate "RVxF" motif in RSV P , 81RKPLVSF87 , is well conserved among Pneumoviridae , with a consensus KxxVxF ( Fig 6A ) . The lysine residue is surrounded by basic residues , with an arginine just upstream for orthopneumoviruses , and two lysines downstream for metapneumoviruses . Thus , it is likely that the P proteins of Pneumoviridae share the property of interacting with PP1 to regulate viral protein phosphorylation . Notably , M2-1 protein is unique to Pneumoviridae and present in all members of this virus family . It was shown that residues S57 and S60 of hMPV M2-1 protein , which are equivalent to RSV M2-1 S58 and S61 , are also critical for virus replication , consistent with the critical role of cyclic phosphorylation/dephosphorylation of hMPV M2-1 for efficient RNA synthesis [52] . It is thus expected that hMPV and RSV present the same mechanism of regulation of M2-1 dephosphorylation . It is noteworthy that PP1 was previously shown to play a significant role in the replication of several viruses , including papovavirus , adenovirus , human immunodeficiency virus 1 ( HIV-1 ) and 2 , Ebola virus ( EBOV ) , and Rift Valley Fever virus [46 , 53 , 54] . Within Mononegavirales , the VP30 protein from filoviruses is the only protein that shares structural and functional similarity with the M2-1 protein from Pneumoviridae . It was shown that the phosphorylation status of VP30 was also regulated by PP1 [46] . It has also been demonstrated that PP1 regulates the innate immune responses for numerous RNA viruses , such as influenza virus , Sendai virus , dengue virus , and picornavirus [55] . The V protein of measles virus was shown to interact directly with PP1α/γ , via a canonical PP1-binding motif , 288RIWY291 , preventing PP1-mediated dephosphorylation of MDA5 , a cytosolic sensor crucial for innate immune defense against various RNA viruses , thereby impairing its activation [56] . Previous reports indicated that the phosphorylation state of M2-1 regulates the affinities with its partners [25] . The highest affinities of RSV M2-1 ( produced as recombinant protein in E . coli , i . e . unphosphorylated ) for RNA were found with poly ( A ) ( Kd~20 nM ) and sequences present on viral mRNAs that are complementary to GE signals ( Kd ~ 46 nM ) [19 , 24] . We previously determined that the phosphomimetic S58D/S61D substitution decreased the RNA binding affinity as compared to WT M2-1 [24] . This is consistent with the crystal structure of full-length tetrameric RSV M2-1 [24] , where S58 and S61 are located on a flexible loop , facing the RNA binding region located in M2-1core . Addition of a negative charge on these residues by phosphorylation could thus affect the interaction with RNA . Recombinant tetrameric P and M2-1 proteins ( produced in E . coli , i . e . unphosphorylated ) form a complex with a 1:1 stoichiometry and a Kd of ~ 8 . 1 nM [32] . The affinities of P and RNA for M2-1 are therefore comparable , which would be in line with a switch of M2-1 between the two M2-1–RNA and M2-1–P complexes . This assumption was confirmed by comparing the organization of IBs in the presence of WT or F87A P variant in our minigenome assay . We previously observed a distinct compartment in IBs that contains concentrated viral mRNAs and M2-1 ( IBAG ) . The rest of the IBs holds all the other proteins of the RSV polymerase complex together with the genomic RNA [20] . When the P F87A variant was used , PP1 was absent from IBs , and M2-1 , which was found mainly in a phosphorylated form ( see Fig 5C ) , was no longer associated with IBAGs . The M/Luc minigenome we used for fluorescence microscopy studies has two transcription units ( see materials and Methods ) ; the first one can be transcribed in the absence of M2-1 , although with a 5 to 7 fold reduction ( see S3 Fig ) , while the second one coding for Firefly luciferase fully depends on a functional M2-1 [17 , 23 , 57] . It is thus likely that the poly ( A ) RNA seen in IBs when P F87A was used represents transcription from the first gene . These results also indicate that IBAGs form in the absence of dephosphorylated , competent for mRNA binding , M2-1 . Finally , by using two different RNA probes , i . e . NS1 and poly ( dT ) , we observed different effects on viral RNA poly-adenylation when M2-1 was either absent or co-expressed with P F87A and thus in the absence of PP1; in the first case some residual transcription was detected with the NS1 probe but not with the poly ( dT ) probe; in the second case ( phosphorylated M2-1 only ) , both probes could detect some IBAGs . Together these results suggest that ( i ) poly-adenylation of the first transcription unit is impaired in the absence of M2-1 and ( ii ) phosphorylated M2-1 can help poly-adenylation , although it is excluded from IBAGs after transcription . To summarize , RSV P can be considered as a newly identified PIP , targeting PP1 to the M2-1 substrate . To our knowledge , this is the first report showing such a mechanism of regulation of Pneumoviridae transcription . Recently , we have shown that , in RSV-infected cells , viral RNA synthesis occur in IBs , M2-1 and viral mRNAs concentrating in IB sub-compartments called IBAGs [20] . The data indicated that IBAGs are dynamic structures , allowing the sorting of viral mRNAs and their transport to the cytoplasm together with M2-1 . Accordingly , we propose the following model ( Fig 10B ) : in the cytoplasm of infected cells the P protein binds PP1 and the phosphorylated form of M2-1 allowing their recruitment into IBs . M2-1 works as an anti-terminator of transcription in IBs and could intervene as a poly-adenylation factor . Once dephosphorylated by PP1 , M2-1 has a higher affinity for RNA , in particular for GE and poly ( A ) sequences at the end of the transcripts . Terminated mRNAs concentrate in IBAGs and drag M2-1 along . M2-1 could act in a manner similar to the cellular poly ( A ) binding protein , protecting mRNA from degradation and perhaps playing a role in the transport of mRNAs from IBAGs to the cytosol in order to translate viral mRNAs , and possibly playing an active role in translation . M2-1 phosphorylation could then occur in the cytosol , resulting in the detachment of M2-1 from the poly ( A ) tail of mRNA , before being recycled by P and redirected to IBs for a new round of transcription .
All viral sequences were derived from the human RSV strain Long . The full length or segments of the P gene were PCR amplified by using Pfu DNA polymerase ( Stratagene , Les Ulis , France ) and cloned into pGEX-4T-3 bacterial expression vector ( GE Healthcare ) at BamHI-SmaI sites to engineer the pGEX-P and derived plasmids . The M2-1 cDNA [23] was subcloned into pET-22b+ ( Novagen ) to allow bacterial expression of full-length M2-1 with a C-terminal poly-histidine tag . Plasmids for eukaryotic expression of the human RSV ( Long strain ) proteins N , P , M2-1 , and L , designated pN , pP , pM2-1 , and pL , respectively , and pM/Luc have been described previously [22 , 23] . The pM/Luc minigenome has two transcription units; the first ORF is a chimera between NS1 ( 327 first nucleotides ) and M genes ( 138 last nucleotides ) , and transcription termination depends on a N Gene End sequence . The second ORF codes for firefly luciferase and ends with a SH Gene End sequence The first and second mRNA expressed by this minigenome are 698 and 1897 nucleotides in length , excluding the poly ( A ) tail , respectively . A second minigenome containing Gaussia and Firefly luciferases was engineered and synthesized by Genscript . This pGaussia/Firefly minigenome is similar to the pM/Luc minigenome excepted that it contains the Gaussia luciferase gene upstream in place of the NS1-M chimeric gene ( complete sequences available on demand ) . Point mutations were introduced in the P sequence by site-directed mutagenesis using the QuikChange site-directed mutagenesis kit ( Stratagene ) . To generate the plasmid pHA-P , complementary oligonucleotides encoding a hemagglutinin ( HA ) tag epitope ( MYPYDVPDYA ) were annealed and inserted at the BamHI restriction site in frame at the 5’ end of the P gene in pP . For the eukaryotic expression of a M2-1–mCherry fusion protein , the mCherry gene was amplified by PCR from the pmCherry vector ( Clontech ) and cloned in frame at the 3’ end of the M2-1 gene at BglII-XhoI sites in pM2-1 . To engineer the pP-BFP vector , first a NheI site was introduced at nucleotides 741–746 of the P sequence; then , the BFP gene was PCR amplified from the pTagBFP-Tubulin vector ( Evrogen ) and inserted at the NheI restriction site , between P residues 73–74 . The eukaryotic expression vector pEGFP ( C1 ) -PP1α was purchased from Addgene . The PP1A insert ( residues 7–300 ) was subcloned into pGEX-4T-3 at BamHI-XhoI sites . Sequence analysis was carried out to check the integrity of all the constructs . All the oligonucleotide sequences are available on request . For M2-1 expression , E . coli BL21 ( DE3 ) ( Novagen ) bacteria were transformed with pET-M2-1 plasmid , and bacteria were grown at 37°C for 8 h in Luria-Bertani medium ( LB ) containing 100 μg/ml ampicillin . Protein expression was induced by adding one volume of fresh LB medium , 400 μM isopropyl β-D-1-thiogalactopyranoside ( IPTG ) and 50 μM ZnSO4 for 16 h at 28°C . Cultures were centrifuged at 5 , 000 g for 15 min and the pellet was resuspended in lysis buffer ( 20 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 50 mM imidazole , 0 . 1% Triton X-100 and 1 mg/ml lysozyme ) . Benzonase ( Novagen ) was then added to the lysates ( final concentration 5U/mL ) , which were further incubated for 1h at room temperature under rotation . NaCl was then added to reach a final concentration of 1M and lysates were clarified by centrifugation at 10 , 000 g for 1h at 4°C . The supernatant was loaded onto a 5-mL HiTrap IMAC column ( GE Healthcare ) charged with 0 . 2 M ZnSO4 and equilibrated with low-imidazole buffer and high salted buffer ( 50 mM imidazole , 20 mM Tris-HCl [pH 7 . 4] , 1M NaCl ) using a 50-mL Superloop . Then a linear gradient of 1–0 . 15M NaCl was applied to reduce the concentration in NaCl . Finally , a linear gradient of 80–800 mM imidazole in the same buffer was applied to elute M2-1 fractions containing the His-tagged proteins . After equilibration with 20 mM Tris-HCl [pH 7 . 4] , 150 mM NaCl buffer , M2-1 was further purified by size exclusion chromatography on a HiLoad Superdex-200 column with a 120-mL total bed volume ( GE Healthcare ) . Appropriate fractions were pooled . M2-1 protein was confirmed RNA-free by spectrophotometry ( OD 260/280 ratio ) and stored at 4°C . For P expression , E . coli BL21 ( DE3 ) bacteria transformed with pGEX-P derived plasmids were grown as described above . Bacterial pellets were resuspended in lysis buffer ( 20 mM Tris/HCl pH 7 . 4 , 60 mM NaCl , 1 mM EDTA , 1 mg/mL lysozyme , 1 mM DTT , 0 , 1% Triton X-100 ) supplemented with complete protease inhibitor cocktail ( Roche ) for 1 h on ice . Benzonase was then added and the lysate was incubated for 1 h at ambient temperature under rotation . The lysates were centrifuged at 4°C for 30 min at 10 , 000 g . Glutathione-Sepharose 4B beads ( GE Healthcare ) were added to the clarified supernatants and the mixtures were incubated overnight at 4°C under rotation . The beads were washed with lysis buffer , three times with 1X PBS and then stored at 4°C in an equal volume of PBS . For PP1 expression , chaperone competent cells pGro7/BL21 ( Takara ) were transformed with pGEX-PP1 and grown as previously described [58] . Briefly , an overnight starter culture was grown at 37°C in LB medium supplemented with antibiotics and 1 mM MnCl2 . PP1 production was initiated by inoculating 1/2 liter of LB supplemented with 1 mM MnCl2 with 35 ml of starter culture . The bacteria were grown at 30°C to an OD of ∼0 . 5 , then arabinose was added ( 2 g/l ) to induce the expression of the GroEL/GroES chaperone . When OD was ∼1 , the temperature was lowered to 10°C ( ice-bath ) and the expression of PP1 was induced with 0 . 1 mM IPTG for ∼20 h . Culture was centrifuged at 5 , 000 g for 15 min and bacterial pellets were resuspended in lysis buffer ( 20 mM Tris/HCl pH 8 . 0 , 150 mM NaCl , 1 mM MnCl2 , 1 mg/mL lysozyme , 1 mM DTT , 0 , 1% Triton X-100 ) supplemented with complete protease inhibitor cocktail ( Roche ) for 1 h on ice and treated as described above except that NaCl was then added to reach a final concentration of 700mM . For NMR experiments 15N-labeled P and two N-terminal fragments of P , P[1–126] ( residues 1–126 ) and P[1–163] ( residues 1–163 ) , were produced in M9 medium supplemented with 15N-labeled NH4Cl ( Eurisotop ) and glucose and purified following the same protocol as for full-length P . The core domain of M2-1 ( residues 58–177 ) was prepared as described previously [19] . Proteins were cleaved from GST with biotinylated thrombin ( Novagen ) . Thrombin was later removed using streptavidin resin ( Novagen ) . The samples were subsequently concentrated on centrifugation filter units ( Amicon Ultra ) to 50–150 μM and dialyzed against NMR buffer ( 20 mM sodium phosphate pH 6 . 8 , 100 mM NaCl ) . GST-PP1α was eluted from GSH-sepharose beads by using 50 mM glutathione , concentrated and dialyzed against NMR buffer . Purity was assessed by SDS-PAGE and by mass spectrometry . GST pull-downs were performed by incubating 50μl of a 50% slurry of Glutathione-Sepharose 4B beads ( GE Healthcare ) containing either GST-PP1 or GST-P ( WT and mutants ) at 25 μM in 20mM Tris/HCl [pH 7 . 4] , 150mM NaCl ( TN buffer ) with a 3-fold molar excess of M2-1 or P and BSA 3% . After 1 h at 20°C under agitation , the beads were washed extensively with TN buffer , boiled in 25 μl of Laemmli buffer and analyzed by SDS-PAGE and Coomassie blue staining . BSRT7/5 [59] cells were maintained in Eagle’s minimum essential medium and Dulbecco’s modified Eagle’s medium , respectively , supplemented with 10% fetal calf serum , 2 mM L-glutamine , and penicillin–streptomycin solution . The cells were grown at 37°C in 5% CO2 . Cytotoxicity measurements were performed using the CellTiter-Glo Luminescent cell viability assay ( Promega ) . BSRT7/5 cells at 90% confluence in 24-well dishes were transfected using Lipofectamine 2000 ( Invitrogen ) with a plasmid mixture containing 0 . 25 μg of pM/Luc minigenome , 0 . 25 μg of pN , 0 . 25 μg of pP ( WT and mutants ) , 0 . 125 μg of pL , and 0 . 06 μg of pM2-1 , as well as 0 . 06 μg of pSV-β-Gal ( Promega ) to normalize transfection efficiencies as previously described [23] . Transfections were done in triplicate and each independent transfection was performed three times . Cells were harvested at 24 h post-transfection and lysed in luciferase lysis buffer ( 30 mM Tris [pH 7 . 9] , 10 mM MgCl2 , 1 mM dithiothreitol [DTT] , 1% [vol/vol] Triton X-100 , and 15% [vol/vol] glycerol ) . Luciferase activities were measured for each cell lysate after injection of lysis buffer supplemented with ATP and D-luciferin ( final concentrations 1mM each ) with an Infinite 200 Pro ( Tecan , Männedorf , Switzerland ) and normalized to β-Gal expression levels . BSRT7/5 cells grown on coverslips were transfected with pN , pM2-1–mCherry and pP or p-BFP ( WT or variants ) using Lipofectamine2000 ( Invitrogen ) . At 24 h post-transfection , samples were fixed in 4% paraformaldehyde ( PFA ) for 30 min , and permeabilized in PBS containing 0 . 1% Triton X-100 and 3% BSA . Coverslips were incubated for 1h at room temperature with primary antibodies , washed , and then incubated for an additional hour with Alexa Fluor 488 goat anti-mouse IgG ( Invitrogen ) . For P detection the mouse anti-P monoclonal antibody 021/2P [18] was used . Coverslips were mounted with ProLong Gold Antifade reagent containing DAPI ( Life Technologies ) . Cells were observed with a Nikon TE200 inverted microscope equipped with a Photometrics CoolSNAP ES2 camera . Images were processed using MetaVue software ( Molecular Devices ) . Confocal microscopy was used to study IB ultrastructure . Z-stack image acquisitions of multi-labeled ( P-BFP , N , M2-1-Cherry , FISH ) cells were performed under a 63x apochromatic lens and a numerical zoom comprised between 1x and 15x ( LSAF acquisition software ) under the WLL Leica SP8 microscope and representative pictures were taken . Infected cells were fixed 24 h p . i . and permeabilized as described above . Endogenous biotin was blocked in PBS-BSA 1% ( w/v ) supplemented with free streptavidin ( 4 μg/ml ) for 1h . Coverslips were rinsed 3 times with PBS , post-fixed 10 min at 4°C in formaldehyde 4% ( v/v ) , rinsed 2 times with PBS , and incubated in hybridization mix ( 2x SSC ( 1x SSC is 150 mM NaCl and 15 mM sodium citrate ) , dextran 10% ( w/v ) , formamide 20% or 50% ( v/v ) for oligo ( dT ) and NS1 probes , respectively , 1 mg/ml herring sperm DNA; mRNAs were detected by using either 3’-biotinylated poly ( dT ) or a pool of NS1 oligonucleotides ( for sequences see ref . [20] at a final concentration of 100 μM in a humidified chamber at 37°C for 3h . Next , cells were washed 2 times at 42°C with the following 3 solutions: 2x SSC plus formamide 20% ( v/v ) , 2x SSC , 1x SSC and finally PBS at room temperature . Probes were then detected by incubating cells with streptavidin-Alexa Fluor 647 conjugate ( 8 μg/ml ) in PBS-BSA 1% ( w/v ) during 1h prior to 3 washes with PBS . Cells were then submitted to immunofluorescent staining and confocal microscopy . Cells were lysed for 30 min at 4°C in lysis buffer ( 20 mM Tris [pH 7 . 4] , 150 mM NaCl , 0 . 1% Triton X-100 ) supplemented with a complete protease inhibitor cocktail ( Roche ) . Cell lysates were spun for 10 min at 10 , 000 g; supernatants were recovered , mixed with Laemmli buffer , and boiled . Proteins were resolved by SDS-PAGE and transferred onto nitrocellulose membranes . The membranes were incubated in blocking solution ( 1X PBS , 0 . 05% Tween 20 supplemented with 5% milk ) for 1 h . Blots were incubated with primary antibodies in blocking solution: rabbit anti-P and anti-M2-1 antisera [31] , mouse monoclonal anti-α-tubulin antibody ( Sigma ) , rabbit polyclonal anti-PP1A antibody ( Abcam ) and rat monoclonal anti-HA-peroxidase antibody ( Roche ) . The membranes were rinsed with PBS containing 0 . 05% Tween 20 and incubated for 1 h with the appropriate HRP-conjugated secondary antibodies diluted in blocking solution . The membranes were rinsed , and immunodetection was performed by using an enhanced chemiluminescence ( ECL ) substrate ( BioRad , France ) . BSRT7/5 cells were cotransfected with pHA-P ( WT and variants ) , pN and pM2-1 . After 24 h , transfected cells were lysed for 30 min at 4°C in ice-cold lysis buffer ( 20 mM Tris HCl [pH 7 . 4] , 150 mM NaCl , 0 . 1% Triton X100 , 20μM RNAse A and 15% glycerol ) with a complete protease inhibitor cocktail ( Roche ) . Cell lysates were centrifuged at 4°C for 10 min at 10 , 000 g and incubated overnight at 4°C with a rat anti-HA monoclonal antibody ( Roche cl . 3F10 ) coupled to magnetic beads ( Invitrogen ) . The beads were then washed 3 times with lysis buffer and 1 time with PBS , proteins were boiled in Laemmli buffer for 5 min and samples were subjected to SDS-PAGE and immunoblotting as described above . 1H-15N correlation spectra , Heteronuclear Single Quantum Correlation ( HSQC ) or BEST-TROSY , were measured at a temperature of 288 K on Bruker Avance III 800 or 950 MHz spectrometers equipped with cryogenic TCI probes . 7% D2O was added to the samples to lock the magnetic field . Spectra were processed with Topspin 3 . 2 ( Bruker Biospin ) and analyzed with CCPNMR 2 . 2 software [60] . Flexible docking was carried out on the guru interface of the Haddock Webserver [61 , 62] , using the X-ray structure of M2-1core extracted from PDB 4C3E , chain B . Models of a P helix spanning residues 94–112 were built using CYANA 3 . 2 [63] under torsion angle constraints obtained from backbone chemical shifts of P . Following active M2-1 ( 126 , 127 , 129 , 130 , 133 , 148 , 152 , 156 , 160 , 163 ) and P residues ( 98 , 101 , 102 , 105 , 106 , 108 and 109 ) were identified by mutagenesis experiments or by NMR interaction experiments , in this work or in [19] . Passive residues were automatically defined around active residues . 1000 initial structures were generated . 200 final structures were refined in water and clustered according to RMSD criterion . More than 50% structures clustered in the same cluster with the best Haddock score . Statistics are shown in S1 Table .
|
Respiratory syncytial virus ( RSV ) is the leading cause of lower respiratory tract illness in infants . Since no vaccine and no potent antivirals are available against RSV , it is essential to better understand the mechanisms of viral replication to develop new antiviral strategies . Here we have investigated the mechanisms by which two essential components of the viral RNA polymerase machinery , the phosphoprotein P and the M2-1 transcription factor , interact and function . We identified the amino acid residues of P critical for this interaction and showed that they are required for P recruiting M2-1 to cytoplasmic inclusions , where viral polymerase complex proteins concentrate and viral RNA synthesis occurs . We also showed that M2-1 dephosphorylation , required for viral transcription , is achieved by a complex formed between P and the cellular phosphatase PP1 . The region of P binding to PP1 is located nearby and upstream of the M2-1 binding domain . This is the first report showing that the phosphoprotein of a negative strand RNA virus can hijack a cellular phosphatase to modulate the phosphorylation state of its partners . These two P regions interacting with M2-1 and PP1 are also potential targets for future antiviral therapy .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"phosphorylation",
"luciferase",
"nucleic",
"acid",
"synthesis",
"enzymes",
"messenger",
"rna",
"enzymology",
"dna-binding",
"proteins",
"phosphatases",
"dna",
"transcription",
"polymerases",
"sequence",
"motif",
"analysis",
"rna",
"synthesis",
"chemical",
"synthesis",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"bioinformatics",
"proteins",
"oxidoreductases",
"gene",
"expression",
"biosynthetic",
"techniques",
"biochemistry",
"rna",
"post-translational",
"modification",
"nucleic",
"acids",
"database",
"and",
"informatics",
"methods",
"genetics",
"biology",
"and",
"life",
"sciences"
] |
2018
|
RSV hijacks cellular protein phosphatase 1 to regulate M2-1 phosphorylation and viral transcription
|
The Notch signaling pathway is a highly evolutionarily-conserved cell-cell signaling pathway that regulates many events during development . It plays a pivotal role in the regulation of fundamental cellular processes , such as cell proliferation , stem cell maintenance , and differentiation during embryonic and adult development . However , functions of Notch signaling in Aedes aegypti , the major mosquito vector for dengue , are largely unknown . In this study , we identified a unique feature of A . aegypti Notch ( AaNotch ) in the control of the sterile-like phenotype in female mosquitoes . Silencing AaNotch with a reverse genetic approach significantly reduced the fecundity and fertility of the mosquito . Silencing AaNotch also resulted in the prevention of micropyle formation , which led to impaired fertilization . In addition , JNK phosphorylation ( a signaling molecule in the non-canonical Notch signaling pathway ) was inhibited in the absence of AaNotch . Furthermore , treatment with a JNK inhibitor in the mosquito resulted in impaired fecundity and fertility . Taken together , our results demonstrate that non-canonical Notch signaling is essential for controlling fertility in the A . aegypti mosquito .
Mosquitoes are highly-effective vectors that transmit many devastating diseases , including malaria , dengue , and Zika . Together , these diseases are responsible for over one million deaths each year [1–4] . Of note , cases of dengue are reaching disastrous levels in Central and South America and in Southeast Asia [5–7] . Recently , the outbreak of Zika became a threat to global health and now poses a significant public health challenge [8 , 9] . Major reasons for this tragic situation are the unavailability of effective vaccines , an increase of vector resistance to insecticides , and pathogen resistance to drugs [10–12] . Most mosquitoes can obtain amino acids and other nutrients needed for egg development from the blood of their vertebrate hosts . A blood meal results in a highly-regulated cyclicity in egg production , with each cycle tightly coupled to blood intake [13] . Mosquito vitellogenesis is initiated following a blood meal . A blood meal induces the production of ovarian ecdysteroidogenic hormone from the mosquito’s brain , which stimulates the production of ecdysone in follicle cells [14] . Ecdysone is then converted to 20-hydroxyecdysone ( 20E ) to activate the production of yolk protein precursors in fat bodies [13] . The target of rapamycin ( TOR ) signaling pathway has been shown to serve as a key cell regulator needed to complete vitellogenesis [15 , 16] . TOR signaling is regulated by rapidly increasing concentrations of specific amino acids in the hemolymph post blood meal ( PBM ) particularly leucine [17] . Inhibition of TOR in fat body culture systems , by either rapamycin or RNA interference ( RNAi ) -mediated gene depletion , results in a significant down-regulation of Vg gene transcription after amino acid stimulation [15 , 16] . In addition , inhibition of TOR in vivo inhibits egg development [15 , 16] . Results of these studies suggest that a thorough understanding of the molecular machinery involved in mosquito fertility will be useful for developing vector control strategies . The Notch gene was discovered by Morgan et al , who observed that a partial loss of Notch function results in the formation of notches at the wing margins of Drosophila melanogaster [18] . Experiments in the early 1980s established that the Notch gene encodes a 300-kDa , single-pass transmembrane receptor . In addition , the extracellular domain of the Notch receptor contains 36 epidermal growth factor ( EGF ) -like repeats that are essential for ligand binding , whereas the intracellular domain is involved in cellular signaling and contains multiple conserved protein domains . Notch-like molecules have been identified in a wide-range of organisms , from free-living nematodes ( e . g . , Caenorhabditis elegans ) to humans , suggesting that they have important ( and apparently conserved ) functional roles in embryonic development [19] . However , it is not clear what role Notch signaling plays in the development of specific tissues or how it might activate downstream genes [20] . The most extensively characterized signaling pathway is known as the canonical Notch signaling pathway [21] . In canonical Notch signaling , a Notch transmembrane receptor interacts with a ligand ( Delta ) on a neighboring cell , followed by a proteolytic cleavage of the receptor and the subsequent release of the Notch intracellular domain ( NICD ) . Translocation of NICD to the nucleus leads to its interaction with a CBF1/Suppressor of the Hairless/LAG-1 ( CSL ) family DNA-binding protein , which results in the transcription of Notch target genes [22] . In contrast , non-canonical Notch signaling has been shown to differ markedly from canonical Notch signaling in that the initiation of non-canonical Notch signaling may function without ligand binding [23 , 24] . The JNK pathway is activated when a MAPK kinase ( Hemipterous or Hep in Drosophila ) phosphorylates JNK , which in turn , phosphorylates the downstream AP-1 transcription factors Jun and Fos . Notably , JNK has been implicated as an important factor in egg-micropyle development in fruit flies and participates in the CSL-independent , non-canonical Notch signaling pathway [25 , 26] . In this study , we observed a unique feature of Aedes aegypti Notch ( AaNotch ) in the control of a sterile-like phenotype in female mosquitoes . Silencing AaNotch in the mosquito ( but not AaDelta , a canonical , Notch transmembrane ligand ) using a reverse genetic approach resulted in a significant reduction in fecundity and fertility . Silencing AaNotch abolishes micropyles , which leads to impaired fertilization . Although JNK is a downstream molecule of the non-canonical Notch signaling pathway , chemical inhibition of JNK results in impaired fecundity and fertility . Taken together , our results demonstrate that Notch-dependent regulation of sterile-like female mosquitoes is controlled by non-canonical Notch signaling .
The A . aegypti UGAL/Rockefeller mosquito strain used in this study and was raised ( with slight modification ) in manner described by other investigators [27 , 28] . Briefly , mosquitoes were provided with 10% sucrose solution and maintained at 28 °C in 75%–80% humidity with a 12/12 h light/dark cycle . Both males and females were kept in the same cage until a blood meal was provided to the females . Female mosquitoes at 3–5 days post eclosion were allowed to feed on anesthetized ICR mice ( Institute of Cancer Research , USA ) to initiate egg development . The ICR mice used in this study were obtained from the Laboratory of Animal Center at National Taiwan University ( Taipei , Taiwan ) . Females that had not obtained blood from the mice were immediately separated from those that had . Only blood-fed females were used for further experiments and egg-laying behavior was observed between 72 and 96 h PBM . The research plan for animal use was approved by the Laboratory of Animal Center at National Taiwan University ( Taipei , Taiwan ) under approval ID #20100268 . All procedures and care are described in the Standard Operating Procedure of the Laboratory of Animal Center at National Taiwan University . All persons involved in animal work had successfully completed Animal Care Training at National Taiwan University ( Taipei , Taiwan ) and were specifically trained in protocols used in the research plan . Standard procedures were used in recombinant DNA manipulations . Expressed sequence tag cDNA sequences coding for the Notch gene were identified in the VectorBase database ( https://www . vectorbase . org ) , using Drosophila Notch protein as the template ( tBLASTn ) . Full-length Notch cDNA from the cDNA pool of A . aegypti was amplified with PCR using gene-specific primers . All PCR products were cloned into the pCRII-TOPO vector ( ABI/Invitrogen , Carlsbad , California , USA ) . Full-length cDNA , deduced amino acid sequences and sequence alignment of Notch were compared using the BLAST tool provided by the National Center for Biotechnology Information ( https://blast . ncbi . nlm . nih . gov/Blast . cgi ? PAGE_TYPE=BlastSearch&BLAST_SPEC=blast2seq&LINK_LOC=align2seq ) via the Clustal algorithm . Total RNA from dissected mosquitoes was extracted with TRIzol ( ABI/Invitrogen , Carlsbad , California , USA ) and reversely transcribed . Quantitative PCR ( qPCR ) was performed using the ABI 7900 system ( ABI/Invitrogen , Carlsbad , California , USA ) and reactions were performed in 96-well plates using specific primers for AaNotch and the S7 ribosomal protein gene ( internal control ) . ABI supermix ( ABI/Invitrogen , Carlsbad , California , USA ) was used for the SYBR green reaction . All qPCR reactions were run in duplicate using 2 μl cDNA per reaction . For each experiment , data were generated from at least three different cohorts of female mosquitoes . Quantitative measurements were performed in triplicate and normalized against S7 ribosomal mRNA . A fold-change value was derived using the 2-ΔΔCt method . Time points chosen to characterize the complete vitellogenic cycle were: pre-vitellogenesis ( 3–4 days post eclosion ) , vitellogenesis ( 6 , 12 and 24 h PBM ) , early post-vitellogenesis ( 48 h PBM ) , and late post-vitellogenesis ( 72 h PBM ) . Standard curves for qPCR experiments were generated using a serial dilution of plasmids containing the transcript of the gene of interest [27] . The lowest dilution of the standard curve was given an arbitrary value of 105 and so subsequent values for serial dilutions were five orders of magnitude lower . Amounts of amplicon in test samples were generated by comparing them with the standard curve . Hence , the term “relative” means that the samples were measured relative to the standard curve of the gene of concern . The number on the Y-axis thus represents a relative value and so has no unit . Primers were as follows: S7 forward ( 5′-TCAGTGTACAAGAAGCTGACCGGA ) , S7 reverse ( 5′-TTCCGCGCGCGC-TCACT-TATTAGATT ) , AaNotch qPCR-F ( 5′-GCGTTTCGGTGCTGCTTAG ) , AaNotch qPCR-R ( 5′-CCAATTGCTGGAATCTGTTACG ) , AaNotch RNAi-F ( 5′-TAATACGACTCACTATAGGGCTCAATGGGGCAGAGTTCAT ) , and AaNotch RNAi-R ( 5′-TAATACGACTCACTATAGGGCTACCGTTTTGCCAGACCAT ) . Primers used specifically for reverse-transcription PCR analysis were AaNotch forward ( 5′-ACTGTG-CGAACGCAATTCGGAAGC ) for RNAi confirmation and AaNotch reverse ( 5′-GGCTACTG-TGATTGGGCTGGGGAGA ) for RNAi confirmation . All other primers used in this study are listed in S1 Table . Amplifications were performed with SYBR Green PCR master mix ( ABI/Invitrogen , Carlsbad , California , USA ) and analyzed using the ABI PRISM 7900 sequence detection system ( following the manufacturer’s instruction ) . Raw data were exported to EXCEL ( Microsoft ) for analysis . To generate double-stranded RNA ( dsRNA ) female mosquitoes were injected with 1 μg of AaNotch dsRNA ( 3μg/μL ) using a Nanoject II injector ( Drummond , Broomall , Pennsylvania , USA ) following procedures described previously [28] . After four days of recovery , mosquitoes were given a blood meal and examined for AaNotch depletion . Control LacZ dsRNA containing a nonfunctional part of the E . coli LacZ gene was amplified from the DH5α strain . Mosquito eggs were pre-fixed with 4% glutaraldehyde for 1 h and then post-fixed in 1% osmium tetroxide for 1 h . Each sample was washed three times with 0 . 1 M phosphate buffer ( pH 7 . 4 ) . Then , samples were dehydrated for 30 min each with increasing concentrations of ethanol ( 30% , 50% , 70% , 90% , and 100% ) and then placed in 100% acetone for another 30 min . Subsequent critical-point drying and gold coating of particles were performed by the National Taiwan University TechComm . Gold-coated egg samples were analyzed with an FEI Inspect S scanning electron microscope ( Thermo Fisher Scientific , Inc . ) . Female mosquitoes at 3–5 days post-emergence were given a blood meal . Then , three days after obtaining a blood meal , mosquitoes were placed individually into a 50 mL centrifuge tube with a wet piece of 3M paper on which they could oviposit . The 3M papers were then dried and kept at room temperature for at least five days . Then , the 3M papers were placed in 20–30 °C water and exposed to a vacuous atmosphere for 1 h for hatching . Numbers of hatched larvae were calculated to compare hatching rates . Mosquito tissues collected from individual mosquitoes were separately put into micro-centrifuge tubes containing 100μL of breaking buffer [50 mM Tris ( pH 7 . 4 ) , 1% IGEPAL , 0 . 25% sodium deoxycholate , 150 mM NaCl , 1 mM EDTA , 1 mM phenylmethyl-sulfonylfluoride , 1X protease inhibitor mixture , and 1X phosphatase inhibitor mixture ( Sigma-Aldrich , St . Louis , Missouri , USA ) ] and homogenized using a pellet pestle . The homogenates were centrifuged at 13 , 000 rpm for 5 min . The supernatants were transferred into a Qiashredder Column ( Qiagen , Los Angeles , California , USA ) and centrifuged again under the same conditions for 10 min . The flow-through was transferred to a clean micro-centrifuge tube to conduct a Western blot analysis using anti-phosphoric JNK antibody ( V7931 , Promega ) and anti-JNK antibody ( sc-571 , Santa Cruz ) . The blot was developed by VisGlow Chemiluminescent Substrate and HRP ( Visual Protein ) . Female mosquitoes at three to five days post-emergence were fed with blood they obtained from anesthetized ICR mice . Each mosquito was injected with 0 . 75 μg of SP600125 at 24 h PBM . Mosquitoes injected with dimethyl sulfoxide ( DMSO ) were used as controls . All statistical analyzes in this study were performed using GraphPad Prism 5 software ( GraphPad Prism software ) . Gene-expression , fecundity , and fertility data were analyzed using ANOVA for all independent experiments .
We cloned Notch cDNA from the mosquito A . aegypti UGAL/Rockefeller strain ( Vector Base ID: AAEL001210 ) . The cDNA encodes for a deduced 2599 amino acids with a relative molecular mass of approximately 285 . 8 kDa . To decipher the specific expression patterns of AaNotch in various tissues , we examined the transcription level of AaNotch in fat bodies ( homologous to the mammalian liver ) , midgut , ovary , and carcass ( a collection of the remaining tissues ) . Analysis of three independent cohorts showed that AaNotch transcripts were expressed in ovary , midgut , and fat body in response to a blood meal . It is worth noting that AaNotch transcription was greatly increased in ovaries PBM ( S1 Fig ) . To investigate the role of AaNotch in mosquito fecundity , three-day-old mated female mosquitoes were injected with the dsRNA from LacZ or AaNotch and their egg productions were compared to female mosquitoes without any double-stranded RNA treatment . Egg production was examined four days PBM . Fig 1A showed that while AsNotch was efficiently knocked down ( right panel ) , there was also a significant reduction in the number of eggs deposited by the AaNotch-silenced mosquitoes ( 20 ± 5 ) compared to that of controls ( 73 ± 6 ) or dsLacZ-treated ( 68 ± 5 ) mosquitoes ( left panel ) . Follicles from dsRNA-treated mosquitoes randomly selected for stereomicroscopic observation showed no obvious difference in morphologies ( S2A Fig ) and the number of follicles between dsLacZ ( 90 ± 4 ) and dsNotch-treated ( 84 ± 5 ) mosquitoes , suggesting that silencing Notch does not affect follicle development . To elucidate the effect of AaNotch on egg tanning , we compared the percentages of melanized eggs relative to control , dsLacZ , and dsNotch-treated mosquitoes . A large portion ( 44% ) of eggs from AaNotch-silenced mosquitoes remained soft and white at five days post-egg laying , while eggs from control and dsLacZ-treated mosquitoes were completely melanized ( Fig 1B and 1C ) . Inset of Fig 1C showed that AsNotch was efficiently knocked down . A hatching assay was performed to determine the percentages of hatching larvae in control and dsLacZ- or dsNotch-treated mosquitoes . Although 100% of the eggs from control and dsLacZ-treated mosquitoes hatched , only 7% of the melanized eggs and none of the non-melanized eggs from AaNotch-silenced mosquitoes hatched ( Fig 1D , right and left panel ) . Our analysis of scanning electron microscopy on the ultrastructure of the eggs showed that while the micropyle and micropylar pores of eggs from control ( Fig 2A and 2A’ ) and dsLacZ-treated ( Fig 2B and 2B’ ) mosquitoes were detectable , those of both melanized ( Fig 2C and 2C’ ) and non-melanized ( Fig 2D and 2D’ ) eggs from AaNotch-silenced mosquitoes were missing . The ultrastructure of eggs from AaNotch-silenced mosquitoes indicates that these eggs would not be fertilized and hence , would have low fertility ( Fig 1D ) . While micropylar pores could be detected in 100% of the eggs from control and dsLacZ-treated mosquitoes , they were present in only two of 21 melanized eggs from dsNotch-treated mosquitoes . Most importantly , none of the non-melanized eggs from dsNotch-treated mosquitoes exhibited micropylar pores ( Fig 2E ) . ( Eggs from control , dsLacZ- and dsNotch-treated female mosquitoes were treated with 50% bleach to remove the chorion and examined the interiors of these eggs . ) We discovered that developing embryos were detected in eggs from control mosquitoes , but not in melanized or non-melanized eggs from dsNotch-treated mosquitoes ( S3 Fig ) , showing that embryo development is impaired in the eggs of Notch-silenced mosquitoes . These results together strongly suggest that AaNotch is responsible for the formation of micropyle and hence , is crucial for mosquito fertility . We hypothesized that fertility reduction in AaNotch-silenced mosquitoes results from the abolishment of micropyles . To examine the status of fertilization in non-melanized and melanized eggs from Notch-silenced mosquitoes , one sperm and one embryo-specific gene were selected as indicators to determine the status of fertilization and embryo development . Eggs from dsNotch-treated mosquitoes were then separated into melanized ( dsNotch-MZ ) and non-melanized ( dsNotch-non-MZ ) groups . The sperm-specific gene ( Vector Base ID: AAEL008779 ) was detected in eggs from controls and dsLacZ-treated mosquitoes , but not in eggs from Notch-depleted mosquitoes , indicating that eggs from Notch-silenced mosquitoes had not been fertilized ( Fig 3A ) . When we examined AaNotch embryonic development based on total RNA , we found that the early-embryo gene KLC2 . 2 was detected only in the eggs from controls and dsLacZ-treated mosquitoes , but not from Notch-silenced mosquitoes ( Fig 3B ) . Taken together , these findings indicate that AaNotch controls the fertilization processes in female A . aegypti . When we analyzed effects of silencing the binding-ligand Delta and transcription factor CSL on Notch-controlled processes , we found that neither Delta not CSL affected mosquito fecundity ( S4A Fig ) , egg melanization ( S4B Fig ) , or fertility ( S4C Fig ) . These results suggest that Notch-dependent regulation of mosquito fertility is likely not controlled by the canonical Notch signaling pathway . JNK has been implicated as an important factor in egg-micropyle development in fruit flies and it participates in the CSL-independent , non-canonical Notch signaling pathway [25 , 26] . It has been demonstrated that JNK phosphorylates transcription factors Jun and Fos , giving rise to a Jun/Fos dimer that activates transcription of target genes [29] . When we monitored the inhibition efficiency of the chemical inhibitor of JNK , we found that the expression of Jun was significantly inhibited with the treatment of SP600125 at dosages > 0 . 75 μg ( S5A Fig ) . Furthermore , the specificity of SP600125 was confirmed because it did not affect the expression of A . aegypti p38 ( AAEL008379 ) or EGFR ( AAEL004391 ) , both downstream components of other signaling pathways involving JNK ( S5C and S5D Fig ) . However , inhibition of JNK phosphorylation in the non-canonical Notch pathway significantly reduced egg melanization ( Fig 4A and 4B ) , fertility ( Fig 4C ) , and micropyle formation ( Fig 4D ) . Specifically , inhibition of JNK rendered 45% of eggs soft and white at five days after egg laying ( Fig 4A and 4B ) . Our hatching assay showed that only 7% of the melanized eggs from mosquitoes treated with the JNK inhibitors hatched , while none of the non-melanized eggs hatched ( Fig 4C ) . Ultrastructural analysis also revealed that eggs from mosquitoes treated with the JNK inhibitor had missing micropyles and micropylar pores ( Fig 4D ) . Although micropylar pores could be detected in 100% of the eggs from control and DMSO-treated mosquitoes , the pores were present in only 2 of 19 ( 10% ) of melanized eggs from mosquitoes treated with the JNK inhibitor ( Fig 4E ) and none of the non-melanized eggs had micropylar pores ( Fig 4E ) . These results demonstrate that Notch-dependent regulation of mosquito fertility is controlled by a non-canonical Notch signaling pathway . Our results from three biological cohorts showed that silencing AsNotch significantly inhibited JNK phosphorylation in mosquitoes that produced either melanized eggs or non-melanized eggs ( S6 Fig and Fig 5A , upper panel ) , while total JNK did not differ between controls , dsLacZ- , and dsNotch-treated mosquitoes ( Fig 5A , middle and lower panel ) . When we examined signal intensities ( quantified with Image J software ) that had been normalized to controls , we found that there was a significant reduction in signal intensity of JNK phosphorylation in AaNotch-silenced mosquitoes producing either melanized eggs or non-melanized eggs ( 22% and 20% , respectively ) ( Fig 5B ) . Our results demonstrate that non-canonical Notch signaling is critical for the control of fertility in the mosquito A . aegypti .
The Notch pathway is an evolutionarily-conserved signaling pathway that functions during diverse developmental and physiological processes , including embryonic development , cell-fate specification , and stem cell maintenance [21–24] . One Notch receptor gene has been identified in A . aegypti , one in Drosophila , two in C . elegans ( Lin-12 and Glp-1 ) and four in mammals ( Notch1 , Notch2 , Notch3 , and Notch4 ) [30–34] . The initial study of Notch was on a mild phenotype at the wing tip of Drosophila [18] . Notch study has since grown into an interdisciplinary field involving genetics , developmental , cellular , and molecular biology . However , the function of the Notch signaling pathway in A . aegypti still remains largely unknown . In this paper , we demonstrate the crucial role of non-canonical Notch signaling in the control of a sterile-like phenotype in the mosquito A . aegypti and indicate that AaNotch plays an important role in regulating mosquito fecundity and fertility . Notch signaling has been demonstrated to be involved in the regulation of oogenesis in Drosophila [22–24] by regulating multiple aspects of somatic follicle cell differentiation in Drosophila ovaries , including differentiation of stalk and polar cells [35 , 36] . In addition , Notch signaling ( in concert with an ecdysone receptor ) has been found to control of dorsal volume of appendage tubes by promoting apical re-expansion and lateral shortening of dorsal appendage-forming follicle cells [35] . Thus , Notch signaling differs in its physiological functions between mosquitoes and Drosophila . AaNotch also affects melanization of mosquito eggs , but the mechanism for how this occurs is not known and so must be investigated further . Our ultrastructural analysis showed that micropyle and micropylar pores do not occur in eggs from AaNotch-silenced mosquitoes . Because mosquito sperms penetrate eggs through micropylar pores , fertilization cannot occur without an intact micropylar pore . Our results suggest that AaNotch signaling modifies micropylar pore formation in mosquito eggs , essentially resulting in defective fertilization . By silencing Delta ( ligand of Notch ) and CSL ( transcription factor of Notch signaling ) , we discovered that Notch-dependent regulation of reproduction is not controlled by canonical Notch signaling pathway , but rather that there might be a non-canonical Notch signaling role in the regulation of mosquito fecundity and fertility . Zecchini et al . showed that , in Drosophila , Notch plays a role in the patterning of dorsal epidermis through a JNK-signaling pathway [25] . The JNK cascade is essential for the correct morphogenesis of dorsal appendages and micropyle formation during Drosophila oogenesis [25] . We found that treating mosquitoes with JNK inhibitor significantly reduced micropylar pore formation , egg melanization , and hatching . These results indicate that JNK is essential for controlling fertility in mosquitoes . We also showed that silencing AsNotch inhibits JNK phosphorylation , thus suggesting that AaNotch controls an upstream process of JNK phosphorylation and so controls mosquito reproduction through a non-canonical Notch signaling pathway . A recent report indicated that Notch signaling controls gut actin cytoskeleton in mosquitoes via micro-RNA 275 [37] . Thus , it is very likely that Notch signaling controls multiple physiological functions in mosquitoes . In recent years , use of the mosquito endosymbiont bacterium Wolbachia pipientis has become a promising strategy for controlling mosquitoes that carry diseases [38 , 39] . Wolbachia is well known for its ability to induce cytoplasmic incompatibility , which causes reproductive abnormalities in its insect host . A Wolbachia-based strategy has been used in several field study sites to control dengue [38 , 39] . An alternative , transgenic-based strategy has also been developed to sterilize insect vectors to reduce their populations [40 , 41] . Both of these strategies aim to reduce vector populations by controlling mosquito reproduction . In our study , we discovered that the non-canonical Notch signaling pathway controls A . aegypti reproduction . Therefore , it is possible that modulating AaNotch could be used as an alternative strategy for controlling A . aegypti populations . In summary , our study identified a fundamental role of non-canonical Notch signaling pathway in the regulation of mosquito fertility . Because mosquito-borne diseases remain an important threat to several billion people worldwide who inhabit tropical and subtropical countries , novel or alternative approaches for vector control are urgently needed . Wolbachia-based elimination strategies [42 , 43] and engineered genetic approaches for vector control [40 , 41] shed new light on the control of mosquito-borne diseases . Our study reveals the pleiotropic action of non-canonical Notch signaling in the control of mosquito reproduction , thereby providing new insight for developing environmentally-friendly methods to target vector reproduction .
|
Mosquitoes transmit many devastating diseases , including malaria , dengue , and Zika , which together are responsible for over one million deaths per year . Major reasons for this tragic situation are the unavailability of effective vaccines and drugs for most mosquito-borne diseases , increased resistance of vectors to insecticides , and resistance of pathogens to currently available drugs . A thorough understanding of the molecular machinery involved in mosquito fertility is essential for developing vector control strategies . In this study , we observed a unique feature of the Aedes aegypti Notch ( AaNotch ) in the control of a sterile-like phenotype in female mosquitoes . Silencing AaNotch using a reverse genetic approach revealed significant reductions in fecundity and fertility . It also resulted in the abolishment of micropyles , which led to impaired fertilization . However , no effect on fecundity and fertility was observed in the absence of AaDelta , a canonical Notch transmembrane ligand . Although JNK is a downstream component of the non-canonical Notch signaling pathway , treatment with a JNK inhibitor resulted in impaired fecundity and fertility . In conclusion , our results demonstrate that Notch-dependent regulation of sterile-like female mosquitoes is controlled by non-canonical Notch signaling .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"phosphorylation",
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"body",
"fluids",
"animals",
"notch",
"signaling",
"animal",
"models",
"developmental",
"biology",
"drosophila",
"melanogaster",
"model",
"organisms",
"experimental",
"organism",
"systems",
"population",
"biology",
"insect",
"vectors",
"drosophila",
"fecundity",
"research",
"and",
"analysis",
"methods",
"infectious",
"diseases",
"aedes",
"aegypti",
"proteins",
"fertilization",
"disease",
"vectors",
"insects",
"arthropoda",
"population",
"metrics",
"signal",
"transduction",
"mosquitoes",
"biochemistry",
"eukaryota",
"blood",
"cell",
"biology",
"anatomy",
"post-translational",
"modification",
"physiology",
"biology",
"and",
"life",
"sciences",
"species",
"interactions",
"cell",
"signaling",
"organisms"
] |
2018
|
The non-canonical Notch signaling is essential for the control of fertility in Aedes aegypti
|
Spinster ( Spin ) in Drosophila or Spinster homolog 1 ( Spns1 ) in vertebrates is a putative lysosomal H+-carbohydrate transporter , which functions at a late stage of autophagy . The Spin/Spns1 defect induces aberrant autolysosome formation that leads to embryonic senescence and accelerated aging symptoms , but little is known about the mechanisms leading to the pathogenesis in vivo . Beclin 1 and p53 are two pivotal tumor suppressors that are critically involved in the autophagic process and its regulation . Using zebrafish as a genetic model , we show that Beclin 1 suppression ameliorates Spns1 loss-mediated senescence as well as autophagic impairment , whereas unexpectedly p53 deficit exacerbates both of these characteristics . We demonstrate that ‘basal p53’ activity plays a certain protective role ( s ) against the Spns1 defect-induced senescence via suppressing autophagy , lysosomal biogenesis , and subsequent autolysosomal formation and maturation , and that p53 loss can counteract the effect of Beclin 1 suppression to rescue the Spns1 defect . By contrast , in response to DNA damage , ‘activated p53’ showed an apparent enhancement of the Spns1-deficient phenotype , by inducing both autophagy and apoptosis . Moreover , we found that a chemical and genetic blockage of lysosomal acidification and biogenesis mediated by the vacuolar-type H+-ATPase , as well as of subsequent autophagosome-lysosome fusion , prevents the appearance of the hallmarks caused by the Spns1 deficiency , irrespective of the basal p53 state . Thus , these results provide evidence that Spns1 operates during autophagy and senescence differentially with Beclin 1 and p53 .
Autophagy is an evolutionarily conserved intracellular catabolic process whereby cytoplasmic proteins and organelles are engulfed into autophagosomes and subsequently degraded in autolysosomes , following fusion with lysosomes . Biologically significant roles of autophagy have been illuminated in a variety of physiological and pathophysiological conditions , such as occurs during the adaptation to nutrient starvation , the clearance of damaged proteins and cell organelles , development , cell survival and death , tumor progression and suppression , elimination of pathogens , and aging [1] . It has also been suggested that autophagy can have a beneficial effect on longevity in many lower organisms from yeast to flies , although a clear role in lifespan extension still remains elusive in vertebrates [2] . Furthermore , several interventions that promote longevity , including caloric restriction and chemical treatment with rapamycin , have exploited their impact through autophagy [3] . Zebrafish is an ideal organism to study the entire developmental process ex utero and are easily accessible for both experimental and genetic manipulations . Therefore , the zebrafish model system has become a popular platform to explore the mechanisms of human diseases [4] . Recently in our laboratory , we screened mutagenized zebrafish embryos for the altered expression of senescence-associated β-galactosidase ( SA-β-gal ) , which is a versatile senescence biomarker widely used in both cellular senescence and organismal aging studies [5] , [6] , [7] . SA-β-gal has also been utilized for various detection of embryonic/larval senescence in our studies and those of others [8] , [9] , [10] , [11] . We successfully validated the use of embryonic SA-β-gal production as a valuable screening tool by analyzing over 500 zebrafish mutants [12] . Of our identified mutants , the highest SA-β-gal activity was found to be associated with an insertion in the gene denoted “not really started” ( nrs ) ( currently denoted as zebrafish spinster homolog 1 , spns1 ) , which is a homolog of Drosophila spinster , a gene that regulates aging and lifespan in flies [13] . Zebrafish harboring a homozygous mutation in the spns1 gene revealed embryonic/larval lethality , associated with yolk opaqueness and senescence [12] , [14] . Adult zebrafish with a heterozygous deletion of spns1 show accelerated signs of aging , including an increased accumulation of the “aging pigment” lipofuscin in the muscle and liver , and have shortened lifespan [12] . Spinster has been implicated in a lysosomal storage function in flies [13] , [15] , and Spns1 deficiency leads to impaired autophagic termination and lysosome reformation problems in the mammalian cell culture system [16] . However , it remains unknown how Spns1 physiologically and pathophysiologically has an impact on autophagic homeostasis in conjunction with senescence in higher organisms in vivo , where we lack an appropriate vertebrate model system except for zebrafish . Beclin 1 , an autophagic regulator , is essential for early embryonic development , and is a haploinsufficient tumor suppressor [17] . During starvation of cultured cells , the accumulation of large and long-lasting autolysosomes caused by Spns1 deficiency is attenuated by concurrent beclin 1 knockdown , suggesting dependence on autophagy induction and progression [16] . p53 , the most extensively characterized tumor suppressor , is a master regulator with pleiotropic effects on genomic stability , cell cycle , proliferation , cell death , tumorigenesis , stress response , senescence and energy metabolism , and is also involved in autophagic regulation [18] . p53 had been exclusively considered as a positive regulator of autophagy [19] , but was recently found also to act as an autophagic inhibitor [20] , [21] . Thus , the role of p53 in autophagy regulation requires further study since it may underlie key aspects of metabolism , aging , and cancer biology . We examined the impact of Spns1 impairment on the autophagic process and on the induction of embryonic senescence in zebrafish , in order to clarify how autolysosomal processing is linked to these two tumor suppressors , Beclin 1 and p53 . In this study , we found that inhibition of Beclin 1 can attenuate the yolk opacity and senescence caused by the Spns1 defect , whereas deficiency of “basal” p53 augments them ( “basal” meaning in the absence of extrinsic genotoxic stress , e . g . , ultraviolet light ) . Conversely , p53 “activated” by DNA damage apparently induced autophagy and apoptosis , intensifying the Spns1-deficient phenotype . Moreover , a chemical and genetic blockage of lysosomal acidification by inhibition of vacuolar-type H+-ATPase ( v-ATPase ) prevented the appearance of the hallmarks of Spns1 deficiency irrespective of the p53 state , while at the same time preventing autophagosome-lysosome fusion . Our findings thus suggest that Spns1 is critically involved in lysosomal acidification and trafficking during autophagy , and acts in the same pathway as Beclin 1 and p53 in the regulation of senescence .
Spin/Spns1 has been implicated in the regulation of autophagic lysosomal homeostasis in mammalian cells and flies [15] , [16] . In fact , in zebrafish , electron microscopy revealed that compared with the wild-type control , spns1-mutant larvae accumulated cytoplasmic membranous inclusions corresponding to late endosomal , autophagic , and lysosomal structures in the hypodermal and retinal epithelial cells ( Figure S1A ) . To verify that the autophagic process of spns1-deficient ( spns1hi891/hi891 ) vertebrates is fundamentally disturbed , we generated EGFP-tagged microtubule-associated protein 1 light chain 3 ( LC3 ) transgenic zebrafish with the spns1-mutant background . In the resulting EGFP-LC3-transgenic spns1-mutant [Tg ( CMV:EGFP-LC3 ) ; spns1hi891/hi891] fish line , grossly enhanced EGFP intensity was observed throughout the body in comparison with the original Tg ( CMV:EGFP-LC3 ) line [22] , [23] ( Figure 1A ) . In addition , intracellular localization of EGFP-LC3 was detectable as aggregated puncta in periderm or basal epidermal cells of the skin ( above the eye on the head or in the caudal fin ) and epithelial cells of several other organs including yolk sac , retina , and liver ( Figure 1B ) , suggesting excessive autophagosome and/or autolysosome accumulation . To gain additional information concerning the site of action of Spns1 , we examined LC3 conversion as a hallmark of autophagy induction in whole zebrafish embryos by immunoblotting to distinguish the autophagosome-associated phosphatidylethanolamine-conjugated LC3-II from the cytosolic LC3-I form by showing the increased mobility of LC3-II . In spns1 mutants , both endogenous LC3-II and exogenous EGFP-LC3-II were detected at higher levels ( Figure 1C ) . Extending our analysis to a second animal model , we also examined autophagy activity in Caenorhabditis elegans containing a loss-of function mutation in the gene homologous to spin-1 ( C13C4 . 5 ) [24] . Similar to our results in zebrafish , the C . elegans spin-1 mutation conferred augmented autophagic induction , as demonstrated by the increased expression and cytoplasmic aggregation of the EGFP::LGG-1 reporter gene product ( LGG-1 is the ortholog of LC3 ) in seam cells of mutant animals ( Figure S1B and C ) . We found the spin-1 mutant worms were more sensitive to starvation-induced death ( Figure S1D ) , consistent with defective autophagy . In addition , decrease of Spns1 in heterozygous zebrafish as well as loss of Spin-1 in homozygous worms resulted in significant reductions in their adult lifespan ( Figure S1E and F ) . These data suggest that across these different species , the defects in the spns1/spin-1 gene induce autophagic abnormality with excessive autophagosomes and/or autolysosomes , potentially leading to the accumulation of undegraded macromolecules and organelles in cells of mutant animals , which subsequently have a shortened life expectancy . Spin/Spns1 is a multi-pass transmembrane protein localized in late endosomes and lysosomes [15] , [25] . In mammalian cells , however , Spns1 has been reported to occasionally localize to mitochondria [26] . To elucidate a potential relationship between lysosomal and mitochondrial biogenesis with the pathogenesis induced by the Spns1-defective animals in vivo , we performed double staining of these two organelles by using LysoTracker ( red ) and MitoTracker ( green ) probes . In whole animal images , we found prominent increases of LysoTracker intensity in spns1-mutant fish , whereas no significant difference was detected by MitoTracker staining ( Figure S2A ) . By further utilizing Tg ( CMV:EGFP-LC3 ) ;spns1hi891/hi891 animals , concurrent LysoTracker staining revealed significant numbers of intracellular yellow ( both green- and red-positive ) puncta . Since the EGFP green signal is normally lost by quenching in acidic compartments such as the lysosome [27] , this finding suggests the existence of insufficiently acidic autolysosomes ( Figure 1D and E ) . In contrast , staining with a mitochondrial superoxide indicator , MitoSOX , revealed no critical abnormality of superoxide generated in the mitochondria ( Figure S2B ) . These results suggest that Spns1 deficiency fundamentally leads to impaired lysosomal and/or autolysosomal acidification , but not to any significant modulation of mitochondrial biogenesis and oxidative stress . Autophagosomes subsequently fuse with lysosomes to degrade their contents . The Spns1 defect causes excessively enlarged undegraded deposits of autolysosomal compartments in cells [16] . The inability of spns1 mutants to degrade protein aggregates , despite the apparent induction of autophagosomes , prompted us to ask whether Spns1 is required for degradation of autophagic cargos by ensuring proper acidification in autolysosomes . To address this question , we generated EGFP-LC3;mCherry-LC3 double-transgenic zebrafish [Tg ( CMV:EGFP-LC3;mCherry-LC3 ) ; spns1hi891/hi891] to determine the acidification efficiency . As EGFP fluorescence is lost in acidic compartments , but mCherry red fluorescence is not , the coexpression of EGFP-LC3 and mCherry-LC3 can label insufficiently acidified autolysosomes as well as non-acidic autophagosomes to produce yellow fluorescence ( positive for both green EGFP and red mCherry ) , whereas acidic autolysosomes would only show a red fluorescent signal . To first validate that the EGFP signal was decreased or lost by quenching in acidic autolysosomes of wild-type animals , we utilized two lysosomal protease inhibitors , pepstatin A , an inhibitor of cathepsins D and E , and E-64-d , an inhibitor of cathepsins B , H and L . Because these inhibitors can target the proteases without altering autolysosomal acidity , we anticipated that the EGFP signal would only be reduced in truly acidic vesicles . In wild-type animals , as expected , only the large punctate signals of EGFP-LC3 were faded , whereas neither the LysoTracker nor mCherry-LC3 signals were affected ( Figure S2C and D ) . On the other hand , as shown in Figure 1F , once spns1 morpholino antisense oligonucleotide ( MO ) was injected into the GFP- and mCherry-LC3-double transgenic fish embryos to knockdown the gene expression , we observed a prominent increase in the number of yellow-fluorescent enlarged intracellular vesicles as compared with those in standard control MO-injected animals , consistent with the accumulation of insufficiently acidified autolysosomes . The EGFP-LC3-positive vesicles in the spns1 mutants were further confirmed to be autolysosomes by the co-expression of a mCherry-tagged lysosomal membrane marker , lysosomal-associated membrane protein 1 ( Lamp1 ) ( Figure 1G ) . mCherry-LC3-positive enlarged vesicular aggregations that accumulated in the spns1-mutant fish were suppressed by expression of EGFP-tagged Spns1 vector ( Spns1 WT ) but not by that of an empty EGFP vector or an EGFP-tagged mutant Spns1 vector ( Spns1 E153K; presumably disrupted for the transporter activity ) [15] , [16] ( Figure 1H ) . In addition , the vast majority of EGFP-LC3-positive vesicles in spns1 mutants were found to be still positive for a fluorogenic lysosomal substrate DQ Red BSA at the earlier phenotypic stages ( ∼60 hours post fertilization; hpf ) ( Figure S2E ) . DQ Red BSA fluoresces upon lysosomal degradation due to dequenching; the released peptide fragments are brightly fluorescent . Thus , the autolysosomes of spns1-mutant fish appeared to still contain hydrolytic activity at least in early autolysosomes , indicating that the primary reason for the retained EGFP-LC3 signal is probably due to suboptimal acidity at later stages . Therefore , the observed increase in both EGFP-LC3 and mCherry-LC3 double-positive yellow fluorescent intracellular vesicles in spns1-mutant fish could be attributed to ineffective or insufficient acidification ( “mal-acidification” ) at the late autolysosomal stage . Based on a recent report of an autophagy-dependent effect of spns1 knockdown in a mammalian cell culture [16] and our current observations described above in the zebrafish model , we assumed that inhibition of the early stages of autophagy by blocking the class III phosphatidylinositol 3-kinase ( PtdIns3K ) complex containing Vps34/Pik3c3 and Beclin 1 would reduce aggregated LC3 puncta in cells of spns1 mutants and ameliorate yolk opaque abnormalities induced by the Spns1 deficiency . We therefore designed a splice-block morpholino antisense oligonucleotide ( MO ) targeting the zebrafish beclin 1 ( becn1; zbeclin 1 ) gene at the 5′ end of exon 4 ( Figure 2A ) . RT-PCR and DNA sequencing results showed this splice-block MO ( beclin 1 MO ) generated a loss of exon 4 and a premature stop codon , resulting in a truncated protein lacking the entire Bcl2 homology domain 3 ( BH3 domain ) ( Figure 2B ) . The phenotype induced by the knockdown of beclin 1 by the MO during early development was not particularly evident at the gross morphology level apart from some minor developmental retardation at 24 hpf , without any obvious abnormality later on ( Figure S3A ) . In contrast , the concurrent suppression of both spns1 and beclin 1 by MO targeting strikingly diminished the yolk opaqueness seen with the spns1 morphants and produced an increased number of viable larvae that survive beyond 72 hpf ( Figure 2C–E ) . We also performed beclin 1 MO injections into spns1-mutant embryos , and reproducibly confirmed the ameliorated yolk phenotype through 3 dpf ( Figure S3B ) , but mutant animals subsequently relapsed into deterioration , presumably due to the persistent impact of the Spns1 mutation and/or transient activity of the beclin 1 MO . These results indicate that suppression of the early stage of autophagy by beclin 1 knockdown can offset the deleterious effect of Spns1 deficiency that occurs at the late stage of autophagy . We next examined whether the enlarged aggregations of LC3 in spns1 morphants and mutants can be restored by Beclin 1 knockdown . spns1 MO and/or beclin 1 MO were introduced into Tg ( CMV:EGFP-LC3 ) fish embryos and resultant specimens were observed by confocal microscopy at the cellular level . The appearance of punctate vesicle-like intracellular aggregates and deposits observed in spns1 morphants was diminished by the beclin 1 knockdown ( Figure 3A ) . LC3 has several functional homologs , including gamma-aminobutyric acid A ( GABA ) -receptor associated protein ( GABARAP ) and GABARAPL2/GATE-16 . It has been reported that both LC3 and GABARAP are indispensable for the autophagic process in mammalian cells [21] . The restorative effect of beclin 1 knockdown was also demonstrated in spns1-depleted Tg ( CMV:EGFP-GABARAP;mCherry-LC3 ) fish . The concomitant microinjection of spns1 MO and beclin 1 MO showed consistently similar outcomes in terms of the obvious reduction of both EGFP-GABARAP and mCherry-LC3 puncta ( Figure 3B ) , as observed with the EGFP-LC3 puncta ( Figure 3A ) . Another hallmark of spns1-mutant fish is the striking induction of senescence-associated β-galactosidase ( SA-β-gal ) , which is an endogenous lysosomal β-D-galactosidase detectable at pH 6 . 0 [12] , [28] . Previously we demonstrated that an embryonic ( or larval ) senescence phenotype caused by specific gene mutations ( or MO-mediated knockdowns ) and also by stress is readily detectable via SA-β-gal staining of zebrafish embryos and larvae [12] . Additionally , we also tested another lysosomal hydrolase/glycosidase , α-L-fucosidase ( α-fuc ) that has been reported in mammalian cells as a novel sensitive biomarker , senescence-associated α-fuc ( SA-α-fuc ) [29] . We found that higher activity of SA-α-fuc , as well as of SA-β-gal , was detected in spns1-mutant fish , compared with wild-type control fish , with SA-β-gal being the more sensitive assay ( Figure S3C; see also Text S1 and S2 ) . We therefore examined the effect of beclin 1 MO by staining with SA-β-gal in both spns1 morphants and mutants . Consistent with the restored yolk clarity and reduced LC3 puncta observed with beclin 1 knockdown in conditions of Spns1 deficiency , the beclin 1 MO markedly decreased the intensity of SA-β-gal at 3 . 5 dpf ( Figure 3C and Figure S3B ) , whereas control injections ( water and standard control MO ) did not significantly affect the SA-β-gal activity in spns1 morphant and mutant animals ( Figure 3C and Figure S3B ) . These results suggest that the aberrant SA-β-gal activity in spns1-defective animals coincides with autophagic initiation and its progression , and is accompanied by an increase in autolysosomes at the late autophagy stage . While the excessive accumulation of autophagosomes and autolysosomes was observed in spns1-deficient animals , we anticipated that induction of apoptosis may be accompanied or preceded by the autophagic abnormality . We found , however , that such apoptotic induction was undetectable in spns1 mutants and morphants ( Figure S4 and Figure S5; see also Text S1 and S2 ) . Acridine orange ( AO ) staining , which can correspond to the detection of acidified compartments [30] , [31] as well as of apoptotic and necrotic cell death [32] , [33] , showed positive signals co-stained by LysoTracker in spns1 mutants ( Figure S4 ) . However , when we performed a TUNEL assay for detecting DNA fragmentation associated with apoptosis , we found no staining upon knockdown of spns1 ( Figure S5 ) , while the positive control of ultraviolet light ( UV ) irradiation produced a TUNEL-positive signal , as reported previously [34] . The UV irradiation-mediated apoptosis was slightly but not significantly inhibited by beclin 1 knockdown ( Figure S6a ) , which can fully suppress autophagy induced by UV ( Figure S6B ) , suggesting that Beclin 1 plays a critical role in initiating autophagy , but is potentially dispensable for the induction of UV-mediated apoptosis in zebrafish embryos . It has been reported that cells deficient in Beclin 1 exhibit an elevated DNA damage response [35] , along with an increase in reactive oxygen species ( ROS ) [36] . In addition , a reduction of p53 by proteasomal degradation has been documented under the condition of beclin 1 knockdown [37] . The stress-responsive function of p53 still remains poorly understood with regard to how it is linked to autophagy impairment . In fact , although activated nuclear p53 can induce autophagy [38] , it has also been reported that a removal of basal cytosolic p53 can stimulate autophagy [20] . We wondered which state of p53 , if either , is involved in the Spns1 impairment . Moreover , since p53 activation is ordinarily thought to induce cellular senescence , which is also the case for zebrafish embryonic senescence [33] , we suspected that the suppression of senescence by Beclin 1 depletion might be due to an intrinsic reduction in p53 [37] . We therefore investigated the requirement of p53 in the Spns1 deficiency-mediated senescence in zebrafish embryos under various experimental conditions through the genetic manipulations described below . First , we examined the potential contribution of Spns1 and p53 separately in spns1 and p53 mutant fish backgrounds . We tested spns1 MO and p53 MO in p53 mutants and spns1 mutants , respectively ( Figure S7 ) . Unexpectedly , either p53 mutation or knockdown enhanced , rather than suppressed , the senescence phenotype under the Spns1-defective conditions . This increased SA-β-gal activity that is induced by p53 suppression was further demonstrated by coinjection of p53 MO and spns1 MO into normal wild-type animals to rule out any background influence in the mutants ( Figure 4A , upper panels and B ) . Next , we performed coinjections of p53 and spns1 MOs into Tg ( CMV:EGFP-LC3 ) fish to concurrently monitor the autophagic process with EGFP-positive LC3 aggregate formation , in addition to subsequent senescence induction ( Figure 4A , middle and lower panels , and C ) . Upon transient knockdown , although the total EGFP fluorescence became brighter , the number of EGFP-LC3 puncta were only slightly increased by p53 MO , compared with the control injected fish ( Figure 4C , columns 1 and 2 ) . On the one hand , enhanced LC3 puncta induction was observed when both MOs were coinjected , as similarly seen in the case of spns1 MO injection only ( Figure 4C , columns 3 and 4 ) , suggesting that autophagy induction associated with Spns1 depletion does not require p53 . On the other hand , there were more cumulative LysoTracker-positive aggregates ( dysfunctional autolysosomes ) colocalized with LC3 by the double knockdown than spns1 knockdown alone , as EGFP-LC3 and LysoTracker double-positive yellow puncta were obviously increased by the p53 suppression in spns1 morphants ( Figure 4A , middle panels , and C , columns 11 and 12 ) . Moreover , the enhancing effect of p53 knockdown on senescence in spns1 morphants was obviously seen ( Figure 4A , upper panels , and Figure S7 ) . We further generated spns1-mutant fish harboring a p53 mutation ( tp53zdf1/zdf1 ) , spns1hi891/hi891;tp53zdf1/zdf1 , and confirmed that there was no requirement of normal p53 inheritance for the induction of embryonic senescence resulting from Spns1 deficiency , but instead there was an enhancement of SA-β-gal activity caused by the constitutive loss of wild-type p53 ( Figure 4D and E ) . To further obtain robust hallmarks of senescence in zebrafish embryos , we examined the expression of other markers and/or mediators of senescence in spns1-defective animals . Quantitative RT-PCR ( qPCR ) as well as semi-qPCR in individual embryos demonstrated that the expression of p21waf1/cip1 and plasminogen activator inhibitor-1 ( pai-1 ) , which are known downstream targets of the p53 pathway [39] , were upregulated in spns1 morphants and mutants ( Figure 4F , and Figure S13; see also Text S1 and S2 ) . Senescence marker protein-30 ( smp-30 ) was downregulated in spns1-deficient animals compared with the corresponding controls . While the induction of p21waf1/cip1 as well as bax was apparently regulated in a p53-dependent manner , both the pai-1 induction and the smp-30 reduction in spns1 mutants were not influenced by the p53 defect . We extended the analysis by monitoring the conversion of LC3-I into LC3-II among normal wild-type , tp53zdf1/zdf1 , spns1hi891/hi89 , and spns1hi891/hi891;tp53zdf1/zdf1 fish through 4 dpf . Autophagy was minimally induced in tp53zdf1/zdf1 fish based on detection of LC3-II conversion by immunoblotting , while the total amount of LC3 ( LC3-I plus -II ) was increased ( Figure 4G and H ) . In spns1hi891/hi891;tp53zdf1/zdf1 fish , the LC3-II conversion/accumulation was similar to that seen in spns1-mutant fish ( Figure 4G and H ) . These results suggest that either decrease or loss of basal p53 enhances the Spns1 impairment , potentially by augmenting autophagy progression ( but not initiation ) and/or lysosomal biogenesis ( i . e . , subsequent autolysosomal formation and maturation ) . We then proceeded to assess the epistasis among spns1 , beclin 1 and p53 . We first confirmed that Beclin 1 suppression had no significant impact on p53 morphants or tp53zdf1/zdf1 fish ( Figure 4H and I , columns 1 , 3 , 5 , and 7 , and Figure S8 ) . Conversely , p53 depletion prevented the ability of beclin 1 MO to suppress the appearance of the yolk opaqueness and senescence phenotypes of spns1 mutants ( Figure 4H and I , and Figure S8 ) . Moreover , the beclin 1 knockdown significantly suppressed the SA-β-gal activity in spns1hi891/hi891;tp53zdf1/zdf1 fish to a similar extent as seen in standard control MO-injected spns1hi891/hi891;tp53+/+ fish ( Figure 4H and I , columns 2 and 8 , and Figure S8 ) . However , the reduction of the SA-β-gal activity was more obvious in beclin 1 MO-injected spns1hi891/hi891;tp53+/+ fish than in spns1hi891/hi891;tp53zdf1/zdf1 fish ( Figure 4H and I , columns 6 and 8 , and Figure S8 ) . Thus , basal p53 activity has a certain protective role ( s ) in preventing the deleterious phenotypes caused by genetic ablation of the spns1 gene , by competing with Beclin 1-mediated autophagy progression . Although basal p53 can contribute to attenuating the Spns1 deficiency conceivably through suppressing autophagic progression and lysosomal biogenesis , we also wondered whether “activated p53” in response to DNA damage ( e . g . , UV ) has any impact on the Spns1 deficiency , based on the result that the UV irradiation activates and/or enhances autophagy in zebrafish embryos ( Figure S6B ) . As anticipated , apoptosis was similarly induced in spns1 mutants , compared with wild-type animals after UV treatment , whereas such apoptotic induction was almost undetectable under the p53 mutant condition ( Figure S9A; see also Text S1 and S2 ) . The UV exposure apparently augmented both autophagic progress ( i . e . , GFP-LC3 puncta formation ) and lysosomal biogenesis ( i . e . , LysoTracker-stained puncta ) in spns1 mutants only when functional p53 was present ( Figure S9B and C ) . A DNA damage response can be visualized as persistent foci of damaged nuclear DNA and its interacting proteins such as the phosphorylated histone variant , γH2AX [40] . DNA damage induced by UV treatment and the subsequent cell-cycle arrest in S phase were demonstrated by an increase of γH2AX intensity and a decrease of 5-bromo-2-deoxyuridine ( BrdU ) incorporation , respectively ( Figure S10; see also Text S1 and S2 ) . spns1 mutants had a negligible difference in γH2AX levels but had a significant reduction of BrdU incorporation , irrespective of the p53 state ( Figure S10 ) , which is indicative of a slowdown of cell proliferation without apparent DNA damage . The immunostaining of a mitotic marker , phosphorylated histone H3 ( pH 3 ) also showed a significant reduction in tp53+/+-spns1-mutant animals , even without UV treatment . There was a similar tendency of pH 3 reduction in non-irradiated spns1;tp53-double mutants , but it was not statistically significant ( Figure S11 ) . Embryonic SA-β-gal activity was consistently increased by the UV stimulation in both wild-type and spns1-mutant animals in the presence of p53 ( Figure S12 ) . Finally , we extended our analysis to examine the expression profiles of p21waf1/cip1 , pai-1 , and smp-30 as potential markers and/or mediators of senescence in spns1-defective animals ( Figure 4F and Figure S13 ) . beclin 1 morphants did not show any significantly detectable changes in expression of these genes ( Figure S14A ) . Importantly , however , the suppression of beclin 1 significantly counteracted the impact of the spns1 depletion by restoring expression of the pai-1 and smp-30 genes ( Figure S14A ) . As described above , even in the absence of p53 , the altered regulation of these two critical senescence markers was still detectable in spns1-deficient animals ( Figure S14B ) , indicating that p53-independent regulation may be responsible for the expression of these genes . In contrast , the induction of p21waf1/cip1 , bax , and mdm2 genes in the spns1-defective condition was apparently p53 dependent and UV responsive , as confirmed by the level of their expression in p53 mutants ( Figure S14B ) . It is also important to note that expression of ink4ab ( the zebrafish homolog of both p15ink4b and p16ink4a ) was induced by UV treatment but not by Spns1 loss ( Figure S15 ) . Taken together , the upregulation of pai-1 and p21 , and the downregulation of smp-30 in spns1-defective fish embryos are consistent with the induction of senescence characteristics in aging organisms [40] , [41] , [42] , [43] , [44] , [45] . Chemical genetic approaches are emerging in the zebrafish model system , and increasing numbers of chemical compounds are currently available for examining autophagic regulation [46] , [47] , [48] . We determined the effects of several chemical compounds and selective modulators of autophagy on Spns1 deficiency to see if any chemical ( s ) ameliorates or exacerbates the Spns1 phenotypes of zebrafish embryos . Of the chemicals tested , bafilomycin A1 ( BafA ) and other proton pump inhibitors ( PPIs ) such as the acid reducer omeprazole stood out due to their apparent inhibitory effect on overall phenotypic deterioration in spns1 animals ( Figure 5A , B and Figure S16 ) . BafA is a specific inhibitor of vacuolar-type H+-ATPase ( v-ATPase ) , and inhibits lysosomal acidification , slowing or blocking degradation of LC3-II within autolysosomes as well as inhibiting the fusion between autophagosomes and lysosomes [49] , [50] , and subsequently it also enhances EGFP-LC3 puncta accumulation corresponding to mammalian autophagosomes [27] . Consistently , we found that BafA significantly increased the formation of cellular LC3 puncta as well as their gross EGFP intensity in wild-type zebrafish ( Figure 5C–F ) . Intriguingly , both the progression of yolk opacity and SA-β-gal activity in spns1 mutants during the time period of 36–60 hpf were entirely suppressed by BafA treatment ( Figure 5A and B ) . While EGFP-LC3 puncta signals in BafA-treated spns1 mutants did not appear significantly different compared with those in untreated counterparts , LysoTracker-positive compartments in cells were reduced by BafA treatment ( Figure 5E and F ) , similar to the result seen with whole animal staining ( Figure 5C and D ) . This is likely due to ‘prior’ alkalinization in lysosomes/autolysosomes and reduction of their biogenesis ( Figure 5E and F ) . Importantly , these effects of BafA on spns1-mutant animals were essentially unaltered under the p53-depleted condition . Thus , BafA-induced pre-alkalinization might compensate for vulnerability of the spns1 mutants lacking basal p53 activity ( Figure 5A ) . BafA specifically binds to subunit c of the v-ATPase and thereby inhibits its enzymatic and proton-pump activity , but it has been shown that the concentration used and the duration of treatment with this drug are fairly critical to observe this effect [49] . In addition , BafA may have other off-target effects [51] . Therefore , we specifically knocked down the v-ATPase subunit gene atp6v0c by using a MO , whose effectiveness had already been demonstrated [52] . We obtained comparably consistent outcomes for the ameliorative effect of atp6v0c knockdown on the Spns1 deficiency ( Figure S17A and B ) . In addition , we found that three other PPIs ( omeprazole , lansoprazole , and pantoprazole ) , which can all interfere with the v-ATPase [53] , [54] , could also suppress the senescence phenotype in spns1 mutants ( Figure S17C ) . We further utilized LysoSensor dye to monitor acidification levels in lysosomes and autolysosomes , to verify that possible pre-alkalinization by BafA treatment or direct atp6v0c knockdown can efficiently suppress the spns1-mutant phenotypes . In contrast to the LysoTracker probes , which exhibit fluorescence that is largely independent of the pH level , the LysoSensor reagents can show a pH-dependent increase in fluorescence intensity upon acidification [55] . The neutral pH-sensitive LysoSensor 153 fluoresces optimally at pH 7 . 5 , while the acidic pH-sensitive LysoSensor 189 fluoresces optimally at pH 5 . 2 . When these probes ( green ) were used in combination with LysoTracker ( red ) , we found a much stronger signal with LysoSensor 153 than with LysoSensor 189 in spns1-mutant animals ( Figure S18A and B ) , which was also quite obvious at the cellular level ( Figure 5G and H ) . By contrast , treatment of wild-type animals with lysosomal protease inhibitors , pepstatin A and E-64-d , which allows the retention of intact autolysosomal/lysosomal acidity while preventing autolysosomal maturation and turnover , showed highly acidic vesicles stained by LysoSensor 189 , rather than by LysoSensor 153 ( Figure 5G and H ) . Lysosomal compartments in spns1 mutants may still retain some weak acidification allowing lysosomal biogenesis and subsequent autophagosome-lysosome fusion , as short-term treatment ( for 1 h ) with BafA can completely abolish the acidic compartments stained by LysoSensor and significantly reduce the LysoTracker-positive signals ( Figure S18C and D ) . Finally , we examined the colocalization of EGFP-LC3 puncta and lysosomes in wild-type fish in the presence of BafA or pepstatin A and E-64-d , compared to that in the spns1hi891/hi891 fish ( Figure S19A and B ) . In wild-type animals , BafA caused the accumulation of EGFP-LC3 and colocalization of EGFP-LC3-mCherry-LC3 signals ( Figure S19C ) , but no accumulation of LysoTracker , indicating a block in fusion of autophagosomes with lysosomes ( Figure S19B ) . Inhibition of lysosomal hydrolase activity with pepstatin A and E-64-d resulted in accumulation of lysosomes ( red ) and autolysosomes ( yellow by overlapping EGFP-LC3 and LysoTracker ) ( Figure S19B ) . In contrast , the spns1hi891/hi891 fish ( Figure S19A ) and their cells ( Figure S19B and C ) displayed both an accumulation of autolysosomes ( yellow by overlapping EGFP-LC3 and LysoTracker ) and autophagosomes ( yellow by overlapping of EGFP-LC3 and mCherry-LC3 ) without any inhibitors , again indicating defects in both fusion of autophagosomes with lysosomes and autolysosomal maturation . Collectively , these results demonstrate that the appearance of deleterious changes in spns1 animals is due to aberrant autophagic progression caused by impaired suboptimal acidification in malformed autolysosomes , and that p53 may also be involved in the process of both lysosomal and autolysosomal pathogenesis in Spin1 deficiency .
We demonstrated that loss of Spns1 leads to defects in autophagic and lysosomal homeostasis in zebrafish , and the tumor suppressors Beclin 1 and p53 are differentially involved in autophagy and senescence pathways regulated by Spns1 . A reduction of Beclin 1 as an autophagy regulator can attenuate the Spns1 defect , whereas a decrease/loss of basal p53 activity , as well as activated p53 by DNA damage , augments it and exacerbates the deleterious phenotype in zebrafish . If both Spns1 and p53 were abrogated , the Beclin 1 reduction was no longer effective in suppressing the spns1-mutant phenotypes sufficiently , whereas v-ATPase reduction was robust enough to suppress the phenotypes regardless of p53 state . Importantly , we have successfully generated valuable zebrafish tools by crossing the fluorescent protein-tagged LC3- and GABARAP-transgenic lines with the spns1-mutant line to monitor real-time alterations of autophagic abnormalities in vivo . Vertebrates have approximately seven Atg8 homologs [56] , and the best studied of these is LC3 . GABARAP shows many similarities with LC3 , but its conjugation is only mildly affected by starvation , and under certain conditions conjugation may be activated independent of target of rapamycin ( TOR ) inactivation [57] , [58] . We have found , however , an indistinguishable behavior between LC3 and GABARAP in the transgenic animals harboring either spns1 mutation or depletion , although it has been suggested that LC3 and GABARAP differentially act in autophagosome biogenesis [59] . The evolutionarily conserved autophagy gene beclin 1 ( vps30/atg6 ) is frequently inactivated at one locus in several cancers [60] , [61] . Studies in mice have also demonstrated that beclin 1 is a haploinsufficient tumor suppressor [17] , [62] . It has been demonstrated that Spns1-loss-associated EGFP-LC3 puncta accumulation in cells , which reflects autophagic progression by autophagosome formation , is suppressed by the depletion of Beclin 1 , Atg7 , or Ulk1 , as well as by treatment with a PtdIns3K inhibitor , 3-methyladenine [16] . Consistently , we also demonstrated that beclin 1 morphants were resistant to forming LC3 puncta induced by Spns1 deficiency in zebrafish . However , once both spns1 and p53 were depleted , the beclin 1 knockdown was no longer effective enough to suppress the punctate accumulation of LC3 as well as the mutant hallmarks of both yolk opaqueness and embryonic senescence characteristic of Spns1 deficiency in zebrafish . p53 is one of the most commonly mutated tumor suppressor genes found in many types of human cancers [63] . We found that the loss of basal p53 compromises the ability to properly adjust autolysosomal formation , and exacerbated the spns1 deficiency , while beclin 1 knockdown can ameliorate it by suppressing the early stage of autophagy . p53 has been linked to the regulation of autophagy , but the exact nature of its role still remains controversial . On the one hand , onocogenic and genotoxic stress events result in p53 stabilization and activation , which can stimulate autophagy through both transcription-independent mechanisms ( e . g . , AMP-activated protein kinase; AMPK activation and TOR inhibition ) and transcription-dependent mechanisms ( e . g . , transcriptional upregulations of PTEN , tuberous sclerosis complex 1/TSC1 and damage-regulated autophagy modulator/DRAM1 ) [64] . On the other hand , it has been reported that genetic or chemical inhibition of basal cytoplasmic p53 , or proteasomal depletion of p53 during starvation and/or endoplasmic reticulum stress , activates autophagy through transcription-independent mechanisms involving AMPK activation and TOR inhibition [20] . Loss of p53 may lead to homeostatic imbalance in cells , such as induction of bioenergetic compromise , increased ROS , and/or defective cell-cycle checkpoints , which can lead to autophagy induction . Thus , p53 depletion may promote or enhance autophagy indirectly as a result of imbalanced metabolic stress conditions . This therefore suggests that p53 maintains cellular homeostasis by adjusting the rate of autophagy in a context-dependent manner , as circumstances require . Intriguingly , Spns1-loss-induced embryonic senescence ( SLIES ) represents an atypical senescence response that is distinct from p53-induced senescence and can be suppressed by autophagy inhibition mediated through beclin 1 knockdown ( Figure 6 ) . Since the Beclin 1 suppression may lead to reduction in the level of p53 [37] , and then might subsequently prevent SLIES , we intensively examined the effect of p53 depletion on SLIES . To our initial surprise , SLIES cannot be suppressed by the loss of p53 at all , but is rather enhanced . This seems to contradict the conventional role of p53 as an inducer of cellular senescence in various contexts including the zebrafish model [33] , [65] . However , given recent evidence of a certain anti-aging mechanism by p53 in mice and p53-mediated suppression of senescence in cells [66] , [67] , it might not be surprising that p53 can also act both as a suppressor of senescence and of autophagy in some contexts , although the exact molecular mechanism remains elusive at this point . In addition , there remains a p53-independent cellular senescence mechanism that still depends on its authentic downstream target , p21Waf1/Cip1/Cdkn1a , among others , such as Arf and p27Kip1/Cdkn1b triggered by Skp2 inactivation [68] . Moreover , a recent report indicated that p21Waf1/Cip1/Cdkn1a also has a tissue-selective and context-dependent modulation of senescence in BubR1 progeroid mice [69] . In addition , most recently , SA-β-gal-positive “developmental senescence” observed in mice , which shares some , but not all , regulatory pathways detectable in adults , was shown to involve the activation of p21Waf1/Cip1/Cdkn1a in the absence of a DNA damage response and any alteration in p53 , p16Ink4a , or p19Arf [70] , [71] . Interestingly , we found that in spns1-deficient fish embryos , the upregulation of p21 and pai-1 expression and the downregulation of smp-30 expression were detected without a DNA damage response . Further investigation and elucidation of their functional roles as senescence mediators or attenuators will be required to determine how they are responsible for SLIES . p53 is also well known for its pro-apoptotic cell death-inducing activities , but it can conversely possess pro-survival effects , particularly under mild stress conditions [72] , [73] , [74] . In zebrafish embryos , however , we determined that SLIES occurs regardless of p53-mediated impacts on apoptotic cell death and/or the cell-cycle checkpoint response as well . Thus , spns1-mutant animals show a new type of developmental senescence that can be triggered by autophagic initiation followed by autolysosomal fusion in the absence of the authentic senescence moderator p53 , while basal p53 and activated p53 can play contrasting roles; attenuation in SLIES and mediation in apoptosis , respectively . “Activated p53” is not specifically involved in the spns1-ablated condition but can generally induce and/or augment the deleterious condition caused by the DNA damage response and apoptosis . In contrast , “basal p53” may have an antagonistic effect on lysosomal biogenesis ( or autolysosomal maturation ) rather than on the autophagic progress in the absence of Spns1 . Alternatively , the p53 status may rather influence endosomal-lysosomal homeostasis where Spns1 is primarily involved . It should be noted that p53 may be involved in lysosomal stabilization [75] , as well as in various metabolic changes and the regulation of energy metabolism including aerobic glycolysis ( the Warburg effect ) in which the lysosome is also engaged for degradation [38] . Our preliminary observation suggests that SLIES and the yolk opaqueness hallmarks of spns1 embryos are only mildly affected by chemical ( e . g . , rapamycin ) -mediated autophagy induction . This may be a reflection of the consistent outcome of already attenuated TOR ( re ) activation due to impaired autophagic lysosome reformation by Spns1 deficiency , as has been demonstrated in mammalian cells and flies [16] , [76] . We are also wondering if basal p53 depletion may have any effect on autophagy enhancing activity independent of or different from the rapamycin-sensitive TOR pathway . Of note , rather than simple depletion of wild-type p53 , the p53 mutant ( tp53zdf1/zdf1 ) fish used here retain an accumulation of the mutant p53 protein ( p53M214K ) [77] , which corresponds to the human p53M246K mutant protein whose function is completely abolished [78] . A recent study suggests that this mutant p53 protein is degraded through chaperone-mediated autophagy ( CMA ) in a lysosome-dependent fashion [79] . Thus , the regulation of the stability of mutant p53 differs from that of wild-type p53 . There is a possibility of activating the CMA pathway by inhibiting ( macro ) autophagy , to specifically promote the degradation of mutant p53 , under a nutrient-starved condition . Therefore , it is also important to examine any involvement of the Spns1 function in the protein stability of mutant p53 , whether the Spns1 defect selectively activates the CMA pathway for the removal of mutant p53 or not . Altogether , our present results support the notion that the interruption of the intrinsic nutrient supply through autophagy , supposedly from yolk in zebrafish embryos and larvae [80] , may lead to profound energetic exhaustion under the aberrant autolysosomal condition resulting from Spns1 deficiency , and this effect is dependent on the p53 state . Since BafA can inhibit the import of H+ through the v-ATPase into the lysosome lumen , while the Spns1 defect presumably prohibits the symport of H+/sugar by loss of its function , it was anticipated that BafA might at least temporarily rescue the spns1-mutant animals , by restoring the balanced acidity condition of autolysosomes and/or lysosomes , as well as subsequent autophagosome-lysosome fusion . In fact , we found that BafA effectively inhibited the progression of both yolk opacity and embryonic senescence that appeared in spns1 mutants . Moreover , a direct depletion of the v-ATPase subunit c ( a direct target of BafA ) by MO recapitulated the restorative effect on the mutant animals . Importantly , the lysosomal pH of spns1 mutants was found to be less acidic , suggesting that protons may pass through the membrane via other H+-coupled transporters and/or channels such as lysosomal amino acid transporter 1 ( LYAAT-1/SLC36A1 ) [81] , chloride channel 7 ( CLCN7 ) [82] , and cystic fibrosis transmembrane conductance regulator ( CFTR ) [83] . It should be noted that SA-β-gal is acid β-D-galactosidase , a lysosomal glycoside hydrolase ( glycosidase ) , which catalyses the hydrolysis of β-galactosides into monosaccharides [28] , and its substrates also include various glycoproteins , gangliosides ( glycosphingolipids ) , lactose , and lactosylceramidases [84] , [85] . The aberrant increase of the in situ SA-β-gal activity induced by Spns1 deficiency indicates that such a glycosidase product itself can be preserved in autolysosomes and/or lysosomes , but may not function properly in vivo without an essential permease ( s ) to transport degradation products that need to be delivered into the cytoplasm as energy sources . The extent to which our current observations of Spns1 functions during early development pertain to actual aging and age-related disease situations remains to be rigorously determined under both physiological and pathological conditions in animals . However , an increase in the abundance of the lysosomal hydrolases is presumably linked to the increased lysosomal biogenesis observed in senescent cells . Indeed , cumulative evidence suggests that an increased number of lysosomes and elevated lysosomal activity have been associated with replicative senescence [85] . Thus , the current finding suggests that temporal suppression of autophagy through Beclin 1 and/or v-ATPase by approved therapeutics ( e . g . , omeprazole ) may be an effective therapeutic approach in the prevention of autophagic impairments similar to the Spns1 deficiency ( Figure 6 ) . Similar intervention has been demonstrated successfully in a mouse model of Pompe disease , a lysosomal glycogen storage disorder [86] .
Zebrafish ( AB and casper strains ) were maintained under a 14:10 h light/dark cycle and fed living brine shrimp twice daily . Brine shrimp were presented using 1 mL pipettes ( about 0 . 75 mL brine shrimp per 20 fish ) . Flake food was also given every other day in proportion to the number of fish in the tanks . A continuously cycling aquarium system was used to maintain water quality ( Aquatic Habitats Inc . ) . Zebrafish embryos were collected from pairwise matings of adults and raised at 28 . 5°C . The embryos to be used in the experiments were then staged by hours post fertilization ( hpf ) at 28 . 5°C and also by morphological appearance for experiments [87] . All animal experiments were approved by and conducted in accordance with the guidelines established by the Institutional Animal Care and Use Committee ( IACUC ) at The Scripps Research Institute , IACUC approval number 09-0009 . Zebrafish embryos ( in the case of the AB fish line ) were transferred into 0 . 003% ( w/v ) 1-phenyl-2-thiourea ( PTU ) prior to 24 hpf to prevent pigmentation . Embryos or larvae were then mounted live in water containing 0 . 16 mg/ml tricaine ( Sigma , A5040 ) for imaging . Images were taken using the FluoView 1000 confocal laser scanning microscope system ( Olympus ) with a 60× objective lens ) . Since EGFP- or mCherry-LC3 and EGFP-GABARAP showed both a uniform cytosolic signal and more intense spots , threshold values were set to reduce the cytosolic signal and identify the more intense dots . The same threshold value was applied for all samples in the indicated experiments . The extent of colocalization between LysoTracker and LysoSensor signals and EGFP- or mCherry-LC3 and EGFP-GABARAP dots was quantified in three independent visual fields from three independent embryos . All values are represented as mean ± standard deviation ( S . D . ) . Mounted animals were photographed using each specific fluorescent signal by confocal laser microscopy . Fluorescence intensities were quantified using Adobe Photoshop over a color range that was chosen according to 25 additive color selections of regions that showed visually positive signals . For analyses of cells within the zebrafish embryos , these regions were selected in each actual embryo only and not in the yolk . Following pixel selection , a fuzziness setting of 64 was used , and the chosen pixel number was determined using the image histogram calculation . Morpholino oligonucleotides ( MOs ) were designed and synthesized by Gene Tools , LLC ( Philomath , OR ) . The sequence of the beclin 1 MO is 5′-CATCCTGCAAAACACAAATGGCTTA-3′ , which overlaps the intron-exon boundary at the 5′-splice junction of exon 4 in the zebrafish beclin 1 gene . The sequence of the standard control MO is 5′-CCTCTTACCTCAGTTACAATTTATA-3′ . MOs were resuspended in sterile water at a concentration of 1 mM as stock solutions . For microinjection into embryos , the stock solutions ( 1 mM ) were diluted to 125 , 250 , 500 , and 750 µM . A 10 nl volume of each MO solution was injected into the yolk during the one-cell stage . All other MO sequences have been reported previously [8] , [12] , [52] , [88] , except Inverse-sequence p53 MO ( inv . p53 MO ) ; 5′-GTTAAGAACGTTTCGTTACCGCG3′ . The vital mitochondrial and lysosomal dyes MitoTracker Green FM ( Invitrogen; molecular probes , M7514 ) , LysoTracker Red DND-99 ( Invitrogen; molecular probes , L7528 ) , LysoSensor Green DND-189 ( Invitrogen; molecular probes , L7535 ) and LysoSensor Green DND-153 ( Invitrogen; molecular probes , L7534 ) were diluted to final concentrations of 1 µM , 10 µM , 1 µM and 1 µM , respectively , in E3 medium ( 5 mM NaCl , 0 . 17 mM KCl , 0 . 33 mM CaCl2 , 0 . 33 mM MgSO4 ) , and pre-warmed to 28 . 5°C . Each dye was then added to an equal volume of fresh water on embryos and incubated at 28 . 5°C in the dark for 30 min to 1 h . Embryos were then rinsed four times in fresh E3 medium before imaging . DQ Red BSA ( Invitrogen; molecular probes , D12050 ) was diluted to a final concentration of 0 . 5 mg/ml in E3 medium , directly injected into the yolk sac at 72–84 hpf , and subjected animals were incubated for 4 h prior to observation by microscopy . Zebrafish larvae were fixed in 4% paraformaldehyde , 2 . 5% glutaraldehyde , 0 . 02% picric acid , 0 . 1 M Na cacodylate buffer , washed and fixed in 1% osmium tetroxide in 0 . 1 M Na cacodylate buffer . They were subsequently treated with 0 . 5% tannic acid followed by 1% sodium sulfate . The pellets were treated with propylene oxide and embedded in Epon/Araldite . Thin sections ( 70 nm ) of the pelleted samples were cut on a Reichert Ultracut E ( Leica , Deerfield , IL ) using a diamond knife ( Diatome , Electron Microscopy Sciences , Hatfield , PA ) , mounted on parlodion-coated copper slot grids and stained in uranyl acetate and lead citrate . Sections were examined on a Philips CM100 transmission electron microscope ( FEI , Hillsbrough , OR ) . Images were documented and measurements were taken using a Megaview III CCD camera ( Olympus Soft Imaging Solutions , Lakewood CO ) . Transverse sections were obtained through the trunk muscle region , the yolk and the eye region . RT-PCR analysis of a single zebrafish embryo was performed to determine the effects of the splice-block MO for the zebrafish beclin 1 gene . Total RNA was extracted from 24–48 hpf embryos injected with control MO , beclin 1 MO , or beclin 1 plus spns1 MO , using TRIzol reagent according to the manufacturer's protocol ( Invitrogen ) . cDNA was synthesized using M-MLV reverse transcriptase ( Promega ) , followed by PCR with ExTaq ( Takara ) . For semi-quantitative analysis , the linear amplification ranges were then determined for each of the primer sets . PCR primers used to amplify the fragments of the zebrafish beclin 1 gene were designed using a web-based primer design tool , PrimerQuest ( Integrated DNA Technology , Inc . ) ( zbeclin 1 EX3 forward primer; 5′-CAAACAAGATGGCGTGGCTCGAAA-3′ , zbeclin 1 EX4 forward primer; 5′-GTGGAACTATGGAGAACTTGAGTCGCA-3′ , and zbeclin1 EX7 reverse primer; 5′-TCCAACTCCAGCTGCTGTCTCTT-3′ ) . The amplified products were validated by sequencing . As controls for these PCR analyses , ef1α and β-actin were examined . The forward and reverse primers used to amplify ef1α were 5′-ACCACCGGCCATCTGATCTACAAA-3′ and 5′-ACGGATGTCCTT GACAGACACGTT-3′ , respectively , and for β-actin were 5′-CCCAGACATCAGGGAGTGAT-3′ and 5′-CACCGATCCAGACGGAGTAT-3′ , respectively . For amplification by PCR , the initial denaturing step at 94°C for 5 min was followed by 18–25 amplification cycles of 30 sec at 94°C; 30 sec at 60°C; 60 sec at 72°C , and a final extension period of 10 min at 72°C . Amplified products were separated on a 1 . 5% agarose gel stained with ethidium bromide and the bands were visualized and recorded using a Multi Image Light Cabinet ( Cell Bioscience ) . Other PCR primers , parameters and conditions are summarized in Supplemental Table S1 and S2 . Zebrafish embryos and larvae at 48–72 dpf were washed three times in phosphate buffered saline ( PBS ) and fixed overnight in 4% paraformaldehyde with PBS at 4°C . After fixation , the samples were washed three times in PBS , pH 7 . 5 , twice again in PBS , pH 6 . 0 at 4°C , and then incubated at 37°C ( in the absence of CO2 ) for 12–16 h with SA-β-gal staining solution ( 5 mM potassium ferricyanide , 5 mM potassium ferrocyanide , 2 mM MgCl2 in PBS at pH 6 . 0 ) . All animals were photographed under the same conditions using reflected light with a macro microscope , AZ100 ( Nikon ) . SA-β-gal activity in each animal was quantified using a selection tool in Adobe Photoshop software for a color range that was chosen using 25 additive color selections of regions that showed visual SA-β-gal staining . For analyses of embryos , these regions were selected in each embryo proper only and not in the yolk in order to exclude variability in the initial yolk volume and yolk consumption levels over time . Since the yolk stains much more intense for SA-β-gal at all stages of development than any other embryonic tissues in general , it was desirable to eliminate this as a source of variability . Following pixel selection , a fuzziness setting of 14 was used , and the chosen pixel number was determined using the image histogram calculation . Embryos were dechorionated , deyolked and homogenized in RIPA buffer . Protein concentrations of embryo lysates were determined using the bicinchoninic acid ( BCA ) protein assay . The lysates were mixed with equal volumes of 2× SDS sample buffer , heated at 95°C for 2 min , and resolved on 12 . 5% or 15% gels . After transfer , the polyvinylidene difluoride membranes were incubated with primary antibodies [anti-LC3A/B ( Cell Signaling Technology , Inc . , #4108 ) , anti-β-actin ( Cell Signaling Technology , #4967 ) , or anti-GFP ( Life Technologies , A11122 ) antibody] , diluted in TBST overnight at 4°C . After washing , the blot was then incubated with a secondary anti-rabbit horseradish peroxidase-conjugated antibody ( Cell Signaling Technology , #7074 ) at room temperature for 1 h and visualized using an ECL kit ( Perkin Elmer ) in accordance with the manufacturer's instructions . To generate transgenic zebrafish expressing mCherry-tagged LC3 , the corresponding expression construct pminiTol2-mCherry-LC3 was generated using the QuikChange Site-Directed Mutagenesis Kit ( Stratagene ) in accordance with the manufacturer's instructions . pT3TS-Tol2 was linearized by XbaI and transcribed with T3 RNA polymerase using the Ambion mMESSAGE mMACHINE kit ( Ambion , AM1348 ) to produce Tol2 transposase mRNA . Approximately 5 nl of the mixture of plasmid DNA ( 100 ng/µl ) ( pminiTol2-mCherry-LC3 ) and 50 pg of Tol2 transposase mRNA ( 100 ng/µl ) were coinjected into newly fertilized embryos at the one-cell stage to produce transgenic fish . Injected embryos were raised to adulthood and out-crossed to wild-type fish to identify germline-transmitted transgenic founders ( F0 ) as described previously [22] . Positive founders were determined by screening F1 embryos for visible mCherry expression . The mCherry-positive offspring were then allowed to grow to maturity for further experiments . Bafilomycin A1 ( BafA ) ( LC Laboratories , B-1080 ) , omeprazole , lansoprazole , and pantoprazole ( Sigma , O104 , L8533 , and P0021 , respectively ) treatment was performed from 36 through 48 hpf or 48 through 60 hpf in E3 medium at 28 . 5°C in 12- or 6-well plates . The chemicals dissolved in DMSO were added to the embryo water ( E3 medium ) at the final concentrations of 200 nM for BafA and 25 µM for lansoprazole , omeprazole and pantoprazole . Pepstatin A ( Fisher BioReagent , BP26715 ) and E-64-d ( Enzo Life Sciences , BML-PI107 ) treatment was administrated from 60 through 72 hpf for 12 h in E3 medium at 28 . 5°C in 12- or 6-well plates . These reagents were both dissolved in DMSO and added to the embryo water ( E3 medium ) at the final concentration of 5 µg/ml . Data processing and statistical analyses were performed using Statistical Package for the Social Sciences ( SPSS ) version 14 . 0 . This software was used to generate each of the graphs shown in the text to perform statistical tests where appropriate .
|
Spinster homolog 1 ( Spns1 ) in vertebrates , as well as Spinster ( Spin ) in Drosophila , is a hypothetical lysosomal H+-carbohydrate transporter , which functions at a late stage of autophagy . The Spin/Spns1 defect induces aberrant autolysosome formation that leads to embryonic senescence and accelerated aging symptoms , while the molecular mechanisms of the pathogenesis are unknown in vivo . Using zebrafish , we show that Beclin 1 suppression ameliorates Spns1 loss-mediated senescence as well as autolysosomal impairment , whereas p53 deficit unexpectedly exacerbates these characteristics . We demonstrate that basal p53 activity has a certain protective role ( s ) against the Spns1 defect via suppressing autophagosome-lysosome fusion , while p53 activated by ultraviolet radiation amplifies the Spns1 deficit . In addition , we found that excessive lysosomal biogenesis and prolonged suboptimal acidification , modulated by v-ATPase , could be the primary reason for the appearance on the hallmarks of Spns1 deficiency . Our findings thus suggest that Spns1 is critically involved in lysosomal acidification and trafficking during autophagy , and differentially acts in a pathway with Beclin 1 and p53 in the regulation of senescence .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology",
"and",
"life",
"sciences",
"medicine",
"and",
"health",
"sciences"
] |
2014
|
Aberrant Autolysosomal Regulation Is Linked to The Induction of Embryonic Senescence: Differential Roles of Beclin 1 and p53 in Vertebrate Spns1 Deficiency
|
Adaptation is likely to be an important determinant of the success of many pathogens , for example when colonizing a new host species , when challenged by antibiotic treatment , or in governing the establishment and progress of long-term chronic infection . Yet , the genomic basis of adaptation is poorly understood in general , and for pathogens in particular . We investigated the genetics of adaptation to cystic fibrosis-like culture conditions in the presence and absence of fluoroquinolone antibiotics using the opportunistic pathogen Pseudomonas aeruginosa . Whole-genome sequencing of experimentally evolved isolates revealed parallel evolution at a handful of known antibiotic resistance genes . While the level of antibiotic resistance was largely determined by these known resistance genes , the costs of resistance were instead attributable to a number of mutations that were specific to individual experimental isolates . Notably , stereotypical quinolone resistance mutations in DNA gyrase often co-occurred with other mutations that , together , conferred high levels of resistance but no consistent cost of resistance . This result may explain why these mutations are so prevalent in clinical quinolone-resistant isolates . In addition , genes involved in cyclic-di-GMP signalling were repeatedly mutated in populations evolved in viscous culture media , suggesting a shared mechanism of adaptation to this CF–like growth environment . Experimental evolutionary approaches to understanding pathogen adaptation should provide an important complement to studies of the evolution of clinical isolates .
In the mid-1800's , Louis Pasteur advised microbiologists to think of the human body as a “culture vessel” for microbes , in the context of understanding immunity [1] . Pasteur's approach has been revised and updated several times [2] , [3] , with a recent review encouraging researchers to be attentive to the effects of different in vivo carbon sources on bacterial metabolism and physiology [2] . Pasteur's advice is particularly relevant for an understanding of the evolution of disease-causing microbes . Natural selection may be imposed by the particular nutritional and metabolic resources available in a given tissue , the innate and adaptive immune systems , and , in the past 80 or so years , by antibiotics or anti-virals . Many pathogens – particularly opportunistic pathogens , emerging pathogens , and microbes causing chronic disease – are faced with a novel and hostile growth environment to which they must adapt or face extinction . Colonization and establishment of an infection in a new host or host species can thus be interpreted as a specific instance of a more general process of adaptation to a novel environment . Understanding adaptive processes in pathogen populations , and in particular characterizing the variety of genetic routes to adaptation , is important for developing effective treatment strategies . Take as an example the management of antibiotic resistance . Resistance is often thought to be costly , in the sense that resistant strains should be less fit than susceptible strains in the absence of antibiotic . If so , then attempts to reduce the frequency of resistance in patient populations by stopping the use of an antibiotic should afford sensitive strains an advantage , and so prolong the utility of an antibiotic for treatment . Antibiotic cessation has met with mixed success ( e . g . , [4]–[6] ) , however , either because some resistance mutations actually pay little or no cost , or because second site mutations that restore fitness without compromising resistance are common . The management of antibiotic resistance in patient populations depends crucially on which of these two mechanisms is more often responsible for the persistence of resistance . The last 15 years have seen a number of studies of in vivo genome evolution in select pathogens , primarily viruses ( e . g . , [7] , [8] ) and bacteria ( e . g . , [9] , [10] ) , that shed vital insight onto the genetic changes that occur during epidemics or chronic infections . The importance of these changes for pathogen fitness in a host can be difficult to ascertain , however , because it is rarely possible to establish with certainty that the observed mutations are adaptive , since some neutral or deleterious mutations may accumulate through drift or by hitchhiking with adaptive mutations . Moreover , it can be difficult to obtain sufficient in vivo samples to ask questions about the repeatability of in vivo evolution – that is , how often pathogens take the same adaptive routes in independent patients or populations . For these reasons we have turned to a complementary approach , laboratory selection experiments , to provide an understanding of the broad patterns and principles of pathogen evolution . In a typical microbial experimental evolution protocol , many populations are founded from a single genotype , and are propagated serially or in a chemostat for tens , hundreds , or thousands of generations ( reviewed in [11] ) . By maintaining multiple replicate populations in each of two or more environments ( e . g . , antibiotic treated vs . not antibiotic treated ) , the effects of a treatment can be systematically investigated in a manner that is often inaccessible with in vivo samples . Experimental evolution has by now a rich history in studying basic evolutionary processes ( e . g . , [11]–[14] for reviews ) , as well as more applied topics such as the evolution of antibiotic resistance [15] , [16] and of virulence [7] . In addition , experimental evolution has significant potential as an investigative tool for elucidating basic biological processes [17] , [18] . With the development of technologies that allow the rapid and affordable sequencing of entire bacterial genomes , an increasing number of studies have sought to describe the genomic basis of laboratory adaptation ( reviewed in [19] ) . Here we use a combination of experimental evolution and whole-genome sequencing ( WGS ) to investigate the initial stages of pathogen adaptation using the bacterium Pseudomonas aeruginosa . This gram-negative bacterium is widely distributed in nature [20] , and is an important opportunistic pathogen . P . aeruginosa can cause acute infections of wounds , burns and of lungs , and is frequently implicated in nosocomial infections . Moreover , P . aeruginosa is an important pathogen of individuals with cystic fibrosis ( CF ) , with approximately 60–70% of Canadian adults with CF harbouring this bacterium [21] . P . aeruginosa chronically infects the CF lung , and once the infection is established , it is virtually impossible to eradicate: Intensive antibiotic regimens are effective at reducing symptoms , but almost never succeed in clearing the infection entirely . P . aeruginosa populations that have persisted for long periods of time in the lungs of individuals with CF show characteristic signatures of adaptation to this novel culture environment . Recent studies have documented patterns of parallel evolution at the level of phenotype , gene expression , and genotype [10] , [22]–[25] , indicating repeatable patterns of long-term adaptation to the CF lung . For example , CF lung sputum is highly viscous , and P . aeruginosa typically grows as an unattached biofilm , or microcolony , in this environment [26] . While environmental isolates of P . aeruginosa are motile , long-term CF colonists show evidence of adaptation to the sessile lifestyle of the microcolony , including reduced motility , and a morphological shift to small colony variants ( SCVs ) on agar plates [27] , [28] . Increased intracellular levels of cyclic di-GMP are thought to be important for this adaptive shift [27]–[29] , but the causative mutations have yet to be fully elucidated . Other characteristic changes include mutations associated with reduced virulence , presumably to avoid detection by the host immune system , and increased small molecule efflux that can afford resistance to antibiotics commonly used with CF patients [10] . Given evidence of long-term adaptation during chronic infection in P . aeruginosa , we have examined the genomic basis of adaptation to CF-like culture conditions and to fluoroquinolone antibiotics through WGS of experimentally evolved P . aeruginosa isolates . Our primary aim is to describe the genetic changes underlying adaptation to this novel environment , and to ask how repeatable these changes are . In addition , we also investigate the genetic architecture of the costs of resistance: When antibiotic resistance evolves , how often is it costly , and what mutations underlie those costs ? Our data allow us to quantify the nature and extent of parallel genomic evolution and , in so doing , provide a unique view of the variety of genetic routes taken during adaptation to a medically relevant novel environment .
In our selection experiment , we manipulated the bacterial growth environment so as to resemble the CF lung with respect to nutrition , viscosity , and antibiotic treatment . Populations of P . aeruginosa were evolved in synthetic cystic fibrosis sputum ( scfm; [30] ) for 8 days in the presence or absence of ciprofloxacin ( Cip ) and/or mucin . Scfm is a defined medium resembling the nutritional environment of the CF lung [30] . Ciprofloxacin was added at a concentration comparable to that found in the sputum of CF patients ( 1 ug/ml; [31] ) . Mucin increases the viscosity of the culture medium , and is meant to mimic the high viscosity of CF sputum [32] , [33] . In vivo , viscous sputum is thought to support the growth of P . aeruginosa in unattached biofilms , called microcolonies [26] , [34] , and similar structures have been observed in mucin-supplemented media ( e . g . , [32] , [33] ) . Mucin was added at 10 g/L . Mucin may also act as a source of nutrients . The selection experiment comprised a fully factorial design giving four selection environments: scfm alone , scfm+Cip , scfm+mucin , and scfm+mucin+Cip; 12 replicate populations were propagated in each environment . Populations were maintained in a 37°C shaking incubator in 1 . 5 ml of medium , with serial transfer at a 1∶61 dilution every 24 hours , with approximately 5 . 9 generations of growth per day ( 47 . 5 generations in total ) . Since the CF lung – and by extension laboratory media designed to mimic aspects of the CF lung – is a unique growth environment for bacteria , our evolved P . aeruginosa populations are expected to adapt to this novel habitat . Adaptation is also expected to occur in response to ciprofloxacin through the selection of mutations conferring resistance . Our experimental design allows us to disentangle these two effects , with fitness in the absence of antibiotic serving as a measure of adaptation to the growth medium , and changes in resistance to ciprofloxacin indicating adaptation to the presence of this antibiotic . Since populations may harbour extensive genetic and phenotypic variation , we measured resistance and fitness for evolved populations , as well as for a single genotype isolated from each population . As expected , antibiotic resistance evolved in the presence of ciprofloxacin at both the population and genotype levels ( Figure 1 ) . Populations evolved in the presence of Cip showed a 32-fold to 192-fold increase in minimal inhibitory concentration ( MIC ) over the ancestral genotype Pa14 , whereas those evolved in the absence of Cip increased MIC by no more than 2-fold . Single genotypes isolated from each population gave similar results: genotypes evolved in Cip had MICs ranging from 32-fold to 192-fold greater than the ancestor . To detect adaptation to the growth medium we assayed the fitness of evolved populations and genotypes in the absence of antibiotic using direct , head-to-head competitions against Pa14 ( see Materials and Methods ) . We interpret the population-level assays as a measure of the extent of adaptation achieved , since these reflect the average increase in fitness of all genotypes present at the end of the experiment . The single-genotype assays provide a measure of adaptation for the same genotypes we have sequenced ( see below ) . Note that there will be a close correspondence between measures of fitness at the population and single-genotype levels only if the population is genetically uniform , as expected under a model of periodic strong selection . If , however , the population is genetically polymorphic , perhaps because mutation supply rates ( the product of population size , N , and mutation rate , u ) are high or distinct genotypes are maintained by negative frequency dependent selection , then adaptation detected at the level of the population may not be accurately predicted by assays of fitness from single genotypes . Our results are shown in Figure 2 , where the dark bars represent the extent of adaptation by entire populations and the light bars adaptation by single genotypes . Evolved populations adapted to the growth medium without antibiotic only when mucin was present in the medium . In the absence of mucin , there was either no response to selection ( scfm ) or a significant cost to adaptation to Cip ( scfm+Cip; ANOVA: P = 2 . 9×10−5; Table 1 ) . Thus , the presence of mucin in the environment affords a greater opportunity for rapid adaptation . The single genotype fitness data are more mixed and do not correspond well with the population-level fitness assays ( Figure S1 ) , suggesting the presence of substantial amounts of genetic diversity within populations . We saw no consistent effect of mucin or of antibiotic on adaptation to the growth medium , as indicated by a lack of main effect for either of these factors by ANOVA ( Table 1 ) . There was , however , a significant interaction between medium and antibiotic ( ANOVA: P = 0 . 013; Table 1 ) , reflecting the observation that scfm+Cip-evolved genotypes were on average more fit than the ancestor ( mean relative fitness w = 1 . 09/generation ) , whereas the scfm+mucin+Cip-evolved genotypes were on average less fit than the ancestor ( mean w = 0 . 86/generation ) . This interpretation is reinforced by a lack of correlation between genotypes and populations for MIC , for which there was little correspondence between the level of resistance ( Figure S2 ) . Taken together , these results suggest two important conclusions about short-term adaptation to a CF lung-like environment: ( 1 ) adaptation does occur , and it is driven primarily by the presence of mucin; and ( 2 ) substantial genetic diversity is likely to be present in evolving populations shortly after colonization , a result consistent with the observation that P . aeruginosa isolates from CF patients can often be highly diverse [10] , [35] , [36] . In order to gain insight into the genetic causes of adaptation , we sequenced the genomes of the pure genotypes assayed above , with one genotype sampled from each of the 48 evolved populations ( that is , a single genotype from each population evolved in scfm alone , scfm+ciprofloxacin , scfm+mucin , and scfm+mucin+ciprofloxacin ) , as well as of our laboratory's isolate of the ancestral strain Pa14 . We obtained a median coverage of ∼56-fold per genotype ( mean = 55 . 5; range 31 . 8–85 . 4 ) on the Illumina platform , using 75-bp paired-end reads . Given that a previous study suggested that 15–20-fold coverage is sufficient for identifying a modest number of mutations in laboratory selected microbial strains [37] , the depth of coverage we achieved should allow us to identify all SNPs and small indels throughout most of the genome . In addition , the sequenced genomes were surveyed for large insertion/deletion events , such as mobile element insertions or excisions . We were unable to survey ∼0 . 53% of the genome in each strain due to low coverage ( defined as less than five reads covering a given nucleotide ) . Across all 48 evolved strains , we identified 98 SNPs and small indels ( mean 2 . 04/strain ) not present in the ancestor ( Table S1 lists all mutations and their predicted functional consequences ) . These mutations represented 77 unique changes , affecting a total of 44 genes and 4 putatively intergenic regions . No large insertion/deletion events were found using BRESEQ [38] . Two genotypes , both isolated from the scfm+mucin+Cip treatment , bore lesions in mutS and were thus likely mutator strains , an inference supported by the relatively high number of mutations found in these strains ( one carried 30 mutations , and the other carried 4 , representing the 1st and 3rd ranked genotypes in terms of number of mutations ) , as well as by an extreme transition∶transversion bias amongst point mutations ( all 26 point mutations found in these two strains were transitions ) , which is characteristic of mutS mutants [39] . If these putative mutator strains are omitted , we found 64 mutations ( 44 unique changes ) affecting 20 genes and 1 intergenic region ( Figure S3 ) . These mutations included 41 point mutations and 23 insertion/deletions ( indels ) . Genotypes evolved in the presence of ciprofloxacin or mucin carried more mutations on average than genotypes not evolved with antibiotic ( Figure 3 ) . Interestingly , genotypes from the most complex environment , containing both ciprofloxacin and mucin , carried more mutations than any other environment , on average . This result is broadly consistent with the idea that the number of mutations involved in adaptation increases with the number of distinct niche dimensions in the environment , an interpretation supported by both antibiotic and presence/absence of mucin being significant predictors of the number of mutations identified ( ANOVA , mutators excluded; medium: F = 8 . 6 , P = 0 . 005; antibiotic: F = 111 . 8 , P = 2×10−13 ) . Previous studies of the genomic basis of adaptation in experimentally evolved bacterial populations have detected , on average , 1 . 07 mutations/100 generations ( range: 0 . 09–3 . 94; [40] ) . The numbers of mutations observed after ∼48 generations in our antibiotic-evolved genotypes ( mean 2 . 1 and 2 . 6 in scfm and scfm+mucin , respectively ) are thus substantially higher than observed in previous studies . This difference probably reflects the strong selection imposed by antibiotic treatment , as opposed to the weaker selection commonly observed in resource-adaptation experiments , combined with sufficiently large population sizes to ensure the availability of multiple beneficial mutations in the same population or even the same genome [41] . Notably , the rate of accumulation of adaptive mutations observed here is consistent with theoretical models of substitution under strong selection that show expected fixation times of 50 generations or less for mutations with large selection coefficients ( see Figure S4 from [42] ) . At the opposite end of the spectrum , very few mutations were detected in our scfm populations , with 10 genotypes bearing no mutations , and 2 genotypes carrying a single mutation each . This result is consistent with the lack of fitness response observed above ( Figure 2 ) and is broadly consistent with the theoretical expectation under neutrality , whereby the expected fraction of 6 . 5 Mb genomes with zero mutations after 48 generations should be 0 . 73–0 . 97 , depending on the per base pair mutation rate ( taken as 1×10−10 to 1×10−9 for these estimates; [43] ) . Broad patterns of nucleotide variability suggest that natural selection has played an important role in shaping the observed spectrum of mutations . Amongst the 41 point mutations observed in the non-mutator strains , 39 were nonsynonymous , 1 was synonymous , and 1 was putatively non-coding . Since approximately 1/3 of random coding changes are expected to be synonymous , the lack of synonymous mutations is consistent with natural selection favouring a substantial fraction of the observed mutations in the non-mutators . Using a randomization approach ( see Materials and Methods ) , we find that both the excess of non-synonymous mutations , and the paucity of synonymous mutations , are highly significant ( Figure S4; P<0 . 0005 ) . By contrast , many more synonymous mutations were observed in the putative mutator strains , with 15 non-synonymous , 8 synonymous , 8 genic frame-shifts , and 3 intergenic mutations identified in the 2 putative mutators . The observed counts of non-synonymous and synonymous mutations in these mutators are not significantly different than expected by chance ( non-synonymous: P = 0 . 30; synonymous: P = 0 . 43 ) , suggesting that many more mutations are neutral and that these strains show a general and unbiased increase in mutation rate . The observed number of intergenic mutations ( 3 ) in the mutator strains is significantly higher than expected by chance , however ( P = 0 . 011 ) , suggesting that at least one of these mutations has been driven by selection . Observed changes in ciprofloxacin MIC and in fitness are attributable to some or all of the mutations identified by WGS . For example , in the ciprofloxacin-evolved strains , we observed multiple mutations in the known fluoroquinolone-resistance genes gyrA , gyrB , and nfxB . Amongst 24 genotypes from populations evolved in the presence of ciprofloxacin , 20 bore mutations in nfxB , 9 carried mutations in gyrB , and 4 genotypes bore gyrA mutations . Each of the gyrA mutations is a known resistance mutation affecting its quinolone-resistance determining region ( QRDR; [44] , [45] ) , with one strain carrying a T83I mutation , two with D87G , and one with a D87N mutation . The gyrB mutations were dispersed throughout this gene , with 6 different lesions amongst the 9 strains ( Figure 4 ) . In nfxB , loss of function mutations would be expected to be prevalent , since inactivation of this transcriptional repressor results in up-regulation of the MexCD-OprJ efflux pump ( e . g . , [46] ) . Concordant with this expectation , 8 distinct mutations were found in nfxB among the 20 genotypes bearing mutations ( Figure 4 ) . Interestingly , three sites were mutated in multiple strains ( T39P in 3 strains , in a predicted helix-turn-helix DNA-binding domain; E146K in 5 strains; G180S in 8 strains ) , providing further evidence that these mutations are adaptive . Additionally , 7 ciprofloxacin-resistant genotypes carried mutations in the gene orfN , 6 being isolated from populations evolved in scfm+Cip . orfN encodes a predicted glycosyl transferase , and is necessary for the glycosylation of type A flagellins [47] . 6 of the orfN mutants carried a single base pair deletion in a poly-G repeat , leading to the introduction of a premature stop codon . The predicted mutant protein is truncated after 53 amino acid residues ( vs 338 for the wild-type protein ) . The seventh orfN mutant carries a single base-pair deletion in a poly-T repeat , leading to a truncated protein of 133 residues . The predicted mutant proteins are truncated before or in the glycosyl transferase domain , suggesting that the orfN mutations are likely to be loss-of-function mutations ( Figure 4 ) . While this gene has not previously been associated with fluoroquinolone resistance , this observation of extensive parallel evolution strongly suggests that orfN mutants have increased fitness in the presence of ciprofloxacin . To obtain further evidence for an effect of orfN and other putative novel resistance mutations on Cip resistance , we surveyed isolates from evolving populations from early time points and assayed their MICs in the genetic backgrounds in which they arose . This approach allows us to sample candidate genes relatively quickly in the context in which they evolved . For orfN mutants , we sampled single colony isolates from early time points ( days 3–5 of the evolution experiment ) from populations where an orfN mutation was observed at day 8 . Early time-point isolates were sequenced at all genes bearing a SNP at day 8 , and clones bearing only an orfN mutation were selected . In this way , we identified several apparent single orfN mutants: 2 from population scfm-A5 at day 3 , and 1 from population scfm-D6 at day 5 . As expected each of these putative single mutants showed a 32-fold elevation in ciprofloxacin MIC in comparison to the ancestral Pa14 genotype , suggesting that orfN is a novel resistance gene . While the observation of parallel evolution at nfxB , gyrA , gyrB , and orfN is indicative of natural selection acting on these genes , 12 of the mutations identified in the non-mutator strains appeared in only a single isolate each ( Figure S5 ) . Such mutations may represent adaptive mutations of minor effect , or they may be neutral mutations that are either segregating due to drift or have hitchhiked alongside other strongly adaptive mutations . In several cases , MIC analyses suggest a benefit to these mutations arising through increased levels of antibiotic resistance . Genotypes containing a single mutation in Pa14_32420 ( encoding a putative oxidoreductase ) isolated from an early time point ( day 3 ) showed a 4-fold increase in ciprofloxacin MIC and a SNP in Pa14_46110 ( encoding a predicted sodium∶solute symporter ) , which was the third mutation to arise in the population , had an 8-fold higher MIC than did genotypes carrying only the first two mutations ( which occurred in nfxB and Pa14_23430 ) . Thus , the evolution of quinolone resistance appears to have involved both highly parallel changes , as well as mutations specific to individual experimental populations . Previously , Breidenstein et al . [48] conducted a screen of transposable-element insertions for novel ciprofloxacin resistance determinants . Interestingly , there is almost no overlap between between the 114 genes identified by Breidenstein et al . and the 44 genes bearing SNPs in this study . nfxB and mutS mutants were isolated in both experiments , but no other gene was found as a potential resistance factor in both studies . In addition , Breidenstein et al . identified a number of phage-related or phage-derived genes as resistance modifiers , and we found a non-coding mutation in a different cluster of phage-related genes ( at position 1927375 of the Pa14 genome ) . The difference between these two studies is likely due to the different mechanisms that lead to resistance mutations in the two studies: transposon insertions were used by Breidenstein et al . paper , and spontaneous point mutations and indels in the current study . Importantly , the lack of overlap between the two studies is an indication that many genes potentially contribute to fluoroquinolone resistance in P . aeruginosa , and suggests that in general multiple approaches should be taken in the identification of genes underlying phenotypes of interest . Experimental evolutionary approaches , such as the one adopted here , differ from traditional mutational studies in that selection acts as an extra sieve that will weed out slow-growing mutants that , while they confer resistance , are out-competed on the way to fixation by other mutations conferring higher fitness ( see [17] , [18] for discussions of the use of experimental evolution as a tool for mutation discovery ) . While this effect of natural selection will likely eliminate some mutations of interest ( especially for understanding underlying biological pathways ) , mutations observed under selection may be more clinically relevant due to their relatively high fitness . Surveys of clinical samples of Pseudomonas aeruginosa often uncover a handful of genes with major effects on fluoroquinolone resistance . Most commonly , these genes are gyrA and gyrB , which encode the subunits of the fluoroquinolone target DNA gyrase , and the efflux pump regulators nfxB and mexR ( e . g . , [44] , [46] , [49] , [50] ) . Given that mutational surveys have revealed many other genes that can confer resistance to fluoroquinolones , why is it that these four genes are repeatedly recovered from clinical samples ? One possibility is that these genes enjoy a large fitness advantage in the presence of antibiotic because they confer large increases in MIC . To test this prediction , we asked to what extent the presence or absence of mutations in classical resistance genes is a predictor of the level of ciprofloxacin resistance . As described above , many of the ciprofloxacin-evolved strains in this study bore mutations in one or several of gyrA , gyrB , and nfxB , although no mexR mutants were isolated . A linear model including selection medium ( scfm+Cip or scfm+mucin+Cip ) and presence or absence of mutations in gyrA , gyrB , and nfxB explains ∼87% of variation in MIC between genotypes ( Table 2 , Figure 5A , 5B ) . Under this model , mutations in nfxB , gyrA , and gyrB are associated with average MIC increases of 25 . 3 , 3 . 2 , and 10 . 9-fold , respectively . Thus , a substantial fraction of variation in the level of resistance is attributable to mutations in classical resistance genes . It should be noted that the genotypes indicated in Figure 5 are not exhaustive – for example , a given nfxB mutant on Figure 5 will also carry at least one additional mutation . Thus , variation within a genotype class ( for example , the nfxB mutants ) is attributable to these additional mutations . An alternative , and not mutually exclusive , possibility is that these mutations pay little cost of resistance in the absence of antibiotic . Cost-free resistance may arise because the mutations themselves are not costly or because second-site mutations rapidly evolve that compensate for whatever cost they do incur . We tested this prediction by examining the fitness of strains bearing ( or not ) mutations in classical resistance genes in the absence of ciprofloxacin and found little relationship between genotype and fitness ( Table 3 , Figure 5C , 5D; see also Figure S6 ) . Notably , only strains carrying nfxB mutations from the scfm+Cip environment show an increase in fitness in the absence of antibiotic ( Table 3 ) and none of the gyrA , gyrB , or nfxB mutants from the scfm+mucin+Cip environment were significantly different from the ancestor . This result may be surprising , given that single mutations in gyrA and nfxB are typically costly [16] , [51] , [52] but we note that none of the strains examined here carried only a gyrA or nfxB mutation; all were at least double mutants . This result suggests that fitness in the absence of antibiotic appears to be determined or modulated by mutations in genes other than nfxB , gyrA , and gyrB . Thus cost-free resistance probably arises through second-site mutations that compensate for the costs incurred by these classical resistance genes , consistent with the results of previous studies [13] , [53]–[56] . It is notable that these compensatory mutations would have to have arisen very quickly alongside or soon after resistance had evolved for them to be observed in the short time frame of our experiment . What sorts of second-site mutations might be involved in compensating for the fitness costs of nfxB , gyrA , or gyrB resistance mutations ? Our genome-wide survey of mutations provides some insight . We have found a wide range of mutations amongst the Cip-resistant genotypes sequenced in this study . These include mutations in the gene nusA encoding an elongation factor , a putative kinase encoding gene Pa14_28895 , and ate1 , which encodes an arginyl-trNA-protein transferase ( see Table S2 for a full list ) . While genotype at classical resistance genes predicts MIC ( but generally not fitness ) , we find no evidence that the raw number of mutations present in a lineage predicts either MIC or fitness in the absence of antibiotic ( data not shown ) . These data are consistent with a model in which classical resistance genes make particularly large contributions to MIC that can mask the smaller effects of other resistance mutations , even if these latter mutations occur first or provide additional increases to MIC or fitness . Taken together , these results suggest that the prevalence of classical fluoroquinolone resistance mutations such as those in gyrA and nfxB in clinical isolates is due to the combination of high levels of resistance and apparent lack of costs due to second site mutations . These results are of clinical importance because they suggest that attempts to combat resistance in patient populations by stopping the use of the offending antibiotic in the hopes that drug sensitive types will replace resistant ones will often fail ( e . g . , [57] ) . Epidemiological evidence on the effectiveness of this strategy at controlling resistance is both limited and mixed [6] , [58]: reducing the use of antibiotics often leads to a reduction in the frequency of resistant strains , but it rarely succeeds in eliminating them altogether [4] , [5] . Our results suggest that the mechanistic reason for this failure is not that resistance mutations are cost-free but , rather , that their costs are rapidly compensated for by a diverse array of mutations elsewhere in the genome . Our genomic analysis also sheds light on the genetic pathways to adaptation in CF-like conditions . Strains evolved in the most CF-like environment , scfm+mucin , often contained mutations in genes implicated in cyclic-di-GMP signalling . Elevated levels of intracellular cyclic-di-GMP are thought to induce a shift from a motile , planktonic lifestyle to a non-motile biofilm state in a variety of bacteria [27]–[29] . We suspect that increases in diguanylate cyclase activity may be adaptive in the presence of mucin , which encourages biofilm growth . Consistent with this hypothesis , three genes with putative roles in diguanylate cyclase signalling were repeatedly found mutated in the evolved strains . 9 of 24 populations ( 8 without ciprofloxacin , 1 with ciprofloxacin ) contained isolates bearing mutations in the morA gene ( Figure 4 ) . morA encodes a predicted membrane-localized diguanylate cyclase , and serves as a negative regulator of flagellum formation [59] . In P . aeruginosa , expression of morA is required for the switch from wild-type colony morphology to the small-colony variant morphology [27] , which is associated with biofilm formation in CF infections [25] . 7 distinct morA mutations – all missense point mutations - were identified in our evolved strains ( Figure 4 ) . Two scfm+mucin-evolved strains bore mutations in wspF , which encodes a regulator of the diguanylate cyclase WspR , with wspF loss-of-function mutants showing increased biofilm formation [28] and wrinkly colony morphologies in Pseudomonas fluorescens [60] . One of the wspF alleles recovered in this study is likely a loss-of-function mutation , since it encodes an early frame-shift . The second allele is a single in-frame codon deletion whose effects we cannot predict . Finally , the gene Pa14_56280 , encoding another predicted diguanylate cyclase , was found to be mutated in two further scfm+mucin adapted strains . In light of the role of cyclic-di-GMP signalling in biofilm formation [27]–[29] , we predicted that our putative cyclic-di-GMP signalling mutants should show increased aggregation and biofilm formation . To test this prediction , we examined colony morphology on Coomassie blue/Congo red agar plates , which is a sensitive indicator of aggregation ( e . g . , [61]–[63] ) . Isolates bearing mutations in morA , wspF , or Pa14_56280 showed wrinkly , red morphologies in comparison to the ancestral Pa14 strain ( Figure 6A–6E ) , consistent with increased aggregation and biofilm formation . Genotypes bearing mutations in different genes , and even different mutations in the same gene ( e . g . for morA , compare Figure 6B and 6C ) , showed different colony morphologies , suggestive of different effects on the level , timing , and/or localization of aggregation signals , presumably cyclic-di-GMP . The frequency with which cyclic-di-GMP signalling genes are mutated in our mucin evolved strains – with apparent consequences for aggregation and biofilm formation – strongly suggests a shared mode of adaptation towards a novel in vitro environment . This finding parallels data from clinical isolates of P . aeruginosa: Long-term adaptation of P . aeruginosa to the CF lung is characterized in part by extensive biofilm formation ( e . g . , [26] , [64] ) and the switch to a largely non-motile lifestyle is likely mediated by cyclic-di-GMP signalling ( e . g . , [25] , [65] ) . Notably , wspF mutations have previously been documented in CF isolates ( e . g . , [10] ) ; the current data suggest several other possible mediators of biofilm formation in clinical isolates . Unexpectedly , all strains bearing mutations in the quinolone-resistance gene nfxB showed smooth colony morphologies ( Figure 6F ) , a phenotype typically associated with impaired biofilm production ( e . g . , [61]–[63] ) . This observation suggests an effect of nfxB on biofilm formation and/or extracellular matrix production , which to our knowledge has not been previously reported . The extent of parallel evolution during adaptation is of interest for a variety of reasons; evolution is in principle predictable ( or not ) to the extent that independent populations adapt to similar environments via the same ( or different ) mutations . The observation of substantial parallel evolution is also used as an indicator of strong positive selection . Previous experimental evolution studies have documented varying degrees of parallel evolution at both the phenotypic and genotypic levels [66]–[73] . We have already noted parallel evolution in response to ciprofloxacin and to mucin in our study , with multiple lineages bearing mutations in the quinolone resistance genes gyrA , gyrB , nfxB , orfN , and in the apparently mucin-adaptive genes morA , Pa14_56280 , and wspF . These observations provide strong evidence that these mutations are beneficial . How prevalent is parallel evolution in our study ? To answer this we used the Jaccard index ( J ) to quantify the extent of within- and between-environment genic parallel evolution . For a given pair of evolved genotypes , J ranges from 0 to 1 , with 0 indicating no parallel evolution and 1 indicating identity ( see Materials and Methods for further details ) . We calculated the average Jaccard index for within- and between-environment comparisons , excluding genotypes with no SNPs , as well as mutS mutator strains ( Figure S7 ) . Within environments , was highest for the scfm+mucin genotypes , due to the high frequency of morA mutations in this environment . was intermediate for the scfm+Cip and scfm+mucin+Cip genotypes , reflecting parallel evolution at a handful of genes combined with a number of lineage-specific mutations . Between-environments , was 0 , except for between the two ciprofloxacin treatments , indicative of some shared mechanisms of resistance . We rarely saw the exact same mutation evolving in parallel selection lines , suggesting that the bulk of parallel evolution in our experiment is through de novo mutations rather than the selection of rare , pre-existing variants . For the few cases where the same mutation was observed in multiple lineages , however , we note that the current study design cannot formally distinguish between these two alternatives since our experimental populations were started from a common founding culture . We suspect that several different factors contribute to differences in the propensity for parallel evolution at different genes . Chevin et al . [74] , analyzing an explicitly genomic model of trait evolution , show that the probability of parallel evolution at a given locus can depend on the locus specific mutation rate , the probability of a mutation being beneficial , and the probability of a mutation going to fixation . For some loci , e . g . nfxB , loss-of-function mutations are likely to be beneficial , and so the probability of a mutation being beneficial will be quite high ( see [73] for a similar example ) . For other loci , such as gyrA , the probability of fixation for beneficial mutations may be high due to their large effects on MIC . Finally , in the case of orfN , where a slippage mutational mechanism is implicated by the observation of single base deletions in repeat regions , both the mutation rate and the probability of a mutation being beneficial are likely to be elevated . Thus , different genes may undergo parallel evolution for rather different reasons . We have studied the genomic basis of adaptation to CF-like culture conditions and to ciprofloxacin in experimentally evolved isolates of the opportunistic pathogen P . aeruginosa . Adaptation did occur to the most CF-like conditions and to the presence of ciprofloxacin , although our evolving populations are likely highly polymorphic . We observed parallel evolution at a handful of antibiotic resistance genes ( gyrA , gyrB , nfxB , and orfN ) , as well as at putative cyclic-di-GMP signalling genes in the mucin environment . While the level of antibiotic resistance was determined largely by known resistance genes , fitness in the absence of antibiotic was not , such that there was no overall relationship between resistance and its associated costs . These findings have several implications for understanding antibiotic resistance and pathogen evolution . First , we have identified a suite of novel ciprofloxacin resistance mutations . Our evolved antibiotic resistant isolates harbour mutations in 12 genes not previously implicated in fluoroquinolone resistance , and initial assays are consistent with effects on ciprofloxacin MIC for 3 of these genes ( orfN , Pa14_46110 , and Pa14_32420 ) . Thus , experimental evolution , coupled with WGS , represents a powerful approach to identifying novel genes of interest . Second , we find that the costs of resistance are not systematically determined by the same mutations that account for most of the variation in level of resistance ( i . e . , mutations in gyrA , gyrB , and nfxB ) . This finding suggests that whatever costs are associated with single resistance mutations are easily remediated by mutations at other loci . Moreover , these results suggest that the prevalence of these resistance mutations in clinical isolates are likely the result both of the high levels of resistance they confer and the rapid compensation of costs by second-site mutations . Third , the finding of multiple cyclic-di-GMP mutations in the mucin environment underscores the importance of GMP-mediated biofilm formation in viscous environments , such as the CF lung . Finally , our findings suggest that pathogen evolution has a partially repeatable genomic basis , insofar as some genes are repeatedly mutated in multiple replicate populations , while others are not . This observation has important implications for understanding pathogen evolution . Those genes that show highly parallel evolution may be particularly important in their influence on key adaptive traits governing infection or resistance to antibiotics . However , genes that are mutated only rarely are not necessarily unimportant: they often appear to have important phenotypic consequences , such as compensating for costs of resistance , and so cannot be ignored . In designing novel medical interventions , therefore , our results suggest that we would do well to focus attention first on these common targets of adaptation to the lung environment , while not losing sight of the potential importance of rare and sometimes idiosyncratic mutations that nevertheless play a major role in determining the overall fitness of the pathogen .
A single colony of P . aeruginosa strain Pa14 was grown overnight in minimal medium ( NH4Cl 1 g/L , KH2PO4 3 g/L , NaCl 0 . 5 g/L , Na2HPO4 6 . 8 g/L; supplemented with CaCl2 15 mg/L , MgSO4 0 . 5 g/L; 0 . 8% dextrose as a carbon source ) . Forty-eight populations were founded from this progenitor by adding 25 µL overnight culture to 1 . 5 mL of fresh medium ( media described below ) . An aliquot of progenitor was frozen at −80°C in glycerol . Populations were grown on an orbital shaker ( 150 rpm ) at 37°C for 24 hours in 24-well plates . After 24 hours , each population was serially propagated by transferring 25 µL of overnight culture to 1 . 5 mL of fresh medium . Overnight cultures were frozen at −80°C in glycerol . Seven such transfers were conducted in total , such that approximately 50 generations of evolution occurred ( ∼5 . 9/day for 8 days ) . Four selection environments were used , consisting of two different media with or without antibiotic . The media were chosen so as to examine the effects of CF sputum nutrition and viscosity on the evolution of antibiotic resistance in P . aeruginosa . Synthetic CF sputum ( scfm ) was prepared as described by [30] ) . In order to manipulate viscosity , we added 10 g/L porcine mucin ( Sigma ) to synthetic CF sputum ( scfm+mucin ) [32] , [33] . For antibiotic treated populations , we used 1 µg/mL ciprofloxacin to mimic the concentration typically found in the sputum of CF patients [31] . For each evolved population , or for pure genotypes isolated from each population , level of resistance was assayed as the minimal inhibitory concentration ( MIC ) of ciprofloxacin . Overnight cultures were grown in Mueller-Hinton broth ( MHB; Sigma ) , of which 5 µL was inoculated into 195 µL of fresh MHB with varying concentrations of ciprofloxacin in 96 well plates . MIC of the ancestor , i . e . , the concentration at which growth was inhibited by 90% , was 0 . 05 µg/mL . For each evolved strain , we assayed growth at 0x , 0 . 5x , 1x , 2x , 4x , 8x , 16x , 32x , 64x , 128x , 192x , and 256x the ancestral MIC . Fitness of each evolved population or genotype was assayed using a competitive fitness assay against a lacZ marked ancestral strain . Independent assays verified that the lacZ-marked strain did not bear a fitness cost in competitions with unmarked Pa14 . Both competitors were grown for 24 hours in the competition medium . At time 0 , 12 . 5 µL of marked ancestor and 12 . 5 µL of evolved strain were inoculated into 1 . 5 mL of fresh medium in a 24-well plate , and an aliquot was frozen at −80°C in glycerol . Following 24 hours of growth at 37°C at 150 rpm , a final aliquot was frozen at −80°C in glycerol . Serial dilutions of initial and final aliquots were grown on solid minimal media+X-gal , allowing us to determine the numbers of blue ( ancestral ) and white ( evolved ) individuals at the beginning and end of the competition . The selection coefficient s was calculated as:Relative fitness w was then calculcated as 1+s , where the units for both w and s are in per generation . Colony morphology was assayed according to [61] . Briefly , 10 µL of culture grown overnight in LB were spotted in triplicate onto tryptone plates ( 10 g/L ) supplemented with 20 µg/ml Coomassie blue and 40 µg/ml Congo red . Plates were grown for 4 days at room temperature , after which digital photos were taken . For whole-genome sequencing , a single colony was picked from each evolved population , as well as for the ancestral Pa14 genotype . For each genotype , genomic DNA was extracted from an overnight culture using the Promega Wizard Genomic DNA Purification kit . 75-bp paired-end Illumina sequencing was performed by the Michael Smith Genome Sciences Centre , using DNA barcodes to sequence 10–12 isolates per lane . Mean coverage across all 49 genotypes was 55 . 5-fold at a quality score of 20 ( range: 31 . 8–85 . 4 ) . We performed a pair-end mapping of reads on the Pa14 reference genome number NC_008463 . 1 using novoalign ( http://novocraft . com/main/index . php ) . We used samtools [75] to call snps/indels , and filtered the resulting calls using the provided samtools . pl script , changing the window size for snps around indels at 5 base pairs , removing the limit on number of reads spanning a snp/indel position , and leaving the remaining parameters at their default values . We further filtered calls with quality scores below 60 for indels , and 20 for snps . To annotate the remaining snps/indels with respect to the reference genome , we used snpEff ( http://snpeff . sourceforge . net/ ) . We found results to be robust to performing a pre-mapping clipping of reads based on quality across cycles using FastQC ( http://www . bioinformatics . bbsrc . ac . uk/projects/fastqc/ ) , and to performing local multiple sequence re-alignment around indels using the Genome Analysis ToolKit [76] . We also used the BRESEQ [38] pipeline as a further validation , and for its insertion/deletions detection capabilities . Following removal of common assembly errors using custom perl scripts , a subset of SNPs was verified by Sanger sequencing of polymerase chain reaction ( PCR ) amplicons . For each of 31 mutations ( out of 98 mutations identified in the 48 evolved strains ) , we amplified a 500–700 bp PCR product containing the putative SNP , and directly sequenced the PCR products ( Genome Quebec , Montreal ) . All 31 mutations that we interrogated were successfully verified . We used a randomization approach to determine the probability of observing by chance the distribution of non-synonymous , synonymous , and intergenic point mutations . This analysis was performed separately for putative mutator strains ( two mutS mutants ) and for putative non-mutator strains ( the remaining 46 strains ) . 10 000 sets of point mutations were generated at random from the Pa14 genome sequence , maintaining the observed numbers of transitions and transversions ( mutators: 30 transitions and 11 transversions; non-muators: 26 transitions and 0 transversions ) , and SNP effects were predicted using snpEff . Mean numbers of non-synonymous , synonymous , and intergenic mutations , as well as the 2 . 5% and 97 . 5% quantiles of the random distribution , were calculated in R [77] . The extent of parallel evolution was quantified using the Jaccard Index J . Given two sets G1 and G2 that list mutation-bearing genes found in genotypes 1 and 2 , respectively , That is , J is the number of genes mutated in both strains divided by the total number of genes mutated in genotype 1 or in genotype 2 . J ranges from 0 to 1 , with 1 indicating identical genotypes and 0 indicating no shared mutations . J was calculated for all possible pairs of different genotypes amongst the 46 non-mutator strains . The average Jaccard Index was calculated within a treatment group as the mean J for all pairs of strains , where both strains were evolved under the same treatment . Similarly , was calculated between treatments A and B as the mean J for all pairs of strains , where one strain was evolved under treatment A and the second strain was evolved under treatment B .
|
Pathogens face a hostile and often novel environment when infecting a new host , and adaptation to this environment can be critical to a pathogen's survival . The genetic basis of pathogen adaptation is in turn important for treatment , since the consistency with which therapies succeed may depend on the extent to which a pathogen adapts via the same routes in different patients . In this study , we investigate adaptation of the bacterium Pseudomonas aeruginosa to laboratory conditions that resemble the lungs of cystic fibrosis patients and to quinolone antibiotics . We find that a handful of genes and genetic pathways are repeatedly involved in adaptation to each condition . Nonetheless , other , less common mutations can play important roles in determining fitness , complicating strategies aimed at reducing the prevalence of antibiotic resistance .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbial",
"evolution",
"microbial",
"pathogens",
"biology",
"evolutionary",
"biology",
"microbiology",
"evolutionary",
"genetics"
] |
2012
|
Genomics of Adaptation during Experimental Evolution of the Opportunistic Pathogen Pseudomonas aeruginosa
|
Upon phagocytosis , Legionella pneumophila translocates numerous effector proteins into host cells to perturb cellular metabolism and immunity , ultimately establishing intracellular survival and growth . VipD of L . pneumophila belongs to a family of bacterial effectors that contain the N-terminal lipase domain and the C-terminal domain with an unknown function . We report the crystal structure of VipD and show that its C-terminal domain robustly interferes with endosomal trafficking through tight and selective interactions with Rab5 and Rab22 . This domain , which is not significantly similar to any known protein structure , potently interacts with the GTP-bound active form of the two Rabs by recognizing a hydrophobic triad conserved in Rabs . These interactions prevent Rab5 and Rab22 from binding to downstream effectors Rabaptin-5 , Rabenosyn-5 and EEA1 , consequently blocking endosomal trafficking and subsequent lysosomal degradation of endocytic materials in macrophage cells . Together , this work reveals endosomal trafficking as a target of L . pneumophila and delineates the underlying molecular mechanism .
Legionella pneumophila is an opportunistic human pathogen that replicates inside macrophages , which are at the front line of immune defense . This Gram-negative bacterium causes Legionnaires' disease characterized by severe pneumonia or less acute Pontiac fever . By phagocytosis , the bacteria are enclosed in a membrane-bound vacuole , called Legionella-containing vesicle ( LCV ) . This vesicle evades the endocytic pathway to avoid fusion with lysosomes [1] , and becomes the growth and replication niche for the bacteria [2] , [3] . The intracellular survival and replication depend on the Dot/Icm type IV secretion system of the bacterium , which translocates about 270 effector proteins into the host cytosol [4] , [5] . Understanding of detailed molecular mechanisms of the L . pneumophila effectors has been achieved for a number of proteins , including SidM ( substrate of Icm/Dot transporter M; also known as DrrA ) [6]–[12] , LpGT ( L . pneumophila glucosyltransferase; also known as Lgt1 ) [13]–[15] , AnkX ( Ankyrin repeat protein X ) [16]–[18] and others as reviewed recently [19] . VipD ( vacuolar protein sorting inhibitor protein D ) is one of the L . pneumophila effector proteins , which interrupts Golgi-to-vacuole trafficking of three yeast proteins ( carboxypeptidase S , carboxypeptidase Y and alkaline phosphatase ) as well as endoplasmic reticulum ( ER ) -to-Golgi trafficking of carboxypeptidase Y when expressed in Saccharomyces cerevisiae [20] . VipD contains an N-terminal lipase domain which shares sequence homology with patatin , a phospholipase in potato tuber having phospholipase A and lysophospholipase A activities [21] . A similar lipase domain is present in two other L . pneumophila effector proteins VpdA and VpdB [22] and in ExoU of Pseudomonas aeruginosa , which is a potent secreted cytotoxin [23] , [24] . On the other hand , their C-terminal domains do not exhibit sequence homology with each other or with any functionally annotated protein domain . Previously , overexpression of VipD was shown to be mildly toxic to 293T cells and S . cerevisiae , and its toxicity was only partially dependent on the putative lipase activity of the protein [22] . Moreover , a VipD fragment lacking the N-terminal lipase domain interfered with vesicle transport in S . cerevisiae to a much greater extent than full-length VipD did [20] , indicating that the C-terminal domain is critical for the function of VipD . But , how the C-terminal domain of VipD perturbs vesicle trafficking in yeast is unknown . It is also unknown whether VipD may manipulate intracellular trafficking in macrophages , the major mammalian host cells of L . pneumophila . We undertook an integrative approach involving X-ray crystallography , biochemistry and cellular imaging to understand whether and how VipD might affect mammalian host cells . We show that the C-terminal domain of VipD tightly binds to the GTP-bound form of Rab5 and Rab22 , blocks their interactions with three downstream effector molecules , and inhibits endocytic trafficking in mouse macrophages . Together , this study demonstrates that VipD targets and interferes with endosomal membrane trafficking in mammalian host cells .
Full-length VipD was crystallizable , but the X-ray diffraction of the crystals was too poor for structure determination . Various attempts were made to improve the crystal quality , and the successful trial was to employ a truncated VipD lacking C-terminal 46 residues and to dehydrate resulting crystals with 30% glycerol at −20°C . The structure of this truncated version of VipD , referred to as VipD ( 1-575 ) , was determined at 2 . 9 Å resolution ( Table 1 ) . VipD ( 1-575 ) folds into two domains which are roughly discernable: the N- and C-terminal domains , designated as VipD ( 1-316 ) and VipD ( 316-575 ) , respectively ( Figure 1A ) . Ala316 is at the boundary of the two domains and located in the middle of the structure lengthwise ( Figure 1A ) . The two domains interact with each other mostly through secondary structural elements . β1 and β2 of VipD ( 1-316 ) form a “mini” β-sheet together with β11 of VipD ( 316-575 ) in the C-terminal domain . Likewise , β10 of VipD ( 316-575 ) is a part of the central β-sheet in the N-terminal domain . In addition , α14 of VipD ( 316-575 ) interacts with α2 of VipD ( 1-316 ) ( Figure 1A ) . These observations suggested that division of VipD into the two fragments containing residues 1-316 or 316-575 would result in misfolded proteins . However , both VipD ( 1-316 ) and VipD ( 316-575 ) or VipD ( 316-621 ) produced in E . coli were soluble and purifiable . A search for similar structures in the Protein Data Bank with the program Dali [25] showed that the N-terminal domain is most homologous to patatin ( PDB entry: 1OXW ) and cytosolic phospholipase A2 ( cPLA2; PDB entry: 1CJY ) with the Z-scores of 14 . 0 and 11 . 4 , respectively ( Figure S1A ) . In particular , the two residues of cPLA2 ( Ser228 and Asp549 ) , which form the catalytic dyad [26] , are closely superposable on Ser73 and Asp288 in VipD ( Figure 1B ) . Moreover , the Gly196-Gly-Gly-Phe-Arg200 sequence , which forms the oxyanion hole in cPLA2 , is also present in VipD as a Gly42-Gly-Gly-Ala-Lys46 sequence at spatially the same location ( Figure 1B ) . In cPLA2 , the active site groove containing the catalytic dyad is partially covered by loop αH-αI . Likewise , a similar groove covered by loop β10-α14 is present in VipD ( Figure S2 ) . These features indicate that VipD is a catalytically active phospholipase A2 . However , whether VipD has an intrinsic phospholipase A2 activity or not has been unsettled [22] , [27] . We examined a phospholipase A2 activity of VipD by using an artificial fluorogenic phospholipid substrate red/green BODIPY PC-A2 ( specific for PLA2 enzyme ) , and show here that VipD has a phospholipase A2 activity ( Figure 1C ) . Alanine substitution of Ser73 or Asp288 abrogated the lipase activity of VipD , demonstrating that the two residues indeed form a catalytic dyad ( Figure 1C ) . VipD ( 316-575 ) contains ten α-helices and two short β-strands . This domain is not obviously homologous to any of the known protein structures in the Protein Data Bank . The best match ( Z-score: 4 . 6 ) in the Dali search was the structure of the Vps9 domain of Rabex-5 ( PDB entry: 1TXU ) , which is a guanine nucleotide exchange factor ( GEF ) for Rab5 , Rab21 and Rab22 [28] , [29] . Superposition of the two structures showed only a gross similarity in the spatial arrangement of five out of ten α-helices in VipD ( 316-575 ) ( Figure S1B ) , providing only an unconvincing clue for the function of the C-terminal domain . A clue for the biochemical function of the C-terminal domain of VipD was obtained by investigating the subcellular localization of VipD . In HeLa cells , full-length VipD , VipD ( 1-316 ) or VipD ( 316-621 ) was transiently expressed , each as a fusion protein containing yellow fluorescent protein ( YFP ) at the C-terminus . Full-length VipD and VipD ( 316-621 ) exhibited a similar fluorescence pattern , which was indicative of endosomal localization ( Figure 2A ) . To elaborate this observation further , full-length VipD or VipD ( 316-621 ) was coexpressed with the early endosomal markers Rab5b and Rab22a and also with the ER-to-Golgi trafficking regulator Rab1a [30] , respectively , in HeLa cells and in RAW264 . 7 macrophages . The GTPase-defective constitutively active forms , Rab5b ( Q79L ) , Rab22a ( Q64L ) and Rab1a ( Q70L ) , were employed , all tagged with cyan fluorescent protein ( CFP ) . Both full-length VipD and VipD ( 316-621 ) colocalized with Rab5b ( Q79L ) and Rab22a ( Q64L ) , but not with Rab1a ( Q70L ) , in both types of cells ( Figures 2B and S3 ) . In contrast , VipD ( 1-316 ) was evenly dispersed throughout cells with a noticeable enrichment at the plasma membranes ( Figure 2A ) . Notably , the characteristic tubular structures of endosomes observed with the expression of Rab22a ( Q64L ) alone ( Figure S4A ) [31] disappeared when this Rab protein was coexpressed together with full-length VipD or VipD ( 316-621 ) , while their formation was unaffected by the expression of VipD ( 1-316 ) ( Figure S4B ) . We additionally noted that Rab22a ( Q64L ) colocalized with Rab5b ( Q79L ) without inducing the tubular structures when the two proteins were coexpressed in both types of cells ( Not shown ) . We also found that VipD colocalized with the wild-type forms of Rab5b and Rab22a ( Figure S5A ) , which cycle between the endosomal membrane and the cytosol [30] . Finally , like Rab5b ( Q79L ) , full-length VipD did not localize to lysosomes , as probed by the lysosomal marker Lysotracker Red ( Figure S5B ) . These results convincingly indicated that VipD localizes to early endosomes via the C-terminal domain of the protein . In addition , the precise overlaps of the two different fluorescence images suggested that the C-terminal domain of VipD may directly interact with the two Rabs . The possibility of the direct interactions of VipD with Rab5b and Rab22a was probed using Rab5b ( 1-190;Q79L ) and Rab22a ( 1-175;Q64L ) , and a wild-type version of the two Rabs . These Rab proteins were C-terminally fused to a ( His ) 10-tagged cysteine protease domain ( CPD ) to improve the solubility of the target proteins [32] . Indeed , VipD interacted with the GTP-bound Q-to-L mutant form of the two Rabs in a ( His ) 10 pull-down assay ( Figures 3A , second panel and 3B , first panel; lane 5 ) . VipD also interacted with the wild-type version of the two Rabs in the GDP-bound inactive form , although its interaction with Rab5b ( 1-190 ) :GDP was comparatively quite weak ( Figures 3A , second panel and 3B , first panel; lane 3 ) . Quantification of these interactions by isothermal titration calorimetry ( ITC ) revealed that VipD bound tightly to Rab5b ( 1-190;Q79L ) :GTP , but weakly to Rab5b ( 1-190 ) :GDP , with the dissociation constants ( KD ) of 254 nM and 3150 nM , respectively ( Figure 3C ) . In comparison , VipD interacted with both the GTP-bound and the GDP-bound forms of Rab22a ( 1-175 ) tightly with the similar KD values of 132 nM and 123 nM , respectively ( Figure 3C ) . The binding interactions are through the C-terminal domain of VipD , because VipD ( 316-621 ) interacted with Rab5b ( 1-190;Q79L ) :GTP and Rab22a ( 1-175;Q64L ) :GTP similarly as full-length VipD ( Figure 3D ) . The ( His ) 10 pull-down assay was also performed with Rab5a and Rab5c , the two other isoforms of Rab5 . VipD bound to the two forms of Rab5a and Rab5c similarly as it did to Rab5b: tightly to the active form and weakly to the inactive form ( Figure 3A; first and third panels ) . We also examined the interaction between VipD and Rab22b ( also known as Rab31 ) , the other isoform of Rab22 . VipD tightly bound to both the GTP-bound and the GDP-bound forms of Rab22b ( 1-175 ) , as it did to the two forms of Rab22a ( 1-175 ) ( Figure 3B; second panel ) . We , in turn , examined whether these isoforms of Rab5 and Rab22 colocalize with VipD in HeLa cells . The active forms of Rab5a and Rab5c indeed colocalized with VipD , as Rab5b ( Q79L ) did ( Figure S5C ) . However , Rab22b ( Q64L ) did not colocalize with VipD ( Figure S5D ) . Rab22b is known to be largely associated with the trans-Golgi network in HeLa cells [33] . Consistently , the subcellular distribution of Rab22b ( Q64L ) overlapped only partially with that of the endosomal marker Rab22a ( Q64L ) ( Figure S5D ) . These observations implied that the endosomal localization of VipD does not simply depend on the interaction with Rab proteins . To test this notion , a set of small interfering RNAs ( siRNAs ) was prepared which blocked the expression of Rab5a , Rab5b , Rab5c and Rab22a [31] , [34]–[36] . Treatment of HeLa cells with each siRNA alone or together did not block the endosomal localization of VipD ( Figure S6 ) , indicating that VipD localizes to endosomes through an as yet unknown mechanism and then interacts with the endosomal Rab proteins . To learn whether VipD might interact with other Rabs that are known to mediate endosomal trafficking , wild-type and GTPase-defective versions of Rab4b ( 1-178 ) , Rab7a ( 1-190 ) , Rab9a ( 1-185 ) , Rab14 ( 1-189 ) and Rab21 ( 15-200 ) were produced . Additionally , we also produced two other Rabs , Rab1a ( 1-182 ) and Rab2a ( 1-182 ) , which mediate trafficking between ER and Golgi . In the ( His ) 10 pull-down assay , VipD did not exhibit a noticeable interaction with both the active and the inactive forms of all the seven Rab proteins ( Figure S7 ) . Given the protein-binding analyses and the minor structural similarity between the C-terminal domain of VipD and the Vps9 domain of Rabex-5 ( Figure S1B ) , we suspected that VipD might have a GEF activity toward Rab5 and Rab22 . This possibility was tested by fluorescence resonance energy transfer assay using 2′/3′-O- ( N′-methylanthraniloyl ) -GDP ( mant-GDP ) -loaded Rab5b ( 1-190 ) and Rab22a ( 1-175 ) . VipD exhibited no observable GEF activity toward the two Rabs ( Not shown; indirectly shown in Figure 4A ) , and thus it is not a GEF for the two Rabs . An alternative possibility that VipD might competitively inhibit a cellular GEF for Rab5 and Rab22 was examined by performing a GEF activity assay with Rab5b ( 1-190 ) :mant-GDP , Rab22a ( 1-175 ) :mant-GDP and the Vps9 domain ( residues 132-397 ) of Rabex-5 , which is a strong and a comparatively weak GEF for Rab5 and Rab22 , respectively [28] . VipD noticeably but very weakly inhibited the GEF activity of the Vps9 domain; 1000 molar excess of VipD over the Vps9 domain decreased kcat/KM by only about two folds for Rab5b ( 1-190 ) ( Figure 4A; left panel ) . VipD inhibited the weak GEF activity of Rabex-5 toward Rab22a more evidently . However , also in this case , only five folds decrease of kcat/KM was detected when VipD was present at 1000 molar excess over Rabex-5 ( Figure 4A; right panel ) . These results indicate that VipD can interfere with the GEF activity of Rabex-5 but only slightly . These inhibitory effects presumably arise from the binding affinity of VipD for the GDP-bound forms of the two Rabs ( Figure 3 ) . Whether VipD could function as a GTPase-activating protein ( GAP ) for Rab5b was also tested by employing the GAP domain of RabGAP-5 ( residues 1-451 ) , a specific cellular GAP for Rab5 [37] , and performing an enzyme assay designed to detect the phosphate ion released from GTP hydrolysis by Rab5b ( 1-190 ) . Addition of the GAP domain markedly increased the GTP hydrolysis ( Figure 4B ) . In contrast , VipD had no effect on the GTP hydrolysis ( Figure 4B ) , demonstrating that VipD does not function as a GAP for Rab5b . Another possibility was that VipD binding to activated Rab5b and Rab22a prevents the interactions with their direct downstream effectors . Rabaptin-5 and Rabenosyn-5 bind directly to activated Rab5 and mediate endocytic membrane docking and fusion as well as early endosomal trafficking [38]–[41] . In a glutathione S-transferase ( GST ) pull-down assay , GST-tagged Rabaptin-5 ( 739-862 ) , encompassing the Rab5-binding domain of the protein [40] , bound to the GTP-bound form , but not to the GDP-bound form of Rab5b ( Figure 5A; lanes 3 and 4 ) . This complex was disrupted when VipD was challenged in a 1∶1 molar ratio with GST–Rabaptin-5 ( 739-862 ) ( Figure 5A; lane 5 ) . Likewise , VipD disrupted the interaction between Rab5b ( 1-190;Q79L ) :GTP and GST-tagged Rabenosyn-5 ( 1-70 ) , which includes the Rab5-binding domain of the protein ( Figure 5B ) . We also examined whether VipD affects the interaction between Rab22a and its effector protein early endosome autoantigen 1 ( EEA1 ) , whose N-terminal C2H2 Zn2+ finger domain is necessary for binding Rab22a and for controlling endosomal trafficking [42] , [43] . VipD aptly displaced GST–EEA1 ( 36-91 ) bound to Rab22a ( 1-175;Q64L ) :GTP even at a 1∶10 molar ratio between VipD and EEA1 ( 36-91 ) ( Figure 5C; lanes 3 to 5 ) . Consistently with these in vitro displacement assays , the endogenous association between Rab5b and Rabaptin-5 in RAW264 . 7 macrophages was disrupted by the expression of full-length VipD or VipD ( 316-621 ) , but not by the expression of VipD ( 1-316 ) ( Figure 5D ) . What would be the basis for the observed competitive binding of VipD to the activated Rabs ? The Rab effectors commonly make contacts with a predominantly nonpolar surface of their cognate Rab , on which three highly conserved apolar residues ( Phe57 , Trp74 and Tyr89 in human Rab5b; see Figure S8 ) form a hydrophobic triad that is critical for the binding interaction [38] , [40] , [42] , [44] , [45] . In a ( His ) 10 pull-down assay , three Rab5b variants with an alanine substitution of one of the three residues exhibited no or barely detectable interaction with VipD ( Figure 5E ) , pointing that VipD also recognizes the hydrophobic triad and therefore competes with the effector molecules for binding to the activated Rabs . Together , these results indicate that the C-terminal domain of VipD is able to counteract the downstream signaling from the activated form of Rab5 and Rab22 . The capacity of VipD to disrupt the interactions between the three effectors and Rab5b or Rab22a strongly suggested that VipD interferes with endosomal trafficking leading to the degradation of endocytic materials . We therefore analyzed the effect of VipD expression on the transport and the degradation of exogenously added DQ-Red bovine serum albumin ( BSA ) , which emits red fluorescence upon proteolytic degradation and is used as a sensitive indicator of lysosomal activity . In lipopolysaccharide ( LPS ) -treated RAW264 . 7 mouse macrophages , the degradation of DQ-Red BSA was significantly attenuated in cells stably expressing full-length VipD or VipD ( 316-621 ) compared with that in cells expressing vector alone or VipD ( 1-316 ) ( Figures 6A and 6B ) . Furthermore , expression of full-length VipD or VipD ( 316-621 ) also blocked the degradation of phagocytosed E . coli in RAW264 . 7 cells , while the bacteria were disintegrated within 24 hours in macrophages expressing vector alone or VipD ( 1-316 ) ( Figure 6C ) . Next , time-course confocal microscopy was performed to identify which step of the endocytic degradation pathway was affected by VipD ( Figure 6D ) . LPS is recognized by the Toll-like receptor 4 ( TLR4 ) –MD-2 complex and induces endocytic internalization and consequent lysosomal degradation of the receptor complex [46] . TLR4 was internalized into the RAW264 . 7 macrophage cytoplasm and colocalized with the early endosomal marker EEA1 within 20 min after LPS treatment , regardless of the expression of any VipD constructs ( Figure 6D; left panels ) , indicating that VipD does not interfere with the formation of endocytic vesicles or their heterotypic fusion with early endosomes . Critically , in 1 hour after LPS treatment , TLR4 colocalized with the late endosomal/lysosomal marker lysosome-associated membrane protein-1 ( LAMP-1 ) in cells expressing vector alone or VipD ( 1-316 ) , but not in cells expressing full-length VipD or VipD ( 316-621 ) ( Figure 6D; right panels ) . These results suggest that VipD might block the endosome maturation step in macrophage cells via the C-terminal domain . Stably expressed Rab5c was shown to be excluded from L . pneumophila-containing phagosomes in HeLa cells [47] . We sought to examine whether endogenous Rab5 might be excluded , and if it is , VipD might be responsible for the exclusion . C57BL/6 mouse bone marrow-derived macrophages ( BMDM ) and three different L . pneumophila mutant strains were prepared: Lp03 ( dotA-deficient type IV secretion system-defective ) , ΔflaA ( flagellin-gene deficient ) and ΔvipD/ΔflaA ( vipD and flaA-deficient ) . However , we found that endogenous Rab5b does not localize to the LCV in L . pneumophila-infected macrophages regardless of the strain background ( Figure S10A; columns 1–3 ) . In a positive control experiment , endogenous Rab1b localized to the LCV in cells infected by the ΔflaA or ΔvipD/ΔflaA strain but not in cells infected by the Lp03 strain ( Figure S10A; columns 4–6 ) . Similar results were obtained with two different cell lines ( macrophage-like human monocytic leukemia U937 and human alveolar basal epithelial A549 cells ) , which were infected by the L . pneumophila strain Lp02 ( wild-type ) or ΔvipD ( vipD-deficient ) . In both type of cells , Rab5b did not localize to the LCV , irrespective of the presence of VipD ( Figures S10B and S10C; rows 1–2 ) . In contrast , Rab1b localized to the LCV in both types of cells infected by the Lp02 strain ( Figures S10B and S10C; row 3 ) . These observations reinforce the notion that Rab5 is excluded from the LCV , and suggest that at least VipD is not responsible for this exclusion . As expected , the Rab5 effectors EEA1 and Rabaptin-5 did not localize to the LCV , irrespective of the presence of VipD in these infected cells ( Figures S10B and S10C; rows 4–7 ) .
L . pneumophila resides and replicates in macrophages , which is at the forefront against infectious agents . To understand L . pneumophila's strategies to evade the immune defense of macrophages , it is critical to know how pathogen's effector proteins manipulate host molecules . However , such information is yet very limited . Through elegant studies [6]–[12] , [17] , [48]–[51] , a number of L . pneumophila effectors , SidM/DrrA , SidD , LepB , AnkX and LidA , have been identified to target host Rab proteins , especially and commonly Rab1 , a key regulator of ER-to-Golgi vesicle trafficking . Dysregulation of Rab1 by these effectors enables L . pneumophila to divert ER-derived vesicles to the LCV for the supply of nutrients and membrane components , highlighting that ER-to-Golgi vesicle trafficking is an important target for the intracellular growth of the pathogen . The study presented herein shows that endosomal vesicle trafficking is also targeted by L . pneumophila via VipD that blocks downstream signaling from Rab5 and Rab22 . These two Rabs compose a Rab22–Rabex-5–Rab5 signaling relay [52] , where activated Rab22 recruits Rabex-5 , the GEF promoting the GDP-to-GTP exchange on Rab5 [28] , [29] . Activated Rab5 then recruits downstream effector proteins such as Rabaptin-5 , Rabenosyn-5 and EEA1 , which mediate diverse endosomal processes including vesicle fusion and membrane trafficking [39] , [41] , [53] . In addition , Rab22a regulates the formation of tubular recycling endosomes , which are necessary for endosome-to-plasma membrane recycling trafficking of internalized materials [31] . We show that VipD specifically and potently interacts with the two endosomal Rabs , blocking their binding interactions with the three downstream effectors through its C-terminal domain . In the interaction of VipD with Rab5 and Rab22 , three features are outstanding . First , VipD primarily targets the activated form of the two Rabs . Second , while activated Rab5 and Rab22 interact with their effector molecules weakly ( KD>0 . 9 µM ) [38] , [42] , the binding affinity of VipD for these Rabs is exceedingly higher ( KD<254 nM ) . Third , VipD recognizes the conserved hydrophobic triad ( Phe-Trp-Tyr ) , which is a common binding motif in diverse Rabs for the interaction with their downstream effector molecules [38] , [40] , [42] , [44] , [45] . These three features should enable VipD to potently block the downstream signaling from Rab5 and Rab22 by abrogating their association with the three effector molecules we tested in this study and probably with other effectors . To our knowledge , VipD is the first established example of a pathogen protein that antagonizes downstream signaling through binding to an activated Rab to competitively inhibit the binding of effector molecules . Of note , VipD does not interact with Rab7 ( Figure S7 ) , which replaces Rab5 on early endosomes [54] and mediates endosomal-lysosomal trafficking [55] . VipD also does not interact with Rab4b , Rab9a , Rab14 and Rab21 ( Figure S7 ) , which are known to mediate endosome-related trafficking [30] . Therefore , the observed endosomal trafficking block by VipD is most likely through selectively inhibiting the function of Rab5a , Rab5b , Rab5c and Rab22a . In this study , we also confirmed that VipD has a phospholipase A2 activity and that Ser73 and Asp288 , invariant in cPLA2 , VipD , VpdA , VpdB and ExoU [22] , constitute a catalytic dyad in VipD ( Figures 1B and 1C ) . Since the N-terminal lipase domain of VipD is dispensable for VipD to localize to endosomes ( Figures 2 and S3 ) , to bind Rab proteins ( Figure 3D ) and to perturb endosomal trafficking ( Figures 6 and S4B ) , the role of this domain is elusive . As VipD localizes to endosomes , one possibility is that VipD exhibits its catalytic activity on the endosomal membrane , the consequence of which remains to be elucidated . In summary , the structural and biochemical analyses identified VipD as a signal blocker disabling the key endosomal regulators Rab5 and Rab22 . As phagocytic vesicles could undergo fusion with lysosomes , our findings raise an important question of whether VipD facilitates the survival of L . pneumophila in macrophage , which needs further investigation . Our observations also form rational grounds for future investigations to delineate the role of the lipase activity of VipD and to decipher the functional roles of the C-terminal domain of the VipD-related bacterial effectors VpdA and VpdB , which are also translocated into host cells .
The crystals of native VipD ( 1-575 ) were obtained by the hanging-drop vapor diffusion method at 22°C by mixing and equilibrating 1 . 5 µL of the final VipD ( 1-575 ) sample ( 16 mg/mL ) and 1 . 5 µL of a precipitant solution containing 100 mM Tris-HCl ( pH 8 . 0 ) , 1 . 0 M ammonium citrate tribasic ( pH 7 . 0 ) and 10 mM MgCl2 . The crystals of selenomethionine-substituted VipD ( 1-575 ) grew from a mixture of 100 mM MES ( pH 6 . 0 ) and 1 . 3 M ammonium sulfate . Before data collection , the crystals were immersed in the precipitant supplemented with 30% glycerol and incubated overnight at −20°C . This dehydration process at high glycerol concentration improved the resolution of X-ray diffraction; from typical 5 Å up to 2 . 9 Å . The crystals were plunged into liquid nitrogen before X-ray data collection . X-ray data sets were collected using synchrotron X-ray radiation . The structure was determined by single-wavelength anomalous dispersion phasing using a selenomethionine-substituted VipD ( 1-575 ) crystal with the programs SHELX [56] and autoSHARP [57] . Subsequently , model building and refinement were carried out using the programs COOT [58] and CNS [59] . The final model does not include residues 559–575 , whose electron densities were not observed or very weak . Crystallographic data statistics are summarized in Table 1 . Full-length VipD ( wild-type , S73A or D288A ) , VipD ( 1-575 ) , VipD ( 316-621 ) , 31 different Rab constructs , the GEF domain of Rabex-5 , the Rab5-binding domains of Rabaptin-5 and Rabenosyn-5 , the Rab22-binding domain of EEA1 , and the GAP domain of RabGAP-5 were prepared for crystallization or biochemical assays , the details of which are described in Text S1 . For ( His ) 10 pull-down assays , 25 µM of Rab–CPD– ( His ) 10 and 37 . 5 µM of VipD or VipD ( 316-621 ) were incubated at room temperature for 30 min and mixed with 30 µL of Co2+ resin . The resin was washed four times with a buffer solution containing 20 mM Tris-HCl ( pH 7 . 5 ) , 100 mM NaCl and 2 mM MgCl2 , and subjected to denaturing polyacrylamide gel electrophoresis . For quantification of protein-protein interaction , ITC measurements were carried out at 25°C on a microcalorimetry system iTC200 ( GE Healthcare ) . Protein samples were prepared in a buffer solution containing 20 mM Tris-HCl ( pH 7 . 5 ) and 100 mM NaCl . The samples were centrifuged to remove any residuals prior to the measurements . Dilution enthalpies were determined in separate experiments ( titrant into buffer ) and subtracted from the enthalpies of the binding between the proteins . Data were analyzed using the Origin software ( OriginLab ) . For the subcellular localization analysis , HeLa cells and mouse macrophage RAW264 . 7 cells were transfected with the pEYFP-N1 or pECFP-C1 vectors ( Clontech ) encoding Rab or VipD proteins and visualized by confocal microscopy . For the analysis of endocytic trafficking , RAW264 . 7 cells were transfected with the pCDH-CMV vector ( System Biosciences ) encoding VipD proteins , and stable cell lines were established by puromycin selection . The details of mammalian cell culture , immunoblotting , flow cytometry and live cell imaging are described in Text S1 . The coordinates of the VipD ( 1-575 ) structure together with the structure factors have been deposited in the Protein Data Bank with the accession code 4AKF .
|
Legionella pneumophila is a pathogen bacterium that causes Legionnaires' disease accompanied by severe pneumonia . Surprisingly , this pathogen invades and replicates inside macrophages , whose major function is to detect and destroy invading microorganisms . How L . pneumophila can be “immune” to this primary immune cell has been a focus of intensive research . Upon being engulfed by a macrophage cell , L . pneumophila translocates hundreds of bacterial proteins into this host cell . These proteins , called bacterial effectors , are thought to manipulate normal host cellular processes . However , which host molecules and how they are targeted by the bacterial effectors are largely unknown . In this study , we determined the three-dimensional structure of L . pneumophila effector protein VipD , whose function in macrophage was unknown . Ensuing analyses revealed that VipD selectively and tightly binds two host signaling proteins Rab5 and Rab22 , which are key regulators of early endosomal vesicle trafficking . These interactions prevent the activated form of Rab5 and Rab22 from binding their downstream signaling proteins , resulting in the blockade of endosomal trafficking in macrophages . The presented work shows that L . pneumophila targets endosomal Rab proteins and delineates the underlying molecular mechanism , providing a new insight into the pathogen's strategies to dysregulate normal intracellular processes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"proteins",
"protein",
"structure",
"biology",
"microbiology",
"host-pathogen",
"interaction",
"bacterial",
"pathogens"
] |
2012
|
VipD of Legionella pneumophila Targets Activated Rab5 and Rab22 to Interfere with Endosomal Trafficking in Macrophages
|
Lymphatic filariasis is a major tropical disease caused by the parasite Brugia malayi . Microfilariae ( Mf ) circulate in the peripheral blood for 2–3 hours in synchronisation with maximal feeding of the mosquito vector . When absent from the peripheral blood , Mf sequester in the capillaries of the lungs . Mf are therefore in close contact with vascular endothelial cells ( EC ) and may induce EC immune function and/or wound repair mechanisms such as angiogenesis . In this study , Mf were co-cultured with human umbilical vein EC ( HUVEC ) or human lung microvascular EC ( HLMVEC ) and the transendothelial migration of leukocyte subsets was analysed . In addition , the protein and/or mRNA expression of chemokine , cytokine and angiogenic mediators in endothelial cells in the presence of live microfilariae were measured by a combination of cDNA arrays , protein arrays , ELISA and fluorescence antibody tests . Surprisingly , our findings indicate that Mf presence partially blocked transendothelial migration of monocytes and neutrophils , but not lymphocytes . However , Mf exposure did not result in altered vascular EC expression of key mediators of the tethering stage of extravasation , such as ICAM-1 , VCAM-1 and various chemokines . To further analyse the immunological function of vascular EC in the presence of Mf , we measured the mRNA and/or protein expression of a number of pro-inflammatory mediators . We found that expression levels of the mediators tested were predominantly unaltered upon B . malayi Mf exposure . In addition , a comparison of angiogenic mediators induced by intact Mf and Wolbachia-depleted Mf revealed that even intact Mf induce the expression of remarkably few angiogenic mediators in vascular EC . Our study suggests that live microfilariae are remarkably inert in their induction and/or activation of vascular cells in their immediate local environment . Overall , this work presents important insights into the immunological function of the vascular endothelium during an infection with B . malayi .
The filarial parasite Brugia malayi is a causative agent of human lymphatic filariasis in South and South-East Asia . B . malayi is transmitted by mosquitoes , which take up the blood-borne microfilarial stage ( Mf ) of the parasite . For the majority of the day , Mf sequester predominantly in the lungs of the host and they only appear in the peripheral blood circulation for a few hours , which coincides with maximal mosquito feeding [1] , [2] . While sequestered in the lungs , B . malayi Mf are likely to interact with vascular endothelial cells ( EC ) and we have observed them binding to the surface of vascular EC ( manuscript in preparation ) . Helminths are potent modulators of the immune response and filarial nematodes , in particular , have been shown to influence the secretion of inflammatory mediators from a number of different cell types [3] , [4] , [5] . Vascular EC themselves can modulate the immune response by producing pro-inflammatory cytokines and chemokines , in addition to several angiogenic mediators . Vascular EC also play a critical role in extravasation of leukocytes to the site of inflammation [6] , [7] . To our knowledge no studies have addressed induction of local immune or inflammatory responses by vascular EC to live microfilariae of lymphatic filarial parasites . However , Bennuru et al . ( 2009 ) have shown that lymphatic EC ( LEC ) proliferate in response to adult , but not microfilarial , antigen and live parasites can induce tube formation by LEC in a contact-dependent manner . B . malayi microfilarial antigen also induced a number of angiogenic mediators in LEC . These data , together with an increased expression of angiogenesis and lymphangiogenesis mediators found in sera of humans infected with Wuchereria bancrofti , suggest that lymphatic filarial parasites may directly influence inflammation and angiogenesis [8] , [9] , [10] . Other helminths have been shown to induce pro-inflammatory mediators in EC , for example , Schistosoma mansoni schistosomulae stimulate production of the inflammatory cytokines , IL-6 and IL-7 [11] , [12] . In this study , we investigated B . malayi Mf-induced immune responses in the local environment by modelling the interaction of Mf and vascular EC in vitro . Live B . malayi Mf directly inhibited extravasation of both neutrophils and monocytes , but not lymphocytes . However , Mf induced limited immune and angiogenic mediator expression . Several previous studies have shown that the filarial endosymbiotic bacteria , Wolbachia are partially responsible for induction of inflammatory and angiogenic mediators in filarial patients [8] . However , a comparison of angiogenic mediator mRNA expression induced by Wolbachia-depleted and live intact Mf , revealed that few angiogenic mediators were specifically induced by Wolbachia in vascular EC .
Ethical approval was obtained from the East London Local Research Ethics Committee to collect human umbilical cords from mothers from the Royal London Hospital and blood from healthy donors . All study participants provided written informed consent . Parasites were obtained from infected animals in accordance with our Home Office project licence , which was approved under the Home Office ( 1986 ) Scientific Procedures Act . Human umbilical vein endothelial cells ( HUVEC ) were isolated from human umbilical cords using a modified previously published method [13] . In all experiments , HUVEC were used at passage 5 . Cell morphology was confirmed by phase contrast microscopy . HUVEC were cultured in HUVEC medium ( M199 supplemented with 150 U/ml penicillin , 150 U/ml streptomycin , 2 mM L-glutamine , 20% heat-inactivated FBS , 1 U/ml heparin and 0 . 03 mg/ml endothelial cell growth supplement from bovine neural tissue ) . Cryopreserved human lung microvascular endothelial cells ( HLMVEC ) were purchased from Clonetics ( UK ) and were cultured according to the supplier's recommendations . HLMVEC were used for experiments at passage 7–9 . Infected gerbils ( Meriones unguiculatus ) were obtained from TRS Laboratories , Athens , Georgia , USA . Infection of gerbils was performed by i . p . injection of 400 B . malayi L3 . B . malayi Mf were obtained by peritoneal lavage with RPMI-1640 , 100–400 days post infection . Mf were isolated by centrifugation of recovered lavage fluid over lymphocyte separation medium ( MP Biomedicals , USA ) . To harvest Wolbachia-depleted Mf , gerbils were treated with tetracycline in their drinking water ( 2 . 5 mg/ml ) for a period of 6 weeks [14] . Following treatment , Mf were isolated , genomic DNA extracted and the ratio of Brugia glutathione S-transferase ( gst ) to Wolbachia surface protein ( wsp ) copy numbers was measured by qPCR as previously described [15] . Using this measurement , the two batches of Mf isolated for use in Wolbachia-depletion experiments were shown to be 98 . 46% and 99 . 84% Wolbachia-free . 1×106 confluent HUVEC at passage 4 were cultured in HUVEC medium . After 60 hours of incubation the medium in each flask was replaced with co-culture medium ( 50% HUVEC medium ( as above ) plus 50% RPMI-1640 supplemented with 150 U/ml penicillin , 150 U/ml streptomycin , 2 mM L-glutamine , 20 mM HEPES , 20% heat-inactivated FBS and 20% of glucose solution ) containing 125 , 000 B . malayi Mf . Co-culture medium without B . malayi Mf was added to HUVEC in control flasks . After 24 hours of co-culture , EC or the EC supernatant were collected for further investigation . In some experiments , EC were stimulated with 10 ng/ml IFN-γ ( ImmunoContact , USA ) for 24 or 48 hours prior to co-culture with Mf . When HLMVEC were co-cultured with Mf , 50% EGM-2 MV BulletKit medium ( Clonetics ) was used in place of HUVEC medium . With approval from East London Local Research Ethics Committee whole human blood was collected in 20 U/ml heparin . Peripheral blood mononuclear cells ( PBMC ) were isolated using lymphocyte separation medium . The intermediate layer of PBMC was collected , washed twice and re-suspended in complete RPMI-1640 and 10% FBS . To isolate granulocytes , the pellet remaining from the lymphocyte separation medium was re-suspended in a 50∶50 mix of RPMI-1640/10% FBS and 0 . 9% NaCl . The final solution was supplemented with 3% dextran . After one hour the upper layer was removed and centrifuged at 129×g for 10 minutes at 4°C . The pellet was re-suspended in ice cold 0 . 2% NaCl for 30 seconds . An equal volume of ice cold 1 . 6% NaCl was added and the mixture was centrifuged at 129×g for 6 minutes at 4°C . This process was repeated until the cell pellet was free of red blood cells . After the final wash , granulocytes were re-suspended in RPMI-1640 supplemented with 10% FBS and kept on ice until use . 1×105 HUVEC were added to human fibronectin-coated cell culture inserts in the wells of a 24-well plate ( Greiner Bio-One ) . 6 h later HUVEC were stimulated with human TNF-α at a concentration of 20 ng/ml . After another 18 h , 50% medium was removed from each transwell and replaced with complete RPMI-1640 20% FCS 20% glucose solution supplemented with 12 , 500 Mf . In control conditions , no Mf were added . After another 24 h , 50% of medium was removed from each transwell and replaced with RPMI-1640 supplemented 10% FBS and either 1×106 PBMC or 1×106 granulocytes . RPMI-1640 plus 10% FBS was added into the lower wells . After 4 hours transmigrated cells were harvested from the lower wells and analysed by flow cytometry and/or cytospin . For cytospin analyses , cells were centrifuged in a cytospin at 800×g for 5 minutes . The slides were fixed with 50% acetone: 50% methanol for 2 minutes and stained with May-Gruenwald stain for 10 minutes . Cell morphology was examined by phase contrast microscopy . Granulocytes transmigrating through the endothelial monolayer were 100% neutrophils . For chemotaxis experiments , unstimulated HUVEC were co-cultured with Mf in the lower well and after 24 h either 1×106 PBMC or granulocytes were added in RPMI-1640 supplemented with 10% FBS into the upper well . After 4 h , cells that had migrated into the lower well were analysed by flow cytometry . Mouse anti-human CD8 antibodies were prepared by growing the OKT8 hybridoma in RPMI-1640/10% FBS in vitro . Supernatant was harvested after 7 days and centrifuged at 2 , 057×g for 10 minutes . Antibodies were purified over protein G sepharose . Mouse anti-human CCR5 ( BD ) , mouse anti-human CD14 ( 26ic ) ( in-house ) , mouse anti-human CD8 ( OKT8 ) ( in-house ) , PE-conjugated mouse anti-CD56 ( eBioscience ) , FITC-conjugated mouse anti-human CD3 ( eBioscience ) , PE-Cy5-conjugated mouse anti-human CD16 ( BD Pharmingen ) and the isotype control antibodies FITC–conjugated mouse IgG1 ( BD Pharmingen ) , PE-Cy5–conjugated mouse IgG1 ( eBioscience ) and PE–conjugated IgG2a ( BD Pharmingen ) were used to stain cells . Goat anti-mouse IgG FITC conjugated antibodies ( Sigma ) were used as a secondary antibody with unconjugated primary antibodies . Negative control samples for unconjugated primary antibodies were solely stained with this secondary antibody . Data was acquired using a FACS Canto II ( BD Oxfordshire UK ) and analysed with FlowJo software ( Tree Star Incorporation ) . HUVEC were washed twice with ice-cold PBS . Cells were lysed using RIPA Buffer ( 20 mM MOPS , 150 mM NaCl , 1 mM EDTA , 1% Igepal , 1% Sodium deoxycholate and 0 . 1% SDS supplemented with a 1∶1000 concentration of protease inhibitor mix ( Sigma ) ) . Genomic DNA was broken up by mechanical syringe action . The lysates were centrifuged at 10 , 400×g for 10 minutes at 4°C . The supernatant was kept at −80°C until use . The protein concentration was measured using a BCA protein assay ( Pierce ) . The cytokine protein levels in supernatants were analysed using protein arrays ( RayBioTech ) according to the manufacturer's instructions . The dot intensity on the membranes when exposed to X-ray film was measured using QuantityOne Software ( BioRad Laboratories ) . Subsequently , the levels of cytokines were analysed using the RayBio Analysis Tool for the human cytokine antibody array I ( RayBioTech ) . Protein expression was detected in cell lysates by SDS-PAGE followed by Western blotting . Blots were incubated with mouse anti-human heme oxygenase-1 ( HO-1 ) ( BD transduction Laboratories ) or mouse anti-human β-actin antibodies . HRP-conjugated rabbit anti-mouse ( Dako ) antibody was used for detection and developed with SuperSignal West Pico Chemiluminescent Substrate ( Pierce ) . ELISA was used to measure human IL-1β , TNF-α , IL-6 , IL-8 , CCL2 , TGF-β1 ( R&D Systems ) and IL-13 ( Pelikine Compact ) in EC supernatant or lysate according to the manufacturer's instructions . Total EC RNA was harvested using QIAShredder and RNeasy kit as advised by the manufacturer ( Qiagen , Brighton UK ) . RNA quantity and quality were evaluated using the NanoDrop ND-1000 spectrophotometer . Total RNA integrity was verified using agarose gel electrophoresis and ensuring that 18 and 28S ribosomal RNA bands were intact . Oligo microarrays for chemokines and chemokine receptors ( Supp . Table 1–2 ) , and angiogenesis mediators ( Supp . Table 5 ) were purchased from SuperArray Bioscience ( UK ) and were also used according to the manufacturer's instructions . The dot intensity of the oligo microarrays when exposed to X-ray film was measured using GE Array Analysis Suite ( SuperArray Bioscience ) . Sample values were considered to be different , if both values from two duplicate experiments were either lower or higher in gene expression units than the comparative samples , and if the means of the duplicates differed by at least a factor of 4 in gene expression units . The reference value for β-actin in these experiments was 1 ( chemokine & chemokine receptors ) or 11 ( angiogenesis mediators ) gene expression units . cDNA was synthesised from 1 µg total RNA using the QuantiTect Reverse Transcription kit ( Qiagen ) following the manufacturer's instructions . Primer sequences used and Entrez accession numbers for each gene are outlined in Supp . Table 4 . Primers were designed using the Primer-3 Web-Software ( Whitehead Institute for Biomedical Research , MA , USA ) and purchased from MWG-Biotech ( Ebersberg , Germany ) . Real-time qRT-PCR was performed as previously published [16] and quantification analysis was carried out using the MJ Research Opticon 3 . 1 software from standard curves with correlation coefficient ( r2 ) greater than 0 . 98 . Gene expression data was normalised to total RNA and presented as copy numbers . Specificity and purity of amplificons were verified from melting curves and agarose gel electrophoresis . The Students t-test for paired data was used in all statistical analyses and performed with Prism 4 software ( GraphPad Software , Inc ) . P values<0 . 05 were taken to be statistically significant . All data are presented as mean ± standard deviation .
Presence of B . malayi microfilariae in the blood vessels may alter transmigration of leukocytes across the vascular endothelium . In order to investigate this , TNF-α - stimulated HUVEC were co-cultured with or without live Mf in transwells of a transmigration assay plate and the ability of PBMC or neutrophils to transmigrate through the confluent HUVEC monolayer was analysed . The presence of live Mf did not affect the total number of extravasated lymphocytes , CD3+ ( T cells ) , CD8+ cells or CD3−CD56+CD16− ( NK cell subset ) ( Figure 1a–d ) . However , the transendothelial migration of neutrophils and CD14+ , CD3−CD56−CD16+ and CD3−CD56+CD16− monocytes was significantly inhibited in the presence of live Mf ( p<0 . 05 ) ( Figure 1e–h ) . To investigate whether Mf altered the chemotactic ability of leukocytes and/or the ability of vascular EC to chemoattract , the chemotaxis of lymphocytes and neutrophils to HUVEC in the presence of Mf was analysed . Interestingly , neutrophils were more strongly attracted to HUVEC than lymphocytes , however Mf presence did not significantly alter the chemotactic ability of either leukocyte subset ( Figure 2 ) . Altered expression of adhesion molecules and/or chemokines by vascular EC may inhibit the extravasation of leukocytes . To further investigate the mechanism of reduced monocyte and neutrophil extravasation in Mf presence , the key adhesion molecules , ICAM-1 and VCAM-1 , expressed by HUVEC were measured . The presence of B . malayi Mf did not alter the surface expression of these adhesion molecules ( Figure 3a–b ) . The chemokines , CCL2 ( MCP-1 ) and IL-8 are potent inducers of monocyte and neutrophil extravasation , respectively . In endothelial cell biology the amount of chemokine secreted corresponds to the level of chemokine presented at the vascular surface . Therefore , CCL2 and IL-8 were measured by ELISA , in the supernatants of HUVEC cultured with or without Mf . However , the presence of B . malayi Mf did not have a significant effect on the up- or down-regulation of either CCL2 or IL-8 ( Figure 3c–d ) . To further investigate whether B . malayi Mf alter the EC expression of immune mediators in their immediate environment , a comprehensive analysis of cytokine and chemokine mRNA expression was performed by oligo microarray ( Figure 4a , Supp . Table 1 and 2 ) . Since Mf are situated in the lung capillaries for long periods of time , in addition to HUVEC , we also used HLMVEC , as the latter may more closely resemble EC in the locality of Mf in vivo . Within the stringency criteria of our experiments , neither cytokine nor chemokine mRNA expression in vascular EC was found to be altered in live Mf presence ( Figure 4a ) . However , the mediators with the highest fold increases in mRNA expression in the presence of Mf were almost identical between the two different vascular EC , HUVEC and HLMVEC . These mediators were CCL1 , CCL23 , IL-1α , C5 , and the chemokine receptors CCR5 and CCR10 ( Figure 4a ) . To investigate whether live Mf stimulate and/or down-regulate the immune function of vascular EC , secretion of pro- and anti-inflammatory cytokines and chemokines was measured in the supernatants of HUVEC following exposure to Mf ( Figure 4b–d ) . Initially , an exhaustive exploration of cytokines and chemokines produced by HUVEC in the presence of B . malayi Mf , was conducted by protein expression array in culture supernatants ( Figure 4b , Supp . Table 3 ) . Mf presence appeared not to significantly alter the secretion of any of the immune mediators tested . Indeed the array confirmed our previous results that CCL2 and IL-8 are not altered in Mf presence ( Figure 3c–d and 4b ) . Although high levels of GRO family members ( CXCL1 , CXCL2 , CXCL3 ) were detected , expression of these chemokines was not significantly enhanced by Mf . Key inflammatory cytokines known to be produced by EC were also measured by ELISA ( Figure 4c–d , and data not shown ) . In confirmation of the protein array data , the secretion of IL-6 , TGF-β1 , TNF-α and IL-1β by HUVEC was not altered in Mf presence . Indeed , IL-1β and TNF-α were not detected in the HUVEC supernatant in the presence or absence of Mf ( data not shown ) . IL-13 was not found in HUVEC supernatants but was detected in HUVEC lysates by ELISA ( Figure 4e ) , however , live Mf did not alter the protein expression of this cytokine . While the oligo microarray analysis did not show any mediators significantly up- or down-regulated in HUVEC or HLMVEC in the presence of Mf; we sought to more definitively determine whether the mediators with highest mRNA expression levels were altered by Mf . Therefore , we used qRT-PCR to analyse the mRNA levels of selected genes . In accord with the oligo microarray data and the applied analysis criteria , qRT-PCR confirmed that HUVEC mRNA expression of CCL1 ( not detected ) , CCL23 and IL-1α were not altered by Mf presence ( Figure 5a–b ) . In addition , Mf presence caused no alteration in CCL1 ( not detected ) and IL-1α mRNA expression in HLMVEC ( Figure 5b ) . However , CCL23 mRNA was significantly ( p<0 . 0001 ) downregulated upon Mf exposure . Interestingly , Mf presence also caused a down-regulation of the mRNA levels of pro-inflammatory C5 in both HUVEC and HLMVEC as analysed by qRT-PCR ( Figure 5c ) . Expression of the chemokine receptors , CCR5 and CCR10 , were also further analysed in both HUVEC and HLMVEC exposed to live Mf ( Figure 6a–c ) . Initially , HUVEC co-cultured with or without B . malayi Mf were analysed by flow cytometry for surface expression of CCR5 ( Figure 6a ) . CCR5 was found to be significantly upregulated on the surface of HUVEC exposed to live Mf ( p<0 . 05 ) . However , mRNA expression analysis of HUVEC and HLMVEC CCR5 by qRT-PCR did not show alteration in the presence of live Mf . Furthermore , qRT-PCR for CCR10 revealed that live Mf increased mRNA in both HUVEC and HLMVEC , however this was only significant in HLMVEC ( p<0 . 05 ) ( Figure 6c ) . The oligo microarray analysis of other chemokine receptors revealed no other differences in mRNA expression in either HUVEC or HLMVEC in the presence of Mf ( Figure 4a ) . In some instances therefore , discrepancies existed between the recognition of mRNA by the primers used in qRT-PCR and the sensitivity of the probes used on the oligo-microarray . Live Mf could be responsible for increased levels of pro-angiogenic mediators found in the sera of filarial patients [8] , [9] . Furthermore , previous studies have suggested that the filarial endosymbiotic bacteria , Wolbachia , may induce angiogenesis [8] . In order to investigate whether live Mf induce angiogenic mediators in EC , the mRNA expression of these mediators in HUVEC and HLMVEC following co-culture with B . malayi Mf was analysed ( Figure 7 , Supp . Table 5 ) . In addition , to determine whether Wolbachia endosymbionts are responsible for any angiogenic mediator induction , oligo microarray of mRNA from EC cultured with either intact Mf or Mf-depleted of Wolbachia were compared in two separate experiments . These studies showed that angiogenic factors were not altered in HUVEC in the presence of either intact Mf or Wolbachia-depleted Mf ( Figure 7a ) . A qRT-PCR analysis of several mediators with the highest fold change expression in Mf presence ( angiopoietin-2 ( Ang-2 ) , brain-specific angiogenesis inhibitor-1 ( BAI-1 ) , tumor necrosis factor superfamily member 15 ( TNFSF15 ) , cyclooxygenase-2 ( COX-2 ) and CCL11 ) , confirmed these results ( Figure 7b , Supplementary Figure 1 ) . However , in HLMVEC , Ang-2 mRNA was downregulated and the angiostatic factor TNFS15 was upregulated by live Mf ( Figure 7b , d ) . Further analysis of the pro-angiogenic mediator COX-2 , showed that this mediator was upregulated in HLMVEC , but not HUVEC , by Mf presence ( Figure 7b ) . Live B . malayi Mf . enhanced , protein expression of the hypoxia-induced product , heme oxygenase-1 ( HO-1 ) , in HLMVEC after 6 , 12 and 24 h of co-culture with Mf ( Figure 7f ) . Following IFN-γ-stimulation , HO-1 was no longer detectable at any of these time points . Interestingly live Mf also induced relatively high levels of hypoxia-inducible factor ( HIF-1α ) mRNA in HLMVEC ( Figure 4a ) . Presence of HIF-1α is an indicator of hypoxia which in turn is a potent promoter of angiogenesis .
In an area endemic for lymphatic filariasis , the majority of people have asymptomatic infection and harbour several million Mf in their blood stream . Vascular EC play an important role in mediating immune and angiogenic responses . Therefore , maintenance of this asymptomatic condition , as well as survival of B . malayi Mf in the blood stream , could depend upon Mf-driven modulation of EC activity . In this study we sought to investigate the vascular EC response upon exposure to live B . malayi Mf . We found that the transendothelial migration of monocytes and neutrophils , but not lymphocytes , is inhibited by live Mf presence; while either intact or Wolbachia-depleted Mf stimulate few cytokines , chemokines or angiogenic mediators . Both macrophages and neutrophils are capable of killing B . malayi Mf in vitro [17] , [18] , [19] . Reduced extravasation of monocytes and neutrophils could therefore lead to retention of effector leukocytes in the vascular location of the parasite , resulting in increased clearance of Mf . Indeed , reduced eosinophil extravasation , in eotaxin-1−/− mice infected with B . malayi Mf , lead to eosinophil retention in the blood stream and enhanced Mf clearance [20] . Both monocytes and neutrophils appear to kill Mf via production of reactive intermediates , however , in turn , Mf can partially neutralise the toxic effects of these intermediates by secreting anti-oxidant enzymes such as peroxidases and superoxide dismutase [17] , [21] , [22] , [23] . There are a number of potential mechanisms , which could result in the inhibition of monocyte and neutrophil transendothelial migration in the presence of Mf . In general , leukocyte extravasation is a multi-step cascade involving rolling mediated by selectin-selectin ligand axes , tethering mediated by integrin-adhesion molecule axes strengthened by chemokine-triggered activation and finally , diapedesis [24] . Selectin-selectin ligand axes are unlikely to have a functional role in the static transendothelial migration experiments performed in this study . Furthermore , HUVEC surface expression of the adhesion molecules ICAM-1 and VCAM-1 , which have crucial roles at the tethering step , was not modulated upon Mf exposure . Another potential mechanism investigated was the possibility that alteration ( s ) in chemokine expression in the presence of Mf selectively interfered with leukocyte tethering . IL-8 and CCL2 are considered to be the most important chemokines for the transendothelial migration of neutrophils and monocytes respectively [25] . However , Mf presence had no effect on IL-8 or CCL2 production by EC . In accord with this , a comprehensive examination ( by oligo microarray , qRT-PCR and protein array ) of chemokines in EC exposed to Mf , did not reveal any major differences in these or other chemokines that may have a role in extravasation of monocytes and neutrophils . No alteration in the transendothelial migration of whole T cells , CD8+ cells or NK cells was observed in Mf presence . Interestingly , in agreement with our study , experiments in mice implanted with adult B . malayi or Mf in vivo showed that in the presence of Mf alone , infiltration of leucocytes into the peritoneal cavity is reduced in comparison to adult nematode implanted mice [26] . In addition , the proportion of macrophages within these leukocyte populations was significantly lower in Mf implanted rather than adult implanted mice [26] . Previous work has also shown that a serine protease derived from B . malayi Mf abolishes C5a-mediated chemotaxis of granulocytes [27] . Furthermore both adult B . malayi and Mf extracts inhibit hyper-permeability induced by TNF-α or IL-1α , of lymphatic EC monolayers to dextran . Although neither extract showed any effect on the permeability of confluent EC per se [10] . Dirofilaria immitis adult extracts , however , did reduce the transendothelial permeability of a human EC line . Enhanced expression of tight junction and/or adherence molecules by both Brugia and Dirofilaria extracts has been shown to be the likely mechanism of this reduced permeability [10] , [28] , [29] . Indeed , Wolbachia surface protein ( WSP ) , but not whole D . immitis extract , induced the expression of ICAM-1 and VCAM-1 on a human EC line [28] , and , WSP or D . immitis extracts up-regulated CD31 on this EC line [28] , [29] . Strikingly , lymphatic EC exposed to Brugia adult or Mf extract also had higher mRNA levels of CD31 , in addition to , VE-cadherin and Junctional Adhesion Molecule-C ( JAM-C ) [10] . If live Mf presence also causes elevated expression of these intercellular adhesion molecules , this may provide an explanation for the retention of monocytes and neutrophils while the transmigration of smaller lymphocytes is not affected . In addition , we investigated whether live B . malayi Mf initiate immune responses in their local environment . Perhaps , not surprisingly , live B . malayi Mf ( as opposed to extracts [10] , [21] ) appear to be relatively inert in their local vascular environment and do not induce significant levels of pro-inflammatory immune mediators from EC , such as IL-6 , TNF-α or IL-1β . Interestingly , Mf also did not induce increased levels of IL-13 , which promotes alternatively-activated macrophages ( AAMø ) , or the down-regulatory cytokines IL-10 or TGF-β1 . However , Mf presence did down-regulate mRNA expression of the inflammatory complement component , C5 , in HUVEC and HLMVEC . In light of the recent report , that B . malayi Mf secrete a C5a-cleaving serine protease , this suggests that C5 products may be potentially damaging to filarial nematodes [27] . Similarly , mRNA expression of CCL23 , a chemoattractant for monocytes , neutrophils and T cells , was downregulated in HLMVEC . Both of these latter observations indicate that Mf may modulate inflammatory responses . This is in accord with the fact that most filarial patients are asymptomatic and have down-regulated cellular immune responses to filarial antigens , however , when given therapeutic treatments , patients subsequently regain responses to filarial antigen [30] . This also suggests that while the inflammatory potential of B . malayi is dependent on the presence of Wolbachia [31] , [32] , Wolbachia and/or their products are not released or secreted from living Mf to induce inflammatory mediators in their local environment . However upon death of worms , Wolbachia and their inflammatory products such as lipoprotein , which has been shown to stimulate both innate and adaptive immunity are released [31] , [33] , [34] . Interestingly , we observed that Mf exposure induced upregulation of the hypoxia-responsive mediator HO-1 in HLMVEC , indicating that Mf may induce hypoxia , which is an angiogenesis-promoting condition . Furthermore in HLMVEC Mf upregulated mRNA for hypoxia-inducible factor ( HIF-1α ) which is known to induce HO-1 . In addition to hypoxia and HIF-1 , HO-1 can be induced by other components such as heme , IL-6 , IL-1 or LPS in a number of model systems [35] , [36] , [37] , [38] , [39] , [40] , and is often used as a marker of inflammatory as well as oxidative stress . Neither IL-1 nor IL-6 increased in the EC supernatant following incubation with Mf . However , as Wolbachia spp . are an endosymbiotic bacteria of Brugia malayi , they produce heme [41] . Therefore , it is possible that Wolbachia spp . derived heme is a trigger of HO-1 production by HLMVEC . Additionally , HO-1 expression was repressed upon IFN-γ-stimulation of HLMVEC . Previous work has also shown that IFN-γ inhibits HO-1 in various cell types [42] , [43] however , to the best of our knowledge the role of this mechanism has not been investigated in a functional context . While HO-1 has anti-inflammatory properties , Mf are also known to induce IFN-γ [44] , [45] , [46] thus the role HO-1 induction by Mf warrants further investigation . Surprisingly , live intact Mf did not stimulate the expression of many angiogenic mediators including the key mediator , VEGF-A , in vascular EC , although , live Mf did stimulate pro-angiogenic COX-2 in HLMVEC . This is in line with previous work in which Simόn et al . found that Wolbachia surface protein from D . immitis and adult somatic antigen from D . immitis , both induce COX-2 in a human EC cell line [28] , [29] . Mf also enhanced the surface expression of CCR5 , which binds CCL3 ( MIP-1α ) , CCL4 ( MIP-1β ) and CCL5 ( RANTES ) , and mRNA expression of CCR10 , which binds to CCL27 and CCL28 in vascular EC . The role of this increased expression of chemokine receptors is not clear , however , CCR5 itself is known to mediate angiogenesis [47] . Other work has investigated the potential of filarial antigen , and/or live worms , to initiate vessel dilatation and/or angiogenesis by measuring EC proliferation and tube formation in vitro [10] , [28] , [29] , [48] . The results varied depending on differing use of HUVEC , lymphatic EC ( LEC ) or a human vascular EC cell line and parasite extracts or live nematode stages . For example , live female B . malayi decreased HUVEC proliferation [48] while LEC , but not HUVEC , cultured with adult Brugia or Mf extract showed increased proliferation [10] and D . immitis adult extract had no effect on the proliferation of a human EC cell line [29] . Live Mf and adults and their extracts all induced tube formation in LEC , however , in our experiments using live B . malayi Mf with vascular EC , both HUVEC and HLMVEC , we did not observe these structures [10] . In this study we report new insights into the EC response to live B . malayi Mf in their vascular environment , albeit within by the limitations of an ex vivo model which uses an EC isolate under static conditions incubated with parasites . Upon Mf exposure , extravasation of monocytes and neutrophils was partially blocked , while the transendothelial migration of lymphocytes was not altered . However , overall , Mf induced the expression of only a small number of cytokines , chemokines or pro-angiogenic mediators in human vascular EC . Furthermore , depletion of Wolbachia from live Mf did not significantly alter mRNA expression of these mediators . Taken together , our study suggests that live Mf are either relatively inert or that they are able to modulate local responses to promote their own survival and limit infection-induced pathology . Alternatively , Mf may induce a highly localised response mediated by other cells not present in this model system , rather than , a direct interaction between Mf and endothelium .
|
Brugia malayi is a nematode which causes lymphatic filariasis in South and South-East Asia . Most infected people harbour many millions of the microfilarial stage of the parasite in their blood stream and yet they show few visible symptoms of disease . Vascular endothelial cells ( EC ) line the blood vessels and are therefore in direct contact with microfilariae . Since vascular EC are potent immune cells functioning in the production of both immune mediators and regulating the migration of immune cells from the blood into the tissue , we have established an in vitro model in which to test the effect of live Mf upon vascular EC function . Strikingly , we observed that Mf exposure caused reduced transendothelial migration of neutrophils and monocytes , but not lymphocytes . However , microfilariae stimulated EC production of few pro-inflammatory mediators . Additionally , while filarial infection is known to stimulate mediators that increase blood vessel formation in vivo , live microfilariae promoted only a limited number of these regulators in cultured vascular EC . Our study suggests that the live microfilariae are remarkably inert in their induction and/or activation of vascular cells in their immediate local environment .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"filariasis",
"neglected",
"tropical",
"diseases",
"parasitic",
"diseases"
] |
2012
|
Live Brugia malayi Microfilariae Inhibit Transendothelial Migration of Neutrophils and Monocytes
|
SMYD4 belongs to a family of lysine methyltransferases . We analyzed the role of smyd4 in zebrafish development by generating a smyd4 mutant zebrafish line ( smyd4L544Efs*1 ) using the CRISPR/Cas9 technology . The maternal and zygotic smyd4L544Efs*1 mutants demonstrated severe cardiac malformations , including defects in left-right patterning and looping and hypoplastic ventricles , suggesting that smyd4 was critical for heart development . Importantly , we identified two rare SMYD4 genetic variants in a 208-patient cohort with congenital heart defects . Both biochemical and functional analyses indicated that SMYD4 ( G345D ) was pathogenic . Our data suggested that smyd4 functions as a histone methyltransferase and , by interacting with HDAC1 , also serves as a potential modulator for histone acetylation . Transcriptome and bioinformatics analyses of smyd4L544Efs*1 and wild-type developing hearts suggested that smyd4 is a key epigenetic regulator involved in regulating endoplasmic reticulum-mediated protein processing and several important metabolic pathways in developing zebrafish hearts .
Protein post-translational modifications ( PTMs ) are critical for the biological function of proteins . Histone modification is a common epigenetic mechanism that plays essential roles in the regulation of chromatin structure and gene expression . Different types of histone modifications , which are mediated by a series of specific enzymes , can either enhance or inhibit transcription to regulate specific cellular functions or signaling pathways . SET and MYND domain-containing proteins ( SMYDs ) belong to a unique family of histone lysine methyltransferases . This family is composed of five members , including SMYD1 , SMYD2 , SMYD3 , SMDY4 , and SMYD5 . These proteins share a Su ( var ) 3-9 , an Enhancer-of-zeste and Trithorax ( SET ) domain with lysine-specific methyltransferase activity , a Myeloid , Nervy , and DEAF-1 ( MYND ) domain , and a tetratricopeptide repeat ( TPR ) domain , which are involved in protein-protein interactions [1–3] . Several biochemical studies and functional analyses showed that SMYDs 1–3 exhibit methyltransferase activities for both histone and non-histone proteins [3–6] . SMYD members are widely present in multiple cell types , including those of skeletal and cardiac muscles [7–9] . Genetic ablation of Smyd1 in mice led to defects in right ventricular development [8 , 10] . The knockdown of smyd1 , smyd2 , and smyd3 in zebrafish using morpholino technology also led to cardiac malformation and defects in skeletal and cardiac myofibrillogenesis [11–13] . Zebrafish smyd5 was recently reported to play important roles in hematopoiesis [14] . Our knowledge of the biological function of SMYD4 remains limited . A previous study found that dSMYD4 was crucial for muscle development in Drosophila [15] . However , the role of SMYD4 in vertebrate development and its underlying molecular mechanism have not yet been analyzed thoroughly . Congenital heart diseases ( CHDs ) are the most common birth defects , with an annual incidence of approximately 1% of newborns worldwide [16] . Heart development involves complex genetic and epigenetic regulation [17–19] . Cardiac-specific ablation of HDAC1 and HDAC2 in the murine heart led to aberrant gene expression , contributing to defects in cardiac morphogenesis and contractility [20] , suggesting the critical roles of histone modification and epigenetic regulation in cardiac development . The significant enrichment of mutations in genes encoding chromatin modifiers in patients with CHDs provided further evidence to support this notion [21 , 22] . In this study , we analyzed smyd4 expression in zebrafish embryos and generated a smyd4 loss-of-function mutation ( smyd4L544Efs*1 ) using the CRISPR/Cas9 genome editing technology . We demonstrated that smyd4 is critical for cardiac malformation in zebrafish development . Two rare missense SMYD4 variants were identified in patients with CHDs . Both in vitro biochemical assays and in vivo functional analyses strongly suggested that the variant SMYD4 ( G345D ) was pathogenic . Our data suggested that smyd4 functions as a histone methyltransferase and , by interacting with HDAC1 , also serves as a potential modulator for histone acetylation . Transcriptome and bioinformatics analyses of the differentially expressed genes in developing hearts isolated from maternal and zygotic smyd4L544Efs*1 ( MZsmyd4L544Efs*1 ) mutant and normal control embryos showed a significant enrichment of the key genes involved in cardiac development and contractile function , and the endoplasmic reticulum-mediated protein processing pathway and several important metabolic pathways . Taken together , our results suggest that smyd4 , in association with hdac1 , is an important epigenetic regulator of these critical pathways during zebrafish cardiac development .
To determine the smyd4 mRNA levels in early to late zebrafish embryos , we performed a qRT-PCR analysis on embryos at the single-cell ( 0 . 2 hours post-fertilization ( hpf ) ) , 64-cell ( 2 hpf ) , blastula ( 4 hpf ) , mid-gastrula ( 8 hpf ) , late-gastrula ( 10 hpf ) , early primordium ( 24 hpf ) , long pectoral ( 48 hpf ) , and protruding mouth stage ( 72 hpf ) stages ( Fig 1A ) . We found that smyd4 transcripts were highly present in the single-cell stage , suggesting that a large amount of smyd4 was present as maternal transcripts . Zygotic smyd4 transcription peaked at the blastula stage and was followed by downregulation in the gastrula stage , indicating the role of this transcript in zebrafish early development . The overall expression levels of smyd4 were significantly further downregulated at 48 hpf and followed by a quick reactivation of expression at 72 hpf . We then used whole-mount in situ hybridization to determine the spatio-temporal expression pattern of smyd4 in developing zebrafish embryos . As shown in Fig 1B–1E , smyd4 was expressed ubiquitously in mid- and late-gastrula embryos; the highest level of expression was found at the polster in late-gastrula embryos ( Fig 1D and 1E ) . By 24 hpf , smyd4 transcripts were found to be enriched in the developing heart and blood vessel ( Fig 1F and 1G ) and became more restricted to the cardiovascular system at 48 hpf ( Fig 1H–1M ) . Interestingly , the developing ventricle had a significantly higher level of smyd4 expression than the atrium ( Fig 1J and 1K ) , suggesting its role in cardiac development . The reactivation of smyd4 expression at 72 hpf appeared not to be cardiac specific ( Fig 2F ) . To determine the biological function of smyd4 , we generated smyd4-deficient zebrafish using the CRISPR/Cas9 technology . Three sgRNAs were designed to target different exons of smyd4 that contribute to the ZMYND , C-terminal TPR2 , and SET domains . We were able to generate an 11-nt insertion in exon 6 that was targeted by sgRNA3 ( Fig 2A ) . As shown in Fig 2B , the sgRNA3 targeted sequence is well conserved from zebrafish to humans . Sequencing analysis confirmed this 11-nt insertion , which led to a frameshift at amino acid 545 ( smyd4L544Efs*1 ) ( Fig 2C and 2D and S1 Fig ) . This frameshift mutation yielded a premature stop codon ( TAA ) , as indicated by the asterisk in Fig 2C , giving rise to a truncated mutant protein that lacks the entire C-terminus containing the TPR2 domain ( Fig 2D ) . qRT-PCR and in situ hybridization analyses demonstrated that the smyd4 mRNA transcript was completely abolished in MZsmyd4L544Efs*1 embryos ( Fig 2E and 2F ) . The lack of the smyd4 mRNA transcript was likely due to the well-known effect of nonsense mutation-mediated degradation ( NMD ) [23] , a process common to frameshift mutations . Thus , we concluded that smyd4L544Efs*1 was a loss-of-function mutation . To better analyze the cardiac defects in MZsmyd4L544Efs*1 mutants , we crossed the smyd4L544Efs*1 line with the cardiomyocyte-specific transgenic reporter line Tg ( cmcl2:GFP ) . The entire work presented here was performed using this bi-genic line ( smyd4L544Efs*1;cmcl2:GFP ) with Tg ( cmcl2:GFP ) as a normal control , unless otherwise indicated in the text . Using the heterozygous breeding scheme , we were able to create heterozygous and homozygous smyd4L544Efs*1 mutant and wild-type embryos . First , we analyzed the survival of smyd4L544Efs*1 homozygous mutants and found no early lethality in these mutants , as the total amount of surviving smyd4L544Efs*1 homozygous mutants reached 25% among all three genotypes , which matched the normal Mendelian ratio . These homozygous mutants appeared normal in terms of growth and reproductivity . However , when examining these mutants , we observed a slight increase in embryos with abnormal cardiac situs ambiguus in smyd4L544Efs*1 homozygous ( 6 out of 14 , 43% ) and heterozygous ( 17 out of 48 , 35% ) mutants compared to the number of wild-type embryos ( 2 out of 10 , 20% ) ( S2 Fig ) . As situs ambiguus is highly relevant for defects in early patterning , this finding prompted us to speculate that the reduced but remaining maternal smyd4 transcripts in heterozygous females might contribute to the reduced severity of the resulting phenotype . Therefore , we established a homozygous breeding scheme to eliminate the effect of maternal smyd4 transcripts . The MZsmyd4L544Efs*1 embryos from the homozygous breeding scheme displayed severe pericardial edema ( Fig 3A and 3B ) and/or congested blood flow in the ventral veins ( Fig 3A and 3B ) , suggesting prominent cardiac defects or dysfunctions associated with the MZsmyd4L544Efs*1 embryos . The cardiac defects were analyzed carefully . Major defects included a significantly smaller ventricular size and anomalies of cardiac left-right asymmetric patterning or looping in approximately 60% of MZsmyd4L544Efs*1 embryos at 72 hpf ( Fig 3C and 3G ) , such as situs ambiguus ( straight heart tube ) and situs inversus ( D-loop heart tube ) ( Fig 3C ) . The 3D-reconstruction of confocal images of 96 hpf hearts further confirmed this looping defect ( Fig 3F and S1 and S2 Movies ) , as well as hypoplastic ventricles with less trabeculated myocardial structures in the MZsmyd4L544Efs*1 hearts ( Fig 3F and 3G ) . The number of cardiomyocytes on the largest section plane of the MZsmyd4L544Efs*1 mutant ventricle was found significantly reduced when compared to the comparable section plane of wild-type control hearts ( S3 Fig and Fig 3H ) , suggesting a great reduction of total number of cardiomyocytes in MZsmyd4L544Efs*1 hearts . To determine whether reduced cell number was due to the decreased cellular proliferative activity , we used p-H3 and PCNA immune reactivities to respective antibodies as the indicators for the level of cell proliferative activities in mutant developing hearts . As shown in Fig 4A and S4 Fig , MZsmyd4L544Efs*1 mutant cardiomyocytes had a dramatically reduced level in cellular proliferation when compared to wild-type controls . In addition , we also evaluated the levels of apoptosis in mutant hearts and we found no evidence of increased level of apoptotic cell in MZsmyd4L544Efs*1 mutant hearts ( S5 Fig ) . As adults , these MZsmyd4L544Efs*1 mutants had abnormal gross cardiac morphologies and histologies , typically with less trabecular myocardia and sometimes with a dramatically increased thickness of the ventricular compact wall ( Fig 4B and 4C ) . Despite these cardiac defects , we observed no apparent defects in skeletal muscle development in MZsmyd4L544Efs*1 mutants examined at 48 and 72 hpf ( S6 Fig ) , suggesting that smyd4 is lesser important than smyd1 in vertebrate muscle development [11] . As shown in Fig 5A , SMYD4 was localized to both the nucleus and cytoplasm . To determine the biochemical function of SMYD4 , flag-tagged SMYD4 ( SMYD4flag ) was first overexpressed in the HL-1 mouse cardiomyocyte cell line , followed by immunoprecipitation and mass spectrometric analysis to identify its interacting proteins . HDAC1 was identified as one of the major proteins to interact with SMYD4 ( Fig 5B ) . This finding was further confirmed by Co-IP/western blotting analysis using a HEK293T cell line in which both SMYD4flag and HA-tagged HDAC1 ( HDAC1HA ) were co-overexpressed ( Fig 5C ) . There are four functional domains in SMYD4 . Two TPR domains are located at the N- and C- termini , an MYND domain can mediate interactions with partner proteins , and a SET domain functions as a methyltransferase . To determine the functional domain that was responsible for the SMYD4/HDAC1 interaction , as shown in Fig 5D and 5E , we generated several mutations in SMYD4 with different combinations of deletions in the SMYD4 protein and co-expressed these mutants with HDAC1 in HEK293T cells . We were able to use Co-IP/western blotting assays to demonstrate that the MYND domain was responsible for the interaction between SMYD4 and HDAC1 . To confirm the biochemical activities of SMYD4 as a methyltransferase and as a functional partner of HDAC1 in histone modification , we analyzed the changes in both histone methylation and acetylation modifications in the MZsmyd4L544Efs*1 embryos . As shown in Fig 5F and 5G , di- ( me2 ) and tri-methylation ( me3 ) at the lysine 4 site ( K4 ) of histone 3 ( H3 ) were significantly reduced , and mono-methylation of lysine 4 ( H3K4me ) was increased , while other lysine residues ( i . e . , K9 and K27 ) were not affected , suggesting that SMYD4 was specifically involved in H3K4 methylation . Interestingly , the acetylation of lysines 4 , 9 , 14 , and 27 was dramatically reduced in the MZsmyd4L544Efs*1 mutants examined at 48 hpf ( Fig 5F and 5G ) . This finding suggested that SMYD4 is a critical part of the HDAC1 functional complex and may function as an important negative regulator of HDAC1-mediated histone 3 modification and epigenetic regulation . Taken together , these data indicate that SMYD4 is a functional methyltransferase specific for H3K4 methylation and a functional partner of HDAC1 for regulating H3 acetylation . We used Target Exome Sequencing ( TES ) and screened a cohort of 208 patients with CHDs for potential genetic variants of SMYD4 . The patient information is summarized in S1 Table and S2 Table . Two rare missense variants ( c . 1034G>A , p . G345D and c . 1736G>A , p . R579Q ) were identified and confirmed by Sanger sequencing in two individual patients ( Fig 6A and 6B ) . The variants were not recorded in the 1000G database or in our internal whole-exome sequencing database generated from more than 3 , 500 patients without CHDs . The frequencies of G345D and R579Q in the EXAC database are 1/121 , 404 and 3/120 , 896 , respectively . G345D was identified in a patient who was diagnosed with DCRV/VSD , and R579Q was identified in a patient with TOF ( S3 Table ) . Both sites were evolutionally conserved from zebrafish to humans ( Fig 6C ) . Both variants ( G345D and R579Q ) were predicted to be highly pathogenic and harmful by SIFT , PolyPhen2 and MutationTaster . Based on 3D-computational structure prediction using the SWISS MODEL , as shown in Fig 6D and 6E , both mutations led to significant changes in protein structure compared with that of the wild-type SMYD4 . To confirm the pathogenicity of the variant SMYD4 ( G345D ) , Co-IP/western blotting assays were performed , and we found that the biochemical interaction between SMYD4 ( G345D ) and HDAC1 was greatly attenuated compared to the interaction between SMYD4 and HDAC1 in HL-1 cells ( Fig 6F and 6G ) , consistent with the predicted alteration of protein structure and function in SMYD4 ( G345D ) . To confirm SMYD4 ( G345D ) as a pathogenic mutation , we performed gain-of-function transgenic overexpression experiments by injecting wild-type smyd4 and smyd4 ( G295D ) mRNA into normal Tg ( cmcl2:GFP ) embryos ( Fig 7A and 7C ) . Based on the amino acid sequences of zebrafish smyd4 and human SMYD4 , we generated smyd4 ( G295D ) mutant cDNA , which was equivalent to human SMYD4 ( G345D ) ( Fig 6C and S7 Fig ) . We found that the smyd4 ( G295D ) mRNA caused significantly more embryos with severe heart defects ( e . g . , D-loop and tubular hearts ) than wild-type smyd4 mRNA ( Fig 7A and 7C ) , suggesting that SMYD4 ( G345D ) was harmful to cardiac development . To further confirm the effects of this mutation , we performed rescue experiments by analyzing and comparing the ability of mutant SMYD4 ( G345D ) and wild-type SMYD4 to rescue the abnormal cardiac phenotypes of MZsmyd4L544Efs*1 mutants . We injected smyd4 wild-type and smyd4 ( G295D ) mutant mRNAs into MZsmyd4L544Efs*1 single-cell embryos harvested from the homozygous breeding scheme described above . As shown in Fig 7B and 7C , wild-type smyd4 mRNA significantly reduced the number of embryos with malformed hearts compared to the number in the MZsmyd4L544Efs*1 mutant group , which indicates a partial but significant rescue phenotype for the wild-type smyd4 mRNA . In contrast , the smyd4 ( G295D ) mRNA not only failed to rescue MZsmyd4L544Efs*1 but also significantly increased the number of embryos with malformed hearts and severe cardiac defects , such as tubular hearts ( Fig 7B and 7C ) , further confirming that the smyd4 ( G295D ) mutation is pathogenic . Taken together , our data implied that human SMYD4 ( G345D ) was deleterious for heart development and a CHD-causing genetic variant . Given the severe cardiac defects and abnormal histone modifications in the MZsmyd4L544Efs*1 embryos , we anticipated a large number of gene alterations in MZsmyd4L544Efs*1 mutant hearts . We performed RNA-seq analysis , comparing normal and MZsmyd4L544Efs*1 hearts harvested at 72 hpf . As shown in Fig 8 , a total of 3 , 856 differentially expressed ( DE ) genes were identified in MZsmyd4L544Efs*1 hearts . Among those genes , 2 , 648 genes were upregulated , and 1 , 208 genes were downregulated ( Fig 8A ) . Not surprisingly , some important genes that were highly relevant to cardiac development were altered , which included the genes involved in cardiac muscle contraction ( upregulated: 10; downregulated: 22 ) and key cardiac signaling pathways , such as the canonical Wnt signaling pathway ( upregulated: 36 , downregulated: 10 ) and the Hedgehog signaling pathway ( upregulated: 15 , downregulated: 3 ) ( Fig 8B ) . To investigate whether this altered transcriptional profile was associated with specific pathways or biological processes , we performed KEGG pathway analysis , which indicated that the upregulated genes were enriched in the endoplasmic reticulum-mediated protein processing pathway in the Biological Process domain ( Fig 8C ) and the downregulated genes were enriched in several metabolic pathways , including carbon metabolism and the glycolysis/gluconeogenesis pathway ( Fig 8D ) . Gene ontology ( GO ) analysis of the upregulated genes also revealed major terms in cellular metabolic processes , in which 975 genes were involved . A GO term analysis of the downregulated genes revealed the enrichment of a large number of genes in the organonitrogen compound metabolic process ( 185 genes ) , the ATP metabolic process ( 49 genes ) and the glycosyl compound metabolic process ( 55 genes ) ( Fig 8E ) . This finding provided an important hint that smyd4/hdac1-mediated epigenetic regulation likely occurred via the control of endoplasmic reticulum-mediated protein processing and several key metabolic pathways in the heart during zebrafish development .
SMYDs are a family of unique lysine-histone methyltransferases that contain the well-conserved SET and MYND domains , as well as two TPR domains . The biological functions of SMYDs are largely unknown . By generating smyd4 mutant zebrafish using the CRISPR/Cas9 technology , we have shown that smyd4 is indispensable for cardiac development . This finding is consistent with the observation that ubiquitously expressed smyd4 in early zebrafish embryos becomes more enriched to zebrafish developing hearts at 48 hpf during embryogenesis , despite the fact that gross expression levels are reduced dramatically at this stage , which is followed by a quick up-regulation of smyd4 expression in embryos at 72 hpf ( Fig 1A ) . These are critical stages , in which the newly formed heart switches from the cardiac morphogenic pathway to cardiac maturation pathways to eventually form a normal functional heart . There are several major cardiac defects in the MZsmyd4L544Efs*1 mutants , including the defects in left-right patterning and looping , and the hypoplastic ventricular walls in the developing hearts . Furthermore , the cell proliferative activities in MZsmyd4L544Efs*1 developing ventricles are significantly decreased , which likely leads to the hypoplastic ventricle . In adults , the thickening of the ventricular compact wall that is seen in some mutant hearts is likely a maladaptation of compromised cardiac function due to cardiac developmental defects . Considering smyd4 shares similar protein structure and enzymatic activities with other SMYD family members , genetic and functional redundancy may occur in MZsmyd4L544Efs*1 mutants . It has been shown that smyd1b mutants display a similar pericardial edema and congestive blood circulation [24] . The morpholino knock-down of another SMYD family member smyd3 in zebrafish embryos also produces cardiac looping defects [13] . Both of these prior studies suggest potential genetic interactions and/or redundancies among these family members in zebrafish heart development . Some variations in the cardiac defects as well as certain degrees of varying severity of cardiac defects among the mutant embryos further support this notion . However , it is also clear that each member of SMYD family has its unique function . For example , myofibril disorganization in skeletal muscle are only seen in smyd1b mutants [24] . We have not observed any such a defect in MZsmyd4L544Efs*1 mutants , suggesting that the function of smyd4 is more relevant to cardiac development in zebrafish . Our observations strongly suggest that smyd4 plays an important function in cardiac development . This conclusion is also supported by our human genetic study , which identified two rare SMYD4 variants in a 208-patient cohort with CHDs . The data obtained after the overexpression of mutant smyd4 ( G295D ) and from rescue experiments in which smyd4 ( G295D ) mRNA was injected into MZsmyd4L544Efs*1 mutants strongly indicates that the human variant SMYD4 ( G345D ) is pathogenic , further suggesting SMYD4 as a genetic contributor to CHDs . This finding indicates the importance of including SMYD4 in CHD genetic screening panels in the future . One of our key findings is that SMYD4 interacts with the major histone modification enzyme and epigenetic regulator HDAC1 via the well-conserved MYND domain . Our finding is consistent with the previous finding that dSmyd4 can interact with dHDAC1 in Drosophila muscle development [15] . The MYND domain is known for its role in protein-protein interactions and was previously shown to recruit the HDAC complex to regulate gene expression [25] . The mutation in SMYD4 ( G345D ) is located at the edge of the MYND domain and between the MYND and SET domains . Our biochemical data show that SMYD4 ( G345D ) has a dramatically reduced ability to interact with HDAC1 . Although the TPR domains are still poorly understood , previous studies suggest that the C-terminal TPR2 domain is vital for methyltransferase activity and protein-protein interactions [3 , 26] . The TPR2 domain of SMYD2 is indispensable for its interaction with HSP90 , which proved to be critical for titin filament organization [12 , 27] . Currently , we are in the process of generating smyd4-tpr2del mutant zebrafish similarly using the CRISPR/Cas9 technology to further investigate the role of TPR2 in smyd4 biological function . SMYDs 1 and 3 catalyze mono- , di- , and trimethylation of H3K4 [11 , 28] . Similarly , SMYD2 can mono-methylate H3K4 ( H3K4me ) and di-methylate H3K26 ( H3K26me2 ) and p53K37me [6 , 29] . In MZsmyd4L544Efs*1 mutants , H3K4me2 and H3K4me3 are reduced , suggesting that smyd4 is a specific methyltransferase for H3K4 methylation . Notably , H3K4ac , K9ac , K14ac , and K27ac were all abolished in the MZsmyd4L544Efs*1 mutants . This finding implies that the deficiency of smyd4 impacts the function of hdac1 ( the gene homologous to both HDAC1 and HDAC2 in mammals ) . As previously demonstrated , cardiac-specific deletion of the mouse Hdac1 and Hdac2 genes evoked a strong heart failure phenotype [20] , which is consistent with our finding . We are currently using biochemical approaches to determine whether smyd4 serves as a simple docking protein to provide chaperone functions for hdac1 or functions as a key modulating molecule for hdac1 . Nevertheless , our data suggest that smyd4 plays a critical role in the epigenetic regulation of gene expression via its dual activities as a methyltransferase and negative regulator of hdac1 . RNA-seq analysis comparing wild-type and MZsmyd4L544Efs*1 mutant hearts demonstrates that the expression of over 3 , 000 genes is altered , which may reflect the potential function of smyd4’s broad epigenetic regulation of its target genes . In addition to genes related to cardiac muscle contraction and cardiac signaling pathways that are highly relevant to cardiogenesis ( e . g . , the canonical Wnt and Hedgehog signaling pathways ) ( Fig 8 ) , our KEGG pathway and GO annotation analyses of altered genes revealed an overwhelming enrichment in several cellular metabolic pathways , including the endoplasmic reticulum-mediated protein processing pathway . This finding is very different from the publicly available RNA-seq database for zebrafish heart developmental defects [30–32] . This finding suggests that smyd4 has a unique and specific biological function in regulating cellular metabolism . However , as it is technically difficult to perform ChIP-seq on zebrafish embryonic hearts , we cannot currently determine which specific components of the pathways are primarily affected and which are affected secondarily . Our future study will switch to a mammalian system to determine the detailed molecular mechanism by which SMYD4 modulates cellular metabolism or signaling pathways via its important role in epigenetic regulation . We will re-evaluate whether these altered metabolic pathways play critical roles in cardiac development and the cardiac defects seen in smyd4 mutant embryos . This study is the first characterization of SMYD4 in vertebrate development and physiological function . Taken together , our results demonstrate the critical role of smyd4 in embryonic development and heart formation . Our data suggest that smyd4 functions as a histone methyltransferase and , by interacting with HDAC1 , also serves as a potential modulator for histone acetylation . In addition , our work has also provided genetic and functional evidences that rare SMYD4 variants likely contribute to CHDs .
All genetic studies were approved by the Ethics Committee of the Children’s Hospital of Fudan University , China . The approval number is: [2015]92 ) . All patients provided written informed consent in accordance to the Declaration of Helsinki . The Research Ethics Committee of the Children’s Hospital of Fudan University , China , approved and monitored all zebrafish procedures following the guidelines and recommendations outlined by the Guide for the Care and Use of Laboratory Animals . The approval number is: [2015]92 ) . For all experiments , wild-type zebrafish embryos of the Tu and transgenic Tg ( cmcl2:GFP ) ( cardiac myosin light chain 2:GFP reporter ) strains were used . The expression of smyd4 was detected in zebrafish embryos from the 10 to 72 hpf stages using a smyd4-specific antisense probe . The template for the smyd4 probe was amplified from the cDNA of zebrafish at 24 hpf . The 508-bp fragment , which was obtained using specific primers ( smyd4-probe-F: GAAGTGTGTGAAATGTGGAAAGCCTCTT and smyd4-probe-R: TTCACTCAGTTCCTGCAGTTCTTCACAG ) , was cloned into the pEasy-T vector ( Promega , USA ) . After linearization of the plasmids , the antisense and sense probes were transcribed and labelled with digoxigenin in vitro . RNA in situ hybridization was performed as described previously [33] . Briefly , zebrafish embryos at different stages were collected and fixed in 4% paraformaldehyde at 4°C overnight . Embryos older than 24 hpf were digested by proteinase K at room temperature . Then , the embryos were pro-hybridized at 65°C for 4 hours and subsequently incubated with the antisense or sense probes overnight . An anti-digoxigenin antibody ( Roche , USA ) was used to bind the probes overnight at 4°C . Finally , the embryos were stained with NBT/BCIP ( Vector , USA ) and photographed in methylcellulose using a Leica M205C microscope . Embryos of the wild-type Tu zebrafish strain were collected at 0 . 2 , 2 , 4 , 8 , 10 , 24 , 48 and 72 hpf . The total RNA was extracted using the TRIzol reagent ( Invitrogen , USA ) and converted to cDNA using the PrimeScript RT Reagent Kit ( Takara Bio , Japan ) . The real-time qPCR reactions were performed with SYBR Premix Ex Taq ( Takara Bio , Japan ) using the Roche 480 plus system ( Roche , USA ) . The real-time primers for the zebrafish are summarized in S4 Table . smyd4 target sites were designed using the website http://zifit . partners . org/ZiFiT/CSquare9Nuclease . aspx . The provided sites were then screened in Ensemble . Three sites that specifically recognize the sequence of smyd4 in the zebrafish genome were chosen for the interruption of smyd4 . sgRNA1 ( GGAGTAATGAAGCACTGCTG ) , sgRNA2 ( GGAGCTGATCTGCTGGCCAT ) , and sgRNA3 ( GGAGCGTCAGCGCCTCCTGC ) targeted exons 2 , 4 and 6 of smyd4 , respectively . We cloned these sites into the gRNA plasmid p-T7-gRNA , which was provided by Professor Li Qiang . gRNAs were transcribed in vitro using the MAXIscript T7 kit ( Ambion , USA ) . Cas9 mRNA was transcribed from the pSP6-2Snls-spCas9 plasmid using the SP6 mMESSAGE mMACHINE Kit ( Ambion , USA ) , and poly A tails were added using the poly A Tailing Kit ( Ambion , USA ) . All gRNAs and the Cas9 mRNA were purified and dissolved in nuclease-free water before injection using the mirVana miRNA Isolation Kit ( Ambion , USA ) and the RNA Purification Kit ( TIANGEN , China ) . gRNA and Cas9 mRNA were co-injected into the embryos at the single-cell stage . Twenty injected embryos were used to identify the efficiency , and the remaining embryos were raised to adulthood to obtain the mosaic founders . These mosaic fish were crossed with wild-type zebrafish to produce heterozygotes , which were genotyped using Sanger sequencing methods . To analyze the cardiac defects in MZsmyd4L544Efs*1 mutants , we crossed the smyd4L544Efs*1 line to the cardiomyocyte-specific transgenic reporter line Tg ( cmcl2:GFP ) . All primers and target sites of smyd4 are summarized in S4 Table . Embryos were collected at 48 , 72 , and 96 hpf for phenotype analysis . The embryos were fixed in methylcellulose and imaged using Leica M205C and Leica SP8 microscopes ( Leica , Germany ) . To determine the number of cardiomyocytes in the developing ventricle , the embryonic hearts at 96 hpf were carefully collected and scanned using Leica SP8 confocal microscope . The z-step was set at 1μm . The images with largest section of ventricles were chosen for the analysis . DAPI and EGFP double positive cells were scored for cardiomyocyte . Adult fish at 6 months of age were photographed to record the body size and the developmental states of different organs , including the head , eyes , fins , and tails . These fish were dissected after anesthesia . The hearts of adult zebrafish were fixed and photographed in 4% paraformaldehyde . Serial sectioning with H&E staining was performed for these heart samples . Embryos were collected at 48 hpf , fixed in 4% paraformaldehyde at 4°C overnight . For the proliferation assay , the embryos were digested using Collagenase , Type II ( Life technologies , USA ) at room temperature , and blocking was performed for one hour at room temperature , and followed by incubating with the primary antibody against p-H3 ( S10 ) ( Abacam , USA ) or PCNA ( Genetex , USA ) at 4°C overnight . Second antibody were from the series of Alexa Fluor ( Life technologies , USA ) . For the apoptosis assay , In Situ Cell Death Detection kit , TMR red ( Roche , USA ) was used and all procedures were performed as the instruction manual described . Finally , embryo hearts were collected under a Leica M205C stereomicroscope and were imaged using a Leica SP8 microscope . A plasmid containing wild-type human SMYD4 ( BC035077 ) was obtained from Abmgood ( Abmgood , USA ) . Then , Flag-tagged wild-type SMYD4 and HA-tagged wild-type HDAC1 were cloned into the expression plasmid . The mutation ( G345D ) identified in patients was obtained using the KOD-Plus Mutagenesis Kit ( Toyobo , Japan ) . All plasmids were confirmed via Sanger sequencing . The anti-SMYD4 ( Proteintech , USA ) , anti-HDAC1 ( Proteintech , USA ) , anti-Flag ( Abmart , China ) , and anti-HA ( Abmart , China ) antibodies were used . Wild-type SMYD4 was overexpressed in HL-1 cells . After 48-h transfections , cell lysates were obtained in RIPA containing 1 mM PMSF and complete protease inhibitors ( Roche , USA ) . Immunoprecipitation was performed using an anti-Flag affinity gel ( Biotool , USA ) . SDS-PAGE was performed to resolve the eluates . After sliver staining , the proteins underwent mass spectrometry analysis . Protein-protein interactions were verified in HL-1 cells after transient overexpression of SMYD4 . Co-immunoprecipitation was performed to confirm the interaction between SMYD4 and HDAC1 in HEK293T cells using anti-tag antibodies . HEK293T cells were transiently co-transfected with pCDH-Flag-SMYD4 deletion mutants and pcDNA3-HA-HDAC1 . Plasmids of SMYD4 were co-transfected into HEK293T cells , and cell extracts were prepared as described above . Immunoprecipitations were performed with anti-HA affinity beads ( Biotool , USA ) . The beads were washed five times , and bound proteins were eluted in SDS-PAGE loading buffer and analyzed via western blotting . Briefly , the immunofluorescence process is described as follows . The cells were fixed in 4% paraformaldehyde and then underwent cell permeation and blocking . The antibody used for immunofluorescence was anti-SMYD4 ( Proteintech , USA ) . Primary antibodies were incubated overnight at 4°C . Secondary antibodies were from the Alexa Fluorescence Series ( Life technologies , USA ) . Finally , the cells were imaged in Diamond anti-fade agent ( Life technologies , USA ) using a Leica SP8 microscope . Tg ( cmcl2:GFP ) and MZsmyd4L544Efs*1 embryos were collected at 48 hpf . Protein was obtained in RIPA containing 1 mM PMSF and complete protease inhibitors ( Roche , USA ) after sonication . The histone modification antibodies used in this study include anti-H3 ( CST , USA ) , anti-H3K4ac ( Active Motif , USA ) , anti-H3K9ac ( Active Motif , USA ) , anti-H3K14ac ( Active Motif , USA ) , anti-H3K27ac ( Active Motif , USA ) , anti-H3K4me1 ( Active Motif , USA ) , anti-H3K4me2 ( Active Motif , USA ) , anti-H3K4me3 ( Abcam , USA ) , anti-H3K9me3 ( Abcam , USA ) , and anti-H3K27me3 ( Millipore , USA ) . This study was approved by the research ethics committee of the Children’s Hospital of Fudan University in Shanghai , China ( number: [2015]92 ) . The diagnosis of CHD patients was based on echocardiography at the Children’s Hospital of Fudan University in Shanghai , China . All patients involved in this research had not been diagnosed with extra cardiac anomalies and did not have common chromosomal anomalies , such as the 22q11 microdeletion . Human cardiac tissue samples from CHD patients were obtained from the Biobank of the Children’s Hospital of Fudan University in Shanghai , China . Cardiac tissues were removed from the blocked right ventricular outflow tract during surgery . All tissue samples were maintained in RNAlater RNA Stabilization Solution ( Thermo Scientific , USA ) after surgery and stored at -80°C before use . RNA was extracted from the tissue samples using the Trizol reagent ( Invitrogen , USA ) and immediately underwent reverse transcription using the PrimeScript RT Reagent Kit ( Takara , Japan ) . All detailed patient information is summarized in S2 Table . The peripheral venous blood samples from 113 patients were prepared for DNA extraction using the Blood Extraction Kit ( QIAGEN , Germany ) . The cardiac tissue samples from 95 patients were prepared for cDNA extraction . All of the regions covered by TES and all primers for smyd4 exon sequencing in cDNA are listed in S5 Table . Variant analysis was performed using the Mutation Surveyor software ( Softgenetics , USA ) . All variants were screened in public databases , including the 1000 Genome database , the dbSNP database , and the ExAC database , and an internal database in the molecular diagnosis laboratory at the Children’s Hospital of Fudan University . A risk analysis of SNVs was performed using SIFT , Polyphen2 , and Mutation Taster to predict the possible effects on protein function . A 3D structure analysis of the wild-type and mutant proteins was performed on the SWISS MODEL website ( https://www . swissmodel . expasy . org/ ) . Based on its pathogenic prediction , the G345D SMYD4 variant was selected for mutation analysis . Homology analysis showed that the mutant G295D in smyd4 was equivalent to the mutant G345D in SMYD4 . The template for smyd4 wild-type mRNA transcription was amplified from zebrafish cDNA at 24 hpf . The template of the mutant ( G295D ) in smyd4 transcription was obtained using the KOD-Plus Mutagenesis Kit ( Toyobo , Japan ) . The wild-type and mutant mRNAs of smyd4 were transcribed using the mMessage mMachine T7 Ultra Kit ( Ambion , USA ) , and poly A tails were added using the poly A Tailing Kit ( Ambion , USA ) , according to the instruction manual . The mRNAs were resolved in nuclease-free water and finally quantified to 150 ng/μl for microinjection . Embryos of Tg ( cmcl2:GFP ) and MZsmyd4 L544Efs*1 were collected . A total of 3 nl of mRNA was microinjected into embryos at the single-cell stage . Fifty embryos from each group with cardiac GFP at 48 hpf were chosen for phenotype analysis . The embryos were fixed in 3% methylcellulose after anesthetization and then observed for cardiac morphology using a Leica M205C stereomicroscope . Heart tissue was collected from 50 MZsmyd4L544Efs*1 or Tg ( cmcl2:GFP ) embryos . Cardiac-specific GFP helped us successfully obtain embryo heart tissue . Embryo hearts were collected at 72 hpf after anesthesia using a Leica M205C stereomicroscope . In-depth RNA sequencing was performed by the Novogene Experimental Department in China . The raw sequencing image data were examined via the Illumina analysis pipeline and aligned with the unmasked zebrafish reference genome . Differential expression analysis of the two groups was performed using the DESeq2 R package ( 1 . 10 . 1 ) . The resulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate . Genes with an adjusted P-value < 0 . 005 and |log2 ( Fold change ) |>1 found by DESeq2 were assigned as differentially expressed . The Student’s t-test was used for all statistical analyses . A p-value of < 0 . 05 ( 2-sided ) was regarded as statistically significant . All experiments were repeated three times . All data were analyzed with GraphPad Prism ( version 5 . 0 ) .
|
SMYD4 belongs to a SET and MYND domain-containing lysine methyltransferase . In zebrafish , smyd4 is ubiquitously expressed in early embryos and becomes enriched in the developing heart at 48 hours post-fertilization ( hpf ) . We generated a smyd4 mutant zebrafish line ( smyd4L544Efs*1 ) using the CRISPR/Cas9 technology . The maternal and zygotic smyd4L544Efs*1 mutants demonstrated a strong defect in cardiomyocyte proliferation , which led to a severe cardiac malformation , including left-right looping defects and hypoplastic ventricles . More importantly , two rare genetic variants of SMYD4 were enriched in a 208-patient cohort with congenital heart defects . Both biochemical and functional analyses indicated that SMYD4 ( G345D ) was highly pathogenic . Using mass spectrometric analysis , SMYD4 was shown to specifically interact with histone deacetylase 1 ( HDAC1 ) via its MYND domain . Altered di- and tri-methylation of histone 3 lysine 4 ( H3K4me2 and H3K4me3 ) and acetylation of histone 3 in smyd4L544Efs*1 mutants suggested that smyd4 plays an important role in epigenetic regulation . Transcriptome and pathway analyses demonstrated that the expression levels of 3 , 856 genes were significantly altered , which included cardiac contractile genes , key signaling pathways in cardiac development , the endoplasmic reticulum-mediated protein processing pathway , and several important metabolic pathways . Taken together , our data suggests that smyd4 is a key epigenetic regulator of cardiac development .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"fish",
"medicine",
"and",
"health",
"sciences",
"cardiovascular",
"anatomy",
"enzymes",
"cardiac",
"ventricles",
"enzymology",
"vertebrates",
"dna-binding",
"proteins",
"animals",
"animal",
"models",
"osteichthyes",
"organisms",
"developmental",
"biology",
"model",
"organisms",
"experimental",
"organism",
"systems",
"epigenetics",
"embryos",
"research",
"and",
"analysis",
"methods",
"embryology",
"proteins",
"gene",
"expression",
"histones",
"methyltransferases",
"biochemistry",
"zebrafish",
"eukaryota",
"anatomy",
"genetics",
"biology",
"and",
"life",
"sciences",
"heart"
] |
2018
|
The roles of SMYD4 in epigenetic regulation of cardiac development in zebrafish
|
Some pathogens have evolved mechanisms to overcome host immune defenses by inhibiting host defense signaling pathways and suppressing the expression of host defense effectors . We present evidence that Pseudomonas aeruginosa is able to suppress the expression of a subset of immune defense genes in the animal host Caenorhabditis elegans by activating the DAF-2/DAF-16 insulin-like signaling pathway . The DAF-2/DAF-16 pathway is important for the regulation of many aspects of organismal physiology , including metabolism , stress response , longevity , and immune function . We show that intestinal expression of DAF-16 is required for resistance to P . aeruginosa and that the suppression of immune defense genes is dependent on the insulin-like receptor DAF-2 and the FOXO transcription factor DAF-16 . By visualizing the subcellular localization of DAF-16::GFP fusion protein in live animals during infection , we show that P . aeruginosa–mediated downregulation of a subset of immune genes is associated with the ability to translocate DAF-16 from the nuclei of intestinal cells . Suppression of DAF-16 is mediated by an insulin-like peptide , INS-7 , which functions upstream of DAF-2 . Both the inhibition of DAF-16 and downregulation of DAF-16–regulated genes , such as thn-2 , lys-7 , and spp-1 , require the P . aeruginosa two-component response regulator GacA and the quorum-sensing regulators LasR and RhlR and are not observed during infection with Salmonella typhimurium or Enterococcus faecalis . Our results reveal a new mechanism by which P . aeruginosa suppresses host immune defense .
The innate immune system is a genetically-encoded host defense mechanism that constitutes the first line of defense against pathogens in plants and animals . Innate immunity in animals is evolutionarily ancient , and the molecular components of mammalian innate immunity are partly conserved in invertebrates such as Drosophila and C . elegans that lack a somatic recombination-based adaptive immunity . Innate immunity comprises several functions , including the production of defense proteins , such as antimicrobial peptides , lysozymes , and other immune modulators [1] . A common theme emerging from the studies of host-pathogen interactions is that recognition of pathogen-associated molecular patterns ( PAMPs ) or of infection byproducts by host receptors , such as the Toll-like receptors ( TLRs ) , trigger highly regulated immune responses , including the induction of antimicrobial effectors [2] , [3] . For example , infection by Gram-positive bacteria triggers activation of the Toll pathway in Drosophila . Activation of Toll signaling in turn induces expression of specific antimicrobial genes through the activation of a Rel/NF-κB transcription factor [4] , [5] . Despite lacking a functionally conserved TLR/NF-κB pathway [6] , C . elegans is able to mount robust immune responses against a variety of pathogens ( see [7]–[10] for examples ) . This underscores the importance of other pathways in C . elegans innate immunity . Recently , through genetic studies , several conserved signal transduction pathways that are required for innate immunity in C . elegans have been identified . They include the p38 MAPK , the Sma/TGF-β , and the DAF-2/DAF-16 insulin-like signaling pathways ( reviewed in [11] , [12] ) . For example , mutants in sek-1 , which encodes a p38 MAPK kinase , and pmk-1 , which encodes a p38 MAPK , are sensitive to killing by bacterial pathogens [13] . Mutants in sma-6 , which encodes a TGF-β receptor , are also sensitive to killing by bacterial pathogens [10] , [14] . In contrast , mutants in daf-2 , which encodes an insulin-like receptor , are resistant to killing by bacterial pathogens . The resistance of daf-2 mutants is completely dependent on DAF-16 , a FOXO transcription factor [15] . Microarray studies suggest that each of these immune signaling pathways regulates the expression of host effector genes , which may account for the altered pathogen susceptibility of pathway mutants [8] , [16] , [17] . Host defense effectors include diverse classes of small molecules and antimicrobial peptides . Lysozyme , a bacteriolytic enzyme , is ubiquitously expressed in mammalian secretions . The C . elegans genome encodes ten lysozyme-like proteins ( lys-1 to lys-10 ) , some of which have been directly implicated in host defense [7] , [10] . The C . elegans genome also encodes many amoebapore or saposin-like proteins ( e . g . , spp-1 ) that are members of a large and diverse class of antimicrobial peptides and a number of defensin-like molecules homologous to ASABF ( Ascaris suum antibacterial factor ) , including abf-2 . In mammals and Drosophila , the expression of defensin-family proteins contributes to antibacterial , antifungal , and antiviral defenses . Recombinant SPP-1 and ABF-2 have antimicrobial activity [18] , [19] , and endogenous expression contributes to antibacterial defense in C . elegans [20] . The C . elegans genome also encodes homologs of the thaumatin family of plant antifungal proteins ( thn-1 to thn-8 ) . While it is not known whether C . elegans thaumatins have antifungal activity , RNAi knockdown of thn-family genes results in worms that are more sensitive to killing by P . aeruginosa [7] . Host effector genes are differentially regulated during infection of C . elegans [7]–[10] . Microarray studies also suggest that different pathogens elicit specific transcriptional responses [21] . This is presumably due to host recognition of different PAMPs followed by induction of specific host defense pathways . For example , during fungal infection , TIR-1 ( Toll and IL-1 receptor ) activates an antifungal defense through p38 MAPK signaling [22] . The mechanisms by which specific transcriptional responses are elicited are still largely unknown . However , the intestine-specific GATA transcription factor ELT-2 is required for the regulation of host immune defense effectors and resistance to bacterial pathogens [7] , [23] . P . aeruginosa is an important Gram-negative human pathogen that is associated with infection of immunocompromised patients [24] , including cystic fibrosis ( CF ) patients and individuals with burn wounds [25] , [26] . P . aeruginosa has evolved at least three strategies to combat the vast repertoire of host defenses . First , P . aeruginosa can produce an extensive array of cell-associated and secreted virulence factors that are deleterious or damaging to the host . A substantial number of these virulence determinants are regulated by the two-component regulator encoded by gacA and the quorum-sensing regulators encoded by lasR and rhlR [27] , [28] . For example , P . aeruginosa secretes several phenazines , including pyocyanin [29] , that have tissue-damaging properties attributed to the induction of free radical production in host cells [30] . Second , P . aeruginosa can evade detection by the host , either by directly destroying host molecules that are involved in pathogen detection or by downregulating PAMP expression . For example , an important component of host defense is the deposition of a complement component C3b on the bacterial surface , leading to the induction of host responses and pathogen clearance [31] . To counter complement activation , P . aeruginosa produces alginate to limit accessibility of complement and secretes proteases , including alkaline protease and elastase that degrade C3b [32] , [33] . The flagellum , an important virulence determinant required for motility and attachment , is also a PAMP that is detected by the host through the interaction of monomeric flagellin with TLR5 , resulting in NF-κB and p38 MAPK activation; this innate immune response is intended to protect the host . Upon growth on purulent mucus from CF and non-CF patients , P . aeruginosa downregulates flagellin synthesis , thereby blunting the host protective immune response [34] , [35] . A third strategy is to compromise the host by suppressing the host defense responses . It has been suggested that the ability of P . aeruginosa to rapidly kill Drosophila is associated with downregulation of antimicrobial peptide expression by a yet-unknown mechanism that requires a putative S-adenosyl-methionine-dependent methyltransfrease [36] . We found that an unexpected feature of the transcriptional response to P . aeruginosa is the downregulation of several intestinally-expressed host defense effectors [7] , [37] . We hypothesized that repression of immune effector expression , such as thn-2 , spp-1 , and lys-7 , may represent a virulence mechanism used by P . aeruginosa to suppress host defenses . In this report , we identify both host and pathogen factors required for the downregulation of immune effectors during P . aeruginosa infection of C . elegans . We present data indicating that P . aeruginosa infection causes the activation of DAF-2 insulin-like signaling , which leads to translocation of DAF-16 protein from nuclei of intestinal cells and downregulation of DAF-16 transcriptional targets . Delocalization of DAF-16 requires DAF-2 and an upstream neuroendocrine signaling pathway , including the DAF-2 agonist INS-7 . Each of these effects is dependent on the P . aeruginosa two-component regulator GacA and the quorum-sensing regulators LasR and RhlR . Our results demonstrate that P . aeruginosa infection of C . elegans results in the suppression of intestinal immune defense through virulence factor mediated effects on the activity of insulin-like signaling in the intestine .
An important component of the innate immune response in plants and animals is the induced expression of host defense effectors following pathogenic challenge [38] . Several genes that are induced following infection and are important to protect C . elegans from pathogenic challenge have been identified . These host defense effectors include defensin ( abf-2 ) , saposin ( spp-1 ) , and several genes with homology to antimicrobial proteins: lysozymes ( lys-2 and lys-7 ) , thaumatin ( thn-2 ) , and a CUB-domain containing protein , F08G5 . 6 . The expression of abf-2 and spp-1 was induced following infection by the Gram-negative bacterium Salmonella typhimurium , and both genes were required to protect against S . typhimurium infection [20] . Independent microarray studies showed that lys-2 and F08G5 . 6 were induced following infection by P . aeruginosa and that thn-2 and lys-7 were induced by the Gram-positive pathogens E . faecalis and M . nematophilum [7]–[9] , [21] . Interestingly , spp-1 , thn-2 , and lys-7 expression was repressed during infection by P . aeruginosa [7] , [8] , [39] . This expression pattern is unexpected given that these genes are required for optimal survival on P . aeruginosa ( Figure S1 ) . To confirm the expression data , we used quantitative RT-PCR ( qRT-PCR ) to measure the expression of these genes in worms exposed to P . aeruginosa ( PA14 ) , E . faecalis ( V583 ) , and S . typhimurium ( SL1344 ) for 12 hours at 25°C ( Figure 1A–B ) . Three of the genes ( thn-2 , lys-7 , and spp-1 ) were significantly repressed by exposure to P . aeruginosa compared to the laboratory food source E . coli ( OP50-1 ) ( Figure 1A ) . Three of the genes ( abf-2 , F08G5 . 6 , and lys-2 ) were significantly induced by exposure to P . aeruginosa ( Figure 1B ) . In contrast to P . aeruginosa , none of the six genes tested were significantly repressed following exposure to either S . typhimurium or E . faecalis . Among the genes that were significantly repressed by exposure to P . aeruginosa , lys-7 was induced by exposure to S . typhimurium and E . faecalis , while thn-2 and spp-1 were induced by exposure to E . faecalis ( Figure 1A ) . Though we did not detect a significant induction of spp-1 by S . typhimurium following 12-hour exposure ( Figure 1A ) , spp-1 has been previously observed to be induced after 48-hour exposure to S . typhimurium [20] . Thus , the downregulation of known immune effectors appears to be an atypical response to infection that is characteristic of infection by P . aeruginosa because similar responses are not observed by exposure to S . typhimurium or E . faecalis . P . aeruginosa GacA is a two-component response regulator that is required for full virulence in C . elegans and mammals [40]–[42] . GacA regulates the production of molecules that are detrimental to the host , including pyocyanin , elastase , and exotoxin A [27] , [28] . We wondered whether the suppression of host defense effectors is an active outcome of infection: specifically , whether GacA regulates factors that are important in downregulating host defense gene expression in C . elegans . We therefore compared the expression of thn-2 , lys-7 , and spp-1 in worms exposed to the P . aeruginosa gacA mutant for 12 hours ( Figure 1C ) . In contrast to wildtype P . aeruginosa ( hereafter referred to as PA14 ) , none of the genes were repressed by exposure to an in-frame deletion mutant of gacA ( PA14 gacA ) . This indicates that downregulation of immune genes by PA14 requires gacA . The quorum-sensing regulators encoded by lasR and rhlR function downstream of GacA [27] . lasR and rhlR are also required for PA14 virulence in C . elegans ( [42] and Table S1 ) . As with exposure to PA14 gacA , thn-2 , lys-7 , and spp-1 were not repressed in worms exposed to a lasR transposon insertion mutant ( PA14lasR ) compared to OP50-1 ( Figure 1C ) . In worms exposed to a rhlR transposon-insertion mutant ( PA14rhlR ) , neither thn-2 nor lys-7 was downregulated , but spp-1 remained significantly repressed ( Figure 1C ) . Thus , the ability of PA14 infection to downregulate the expression of thn-2 and lys-7 requires factors that are dependent on gacA , lasR , and rhlR . By contrast , while the downregulation of spp-1 requires gacA and lasR , it is independent of rhlR . The PA14 gacA and PA14 lasR mutant strains are unable to colonize the worm intestine [42] . To determine whether the failure of PA14 gacA , PA14 lasR , and PA14 rhlR mutants to downregulate immune gene expression is a consequence of a low inoculum in the intestine , we compared the expression of thn-2 , lys-7 , and spp-1 in the C . elegans tnt-3 ( aj3 ) mutant following infection with the wildtype PA14 , PA14 gacA , PA14 lasR , and PA14 rhlR strains . The tnt-3 ( aj3 ) mutant is unable to grind bacteria , thus a large inoculum of live bacteria , including the nonpathogenic OP50-1 , accumulate in the intestinal lumen [13] , [20] . First , we observed that although the tnt-3 ( aj3 ) animals accumulate OP50-1 in the intestine , expression of thn-2 , lys-7 , and spp-1 was indistinguishable from expression in wildtype worms which do not accumulate OP50-1 ( t-test , p = 0 . 46 , 0 . 43 , and 0 . 07 , respectively ) . Importantly , despite the accumulation of intact PA14 gacA , PA14 lasR , or PA14 rhlR mutant bacteria within the intestinal lumen of tnt-3 ( aj3 ) animals , the expression of thn-2 , lys-7 , and spp-1 was not repressed ( Figure S2 ) . Thus , the lack of immune suppression by the PA14 gacA , PA14 lasR , and PA14 rhlR mutants is not due simply to limited intestinal colonization of wildtype worms . These results , coupled with the observation that S . typhimurium and E . faecalis infections do not downregulate thn-2 , lys-7 , and spp-1 expression ( Figure 1A ) , indicate that the mere presence of live bacteria in the intestinal lumen is insufficient to suppress the expression of a subset of immune genes . We conclude that a genetically regulated aspect of PA14 virulence , which is absent in S . typhimurium or E . faecalis , causes downregulation of a subset of immune effectors in C . elegans . Several Gram-negative bacterial pathogens suppress host immunity by employing the type III secretion system ( T3SS ) , which injects virulence effectors directly into host cytoplasm to inhibit or limit the duration of NF-κB and MAP kinase activation ( reviewed in [43] , [44] ) . In P . aeruginosa , T3SS is an important virulence determinant in pathogenesis in insects and mammals [45]–[48] . Type III secretion genes are under the control of the GacS/GacA two-component regulator and the quorum-sensing system [49] , [50] . To date , four T3SS effector proteins have been identified for P . aeruginosa: ExoS , ExoT , ExoU , and ExoY . In PA14 , only ExoT , ExoU , and ExoY are encoded in the genome and their expression requires PscD . Although the T3SS is induced during infection of the C . elegans intestine , it appears to be dispensable for C . elegans killing [46] , [51] . This led to the proposal that other virulence factors that play a predominant role in C . elegans pathogenesis could mask the effect of type III secretion effectors when death was used as the metric for the pathogenesis assay . We therefore determined whether the T3SS contributes to the suppression of C . elegans immune effectors , an arguably more sensitive assay . As previously observed , neither loss of any of the Type III effectors nor the entire repertoire of effectors in the ΔpscD mutant significantly affects the ability of these strains to kill C . elegans ( [46] and data not shown ) . We found that the ΔpscD mutant was still able to significantly suppress the expression of lys-7 and spp-1 , as measured by qRT-PCR ( Figure S3A ) . We further confirmed that the P . aeruginosa T3SS is not required for immune suppression by showing that neither ΔexoT , ΔexoU , ΔexoY , nor ΔpscD mutant significantly affected the expression of a lys-7 GFP-reporter ( Figure S3B ) . In Drosophila , downregulation of NF-κB-regulated antimicrobial peptide expression by P . aeruginosa is mediated by an unknown mechanism that requires an S-adenosyl-methionine-dependent methyltransferase domain-containing protein encoded by PA14_41070 [36] . A PA14_41070 transposon insertion mutant is not defective in the ability to downregulate lys-7 or spp-1 expression , as measured by qRT-PCR ( Figure S3A ) and by GFP-reporter gene expression of lys-7 ( Figure S3B ) . Thus , PA14_41070 is dispensable for immune suppression in C . elegans . To determine whether suppression of host defense gene expression is strictly associated with P . aeruginosa virulence , we tested several mutants that are impaired in C . elegans killing . First , we tested two genes that are part of the GacA-LasR-RhlR regulon: dsbA and pqsA . Expression of dsbA , which encodes a periplasmic dithiol:disulfide oxidoreductase , requires GacA [52] . DsbA is required for the formation of disulfide bonds in periplasmic proteins and important for proper folding of multiple virulence factors exported by Type II secretion , including elastase and lipase . Pseudomonas quinolone signal ( PQS ) system is the third component of the quorum-sensing signaling system , and it is regulated by Las and Rhl quorum-sensing systems [53] , [54] . Production of all known quinolone/quinolines in P . aeruginosa requires PqsA , an anthranilate-coenzyme A ligase that is the product of the pqsABCDE operon [55]–[57] . Both the dsbA and pqsA mutant strains are attenuated for killing C . elegans ( [42] and Table S1 ) . Yet , neither the dsbA nor the pqsA mutants is defective in the ability to downregulate lys-7 expression , as measured by a GFP-reporter ( Figure S3B ) . Thus , PQS and DsbA , despite their requirement for virulence are not necessary for host immune suppression in the C . elegans model . Because dsbA and pqsA are part of the GacA-LasR-RhlR regulon , these results suggest that only a subset of the genes regulated by the GacA two-component and acyl-homoserine lactone quorum-sensing systems are required for immune suppression . To determine the specificity of the GacA-LasR-RhlR regulon in immune suppression , we tested three additional genes that are not known to be part of this regulon: PA14_23420 , PA14_23430 , and PA14_59010 [58] , [59] . We found that while these mutants are attenuated for killing C . elegans ( Table S1 ) , they had no detectable defect in the ability to downregulate lys-7 expression as measured by a GFP-reporter ( Figure S3B ) . Overall these results indicate that virulence in P . aeruginosa is not strictly associated with immune suppression and that a subset of the GacA- , LasR- and RhlR-dependent factors are required for the downregulation of immune genes by P . aeruginosa . In C . elegans , at least three conserved signaling pathways contribute to host defense: p38 MAPK signaling , Sma/TGF-β signaling , and DAF-2 insulin-like signaling ( reviewed in [11] , [12] ) . We had previously noted that the transcriptional profiles of PA14-infected and daf-2 loss-of-function worms were overlapping , but the genes regulated in common tend to be regulated in opposite directions [7] . Here , we compared whole-genome transcriptional profiles of uninfected daf-2 mutants [16] , [60] to PA14-infected wildtype animals [7] , [8] and found that daf-2 mutants and PA14 infection have predominately discordant effects on gene expression across a range of data sets using a variety of criteria for comparison ( Table S6 , Table S7 , Figure S10A ) . This suggests that the gene expression pattern in PA14-infected animals is opposite of the pattern produced by reducing the activity of DAF-2 , such as occurs in loss-of-function daf-2 mutants . Importantly , genes that were inversely regulated by daf-2 and PA14 infection were enriched for immune effector genes , thus raising the possibility that PA14 infection activates DAF-2 insulin-like signaling ( Table S8 , Figure S10B; for details , see Text S1 ) . If indeed activation of DAF-2 insulin-like signaling mediates PA14 suppression of host defense effectors , then the ability of PA14 to suppress host defense effectors would be attenuated or eliminated when loss-of-function daf-2 ( e1370 ) mutants are infected with PA14 . Alternatively , if the transcriptional effect of daf-2 loss of function and PA14 infection operate in parallel , then the transcriptional response to PA14 will be unaffected in daf-2 ( e1370 ) animals . We therefore compared the change in gene expression following PA14 infection between wildtype and daf-2 ( e1370 ) animals using whole-genome microarrays . First , using the criteria of t-test p-values<0 . 05 and 2-fold up- or down-regulation , we identified 247 induced and 137 repressed genes in wildtype worms infected with PA14 for 24 hours compared to uninfected controls . We confirmed that the selection of these criteria did not affect our conclusions by repeating the analysis with a range of p-value and fold-change thresholds ( data not shown ) . Next , using this list of PA14-induced and -repressed genes , we compared the change in gene expression in response to PA14 in daf-2 ( e1370 ) and wildtype ( N2 ) animals ( Figure 2A ) . Separate linear regressions of induced and repressed genes revealed that the induction response to PA14 was largely intact in daf-2 ( e1370 ) animals ( r2 = 0 . 4280 , p<0 . 0001 ) , but the repression response to PA14 was substantially attenuated to the extent that the repression response observed in N2 and daf-2 ( e1370 ) was not significantly associated ( r2 = 0 . 001 , p = 0 . 3 ) . Comparison of induced and repressed genes provides an internal control for this analysis and indicates that attenuation of the downregulation of genes in response to PA14 infection does not simply reflect a failure of daf-2 animals to become infected by PA14 or to respond transcriptionally to PA14 infection . These results are consistent with the model that PA14 infection suppresses host defense genes through activation of the DAF-2 insulin-like signaling pathway . It also indicates that the induction of genes in response to PA14 infection is largely independent of DAF-2 . To examine whether the Sma/TGF-β signaling pathway could also contribute to the suppression of host defense genes following PA14 infection , we compared whole-genome expression data from infected and uninfected TGF-β receptor null mutant sma-6 ( wk7 ) and wildtype worms . Using the same parameters as the daf-2 ( e1370 ) analysis , we note that both the induction and repression of genes in response to PA14 infection were largely intact in sma-6 ( wk7 ) ( r2 = 0 . 5231 and 0 . 4051 , respectively , p<0 . 0001 each; Figure 2B ) . The correlation coefficients for induced and repressed genes were not significantly different . Comparison of the regression results from daf-2 ( e1370 ) with sma-6 ( wk7 ) is revealing . The correlations for induced genes between the daf-2 ( e1370 ) and sma-6 ( wk7 ) analyses ( r2 = 0 . 4280 and r2 = 0 . 5231 , respectively ) were not significantly different ( p = 0 . 09 , one-tailed test ) . Among the repressed genes , however , correlations with daf-2 ( e1370 ) were significantly less than with sma-6 ( wk7 ) ( p = 10−5 , one-tailed test ) . Together , the data indicate that the Sma/TGF-β pathway is unlikely to contribute substantially to the suppression of host defense genes by PA14 infection . To corroborate the results obtained from whole-genome microarray analysis , and also to analyze the involvement of p38 MAPK signaling , we repeated the transcriptional profile analysis using qRT-PCR measurement of a panel of 146 infection and stress response genes . We designed gene-specific qRT-PCR primers to a panel of 146 genes selected on the basis of their likely involvement in the response to infection and stress . Many immune and stress response genes are members of large gene families [7] , [61] . The use of gene-specific qRT-PCR primers overcomes the problem of cross hybridization of gene families in microarray studies and provides more precise measures of mRNA levels . Moreover , the use of genes with known or putative function in immune and stress response supports the inference that observed transcriptional effects are functionally important . We measured gene expression in young adult worms exposed to OP50-1 or PA14 for 12 hours for N2 , daf-2 ( e1370 ) , sma-6 ( wk7 ) , and sek-1 ( km4 ) , a p38 MAPKK null mutant , to obtain the change in gene expression following infection for each worm strain ( Table S2 ) . We repeated the linear regression analysis of induced and repressed genes , comparing the transcriptional response to PA14 in each mutant to N2 ( Figure 2C–2E ) . Transcriptional analysis of daf-2 ( e1370 ) using this targeted gene set indicated that the induction of immune and stress response genes in response to PA14 was largely intact in daf-2 ( e1370 ) animals ( r2 = 0 . 62 , p<0 . 0001 ) , but the repression of genes in response to PA14 was substantially attenuated to the extent that the correlation between N2 and daf-2 ( e1370 ) was not statistically significant ( r2 = 0 . 061 , p = 0 . 11; Figure 2C ) . This pattern of gene expression mirrors the result of the whole-genome analysis ( Figure 2A ) and provides further support that a substantial subset of the normal downregulation of gene expression in response to PA14 infection requires daf-2 , but the upregulation of gene expression is largely independent of daf-2 . In contrast to daf-2 ( e1370 ) , both induced and repressed genes in sek-1 ( km4 ) and sma-6 ( wk7 ) mutants correlated significantly with N2 ( Figure 2D–2E ) , thus corroborating the results of our whole-genome analysis with sma-6 ( wk7 ) . Visually , the induced and repressed linear regression lines are concordant for sek-1 ( km4 ) ( Figure 2D ) and sma-6 ( wk7 ) ( Figure 2E ) , but highly discordant in daf-2 ( e1370 ) ( Figure 2C ) . Analysis with a p38 MAPK mutant pmk-1 ( km25 ) yielded nearly identical results to sek-1 ( km4 ) : the response to PA14 infection in pmk-1 ( km4 ) correlated significantly ( r2 = 0 . 80 , p<0 . 0001 ) with the response in sek-1 ( km4 ) ( data not shown ) . To detect more subtle effects of sma-6 , sek-1 and daf-2 mutations on transcriptional responses to PA14 we compared the average differential expression of the immune and stress response genes under normal ( OP50-1 exposure ) and infection ( PA14 ) conditions between mutant ( Xmutant ) and wildtype ( Xwildtype ) worms using a paired t-test ( see Materials and Methods ) . The average difference in induction or repression ( XΔ = Xmutant−Xwildtype ) was calculated for each mutant-wildtype pair . This approach accounts for both the magnitude and direction of attenuation of the response to infection , with positive values of XΔ indicating attenuated repression and negative values of XΔ indicating attenuated induction . In sma-6 ( wk7 ) mutants , the correlation analysis indicated that both induction and repression were largely intact . Consistent with this analysis , the average difference in either induction or repression ( XΔ ) of immune and stress response genes in sma-6 ( wk7 ) mutants was not significantly different from wildtype ( induction: XΔ = 0 . 09 , p = 0 . 38; repression: XΔ = 0 . 00 , p = 0 . 99 ) . It remains possible that the increased susceptibility of sma-6 ( wk ) to PA14 may be a consequence of deregulation of immune gene expression that could not be detected by this analysis . In sek-1 ( km4 ) mutants , the average induction in response to infection is significantly less than that of wildtype ( induction: XΔ = −0 . 61 , p<10−4 ) , indicating that the induction response is attenuated when p38 signaling is abrogated . Although there is a trend towards attenuation of host gene repression in sek-1 ( km4 ) , the overall effect is not statistically significant for this set of 42 genes ( XΔ = 0 . 38 , p = 0 . 16 ) . Thus , a definitive conclusion regarding the requirement of p38 in repression of immune genes following PA14 infection awaits a whole-genome analysis . By this analysis we are able to show that p38 MAPK signaling is required for the induction of many genes during PA14 infection , consistent with a previous report that p38 MAPK is an important regulator of the transcriptional response to PA14 [8] . Immune and stress response genes that require sek-1 for induction by PA14 include clec-85 , lys-1 , lys-8 , F35E12 . 5 , Y40D12A . 2 and gst-38 . Interestingly , with the exception of gst-38 , the basal expression of these genes under normal growth conditions on OP50-1 also requires sek-1 ( Figure S4A–S4F ) . We also identified a class of genes whose expression levels during normal growth and following infection require sek-1 but whose induction or repression in response to PA14 do not require sek-1; they include lys-2 , cpr-3 , spp-18 , F55G11 . 2 , and T10D3 . 6 ( Figure S4G–S4K ) . For example , expression levels of lys-2 in sek-1 ( km4 ) animals are 0 . 5% of levels in wildtype worms both in worms exposed to OP50-1 and worms exposed to PA14 , yet expression of lys-2 is induced by a similar ratio in wildtype and sek-1 mutant worms ( Figure S4G ) . The average differences in induction and repression of immune and stress response genes in daf-2 ( e1370 ) mutants were both significantly different from wildtype ( induction: XΔ = −0 . 36 , p = 0 . 0004; repression: XΔ = 1 . 32 , p<10−5 ) . Thus , by this analysis we are able to detect a small but significant attenuation in gene induction following infection in daf-2 ( e1370 ) mutants , suggesting that daf-2 activity is required for the induction of a small subset of infection-responsive genes , which include abf-2 , lys-2 , F08G5 . 6 , ZK6 . 11 , and C17H12 . 8 ( Table S2 ) . The effect of daf-2 ( e1370 ) on repression of gene expression in response to infection was the strongest observed effect , consistent with the regression analysis . The immune and stress response genes that require daf-2 for repression include thn-2 , lys-7 spp-1 , and gst-4 ( Table S2 ) . Importantly , among sma-6 ( wk7 ) , sek-1 ( km4 ) , and daf-2 ( e1370 ) , only daf-2 ( e1370 ) significantly attenuated repression of infection response genes . Together , the transcriptional analyses confirm that of the three immune signaling pathways , DAF-2 insulin-like signaling is required for the downregulation of many genes during PA14 infection . Loss-of-function daf-2 mutants are resistant to bacterial pathogens , and this resistance is dependent on the FOXO transcription factor DAF-16 [15] . DAF-2 regulates DAF-16 at least in part through the activation of phosphoinositide 3-kinase ( PI3-kinase ) , which is encoded by age-1 [62] , [63] . PI3-kinase potentiates the activity of several serine threonine kinases , including homologs of mammalian PDK1 , AKT , and SGK [64]–[66] . These kinases phosphorylate DAF-16 , retaining it in the cytoplasm and suppressing DAF-16 transcriptional activity [67] , [68] . To determine whether DAF-16 is required for the suppression of host defense genes , we quantified the mRNA levels of thn-2 , lys-7 , and spp-1 by qRT-PCR in N2 , daf-2 ( e1370 ) , daf-16 ( mu86 ) , and double mutant daf-16 ( mu86 ) ;daf-2 ( e1370 ) worms under normal growth conditions ( on OP50-1 ) or following infection with PA14 . Downregulation of thn-2 , lys-7 , and spp-1 by PA14 exposure was abolished in daf-2 ( e1370 ) ( Figure 3A–3C ) , confirming that daf-2 activity is required for the downregulation of a number of functionally important immune genes . Next , we inactivated each of these genes by RNAi in daf-2 ( e1370 ) and compared the degree of colonization by a PA14 strain that expresses GFP ( PA14-GFP ) in these animals to daf-2 ( e1370 ) animals exposed to vector control . Knockdown of thn-2 , lys-7 , and spp-1 individually resulted in a significant increased in colonization ( Figure S5 ) , indicating that the ability to prevent downregulation of immune genes contributes to the resistance of daf-2 ( e1370 ) to PA14 . Under normal growth conditions , both thn-2 and lys-7 were expressed at lower levels in daf-16 ( mu86 ) compared to N2 , indicating that daf-16 is required for basal expression of these immune effectors ( Figure 3A–3B ) . Following infection with PA14 , the levels of thn-2 and lys-7 mRNA were not reduced further in daf-16 ( mu86 ) , indicating that suppression of thn-2 and lys-7 by PA14 requires daf-16 ( Figure 3A–3B ) . Curiously , the expression of lys-7 in daf-16 ( mu86 ) ;daf-2 ( e1370 ) double mutants was intermediate to the expression in either single mutant . Nonetheless , lys-7 expression was not repressed by PA14 infection in either single or double mutants . These results suggest that basal levels of lys-7 expression are regulated by daf-2-dependent factors in addition to DAF-16 . By contrast , under normal growth conditions , spp-1 expression was not significantly different between N2 and daf-16 ( mu86 ) , indicating that the basal expression of spp-1 is independent of daf-16 ( Figure 3C ) , in contrast to previous reports [39] . Curiously , as in wildtype animals , spp-1 expression was significantly downregulated in daf-16 ( mu86 ) and daf-16 ( mu86 ) ;daf-2 ( e1370 ) mutants , indicating that while the downregulation of spp-1 is daf-2-dependent , it does not require daf-16 . Overall , these results implicate DAF-2 and DAF-16 in the downregulation of thn-2 , lys-7 , and spp-1 during PA14 infection . DAF-16 appears to be required for the expression of thn-2 and lys-7 , but the role of DAF-16 in the regulation of spp-1 expression is more complex . Next , we determined whether the induction of abf-2 , F08G5 . 6 , and lys-2 by PA14 infection is mediated by daf-2 and daf-16 ( Figure 3D–3F ) . In contrast to wildtype , the expression of abf-2 was not significantly induced in daf-2 ( e1370 ) , daf-16 ( mu86 ) , and daf-16 ( mu86 ) ;daf-2 ( e1370 ) mutants following infection , suggesting that the induction of abf-2 is modulated by the DAF-2/DAF-16 signaling pathway ( Figure 3D ) . The induction of F08G5 . 6 was not statistically significant only in daf-2 ( e1370 ) , suggesting that F08G5 . 6 induction requires daf-2 but not daf-16 ( Figure 3E ) . The expression of F08G5 . 6 in daf-2 and daf-16 single and double mutants mirrors the expression pattern of spp-1 . Thus , the induction of some genes is dependent on daf-2 as suggested by the paired t-test analysis performed on the immune and stress response gene set . Expression of lys-2 was largely unaffected in the insulin-like signaling mutants . However , expression of lys-2 was higher in daf-2 ( e1370 ) under basal conditions ( on OP50-1 ) . This difference was not observed in worms exposed to PA14 , resulting in net a reduced induction of lys-2 in daf-2 ( e1370 ) ( Figure 3F ) . Overall , the gene expression analyses suggest that while DAF-2 and DAF-16 are largely dispensable for the induced response to PA14 infection , some genes do require DAF-2 for induction . In addition to immune effectors , the insulin-like signaling pathway also regulates stress response genes [16] , [69] . For example , sod-3 encodes a well-characterized DAF-16-regulated superoxide dismutase that is associated with oxidative stress resistance and longevity in C . elegans , presumably through its reactive oxygen species detoxification activity [16] , [70] , [71] . We showed by qRT-PCR that the expression of sod-3 was significantly repressed following 24-hour exposure to PA14 ( Figure S6 ) , consistent with previous microarray studies [8] . This further supports the model that PA14 activates DAF-2 and inhibits DAF-16 . Suppression of an antioxidant may be beneficial to P . aeruginosa , which produces pyocyanin as a virulence determinant that causes oxidative damage to host tissues [30] . However , knockdown of sod-3 by RNAi in daf-2 animals did not significantly affect the ability of daf-2 mutants to resist colonization by PA14 ( Figure S5 ) , perhaps because of the expression of other genes that contributes to oxidative stress resistance , such as gst-4 , mtl-1 , and ctl-1 , are also increased in daf-2 mutants [16] . We note that the expression of gst-4 , which encodes a glutathione-S transferase [72] is also downregulated during PA14 infection , as determined by reporter gene expression ( Figure S7A ) and qRT-PCR analyses ( Figure S7B ) . Downregulation of gst-4 by PA14 requires gacA , lasR , and rhlR ( Figure S7A ) , and is suppressed by daf-2 ( e1370 ) but not daf-16 ( mu86 ) ( Figure S7B ) . Thus , activation of daf-2 signaling during P . aeruginosa infection results in the simultaneous downregulation of stress response and immune effectors genes that together could aid in the pathogenesis of these bacteria . The transcriptional effects of daf-2 mutants are largely dependent on DAF-16 [16] . Under normal growth conditions , the DAF-2 pathway is active and DAF-16 protein is distributed predominately in the cytoplasm of every tissue . Conditions that reduce signaling in the DAF-2 pathway , including heat stress , ablation of the germline , and loss of daf-2 function , cause DAF-16 protein to be localized in the nucleus [68] , [73] . DAF-16 translocates from the nucleus to the cytoplasm when DAF-2 signaling is increased [73] . We determined the effect of PA14 infection on DAF-16 localization using transgenic worms that express a functional DAF-16::GFP fusion protein [73] . We confirmed that exposure to PA14 does not cause increased DAF-16 nuclear localization [7] , [8] . Our gene expression data suggested that PA14 infection activates DAF-2 signaling and could consequently result in delocalization of DAF-16 from the nucleus . To measure this effect , it was necessary to first localize DAF-16 to the nucleus and then compare the reversal of that localization between infected and uninfected animals . We used two independent means to drive DAF-16::GFP to the nucleus: brief heat shock and removal of the germline , both of which are reported to induce DAF-16 nuclear localization in a DAF-2-independent manner [74] , [75] . Heat shock causes transient nuclear localization that reverses over time , whereas the degree of nuclear localization caused by loss of germline proliferation is relatively stable in young worms . For the heat-shock approach , worms exposed to 37°C dry heat for 70 to 90 minutes were shifted onto plates containing OP50-1 , PA14 , or PA14 gacA . After 16 hours at 25°C , almost all of the worms exposed to OP50-1 ( Figure 4A ) or PA14 gacA ( Figure 4B ) retained nuclear DAF-16::GFP . By contrast , in a majority of the PA14-infected population , DAF-16::GFP was delocalized from the nuclei of intestinal cells ( Figure 4C–4D ) . We quantified this effect by counting the number of intestinal nuclei in which DAF-16::GFP fluorescence was apparent . As shown in Figure 4E , the number of nuclei with visible DAF-16::GFP nuclear localization was significantly reduced in PA14-infected worms compared to OP50-fed worms ( p<0 . 001 ) . Because the distribution of nuclei containing DAF-16::GFP per worm was distinctly bimodal ( representative examples shown in Figures 4C and 4D ) , individual worms could be classified as having predominately nuclear-localized or predominately nuclear-delocalized ( i . e . , cytoplasmic ) DAF-16::GFP in subsequent assays . Following 16 hours recovery from acute heat shock , approximately 80% of PA14-infected worms no longer retained the DAF-16::GFP fusion protein in the nucleus , whereas worms exposed to OP50-1 or PA14 gacA were not significantly affected ( Figure 4F , p<0 . 0001 ) . DAF-16::GFP remains nuclear localized in heat-shocked worms exposed to OP50-1 or PA14 gacA for 48 to 60 hours . To confirm that the rapid delocalization of DAF-16 is a general physiological response to PA14 infection and not an artifact specific to the use of heat shock stimulus to nuclear localize DAF-16 , we examined the effect of PA14 infection on nuclear localized DAF-16 using worms in which germline proliferation was eliminated . Loss of germline proliferation causes nuclear localization of DAF-16 in the intestinal cells of adult worms [68] . RNAi knockdown of cdc-25 . 1 produces worms that lack germline proliferation [76] and localizes DAF-16::GFP to intestinal nuclei . Nuclear localization of DAF-16 due to loss of germline proliferation requires kri-1 [77] . We confirmed that knockdown of cdc-25 . 1 by RNAi affects DAF-16::GFP nuclear localization through its effect on germline proliferation by showing that nuclear localization of DAF-16::GFP could be suppressed when kri-1 was knocked down by RNAi ( Figure S8 ) . In adult worms without proliferating germline , PA14 infection caused delocalization of nuclear DAF-16 in approximately 75% of worms after 16 hours ( p<0 . 0001 ) , whereas worms exposed to OP50-1 or PA14 gacA were not significantly affected ( Figure 4G ) . Delocalization of DAF-16::GFP upon PA14 infection was not due to a generalized loss of nuclear localization because we failed to observe a loss of nuclear integrity . Nor was it due to a loss of the ability to retain transcription factors in the nucleus because other nuclear localized GFP constructs , including a translational fusion of GFP to the GATA transcription factor ELT-2 , remained nuclear over the course of the experiment ( data not shown ) . In addition , DAF-16 nuclear delocalization caused by PA14 infection was reversible by subsequent heat shock ( data not shown ) , indicating that PA14 infection does not simply render DAF-16 incapable of nuclear translocation or retention . Notably , the nuclear delocalization of DAF-16 occurred early during PA14 infection and affected DAF-16 in intestinal nuclei . Thus , delocalization of DAF-16 occurred in the appropriate time and location to account for the transcriptional patterns observed during PA14 infection , providing an independent category of evidence for the model that PA14 infection activates the DAF-2 insulin-like signaling pathway . DAF-16 target genes were downregulated following infection by P . aeruginosa ( PA14 ) , but not by E . faecalis ( V583 ) or S . typhimurium ( SL1344 ) ( Figure 1A ) . We therefore hypothesized that infection with V583 and SL1344 would not result in the translocation of DAF-16 from the nucleus . Because survival of worms on V583 and SL1344 is extended compared to PA14 , delocalization of DAF-16 might occur later in worms exposed to V583 or SL1344 than in worms exposed to PA14 . We therefore used worms lacking a proliferating germline to cause DAF-16 nuclear localization to ensure that nuclear localization of DAF-16 is distinguishable for at least 96 hours . Consistent with the failure of V583 and SL1344 to downregulate DAF-16 target genes ( Figure 1A ) , there was no significant decrease in DAF-16 nuclear localization in worms exposed to these pathogens ( Figure 4G ) . Finally , consistent with the requirement for gacA , lasR , and rhlR for the downregulation of immune gene expression during PA14 infection ( Figure 1C ) , similar to the PA14 gacA mutant , the rhlR and lasR mutants also failed to cause significant delocalization of DAF-16::GFP compared to uninfected controls ( Figure 4H ) . Thus , we can conclude that activation of DAF-2 affects the nuclear localization of DAF-16 and the transcription of DAF-2-dependent immune genes , such as thn-2 , lys-7 , and spp-1 . This effect is specific to infection by P . aeruginosa and requires GacA- , LasR- , and RhlR-regulated virulence factors . The results presented thus far indicate that PA14 infection activates DAF-2 , resulting in the translocation of DAF-16 from the nucleus and the DAF-2-dependent repression of immune gene expression . They further suggest that loss-of-function mutations in daf-2 would suppress the delocalization of DAF-16 . Indeed , when we compared DAF-16::GFP localization in daf-2 ( e1370 ) ; DAF-16::GFP animals that were exposed to either OP50-1 or PA14 , no significant difference in DAF-16::GFP localization was observed between PA14-infected and uninfected controls over the course of 4 days ( Figure 5A ) . This indicates that daf-2 is required for the delocalization of DAF-16 during PA14 infection and is consistent with the failure of PA14 to downregulate host effector genes in daf-2 ( e1370 ) . It further suggests that PA14 infection suppresses C . elegans immune gene expression by affecting host components that are upstream of daf-2 . daf-2 encodes the only homolog of a mammalian insulin/IGF-1-family receptor in the C . elegans genome [78] , and its activity is affected by insulin-like molecules [79] , [80] . Therefore , insulin-like peptides are attractive candidates to be subverted by P . aeruginosa to activate DAF-2 . As shown in Figure 5B , two insulin-like peptides , ins-7 and ins-11 , were upregulated in worms exposed to PA14 . Several lines of evidence implicate ins-7—and not ins-11—as contributing to the activation of DAF-2 during PA14 infection . First , ins-7 expression is not induced by exposure to either E . faecalis or S . typhimurium , but ins-11 expression is induced by exposure to E . faecalis ( Figure 5B ) . Also , ins-7 is not induced in worms exposed to PA14 gacA , lasR , or rhlR mutants ( Figure 5B and unpublished data ) . Moreover , ins-7 is known to be an insulin agonist [16] , [80] . Thus , the induction of ins-7 , but not ins-11 , is concordant with the activation of DAF-2 by PA14 but not E . faecalis infection . Second , the ins-7 deletion mutant ins-7 ( tm1907 ) is resistant to PA14 infection , but the ins-11 deletion mutant ins-11 ( tm1053 ) is not distinguishable from wildtype worms with respect to susceptibility to PA14 ( Figure S9 , Table S3 ) . Lastly , RNAi knockdown of ins-7 suppresses the effect of PA14 infection on DAF-16 nuclear delocalization , whereas ins-11 RNAi knockdown has no distinguishable effect ( Figure 5C ) . To confirm that ins-7 is required for the effect of PA14 on DAF-16 localization , we examined DAF-16::GFP localization in the deletion mutant ins-7 ( tm1907 ) . Loss of ins-7 suppressed the effect of PA14 infection on DAF-16 nuclear delocalization in worms lacking germline proliferation ( Figure 5D ) , indicating that ins-7 is required for the effect of PA14 on DAF-16 nuclear localization . daf-16 null mutants are indistinguishable from wildtype in their ability to survive infection by a variety of pathogens [8] , [15] , [23] , [81] . However , the phenotype that results from the loss of gene function in an entire organism is the combination of the effects on various tissues; and the tissue required for daf-16 in immune function has not been investigated . The profound effects of PA14 infection on insulin-like signaling , and the central role for DAF-16 in that interaction , led us to reevaluate the role of DAF-16 in defense against bacterial pathogens . Several lines of evidence suggested an important role for DAF-16 in the intestine . First , the intestine is the site of PA14 infection [82] , and the major site of expression of host defense genes including spp-1 and lys-7 [7] , [39] . Second , resistance to PA14 is associated with nuclear localization of DAF-16 specifically in the intestine . Loss of germline proliferation , which causes DAF-16-dependent resistance to PA14 ( unpublished data ) , causes DAF-16 nuclear localization predominately in the intestine [68] . A forward genetic screen for enhanced resistance to PA14 identified mutants with enhanced nuclear localization of DAF-16 in the intestine [81] . Similarly , we have observed that loss of ins-7 caused DAF-16::GFP nuclear localization primarily in intestinal cells ( unpublished data ) . Third , DAF-16 nuclear delocalization during PA14 infection is most evident in intestinal cells . Thus , we sought to examine the function of intestinal DAF-16 by knocking down the expression of daf-16 only in the intestine . Tissue-specific knockdown of gene expression can be achieved in C . elegans using strains in which the RNAi-deficient rde-1 mutant is rescued by expressing a transgene carrying the rde-1 gene in a specific tissue , such as intestine [83] , hypodermis or muscle [84] . The strain VP303 expresses rde-1 in the intestine of an rde-1 ( ne219 ) mutant background , allowing for intestine-restricted RNAi knockdown [83] , [85] . VP303 and N2 worms are indistinguishable for resistance to PA14 ( Table S4 ) . As expected from previous reports , [8] , [15] , [23] , [81] , RNAi knockdown of daf-16 in wildtype N2 worms had no effect on susceptibility to PA14 ( Figure 6A ) . RNAi knockdown of daf-16 in VP303 worms , however , caused enhanced susceptibility to PA14 ( Figure 6B ) . To confirm the specificity of VP303 for intestine-specific knockdown , we exposed N2 and VP303 strains to bacteria that express double-stranded RNA corresponding to a muscle-specific gene unc-22 , which encodes for twitchin that functions in the muscles to regulate the actomyosin contraction-relaxation cycle and to maintain normal muscle morphology [86] . As expected , RNAi against unc-22 resulted in the canonical twitching phenotype in N2 but not in the VP303 strain . unc-22 RNAi also has no effect on pathogen resistance in both the N2 and VP303 strains ( Table S4 ) . Recently , the hypodermal tissue has also been shown to contribute to immune response to a fungal pathogen [87] . Using the NR222 strain , in which RNAi knockdown is restricted to the hypodermis , we showed that loss of daf-16 in the hypodermis is not required for pathogen resistance ( Table S4 ) . These results indicate that DAF-16 is required in the intestine for resistance to PA14 , whereas loss of DAF-16 in the intestine , in combination with loss of DAF-16 in non-intestinal tissues , has an overall neutral effect on the ability of worms to defend against PA14 infection . Intestinally but not hypodermally expressed DAF-16 is essential for resistance to PA14 , a function that was previously masked in studies examining the requirement for DAF-16 in the whole worm .
Models of host-pathogen interactions predict that pathogen challenge will result in the induction of host defense genes . Repression of host defense genes is often associated with suppression of host defense pathways by the pathogen . Using quantitative RT-PCR , we confirmed that known host defense effectors , including thn-2 , lys-7 , and spp-1 are downregulated during PA14 infection ( Figure 1A ) . Because knockdown of basal expression of thn-2 , lys-7 , and spp-1 by RNAi resulted in enhanced susceptibility to PA14 ( Figure S1 ) , suppression of their expression during infection should compromise host defense . The observation that knockdown of thn-2 , lys-7 , and spp-1 by RNAi causes enhanced sensitivity to PA14 despite the downregulation of their expression in PA14-infected worms is explained in part by the fact that expression levels drop following infection whereas expression levels are already reduced to low levels when RNAi-treated worms are exposed to PA14 . The downregulation of these host defense effectors is not a typical response of C . elegans to pathogen challenge; the expression of these host effectors was induced or unaffected in response to E . faecalis and S . typhimurium ( Figure 1A ) . A large number of host defense effectors are efficiently induced in response to PA14 infection , suggesting that the downregulation of a particular set of host defense genes is a specific effect ( Figure 1B and Table S2 ) . Also , repression of a specific subset of host defense effectors by PA14 is likely to represent a specific interaction between P . aeruginosa and C . elegans because PA14 requires the virulence regulatory genes gacA , lasR and rhlR to suppress host defense genes ( Figure 1C ) . gacA , lasR and rhlR mutants are each attenuated in virulence ( Table S1 ) , suggesting a link between virulence and the downregulation of host defense effectors . The specific requirement of GacA- , LasR- and RhlR-regulated virulence factors in immune suppression is supported by the observation that the PA14_23420 , PA14_23430 , PA14_59010 mutants that are attenuated in virulence are not defective in immune suppression ( Figure S3B ) . As an initial effort to define the GacA- , LasR- and RhlR-regulated virulence factors that are required for immune suppression , we showed that dsbA , pqsA and the T3SS , all of which have been shown to be under the control of the GacS/GacA two component regulator and the quorum-sensing system [49] , [50] , [52]–[54] are not required for the downregulation of lys-7 expression ( Figure S3B ) . The hypothetical protein , PA14_41070 that contains the S-adenosyl-methionine ( SAM ) -dependent methyltransferase domain that is required for downregulation of Drosophila NF-κB-regulated antimicrobial peptides expression [36] is also dispensable for immune suppression in C . elegans ( Figure S3B ) . Overall these results suggest that the ability of P . aeruginosa to suppress C . elegans host defense effectors requires a subset of GacA- , LasR- and RhlR-regulated virulence factors and are not merely reflections of attenuation of virulence . We have thus provided evidence that we have identified a new mechanism of host immune suppression . This mechanism does not require the SAM-dependent methyltransfrease or the type III secretion system , which have been previously implicated in host immune suppression through their effects on NF-κB and MAPK signaling [36] , [43] , [44] . Instead , it requires the GacA two-component regulator and the LasR and RhlR quorum-sensing regulators to regulate factors necessary to subvert host defense . These factors , which we showed are likely to be independent of DsbA and quinolone signaling , could potentially be identified by screening for P . aeruginosa mutants that fail to downregulate the expression of host defense effectors , a strategy that we are actively pursuing . Finally , as discussed below , this immune suppression is mediated by the host insulin-like signaling pathway , instead of the MAPK and NF-κB pathways . The specific downregulation of the host defense effectors thn-2 , lys-7 , and spp-1 during P . aeruginosa infection ( Figure 1A ) suggested that a host defense signaling pathway was being subverted by P . aeruginosa to repress host defenses . Gene expression and host protein localization studies support a model that PA14 infection activates the DAF-2/DAF-16 insulin-like signaling pathway , resulting in the downregulation of DAF-16-regulated immune genes ( Figure 7 ) . The downregulation of thn-2 , lys-7 , and spp-1 during PA14 infection was abolished in daf-2 loss-of-function mutants ( Figure 3A–3C ) . The requirement for daf-2 for gene downregulation during infection held true when the gene expression analysis was extended to include the entire genome by microarray ( Figure 2A ) or to a set of 146 candidate immune and stress genes that were measured more precisely by qRT-PCR ( Figure 2C ) . Comparison of the transcriptional response to infection in mutants of each of the p38 MAPK , Sma/TGF-β , and insulin-like signaling pathways to the response in wildtype N2 worms confirms that the insulin-like signaling mutant , daf-2 ( e1370 ) , suppresses a portion of the wildtype response to PA14 infection in a fashion distinct from the effects of loss of p38 MAPK or TGF-β signaling ( Figure 2C–2E ) . The model we propose in Figure 7 predicts that during PA14 infection , activation of insulin-like signaling will result in the inhibition of DAF-16 . Inhibition of DAF-16 by insulin-like signaling is mediated by phosophorylation of DAF-16 by serine threonine kinases that are homologous to mammalian AKT and SGK , and results in the cytoplasmic retention of DAF-16 [68] , [73] . We used several assay conditions to examine the nuclear localization of DAF-16 during PA14 infection , providing evidence that PA14 infection causes DAF-16 nuclear delocalization ( Figure 4 ) . Based on the transcriptional response data ( Figure 1 ) , we further predicted that nuclear delocalization would occur in response to wildtype PA14 , but would not occur in response to infection by E . faecalis or S . typhimurium , and that PA14 mutants of gacA , lasR and rhlR would also be defective for the ability to cause delocalization of nuclear DAF-16 . Each of these predictions was confirmed when tested ( Figure 4G–4H ) , suggesting that DAF-16 delocalization is a PA14-infection specific effect . The model also predicted that while stimuli that function in parallel to insulin-like signaling to cause DAF-16 nuclear localization can be reversed by PA14 infection , such as heat shock and loss of germline proliferation , mutations that disrupt insulin-like signaling would also disrupt the DAF-16 nuclear delocalization caused by PA14 . We confirmed that nuclear localization of DAF-16 in the insulin-like receptor mutant daf-2 ( e1370 ) was not affected by PA14 infection ( Figure 5A ) . Finally , we showed that PA14 infection , but not infection by E . faecalis , S . typhimurium , or PA14 gacA caused increased expression of the insulin-like peptide ins-7 , suggesting that ins-7 may participate in signaling upstream of daf-2 in response to PA14 infection ( Figure 5B ) . Consistent with this hypothesis , we found that a deletion mutant of ins-7 attenuated the ability of PA14 to cause nuclear delocalization of DAF-16 ( Figure 5C ) . Collectively , the expression profile and DAF-16 localization data indicate that PA14 infection induces the expression of ins-7 to activate insulin signaling that leads to inhibition of DAF-16 and downregulation of immune gene expression . In a separate report , we showed that a neuroendrocine signaling axis that functions upstream of the DAF-2/DAF-16 pathway to regulate lifespan [88] , [89] and dauer formation [90] also regulates innate immunity . Regulation of innate immunity is mediated by the expression of ins-7 in the neurons ( unpublished data ) . We showed that mutants with decreased neurosecretion , such as unc-64 ( e246 ) and unc-31 ( e928 ) , are more resistant to PA14 because they express significantly higher levels of immune effectors due to constitutive nuclear localization of intestinal DAF-16 . In that report , we tested whether neuronal function was required for activation of DAF-2 by PA14 infection . We found that constitutive nuclear localization of DAF-16::GFP in neurosecretion defective mutants , such as unc-64 ( e246 ) is not reversed by exposure to PA14 ( data not shown ) . Taken together , the data indicate neuronal secretion of an insulin-like peptide , INS-7 , contributes to activation of DAF-2 insulin-like signaling during PA14 infection . It will be interesting to determine how PA14 infection induces the expression of ins-7 in neurons and thereby suppress immune gene expression . Activation of DAF-2 appears to account for a substantial proportion of the downregulation of host defense genes during PA14 infection , but is less important for the upregulation of host defense genes ( Figure 2A and 2C ) . To understand the mechanisms contributing to gene upregulation during infection , we also examined the contributions of the Sma/TGF-β and p38 MAPK pathways to the transcriptional response to PA14 ( Figure 2B , 2D , 2E ) . For many genes , the transcriptional response to PA14 is intact in mutants of all three pathways tested ( Table S2 ) . This indicates that the regulation of the transcriptional response to PA14 is redundant and/or that additional pathways contribute substantially to the transcriptional response to PA14 . Functional redundancy in the regulation of host immune effectors is a conserved feature of innate immunity [91] . In light of this observation , it is especially notable that the downregulation of a substantial number of genes is dependent on DAF-2 insulin-like signaling . The suppression of spp-1 by PA14 ( Figure 3C ) , unlike the suppression of thn-2 and lys-7 ( Figure 3A and 3B ) , is not entirely DAF-16 dependent , suggesting additional layers of complexity in the regulation of DAF-2 target genes . Neither p38 MAPK nor Sma/TGF-β is required for the downregulation of spp-1 ( Figure S4 and Table S2 ) . The factor that contributes to the downregulation of spp-1 remains unknown , but may function downstream of DAF-2 in cooperation with DAF-16 ( Figure 7 ) . A number of transcriptional co-regulators have been identified which regulate lifespan and stress resistance in conjunction with DAF-16 [75] , [92] , [93] . We considered two transcription factors , ELT-2 and SKN-1 , as likely candidates because they are also expressed in the intestine . elt-2 encodes a GATA transcription factor that is required for a substantial portion of the transcriptional response to PA14 [7] , and is required to protect C . elegans from infection by pathogens [7] , [23] . However , the pathways that act upstream of ELT-2 in the regulation of immune defense has not be elucidated . Intriguingly , a CTTATCA ( reverse complement: TGATAAG ) DNA motif that is enriched in the 5-prime flanking regions ( 5′-flank ) of DAF-2/DAF-16-regulated genes [16] is essentially identical to a GATA-like motif ( TGATAAGA ) that is enriched in the 5′-flank of genes that are significantly up- or down-regulated in worms exposed to P . aeruginosa [7] , and each is a derivative of the consensus GATA motif ( WGATAR ) . For example , the 5′-flank of spp-1 , thn-2 , gst-4 , lys-7 , and sod-3 each contain GATA motifs . This motif is distinct from the canonical FOXO binding site ( TRTTTAG ) , which has been shown to bind DAF-16 in vitro [70] . The FOXO-binding DNA motif is present in the 5′-flank of lys-7 and sod-3 , but not spp-1 , thn-2 , or gst-4 . Moreover , knockdown of elt-2 by RNAi reduces the expression of lys-7 and spp-1 under uninfected conditions ( data not shown ) and enhances the relative downregulation of thn-2 during PA14 infection [7] . Overall , these findings suggest that ELT-2 or another GATA-motif-binding transcription factor may function downstream of DAF-2 together with DAF-16 to regulate the expression of immune-response gene . One instantiation of the consensus-binding motif of the transcription factor SKN-1 ( ATGATAAT ) is remarkably similar to the WGATAR motifs found upstream of genes regulated by DAF-2 and PA14 infection . Recently , it has recently been shown that for lifespan SKN-1 is regulated by insulin-like signaling [93] . We observed that knockdown of skn-1 by RNAi throughout the life of the animal caused enhanced sensitivity to PA14 ( unpublished data ) . Thus , we wondered whether SKN-1 might contribute to DAF-2-dependent regulation of gene expression following PA14 infection . Knockdown of skn-1 by RNAi does not affect the downregulation of thn-2 , spp-1 , or lys-7 ( data not shown ) . gst-4 is known to be SKN-1-regulated . However , like thn-2 , spp-1 , and lys-7 , knockdown of skn-1 expression by RNAi does not abolish the downregulation of gst-4 following PA14 infection , despite causing a reduction in the basal level of gst-4 expression ( Figure S7C ) . Future work must focus on determining transcription factors in addition to DAF-16 that accounts for the DAF-2-dependent downregulation of host defense genes . We also note that not every downregulated gene is dependent on DAF-2 insulin-like signaling . For example , following PA14 infection , acdh-1 is strongly repressed in wildtype and all of the mutants tested , including daf-2 ( e1370 ) ( Table S2 ) . This suggests that factors in addition to DAF-2 insulin-like , Sma/TGF-β , and p38 MAPK signaling may contribute to the repression of host defense genes during PA14 infection . However , acdh-1 expression is also downregulated in worms exposed to E . faecalis , E . carotovora , P . luminescens , S . marcescens , S . typhimurium and PA14 gacA ( M . Nandakumar and M . -W . Tan , unpublished data , and [21] ) , suggesting that the downregulation of acdh-1 may represent a different phenomena than the repression of other host defense genes . Given the dynamic regulation of insulin-like signaling during infection , and particularly the complex role for DAF-16 in this interaction , we wondered why null mutants of daf-16 are nonetheless indistinguishable from wildtype animals for their ability to survive infection by a variety of bacterial pathogens [8] , [15] , [23] , [81] . Expression of daf-16 in the intestine partially enhanced pathogen resistance of a daf-16 ( mu86 ) ;daf-2 ( e1370 ) worm ( unpublished data ) , consistent with the intestine being the site of infection , and the major site of immune gene expression . Additional observations that germline signaling , neuroendocrine signaling , and PA14 infection primarily modulate DAF-16 nuclear localization in the intestine highlighted the importance of intestinal DAF-16 . A compensatory mechanism or other complex interaction acting across tissues could potentially mask the function of daf-16 in the intestine . Using of intestine-specific daf-16 knockdown by RNAi we show that DAF-16 is required for a protective response against pathogen . Supporting this finding further is the observation that enhanced resistance of ins-7 to PA14 is associated with constitutive nuclear localization of DAF-16 specifically in the intestine ( unpublished data ) . The most parsimonious explanation for the failure to observe enhanced sensitivity to pathogens when daf-16 is knocked down or knocked out in the whole organism is that intestinal and non-intestinal DAF-16 have antagonistic effects on host defense . Given the known complex regulation of DAF-16 , this scenario is plausible . Balanced antagonistic effects on DAF-16 are observed in the context of signaling from the C . elegans germline and somatic gonad that regulate aging . Signals from the germline that normally suppress DAF-16 activity are balanced by distinct signals from the somatic gonad that normally enhance DAF-16 activity . The gonad signal appears to operate via the neurons and DAF-2 insulin-like signaling , while the germline signal appears to operate through a parallel pathway that does not require DAF-2 [94] . In this context , it is most appropriate to describe the effects of genetic manipulations in terms of net aggregate effects . Thus , the net aggregate effect of loss of daf-16 in the entire organism is neutral while the net aggregate effect of loss of daf-16 in the intestine results in pathogen sensitivity . Endodermal GATA transcription factors have been shown to have a conserved role in regulating epithelial innate immune responses in the C . elegans intestine and human lung epithelial cells [7] . Here we find that P . aeruginosa can suppress epithelial immunity by affecting DAF-16 activity in the intestinal cells . The regulation of FOXO/DAF-16 by insulin-like signaling is highly conserved across organisms ( reviewed in [95] ) . Given the medical importance of P . aeruginosa , for example in cystic fibrosis patients where it chronically infects lung epithelial cells [25] , [26] , it will be interesting in the future to investigate whether insulin-like signaling regulates an epithelial immune response and whether P . aeruginosa suppresses this immune response in human patients .
Caenorhabditis elegans and bacterial strains are described in Table S5 . Double mutants were constructed and verified using standard genetic and molecular methods [96] . Bacteria expressing dsRNA directed against daf-16 , lys-7 , thn-2 , and spp-1 was part of a C . elegans RNAi library expressed in E . coli ( Geneservice , Cambridge , U . K . ) . Bacteria expressing dsRNA directed against sod-3 , ins-7 , ins-11 , kri-1 , and skn-1 were part of a C . elegans RNAi library expressed in E . coli ( Open Biosystems , Huntsville , Alabama ) . All bacterial strains were cultured under standard conditions . Growing worms for microarrays , RNA extraction , microarray hybridization , and data processing were performed as previously described [7] . Reference RNA and microarray hardware were matched to allow direct comparison of transcriptional response to PA14 in all worm strains . In particular , sma-6 ( wk7 ) experiments were performed in parallel with previously reported N2 experiments [7] . daf-2 ( e1370 ) animals were grown at 20°C until young adulthood and then placed for 24 hr at 25°C on lawns of either OP50-1 or PA14 grown on modified NGM . Microarray production , hybridization , and scanning were performed at the Stanford Functional Genomics Facility . cDNA was generated from total RNA . Experimental cDNA was labeled with Cy3 and reference cDNA was labeled with Cy5 . Four replicates of each condition were examined . Microarray data was deposited in the Stanford Microarray Database [97] . The default background subtraction and normalization settings were used . Spots were filtered based on foreground to background ratio; values less than 1 . 2 were flagged . Log ( base 2 ) values were exported . Gene expression on OP50-1 and PA14 were compared by t-test . Differences of 2 fold with p-values<0 . 05 were considered significant . Sensitivity analysis was conducted with a range of significance levels and fold-difference values to confirm that the choice of thresholds did not affect our conclusions . Age-matched young adult worms were exposed to bacterial lawns of OP50-1 or PA14 on NGM for 12 hours . RNA extraction and quantitative RT-PCR ( qRT-PCR ) was performed as previously described [7] . Briefly , 25 µl reactions were performed using the iScript One-Step RT-PCR kit with SYBR green according to the manufacturer's instructions ( BioRad Laboratories , Hercules , CA ) , primers at a final concentration of 1 µM , and a data acquisition temperature of 76°C . In order to control for variation in RNA loading concentration , cycle threshold ( Ct ) values were normalized to three primer pairs ( ama-1 , F44B9 . 5 , and pan-actin ( act-1 , 3 , 4 ) ) that were found to not change with infection . Summary statistics and statistical tests were calculated from N2-normalized cycle threshold values prior to conversion to relative fold change . Calculations were performed with a custom Perl script , Excel and R . A panel of 146 infection and stress response genes queried by qRT-PCR included representatives of the antibacterial factor related ( abf ) , lysozymes ( lys ) , saposin-like proteins ( spp ) , or thaumatin family ( thn ) gene classes , as well as genes identified to be transcriptionally regulated by PA14 [7] or by the DAF-2/DAF-16 pathway [16] . Whenever possible , primers were designed to amplify a sequence found in spliced cDNA but not genomic DNA by having one of the primer pairs overlap an exon junction . To this end , primer design was aided with the program AutoPrime [98] . Primer sequences are available from the authors upon request . To compare the response to infection in wildtype and mutant worms , RNA concentrations were measured in matched samples of worms exposed to OP50-1 and PA14 . The RNA concentration of gene g in worms exposed to OP50-1 ( designated OP50g ) indicates the basal level of expression . The RNA concentration of gene g in worms exposed to PA14 ( designated PA14g ) indicates the level of expression that follows infection . The response to infection for gene g is the difference in RNA levels between OP50-1 and PA14 samples . This was quantified as xg = PA14g – OP50g for qRT-PCR cycle threshold measurements and log2-converted microarray measurements . These log2-scale values were interpreted as fold changes using the conversion fold change = 2x . Positive values of xg ( PA14g – OP50g>0 ) indicate induction of the expression of g in response to infection . Negative values of xg ( PA14g – OP50g<0 ) indicate repression of the expression of g in response to infection . An ordered set of xg values for a set of genes ( such as the set of induced or the set of repressed genes ) from a particular worm strain forms a vector designated Xstrain . Correlation analysis can be used to determine the effect of a mutation on the induction or repression response to PA14 infection . The squared correlation between Xwildtype and Xmutant , r2 , indicates the degree to which induction or repression is conserved in the mutant strain . Values of r2 that are statistically indistinguishable from 0 indicate that induction or repression is strongly attenuated . For a more sensitive analysis , Xwildtype and Xmutant were compared by paired t-test . The summary statistic XΔ was calculated as the average of Xmutant – Xwildtype . XΔ indicates both the magnitude and direction of the difference in induction or repression in response to infection between wildtype and mutant strains . For induced genes , XΔ<0 indicates attenuation of induction . For repressed genes , XΔ>0 indicates attenuation of repression . The significance of XΔ values was determined by paired t-test . Acute heat shock was performed at 37°C for 70 to 90 minutes . Precise exposure times were determined empirically during each run by qualitative assessment of worms after heat shock . Germline proliferation was disrupted by RNAi knockdown of cdc-25 . 1 as previously described [76] . Worms were then exposed to PA14 or controls for approximately 16 hours; times varied from 14 to 18 hours as needed . Individual worms were classified as exhibiting predominantly nuclear DAF-16::GFP or predominantly delocalization DAF-16::GFP under 160× total magnification using an Olympus SZX12 dissecting microscope with a 1 . 6× objective and an EN GFP-LP filter cube ( catalog no . 41018 , Chroma Technology , Brattleboro , VT ) which has the following specification: excitation band-pass filter 470±20 nm , emission filters >495 nm long pass followed by another >500 nm long pass . Fluorescence micrographs were collected at 200× magnification by fluorescence microscopy using a Leica DMRXA2 microscope with the Leica I3 filter set ( Excitation 420 nm , Emission 525 nm , 30 nm band pass ) for GFP . The criteria for predominately nuclear was the greater than 4 intestinal nuclei with nuclear localized DAF-16::GFP . The proportion of worms in each category is a metric for comparing the extent of nuclear localization of DAF-16 between populations , and have previously been used to examine the genetic control of DAF-16 nuclear localization in other contexts [99] . Assays scored in this fashion are highly reproducible between experiments and across experimenters . Assays to determine the ability of C . elegans to survive PA14 infection were performed as described [76] . Briefly , to avoid the confounding effects of progeny production and internal hatching on survival , sterile worms were used in survival assays . To sterilize worms , rrf-3 ( pk1426 ) ;glp-4 ( bn2 ) and pha-1 ( e2123 ) were raised at 25°C . ins-7 ( tm1907 ) , ins-11 ( tm1053 ) , and wildtype controls were sterilized using RNAi knockdown of cdc-25 . 1 . VP303 and NR222 worms are resistant to RNAi in the germline . Thus , VP303 , NR222 and N2 worms were grown at 20°C and shifted to 27 . 5°C for 24 hours at the L3/L4 molt , which causes sterility . PA14 was grown overnight in King's Broth containing 100 mg/ml rifampicin at 37°C . 10 µl was spread on modified NGM and grown for 24 hours at 37°C . Worms were infected at 25°C by feeding on PA14 lawns . Kaplan-Meier survival analysis was performed using StatView 5 . 0 . 1 . The Mantel-Cox logrank test was used to assess statistical significance of differences in survival . Only p-values<0 . 01 were considered significant . Mean time to death and standard error of the mean was calculated in StatView and then normalized to N2 for graphical comparison ( Tables S1 , S3 , and S4 ) .
|
Bacterial pathogens have evolved mechanisms to overcome the immune defenses that animals and plants deploy against them . In some cases , this involves directly interfering with the proper functioning of the immune system . Because pathogens that employ these strategies are often the most deadly and difficult to treat , it is important to understand how they are able to suppress the immune system in the context of the whole organism . In this paper , we show that Pseudomonas aeruginosa , a bacterial pathogen that is a major contributor to hospital-borne infections such as pneumonia , suppresses an immune defense pathway during infection of the simple animal host Caenorhabditis elegans . Using genetic modifications of both the pathogen and host , we identify components of the signaling pathways required to suppress host immune defenses . We find that P . aeruginosa employs the cell-to-cell communication system known as quorum sensing , which coordinates the expression of virulence factors to suppress host immune defense . In the host , an evolutionarily conserved insulin-like signaling pathway is affected by P . aeruginosa , resulting in the suppression of genes that are required for defense against infection in the intestinal epithelial cells . These findings suggest the possibility that P . aeruginosa may exploit similar mechanisms when causing infections of human epithelium , such as the epithelial lining of the lungs .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbiology/immunity",
"to",
"infections",
"genetics",
"and",
"genomics/genetics",
"of",
"the",
"immune",
"system",
"immunology/immunomodulation",
"genetics",
"and",
"genomics/gene",
"expression",
"immunology/innate",
"immunity",
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis"
] |
2008
|
Pseudomonas aeruginosa Suppresses Host Immunity by Activating the DAF-2 Insulin-Like Signaling Pathway in Caenorhabditis elegans
|
The reciprocal differentiation of T helper 17 ( TH17 ) cells and induced regulatory T ( iTreg ) cells plays a critical role in both the pathogenesis and resolution of diverse human inflammatory diseases . Although initial studies suggested a stable commitment to either the TH17 or the iTreg lineage , recent results reveal remarkable plasticity and heterogeneity , reflected in the capacity of differentiated effectors cells to be reprogrammed among TH17 and iTreg lineages and the intriguing phenomenon that a group of naïve precursor CD4+ T cells can be programmed into phenotypically diverse populations by the same differentiation signal , transforming growth factor beta . To reconcile these observations , we have built a mathematical model of TH17/iTreg differentiation that exhibits four different stable steady states , governed by pitchfork bifurcations with certain degrees of broken symmetry . According to the model , a group of precursor cells with some small cell-to-cell variability can differentiate into phenotypically distinct subsets of cells , which exhibit distinct levels of the master transcription-factor regulators for the two T cell lineages . A dynamical control system with these properties is flexible enough to be steered down alternative pathways by polarizing signals , such as interleukin-6 and retinoic acid and it may be used by the immune system to generate functionally distinct effector cells in desired fractions in response to a range of differentiation signals . Additionally , the model suggests a quantitative explanation for the phenotype with high expression levels of both master regulators . This phenotype corresponds to a re-stabilized co-expressing state , appearing at a late stage of differentiation , rather than a bipotent precursor state observed under some other circumstances . Our simulations reconcile most published experimental observations and predict novel differentiation states as well as transitions among different phenotypes that have not yet been observed experimentally .
CD4+ T cells are important components of the adaptive immune system in higher vertebrates . By producing various cytokines , they perform critical functions such as helping B cells to produce antibodies , activating CD8+ cytotoxic T cells , enhancing the innate immune system , and suppressing the immune response to avoid autoimmunity [1] , [2] , [3] . In peripheral tissues , such as lymph nodes , blood and sites of infection , antigen-inexperienced ( naïve ) CD4+ T cells can differentiate into effector cells of specialized phenotypes upon stimulation by cognate antigen delivered to the T cell receptor by Antigen Presenting Cells ( APCs ) . Proliferation and differentiation of activated naïve T cells depends on their particular cytokine microenvironment . These specialized effector T cells produce distinct cytokine profiles tailored for their specialized functions . Also , they express lineage-defining transcription factors ( “master regulators” ) . In general , high expression level of a particular master regulator is observed only in cells of a particular lineage , and the overexpression of a particular master regulator induces the production of the corresponding lineage-defining cytokines [4] , [5] . The fate of a naïve CD4+ T cell was traditionally thought to be either T helper 1 ( TH1 ) cell or T helper 2 ( TH2 ) cell [6] . In the last decade , a third type of T helper cell ( TH17 ) , derived from naïve CD4+ T cells , was discovered [7] . TH17 cells produce interleukin-17A ( IL-17A ) , IL-17F and IL-22 as their lineage-defining cytokines , and the retinoic acid receptor-related orphan receptor gamma t ( RORγt ) transcription factor is considered the master regulator of this lineage [8] , [9] . In addition , naïve CD4+ T cells were found to be able to differentiate into a fourth lineage of ( regulatory ) T cells , which were called induced regulatory T ( iTreg ) cells to distinguish them from natural regulatory T ( nTreg ) cells , which differentiate in the thymus instead of the periphery [10] . iTreg cells are characterized by producing IL-10 and transforming growth factor-β ( TGF-β ) and highly expressing forkhead box P3 ( Foxp3 ) transcription factor as their master regulator [11] . TH17 cells are pro-inflammatory because they secret cytokines that promote inflammation , whereas iTreg cells are anti-inflammatory because their lineage-defining cytokines can reduce the inflammatory response . The differentiation pathways of naïve T cells into TH17 and iTreg lineages are closely related . First , stimulation by TGF-β is necessary for the differentiation of both lineages [12] . The differentiation of TH17 and iTreg cells are reciprocally regulated in the presence of TGF-β , i . e . inhibiting the differentiation pathway of one lineage will result in activation of the pathway for the other lineage . This is due to the mutual antagonism between RORγt and Foxp3 . Furthermore , polarizing signals , such as IL-6 and retinoic acid , can induce the differentiation of one lineage and repress that of the other one [12] . Nonetheless , differentiated iTreg cells can be reprogrammed into TH17 cells in an appropriate cytokine environment [13] , suggesting significant plasticity of these two lineages . In addition , stable co-expression of their master regulators ( RORγt and Foxp3 ) is observed both in vivo and in vitro [14] , [15] . Interestingly , these double-expressing cells were found to possess either regulatory or dual ( regulatory and proinflammatory ) functions in vivo [14] , [15] . Perhaps the most intriguing phenomenon is that antigen-activated naïve CD4+ T cells treated with TGF-β alone give rise to a heterogeneous population , which may include three phenotypes ( Foxp3-only , RORγt-only , and double-expressing cells ) at an intermediate TGF-β concentration [16] , or two phenotypes ( RORγt-only and double-expressing cells ) at a higher TGF-β concentration [15] . In combination with TGF-β , IL-6 can induce the differentiation of RORγt expressing cells , whereas all-trans retinoic acid ( ATRA ) can induce the differentiation of Foxp3 expressing cells [16] , [17] ( Figure 1 ) . All of these in vitro derived phenotypes can be observed in vivo , and at least some of their respective functions have been demonstrated , suggesting that these in vitro differentiation assays provide important clues to our understanding of the development of TH17 and iTreg cells in the body . Mathematical modeling has contributed to our understanding of the differentiation of TH1 and TH2 cells [18] , [19] , [20] , [21] , [22] , [23] , [24] . Höfer et al . first demonstrated that the dynamics of the key transcription factors can govern the robustness of the lineage choice and maintenance [18] , [19] . Yates et al . later related transcription factor dynamics to the mix of TH1 and TH2 cells in a population of differentiating T cells [20] . Recently , Bonneau et al . [25] have proposed a Boolean-network model of the comprehensive repertoire of CD4+ T cell phenotypes , including TH17 and iTreg cells . Drawing inspiration from these earlier models , we have sought to explain , with a computational model , the remarkable heterogeneity of the TH17-iTreg reciprocal-differentiation system . In terms of this model , we show that a population of naïve CD4+ T cells , with some small cell-to-cell variability , can differentiate into a heterogeneous population of effector cells with distinct phenotypes upon treatment with the primary differentiation signal ( TGF-β ) . Polarizing signals , such as IL-6 and ATRA , can skew the differentiation to one or two phenotypes . A control system with these properties can generate functional diversity of the induced cell populations and can be regulated with great flexibility by diverse environmental cues . In addition , the model suggests how treatment with different concentrations of TGF-β may favor different responding phenotypes , and how conversions among these phenotypes may be guided . Finally , the model gives a new quantitative explanation for double-expressing cells , suggesting that they are ‘re-stabilized co-expressing’ cells rather than transient intermediate cells in the differentiation pathway . The model predicts that double-expressing cells should appear at a relatively late stage of the differentiation process , and they may be intended for specific functions . In all , our model provides a novel mathematical framework for understanding this reciprocal differentiation system , and it gives new insights into the regulatory mechanisms that underlie the molecular control of certain immune responses .
To illustrate our basic idea , we first construct a model of a simple and perfectly symmetrical regulatory network ( Figure 2A ) . In the Methods section we describe how this network is converted into a pair of nonlinear ordinary differential equations ( ODEs ) for the time rates of change of Foxp3 and RORγt . The rate functions for this model contain 12 kinetic parameters , whose basal values are specified in the Methods section ( Table 1 ) for the “symmetrical model without intermediates” . The solution of these ODEs for the basal values , and with [TGF-β] = 0 , evolves to a stable steady state where both RORγt and Foxp3 have a low level of expression ( RORγtlowFoxp3low ) . This steady state corresponds to a naïve CD4+ T cell ( Figure 3A ) . In the presence of a sufficient TGF-β signal , the regulatory network might evolve to one of three other steady states , namely RORγthighFoxp3low , RORγtlowFoxp3high and RORγthighFoxp3high states , corresponding to RORγt-only , Foxp3-only and double-expressing phenotypes . Note that these stable steady states are also referred as ‘cell fate attractors’ in some other studies , and this concept facilitates our understanding of cell lineage choice and reprogramming ( reviewed in [26] ) . Figure 3B shows a scenario in which the TGF-β signal triggers the formation of a tri-stable system . In this particular case , the RORγtlowFoxp3low state is no longer a stable steady state , and naïve cell , which was previously stabilized in the RORγtlowFoxp3low state , would differentiate into the RORγthighFoxp3high state , whose basin of attraction ( the white region in Figure 2B ) contains the naïve state of the cell . However , cell-to-cell variability can produce other results . We interpret cell-to-cell-variability as small deviations of the parameter values from their basal settings in Table 1 . The basal settings correspond to the behavior of an “average” cell , but any particular cell will deviate somewhat from this average behavior . As consequences of the changing parameter values in any particular cell , the position of the RORγtlowFoxp3low state changes , the boundaries of the basins of attractions change , and the fate of the naïve cell may change . The naïve T cell will differentiate into the stable steady state in whose basin of attraction it lies . That is , depending on the precise parameter values of the cell , its RORγtlowFoxp3low state may lie in any of the three basins of attraction of the TGF-β-stimulated system . Figure 3C depicts three cells in the population that adopt three different fates because of the variability among them . With a random sample of cells , each of the three differentiated states can be populated by a significant fraction of cells ( Figure 3D ) . Although cell-to-cell variability does not make large changes in the position of the RORγtlowFoxp3low state , it has a dramatic influence on the basins of attraction of the stable steady states , which determines the fate of the cell once the differentiation signal is turned on . Since the system has four distinct steady states that correspond to four distinct phenotypes , we next looked for the relationships among these steady states using bifurcation analysis of an average cell . Because of the symmetrical nature of the interactions , an average cell exhibits sub-critical pitchfork bifurcations with TGF-β concentration as the control parameter ( Figure 4A ) . ( The notion of a pitchfork bifurcation was used earlier , in references [27] , [28] , to explain a system of hematopoietic cell differentiation in which multiple lineages might be adopted . ) Notably , the RORγtlowFoxp3low state is only stable at low TGF-β concentration . At an intermediate concentration of TGF-β ( ∼0 . 25 units in Figure 3A ) , the system bifurcates into two lineage-specific branches , corresponding to RORγthighFoxp3low and RORγtlowFoxp3high states . The fourth type of stable steady state ( RORγthighFoxp3high ) appears at higher TGF-β signal strength ( >0 . 37 in Figure 3A ) , when the autoactivation of RORγt and Foxp3 eventually overrides their mutual inhibition and makes the double-expressing state the dominant phenotype of the population . We next checked the influence of TGF-β concentration on the fractions of responding phenotypes in a population of induced cells . For various values of [TGF-β] , we simulated a population of naïve CD4+ T cells with cell-to-cell variability . In agreement with the bifurcation analysis , RORγthighFoxp3low and RORγtlowFoxp3high cells appeared simultaneously over an intermediate range of [TGF-β] ( between ∼0 . 2 and ∼0 . 55 units ) . The fraction of RORγthighFoxp3high cells increases at higher TGF-β concentrations and eventually dominates the population when [TGF-β]>0 . 55 . In the vicinity of 0 . 5 units of TGF-β , the cell population is heterogeneous , with comparable fractions of all three stable phenotypes ( Figure 4A lower panel ) . Although this initial model accommodates the presence of dual-positive TH17/iTreg cells , it cannot fully explain the fine regulatory effects of varying TGF-β concentrations . For example , this model predicts that double-expressing cells dominate the population when TGF-β concentration is high , and that single-expressing cells may be converted into double-expressing cells by increasing [TGF-β] . In fact , this is not necessarily true if the effects of TGF-β saturate at high [TGF-β] . To take saturation effects into account , we incorporated two intermediate signaling proteins between TGF-β and the transcription factors Foxp3 and RORγt ( Figure 2B ) . In this case , the system can be tri-stable even at high concentrations of TGF-β , and the total conversion of single-expressing cells into double-expressing cells would not occur . Instead , co-existence of the three phenotypes in comparable fractions might be observed over a wide range of [TGF-β] ( Figure 4B ) . We next considered an asymmetrical model in which the network topology and parameter values differ from the symmetrical model . In the model with perfect symmetry , we assumed that the inhibitions between Foxp3 and RORγt are equally strong , which is not supported by existing experimental evidence . In fact , Foxp3 is better known for its inhibitory function on IL-17 , a downstream effector of RORγt , as demonstrated by Williams and Rudensky [29] . Therefore , we revised our model by removing the direct inhibition of RORγt expression by Foxp3 and adding the inhibition of IL-17 expression by Foxp3 . This revised model , with broken symmetry ( Figure 1C , Table 1-last column , and Figure 3C ) shows some new features . First , RORγt behaves ultrasensitively in response to varying [TGF-β] because of RORγt's positive ( autoregulatory ) feedback loop . Secondly , Foxp3 exhibits multiple saddle-node bifurcations derived from the broken symmetries of the pitchforks . Interestingly , the four types of stable steady states observed with the symmetrical model have been retained for Foxp3 , and thus for the entire system . In fact , by varying [TGF-β] , it is possible to obtain all three differentiated phenotypes in significant fractions simultaneously . Doing the same analysis for the effect of [TGF-β] on the induced cell population ( Figure 4C lower panel ) , we found that the asymmetrical model behaved similarly to the symmetrical model . At low [TGF-β] , Foxp3 single-positive cells are predicted to be the dominant cell type . As [TGF-β] increases to intermediate or high levels , the RORγt single-positive cells and the double-positive cells should appear and co-exist . These simulation results are in agreement with recently published experimental data documenting the differential effects of TGF-β on the differentiation of TH17 and iTreg cells [16] . Indeed , at certain intermediate concentrations of TGF-β , three phenotypes in comparable fractions have been observed [16] . In addition , the maximum percentage of Foxp3 single-positive cells was observed at some lower concentration of TGF-β . As [TGF-β] was increased , the percentage of Foxp3 single-positive cells decreased , accompanied by a concordant rise in the percentage of RORγt-expressing cells [16] . At higher concentrations of TGF-β , RORγt-only cells and double-expressing cells were found to coexist in comparable percentages [15] . Our model not only validates existing published data on the coexistence of two or more phenotypes in mixed T helper cell populations but also predicts that increasing TGF-β concentration will cause the transformation of Foxp3 single-positive cells into RORγt-expressing cells . Conversely , decreasing TGF-β concentration might result in the reverse transformation . We next simulated the influence of IL-6 on this reciprocal differentiation system . In the asymmetrical model ( Figure 3C ) , IL-6 activates STAT3 , which favors production of RORγt over Foxp3 . In this model , IL-6 will not trigger differentiation in the absence of TGF-β . However , IL-6 significantly increases the fraction of RORγt-only cells over a wide range of TGF-β concentrations ( Figure 4A ) . Also , it stimulates some of the cells in the ( simulated ) population to produce IL-17 . These results are consistent with the observations of a few groups [13] , [16] . In particular , Zhou et al . observed that low level TGF-β favors the RORγt-only phenotype and IL-17 production , whereas higher concentrations of TGF-β inhibit the production of IL-17 . They also reported that the decrease of IL-17 production at higher TGF-β concentration is accompanied by an increase of Foxp3-expressing cells . We see this phenomenon in our simulation , and we further suggest that the decrease of RORγt-only cells , or the increase of the double-expressing cells , accounts for the reduced production of IL-17 at high TGF-β concentration , because double-expressing cells are known to be much less effective in producing IL-17 than the RORγt-only cells , at least in this type of in vitro assay with TGF-β and IL-6 [15] , [16] . However , Zhou et al . observed a pronounced inhibition of IL-17 production at higher TGF-β concentration even when Foxp3 expression had not been remarkably raised [16] . This discrepancy suggests that high TGF-β level may trigger Foxp3-independent repression of IL-17 production . Both the observations by Zhou et al . and our simulations demonstrate that only a minor fraction of RORγt-only cells exhibit IL-17 production even in the presence of IL-6 . In fact , this is not an idiosyncratic phenomenon . Mariani et al . recently discovered that only a subset of TH2 cells produce IL-4 due to cell-to-cell variability [30] , suggesting that the production of lineage-specific cytokines in T helper cells can be controlled by stochastic mechanisms . In the asymmetrical model ( Figure 3C ) , ATRA favors production of Foxp3 over RORγt . Hence , in our simulation of TGF-β+ATRA stimulation , we found that the percentage of Foxp3-only cells and double-expressing cells significantly increased as compared to TGF-β alone ( compare Figure 4B to Figure 3C ) . Like IL-6 , ATRA did not trigger differentiation by itself . We next checked if ATRA can suppress the polarizing effect of IL-6 . In our simulation , ATRA was effective in reducing the IL-6 induced production of IL-17 . In addition , at high TGF-β concentration , ATRA significantly decreased the percentage of RORγt-only cells , and resulted in a population with comparable fractions of RORγt-only cells and double-expressing cells ( Figure 5C ) . All of these simulation results are consistent with published data [13] , [15] , [17] , [31] . Our model suggests that ATRA can significantly increase the percentage of Foxp3-only cells at intermediate TGF-β concentration , and the percentage of double-expressing cells at high TGF-β concentration . With our model , we next checked whether IL-6 could reprogram differentiated iTreg cells into TH17 cells . We first induced a population of naïve CD4+ T cells to differentiate into a population dominated by ‘Foxp3-only’ cells with an intermediate level of TGF-β ( 0 . 28 units ) . After the cells came to their Foxp3-only steady state , we raised the IL-6 signal to 10 units and continued the simulation . We found that almost all the cells expressing Foxp3 before adding IL-6 stopped producing Foxp3 upon the treatment with IL-6 , and a subset of ‘RORγt-only’ cells dominated the population . A fraction of these RORγt-only cells produced IL-17 ( Figure 6A , left panel ) . When we induced the differentiation of iTreg cells with TGF-β+ATRA and performed the same reprogramming simulation , we found that ATRA did not prevent the repression of Foxp3 expression by IL-6 significantly . However , ATRA prevented the formation of IL-17 producing cells ( Figure 6A , right panel ) . The reprogramming capability of IL-6 and the inhibitory effect of ATRA have been observed by Yang et al . [13] . Analyzing the concentration dependence of these reprogramming effects , we found that a high level of IL-6 may exclusively down-regulate Foxp3 expression ( Figure 6B , left panel ) whereas a high level of ATRA may predominantly prevent IL-17 expression ( Figure 6B , right panel ) . Interestingly , when both of these factors are present in high concentration , our model predicts that , although most cells exhibit high expression of RORγt , there are almost no IL-17-producing cells in the population . Future experimental studies are warranted to confirm these intriguing predictions . Table 2 summarizes the observations that are in agreement with our simulation results and the testable predictions that we have made based on the bifurcation analyses and signal-response curves .
Previous mathematical models have shown how differentiation signals can trigger a robust switch during the development of TH1 or TH2 cells [18] , [19] , [20] , [21] , [22] , [23] , [24] . In particular , earlier modeling studies by Höfer et al . demonstrated how the interactions among transcription factors can create a memory for TH2 lineage commitment and govern the choice of TH1 and TH2 lineages [18] , [19] . These studies focused on the dynamics of transcription factors within a single ( average ) cell , but the authors also pointed out that cell-to-cell variability in a CD4+ T cell population can be modeled mathematically by introducing parametric variations to the ordinary differential equations ( ODEs ) . In addition to modeling molecular interactions , the study by Yates et al . related the dynamics of transcription factors to the phenotypic composition of TH1 and TH2 cell populations [20] . The authors built comprehensive ODE-based models which take into account cell proliferation , intercellular communication , and cell-to-cell variability . Yates et al . modeled cell-to-cell variability by variations in initial conditions , but we consider parametric variations to be a more important source of cell-to-cell variability ( see Methods ) . The reciprocal differentiation of TH17 and iTreg cells , although a relatively new research field , has already been shown to exhibit many interesting and unique features , and yet it has not been studied in quantitative detail using mathematical models . The work presented here reveals some of the intriguing regulatory mechanisms of this differentiation system . We showed that the four phenotypes of cells , corresponding to four different steady states of the dynamical system , are derived from a pitchfork bifurcation with certain degree of broken symmetry . A single primary differentiation signal , TGF-β , can give rise to multiple cell types with distinct functions , while other polarizing differentiation signals , such as IL-6 as ATRA , skew the system to particular type ( s ) of cells . If we regard TGF-β as tossing dice for the naïve cells , those polarizing signals may load the dice , although they may not toss the dice themselves . The remarkable advantage of this system is that functionally synergic cells could be generated simultaneously in desired fractions with some simple differentiation inducers . Our model suggests that the double-expressing phenotype is a re-stabilized co-expressing state , which should be observed in relatively late stages of cell differentiation . Previously , van den Ham and de Boer found this type of state in a similar dynamical system , although they chose parameter values to avoid this state for their system [24] . With perfectly symmetrical models , some other groups described a double-expressing state as an intermediate state before the decision making switch , corresponding to some bipotent precursor cells [27] , [32] , [33] . For the TH17-iTreg paradigm , it is also possible that these double-expressing cells are at an intermediate state that should be converted into single-expressing cells at a later stage of the differentiation process . However , we do not favor this view for the following reasons . 1 ) A few studies have shown that the double-expressing cells are effective in repressing effector cell growth and/or secreting pro-inflammatory and anti-inflammatory cytokines [15] , [34] . It is not likely that a differentiation intermediate would perform any conspicuous function in the immune system . 2 ) There are a few reports demonstrating the conversion from iTreg cells to double-expressing cells [13] , [14] , or from RORγt-only cells to double-expressing cells [15] , and to our knowledge it is not yet established that observable double-expressing cells can be converted into single-expressing cells . Assuming that differentiation from early stage to late stage is more readily to be observed than the ‘dedifferentiation’ process , these results indicate that the double-expressing cells might be at a differentiation stage later than the single-expressing states . 3 ) As shown in this report , there is a mathematical basis to support the double-expressing state appearing only at relatively high TGF-β concentration and some late differentiation stage , and the model is in accord with most published experimental observations . In addition , we are aware that the double-expressing cells are also observed for iTreg-TH1 and iTreg-TH2 paradigms [3] . Therefore , the framework presented here may be helpful for understanding iTreg cells that express T-bet or GATA3 as well . Interestingly , conversion of Foxp3-expressing iTreg cells to Foxp3/T-bet double-expressing cells has been reported [35] . In fact , these double-expressing cells may play very specific and indispensable roles in controlling inflammation . Chaudhry et al . have found that iTreg cells require STAT3 for their suppressive function on TH17 , and not on other lineages [36] . Koch et al . discovered that the T-bet expression is required for the function of iTreg cells during TH1-mediated inflammation [35] . These results suggest that there are subpopulations of iTreg cells expressing various master regulators of T helper cells , and they are tailored for different functions [3] . Therefore , the double-expressing cells might be terminally differentiated effectors performing specific suppressive functions . It is possible that the Foxp3-only cells , which mainly appear at low TGF-β concentration , could serve as precursors or reservoir for different terminal effectors , in addition to their general suppressive functions . Although the detailed physiological significance of this delicate differentiation system is yet to be discovered , Lochner et al . have already demonstrated in mice that , during infections and inflammation , the number of IL-17 producing RORγt+ cells and double-expressing cells increased in remarkably comparable proportions [15] . This suggests the need for balance between different cell types in response to pathogenic challenges . A single differentiation network that gives rise to multiple phenotypes might be crucial for the maintenance of such balance . Furthermore , it is worth highlighting the common features shared by the TH17-iTreg differentiation system and the differentiation control systems of hematopoietic cells and of stem cells [27] , [28] , [37] . Functionally , these systems have the potential to generate multiple phenotypes in a single differentiation event , and these phenotypes may play synergic roles under certain physiological conditions . In addition , it has been shown that cell-to-cell variability within clonal populations makes significant contributions to the stochasticity of lineage choice in stem cells [38] . This is also concordant with our basic assumptions . Pitchfork bifurcations ( with broken symmetry ) may be the underlying mechanism generating variable phenotypes in these dynamical control systems . We will not be surprised if other cell differentiation systems possess similar properties . Recently , Heinz et al discovered that the ‘priming factor’ PU . 1 , which is required for both macrophage and B cell differentiation , is responsible for creating some of the lineage specific epigenetic markers by itself [39] . Therefore , it is possible that these priming factors not only drive the differentiation event , but also help to create a heterogeneous population of cells . One limitation of our model is the assumption that the high concentration of TGF-β used by Lochner et al . is above the saturation concentration for TGF-β signaling [15] . We are cautious about extrapolating our model to even higher TGF-β concentration because there is no available experimental result for us to compare with . In fact , it is possible that at even higher TGF-β concentration either the RORγt-only phenotype or the double-expressing phenotype dominates the population , and the conversion between these two phenotypes might be possible by adjusting the concentration of TGF-β . Although Lochner et al . observed the conversion of RORγt-only cells into double-expressing cells at late time points of induced differentiation , we are not sure about the nature of this conversion: it could be a transition from a transient intermediate to a stable steady state; it could be a transition triggered by a slow increase of TGF-β signaling in RORγt cells , possibly mediated by paracrine signaling ( see below ) ; or it may be caused by slow fluctuations in the transcriptomes [38] . Nonetheless , when more experimental results become available , we should be able to pinpoint the missing pieces in this reciprocal differentiation system and make the mathematical model more helpful for our understanding of the system in detail . Another limitation of this study is that we have neglected the effects of intercellular communication on the differentiation of CD4+ T cells . Cytokines secreted by TH1 and TH2 cells are known to influence the differentiation of neighboring T cells [40] , and previous modeling work has highlighted the importance of these paracrine signaling effects [20] . Relevant to our work , the cytokines secreted by TH17 and iTreg cells can influence the differentiation of a population of T cells , and this influence might be reflected in changes of the proportions of induced phenotypes . For example , both TH17 and iTreg cells can produce TGF-β [41] , [42] , which may increase the percentage of both type of cells , or induce the transition from single-expressing cells to double-expressing cells , and this may be causative for the transition observed by Lochner et al . [15] . However , it is not yet clear how important are paracrine signals via secreted cytokines compared to exogenous cytokine signals , with respect to TH17 and iTreg differentiation . We leave the consideration of these factors for future work . In summary , we presented a novel mathematical model of TH17-iTreg differentiation . Based on the model , we show how TGF-β can trigger the differentiation of naïve CD4+ T cells into a heterogeneous population containing RORγt-only , Foxp3-only and double-expressing cells , and how polarizing signals can skew the differentiation to particular phenotype ( s ) . The model suggests how the conversions among different phenotypes can be guided . Additionally , the model gives a new quantitative explanation for the double-expressing cells , which should appear only at a late stage of the differentiation process . Our model provides new insights into the regulatory mechanisms that underlie the molecular control of certain immune responses .
We constructed our mathematical model based on known interactions among key molecules in the differentiation system of TH17 and iTreg cells . For illustrative purposes , we first consider a ‘symmetrical’ model in which the lineages of TH17 and iTreg have identical corresponding interaction types and strengths . Then we added two intermediate proteins for transmitting TGF-β signals in this symmetrical model . Next , we modified our model so that it became asymmetrical , and we incorporated two other input signals . Using this last model , we compared our simulation results with some published experimental data and made several testable predictions . In the symmetrical model ( Figure 2A ) TGF-β upregulates both RORγt and Foxp3 , which has been demonstrated in a few published experiments [13] , [43] . The model includes the ‘autoactivation’ of both master regulators . Although there is no evidence for direct autoactivation of RORγt and Foxp3 , these relationships in our model represent known positive feedback loops in their respective pathways . One origin of these positive feedback loops is the epigenetic modifications observed in the promoter regions of RORγt and Foxp3 in their respective lineages [44] , [45] . These epigenetic modifications recruit additional chromatin remodeling complexes that further stabilize those modifications and help to maintain the gene expression , thus forming positive feedback loops [46] . Additionally , master regulators can enhance their own production by autocrine effects . For example , RORγt can induce production of IL-21 and IL-23 which further stimulate the expression of RORγt , as suggested by Murphy and Stokinger [47] . The symmetric model also includes the cross-inhibition interactions between Foxp3 and RORγt . Inhibition of Foxp3 by RORγt is supported by the recent discovery that RORγt acts as a transcriptional repressor of Foxp3 by binding to its promoter [48] . Although a few reports suggest a functional inhibition of RORγt by Foxp3 [13] , [16] , [49] , the presence of Foxp3 was shown to have no pronounced effect on the expression of RORγt [50] . Our symmetrical model includes the inhibition of RORγt by Foxp3 , but we relaxed this assumption in our model with broken symmetry . In the first version of our symmetrical model , TGF-β directly activates RORγt and Foxp3 . In the second version , we added intermediate proteins between TGF-β and the master regulators . It is known that Smad2 , Smad3 and Smad4 mediate the TGF-β-induced upregulation of Foxp3 [51] , [52] , but the Smad proteins are dispensable for upregulation of RORγt . It is still unclear how the TGF-β signal is transmitted to RORγt [52] . Thus , in Figure 1B , we introduce a generalized ‘Smad’ intermediate between TGF-β and Foxp3 and an ‘unknown intermediate’ between TGF-β and RORγt . The model with broken symmetry also includes IL-17 , which is activated by RORγt and STAT3 , and deactivated by Foxp3 and ATRA [8] , [13] , [16] , [29] , [53] . As a polarizing signal , IL-6 stimulates RORγt and IL-17 production , and represses Foxp3 expression through the STAT3 pathway [54] . Conversely , ATRA upregulates Foxp3 , downregulates RORγt , and inhibits IL-17 production [17] , [31] . These relations are all included in our model with broken symmetry ( Figure 2C ) . To model the TH17-iTreg reciprocal-differentiation system , we use a generic form of ordinary differential equations ( ODEs ) that describe both gene expression and protein interaction networks [55] , [56] , [57] . Each ODE in our model has the form: is the activity or concentration of protein . Xi ( t ) changes on a time scale = 1/γi . Xi ( t ) relaxes toward a value determined by the sigmoidal function , F , which has a steepness set by . The basal value of F , in the absence of any influencing factors , is determined by . The coefficients determine the influence of protein on protein . is the total number of proteins in the network . For example , the pair of ODEs for the first symmetrical model are:All variables and parameters are dimensionless . One time unit in our simulations corresponds to approximately 1 hour . All simulations and bifurcation analyses were performed with PyDSTool , a software environment for dynamical systems [58] . In the Supplementary Information we provide a Python module file ( Text S1 ) for PyDSTool that completely defines the ODEs we are solving in each case , and an example script ( Text S2 ) to reproduce bifurcation diagrams shown in Figure 4A . All the experimental results to which our model has been compared were obtained with differentiation assays that lasted 2–5 days , and these results are essentially consistent from one experiment to another . Thus , we assumed that the observed , differentiated cell phenotypes after 2–5 days are representative of stable steady states in our model . We have chosen to use generic ( phenomenological ) ODEs instead of a more detailed kinetic model of the biochemical reaction network because we lack sufficient mechanistic and kinetic information on the molecular interactions in the TH17-iTreg reciprocal-differentiation system . To build a detailed biochemical model , based on mass-action or Michaelis-Menten kinetics , would require us to make many assumptions on the underlying mechanism and rate constants with little or no experimental evidence to back up these assumptions . In such a case , a phenomenological model seems more appropriate to us . A similar approach has been adopted in earlier theoretical studies of T cell differentiation by Mendoza and Xenarios [22] , who used a sigmoidal function similar to our F ( σW ) , and by van den Ham and de Boer [21] , who used Hill functions in place of our F ( σW ) . To be sure that our results are not overly dependent on our mathematical approach , we have re-formulated our ‘symmetrical model without intermediates’ using Hill functions and confirmed that the model exhibits four types of stable steady states as [TGFβ] is varied . The basic features of the bifurcation diagrams and signal-response curves are similar , regardless of which formalism is used ( details available upon request ) . To account for cell-to-cell variability in a population , we made many simulations of the system of ODEs , each time with a slightly different choice of parameter values , to represent slight differences from cell to cell . We assumed that the value of each parameter conforms to a normal distribution with CV = 0 . 05 ( CV = coefficient of variation = standard deviation/mean ) . The mean value that we specified for each parameter distribution is also referred as the ‘basal’ value of that parameter ( see Table 1 ) . In our bifurcation analysis of the dynamical system , we consider an imaginary cell that adopts the basal value for each of its parameters , and we define this cell as the ‘average’ cell . Note that none of the cells in our simulated population is likely to be this average cell , because every parameter value is likely to deviate a little ( CV = 5% ) from the basal value . Note , in addition , that our simulations sample a volume of parameter space around the ‘average’ cell , thereby probing the sensitivity/robustness of the differentiation process . Because we are varying all parameters simultaneously and randomly , this procedure is more indicative of robust behavior than standard sensitivity analysis , which involves estimating the partial derivative of some output property ( e . g . , steady state level of Foxp3 ) with respect to each parameter separately . In order to simulate the induced differentiation process , we first solved the ODEs numerically with some small initial values of [RORγt] and [Foxp3] state and with [TGF-β] = 0 ( and , if applicable , other input signals , e . g . IL-6 and ATRA , = 0 as well ) . After a short period of time , each simulated cell will find its own , stable RORγtlowFoxp3low steady state , corresponding to a naïve CD4+ T cell . Next , we changed [TGF-β] ( and other input signals , if applicable ) to a certain positive value and continued the numerical simulation . By the end of the simulation , each cell arrives at its corresponding ‘induced’ phenotype , which might vary from cell to cell because of the parametric variability of the population . To simulate the reprogramming effect , the concentration of IL-6 was raised after the cells were stabilized in the differentiated state . We made the simple definition that a protein is expressed when its level is greater than 0 . 5 units . To check the effect of TGF-β concentration on the induced phenotypes , we ran a series of simulations for a group of 1000 cells with various values of [TGF-β] and plotted the percentages of cells that adopt each terminal phenotype , in order to generate a ‘signal-response’ curve for a population of cells . Note that this signal-response curve could only represent a series of induced differentiation experiments with various TGF-β concentrations instead of a single experiment with increasing concentration of TGF-β . Our simulations of cell-to-cell variability are based on the assumptions that each cell follows a deterministic trajectory but that cells differ from one another in the precise values of the kinetic parameters that govern the deterministic trajectory . A similar approach was adopted by Höfer et al . in their model of transcriptional regulation of T lymphocytes [18] . An alternative view of stochasticity assumes that all cells are identical in terms of kinetic constants but they follow unique stochastic trajectories because of random fluctuations in the numbers of molecules of the dynamic variables . The truth is most likely a combination of these effects ( parameter variation and molecular fluctuations ) , but we have adopted the parameter-variation approach for several reasons . First of all , we lack the sort of molecular details ( e . g . , the numbers of molecules of regulatory species per cell ) needed for accurate stochastic simulations of molecular fluctuations . Second , it is unlikely that T cells are identical with respect to parameter values , and there is experimental evidence to the contrary . Peripheral naïve T cells undergo a complex developmental process in the thymus , where they likely inherit many stable cell-to-cell differences , possibly because of the great diversity of T cell receptor specificities generated by VJ or V ( D ) J recombination . Experiments on T cell differentiation are done by selecting cells with some common characteristics , but they may nonetheless differ in many other respects . Even monoclonal populations of mammalian cells ( derived from a single progenitor cell ) exhibit a distribution of properties that can affect cell fate determination [38] . Nonetheless , to be sure that our results are not overly dependent on our view of cell-to-cell variability , we have re-formulated our ‘symmetrical model without intermediates’ as a pair of stochastic differential equations with additive white noise and confirmed that the SDEs generate signal-response curves similar to our results in Fig . 4A , bottom panel ( details available upon request ) . It is also reasonable to attribute variability among cells to different initial conditions for each simulation of the governing ODEs , as suggested by Yates et al . [20] . Since variations of initial conditions can also bias cells toward different phenotypes , we presume that this strategy will produce results similar to our own .
|
In order to perform complex functions upon pathogenic challenges , the immune system needs to efficiently deploy a repertoire of specialized cells by inducing the differentiation of precursor cells into effector cells . In a critical process of the adaptive immune system , one common type of precursor cell can give rise to both T helper 17 cells and regulatory T cells , which have distinct phenotypes and functions . Recent discoveries have revealed a certain heterogeneity in this reciprocal differentiation system . In particular , treating precursor cells with a single differentiation signal can result in a remarkably diverse population . An understanding of such variable responses is limited by a lack of quantitative models . Our mathematical model of this cell differentiation system reveals how the control system generates phenotypic diversity and how its final state can be regulated by various signals . The model suggests a new quantitative explanation for the scenario in which the master regulators of two different T cell lineages can be highly expressed in a single cell . The model provides a new framework for understanding the dynamic properties of this type of regulatory network and the mechanisms that help to maintain a balance of effector cells during the inflammatory response to infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"systems",
"biology",
"theoretical",
"biology",
"immunology",
"biology",
"computational",
"biology",
"molecular",
"cell",
"biology",
"genetics",
"and",
"genomics"
] |
2011
|
A Mathematical Model for the Reciprocal Differentiation of T Helper 17 Cells and Induced Regulatory T Cells
|
In Uganda , control of intestinal schistosomiasis with preventive chemotherapy is typically focused towards treatment of school-aged children; the needs of younger children are presently being investigated as in lakeshore communities very young children can be infected . In the context of future epidemiological monitoring , we sought to compare the detection thresholds of available diagnostic tools for Schistosoma mansoni and estimate a likely age of first infection for these children . A total of 242 infants and preschool children ( 134 boys and 108 girls , mean age 2 . 9 years , minimum 5 months and maximum 5 years ) were examined from Bugoigo , a well-known disease endemic village on Lake Albert . Schistosome antigens in urine , eggs in stool and host antibodies to eggs were inspected to reveal a general prevalence of 47 . 5% ( CI95 41 . 1–54 . 0% ) , as ascertained by a positive criterion from at least one diagnostic method . Although children as young as 6 months old could be found infected , the average age of infected children was between 3¼–3¾ years , when diagnostic techniques became broadly congruent . Whilst different assays have particular ( dis ) advantages , direct detection of eggs in stool was least sensitive having a temporal lag behind antigen and antibody methods . Setting precisely a general age of first infection is problematic but if present Ugandan policies continue , a large proportion of infected children could wait up to 3–4 years before receiving first medication . To better tailor treatment needs for this younger ageclass , we suggest that the circulating cathodic antigen urine dipstick method to be used as an epidemiological indicator .
Throughout the last decade several large-scale preventive chemotherapy campaigns , waged against neglected tropical diseases , have progressively scaled up operations to reach nationwide coverage levels in Uganda [1] , [2] . For control of intestinal schistosomiasis , as caused by Schistosoma mansoni infection , an active monitoring and surveillance programme , set within the national control programme ( NCP ) , has provided important disease-specific information , assessing the impact of treatment upon the recipient population , as well as , re-alignment of original control objectives first set forth in 2003 [3] , [4] . Following WHO guidelines , mass-drug administration of praziquantel ( PZQ ) is typically focused towards treatment of school-aged children ( ≥6 years ) and adults who reside within disease endemic regions [5] , [6] . PZQ is provided free of charge by the NCP and analysis of school and ( or ) community treatment registers has shown that several million people have received at least one annual treatment of PZQ within the last five years [1] , [7] . Although this represents a considerable achievement , targeted epidemiological surveys have revealed that coverage is incomplete as in certain areas , e . g . shoreline environments of Lakes Victoria and Albert , large numbers of preschool-aged children ( ≤5 years ) and infants ( ≤1 years ) are infected with S . mansoni and have been largely overlooked by the treatment campaign [8] , [9] , [10] . To ensure that this unfortunate health inequality does not persist the treatment needs of younger children are being assessed and we have recently called for formal inclusion of these young children within the Ugandan NCP [11] . It can be safely assumed , for example , that mass-treatment initiatives are vital in most in shoreline villages where infections can be common . Given the geographical focality of schistosomiasis and itinerancy of lakeshore communities , however , an important future challenge for the NCP is collection of sufficient disease-specific information to better tailor local drug needs and set parameters for subsequent programme monitoring [12] , [13] . Attention will therefore focus upon those sections of villages where young children are frequently bathed in freshly drawn lake water or are within range of regular ambulation to the lake margins . Owing to the unique natural history and developmental biology of schistosomes within the mammalian host [14] , accurate identification of infected cases is challenging [15] , even more so in the younger child where the founding worm population has only recently established and begun to mature . Before female worms develop their full egg-laying capacity , sporadic deposition of eggs may take place with a proportion of these being voided into the bowel lumen and ejected in faeces whilst the remainder become trapped within the host's tissues [16] . Interacting with this are also the beginnings of the child's innate and adaptive immune responses to excretory-secretory products of the worms themselves , as well as these responses being primed or modulated by maternally induced effects , for example , during pregnancy and ( or ) breastfeeding [17] , [18] , [19] , [20] . It is also of particular note that the child's immune system is in a maturing flux of recognition between self- and non-self epitopes [21] and the efficacy of PZQ , which is poor against immature worms of S . mansoni [22] , is only starting to be explored in this ageclass [11] . From a general diagnostic perspective as existing tools are sub-optimal , improvement of methods and techniques for detection of intestinal schistosomiasis continues [15] but in the context of the younger child , it is not yet clear which of the present methods , or combinations thereof , is either most appropriate or applicable for routine use within the NCP . We therefore report on a field-based study which attempted to determine the age of first infection in very young children with available techniques and also estimate , as accurately as possible , the general prevalence of intestinal schistosomiasis within this ageclass from a typical lakeshore community . The performance of methods that detect schistosome - antigens in urine , antibodies to egg antigens in serum and eggs in stool - was compared . For ease of comparison , our methods are subsequently referred to as: an antigen detection method ( ADM ) , an indirect egg detection method ( IEDM ) and a direct egg detection method ( DEDM ) , respectively .
Owing to itinerancy , the exact number of inhabitants in Bugoigo is not precisely known but is likely in the region of several thousand . The village contains up to three thousand traditional hut dwellings which stretch 3–4 km along the lakeshore and up to 1–2 km inland . Sanitation and hygiene in this village is minimal with few potable water sources and insufficient pit latrines . Household water is typically drawn directly from the lake at specific collection points and then taken back to each homestead in plastic jerry cans for subsequent domestic use . These lakeshore margins , like elsewhere on Lake Albert , provide conducive aquatic habitats for Biomphalaria spp . , the intermediate snail hosts of S . mansoni , and can be found throughout the year , although infected snails vary in numbers seasonally [28] , [29] . The immediate and longer-term objectives of this study were explained to the local community mobiliser who identified a total of 134 mothers that were willing to participate , bringing up to two of their infants/preschool children ( ≤5 years of age ) , and attend the two-day clinic commencing on the following day . After obtaining written informed consent from each mother on her own behalf and on behalf of her child ( ren ) , urine , stool and fingerprick blood samples were obtained from all participants on the first day of the clinic . Mothers were then asked a suite of detailed questions recording their demography and water contact behaviours ( the questionnaire is available upon request to the corresponding author ) . After receipt of the second-day stool ( and urine sample ) , all participants , regardless of their infection status , were treated for schistosomiasis and soil-transmitted helminthiasis with PZQ ( 40 mg/kg ) ( CIPLA , Mumbai , UK ) and 400 mg albendazole ( GSK , Uxbridge , UK ) under medical supervision in conditions typical of mass-drug administration [30] . For smaller children , a chewable albendazole half-tablet ( 200 mg ) was given and PZQ tablets were first crushed in orange juice before being administrated by spoon-feeding by their mother under supervision . The diagnostic findings for schistosomiasis here are reported for the children only . Each child's urine sample was visually inspected for macro-haematuria/turbidity and a random sample was tested for micro-haematuria with Hemastix ( Bayer , UK ) to exclude the possibility of urinary schistosomiasis or other active urinary tract infections . A 50 µl aliquot was then tested for the presence of schistosome circulating cathodic antigen ( CCA ) using a commercially available lateral flow immuno-chromatographic urine dipstick ( Rapid Medical Diagnostics , Pretoria , RSA ) originally developed in Holland [31] . On a subset of 90 children , urine-CCA tests were performed in duplicate to assess variation between dipsticks . To facilitate better recording of the visual intensity of the CCA reaction band within the test zone , results were visually graded against a reference chart for: trace , single ( + ) , double ( ++ ) and triple ( +++ ) positive reactions [32] . When creating binomial variables to depict infection status according to CCA , two variations were taken into account: the first considering trace results as negative infection status and the second considering trace results as positive infection status . The urine CCA reagent strip is referred to as an ADM ( antigen detection method ) from now on . A commercially available ELISA kit ( IVD Inc . ; Carlsbad , USA ) was used to test for host antibodies ( IgG/M ) to soluble egg antigens ( SEA ) according to manufacturer's instructions . Approximately 75 µl of finger-prick blood was taken from each child and serum was harvested , then diluted 1∶40 with specimen dilution buffer before loading a total of 100 µl into each ELISA microwell [11] . Positive and negative control sera were included on each batch of testing . Upon completion , each ELISA plate was placed on a white card and the colour within each microwell ( ranging from colourless to yellow ) was recorded by visual inspection . Positive reactions were classified either as trace ( faint yellow ) , single ( + , light yellow ) , double ( ++ , yellow ) or triple ( +++ , dark yellow ) upon visual comparison with the control sera . The SEA-ELISA is referred to as an IEDM ( indirect egg detection method ) from now on . Three parasitological methods Kato-Katz , percoll and FLOTAC , henceforth referred to as direct egg detection methods ( DEDMs ) , were attempted on each stool specimen to visualise eggs . However , owing to the differing amounts of stool required for each technique , it was not always possible to assemble a complete data set for every child with each of these three methods . Duplicate Kato-Katz ( K-K ) thick smears ( 41 . 7mg ) were made from first and second day stool samples ( N = 242 children ) [33] . The four faecal smears were each examined under the microscope at x100 , schistosome eggs were counted and later expressed as eggs per gram ( epg ) of faeces . Infection intensity was classified as light ( 1–100 epg ) , medium ( 101–400 epg ) and heavy ( >400 epg ) infections according to WHO guidelines [5] . The methodology of Eberl [34] using sedimentation of schistosome eggs by centrifugation through a solution of percoll ( Percoll 77237 ( 1 . 130 g/ml ) , Fluka , Sigma-Aldrich Chemie GmbH , Switzerland ) was also implemented on-site to visualize eggs ( N = 96 children on first day stool ) . The egg-floatation procedure known as FLOTAC [35] was performed off-site back in Kampala on a formalin-fixed stool specimen archive ( N = 191 children taken from the second day stool ) whereby schistosome eggs are collected by floatation centrifugation through a solution of zinc sulphate at specific gravity of 1 . 35 . Data were collected from each individual using pro-forma data sheets , which were then transferred into electronic format using Microsoft Excel . The data thus collated were analysed using MS Excel and R statistical package version 2 . 8 . 0 [36] . For prevalence data and diagnostic parameters , 95% confidence intervals ( CI95 ) were estimated using the exact method [37] . Prevalence comparisons were performed using ( one-tailed ) Fisher's exact modification of the 2×2 chi-squared test [38] . For infection intensity values , the arithmetic mean of positive cases was chosen as the measure of central tendency . Data from the FLOTAC and percoll methods were analysed by combining with K-K results and revising the diagnostic criterion so individuals were considered positive if an egg was detected by at least one DEDM . The diagnostic performances of the ADM ( including and excluding trace reactions as a positive diagnosis ) and IEDM were tested qualitatively as a rapid diagnostic for intestinal schistosomiasis , considering DEDMs as the ‘gold-standard’ . Additionally , a third ‘gold standard’ was created using data from the ADM ( including and excluding trace reactions as positive diagnoses ) against which to test IEDM data ( N = 242 ) . Diagnostic sensitivity , specificity , positive predictive value ( PPV ) and negative predictive value ( NPV ) were calculated according to the different ‘gold standards’ [38] . The diagnostic powers of ADM and IEDM were calculated using all individuals , and then segregated by sex or age ( ≤3 years of age versus >3 years of age ) . P-values <0 . 05 were considered indicative of statistical significance [38] . Approvals for this study were granted by the Ugandan Council for Science and Technology and the London School of Hygiene and Tropical Medicine ( application numbers 06 . 45 and 5538 . 09 ) . After sensitisation of the local community to the study objectives , verbal assent was first requested from each mother which was then formalised upon written informed consent ( for her and behalf of her child ) , as either a thumbprint or signature on data recording sheet . This was witnessed by a Vector Control Division Officer . PZQ treatment ( 40 mg/kg ) was offered to all study participants irrespective of their infection status .
The prevalence of intestinal schistosomiasis estimated by each diagnostic method , and combinations thereof , is shown in Table 1 and Fig . 1 . Prevalence inferred by DEDM , ADM ( including trace reactions as positive diagnoses ) and IEDM ( considering traces as negatives ) were: 24 . 4% , 42 . 6% and 45 . 9% . Of the children who were egg-positive by K-K , three quarters had ‘light’ intensity infections . Girls were equally as likely as boys to be diagnosed positively for intestinal schistosomiasis by ADM ( Odds Ratio ( OR ) = 1 . 06 , p = 0 . 90 ) and DEDM examinations ( OR = 0 . 72 , p = 0 . 29 ) . Children under the age of three , however , were less likely to be positive by ADM ( OR = 0 . 51 , p = 0 . 016 ) or by DEDM ( OR = 0 . 26 , p<0 . 0001 ) than their older counterparts . The prevalence of positives by IEDM was 45 . 9% . General prevalence inferred by pooling DEDM and IEDM was 47 . 7% , with no further change in prevalence when ADM was then added , see Fig . 1 . There was no discordance between duplicate CCA testing for negative or positive classifications ( data not shown ) . The age of first positive ( AFP ) for each method is presented in Table 1 . For DEDM , the youngest child with eggs in stool was 9 months old , with medium and heavy infections found at 3 and 5 years of age , respectively . For ADM , trace reactions , single , double and triple positives were found in an ascending series of 6 months , 9 months , 11 months and 2 years of age , respectively . For IEDM , trace reactions began at 5 months of age while single , double and triple positive reactions were found in children as young as 6 months , 1 year and 9 months old , respectively . All tests concur on a mean age of first infection within the third year of life . ADM detected infections slightly ahead of I/DEDMs ( 3 . 2 years v . 3 . 4 years v . 3 . 7 years , respectively ) . The order of this temporal series is largely concordant with an absolute minimum age of becoming first positive . In the absence of a genuine ‘gold standard’ where the infection status of each child is precisely known , it is necessary to explore relationships between diagnostic scores and infection intensities empirically , and to cross-tabulate diagnostic permutations by investigation . There was negligible variation in diagnostic performance of all protocols tested when classifying the data according to sex and age ( data not shown ) and general trends were reported from now on . Plotting the relationship between ADM and DEDM revealed some immediate trends , Fig . 2 . Whilst there were children positive for ADM who were egg-negative , as the epg increases there was a corresponding increase in the proportion of positive ADM tests and once medium/heavy intensity infections were reached , all ADM tests were clearly positives , see Fig . 2A . Plotting the faecal epg of each child against the intensity of the corresponding ADM test further revealed this positive association , see Fig . 2B . Considering the relationship between IEDM and DEDM revealed similar trends , see Fig . 3 . Despite some children being positive for IEDM while being egg-negative , as the faecal epg increases there was a corresponding increase in the IEDM reaction strength , with all medium/heavy intensity infections diagnosed as clear strong positives ( Fig . 3A & B ) . The relationship between ADM and IDEM was less clear-cut . Children who were ADM negative or trace had a median negative ( or trace ) IEDM reaction , but the proportionate increase of ADM positives with rising IEDM designations of positive ( + ) or strong positives ( ++/+++ ) was not as great as that seen with DEDM . For example , nearly 40% of children who were IEDM strong positive elicited a negative ADM reaction , Fig . 4A . As the intensity of the ADM result stepped up towards double and triple positive reactions , this typically corresponded better with increasing IEDM classifications , Fig . 4B . Using available data it was possible to conduct an exploration of diagnostic performances of the ADM and IEDM versus DEDM and against each other ( Table 2 ) . First , considering an ADM trace reaction to be an infection negative and comparing with positive diagnosis by at least one of the DEDMs , the ADM had a sensitivity of 59 . 3% , specificity of 95 . 6% , PPV of 81 . 4% and NPV of 87 . 9% . When considering an ADM trace reaction to be a positive infection , and comparing to diagnosis by at least one of the DEDMs , ADM had a sensitivity of 81 . 4% , specificity of 69 . 9% , PPV of 46 . 6% and NPV of 92 . 1% . The IEDM when compared to diagnosis by DEDM , demonstrated a sensitivity of 93 . 2% , specificity of 69 . 4% , PPV of 49 . 5% and NPV of 96 . 9% . For details on the performance of the ADM or IEDM compared to diagnosis by all DEDMs ( using a subset of the data ) , and for CI95 around each value , see Table 2 .
While some children were patently infected during the first year of life , others were not . Thus a sub-set of children exists with increased infection risk factors which we explain by the following synopsis . As children are born throughout the year , in a largely asynchronous fashion , whilst their initial age of first exposure to unsafe water might be broadly similar ( i . e . within first few months of life as mothers begin to bathe them in jerry-can collected water or in the lake directly ) their accumulated infection risk will not be equivalent owing the seasonality of local transmission factors and their particular timeframe of exposure within it contingent upon their mother's infant bathing and domestic water drawing practices [11] . Estimating this accumulated risk of infection reliably over the seasonal time frame of potential exposure is problematic as day-to-day variations within water collection times , its storage and actual domestic use ( within each household ) introduce many stochastic processes . Estimating cumulative infection risk is therefore easily confounded but an ad hoc investigation of infection risk associated with jerry-can collected water in June 2009 , however , has confirmed that sentinel laboratory-bred mice could become infected to freshly drawn water [28] . Seasonal patterns , which operate in umbrella fashion over and above these specific-exposure patterns , no doubt effect this asynchronous age of first infection . Thus there will be no ‘absolute age’ of first infection but rather a ‘range of ages’ depending upon these intricate covariates of exposure . Only after a child has passed through sufficient ‘windows of exposure’ , their probability of infection rises to an eventual certainty , after which , it is incumbent on the diagnostic tools to capture their parasitological status as accurately as possible . From first appearances the ADM looks to best capture and identify infections in early stage , especially when we consider trace results as putative infection positives . A contentious issue in the use of the CCA reagent strip has been the interpretation of the exact diagnosis of this ‘trace’ result which can be confounded by non-specific inflammatory factors or breast-feeding [32] , [47] . Interpretation of ‘trace’ is more contentious when surveying children under three years of age , where worm burdens are presumably lower than what might be expected in their school-aged counterparts . Interestingly , the percentage change in prevalence estimated according to the CCA reagent strip when excluding and including trace results as a positive diagnosis is significantly larger in the very young children ( ≤3 years of age ) –10 . 1% v . 36 . 2% ( +358% ) – than in those aged four and five years of age –30 . 1% v . 52 . 7% ( +175% ) which is fitting with our understanding of increasing worm burdens through time . Thus we postulate that using ‘trace’ as positive firmly points towards a future use of the urine CCA-dipstick as an early indicator of infections which are as yet to become egg- or antibody-patent . It is particularly notable that the prevalence based on the ADM , when considering trace as positive , is very close to that of IEDM ( Fig . 1 ) , yet the diagnostic performance with it was not particularly congruent ( see Fig . 3 and Table 2 ) so we still have an incomplete understanding of this infection progression . The dynamics of other ADM have been explored elsewhere in the context of recently acquired infection but not in very young children [48] . The ADM showed very promising diagnostic performance and robust field performance with high sensitivity and NPV scores ( 83 . 9% and 85 . 3% , respectively ) when we considered trace results as a positive diagnoses and very high specificity and PPV scores ( 95 . 5% and 90 . 5% , respectively ) when we considered trace results as negative diagnoses . This bimodal use of the test criteria could be advantageous from a control perspective . For instance , if a confident estimate of the suspected occurrence of infections within a population is needed , one should consider trace results as positives . On the other hand , to monitor the prevalence of ‘actual’ infection , or rather more easily identify those who do not , one should consider trace results as negatives . The former would be important if treatments were to be given out en masse as triggered by exceeding an aggregated local prevalence threshold while the latter would be important if treatment were to be withheld in an individual patient setting on the basis of test and treat . With the gradual rise of infection prevalence in older children ( over and above our asynchronous infection hypothesis ) , this trend must represent the spread of several risk factors , rather incipiently , across our cohort . Aggregation of infections in schistosomiasis is well-known [49] but it would be interesting to establish why approximately half of our study cohort had no evidence of infection despite living within the same village . As we were insufficiently aware of the exact locations of sampled households within the village , this could simply represent a cryptic spatial micro-patterning ( i . e . these children who live slightly further away from the lake have less contact with viable cercariae ) so we are now undertaking fine scale mapping of these individual households with GPS units . If , however , other causal factors could be identified and , perhaps more importantly , were these amenable to manipulation , it could lead to future infection mitigation measures . Presently , within the NCP there are no health education materials targeted towards these mothers and their young children . More importantly and in terms of policy realignment of the NCP , a useful formal recommendation would be to initiate cross-sectorial activities with water and sanitation NGOs to improve immediately the domestic water quality at Bugoigo and elsewhere along the Lake Albert shoreline . Rather than focusing upon expensive infrastructure development , it could be achieved by introduction of simple water storage or modification measures . For example , as schistosome cercariae are an ephemeral larval stage , freshly drawn water can be rendered harmless for schistosomiasis by simple resting for 24 hrs , by crude filtration or by introduction of mild disinfectants [16] . Thus without initiating a better dialogue with these women of children bearing age through better public health education , mothers will remain sadly ignorant of the risks that making use of this unsafe water has for themselves and that of the future health of their child [11] . In this dialogue , the NCP should be receptive to explore which infection mitigation measures are best feasible and , by this token , help to provide safe water for domestic use which is well-received , implementable and effective . It is evident that infants and preschool children in Bugoigo , and other similar lakeshore villages of Uganda [12] , are living in need of treatment . However , addressing how these children could be best identified is not yet clear , as are epidemiological parameters which should be collected for estimating treatment needs and also impact assessment . For example , should mass-treatment of all infants/preschool children take place when a sub-sample of an equivalent age range has been proven to be infected , or should treatment be allocated based at an individual level using the result of a diagnostic test in a ‘test and treat’ setting ? It is outside the remit of this present paper to make a cost-effectiveness calculation but a clear drawback of the IEDM method is that , whilst initially useful to establish if a child is infected ( and there is no evidence in these data to suggest a passive maternal transfer of antibodies has been confounding ) , monitoring this parameter after treatment will be largely uninformative owing to residual antibody titres remaining after infection has putatively cleared . Thus IEDM is only useful at baseline but as an initial estimate of infection prevalence could be powerfully applied in identification and selection of villages , or sentinel locations , to first define the extent of the problem at intervention baseline . This of course assumes the majority of examined children can mount an antibody response and is not confounded by high levels of immune-suppression , by HIV for example , which is likely high in these fishing villages . In contrast , both ADM and DEDMs have the potential ability to better track the dynamics of worm populations after treatment [22] , [34] but the insensitivity of DEDMs is of particular concern . Put simply , numerous adult worms may reside within the host but are yet not depositing sufficient eggs to be visualised in stool on the day of sampling . Thus through lack of alternatives a pragmatic way forward would be to focus upon more widespread application of the ADM . The advantages of the ADM have been discussed elsewhere in the context of programmatic monitoring [14] but the future challenge will be for the NCP to meet the financial costs of using these rapid diagnostic tests in scale-up of operations . This is particularly true if these are to be used in a ‘test and treat’ setting when large numbers of tests would be utilized [14] . Given the low price of PZQ treatment , to maintain an affordable diagnosis versus treatment differential , a rational strategy would be to examine a sub-set of children and if local prevalence exceeded a given threshold , mass-treatment is advised . Such a strategy is presently within the resources available to the NCP but best sample sizes and prevalence thresholds remain to be determined .
|
In sub-Saharan Africa , intestinal schistosomiasis is a debilitating disease caused by a worm infection . To arrest disease progression , de-worming medications are given out , often en masse , to school-aged children . In Uganda , however , much younger children can be infected , and in lakeshore communities both infants and pre-school children can already show signs and symptoms of intestinal schistosomiasis . To change de-worming practices , further information on the occurrence of infections in these younger is needed for evidence-based decision making . Our study applied current methods of disease diagnosis to better define the ‘age of first infection’ and estimate general infection prevalence within a disease-endemic village . Up to 50% of young children were clearly shown to have schistosomiasis and could likely wait up to 3–4 years before obtaining first treatment if present de-worming policies are not changed . In the context of identifying future treatment needs , we propose that antigen detection methods are most suitable .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"health",
"and",
"epidemiology",
"evidence-based",
"healthcare",
"pediatrics",
"and",
"child",
"health"
] |
2011
|
Schistosoma mansoni Infections in Young Children: When Are Schistosome Antigens in Urine, Eggs in Stool and Antibodies to Eggs First Detectable?
|
Half of the human population is at risk of infection by an arthropod-borne virus . Many of these arboviruses , such as West Nile , dengue , and Zika viruses , infect humans by way of a bite from an infected mosquito . This infectious inoculum is insect cell-derived giving the virus particles distinct qualities not present in secondary infectious virus particles produced by infected vertebrate host cells . The insect cell-derived particles differ in the glycosylation of virus structural proteins and the lipid content of the envelope , as well as their induction of cytokines . Thus , in order to accurately mimic the inoculum delivered by arthropods , arboviruses should be derived from arthropod cells . Previous studies have packaged replicon genome in mammalian cells to produce replicon particles , which undergo only one round of infection , but no studies exist packaging replicon particles in mosquito cells . Here we optimized the packaging of West Nile virus replicon genome in mosquito cells and produced replicon particles at high concentration , allowing us to mimic mosquito cell-derived viral inoculum . These particles were mature with similar genome equivalents-to-infectious units as full-length West Nile virus . We then compared the mosquito cell-derived particles to mammalian cell-derived particles in mice . Both replicon particles infected skin at the inoculation site and the draining lymph node by 3 hours post-inoculation . The mammalian cell-derived replicon particles spread from the site of inoculation to the spleen and contralateral lymph nodes significantly more than the particles derived from mosquito cells . This in vivo difference in spread of West Nile replicons in the inoculum demonstrates the importance of using arthropod cell-derived particles to model early events in arboviral infection and highlights the value of these novel arthropod cell-derived replicon particles for studying the earliest virus-host interactions for arboviruses .
Arthropod-borne viruses are transmitted between arthropod vectors , such as ticks and mosquitos , and their vertebrate hosts . Mosquito-borne flaviviruses , such as dengue , Zika , and West Nile viruses ( WNV ) , are responsible for a variety of debilitating pathologies , including hemorrhagic fever , encephalitis , flaccid paralysis , and microcephaly . WNV alone has accounted for over 20 , 000 cases of neuroinvasive disease in the United States since it emerged in New York City in 1999 [1] . Human cases of WNV have been documented on all continents except Antarctica making it the most widespread viral cause of encephalitis ( reviewed in [2] ) and an important pathogen for study . In addition , a robust mouse model makes it an excellent system to study arboviral pathogenesis . WNV has a single-stranded , positive-sense RNA genome that codes for a polyprotein , which is co- and post-translationally cleaved into 10 proteins . Three structural proteins make up the virion: capsid ( C ) , premembrane/membrane ( prM/M ) , and envelope ( E ) . C protein packages the genome into a nucleocapsid , which buds into the ER membrane containing E and prM and forms an immature particle ( reviewed in [3] ) . E and prM proteins are subsequently glycosylated by the host cell machinery . Fully mature particles are formed when prM is cleaved by host cell proteases in the Golgi , resulting in M and E in the viral envelope and structural rearrangement of the particle , prior to release from the host cell [4] . Arboviruses replicate in both arthropods and vertebrates , which confer properties to the virion specific to the host . Lipid content of the cellular membranes differs between vertebrates and invertebrates , resulting in differences in the viral envelope from disparate hosts [5–7] . Insect cells produce less complex carbohydrates compared to mammalian cells [8] . Notably , E proteins on flavivirus particles contain high-mannose glycans when derived from mosquito cells [9 , 10] . For mosquito-borne viruses , the virus transmitted to vertebrates has mosquito-specific lipid composition and post-translational glycosylations , which can affect viral infectivity , spread , and/or host immune response immediately following inoculation . The very first cells infected by WNV are currently unknown although early cell targets in mouse models are keratinocytes [11] and presumably macrophages and dendritic cells , which are infected by flaviviruses in immunocompromised mice early after infection [12 , 13] . In cell culture studies , flaviviruses and alphaviruses derived from mosquito cells have a greater infectivity for dendritic cells compared to virus derived from vertebrate cells due to the interaction of the viral proteins with C-type lectins ( e . g . DC-SIGN ) [9 , 14–16] . Furthermore , this interaction of mosquito cell-derived virus with cultured dendritic cells results in a dampened antiviral response with lower production of Type I interferon for WNV [15 , 17] and alphaviruses [16] . In contrast to the cell culture studies , we previously showed in mice that mosquito cell-derived WNV elicits earlier , but similar levels , of type I interferon in serum compared to mammalian cell-derived WNV [15] . The explanation for the discrepancies between the cell culture and animal studies remains unknown . Finally , early after inoculation and before WNV production , WNV derived from mammalian cells exhibits greater viral spread from the inoculation site to the draining lymph node and blood in mice , compared to WNV derived from mosquito cells [15] . Viral replicons are an important tool to study a single round of viral infection . Replicon genomes are deleted for some or all of the structural protein genes , which are often replaced with a reporter gene . Replicon genomes can be packaged into replicon particles ( RPs ) by providing the structural proteins in trans . Since RPs resemble authentic virus particles , but are unable to produce progeny virions , they are valuable for investigating the first round of cell infection from binding and entry to replication of viral RNA . RPs for WNV have been used in cell culture and animal studies , including vaccine development , antiviral screens , tropism , and immune studies [9 , 11 , 18–24] . Although various packaging systems have been described to produce WNV RPs [9 , 21 , 23 , 25 , 26] , to our knowledge there are no published reports of replicon genomes packaged in mosquito cells for WNV or other flaviviruses . Here we optimize methods for producing WNV RPs in mosquito cells and show that these particles have similar characteristics to fully infectious WNV . Furthermore , the mosquito cell-derived RPs were compared in vivo to mammalian cell-derived RPs in their spread from the inoculation site and replication in target tissues . We discovered that mammalian cell-derived RPs spread from the inoculation site to distant lymphoid tissues earlier and to higher levels than mosquito cell-derived RPs . This greater spread of mammalian cell-derived inoculum at early time points was confirmed using infectious WNV derived from mammalian and mosquito cells . Thus , our West Nile RPs mimic arboviral inoculum and are an essential tool to investigate early immune responses and to characterize initial tropism in vertebrates . Importantly , this work suggests that to accurately simulate the arboviral inoculum for studies of early infection , arthropod cell-derived virus or RPs should be used .
Animal studies were performed in AAALAC-accredited facilities in accordance with an approved protocol ( #V01603 ) by the Institutional Animal Care and Use Committee at the University of Wisconsin-Madison , following the regulations and standards of the Office of Animal Care and Use , National Institutes of Health . Mice were euthanized per the guidelines of the American Veterinary Medical Association . In addition , the research was approved by the Institutional Biosafety Committee at University of Wisconsin-Madison . All WNV and RP packaging experiments were conducted in a biosafety level-3 facility . Prior to working with RP preparations at biosafety level-2 , the stocks were tested for recombined full-length WNV by passaging 10% of total volume on Vero cells for three passages and observing for cytopathic effect , which is a highly sensitive method to detect infectious virus [27] . Only stocks that did not produce cytopathic effect were used at biosafety level-2 . Aedes albopictus clone C6/36 mosquito cells ( CRL-1660 , ATCC , Manassas , VA ) were cultured in complete growth medium [Minimal Essential Medium plus 1X non-essential amino acids solution ( Gibco , Thermo Fisher Scientific , Waltham , MA ) with 10% fetal bovine serum ( Atlanta Biologicals , Flowery Branch , GA ) ] in the presence of 5% CO2 at 28°C . BHK-21 ( BHK ) cells ( CCL-10 , ATCC ) and Vero cells ( CCL-81 , ATCC ) were cultured in 5% CO2 at 37°C and maintained in complete growth medium . Stocks of WNV were produced from an infectious clone by electroporating BHK or C6/36 cells with in vitro transcribed RNA as previously described [28] . Cell culture medium was harvested 2 days ( BHK cells ) or 5 days ( C6/36 cells ) following electroporation and centrifuged at 15 , 000 RCF for 30 minutes at 4°C to remove cellular debris . Aliquots of virus stocks were stored at -80°C . Infectious virus was quantified by plaque assay on Vero cells as described previously [28] . Three replicon clones were used in this study . The WNV replicon construct , described previously [29] , lacks the prM gene and has truncated C and E genes; these structural genes are replaced by Renilla luciferase and the protease motif from the 2a protease of foot-and-mouth disease virus . The alphavirus packaging vector , a Semliki Forest virus replicon with the structural protein genes ( C , E3 , E2 and E1 ) replaced with the WNV structural protein genes C , prM , and E [21] , supplies WNV structural proteins in trans to selectively package WNV replicon RNA . Diagrams of the WNV genome , WNV replicon and SFV packaging vectors are in S1 Fig [21] . The Venezuelan equine encephalitis ( VEE ) virus replicon [30] , lacks its structural protein genes ( C , E3 , E2 , and E1 ) and expresses green fluorescent protein ( GFP ) under its subgenomic promoter . Transformed Escherichia coli containing the WNV and VEE replicon plasmids were grown at 37°C . E . coli stocks containing the packaging vector were grown at 25°C . WNV , VEE , and Semliki Forest virus replicon plasmids were linearized with Xba1 , Not1 , or Spe1 ( New England Biolabs , Ipswitch , MA ) , respectively . RNA was in vitro transcribed using mMESSAGE mMACHINE mRNA kit ( Ambion , Thermo Fisher Scientific ) according to the manufacturer’s instructions . For lipofection , C6/36 cells were seeded at 200 , 000 cells per well in 24-well plates and grown to subconfluency . Prior to lipofection , 90% of the culture medium was removed , and fresh OptiMEM serum-free growth medium ( Gibco ) was added at 40% of the original volume . RNA and lipofection reagents were mixed at various ratios and incubated according to manufacturer’s recommendations . The following RNA:reagent ratios were tested: TransIT-mRNA ( Mirus Bio , Madison , WI ) at 1 μg RNA to 2–4 μL reagent , Lipofectamine 3000 ( Invitrogen , Thermo Fisher Scientific ) at 1 μg RNA to 1–2 μL reagent , and FlyFectin ( OZ Biosciences , San Diego , CA ) at 1–2 μg RNA to 4–7 μL reagent . Following incubation , mixtures of lipofection reagent and RNA were added to cells without removing the culture medium . After 24 hours , medium was removed and replaced with complete growth medium . For electroporation , subconfluent BHK or C6/36 cells were trypsinized and washed twice in cold RNAse-free PBS ( PBS ) . Cells were resuspended at 1x107 cells in 0 . 8 mL cold buffer: PBS , Ingenio ( Mirus Bio ) , or cytomix [31] . Then , 10 μg of appropriate in vitro transcribed RNA was added , and the cell and RNA suspension was electroporated three times using a Gene Pulser Xcell ( Bio-Rad Laboratories , Hercules , CA ) with a 0 . 4 cm electroporation cuvette , voltage of 850 V , capacitance of 20 μF , and a 2–3 second rest between pulses . Cells were incubated at room temperature for 15 minutes , added to complete growth medium in flasks , and incubated at the appropriate temperature with 5% CO2 . Transfection efficiency was determined using in vitro transcribed RNA derived from VEE replicon expressing GFP . Cells were mock-inoculated with diluent only and 48 hours later lipofected with 1 μg VEE replicon RNA mixed with 4μL FlyFectin reagent . After 24 hours , fresh complete growth medium was added . At 4 days post-lipofection , cells were trypsinized for flow cytometry analysis . Briefly , cells were washed , fixed in 1% PFA in PBS for 1 hour , washed again , and kept on ice . Fixed samples were examined by flow cytometry on a LSR Fortessa ( BD Biosciences , San Jose , CA ) . One million cells were acquired per sample ( 1 mock and 3 transfected ) . GFP positive and negative populations were gated and used to calculate a transfection efficiency . The average and standard deviation were determined for triplicate samples using FlowJo ( Ashland , OR ) . Transfection efficiency was confirmed using fluorescence microscopy . C6/36 cells were seeded in 24-well plates , mock inoculated , and transfected with VEE replicon as above . GFP-positive cells were counted in 10 fields of view for three individual wells , and the average and standard deviation were determined . Stocks of BHK cell-derived RPs ( BHK-RPs ) were produced as previously described [21] . Briefly , 107 BHK cells were electroporated with 10 μg in vitro transcribed WNV replicon RNA . Cells were electroporated 24 hours later with 10 μg in vitro transcribed packaging vector RNA . Cell culture medium was harvested 48 hours post-electroporation , clarified by centrifugation at 4°C for 30 min at 10 , 000 RCF , and stored in aliquots at -80°C . Some BHK-RP preparations were concentrated to achieve higher titers by ultracentrifugation on a 20% sucrose cushion for 2 hours at 100 , 000 RCF . RPs were harvested by collecting all the medium from transfected cell cultures and centrifuging the media at 4°C for 10 minutes at 10 , 600 RCF to remove cell debris . Aliquots were stored at -80°C prior to use . Titration by TCID50 was done on Vero cells grown to confluence in 96 well plates . Ten-fold dilutions of harvested RPs or diluent ( mock ) were added to the monolayer in triplicate or quadruplicate and incubated for 1 hour . Complete growth medium was added to the cells and incubated for 2 days . Cells were lysed and assayed for luciferase activity according to manufacturer’s protocol ( Promega Corporation , Madison , WI ) . Luciferase was measured by a Glomaxx Multi + plate reader ( Promega ) using a 10 second integration time/well . Individual wells were considered positive if the observed light units exceeded the average plus three times the standard deviation of the mock wells . RP concentration was calculated as TCID50 using Reed and Meunch method [32] . Immunofluorescence assay ( IFA ) was used to confirm the titer determined by TCID50 for RP stocks . Vero cells were seeded in chamber slides and inoculated with ten-fold dilutions of RP preparations . Cells were incubated for 2 days , washed with PBS , and fixed in 2% paraformaldehyde in PBS . Cells were permeabilized with TritonX-100 , and replicon antigens were detected with anti-WNV mouse hyperimmune ascites fluid ( CDC , Atlanta , GA ) . Goat anti-mouse , FITC-tagged secondary antibody ( Vector Laboratories , Burlington , CA ) was used for detection of positive cells . Positive cells were counted for wells of each dilution , and wells containing 5 to 50 positive cells were used for calculation of particle concentration . WNV is 10-fold more infectious for Vero cells than for C6/36 cells [23 , 33] , meaning that the same virus or RP inoculum at an MOI of 1 on Vero cells is equivalent to an MOI of 0 . 1 on C6/36 cells . For all studies , MOI calculations for C6/36 cells were based on the infectivity for C6/36 cells . Cell lysates or stocks of WNV or RPs were prepared for Western blot analysis by adding sample buffer and incubating at 100°C for 5 minutes to fully denature proteins . Equivalent E protein content of WNV or RPs were loaded , and WNV was diluted in PBS or conditioned medium from mock-inoculated cells to control for non-specific staining that occurred with higher concentrations of medium . Samples were run on a 4–20% Mini-PROTEAN TGX Precast Protein Gel ( Bio-Rad Laboratories ) , transferred to a polyvinylidene fluoride ( PVDF ) membrane ( Thermo Fisher Scientific ) , and blocked with 1% BSA in 1X Tris-Buffered Saline + 0 . 1% Tween 20 . Blots were probed with WNV anti-M antibody ( NB100-56743 , Novus Biologicals , Littleton , CO ) , followed by horseradish peroxidase-labeled goat-anti mouse antibody ( KPL , Gaithersburg , MD ) diluted in 1% BSA in 1X Tris-Buffered Saline . Antibody-antigen complexes were detected using Amersham ECL Prime Western Blotting Detection Reagent ( GE Healthcare Life Sciences , Marlborough , MA ) per manufacturer’s instructions and imaged using BioSpectrum Imaging System ( UVP , Upland , CA ) . A capture ELISA was used to quantify WNV E protein in WNV and RP stocks . We adapted a previously described WNV NS1 capture ELISA method [34] . Purified polyclonal rabbit antibody against WNV E protein ( Novus Biologicals ) was coated onto 96-well MaxiSorp plates ( Thermo Fisher Scientific ) overnight at 4°C at 1 μg/mL in coating buffer ( 15 mM Na2CO3 , 35 mM NaHCO3 , pH 9 . 6 ) . The plate was washed one time with PBS-T ( PBS , 0 . 05% Tween 20 ) and blocked for one hour at 37°C with PBS-T + 5 . 0% skim milk . In order to inactivate infectious virus and replicons prior to use in the ELISA , WNV stocks , RP stocks , and conditioned medium were treated with detergent at a final concentration of 0 . 02% Triton X-100 or 0 . 05% Tween 20 . Antigens were serially diluted 1:2 to 1:64 in diluent buffer ( PBS-T , 0 . 5% bovine serum albumin ) . For the standard curve , WNV E protein ( Reagent Proteins , San Diego , CA ) was diluted in detergent-treated conditioned medium to a concentration of 20 μg/mL and then serially diluted 1:2 to 1:64 in diluent buffer . The plate was incubated for 1 hour at 37°C and washed one time with PBS-T . A cocktail of three monoclonal antibodies against WNV E protein ( clones H79H , J52Q , and L23S ) ( Pierce , Thermo Fisher Scientific ) was used for detection at a final concentration of 1 . 33 μg/mL per antibody . The plate was incubated for 1 hour at 37°C and washed one time with PBS-T . Goat anti-mouse horseradish peroxidase conjugate ( KPL ) at 1:1000 was added and incubated for 30 minutes at 37°C . The plate was then washed three times with PBS-T and developed using TMB substrate ( Thermo Fisher Scientific ) following manufacturer’s protocol . Absorbance was measured at 450 nm using a Glomaxx Multi + plate reader ( Promega ) . A sample was considered positive when the OD was above the average plus three times the standard deviation of conditioned medium ( negative control ) . A standard curve with WNV E protein was established with values above the cut off and used to determine the amount of E protein in WNV and RP stocks . Female C57BL/6J mice ( Jackson Laboratory , Bar Harbor , ME ) were acclimated for one week in the BSL-3 animal facility prior to inoculation at six-weeks-old . For all studies , mice were inoculated subcutaneously ( SC ) in the left rear footpad with 10 μl of inoculum . For the RP studies , mice were inoculated with virus diluent ( mock ) or 2x105 RPs derived from BHK or C6/36 cells and euthanized at 3 , 6 , 12 , 24 , or 48 hours post-inoculation ( hpi ) ( n = 4 per group ) . Ipsilateral ( side of inoculation ) rear footpads , contralateral ( side opposite inoculation ) rear footpads , ipsilateral popliteal and inguinal lymph nodes , contralateral popliteal and inguinal lymph nodes , spleens , and 150 μL whole blood were added to luciferase lysis buffer ( Promega ) ( 1 mL for spleens and whole blood and 200 μL for all other tissues ) . For the WNV studies , mice were inoculated with 105 PFU WNV derived from BHK or C6/36 cells and euthanized at 3 and 6 hpi ( n = 4 per group ) . Ipsilateral rear footpads , ipsilateral inguinal lymph nodes , spleens ( approximately three-fourths ) , and serum samples were processed for infectious virus as previously described [35] . A portion of the spleens ( approximately one-fourth ) was placed in RNAlater ( Ambion ) . For all mouse studies , whole blood ( 150 ul ) was added to 1 mL TRIzol ( Ambion ) for RNA extraction . Solid tissues were homogenized in a TissueLyser II ( Qiagen , Germantown , MD ) using a 4 . 5 mm metal bead or beebee at 24 cycles per second for 4 minutes . Homogenates were then clarified by centrifugation at 6 , 000 RCF for 5 minutes at 4°C , and supernatants were assayed for luciferase activity following manufacturer’s protocol ( Promega ) using lysate volumes of 20 μL or for infectious virus by plaque assay as described previously [35] . Viral loads were reported per organ or per ml of serum or blood ( approximate weights: spleen 0 . 1 g , lymph nodes and footpads 0 . 01–0 . 02g ) . Cutoffs for luciferase assay samples were calculated as the average relative light units ( RLU ) plus three times the standard deviation for tissue samples from mock-inoculated mice . RNA from whole blood was isolated using TRIzol extraction following manufacturer’s protocol . RNA from homogenized tissues , WNV stocks , or RP stocks was isolated using RNeasy Mini Kit ( Qiagen ) . WNV genome equivalents ( GE ) were quantified using TaqMan RNA-to-Ct 1-Step Kit ( Applied Biosystems , Thermo Fisher Scientific ) following the manufacturer’s protocol , using previously described primer-probe sets targeting the 3ʹUTR or E gene [36] . The 3’UTR primer-probe set was used for WNV stocks , RP stocks , and replicon genome in whole blood . The E gene primer-probe set was used for detection of WNV in RNA isolated from tissues . A standard curve of WNV RNA was run with each plate . GraphPad Prism software ( GraphPad Software Inc . , La Jolla , CA ) was used to compare RNA and relative luciferase values using non-parametric two-tailed Mann-Whitney U test . A p-value of less than 0 . 05 was considered significant .
Our goal was to produce WNV RPs packaged in mosquito cells to better mimic mosquito transmission for in vivo studies . For our first attempts to package WNV RPs in C6/36 cells ( C6/36-RPs ) , we followed previously published methods for packaging RPs in BHK cells [21] . Briefly , in vitro transcribed RNA derived from the WNV replicon vector ( WNV replicon RNA ) was electroporated into C6/36 cells . After incubation for 24 hours , the cells were electroporated with in vitro transcribed RNA derived from the packaging vector ( packaging RNA ) . Culture medium was harvested 48 and 72 hours after the second electroporation and titrated by IFA . This method yielded no detectable RPs . We observed high levels of cell death after electroporation of C6/36 cells , which reduced the chances of transfecting one cell with both RNA constructs . Thus , we developed a packaging method to reduce electroporation-induced cytotoxicity and efficiently deliver WNV replicon RNA into the C6/36 cells . Our method consisted of inoculating C6/36 cells at a high MOI with BHK-RPs containing WNV replicon genomes and then electroporating these cells 24 hours later with packaging RNA . This novel packaging method produced the first known mosquito cell-derived RPs and yielded increasing titers from 102 RPs/mL on day 2 to 104 RPs/mL on day 5 post-electroporation ( Fig 1 ) . While these results were encouraging , higher concentrations of mosquito cell-derived RPs are needed to mimic the arboviral inoculum deposited by mosquitoes [37] . We next optimized the RNA delivery to C6/36 cells to produce high titer preparations for use in animal studies . We tested three electroporation buffers ( PBS , Ingenio , and cytomix [31] ) for their ability to deliver RNA while minimizing C6/36 cell death . For each buffer , C6/36 cells were electroporated with WNV replicon RNA . Cells were lysed and assayed for luciferase activity 4 through 9 days post-electroporation . Cells electroporated in cytomix produced the highest luciferase activity through 8 days and resulted in 10-fold higher luciferase activity at 4–6 days post-electroporation compared to cells electroporated in PBS or Ingenio ( Fig 2A ) . In addition , cytomix was observed to improve cell survival during electroporation . These data suggest that cytomix is the best electroporation reagent tested for C6/36 cells . We also investigated lipofection reagents for their ability to deliver replicon RNA to C6/36 cells . Different ratios of RNA to lipofection reagent were tested according to manufacturers’ recommendations . Luciferase activity was an indicator of transfection efficiency . All transfection conditions resulted in luciferase expression . C6/36 cells transfected with FlyFectin exhibited the highest luciferase activity , and transfection was not appreciably different at the various RNA to reagent ratios ( Fig 2B ) . Furthermore , luciferase values were comparable ( approximately 105 RLU ) for electroporation with cytomix and lipofection with FlyFectin although we did not conduct a direct side-by-side comparison for these two transfection methods . Since lipofection offers a smaller scale experimental procedure , allowing for more efficient optimization of other parameters , we used FlyFectin in subsequent experiments at an RNA to reagent ratio of 1 μg RNA to 4 μL FlyFectin . Transfection efficiency for these parameters was quantified using a VEE replicon RNA that expresses high levels of GFP under the subgenomic promoter . Both VEE and WNV efficiently replicate in C6/36 cells [28 , 38] . The VEE system was used because it is more specific and sensitive than using an antibody to detect cells transfected with WNV replicon in C6/36 cells , which are highly autofluorescent . The percentage of GFP-positive cells was determined by flow cytometry , resulting in an average transfection efficiency of 0 . 2+/-0 . 04% ( Fig 2C ) . A similar transfection efficiency of 0 . 3±0 . 05% was determined using fluorescence microscopy . The low transfection efficiency warranted further optimization to produce RPs . In BHK cells , a one day lag between delivery of replicon and packaging RNAs was previously determined to be optimal for production of RPs [26]; however , differences between BHK and C6/36 cell lines limit extrapolation from these data . Peak viral replication and translation in C6/36 cells following either RP inoculation or transfection of WNV replicon RNA using FlyFectin was measured by assaying for luciferase activity . In cells inoculated with RPs , luciferase activity began by 12 hpi at 103 RLU and increased to 107 RLU through 5 days pi ( Fig 2D ) . In comparison , cells lipofected with WNV replicon RNA exhibited 10-fold higher luciferase activity ( 104 RLU ) at 12 hours post-lipofection , but greater than 100-fold lower luciferase activity ( 104 to 105 RLU ) 3–5 days post-lipofection . These results suggest that the method of WNV replicon delivery into cells influences the kinetics and magnitude of replicon replication and translation . A delay between delivery of the replicon and packaging RNAs may enhance RP production by allowing time for WNV replicon RNA amplification , thereby increasing cellular concentrations of WNV replicon RNA and non-structural proteins . Accumulation of these proteins and replicon RNA could also prevent excessive production of empty subviral particles , which lack nucleocapsid , and ensure physiologically relevant ratios of infectious to noninfectious particles for use in vivo . The optimal time between deliveries of WNV replicon RNA by RP inoculation and delivery of packaging vector RNA by FlyFectin was investigated . C6/36 cells were inoculated with BHK-RPs , and 24 , 48 , or 72 hpi , cells were transfected with packaging vector RNA . Twenty-four hours after transfection , the medium was harvested and replaced every 24 hours until the 13th day of culture ( 8 , 9 , and 10 days post-lipofection for 24 , 48 , and 72 hour delay , respectively ) . A transfection delay of 24 hours yielded titers less than 106 RPs/mL/day from 3–10 days post-lipofection , which were over 10-fold less than either the 48 or 72 hour transfection delays from days 3 to 8 post-lipofection ( Fig 3A ) . The 48 and 72 hour delays produced equivalent titers by day 3 post-lipofection with peak titers of 5 . 4x106 RPs/mL/day ( 48 hour delay on 4 days post-lipofection ) and 5x106 RPs/mL/day ( 72 hour delay 6 days post-lipofection ) . All three transfection delay experiments produced particles through 13 days of culture with RP production often remaining above 105 RPs/mL/day . This robust and sustained RP production was observed in all packaging experiments ( Figs 3A , 3B and 4A ) . Since there were no substantial differences between transfection delays of 48 and 72 hours , the shorter transfection delay of 48 hours was selected for future investigations . We next attempted to increase C6/36-RP production by optimizing WNV replicon delivery via BHK-RP inoculation . We hypothesized that inoculating cells with a higher MOI of BHK-RPs would increase the number of cells that receive both the replicon and packaging RNAs and lead to greater RP production . Thus , we measured the yield of RPs packaged in C6/36 cells after inoculating BHK-RPs at an MOI of 0 . 05 , 0 . 5 , or 1 and transfecting with packaging RNA 48 hours later . C6/36-RPs were packaged through 10 days post-lipofection , and peak production was observed between 4 and 6 days post-lipofection for all three MOI conditions ( Fig 3B ) . The greatest C6/36-RP concentration was 2x107 RPs/mL , which is sufficient to inoculate mice in the footpad with 10 μl of 105 RPs , the median dose of WNV inoculated by Culex tarsalis mosquitoes [37] . The MOI of BHK-RPs did not correlate with production of C6/36-RPs . This unexpected outcome is advantageous since a lower MOI for the initial inoculum will result in a C6/36-RP stock with fewer BHK-RPs carried over from the replicon inoculum . For some studies , it might be desirable to eliminate mammalian cell-derived RPs from stocks of mosquito cell-derived RPs . Thus , we produced C6/36-RPs by delivering both WNV replicon and packaging RNAs by lipofection . FlyFectin was used to deliver the WNV replicon RNA and , 48 hours later , the packaging RNA . RPs were harvested 2–11 days post-lipofection . Using this method , RPs were produced through 11 days ( Fig 4A ) , and peak RP production reached 2 . 4x104 RPs/mL/day at 4 days post-lipofection . Higher concentrations of RPs were needed for in vivo studies than could be packaged using FlyFectin to deliver both RNAs , but this technique is useful to produce lower concentrations of pure mosquito-cell derived RPs . The initial BHK-RP inoculation at high MOI did not increase RP production , and the lowest MOI ( 0 . 05 ) was able to produce RPs of sufficient concentration for animal studies ( 107 RPs/ml ) ( Fig 3B ) . Thus , we quantified the residual mammalian cell-derived RPs in our insect cell-derived RP preparations , using an RP inoculation at the low MOI . C6/36 cells were inoculated with BHK-RPs at an MOI of 0 . 05 and mock transfected , and culture medium was harvested and titrated as in our packaging protocol . Carryover of mammalian cell-derived RPs was highest 2 days post-lipofection at 7 . 6x103 RPs/mL/day and decreased through 5 days post-lipofection to 1 . 1x102 RPs/mL/day ( Fig 4B ) . This amount of BHK-RPs corresponds to less than 0 . 1% of the C6/36-RPs harvested per day , and such a low percentage is expected to have negligible effects in in vivo studies . In addition to fully infectious virus particles , flaviviruses can produce immature , non-infectious , and empty subviral particles [4 , 39–44] . Thus , prior to using the mosquito cell-derived RPs in our studies , we compared characteristics of the RP stocks to standard virus stocks produced in mammalian and insect cells . As a measure of immature particles , we examined cleavage of prM to M by Western blot , using an antibody to WNV M protein . In WNV-infected cell lysates , M and prM were easily detected ( Fig 5A ) . Conversely , M was present , but prM was not detected , in WNV and RP stocks derived from both C6/36 ( Fig 5B ) and BHK ( Fig 5C ) cells . These data demonstrate that all preparations , including stocks of the novel C6/36-RPs , consisted of fully mature particles as indicated by cleavage of prM to M . Large amounts of noninfectious particles can trigger host immune responses and possibly confound in vivo study results , especially since immune cells are likely early targets of WNV infection [12] . As a measure of non-infectious particles , we calculated the ratios of GE-to-infectious units ( IU ) for our RP and WNV stocks . The ratios of GE:IU were less than 3-fold different for RP and virus stocks derived from the same cell line ( Table 1 ) . The BHK-RP stock had a 4-fold higher ratio than C6/36-RP stock . The ratios of GE:IU for additional RP samples were 106±50 ( n = 7 ) for BHK-RPs and 56±36 for C6/36-RPs ( n = 4 ) , and this 2-fold difference was not significantly different . Thus , the C6/36-RPs have levels of non-infectious particles expected for virus stocks and within the experimental range for BHK-RPs . Empty subviral particles can be produced by flavivirus-infected cells [39–43] and artificially in cells transfected with structural genes from flaviviruses , e . g . WNV [45 , 46] , Japanese encephalitis virus [42 , 47] , and dengue virus [48] . Subviral particles lack genome and C protein , contain M and E proteins in a lipid bilayer , and have a similar , albeit smaller , structure compared to a virus particle . Since these subviral particles are antigenic [45–47 , 49] and have the potential to interact with cellular receptors [9] , we quantified the E protein content of WNV and RP stocks by capture ELISA and compared the ratio of E protein to GE . A higher ratio indicates greater amounts of empty subviral particles . E protein content of C6/36-RP stocks was below the limit of detection of the assay ( <0 . 5 μg/mL ) , resulting in a ratio of <8x10-10 μg E:GE , which was comparable to C6/36 cell-derived WNV stock at 4x10-10 μg E:GE ( Table 1 ) . The BHK-RP stock exhibited a high E protein to GE ratio of 295x10-10 , which was 7-fold higher than WNV derived from BHK cells , suggesting the presence of more empty subviral particles in BHK-RPs . In summary , the characteristics of our C6/36-RP stock were similar to WNV stocks , validating the use of C6/36-RPs in vivo as a model of WNV inoculum from a mosquito . Replicon particles are useful tools to identify the first cells infected in a single round of infection . We compared the initial tropism and spread of RPs derived from mammalian cells and mosquito cells by assaying for luciferase activity in various tissues of mice from 3 to 48 hpi . After inoculation in the left rear footpad , luciferase activity was detected in the ipsilateral footpad skin and popliteal lymph node as early as 3 hpi for both BHK-RPs and C6/36-RPs ( Fig 6A and 6B ) , demonstrating that the RPs had entered cells and initiated translation of the reporter . No significant differences were observed in the ipsilateral footpad skin through 48 hpi for mice inoculated with the two different RP inocula . At 3 hpi , we observed significantly higher luciferase activity in the draining popliteal lymph node for BHK-RPs , but at all other time points , there were no significant differences in luciferase activity in the draining popliteal and inguinal lymph nodes for mice inoculated with the different RP inocula ( Fig 6B and 6C ) . In contrast , greater differences were observed for distant lymphoid tissues . There was significantly higher luciferase activity in the spleen for BHK-RPs from 3 through 48 hpi compared to C6/36-RPs ( Fig 6E ) . Furthermore , luciferase activity was only observed at 12 and 24 hpi in the spleen for C6/36-RPs . In addition , there was luciferase activity in the popliteal and inguinal lymph nodes on the contralateral leg of mice at 24 hpi only in mice inoculated with the BHK-RPs ( Fig 6F and 6G ) . There was no spread to the footpad skin on the contralateral leg for either RP inocula ( S2 Fig ) . In summary , both the BHK-RPs and C6/36-RPs replicated in skin at the inoculation site , draining lymph nodes , and spleen , but there was more rapid and greater spread of the BHK-RPs to distant lymphoid tissues , suggesting that either RP-infected cells or RPs from the inoculum are moving through the blood to distant tissue sites . We investigated the possibility that RP-infected cells and/or RPs from the inoculum spread in the blood by assaying for luciferase activity and replicon genome by qRT-PCR in whole blood . No luciferase activity was observed in whole blood for either RP inocula ( Fig 6D ) . In contrast , replicon RNA was observed as early as 3 hpi for both RP inocula , but there was significantly higher levels of replicon RNA in blood of mice inoculated with BHK-RPs compared to C6/36-RPs from 3 to 12 hpi ( Fig 6H ) . Replicon RNA levels were 160-fold ( 3 hours ) , 60-fold ( 6 hours ) , and 10-fold ( 12 hours ) greater in the blood of mice inoculated with BHK-RPs compared to C6/36-RPs . Taken together , these results suggest that RP particles in the inoculum spread through the blood to distant tissues , and this spread is significantly greater for mammalian cell-derived RPs than for mosquito cell-derived RPs . In order to confirm these results with RPs , we examined tropism and spread of infectious WNV derived from BHK-21 cells ( WNV-BHK ) or C6/36 cells ( WNV-C6/36 ) . These stocks had less than 2-fold difference in their GE:IU ratios ( Table 1 ) , allowing us to directly compare both infectious virus by plaque assay and genome levels by qRT-PCR in blood and tissues . Mice were inoculated in the left rear footpad , and tissues were harvested at 3 and 6 hpi , which is prior to viral production [28 , 35] . At these early time points , infectious virus is from the inoculum , and viral RNA is from the inoculum and/or infected cells . Significantly higher infectious viral loads in the footpads and draining popliteal lymph nodes were detected in mice inoculated with WNV-BHK compared to WNV-C6/36 ( Fig 7A and 7B ) , suggesting that WNV-BHK enters cells less efficiently at the site of inoculation . This difference was dramatically reduced when the tissues were assayed for WNV RNA ( Fig 7E and 7F ) , supporting the conclusion that WNV-C6/36 enters cells more readily and most of the viral RNA in these tissues was from infected cells in the eclipse phase for mice inoculated with WNV-C6/36 . Infectious virus from the inoculum was detected in serum in 3 of 4 mice at both 3 hpi ( average of 103 . 4 PFU/ml ) and 6 hpi ( average of 102 . 7 PFU/ml ) for WNV-BHK , but no infectious virus ( < 50 PFU/ml ) was detected in serum for WNV-C6/36 in any of the mice ( Fig 7D ) . In addition , greater levels of WNV RNA were observed for WNV-BHK in whole blood compared to WNV-C6/36: over 500-fold more at 3 hpi ( p-value<0 . 05 ) and 14-fold more at 6 hpi ( Fig 7H ) . Systemic spread to the spleen occurred earlier in mice inoculated with WNV-BHK compared to WNV-C6/36 ( Fig 7C and 7G ) with significantly higher levels of WNV RNA ( over 90-fold ) at 3 hpi for WNV-BHK compared to WNV-C6/36 . Taken together these data suggest that WNV-BHK inoculum enters the blood more readily than WNV-C6/36 . Furthermore , these studies with infectious virus confirm our results with WNV RPs , demonstrating greater spread of the inoculum to distant tissues for the mammalian cell-derived compared to mosquito cell-derived virus and replicon particles .
Arboviruses cycle between vertebrates and arthropods , and virus particles derived from these disparate hosts differ in the glycosylation of viral glycoproteins and lipid content of viral envelopes . Since virus inoculum transmitted from the arthropod to the vertebrate host is derived from the arthropod vector , our goal was to mimic this inoculum , using a WNV replicon packaged in mosquito cells , in order to model the very early events following viral transmission from a mosquito . Here we successfully produced and characterized high titer stocks of RPs derived from C6/36 mosquito cells . When inoculated into mice , the mosquito cell-derived RPs showed reduced systemic spread from the inoculation site in comparison to mammalian cell-derived RPs . These results underscore the importance of arthropod cell-derived RPs to accurately mimic the arthropod inoculum when studying early events in arbovirus infection . RPs have been packaged using numerous constructs in mammalian cell lines , often by electroporating in replicon RNA as well as packaging vector RNA . We found that C6/36 cells were not as robust during electroporation; thus , we developed a protocol by which replicon RNA is delivered via RP inoculation , and packaging vector RNA is delivered via lipofection . Although previous studies optimizing RP packaging in mammalian cells observed benefits from delivering the packaging vector 24 hours after delivery of the replicon RNA [26] , we found it was optimal to deliver packaging vector RNA 48 or 72 hours following delivery of replicon RNA ( Fig 3A ) . Numerous variables could account for these different results . For example , inherent differences between WNV replication within mosquito cells compared to mammalian cells may play a role . The growth rate of WNV is faster in mammalian cells compared to mosquito cells [28] , and a longer delay may be required to allow for adequate replicon replication in mosquito cells . In addition , we delivered replicon RNA by RP inoculation and packaging vector RNA by lipofection , which is quite different from the double electroporation method used for BHK cells . Thus , differences in methodology may also account for the optimal delay between the replicon and packaging RNA delivery . We observed increasing production of RPs during the first 2–3 days following packaging vector delivery ( Fig 3A and 3B ) , which was also found in previous studies producing WNV RPs from BHK cells [26] . However , our data differed from these experiments in long term RP production . We produced RPs through 10 days often with minimal decrease in titer whereas the previous study producing RPs in BHK cells using double electroporations observed severe cytopathic effect or a large reduction in RP production after 3 days post-electroporation [26] . These same investigators produced sustained RP production in BHK cells through 10 days post-induction by using a packaging cell line that selected for and maintained the WNV structural protein genes [25] . We propose that the sustained RP production in C6/36 cells in our system is most likely due to minimal cytopathology in mosquito cells . A surprising result of our optimization was that RP production did not correlate with the MOI of the RP inoculation , despite more cells infected at a higher MOI . One explanation is that the transfection efficiency for lipofection of the packaging RNA is very low , resulting in very few cells with both replicon and packaging vector . These few cells will produce RPs , which will then infect other cells in the culture , delivering replicon genome to the limited cells with packaging RNA . The actual MOI would quickly rise , masking any difference between MOIs upon initial inoculation . Since flaviviruses can produce several types of particles , such as mature , immature and empty subviral particles [4 , 39–44] , we characterized our mosquito cell-derived RP stock to ensure that it resembled infectious WNV for several key characteristics . This is especially important for animal studies because immature , non-infectious and empty subviral particles have reduced or no infectivity , but they can still interact with cellular receptors , stimulate the immune response [9 , 45–47 , 49] , and potentially confound results if present in excessive quantities . In our RP and WNV stocks , prM was fully cleaved , indicating that minimal immature particles were present . We used genome equivalents to infectious unit as a measure of non-infectious to infectious particles and again WNV and RPs were similar within a single cell line . The GE:IU ratios were comparable to other published studies for WNV [15 , 50] , but lower than for dengue and yellow fever viruses [51 , 52] . Finally , we used E protein content to genome equivalents as a measure of total particles to particles containing genome ( the latter encompasses infectious , non-infectious and immature particles ) ; a high ratio indicates more empty subviral particles . This ratio was similar for the RPs and WNV derived from C6/36 cells . In contrast , the ratio was 7-fold greater for BHK-RPs compared to WNV derived from BHK cells and 39-fold greater compared to C6/36-RPs , suggesting that BHK-RPs have greater amounts of empty subviral particles . It is possible that the higher transfection efficiency in BHK cells compared to C6/36 cells results in more cells singly transfected with the packaging vector , which would produce more empty subviral particles . For the characteristics measured in this study , C6/36-RPs were very similar to full-length WNV , supporting their use to mimic an arbovirus inoculum transmitted by mosquitoes . On the other hand , it is important to consider that the use of cell culture-derived virus or replicons is still an artificial system and may not fully represent virus particles produced in a mosquito or vertebrate hosts . We compared the replication kinetics and spread of BHK-RPs and C6/36-RPs inoculated SC into the footpads of mice . The BHK-RPs resulted in a more rapid spread and subsequent replication in the draining popliteal lymph node and distant lymphoid tissues ( spleen and lymph nodes of the opposite leg ) compared to C6/36-RPs . Neither RP inoculum spread to the contralateral footpad skin . This is consistent with our previous studies using WNV in which viral loads were first detected in contralateral skin at 2–3 dpi ( 1–2 days later than spleen and contralateral lymph nodes ) [35] . These results demonstrate how RPs can be used to study the kinetics of early local and systemic spread of the inoculum . Since spread to the spleen and contralateral lymph nodes must occur via free RPs or RP-infected cells through the blood , we expected to observe differences in the amount of replicon RNA in the blood as well . This was indeed the case; we observed significantly higher amounts of replicon RNA present in the blood of mice inoculated with BHK-RPs up to 12 hpi compared to mice inoculated with C6/36-RPs ( Fig 7 ) . In addition , the replicon RNA in the blood does not appear to be due to infected cells since we did not find evidence of RP-infected cells trafficking through the blood at the limit of our luciferase assay ( Fig 6 ) . One caveat of these RP studies is that we inoculated equivalent infectious units in order to directly compare the luciferase activity of RP-infected tissues , which necessitated inoculation of different GEs . In fact , four-fold more GEs of BHK-RPs than C6/36-RPs were inoculated ( Table 1 ) , which would affect replicon genome levels . This does not , however , account for the higher levels of replicon RNA in the blood for BHK-RPs ( 160-fold difference compared to C6/36-RPs at 3 hpi ) . Furthermore , we confirmed these results , using WNV stocks that were less than 2-fold different in GE:IU ratios with BHK-WNV ( GE:IU = 57 ) having a lower ratio than C6/36-WNV ( GE:IU = 75 ) ( Table 1 ) . Like the study with RPs , the mammalian cell-derived WNV exhibited greater spread from the site of inoculation to the draining lymph node and into the blood compared to the mosquito cell-derived WNV ( Fig 7 ) . These results are also consistent with our previously published studies , which demonstrated earlier spread with BHK-WNV compared to C6/36-WNV although morbidity and mortality were not altered late in infection [15] . Overall , our data in mice support a model that free particles in the inoculum are trafficking to the draining lymph node and entering the blood to infect distant sites , and mammalian cell-derived particles travel from the site of inoculation more than mosquito cell-derived particles . The exact mechanism responsible for these differences in spread from the inoculation site is unknown . One likely explanation is the glycosylation differences of the E protein of the virus particles derived from vertebrate versus invertebrate cells . Flaviviruses derived from mosquito cells have high-mannose glycans [9 , 10] , which may enhance particle binding to cells and/or the extracellular matrix at the site of inoculation , limiting the number of particles that enter the lymphatics or blood and spread to the draining lymph nodes and spleen . Another possibility is that the glycosylation differences alter cell tropism of the particles . Cell culture studies have shown that more dendritic cells are infected with WNV derived from mosquito cells compared to WNV derived from mammalian cells [9 , 15] , but such an effect in vivo is unclear . Our current studies in mice showed that equivalent replication ( as measured by luciferase expression ) occurs in the skin at the inoculation site through 48 hpi and in the draining lymph node 6–48 hpi for the RPs derived from mammalian and mosquito cells . There was , however , significantly greater replication in the draining lymph node at 3 hpi for the BHK-RP compared to C6/36-RPs , which is due to either movement of infected cells and/or free RPs trafficking to the lymph node . Based on the previous cell culture studies , one would expect more infected dendritic cells trafficking to the lymph node for mosquito cell-derived RPs , but this was not observed . Finally , empty subviral particles are produced in flavivirus-infected mammalian and mosquito cell culture and in mice [39–43] , and it is possible that variable amounts of these particles might influence spread ( e . g . by stimulating immune cells and changing the microenvironment ) . This is an important consideration for the RP studies , in which the BHK-RPs had 39-fold greater E:GE ratios compared to C6/36-RPs ( Table 1 ) . We cannot rule-out this possible factor; however , we still observed greater spread with BHK-WNV , which possessed only 10-fold greater E:GE ratio compared to C6/36-WNV . While empty particles may be a contributing factor to spread of a flavivirus inoculum , it is unlikely to explain all of the differences . In conclusion , we present an optimized protocol to efficiently produce high concentrations of mosquito cell-derived WNV RPs with similar particle characteristics as full-length infectious virus . When used in mice , these particles spread from the inoculation site to distant tissues less than the mammalian cell-derived RPs , resulting in altered replication kinetics . These data make a compelling argument for the use of mosquito cell and not mammalian cell-derived inoculum for arboviral studies to further elucidate the cell targets and progression of arbovirus infection in animal models . Future studies will use the WNV RPs with mosquito saliva to examine its effect on initial cell targets , the numbers of infected cells , and systemic spread .
|
Many emerging viruses of public health concern are arthropod-borne , including tick-borne encephalitis , dengue , Zika , chikungunya , and West Nile viruses . The arboviruses are maintained in nature via virus-specific transmission cycles , involving arthropod ( e . g . mosquitos , midges , and ticks ) and vertebrate animals ( e . g . birds , humans , and livestock ) . Common to all transmission cycles is the requirement of the arbovirus to replicate in these very different hosts . Since viruses rely on the host cell machinery to produce progeny , the virus particles from these hosts can differ in viral protein glycosylation and lipid content . Thus , the viral inoculum deposited by an infected arthropod will have different properties than virus produced in vertebrate cells . We set out to study the early events of arbovirus infection in a vertebrate host , using the mosquito-borne West Nile virus as a model . Here , we are the first to describe a robust protocol to produce West Nile replicon particles from mosquito cells . Since replicon particles are restricted to a single round of infection , we were able to compare the tropism and spread of the inoculum in animals for mosquito cell- and mammalian cell-derived replicon particles . We found that West Nile replicon particles derived from mosquito cells were significantly reduced in spread to distant sites compared to those derived from mammalian cells . Our results suggest that studies on arbovirus pathogenesis should be conducted with arthropod cell-derived virus , especially for the study of early virus-host interactions .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"transfection",
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"luciferase",
"body",
"fluids",
"pathology",
"and",
"laboratory",
"medicine",
"enzymes",
"pathogens",
"microbiology",
"enzymology",
"animals",
"viruses",
"lymph",
"nodes",
"rna",
"viruses",
"lymphatic",
"system",
"molecular",
"biology",
"techniques",
"mammalian",
"genomics",
"research",
"and",
"analysis",
"methods",
"infectious",
"diseases",
"proteins",
"medical",
"microbiology",
"oxidoreductases",
"microbial",
"pathogens",
"arboviral",
"infections",
"molecular",
"biology",
"hematology",
"animal",
"genomics",
"arthropoda",
"biochemistry",
"west",
"nile",
"virus",
"anatomy",
"flaviviruses",
"blood",
"viral",
"pathogens",
"physiology",
"genetics",
"biology",
"and",
"life",
"sciences",
"viral",
"diseases",
"genomics",
"organisms"
] |
2017
|
Mosquito cell-derived West Nile virus replicon particles mimic arbovirus inoculum and have reduced spread in mice
|
Inhibition of N-myristoyltransferase has been validated pre-clinically as a target for the treatment of fungal and trypanosome infections , using species-specific inhibitors . In order to identify inhibitors of protozoan NMTs , we chose to screen a diverse subset of the Pfizer corporate collection against Plasmodium falciparum and Leishmania donovani NMTs . Primary screening hits against either enzyme were tested for selectivity over both human NMT isoforms ( Hs1 and Hs2 ) and for broad-spectrum anti-protozoan activity against the NMT from Trypanosoma brucei . Analysis of the screening results has shown that structure-activity relationships ( SAR ) for Leishmania NMT are divergent from all other NMTs tested , a finding not predicted by sequence similarity calculations , resulting in the identification of four novel series of Leishmania-selective NMT inhibitors . We found a strong overlap between the SARs for Plasmodium NMT and both human NMTs , suggesting that achieving an appropriate selectivity profile will be more challenging . However , we did discover two novel series with selectivity for Plasmodium NMT over the other NMT orthologues in this study , and an additional two structurally distinct series with selectivity over Leishmania NMT . We believe that release of results from this study into the public domain will accelerate the discovery of NMT inhibitors to treat malaria and leishmaniasis . Our screening initiative is another example of how a tripartite partnership involving pharmaceutical industries , academic institutions and governmental/non-governmental organisations such as Medical Research Council and Wellcome Trust can stimulate research for neglected diseases .
Protozoan parasites are major causative agents of global infectious diseases that affect millions of people in tropical and sub-tropical regions of the world [1] . In the absence of effective vaccination strategies , treatment for many of these infections depends on chemotherapy and is reliant on “old” drugs that have often been in use for long periods; were originally developed for other types of disease; give rise to increasing levels of microbial resistance; and often show unacceptable levels of toxicity . There is a pressing need for new therapeutics that can be targeted to the populations that need them . This work focuses on two groups of diseases: the leishmaniases ( caused by species of the kinetoplastid parasite , Leishmania ) and malaria ( caused by species of the apicomplexan parasite , Plasmodium ) . In the case of the leishmaniases ( a spectrum of diseases associated with immune dysfunction ) , there are estimated to be 1 . 5–2 million new cases each year in 88 countries around the globe , with 350 million people at risk and a disease burden of ∼2 . 4 million disability-adjusted life years [2] , [3] . Clinical symptoms , ranging from the disfiguring skin lesions of cutaneous leishmaniasis to the often fatal visceral leishmaniasis ( VL – predominantly caused by Leishmania donovani ) are exacerbated in children and immuno-compromised patients , such as those diagnosed as HIV positive . Pentavalent antimonials have been the first-line treatment for VL since the 1930s but these compounds are toxic , with resistance an increasing problem in the Indian sub-continent [4] . While significant progress has been made in the last 10 years , with the approval of lipid formulations of amphotericin B , miltefosine and paromomycin , none of these has been developed by rational design , and resistance may still be a problem . There is no effective vaccine available , although vaccination should theoretically be possible against these infections that can “self-heal” in their most benign states . Thus new strategies for vaccination and chemotherapy , particularly for visceral leishmaniasis ( VL ) , remain an urgent international priority [5] . Malaria remains one of the most important infectious diseases of the developing world . There were an estimated 216 million episodes in 2010 , resulting in between 650 , 000 and 1 . 2 million deaths , according to two recent reports , with over 90% occurring in Africa [6] , [7] . Although P . falciparum accounts for 75% of malaria cases and most of the deaths , P . vivax is also a significant problem in South East Asia , and South and Central America [8] . There is an urgent need to develop new drugs with rapid efficacy , minimal toxicity and low cost to replace chloroquine and pyrimethamine-sulphadoxine ( available as Fansidar ) , which are failing rapidly due to resistance in P . falciparum [9]–[11] . The use of artemisinin and its derivatives , such as artesunate or artemether , which have good efficacy but very short half-lives , together with longer acting agents such as amodiaquine or lumefantrine in artemisinin-based combination therapy ( ACT ) , offers some respite . However these drugs are expensive , development of resistance is an ever present possibility , and new effective drugs will be required [12] . In addition it is important to develop new drugs that also target blood stage sexual forms of the parasite to prevent transmission , particularly of drug resistant parasites [13] . At a recent Malaria Forum , the Gates Foundation [14] called for the eradication of malaria . This goal will realistically only be achieved by supplementing current control methods with the development of vaccines and new drugs . The disease statistics above make a compelling case for accelerated drug development , which should be facilitated by recent rapid progress in genome sequencing and subsequent post-genomic strategies for target identification [12] , [15] . Numerous targets have been assessed , including pyrimidine biosynthesis [16] , nucleotide signalling [17] , kinase pathways [18] and lipidation [19] . Inhibition of prenylation has shown potential to treat malaria and more recently , lipid modification through inhibition of N-myristoylation has shown encouraging progress . Co–translational myristoylation is catalysed by the monomeric enzyme myristoyl CoA: protein N-myristoyltransferase ( NMT ) in all eukaryotes and has been shown to be essential for viability in fungi and protozoa , through both genetic studies and by chemical inhibition of Candida albicans NMT [20] , [21] and Trypanosoma brucei NMT ( Tb NMT ) [22] , [23] . Our earlier work on the NMTs of T . brucei ( the kinetoplastid causative agent of African sleeping sickness ) [24]–[26] , L . major [26] ( causative agent of cutaneous leishmaniasis ) and P . falciparum ( Pfal ) [27] , [28] , identified NMT as a suitable candidate for drug development against the diseases caused by these protozoan organisms [29] , [30] . NMT from Tb has already been demonstrated to be a druggable target using small molecules ( Figure 1 ) [22] , [23] . In addition , NMTs from fungal species e . g . C . albicans and Aspergillus fumigatus have also been long-standing targets within the pharmaceutical industry and several inhibitor series have been reported [20] , [21] , [31] . With the exception of the Searle series , which are peptidomimetics based on the C . albicans Arf protein , all other published NMT inhibitor series were obtained by high-throughput screening . Structures of representative inhibitors bound to their respective NMT targets are available and each shows inhibitors binding in the same region as the substrate peptide . A wide variety of proteins are reported or predicted as substrates for myristoylation based on an N-terminal consensus sequence for substrates ( GXXXSK/L ) [32] . The broad scope of amino acids that are tolerated close to the amino terminal is a reflection of a relatively wide channel , which can be used to rationalise the diversity of the inhibitor structures . The published molecular structures from the fungal and T . brucei NMT programs were used to overlay the ligands in a common co-ordinate frame , ( Figure 2 ) , and could be used to rationalise the observed selectivity e . g . for fungal vs . protozoan NMTs . The presence of compounds from the legacy Searle and Pfizer fungal NMT programs , within the Pfizer corporate collection , has made screening of the Pfizer file an attractive option for the identification of inhibitors of Plasmodium and Leishmania NMTs [33]–[35] . In this study , we extend the scope of screening to sample the diversity of the entire Pfizer compound file . Due to time and cost constraints , we decided to limit our primary screening campaign to ∼150 , 000 compounds from the Pfizer Global Diverse Representative Set [36] , against both Pfal NMT and L . donovani ( Ldon ) NMT since these protozoan NMTs are sufficiently dissimilar at the sequence level to warrant separate screens . Activity of hit compounds would be confirmed in replicated dose-response assays to generate a preliminary SAR for each target . All mammalian systems studied to date have been shown to have two NMT genes , nmt1 and nmt2 [37] . HsNMT1 has been shown to be essential for embryonic development in mice , whilst the physiological role of HsNMT2 is currently unknown [38] . However , a number of oncogenic proteins are substrates of human NMTs , and certain viruses and bacteria also exploit host NMTs to myristoylate their own proteins . Consequently , human NMTs have been proposed as targets for the treatment of cancer and viral infections [29] . To date , there have been no conclusive reports on the potential toxicity of mammalian NMT inhibition in vivo , but in view of the essential role of NMT in mammalian development , selectivity over human NMTs is desirable . All hits from this study should therefore be screened in dose–response assays against both human isoforms HsNMT1 & HsNMT2 ( Hs1 & Hs2 ) . Hits might also be tested against the NMT from Tb , since activity against multiple protozoan NMTs would be an advantage , provided selectivity over human NMTs could be achieved .
Recombinant P . falciparum [39] ( Swiss-Prot Q81LW6 ) and L . donovani NMTs [40] ( EMBL accession number FN555136 ) were produced at the University of York , using established protocols . An assay format based on scintillation proximity technology to monitor enzyme activity was used as previously described [27] , [30] . This radioactive format provides a quantification of the N-myristoylation of the synthetic peptide CAP5 . 5 ( derived from the N-terminus of the T . brucei CAP5 . 5 protein ) [41] as used in [22] , [24] , and was modified to a 384-well plate screening format with a final volume of 40 µl . The Pfizer Global Diverse Representative Set [36] consisting of 150 , 000 compounds was screened at 20 µM final assay concentration . Assay plates were prepared by dispensing 0 . 1 µL of compound dissolved in DMSO using the Vario system ( Cybio ) into white 384-well plates ( Greiner Bio-One ) . The assay buffer consisted of 30 mM Tris-HCl pH 7 . 4 , 0 . 5 mM EGTA , 0 . 5 mM EDTA , 0 . 1% Triton X-100 and 1 . 25 mM DTT . Enzyme solution containing the appropriate NMT ( Pfal at 3 . 7 nM final assay concentration , Ldon at 0 . 84 nM ) diluted in assay buffer was added to each well in a volume of 10 µl using a Multidrop Combi dispenser ( Thermo Scientific ) . Plates were incubated for 15 min at room temperature ( RT ) before the addition of substrate solution , consisting of cold myristoyl CoA ( Sigma ) , 3H-myristoyl CoA ( ARC ) and CAP5 . 5 at the respective final assay concentrations of 54 nM , 8 . 5 nM and 250 nM . The reaction was initiated by adding 10 µL of the substrate mixture to each well containing the pre-incubated enzyme/compound mixture , and allowed to proceed at RT for 80 min . The reaction was quenched by the addition 20 µl of stop solution to each well . Stop solution consisted of 0 . 75 M MgCl2 ( Sigma ) , 0 . 1 M phosphoric acid ( Sigma ) and 1 mg/ml of streptavidin-coated polystyrene SPA beads ( Perkin-Elmer ) . Plates were sealed using topseals ( Perkin-Elmer ) and left overnight to allow the bead solution to settle . Radioactive counts were measured with an integration time of 300 sec per plate using the Leadseeker Generation 4 plate reader ( GE Healthcare ) . Each plate included a positive control of 1 µM final assay concentration of DDD85646 [22] and 1% DMSO as a negative control . Hit compounds were further titrated using a through-plate IC50 format with a top concentration of 80 µM , and 12 points with a 1∶2 dilution step . The data were analysed using Pfizer SIGHTS software and visualised using Spotfire software ( TIBCO ) . Additional dose-response assays using the T brucei NMT [22] , [24] ( EMBL FN554973 ) and human enzymes HsNMT1 [39] ( Swiss-Prot P30419 ) and HsNMT2 [39] ( Swiss-Prot O60551 ) , produced at the University of York using established protocols , were carried out to assess the activity spectrum of hit compounds . The assay format used was the same as above , however the respective concentrations of the enzymes were 4 . 8 nM , 2 . 6 nM and 2 . 6 nM , respectively . Substrate concentrations were 108 nM myristoyl CoA , 17 nM 3H-myristoyl CoA and 500 nM CAP5 . 5 ( final assay concentration ) for all three specificity screens . The stop solution had a reduced SPA bead concentration of 0 . 5 mg/ml . The Tb NMT screen reaction incubation was 60 min , while the Hs1 and Hs2 reaction incubation was 15 min . The same dose-response format of 80 µM top concentration and a 12-point curve , with a 1∶2 dilution step was used .
While the reported NMT inhibitors all occupy the substrate peptide-binding site , structural studies on C . albicans NMT have shown that distinct inhibitor series exploit different interactions with the protein ( Figure 2 ) . Consequently , we envisaged that a set of high-throughput screening hits would be likely to represent a number of different binding modes . We anticipated that a different binding mode might result in a different selectivity profile against the set of NMTs in this study . In the case of the recently reported TbNMT inhibitors , the lead compound is reported to have equivalent potency against both HsNMT1 and L . major NMT [22] . In contrast , our previous work had shown that even a single residue change in the binding region of C . albicans NMT was sufficient to result in a three-hundred-fold loss of enzyme affinity [35] . We hypothesised that the number of global residue changes between the NMT proteins would correlate with increasingly divergent SAR for the various NMT proteins in this study . Publically available sequence information was used to calculate pairwise similarity and identity between the NMT proteins in the study ( Figure 3 ) . Although an ideal compound would have broad-spectrum activity against the protozoan NMTs but would lack activity against both human NMTs , our analysis suggested that this could difficult to achieve , unless some distinct differences in the binding sites could be exploited . The sequence similarities suggest that it should be more likely for Ldon NMT hits to be selective over Pfal and HsNMTs , but that PfalNMT hits would be less likely to achieve selectivity over HsNMTs . The Pfal and Ldon HTS generated Z′ scores of 0 . 84 and 0 . 78 , respectively , indicating that the screening results were of excellent quality [42] . In order to capture all potential actives , compounds conferring above 40% inhibition were considered to be hits , giving an overall hit rate of 0 . 8% and 0 . 4% , respectively , with 0 . 1% of the compounds being classified as hits against both NMTs . Since the Pfizer file consists of discrete clusters of compounds , either from parallel synthesis libraries or medicinal chemistry series , we used this series of origin definition , rather than a clustering algorithm , to label the series . Encouragingly , hit series tended to inhibit one of the target NMTs selectively . All hits were progressed to dose-response assays using a top concentration of 80 µM . Hits were classified as confirmed if they gave a measured IC50 of <5 µM against either enzyme . They were further sub-divided into selective inhibitors of either NMT or both enzymes ( Figure 4 ) . The activities of the most potent example from selected , novel series of NMT inhibitors is summarised in Table 1 ( see Figure 5 for structures of the hit molecules ) . Several other series identified in the primary screen were discarded due to low potency , lack of selectivity or due to on-going interest for other Pfizer programs . As our initial high-throughput screen sampled only around 5% of the Pfizer screening collection , we sought to expand our hit identification through further analogue screening . Several approaches were employed including substructure searching , similarity searching and by the creation of Bayesian activity models based on the primary screening data [43] . However , the most successful tool used local hit rates to identify hit rich series ( Table 1 ) [44] . In two series , we were able to identify more potent hits from further screening ( compounds in Table 1 without local hit rate value ) . Further series with low local hit rate values tended to be weakly active on repeat testing . When selecting series for further follow-up , we focused on compounds with selective activity against either NMT and with a ligand efficiency ( LE ) of greater than 0 . 30 [45]–[47] . Unlike gene families such as GPCR antagonists or kinase inhibitors , we had insufficient data on transferase enzymes to guide our expectations for the level of LE that might be attained in a drug candidate . However , the level we achieved is consistent with those achieved by peptidomimetic protease inhibitors . Consequently , we believe that all of the series exemplified have sufficiently high ligand efficiency to warrant further development as lead compounds . 2066 compounds were selected for wider profiling against a panel of NMT orthologues , based on either activity in the primary screen or chemical similarity , to generate a pharmacological profile of each NMT in the study , relative to each other . The compound set included three biotin derivatives , which were known to be false positives in this assay format and were shown to have equivalent activity against each NMT orthologue , thus acting as additional positive controls . Two key findings emerged from this study . Firstly , we found that the vast majority of the Pfal NMT hit series were equipotent against both human NMTs ( Figure 6 data shown for Hs1 ) . Only two series ( azetidinopyrimidines and aminomethylindazoles ) showed a divergent SAR for Plasmodium vs . human NMTs ( see Table 2 for data on representative compounds ) , and in the case of the azetidinopyrimidine series , selectivity was only observed in some derivatives . Secondly , and in contrast to the Pfal findings , there was no correlation between activity against Ldon NMT and human NMTs ( Figure 7 for Hs1 ) . In addition , the Leishmania NMT hits were selective over both other protozoan NMTs ( Table 2 ) . Our study also provided an insight into the selectivity profiles between human NMTs and Tb NMT ( Figures S1 and S2 ) .
We have exploited knowledge of the essential function of NMT in protozoa , and harnessed the strength of the Pfizer compound collection , to initiate a drug discovery program for this target in Plasmodium and Leishmania . 150 , 000 compounds were screened against Pfal and Ldon NMTs . Based on initial modelling studies and sequence alignments , we opted to assess the quality of the hits through selectivity assays against both Hs NMT isoforms and against Tb NMT , to assess their potential to deliver broad-spectrum anti-protozoan NMT activity . Our results suggest that this objective is unlikely to be successful since we found that selectivity between the protozoan NMTs is readily achievable but that most Pfal NMT inhibitors are equipotent against the human isoforms . These results suggest that Pfal/human NMT selectivity might be a barrier to drug discovery for this target , unless inhibition of mammalian NMTs is shown to have no toxicological effects . However , we discovered two novel series with sufficient selectivity to encourage further medicinal chemistry follow-up . These findings suggest that some compound series are binding in regions that differ between Pfal and human NMTs . If these differences can be rationalised , ideally through obtaining co-crystal structures with Plasmodium NMT , even non-selective hits could be of potential value as starting points for medicinal chemistry programs . Despite a lower initial screening hit rate , we found four series of Ldon NMT inhibitors with good to excellent selectivity over all other NMTs in our panel . While this result was in line with our predictions for human and Pfal NMTs , the separation of Ldon and Tb activity was unexpected . This result contrasts with those previously reported for another series of Tb NMT inhibitors , therefore suggesting that all of the series we have identified bind in a different region of the binding pocket [23] . This observation will be tested through further structural studies with Leishmania NMT . It also appears that Ldon NMT is more susceptible to potent inhibition , perhaps an indication that the peptide-binding site is smaller than for the other NMTs in this study . Based on the results we describe , it is also likely that high throughput screening of the Pfizer file against other NMT orthologues would have yielded further selective series . These results underline the benefit of high-throughput screening of a diverse compound collection to discover novel protozoan NMT inhibitors , as an alternative to a “piggy-backing” approach [19] . This early drug discovery collaboration was facilitated by grants from the Wellcome Trust and MRC , which demonstrates the power of such public private partnerships in bringing together the drug discovery expertise of pharmaceutical companies and the detailed target knowledge from academia to accelerate drug discovery for neglected tropical diseases . Our most promising compounds are disclosed to accelerate the pace of drug development for malaria and leishmaniasis . These hits represent excellent starting points for a future medicinal chemistry program , although they have yet to be tested in whole cell assays against their target organisms . Our future work on Pfal and Ldon NMTs will focus on the translation of enzyme inhibition into functional activity .
|
Inhibition of N-myristoyltransferase has been validated pre-clinically as a target for the treatment of fungal and trypanosome infections , using species-specific inhibitors . In order to identify inhibitors of protozoan NMTs , we chose to screen a diverse subset of the Pfizer corporate collection against Plasmodium falciparum and Leishmania donovani NMTs . Primary screening hits against either enzyme were tested for selectivity over both human NMT isoforms ( HsNMT1 and HsNMT2 ) and for broad-spectrum anti-protozoan activity against the NMT from Trypanosoma brucei . We have identified eight series of protozoan NMT inhibitors , six having good selectivity for either Plasmodium or Leishmania NMTs over the other orthologues in this study . We believe that all of these series could form the basis of medicinal chemistry programs to deliver drug candidates against either malaria or leishmaniasis . Our screening initiative is another example of how a tripartite partnership involving pharmaceutical industries , academic institutions and governmental/non-governmental organisations such as the UK Medical Research Council and Wellcome Trust can stimulate research for neglected diseases .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicinal",
"chemistry",
"emerging",
"infectious",
"diseases",
"chemistry",
"biology",
"microbiology",
"parasitology",
"parasite",
"physiology"
] |
2012
|
Selective Inhibitors of Protozoan Protein N-myristoyltransferases as Starting Points for Tropical Disease Medicinal Chemistry Programs
|
Genotype III ( GIII ) Japanese encephalitis virus ( JEV ) predominance has gradually been replaced by genotype I ( GI ) over the last 20 years in many Asian countries . This genotype shift raises concerns about the protective efficacy of Japanese encephalitis ( JE ) vaccines , as all of the currently licensed JE vaccines are derived from GIII strains . In this study , we conducted vaccination-challenge protection assays to evaluate the cross-protective efficacy of GI- or GIII-derived vaccines against the challenge of a heterologous genotype using a mouse challenge model . Titration of the neutralizing antibodies elicited by SA14-14-2 live-attenuated JE vaccine ( SA14-14-2 vaccine ) , a GIII-derived vaccine , indicated that the titer of neutralizing antibodies specific to heterologous genotype GI stain was significantly lower than that specific to homologous genotype GIII strain in both pigs and mice immunized with the SA14-14-2 vaccine . Vaccination of mice with SA14-14-2 vaccine or a GIII-inactivated vaccine at high and medium doses completely protected vaccinated mice against challenge with the homologous genotype GIII strains , but failed to provide the vaccinated mice complete protection against the challenge of heterologous genotype GI strains . The protection rates against GI strain challenge were 60%–80% , showing that these vaccines were partially protective against GI strain challenge . Additionally , vaccination of mice with a GI-inactivated vaccine conferred 100% protection against the challenge of homologous genotype GI strains , but 50%–90% protection against the challenge of heterologous genotype GIII strains , showing a reduced protective efficacy of a GI-derived vaccine against GIII strain challenge . Overall , these observations demonstrated a partial cross-protection between GI and GIII strains and suggested a potential need for new JE vaccine strategies , including options like a bivalent vaccine , to control both genotype infection .
Japanese encephalitis virus ( JEV ) is the causative agent of Japanese encephalitis ( JE ) which is prevalent in ~25 Asia-Pacific countries , with the estimated number of human cases ranging from 50 , 000 to 175 , 000 each year [1] . Globally , approximately 75% of human cases happen in children and adolescents , making JE the leading cause of viral childhood encephalitis in Asia [2] . In addition to humans , pigs and horses are susceptible to JEV infection . Infection with JEV causes abortion in pregnant sows and encephalitis in piglets and horses [3] , which results in JEV being a significant public health and economic risk . JEV is a mosquito-borne flavivirus with a single-stranded positive-sense RNA genome that encodes three structural and seven nonstructural proteins . Although JEV exists as a single serotype , it is phylogenetically classified into five genotypes ( genotype I to V ) based on the nucleotide sequence of the viral envelope ( E ) protein [4 , 5] . JEV genotype III ( GIII ) was the historically dominant genotype throughout most of Asia but has been gradually replaced by genotype I ( GI ) over the last 20 years in many Asian countries . Surveillance studies have been able to demonstrate this genotype shift [6 , 7] . Although GI has replaced GIII as the dominant genotype , co-circulation of GI and GIII viruses is present in many Asian countries [8–10] . Vaccination is the most effective way to control JE in both humans and pigs [3 , 11] . However , all currently licensed JE vaccines including the widely used SA14-14-2 live-attenuated JE vaccine ( SA14-14-2 vaccine ) that is one of JE vaccines recommended by the World Health Organization are derived from GIII strains [12] . The emergence of the GI strain as the dominant genotype has raised concerns about the effectiveness of GIII-derived vaccines against the GI strain infection [13] . JEV E protein is the major structural protein containing the receptor-binding domain and the neutralization epitopes . This protein plays major roles in determination of antigenicity and elicitation of neutralizing antibodies [14 , 15] . Mutations in the E protein influence cell tropism , virulence , and antigenicity of JEV [15–17] . Amino acid variations in the E protein have been reported between GI and GIII strains [10 , 18 , 19] , showing an antigenic difference between the two genotypes [20] . Reduced levels of neutralizing antibodies against GI strains have been observed in both humans and pigs vaccinated with GIII-derived vaccines [18 , 21] . In addition , GI viruses have been isolated from JE patients vaccinated with the SA14-14-2 vaccine [19 , 22] . These previous observations imply a reduced protective efficacy of GIII-derived vaccines against GI strain infection . In this study , we conducted vaccination-challenge protection assays using a mouse challenge model to evaluate the cross-protective efficacy of GI- and GIII-derived vaccines against heterologous genotype infection .
All animal experiments were approved by the Institutional Animal Care and Use Committee of Shanghai Veterinary Research Institute , China ( IACUC No: Shvri-mo-2017091601 ) and performed in compliance with the Guidelines on the Humane Treatment of Laboratory Animals ( Ministry of Science and Technology of the People’s Republic of China , Policy No . 2006 398 ) . JEV strains including two GI strains ( SD12 and SH7 ) , four GIII strains ( N28 , SH1 , SH15 and SH19 ) [23] and the SA14-14-2 vaccine strain ( GenBank No . AF315119 ) were used in this study . All JEV strains were grown and tittered on newborn hamster kidney cells ( BHK-21 ) , which were maintained in Dulbecco’s modified Eagle’s medium ( DMEM; Thermo Fisher Scientific , Carlsbad , CA , USA ) supplemented with 10% fetal bovine serum ( FBS ) at 37°C in an atmosphere containing 5% CO2 . After inoculation with JEV , BHK-21 were cultured in DMEM supplemented with 2% FBS at 37°C . 50% lethal dose ( LD50 ) of each JEV strain was tested on three-week-old C57BL/6 strain mice by intraperitoneal inoculation of serially diluted JEV ( S1 Table ) . Amino acid sequences of JEV strains were obtained from GenBank ( S1 Table ) . Multiple sequence alignments on amino acid sequence of JEV E protein were performed using the DNASTAR Lasergene 7 . 1 ( MegAlign ) . JEV was inactivated with binary ethylenimine ( BEI ) as described previously [24 , 25] . Briefly , GI SD12 strain ( SD12 ( GI ) ) and GIII N28 strain ( N28 ( GIII ) ) were cultured in BHK-21 cells and harvested at 3 days post-inoculation with 80% cytopathogenic effect . Following three cycles of freeze-thaw , the supernatants were collected by centrifugation and tittered on BHK-21 cells . The tittered viral supernatants were treated with BEI at final concentration of 0 . 1 mM for 10 h at 37°C and the inactivation was stopped with 2 mM sodium thiosulfate . Inactivation was verified by inoculation of the BEI-inactivated viruses on BHK-21 cells for 7 days . The inactivated virus was emulsified with an equal volume of ISA206 adjuvant ( Seppic , Paris , France ) . One dose of the inactivated vaccine contained a viral titer of 105 plaque-forming units ( PFU; 0 . 3 ml/each ) . Four-week-old C57BL/6 strain mice purchased from the Shanghai SLAC Laboratory Animal Co . LTD were randomly divided into the vaccinated and control groups ( n = 10 mice/group ) . Vaccination and challenge were performed as previously described [26] . For vaccination with the SA14-14-2 vaccine , mice were intraperitoneally injected with SA14-14-2 vaccine ( Lot . 201706116 , Wuhan Keqian Biology , Wuhan , China ) at a dose of 5000 , 500 , or 50 PFU per animal and challenged intraperitoneally with a dose of 20 LD50 of JEV at 14 days post-vaccination . For vaccination with the inactivated JE vaccine , mice were intraperitoneally injected with N28 ( GIII ) - or SD21 ( GI ) -inactivated vaccine at a dose of 105 , 104 , or 103 PFU per animal and boosted with the same dose at 14 days post-primary vaccination . The mice were challenged intraperitoneally with a dose of 20 LD50 of JEV at 14 days post-vaccine boost . The challenged mice were monitored daily for 20 days and the mortality rates were calculated accordingly . Six-month-old clinically healthy and JEV antibody negative crossbred pigs ( n = 40 ) were intramuscularly immunized with SA14-14-2 vaccine at a dose of 105 PFU per animal . Serum samples from each animal was collected at 30 days post-vaccination for detection and titration of neutralizing antibodies . Four-week-old C57BL/6 strain mice ( n = 10 ) were intramuscularly injected with the SA14-14-2 vaccine at a dose of 105 PFU per animal and serum samples were collected at 14 days post-vaccination for detection of neutralizing antibody titers . Neutralizing antibodies in serum samples collected from vaccinated animals were tittered using the plaque reduction neutralization test ( PRNT ) , as described previously [18] . Briefly , serum samples were inactivated in a water-bath for 30 min at 56°C and serially diluted two-fold . The diluted serum samples ( 0 . 1 ml ) were mixed with an equal volume of JEV at a concentration of 200 PFU/0 . 1 ml and incubated for 1 h at 37°C . The mixture was subsequently dispensed onto BHK-21 cells grown in 6-well plates and incubated for 2 h at 37°C . After 2 h adsorption , the cells were overlaid with 1 . 2% methylcellulose ( Thermo Fisher Scientific ) in DMEM containing 2% FBS and incubated for 3−5 days at 37°C . The plaques were stained with crystal violet and counted . Neutralizing antibody ( PRNT50 ) titers were calculated as the reciprocal of the highest dilution that reduced the plaque numbers by at least 50% relative to the virus control . The PRNT90 titers that reduced the plaque numbers by at least 90% relative to the virus control were also calculated . The positive cut-off value of neutralizing antibody titers was defined as PRNT50 ≥ 10 . PRNT50 titers below the positive cut-off value of 10 were given an arbitrary value of 5 for the calculation of the geometric mean titer ( GMT ) [18] . All data were processed using GraphPad Prism 7 . 0 ( GraphPad , La Jolla , CA , USA ) . Fisher’s exact test or Student’s t-tests were used for statistical analyses . A p value < 0 . 05 was considered statistically significant .
We compared the amino acid differences of the E protein among GI and GIII strains used in this study . A total of nine amino acid variations were detected in the E protein between the strains , of which four , highlighted in red , were conserved between the GI and GIII strains including the SA14-14-2 vaccine strain . The varied residues of T129M and A222S are located in domain II ( DII ) , and S327T and A366S are present in domain III ( DIII ) of the E protein ( Table 1 ) . DIII plays a crucial role in elicitation of neutralizing antibodies [14] , therefore the variations of S327T and A366S present in DIII may alter the cross-protection of the SA14-14-2 vaccine against GI strain infection . Given the amino acid variations in the E protein between GI and GIII strains ( Table 1 ) , we measured the neutralizing antibody titers elicited by the SA14-14-2 vaccine against the heterologous genotype SD12 ( GI ) strain . Serum samples were collected from pigs ( n = 40 ) vaccinated with SA14-14-2 vaccine and the neutralizing antibody titers ( PRNT50 ) specific to the homologous SA14-14-2 , homologous genotype N28 ( GIII ) and heterologous genotype SD12 ( GI ) strains were measured , respectively . The seropositive rate , as defined by PRNT50 ≥10 , against the homologous SA14-14-2 strain was 100% ( 40/40 ) , showing a similar trend to that ( 87 . 5% , 35/40 ) of the homologous genotype N28 ( GIII ) strain . However , the seropositive rate against the heterologous genotype SD12 ( GI ) strain was 47 . 5% ( 19/40 ) which was significantly lower than those of the homologous SA14-14-2 ( p<0 . 0001 ) and homologous genotype N28 ( GIII ) ( p = 0 . 0003 ) strains ( Fig 1A ) . The PRNT50 titer against the homologous SA14-14-2 strain was 38 . 0 , which was close to that ( 23 . 5 ) of the antibody specificity to the homologous genotype N28 ( GIII ) strain , but significantly higher than the antibody specificity ( 8 . 8 ) for the heterologous genotype SD12 ( GI ) strain ( Fig 1B ) . The serum samples were stratified into different groups of PRNT50 titer 10 , 20 , 40 , 80 , 160 and ≥ 320 specific to the homologous SA14-14-2 strain , as described previously [18] . The GMT of the specific PRNT50 titers to the homologous genotype N28 ( GIII ) strain and the heterologous genotype SD12 ( GI ) strain were calculated for each group . The cross-protective threshold ( PRNT50 = 10 ) to the homologous genotype N28 ( GIII ) strain and the heterologous genotype SD12 ( GI ) strain was approximately equivalent to the PRNT50 titer of 10 and 40 against the homologous SA14-14-2 strain , respectively ( Table 2 ) . These data indicated a low presumptive protective titer of neutralizing antibodies against the heterologous genotype SD12 ( GI ) strain in pigs vaccinated with the SA14-14-2 vaccine . To confirm this observation , mice ( n = 10 ) were vaccinated with the SA14-14-2 vaccine and the neutralizing antibody titers against the homologous SA14-14-2 , homologous genotype N28 ( GIII ) and heterologous genotype SD12 ( GI ) strains were measured . Serum samples collected from pre-vaccinated mice showed a background level of PRNT50 titers to almost of JEV strains , with one exception that showed the PRNT50 titer of 10 ( Fig 1C ) . In response to vaccination , the PRNT50 titer against the homologous SA14-14-2 strain reached 40 . 6 above the background . The PRNT50 titer specific to the homologous genotype N28 ( GIII ) strain was 25 . 2 which was lower than that produced against the SA14-14-2 strain , but higher than that ( 9 . 8 ) against the heterologous genotype SD12 ( GI ) strain ( Fig 1D ) . The seropositive rate against the homologous SA14-14-2 strain was 100% ( 10/10 ) , showing a similar trend to that ( 90% , 9/10 ) of the homologous genotype N28 ( GIII ) strain . However , the seropositive rate against the heterologous genotype SD12 ( GI ) strain was only 20% ( 2/10 ) which was significantly lower than the vaccine strain ( p = 0 . 0007 ) or the homologous genotype N28 ( GIII ) ( p = 0 . 0055 ) strain ( Fig 1E ) . Additionally , PRNT90 assay was used to detect neutralizing antibodies against the homologous and heterologous genotype strains . A reduced neutralizing antibody titer against the heterologous genotype was also observed ( S1 Fig ) . Taken together these data support the hypothesis of reduced neutralizing antibody response against the heterologous genotype following vaccination . Given the low PRNT50 titers of neutralizing antibodies specific to the heterologous genotype SD12 ( GI ) strain in animals vaccinated with SA14-14-2 vaccine , we tested the protective efficacy of SA14-14-2 vaccine against SD12 ( GI ) strain challenge . Pigs excluding pregnant sows are generally subclinical after JEV infection [27] . We therefore used mice that are susceptible to JEV infection to evaluate the protective efficacy of the SA14-14-2 vaccine against SD12 ( GI ) strain challenge . Mice were vaccinated with the SA14-14-2 vaccine at high ( 5000 PFU ) , medium ( 500 PFU ) or low ( 50 PFU ) doses , respectively , and challenged with the homologous genotype N28 ( GIII ) strain and the heterologous genotype SD12 ( GI ) strain . The SA14-14-2 vaccine completely protected vaccinated mice at the high and medium doses , but not at the low dose ( percent survival = 60% ) , against challenge with the homologous genotype N28 ( GIII ) strain ( Fig 2 ) . However , the vaccine failed to provide vaccinated mice complete protection against challenge with the heterologous genotype SD12 ( GI ) strain . The protection rates against SD12 ( GI ) strain challenge were 80% ( Fig 2A ) , 60% ( Fig 2B ) , and 40% ( Fig 2C ) in the groups vaccinated with high , medium and low doses , respectively . These data indicated a partial protective efficacy of the SA14-14-2 vaccine against the heterologous genotype SD12 ( GI ) strain . To confirm the reduced protective efficacy of the GIII-derived vaccine against GI viral infection , mice were immunized with N28 ( GIII ) -inactivated vaccine at high ( 105 PFU ) , medium ( 104 PFU ) , or low ( 103 PFU ) doses and challenged with the homologous N28 ( GIII ) and heterologous genotype SD12 ( GI ) strains , respectively . N28 ( GIII ) -inactivated vaccine protected the vaccinated mice completely at high , medium and low doses against the homologous N28 ( GIII ) strain ( Fig 3A , 3B and 3C ) . However , the protection rates against the heterologous genotype SD12 ( GI ) strain challenge were 80% ( Fig 3A ) , 80% ( Fig 3B ) and 40% ( Fig 3C ) in the groups vaccinated with high , medium and low doses , respectively . This suggested a reduced protective efficacy against the heterologous genotype SD12 ( GI ) strain . The protective efficacy of the N28 ( GIII ) -inactivated vaccine were further examined at a medium dose against other homologous genotype viruses including SH1 ( GIII ) , SH15 ( GIII ) and SH19 ( GIII ) strains , and the heterologous genotype SH7 ( GI ) strain . N28 ( GIII ) -inactivated vaccine protected the vaccinated mice completely against the challenges of the homologous genotype SH1 ( GIII ) , SH15 ( GIII ) and SH19 ( GIII ) strains , but not against the challenge of the heterologous genotype SH7 ( GI ) strain ( Fig 3D ) . The protection rate was 70% in the group challenged with SH7 ( GI ) strain . Taken together , these data support the finding of reduced protective efficacy of N28 ( GIII ) -inactivated vaccines against heterologous genotype GI strains . Given the emergence of the GI virus as the dominant genotype in Asian regions and the partial cross-protection efficacy of GIII-derived vaccines against GI viral infection , development of a GI-derived vaccine has been proposed to control GI viral infection [25 , 28 , 29] . We therefore examined the protective efficacy of a GI-derived vaccine against the challenge of GI and GIII viruses . Mice were vaccinated with SD12 ( GI ) -inactivated vaccine at high ( 105 PFU ) , medium ( 104 PFU ) , or low ( 103 PFU ) doses and challenged with the homologous SD12 ( GI ) and heterologous genotype N28 ( GIII ) strains , respectively . SD12 ( GI ) -inactivated vaccine protected the vaccinated mice completely against the homologous SD12 ( GI ) strain , but not against the heterologous genotype N28 ( GIII ) strain ( Fig 4 ) . The protection rates against N28 ( GIII ) strain challenge were 90% ( Fig 4A ) , 80% ( Fig 4B ) and 50% ( Fig 4C ) in the groups vaccinated with high , medium and low doses , respectively , suggesting a reduced protective efficacy against the heterologous genotype N28 ( GIII ) strain . The protective efficacy of SD12 ( GI ) -inactivated vaccine were further examined at a medium dose against another homologous genotype strain SH7 ( GI ) and heterologous genotype viruses including SH1 ( GIII ) , SH15 ( GIII ) and SH19 ( GIII ) strains . SD12 ( GI ) -inactivated vaccine protected the vaccinated mice completely against the homologous genotype SH7 ( GI ) strain , but not against the challenge of heterologous genotype SH1 ( GIII ) , SH15 ( GIII ) and SH19 ( GIII ) strains ( Fig 4D ) . The protection rate was 80% , 80% and 70% in the group challenged with SH1 ( GIII ) , SH15 ( GIII ) and SH19 ( GIII ) , respectively . Taken together , these data indicated the reduced protective efficacy of SD12 ( GI ) -inactivated vaccine against the heterologous genotype GIII strains .
The emergence of GI JEV as the dominant genotype in Asian regions [6 , 7] has raised concerns about the efficacy of GIII-derived vaccines against GI viral infection [13] . The goal of this study was to examine the cross-protection between GI and GIII viruses to estimate the potential need for new vaccine strategies for control of both GI and GIII viral infection . Neutralizing antibodies play the most important role in protection of JEV infection and the neutralizing antibody titer correlates with this protection [30 , 31] . We therefore measured the neutralizing antibody titers in pigs and mice vaccinated with the SA14-14-2 vaccine and observed that the neutralizing antibody titers specific to the heterologous genotype SD12 ( GI ) strain were significantly lower than those specific to the homologous SA14-14-2 strain and homologous genotype N28 ( GIII ) strain . These results were consistent with previous observations that the neutralizing antibody titers specific to GI viruses were lower than those specific to GIII viruses in humans and pigs vaccinated with GIII-derived vaccines [18 , 21 , 32–34] . The SA14-14-2 vaccine is currently used for control of JE in both humans and pigs [12] . We therefore evaluated the protective efficacy of the SA14-14-2 vaccine against GI challenge using a mouse challenge model . The SA14-14-2 vaccine provided vaccinated mice with complete protection against the homologous genotype N28 ( GIII ) strain , but not against the heterologous genotype SD12 ( GI ) strain . The protection rates against the heterologous genotype SD12 ( GI ) strain were 60%–80% , suggesting that vaccination was partially protective when using a GIII-derived vaccine . This observation was inconsistent with a previous observation that the SA14-14-2 vaccine affords mice similar protection against both GI and GIII strain challenge [26] , in which KM strain mice immunized with the SA14-14-2 vaccine had an 80%–100% protection rate against the both GI and GIII strains . This apparent discrepancy between our and Liu et al . ’s results may be attributable to differences in the mouse strains used for the JEV challenge . The mouse strain used in Liu et al . ’s study was the KM strain [26] , whereas the mouse strain used in our study was C57BL/6 . We have observed that C57BL/6 strain mice were more sensitive to JEV challenge than KM strain mice . This explanation is also supported by differences in the neutralizing antibody titers . Our and several previous observations demonstrated the reduced neutralizing antibody titers specific to GI viruses in individuals immunized with GIII-derived vaccines [18 , 21 , 34] . However , the reduced neutralizing antibody titers specific to GI viruses were not observed in KM strain mice vaccinated with the SA14-14-2 vaccine in Liu et al . ’s study [26] . In addition , we challenged the vaccinated mice at 14 days post-vaccination and observed the reduced protection against the heterologous genotype strains . The protective efficacy might be changed if the vaccinated mice were challenged at different interval days post-vaccination . The difference in susceptibility to flavivirus infection between C57BL/6 and KM mice has also been observed in infection by Zika virus that is related to JEV in the family Flaviviridae . C57BL/6 mice after Zika virus infection showed higher morbidity ( 100% ) than KM mice ( 62% ) [35] . The specific reasons for the different susceptibility between these two mouse strains are unknown at present , probably attributable to their genetic difference . KM mouse with white coat color is outbred strain originated from the Swiss mice , while C57BL/6 mouse with dark brown coat color is inbred strain derived from the C57BL mice . To confirm the reduced protective efficacy of GIII-derived vaccines against GI viral infection , we immunized mice with N28 ( GIII ) -inactivated vaccine and challenged with the heterologous genotype GI strains . The reason we used the newly-isolated N28 ( GIII ) strain rather than the existing licensed inactivated JE vaccine was that the inactivated GIII Beijing-3 ( P3 ) vaccine available in China is licensed 20 years ago . Several amino acid variations have been observed in E protein between the inactivated Beijing-3 ( P3 ) vaccine and the recently-isolated strains [36] . N28 ( GIII ) -inactivated vaccine provided the vaccinated mice complete protection against the challenge of homologous genotype GIII strains , but not against the challenge of heterologous genotype GI strains , confirming the reduced protective efficacy of GIII-derived vaccines against GI viral infection . These results supported the concern of increased risk of GI infection in populations immunized with GIII-derived vaccines . Indeed , GI virus has been isolated from patient vaccinated with the SA14-14-2 vaccine in China [22] . A similar case was also reported in India [19] . These epidemiological data together with the reduced protective efficacy of GIII-derived vaccines against GI virus infection suggest a potential need for a GI-derived vaccine . In fact , several trials for the development of a GI-derived vaccine have been reported [25 , 28 , 29] . Although GI has replaced GIII as the dominant genotype , the co-circulation of GI and GIII viruses is present in many Asian countries [8–10] . We therefore examined the protective efficacy of a GI-derived vaccine against GIII viral infection . Mice were immunized with SD12 ( GI ) -inactivated vaccine and challenged with heterologous genotype GIII strains . SD12 ( GI ) -inactivated vaccine provided the vaccinated mice complete protection against the challenge of homologous genotype GI strains , but not against the challenge of heterologous genotype GIII strains . This suggests a partial protective efficacy of GI-derived vaccines against GIII viral infection . These results were consistent with a previous observation that GI virus-like particles failed to cross-protect 10% of vaccinated mice against GIII viral challenge [29] . However , swine immunized with these GI virus-like particles showed no fever , viremia or viral RNA in tissues after GI or GIII viral challenge , demonstrating sterile protection against GI and GIII viral infection in swine [29] . Therefore , more detailed studies are needed to evaluate the cross-protective efficacy of GI-derived vaccines against GIII viral infection . In conclusion , the partial cross-protective efficacy of JE vaccines against heterologous genotype JEV challenge was observed using a mouse challenge model . GIII-derived vaccines failed to provide the vaccinated mice complete protection against the challenge of heterologous genotype GI strains . Additionally , vaccination of mice with a GI-inactivated vaccine conferred only partial protection against the challenge of heterologous genotype GIII strains . The partial cross-protection between GI and GIII viruses suggest a potential need for new JE vaccine strategies , including options like a bivalent vaccine , to control both genotype infection . However , the current data obtained from a mouse challenge model cannot be simply extrapolated to the vaccination strategy for humans , more comprehensive studies should be conducted to address the partial cross-protective efficacy of JE vaccines against the heterologous genotype using JEV natural hosts .
|
Japanese encephalitis virus ( JEV ) is a mosquito-borne flavivirus that causes Japanese encephalitis ( JE ) in humans and reproductive disorders in pigs . JEV is phylogenetically classified into five genotypes . JEV genotype III ( GIII ) was historically dominant throughout most of Asia , but has been replaced by genotype I ( GI ) over the last 20 years in many Asian countries . Amino acid variations in JEV envelope protein play major roles in determination of antigenicity . Elicitation of cross-neutralizing antibodies for GI and GIII strains has been reported , showing an antigenic difference between the two genotypes . These amino acid differences in JEV envelope proteins raise a concern about the protective efficacy of JE vaccines against the emerged GI strain infection , because all currently licensed JE vaccines are derived from GIII strains . We evaluated the protective efficacy of JE vaccines against the heterologous genotype strain using a mouse challenge model and found a partial cross-protection between GI- or GIII-derived vaccines against the challenge of the heterologous genotype . This partial cross-protective efficacy suggested a potential need for a new JE vaccine , one solution may be a bivalent vaccine , to control infection with either genotype . However , more comprehensive studies should be conducted to address the partial cross-protective efficacy of JE vaccines against the heterologous genotype strains using JEV natural hosts such as pigs .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"urology",
"viral",
"vaccines",
"medicine",
"and",
"health",
"sciences",
"immune",
"physiology",
"viral",
"transmission",
"and",
"infection",
"immunology",
"geographical",
"locations",
"microbiology",
"vertebrates",
"animals",
"mammals",
"vaccines",
"preventive",
"medicine",
"infectious",
"disease",
"control",
"antibodies",
"vaccination",
"and",
"immunization",
"public",
"and",
"occupational",
"health",
"immune",
"system",
"proteins",
"infectious",
"diseases",
"swine",
"proteins",
"people",
"and",
"places",
"biochemistry",
"eukaryota",
"asia",
"virology",
"genitourinary",
"infections",
"physiology",
"biology",
"and",
"life",
"sciences",
"amniotes",
"organisms"
] |
2019
|
Partial cross-protection between Japanese encephalitis virus genotype I and III in mice
|
Studies of the immunogenicity of the killed bivalent whole cell oral cholera vaccine , Shanchol , have been performed in historically cholera-endemic areas of Asia . There is a need to assess the immunogenicity of the vaccine in Haiti and other populations without historical exposure to Vibrio cholerae . We measured immune responses after administration of Shanchol , in 25 adults , 51 older children ( 6–17 years ) , and 47 younger children ( 1–5 years ) in Haiti , where cholera was introduced in 2010 . A≥4-fold increase in vibriocidal antibody titer against V . cholerae O1 Ogawa was observed in 91% of adults , 74% of older children , and 73% of younger children after two doses of Shanchol; similar responses were observed against the Inaba serotype . A≥2-fold increase in serum O-antigen specific polysaccharide IgA antibody levels against V . cholerae O1 Ogawa was observed in 59% of adults , 45% of older children , and 61% of younger children; similar responses were observed against the Inaba serotype . We compared immune responses in Haitian individuals with age- and blood group-matched individuals from Bangladesh , a historically cholera-endemic area . The geometric mean vibriocidal titers after the first dose of vaccine were lower in Haitian than in Bangladeshi vaccinees . However , the mean vibriocidal titers did not differ between the two groups after the second dose of the vaccine . A killed bivalent whole cell oral cholera vaccine , Shanchol , is highly immunogenic in Haitian adults and children . A two-dose regimen may be important in Haiti , and other populations lacking previous repeated exposures to V . cholerae .
Cholera remains a public health problem for many of the world's poorest individuals . Approximately 3 million cases of diarrheal illness and 120 , 000 deaths are caused by V . cholerae annually [1] . Devastating epidemics occur when V . cholerae is introduced into an immunologically naive population that lacks access to safe water and sanitation . This occurred when a pandemic V . cholerae O1 strain was introduced into Haiti in 2010 [2] , [3] , resulting in 693 , 088 cases and 8474 reported deaths as of November 27 , 2013 [4] . The increasing burden of endemic and epidemic cholera has led to recognition that new approaches to the control of cholera , including vaccination , are urgently needed [5] , [6] . There are two currently licensed cholera vaccines . Both are oral killed whole cell vaccines that have demonstrated efficacy in preventing cholera in endemic settings . Dukoral ( Crucell ) is a whole cell recombinant cholera toxin B subunit vaccine ( WC-rBS ) which contains both the Inaba and Ogawa serotypes of V . cholerae O1 , and recombinant cholera toxin B subunit ( CTB ) . Shanchol ( Shantha Biotechnics ) is a bivalent whole cell vaccine which contains V . cholerae serogroups O1 and O139 , but lacks CTB . Shanchol is less expensive than Dukoral and may be associated with longer lasting protection [7]–[10] . The World Health Organization ( WHO ) recommends that cholera vaccines be used in cholera-endemic settings [11] . However , the use of vaccination during epidemics remains controversial , and in 2010 the WHO position paper on cholera vaccination encouraged studies of the feasibility and impact of vaccination in the setting of ongoing outbreaks of cholera [11] . Recent pilot vaccination campaigns in Haiti , South Sudan , and Guinea have demonstrated the feasibility of reactive and/or preventive cholera vaccination [12]–[14] . In a pilot vaccination campaign in rural Haiti , Shanchol was distributed to 45 , 417 individuals in conjunction with health education messages regarding household water safety and sanitation . Despite logistical challenges in this setting , a vaccination coverage rate in excess of 75% was achieved [12] , exceeding the 50% threshold associated with high levels of herd immunity [15] . Notably , 91% of vaccine recipients in the pilot campaign in Haiti received the recommended two doses of the vaccine [12] . While the immunogenicity of Shanchol has been demonstrated in South Asia [8] , [16] , no studies of the immunogenicity of this vaccine have yet been reported outside of historically cholera-endemic areas . Prior experience suggests that immunogenicity and efficacy of cholera vaccines in populations from historically cholera-endemic areas of Asia may not be extrapolated to populations from other geographic regions . For instance , a study conducted in Peru shortly after the introduction of V . cholerae in 1991 demonstrated that a third dose of the WC-rBS vaccine was required to provide a high rate of seroconversion and boost protective efficacy from 0% to 61% [17] . In contrast , a two-dose regimen of a similar vaccine was associated with 86% protection in Bangladesh [18] . In this study , we address a knowledge gap regarding the use of Shanchol in epidemic settings . To assess the immunogenicity of this vaccine in Haiti , we measured vibriocidal antibody responses , the best characterized immunologic correlate of protection against cholera [19] , [20] . We also assessed IgA responses to the O-antigen specific polysaccharide ( OSP ) , the primary determinant of lipopolysaccharide antigen specificity [21] . We included young children in our analysis , since they are disproportionately affected by cholera [22] and may mount less robust immune responses to cholera vaccination [7] , [23] , [24] . We also included a comparison of immune responses of Haitian vaccinees to Bangladeshi vaccinees to assess whether immune responses to Shanchol would differ in individuals from a historically cholera-endemic area compared to an area where cholera has recently been introduced .
Subjects were enrolled in St . Marc , Haiti , in April 2013 . Subjects 1 year of age and older were eligible to participate . Exclusion criteria included pregnancy , acute medical illness , prior receipt of oral cholera vaccine , or a history of hospitalization for cholera . We also analyzed plasma samples obtained from Bangladeshi individuals who participated in a previously conducted study of the immunogenicity of Shanchol in Bangladesh [16] . The Bangladeshi individuals whose samples were utilized were selected at random from a larger cohort of vaccinees and then age-matched to Haitian vaccinees to within 1 year for young children and within 5 year for adults and blood-group matched for either O or non-O blood groups . The studies were approved by the institutional review board of Partners HealthCare ( Brigham and Women's Hospital and Massachusetts General Hospital ) , the Haitian National Ethics Committee , and the Ethical Review Committee of the International Centre for Diarrhoeal Disease Research in Dhaka , Bangladesh ( icddr , b ) . Written informed consent was obtained from adult participants and from guardians of children . Participants were administered two doses of Shanchol , given 14 days apart . Participants were monitored for 30 minutes after vaccination and were asked to return to the study site or to contact a study coordinator if they felt ill after receipt of the vaccine . Adverse events were evaluated and recorded by study physicians . Venous blood samples were obtained immediately prior to immunization ( day 0 ) and seven days after each dose of vaccination ( day 7 and day 21 ) . Serum was stored at −80°C , and shipped to Massachusetts General Hospital . To avoid any laboratory-related biases , plasma from Bangladesh from a previously conducted study of the immunogenicity of Shanchol vaccine was stored , shipped , and analyzed at Massachusetts General Hospital concurrently with the Haitian samples [16] . Vibriocidal antibody assays were performed as described previously [16] , [25] . Target strains of V . cholerae O1 Inaba ( T19479 ) and Ogawa ( X25049 ) , were incubated with heat inactivated serum and exogenous guinea pig complement . Vibriocidal titers were defined as the reciprocal of the highest serum dilution resulting in a 50% reduction in optical density ( 595 nm ) compared to controls without serum . To account for inter-assay variation , results were normalized using high titer sera . Seroconversion was defined as a 4-fold or greater increase from the baseline vibriocidal titer after vaccination . CTB and OSP responses were measured using a previously described ELISA [23] , [26] . OSP plates were coated with 1 µg of conjugated OSP:BSA per milliliter of carbonate buffer ( pH 9 . 6 ) . CTB plates were coated with GM1 ganglioside followed by recombinant CTB ( 2 . 5 µg/ml ) . Sera ( diluted 1∶25 for OSP , 1∶50 for CTB ) was added to plates , and IgA responses were detected with goat anti-human IgA conjugated with horseradish peroxidase ( Jackson ImmunoResearch ) . A 2-fold or greater rise in milliabsorbance units per second at day 7 or day 21 compared to day 0 was considered a significant response . Because Shanchol does not contain CTB , these responses were assessed to ensure that vibriocidal and OSP responses were not due to either intercurrent natural V . cholerae infection or non-specific immune activation . Statistical analyses were performed using STATA Version 9 . Antibody titers were log2 transformed , and the log-transformed data were used for statistical analyses . The immunologic results were expressed as geometric means ( GMT ) and compared by a paired t-test for within group comparison and by the Kruskal-Wallis analysis of variance ( ANOVA ) and/or Student's t-test for between group comparisons as indicated . Analysis of proportions was performed using chi-square or the Fisher exact test as appropriate . For the matched comparison between the Haitian and Bangladeshi cohorts , subjects were matched by age ( within one year for all children , and within 5 years for adults ) and blood group; the differences between GMT were assessed using a paired t-test . The threshold for statistical significance was a two-tailed p value of <0 . 05 .
The study cohort consisted of 123 Haitian participants ( Table 1 ) , of whom 25 were adults ( ≥18 years ) , 51 were older children ( 6–17 years ) , and 47 were younger children ( 1–5 years ) . A flowchart of participants through the study is provided in Figure 1 . Of the 123 participants , 115 ( 93% ) received both doses of the vaccine . No adverse events related to vaccination were reported among participants . Figure 2 shows the vibriocidal antibody responses . The baseline GMT to V . cholerae O1 Ogawa was 14 , 21 , and 14 for adults , older children , and young children , respectively; and for Inaba the baseline GMT was 11 , 27 , and 16 for each age cohort . There was a statistically significant difference in baseline GMT between adults and older children ( p = 0 . 02 ) to V . cholerae O1 Inaba , but there was no difference in baseline GMT among age cohorts for Ogawa . Overall , 34% of participants had a baseline vibriocidal titer ≥80 to Ogawa and/or Inaba; 14% of participants had a GMT ≥320 and 7% of participants had a GMT ≥640 . This suggests that many individuals had been recently exposed to V . cholerae . However , the proportion of individuals with a baseline vibriocidal titer ≥80 did not differ significantly between age cohorts . Each of the age cohorts had a robust vibriocidal antibody response by day 7 , after a single dose of Shanchol ( p<0 . 0001 for all cohorts ) with a geometric mean fold rise ( GMF ) of 11 , 9 , and 11 in adults , older children , and young children to V . cholerae O1 Ogawa , and 19 , 11 , and 9 to Inaba . Vibriocidal GMTs increased further in each of the age cohorts after the second dose of the vaccine . Although these increases between day 7 and day 21 were not statistically , significant , the GMT at day 21 was significantly increased compared to baseline values in all age cohorts ( Ogawa GMF: 13 , 9 , 12 and Inaba GMF: 19 , 10 , 10 for adults , older children , and young children ) ( p<0 . 0001 ) . The majority of adults , older and younger children demonstrated vibriocidal antibody seroconversion against both serotypes ( Table 2 ) . Approximately half of the individuals who failed to seroconvert after vaccination had high baseline titers suggestive of recent exposure . Of the 22 vaccinees who did not seroconvert to Ogawa , 15 ( 68% ) had a baseline vibriocidal titer of ≥80 , and of the 15 vaccinees who did not seroconvert to Inaba , 8 ( 53% ) had a baseline titer ≥80 . Vaccinees across all age groups developed significant OSP-specific IgA serum responses at day 7 and day 21 ( Figure 3 ) . Rates of seroconversion , as defined as a 2-fold rise in antibody level , were comparable across age groups for OSP of Ogawa and Inaba ( Table 2 ) . We also evaluated CTB IgG and IgA serum responses on a subset of patients . As expected , there was no increase in CTB responses after immunization ( data not shown ) . Because children younger than two years have diminished responses to T-cell independent vaccine antigens , we compared children younger than 2 years of age ( N = 8 ) with children between 2 and 5 years ( N = 35 ) . The very young children ( <2 years ) had a lower vibriocidal GMT on day 7 compared to the 2–5 years old children ( Ogawa GMT 40 vs . 177 , p = 0 . 07; Inaba GMT 20 vs 184 , p = 0 . 02 ) . However , after two doses of the vaccine there was no statistically significant difference in the vibriocidal GMT between 1 year olds and 2–5 year olds ( Ogawa GMT 226 vs 183 p = 0 . 76; Inaba GMT 80 vs . 200 p = 0 . 26 ) . Overall , 63 individuals were blood type O ( 51 . 2% ) . Individuals with blood type O had a greater vibriocidal GMT against serotype Inaba after two doses of vaccine compared to study participants with non-O blood types ( GMT = 300 for group O , GMT = 160 for non-O p = 0 . 02 ) , but there was no significant difference in the vibriocidal response to the Ogawa serotype ( Figure 4 ) . There were no significant differences in magnitude in OSP-specific IgA responses between blood groups ( data not shown ) . We compared immune responses in a subset of Haitian vaccinees with age- and blood group-matched vaccinees from Bangladesh ( Figure 5 ) . The cohort from Bangladesh consisted of 17 adults and 20 young children aged 1–5 years . Notably , half of the young children in the matched cohorts were younger than 2 years old , which skewed the pool of young children in the matched analysis toward a younger average age ( 2 . 3 years in the matched cohort , 3 . 1 years in the larger Haitian cohort ) . Even though cholera has been endemic in Bangladesh , and only recently introduced in Haiti , the baseline GMT vibriocidal antibody titers and proportion of individuals with baseline vibriocidal titers ≥80 were comparable between the two matched cohorts . Among the matched cohorts , the adult Bangladeshi vaccine recipients had higher vibriocidal GMT after the first dose of vaccine compared to adult Haitian vaccinees ( Figure 5A and 5B ) . This was statistically significant for the Inaba serotype ( Inaba GMT in Haitians = 153 and Bangladeshis = 351 , p = 0 . 03 ) . However , this difference was diminished and no longer significant after a second dose of the vaccine ( Inaba GMT for Haitians = 153 and Bangladeshis = 243 , p = 0 . 20 ) . The difference between matched cohorts at day 7 was more pronounced for young children ( Figure 5C and 5D ) . The vibriocidal GMT to V . cholerae O1 Ogawa at day 7 was 63 for Haitian young children compared to 443 for Bangladeshi young children ( p = 0 . 002 ) ; and 40 for Haitians and 465 for Bangladeshi to V . cholerae O1 Inaba ( p = 0 . 004 ) . Again , the differences are diminished and no longer statistically significant after a second dose of vaccine ( Ogawa GMT in Haitian young children = 209 and Bangladeshi young children = 303 , p = 0 . 57; Inaba GMT for Haitians = 160 and Bangladeshis = 435 , p = 0 . 31 ) .
To our knowledge , this is the first report of the immunogenicity of the killed bivalent whole cell cholera vaccine , Shanchol , outside of historically cholera-endemic areas of Asia . We found that Shanchol was immunogenic across all age groups in Haiti , from adults to very young children . Given the ongoing transmission of V . cholerae O1 in Haiti , these findings provide additional evidence to suggest that expansion of cholera vaccination programs would aid cholera control efforts in Haiti . The results of this study are notable because V . cholerae was only recently introduced in Haiti . Previous studies of the immunogenicity and efficacy of Shanchol have been conducted in the historically cholera-endemic Ganges delta area of South Asia [7]–[10] , [16] . Because levels of previous or repeated exposures to V . cholerae may dictate the magnitude of vaccine responses , it was unclear whether similar immune responses would be seen in the Haitian population . In addition , recent evidence suggests that genetic factors influencing the innate immune response to V . cholerae may differ in individuals of Bengali ethnic heritage , providing another possible reason for differing immune response to cholera vaccines between different populations [27] . In fact , the results of our direct age- and blood group- matched comparisons suggest the immunogenicity of Shanchol is comparable in Bangladesh and Haiti , at least when administered in a two-dose regimen . Vibriocidal antibody titers are considered an important marker for assessing the immunologic response to cholera vaccines [28] , [29] , and we found the proportion of Haitian vaccinees who demonstrated vibriocidal seroconversion approached or exceeded 75% across all age cohorts . This compares favorably with the seroconversion rates seen in Bangladeshi vaccinees [16] . In addition , the final magnitude of the vibriocidal antibody response after two doses of the vaccine was comparable in Haitian and Bangladeshi individuals . The major difference between the Bangladeshi and Haitian study populations were that immune responses were of a greater magnitude after the first dose of Shanchol among Bangladeshis . We believe this difference is most likely explained by a higher level of immunologic priming from previous or repeated exposure to V . cholerae in the Bangladeshi vaccinees . The observation that baseline vibriocidal titers were similar in both groups seems counter to this hypothesis , but we and others have previously shown that vibriocidal antibodies are a relatively short-term immunologic marker of past-exposure [25] , [30] . Thus it is possible , that longer lasting memory B cell responses following natural V . cholerae infection may mediate anamnestic responses to vaccines in historically cholera-endemic areas . An alternative possibility is that this difference is due to other genetic or environmental differences , though this seems less plausible as the differences are mitigated ( rather than accentuated ) by a second dose of the vaccine . Regardless , our findings suggest that the efficacy of single dose oral cholera vaccine may differ in an epidemic versus a historically cholera-endemic setting . This report also includes the first analysis of O-specific polysaccharide responses to V . cholerae outside of Asia . The vibriocidal response is largely thought to be comprised of IgM targeting V . cholerae lipopolysaccharide ( LPS ) [31] , [32] . Protective immunity against V . cholerae is serogroup-specific , and serogroup specificity is defined by OSP . OSP is a T cell independent antigen , and young children are not typically able to mount immune responses against such antigens . This is unfortunate since , during a cholera epidemic among an immunologically-naïve population , cholera afflicts children and adults equally , and in endemic populations , children bear a large burden of cholera . In our analysis , however , we found that young children were able to mount serum IgA OSP responses that were comparable to those induced in older children and adults . This is in contrast to serum IgA OSP responses observed with administration of Dukoral to children in Bangladesh where only children over the age of 5 had a significant OSP response to Dukoral [23] . This difference may be due to the lower concentration of LPS present in Dukoral compared to Shanchol , or due to the immunodulatory effects of CTB present in Dukoral vaccine [33] . Interestingly , despite the observation that a second dose of Shanchol boosted vibriocidal responses , no additional boosting of OSP serum IgA responses was observed following a second dose in younger and older Haitian children . The significance of these observations is uncertain . The ABO blood group has been implicated in the susceptibility and severity of cholera [34]–[36] , as well as the immunogenicity and efficacy of oral cholera vaccines , with higher responses and efficacy generally seen in the blood group O population which is at greater risk of severe cholera [37] , [38] . Our study also showed increased vibriocidal antibody responses to Shanchol in blood group O individuals , although this was only seen for Inaba serotype after two doses of the vaccine . There are some important limitations of our study . While the vibriocidal antibody response is the historical immunologic benchmark for cholera vaccines [28] , it is at best an indirect marker of protection as the protection afforded by cholera vaccines outlasts a measurable vibriocidal response by several years [39] . Thus , while immunologic results from our study support the expansion of vaccination efforts , epidemiologic data on vaccine efficacy is still important . In addition , our study design was not a placebo-controlled trial of Shanchol since such as design would not be acceptable in an epidemic setting . However , we believe our immunologic results clearly demonstrate vaccine-specific responses , given the rise in both vibriocidal and OSP-IgA antibodies without concurrent reactivity to CTB , which is not present in the Shanchol vaccine . In summary , we demonstrated that Haitian adults and children had robust immune responses to the killed whole cell bivalent oral cholera vaccine Shanchol . This provides evidence that the vaccine is immunogenic even in areas where cholera has recently been introduced , and contributes to the body of evidence favoring the use of oral cholera vaccines as a component of comprehensive cholera control in epidemic settings in immunologically naïve populations .
|
Studies evaluating the ability of the killed bivalent whole cell oral cholera vaccine , Shanchol , to elicit an immune response have been performed in historically cholera-endemic areas of Asia . There is a need to assess whether the vaccine is able to elicit an immune response in Haiti and other populations without historical exposure to cholera . In this study , we measure immune responses after administration of Shanchol , in 25 adults , 51 older children ( 6–17 years ) , and 47 younger children ( 1–5 years ) in Haiti , where cholera was introduced in 2010 . A killed bivalent whole cell oral cholera vaccine ( Shanchol ) is capable of inducing an immune response in adults and children living in Haiti . However , a two-dose regimen may be important in Haiti and other populations lacking historical exposure to cholera .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"global",
"health",
"biology",
"and",
"life",
"sciences",
"immunology"
] |
2014
|
Immunogenicity of a Killed Bivalent (O1 and O139) Whole Cell Oral Cholera Vaccine, Shanchol, in Haiti
|
Humans who experience a primary dengue virus ( DENV ) infection develop antibodies that preferentially neutralize the homologous serotype responsible for infection . Affected individuals also generate cross-reactive antibodies against heterologous DENV serotypes , which are non-neutralizing . Dengue cross-reactive , non-neutralizing antibodies can enhance infection of Fc receptor bearing cells and , potentially , exacerbate disease . The actual binding sites of human antibody on the DENV particle are not well defined . We characterized the specificity and neutralization potency of polyclonal serum antibodies and memory B-cell derived monoclonal antibodies ( hMAbs ) from 2 individuals exposed to primary DENV infections . Most DENV-specific hMAbs were serotype cross-reactive and weakly neutralizing . Moreover , many hMAbs bound to the viral pre-membrane protein and other sites on the virus that were not preserved when the viral envelope protein was produced as a soluble , recombinant antigen ( rE protein ) . Nonetheless , by modifying the screening procedure to detect rare antibodies that bound to rE , we were able to isolate and map human antibodies that strongly neutralized the homologous serotype of DENV . Our MAbs results indicate that , in these two individuals exposed to primary DENV infections , a small fraction of the total antibody response was responsible for virus neutralization .
Dengue virus ( DENV ) complex consists of 4 serotypes . People exposed to primary DENV infections develop robust antibody responses that cross-react with all serotypes ( Reviewed in [1] ) . Despite the extensive cross-reactivity , individuals only develop long term , protective immunity against the homologous serotype responsible for the primary infection [2] , [3] . Indeed , the risk of progressing to DHF is greater during secondary compared to primary infection [4] . A prevailing theory that explains severe dengue during secondary infection is that pre-existing , non-neutralizing dengue specific antibodies enhance DENV entry and replication in Fc-receptor-bearing cells , which leads to a higher viremia and more severe disease [4] . Antibodies have been demonstrated to enhance DENV in cell culture [5] , [6] and in animal models of dengue pathogenesis [7]–[9] . Our current understanding of how antibodies interact with DENV and other flaviviruses is primarily based on studies utilizing mouse monoclonal antibodies ( MAbs ) ( Reviewed in [10] ) . The DENV envelope ( E ) protein is the principle target of neutralizing antibodies . Antibody neutralization occurs by blocking critical functions of the E protein , including attachment to host cells and low pH-dependent fusion of the viral and host cell membranes [11] . The crystal structures of the E protein of several flaviviruses have been solved [12]–[15] . Individual subunits of E protein consist of three beta-barrel domains designated domains I ( EDI ) , II ( EDII ) and III ( EDIII ) , with the native protein forming a head-to-tail homodimer . Mouse MAbs that bind to all three domains of DENV E have been generated and characterized [16]–[23] . Although neutralizing mouse MAbs have been mapped to all three domains of E , the most strongly neutralizing MAbs recognize epitopes on the lateral ridge and A strand of EDIII [24] . Following a primary DENV infection , humans develop antibodies that cross-react with all 4 serotypes , but mainly neutralize the homologous serotype responsible for the infection ( Reviewed in[3] ) . Studies with human immune sera and , more recently , human monoclonal antibodies have demonstrated that the dominant antibody response is cross-reactive and weakly neutralizing [25]–[30] . Multiple viral antigens including E protein , pre-membrane ( prM/M ) protein and non-structural protein 1 ( NSP1 ) are recognized by the human humoral response [25]–[30] . Nonetheless , few studies have defined the actual epitopes of DENV recognized by type-specific and cross-reactive human antibodies at the structural level and compared this to the epitopes defined using mouse antibodies . The target ( s ) of dengue type-specific , strongly neutralizing human antibodies remain unknown . The goal of this study was to study two subjects in-depth to define the major antigens and epitopes recognized by antibodies that develop following primary human DENV infection . Defining the human B-cell epitopes on DENV is a key step towards understanding how antibodies can both enhance and inhibit the severity of DENV infections .
DENV1 WestPac-74 , DENV2 S-16803 , DENV3 CH-53489 , and DENV4 TVP-360 , provided by Dr . Robert Putnak ( Walter Reed Army Institute of Research , Silver Spring , MD ) were used in the present study [29] . Recombinant envelope ( rE ) proteins from the 4 DENV serotypes were kindly provided by Dr . Beth-Ann Coller ( Hawaii Biotech , Inc ) [12] . The recombinant proteins bind to conformational MAbs and X-ray crystallography studies have demonstrated that these proteins retained a native-like structure [12] , [13] . Convalescent DENV immune sera were obtained from volunteers who had experienced natural DENV infections during travel abroad . The protocol for recruiting and collecting blood samples from people was approved by the Institutional Review Board of the University of North Carolina at Chapel Hill . Written informed consent was obtained from all subjects before collecting blood . ELISA plates were coated with 50 ng of purified virus or 100 ng of rE in carbonate buffer at pH 9 . 6 for 2 hrs at room temperature and incubated with blocking buffer ( 0 . 05% TBS-T containing 3% skim milk or 3% normal goat serum ) at 37oC for 1 hr . Human immune sera or hMAbs serially diluted in blocking buffer were added for 1 hr at 37°C followed by alkaline phosphatase-conjugated goat anti-human IgG ( Sigma ) for 1 hr at 37°C . Finally , p-nitrophenyl phosphate substrate ( Sigma ) was added to each well and the reaction was allowed to develop for 15 minutes before recording optical density at 405 nm on a spectrophotometer . DENV neutralizing antibodies was measured by a focus reduction neutralization test ( FRNT ) with Vero cells or using a flow cytometry-based neutralization assay with the U937 human monocytic cell line stably transfected with DC-SIGN as previously described [31] . Peripheral blood samples were obtained from two healthy adult donors who were infected by DENV during foreign travel . The dengue neutralization profiles confirmed previous primary DENV2 ( Donor 013 ) and DENV3 ( Donor 033 ) infections ( Table S1 ) . From both donor hMAbs were produced as previously described [32] . B-cells producing DENV specific antibody were identified by screening culture supernatants by flow cytometry for antibodies that bound to C6/36 insect cells infected with DENV2 ( Donor 013 ) or DENV3 ( Donor 033 ) [32] . A secondary screen to identify antibodies that bound to the rE was performed by ELISA as previously described [32] . DENV antibody escape mutant viruses were selected for by infecting Vero cells with DENV2 ( strain S-16803 ) in the presence of hMAb concentrations estimated to neutralize greater than 99% of infectious virus ( i . e . 1 . 0 µg/ml for DVC 3 . 7 and 1 . 5 µg/ml for DVC 10 . 16 ) . Equivalent GC copy numbers of control and antibody treated viruses were repeatedly passaged in the presence of hMAbs until equivalent DENV genomic copy numbers were observed for MAb treated and control samples ( 4–6 passages under antibody pressure ) . Escape mutant viruses were plaque purified and amplified . E genes were amplified by RT-PCR and sequenced to identify mutations linked to antibody escape . Antibody binding sites were also mapped by using yeast cells expressing a library of EDIII as previously described [33] . Mutations were mapped onto the DENV2 EDIII structure using the atomic coordinates of DENV2 EDIII ( RCSB accession number 1OAN ) and displayed using PyMOL Molecular Graphics System , Version 1 . 3 ( Schrödinger , LLC ) .
We have previously reported that dengue reactive memory B cells are common following both primary and secondary DENV infection [30] . To further characterize the human B cell response in donor 033 , we immortalized memory B cells . PBMCs were isolated and IgG+ memory B cells were immortalized with EBV and CpG as previously described [34] . The immortalized B cell culture supernatants were screened for antibodies that bound to C6/36 insect cells infected with DENV3 . Thirty five percent of the B cell cultures generated from donor 033 were positive following this initial screen ( Table 2 ) . From the dengue positive cultures only 7 . 5% of the cultures bound to rE protein ( Table 2 ) . To further characterize the binding and functional properties of human antibodies , we isolated hMAbs from donor 033 . To isolate hMAbs specific for DENV from donor 033 , positive B cell cultures were cloned by limiting dilution and 16 clones were isolated and expanded . All the hybridomas produced IgG1 with the single exception DV20 . 10 , which was IgG3 ( Table S2 ) . To identify antibodies that bound to structural viral antigens , the hMAbs were tested for binding to purified DENV3 particles in ELISA . Fourteen out of 16 hMAbs bound to DENV3 virus . Of the 14 hMAbs that bound to DENV3 particles , 13 cross-reacted with all four dengue serotypes dengue complex reactiveand one antibody ( hMAb DV51 . 3 ) bound to serotypes 1 and 3 , but not 2 and 4 ( dengue sub complex reactive ) ( Table S2 ) . Dengue virions were solubilized and subjected to Western blot analysis to identify the viral structural proteins recognized by hMAbs . Ten of the 14 hMAbs bound to prM and only a single hMAb ( DV64 . 3 ) bound to E protein ( Figure 1 ) . Three hMAbs did not bind to viral antigens by Western blot , although they reacted with DENV3 virion . The 16 hMAbs were also tested for binding to rE protein in ELISA . Only hMAb DV64 . 31 , which had also recognized E protein by Western Blot , bound to rE protein from all 4 DENV serotypes ( Table S2 ) . We next tested the ability of the 16 antibodies generated from donor 033 to neutralize DENV . Five hMAbs including the two that did not bind to the virion lacked neutralizing activity ( Figure 2 ) . The remaining antibodies ranged from weak to moderately neutralizing and had DENV3 50% neutralization titers that ranged from 0 . 09 to 1 µg/ml ( Figure 2A ) . The neutralizing antibodies had similar 50% neutralization titers against all 4 serotypes , which was consistent with their broad binding specificity ( data not shown ) . In general , prM antibodies had neutralization curves that were shallow and did not reach 100% neutralization , indicating that a fraction of the virus population was resistant to antibody neutralization ( Figure 2B ) . The single E reactive antibody ( DV64 . 31 ) exhibited a steeper neutralization curve and neutralized 100% of virus at high concentrations ( Figure 2C ) . In summary , the hMAbs generated from donor 033 , who had experienced a primary DENV3 infection , were broadly cross-reactive , weakly neutralizing , and mainly directed to epitopes on prM . None of the hMAbs mimicked the functional properties of immune serum from donor 033 that displayed strong type-specific neutralization of DENV3 ( Table S1 ) . A complete summary of the functional profiles of all sixteen hMAbs from donor 033 is included as supplementary material ( Table S2 ) . Next , we characterized the dengue specific memory B cell response in donor 013 , who had recovered from a primary DENV2 infection . We have previously reported on some of the properties of B cells and hMAbs generated from this donor [30] . Here we expand on these previous results by comparing properties of serum antibodies and hMAbs from this donor and by epitope mapping a subset of hMAbs from this donor . When immortalized B cell culture supernatants from donor 013 were screened for antibodies that bound to C6/36 insect cells infected with DENV2 , 28% ( 567/2016 ) of the cultures were found positive for DENV-specific B cells following this initial screen ( Table 2 ) . From the DENV positive cultures only 2 . 9% of the cultures bound to rE protein ( Table 2 ) . Thus , as in the case of donor 033 , although dengue specific memory B cells were frequent , only a small fraction of the positive cultures from donor 013 produced antibodies that bound to rE protein . Since a relatively unbiased selection scheme for producing hMAbs from donor 033 indicated that most hMAbs were cross-reactive , weakly neutralizing and directed to antigens other than rE , we altered the selection scheme for donor 013 to enrich for hMAbs that recognized rE from DENV2 . After the initial screening of memory B cell culture supernatants , the relatively rare rE protein binding cultures were selected for cloning and expansion . Ten rE binding hMAbs were produced ( all IgG1 ) . When the antibodies were tested for binding to heterologous serotypes , 5 hMAbs were DENV2 type-specific , 2 hMAbs were dengue subcomplex-specific and 3 hMAbs were dengue complex-specific ( Figure 3A ) . Six of the ten hMAbs bound to EDIII from DENV2 ( Figure 3A ) . The hMAbs from donor 013 displayed variable neutralization properties ( Figure 3A–C ) , with 2 non-neutralizing hMAbs ( DV1 . 6 , and 21 . 5; 50% neutralization titers >1 ug/ml ) , 4 weakly to moderately neutralizing hMAbs ( DV14 . 21 , 35 . 3 , 25 . 5 and 18 . 21; 50% neutralization titers between 0 . 1 and 1 ug/ml ) and 4 strongly neutralizing hMAbs ( DV3 . 7 , 10 . 16 , 13 . 6 and 23 . 13; 50% neutralization titers <0 . 1 ug/ml ) . The strongly neutralizing hMAbs , including those that were cross-reactive in binding assays , neutralized DENV2 better than the other serotypes ( Figure 3 ) . Thus , by biasing the initial screen for hMAbs that bound to rE protein , we identified hMAbs with neutralization profiles that were more similar to the immune sera of donor 013 , which strongly neutralized DENV2 . Several hMAbs from donor 013 bound to EDIII ( Figure 3 ) . Two approaches were used to map the binding sites of these hMAbs on EDIII . Two strongly neutralizing hMAbs that bound EDIII , which were type- ( DV3 . 7 ) or subcomplex- ( DV10 . 16 ) specific , were mapped by identifying neutralization escape variants after passaging DENV2 in the presence of each antibody ( ired a mutation on EDIII . The virus passaged in the presence of hMAb DV3 . 7 acquired the single point mutation V382G ( Table 3 and Figure 4C ) . This residue is located on the EDIII lateral ridge , which is a target of previously mapped type-specific strongly neutralizing mouse MAbs [17] , [23] ( Table 3 and Figure 4C ) . The virus passaged in the presence of hMAb DV10 . 16 acquired the point mutation E311K ( Table 3 and Figure 4C ) . This amino acid is located on the A strand of EDIII and forms part of a dengue subcomplex epitope recognized by neutralizing mouse MAbs [18] , [23] ( Table 3 and Figure 4C ) . As an independent approach to mapping EDIII-reactive hMAbs , we used a yeast surface display assay that has been previously used to map numerous flavivirus antibodies [22] , [23] , [33] . Table 3 summarizes all mutations that resulted in loss of binding or neutralization of EDIII antibodies generated from donor 013 . All the human EDIII-binding MAbs mapped to the lateral ridge or the A strand regions that have previously been described as targets of mouse MAbs [23] ( Figure 4C ) .
Our main objective was to define viral antigens and epitopes recognized by 2 individuals exposed to primary DENV infections . In both these subjects the dengue virion was a major target of the humoral immune response but many of these antibodies did not bind to rE protein . The DENV virion displays 180 E and 180 prM or M proteins that are arrayed with pseudo-icosahedral symmetry . Depending on the maturation state of the virus particle , the 180 E protein molecules are organized as 90 head-to-tail dimers that lie flat on the virion surface or 60 trimers that protrude as spikes from the surface [35] . Since the E protein , with ∼500 amino acids , is considerably larger than the 166 amino acid prM protein , the majority of surface exposed viral protein consists of the ectodomain of E . Thus , our finding that many antibodies bound to epitopes on the virus that were not preserved on rE was somewhat unexpected . These findings are consistent with the results of another study from our group [30] as well as a study by Dejnirattisai and colleagues who observed that many hMAbs that bound to DENV particles did not bind to rE protein [25] . As the rE protein used in the current study lacked ∼20% of the protein , which include the membrane proximal regions and the transmembrane domains , it is possible that some antibodies bind to these regions . Moreover , antibodies may recognize E protein epitopes that are only available in the context of the native oligomeric array on the virion . Several hMAbs generated from individuals infected with West Nile virus bound the virion but not rE protein; these hMAbs recognized epitopes that were created by adjacent E protein molecules on the surface of the virion or formed by hinge regions [36] . When producing MAbs from donor 013 , we increased the probability of identifying strongly neutralizing antibodies by biasing the selection scheme for MAbs that specifically recognized rE protein . In contrast to the weak or non-neutralizing hMAbs isolated from donor 033 , several hMAbs from donor 013 displayed strong type-specific DENV2 neutralization . Of note , even hMAbs from donor 013 that bound to more than one serotype ( dengue subcomplex or complex MAbs ) displayed type-specific neutralization of DENV2 , which was the serotype that infected donor 013 . Thus , by biasing the selection to enrich for rare rE protein binding antibodies , we generated hMAbs from donor 013 that were functionally similar to the polyclonal immune serum from the same donor that neutralized only DENV2 . It is unclear how the results with hMAbs relate to the neutralization properties of polyclonal immune serum from these donors . One possibility is that the abundance of hMABs reflects the functional properties of antibodies in immune sera , where a small fraction of DENV-specific antibodies in immune sera are responsible for neutralization . Alternatively , it is conceivable that individual antibodies that are weakly neutralizing become strongly neutralizing due to cooperative effects that only occur in a polyclonal milieu . Further studies are needed to understand how the properties of hMABs from DENV immune donors relate to the properties of circulating serum antibody . From the neutralizing MAbs from donor 013 that bound to rE , some bound to the lateral ridge and A strand epitopes on EDIII ( ref ) . We also identified several neutralizing hMABs ( 35 . 3 , 18 . 21 , 13 . 6 , 23 . 13 ) that bound to rE but not EDIII and these antibodies most likely bind to epitopes on EDI or EDII . We are especially interested in mapping the binding sites of these hMABs as recent studies indicate that epitopes other than the lateral ridge and A strand of EDIII can be the targets of strongly neutralizing mouse , horse and primate antibodies [29] , [37] , [38] , [7] , [22] , Our results indicating that prM was a dominant target of the primary antibody response are in agreement with other recent studies [25] , [30] . The prM protein is required for the proper folding and assembly of flavivirus particles in the endoplasmic reticulum [39] , while also preventing adventitious fusion of the virus [40] in the acidic environment of the trans-Golgi network . Recent studies have demonstrated that DENV virions produced in cell culture are often partially processed and contain a mixture of unprocessed prM and fully processed M [41] . The maturation state and relative amount of prM on a virion can alter the potency of antibodies that bind specific epitopes on E , including the cross-reactive antibodies that bind the fusion loop in DII [42] . Additionally , immature , non-infectious particles became infectious in the presence of prM antibody by enhancing the ability of immature dengue virions to infect Fc-receptor bearing cells in vitro [25] , [43] . Given our findings and those of others [25] establishing that prM antibodies are common following primary and secondary DENV infections , more work needs to be performed to address their contribution to dengue pathogenesis in humans . In summary , the studies reported here demonstrate an unexpected antibody profile in two individuals following primary dengue infection . In both individuals a majority of the DENV-specific human antibodies were broadly cross-reactive and weakly neutralizing . Many antibodies bound to prM and sites on the virus that were not preserved on rE protein . Only a minor fraction of the total dengue specific antibody response was responsible for potent neutralization of the homologous virus . Given the difficulty of identifying suitable donors and generating antigen specific hMAbs , we only characterized the antibody response in two subjects here . Further studies with more dengue immune subjects are needed to determine if our findings are broadly applicable to primary dengue exposure .
|
Dengue is a mosquito-borne viral disease of humans . The dengue virus complex is made up of four viruses designated as serotypes . People experiencing their first infection develop immune responses that prevent re-infection with the same serotype only . People experiencing a second infection with a new serotype face a greater risk of developing a severe disease known as dengue hemorrhagic fever . Although studies indicate that antibodies can prevent or enhance disease caused by DENV , few studies have explored the specific properties of human antibodies against DENV . The objective of this study was to conduct a detailed analysis of the antibody response of two individuals who had recovered from primary infections . Human antibodies bound to sites on the dengue virus particle including the viral pre-membrane ( prM/M ) and envelope ( E ) proteins . Our studies indicate that the human antibody response consists of a minor population of strongly neutralizing antibody and a major population of DENV serotype cross-reactive , non-neutralizing antibody with potential for enhancement of virus and disease . Further studies with more DENV-immune subjects are needed to determine if our findings are broadly applicable to primary infections .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"humoral",
"immunity",
"medicine",
"infectious",
"diseases",
"immunity",
"immunology",
"biology",
"microbiology",
"viral",
"diseases",
"dengue",
"immune",
"response",
"immunoglobulins"
] |
2011
|
In-Depth Analysis of the Antibody Response of Individuals Exposed to Primary Dengue Virus Infection
|
The formation of mature cells by blood stem cells is very well understood at the cellular level and we know many of the key transcription factors that control fate decisions . However , many upstream signalling and downstream effector processes are only partially understood . Genome wide association studies ( GWAS ) have been particularly useful in providing new directions to dissect these pathways . A GWAS meta-analysis identified 68 genetic loci controlling platelet size and number . Only a quarter of those genes , however , are known regulators of hematopoiesis . To determine function of the remaining genes we performed a medium-throughput genetic screen in zebrafish using antisense morpholino oligonucleotides ( MOs ) to knock down protein expression , followed by histological analysis of selected genes using a wide panel of different hematopoietic markers . The information generated by the initial knockdown was used to profile phenotypes and to position candidate genes hierarchically in hematopoiesis . Further analysis of brd3a revealed its essential role in differentiation but not maintenance and survival of thrombocytes . Using the from-GWAS-to-function strategy we have not only identified a series of genes that represent novel regulators of thrombopoiesis and hematopoiesis , but this work also represents , to our knowledge , the first example of a functional genetic screening strategy that is a critical step toward obtaining biologically relevant functional data from GWA study for blood cell traits .
Erythrocytes and platelets ( thrombocytes in zebrafish ) are the most abundant cells in blood . In an individual , the number and volume of both erythrocytes and platelets are highly heritable and tightly regulated within narrow ranges , but there is a wide variation of these parameters in the population [1] , [2] . The 80% heritability of blood cell indices provided the foundation for our recently completed GWAS meta-analysis in ∼68 , 000 healthy individuals for both cell types . We identified 68 genetic loci that control the mass ( volume x count ) of platelets [3] and another 75 for red cell indices [4] . About a quarter of the genes proximal to the platelet GWAS association single nucleotide polymorphisms ( SNPs ) encode well studied and generally pivotal regulators of hematopoiesis but the function of the remaining ones is unknown , demonstrating the power of GWAS to identify novel regulators of hematopoiesis . We have recently reported functional validation of six genes in which the sentinel SNP was localized within a gene and silenced ak3 , rnf145 , arhgef3 , tpm1 , jmjd1c and ehd3 in zebrafish by MO injections . Profound effects on thrombopoiesis were observed for all but ehd3 [3] . Furthermore , our detailed studies of the arhgef3 gene , which encodes one of the ∼70 Rho guanine nucleotide exchange factors , showed its important role in iron uptake and transferrin receptor internalisation in erythrocytes [5] . Based on these preliminary data , we hypothesized that the majority of genes identified in our recent genomics efforts are important and rate-limiting regulators of hematopoiesis and therefore worthwhile of further investigation . The zebrafish model has distinct advantages over other animal models for screening large numbers of genes . Zebrafish development occurs rapidly over the course of a few days with thrombocytes , erythroid- and myeloid- blood cells being fully formed and functional by 3 days post fertilisation ( dpf ) . External fertilisation and transparency of zebrafish embryos allow easy visualisation of early blood-related phenotypes giving them the advantage over mice , where development occurs in utero . Importantly , transcriptional mechanisms and signalling pathways in hematopoiesis are well conserved between zebrafish and mammals [6] . Herein , we performed a MO injection screen of 15 genes identified in GWAS for platelet size and number to uncover novel pathways essential in thrombopoiesis and hematopoiesis in general . From this screen , we identified 12 new genes required for normal hematopoiesis and ordered them on a hematopoietic lineage tree based on their presumed function during hematopoiesis . Further analysis of the hematopoietic lineage tree revealed a distinct pattern of gene distribution suggesting two main gene clusters . One cluster of genes appears to work at the level of HSCs affecting all derived blood cell types and the second cluster appears to be limited to controlling the specification of the thrombocyte-erythroid progenitors . Additionally , we show that one of the novel candidate genes , brd3a , is essential in differentiation of thrombocytes from HSCs but is dispensable for their maintenance .
To interrogate the large number of novel hematopoietic genes identified in the GWAS for platelet size and number we developed an in vivo functional genomics screen in zebrafish ( Figure S1 ) . The first step was selection of the most suitable candidate genes and initially we selected a single gene , closest to the sentinel SNP , from each GWAS locus [3] ( Table S1 ) . Distance from the nearest gene was calculated as the absolute distance between SNP and transcription start site of the gene or 3′ end of last exon [3] ( Table S1 ) . We further eliminated genes with a known function in hematopoiesis and identified a putative zebrafish ortholog , with over 38% identity , on the protein level , with its human counterpart for 40 genes . Finally , we excluded all genes that would require the use of more than two MOs , resulting in a list of 33 genes . Nearly 80% of these genes had a sentinel SNPs localized within 10 kb . In the last step , we selected 19 genes of which 16 had a sentinel SNP within 10 kb and three genes had a sentinel SNP >10 kb . Five of the selected genes were duplicated in zebrafish , resulting in a total of 24 genes to be further investigated aiming to define their function in blood cell formation by a MO knockdown approach in zebrafish . We designed splice-blocking MOs for each gene and validated their efficacy with RT-PCR and sequencing . Of the 24 MOs tested five MOs had no effect on the target RNA and these MOs were excluded from further analysis ( Figure S2 ) . We then assayed the remaining 19 functional MOs for their effect on overall development , morphology and hematopoiesis during the first 72 hours post fertilisation ( hpf ) and selected the optimal dose of MO to be injected ( Figure S3 ) . Of note , based on the information available at the ZFIN at the time and our in situ hybridization data ( Figure S4 ) none of the selected genes had hematopoietic specific gene expression . For all genes , except grtp1a , the optimal dose of MO was selected that resulted in a specific phenotype but without gross lethality or defects in body shape or size , vasculature , heart and circulation . We found that grtp1a MO injected embryos died by 15 hpf even when injected with 0 . 8 ng of MO , thus we excluded grtp1a from further analysis . Although morphological examination can detect defects with great sensitivity , some specific defects in hematopoiesis can be missed , and as a result information obtained from the initial analysis might be limited . Thus , we carried out a second level of analysis by performing in situ hybridisation with several hematopoietic markers , specifically , c-myb , ae1 globin , mpeg and rag1 . These were complemented with the use of the Tg ( cd41:EGFP ) line and two histochemical stains , o-Dianisidine and Sudan black . The hematopoietic markers used for phenotyping were carefully chosen to distinguish between early and late stages of hematopoiesis as well as thrombocytes , erythrocytes , neutrophils , macrophages and lymphocytes ( Figures S5 ) . We initiated screening by taking advantage of the Tg ( cd41:EGFP ) reporter line , which labels thrombocytes , to identify genes in zebrafish that , when disrupted , affect thrombocyte number . We found that knock down of 15 of the 18 genes resulted in 30–95% reduction in thrombocyte number ( Figure 1 , Figure S6 ) . Importantly , where the functional second MO was available , the observed phenotype was comparable to the one observed with the first MO ( Figure S7 , S8 , Table S2 ) . Furthermore , concurrent knock down of p53 with gene specific MOs did not attenuate the thrombocyte phenotype induced by gene specific MOs , confirming that the observed decrease in the number of thrombocytes was not induced by p53 mediated off target effects of MO injection ( Figure S9 ) . For one of the “phenotypic” genes , brf1b , we have obtained the mutant through ZMP . To test if brf1b mutants have a decreased number of thrombocytes , the offspring were subjected to the “clotting time assay” at 5 dpf [7] . Clotting time in brf1b mutant larvae was significantly longer than in the wild type fish , suggesting a defect in thrombopoiesis ( Figure S10 A ) . To further confirm the specificity of the phenotype observed in MO injected embryos and in the absence of available mutants we performed the rescue of rcor1 MO injected embryos using full-length zebrafish rcor1 RNA ( Figure S10 B , C ) . We focused our further analysis on the 15 “phenotypic” genes and their paralogs . To maintain the population of differentiated blood cells within normal ranges , HSCs need to continuously maintain the balance between self-renewal and differentiation . We reasoned that decreased number of thrombocytes in MO injected embryos could be the result of either reduced numbers of HSCs or altered HSC differentiation . To assess which stage of hematopoiesis was affected in each MO injected embryo , we performed in situ hybridization at 3 dpf and looked for alterations in expression of definitive hematopoiesis marker c-myb ( Figure 2 ) . Although more than half of the MOs tested had no effect on the number of HSCs , depletion of rcor1 resulted in an increased number of HSCs and depletion of kalrn ( 1 and 2 ) , mfn2 , pdia5 , psmd13 and wasplb resulted in decreased numbers of HSCs in caudal hematopoietic tissue ( CHT ) at 3 dpf . This reduction in the number of HSCs was not evident at 30 hpf in kalrn1 , mfn2 , pdia5 , psmd13 and wasplb MO injected embryos ( Figure S11 ) suggesting that the number of HSCs at 3 dpf was most probably adversely affected by either their homing to or survival/proliferation in CHT . However , kalrn2 and rcor1 depleted embryos had a marked decrease in the number of HSCs at 30 hpf , implying the important role of these genes in specification of HSCs in the aorta-gonad-mesonephros ( AGM ) ( Figure S11 ) . Importantly , analysis of vascular development by injecting candidate gene MOs into Tg ( fli1:EGFP ) embryos , which express EGFP in endothelial cells , demonstrated no major abnormalities in vascular morphogenesis or remodeling that would preclude circulation , indicating that the hematopoietic defects were not secondary to a vascular phenotype ( Figure S12 ) . Thus , our screen effectively defined a set of nine genes required for differentiation of HSCs to thrombocytes and possibly other blood lineages . Hematopoiesis is often depicted by a hierarchical differentiation tree , with HSCs at the root and the mature blood cells as the branches . One of the intermediate cellular states is the common myeloid progenitor ( CMP ) , which can proliferate and differentiate into megakaryocyte-erythrocyte progenitors ( MEP ) and granulocyte-monocyte ( GM ) progenitors , which further give rise to megakaryocytes , erythrocytes , granulocytes , monocytes and other cell types . To investigate lineage-specific effects of the candidate genes , we assessed the status of definitive erythropoiesis in MO injected embryos at 4 dpf . As αe1-globin RNA was reported to be expressed in definitive erythrocytes at 4 dpf [8] , a detailed analysis of the expression pattern of αe1-globin transcript was exploited to reveal the initiation of definitive erythropoiesis after gene silencing . Profound effects on definitive erythropoiesis were observed for all but brd3a , brf1b , waspla and wdr66 ( Figure S13 ) . However , silencing of brf1a and wasplb resulted in diminished definitive erythropoiesis , reflecting functional divergence of duplicated genes ( brf1 and waspl ) ( Figure S13 ) . Furthermore , an extensive analysis of hemoglobin levels in primitive erythroid cells at 2 dpf showed that , with the exception of brd3a , kalrn2 and kif1b , primitive erythropoiesis was largely unaffected following MO knock down of candidate genes ( Figure S14 ) . These results are consistent with the notion that the majority of candidate genes are dispensable for specification and differentiation of primitive erythrocytes and that fundamentally different molecular mechanisms regulate primitive and definitive erythropoiesis . To establish the role of candidate genes in differentiation of the myeloid lineage , that is neutrophils and macrophages , we performed Sudan Black staining ( for neutrophils ) and in situ hybridization using mpeg riboprobe ( for macrophages ) in control and candidate gene depleted zebrafish embryos at 3 dpf . Out of 15 genes tested , depletion of nine resulted in reduced numbers of Sudan Black positive cells and two ( kif1b , waspla ) had an effect on the number of macrophages ( Figures S15 , S16 , and S18 ) . Reduction in the number of Sudan Black positive cells could reflect the absence of granules rather than neutrophils . We have , therefore , performed in situ hybridization using mpx riboprobe for all genes for which the knockdown resulted in a decrease in the number of Sudan Black positive cells . For all the tested genes the observed phenotype was comparable to the one we reported following Sudan Black staining ( Figure S17 ) . Finally , we analyzed the impact of loss of candidate gene function on lymphoid development . Differentiated thymic T-cells are exclusively derived from definitive HSCs and can be readily identified by rag1 expression when examined at 4 dpf ( Figure S19 ) . Not surprisingly , a significant decrease in rag1 staining was mostly observed in the same set of genes in which we observed a decrease in c-myb staining ( a marker for HSCs ) , namely kalrn1 , kalrn2 , mfn2 , pdia5 and psmd13 . In addition , injection of akap10 MO and rcor1 MO , which had no negative impact on the number of c-myb positive cells , resulted in a significant decrease in the number of T lymphocytes . The large number of genes analyzed and the resultant volume of data acquired can present challenge in understanding and interpreting the results . Hence , we used the information gained from the initial MO knockdown screen to generate a heat-map of phenotype profiles ( Figure 3 ) and cluster genes with similar phenotypic profiles . We then hierarchically positioned candidate genes on the hematopoietic lineage tree and assigned each of them a potential role during hematopoietic differentiation ( Figure 4 ) . Our analysis of the hematopoietic lineage tree revealed a distinct pattern of gene distribution , suggesting two main gene clusters . The first cluster represents a set of genes , namely kalrn1 and -2 , mfn2 , pdia5 , psmd13 , rcor1 and wasplb , which upon depletion affect the number of HSCs . The second major cluster represents a set of genes , namely akap10 , brf1a , kif1b , satb1 and wasplb , which appear to be essential further down the hematopoietic tree and affect differentiation of both definitive erythrocytes and thrombocytes . These genes have presumed role in HSC fate decisions prior to specification of the thrombocyte and erythrocyte progenitors . Although the frequency of blood defects observed in our screen was high , the screen was not as well suited for the identification of knockdown phenotypes that result in subtle differences in myeloid lineage cell production or skewing of myeloid lineage differentiation . This is mainly because changes in the number of neutrophils and macrophages arising from HSCs may be undetectable using markers and the developmental time point outlined here . Previous studies have shown that erythroid-myeloid progenitor cells ( EMPs ) are capable of generating both macrophages and neutrophils and that these blood cells appear in mib zebrafish despite the absence of HSCs [9] . However , even with these caveats , we believe the screening procedure used has proven effective for extracting functional information from a GWAS dataset in a medium-throughput manner . To gain an additional insight into mechanisms by which these newly discovered genes affect thrombopoiesis , we performed a more extensive analysis of the function of brd3a in hematopoiesis . The bromodomain and extra terminal domain ( BET ) family of proteins , including BRD2 , BRD3 , and BRD4 , are evolutionally conserved and play a key role in many cellular processes by controlling the assembly of histone acetylation-dependent chromatin complexes [10] . To further confirm that the defects observed in the brd3a depleted embryos resulted from loss of brd3a , in vitro–transcribed RNA encoding human BRD3 ( hBRD3 ) was injected into 1-cell stage embryos . Live confocal imaging of zebrafish embryos injected with hBRD3-GFP confirmed that hBRD3 binds to mitotic chromosomes ( Figure 5A ) , a feature previously reported for BET family proteins i . e . BRD2 , BRD3 and BRD4 [11]–[13] . Expression of hBRD3 in brd3a MO injected embryos resulted in partial but statistically significant rescue of the number of thrombocytes demonstrating that brd3a MO used in this study exerted a specific effect ( Figure 5B , C ) . Morpholinos do not allow gene-specific perturbation to be carried out with temporal resolution , which is a disadvantage when dissecting the precise role of a selected gene in hematopoiesis . A number of studies reported that compounds targeting BET proteins might be used to manipulate hematopoietic development for exploratory or therapeutic purposes [14]–[16] . The BET family inhibitor , thieno-triazolo-1 , 4-diazepine ( ( + ) -JQ1 in short ) is a potent , highly specific inhibitor which displaces BET proteins from chromatin by competitively binding to the acetyl-lysine recognition pocket of BET bromodomains [17] , [18] . Thus , we evaluated the pharmacological impact of ( + ) -JQ1 on zebrafish development and thrombopoiesis . Exposure of zebrafish embryos to ( + ) -JQ1 disrupted the chromatin occupancy of hBRD3-GFP confirming the efficacy of the inhibitor ( Figure S20 A–C ) . We next incubated embryos from 6 hpf in various concentrations of ( + ) -JQ1 and ( − ) -JQ1 ( stereoisomer which has no appreciable affinity to BET bromodomains ) [17] as a control ( Figure S21 ) . Exposure of zebrafish embryos to 1 µg/ml ( + ) -JQ1 resulted in complete mortality by 24 hpf whereas the ( − ) -JQ1 enantiomer showed no observable effect on embryo development ( Figure S21 ) . This early embryonic death of zebrafish embryos was not surprising considering that knockout of Brd2 or Brd4 in mice results in embryonic lethality , indicating an important role of these two proteins in embryonic development [19] , [20] . When treated , however , with ( + ) -JQ1 from 24 hpf , embryos exhibited overall normal development even at the higher concentration ( 1 µg/ml ) of ( + ) -JQ1 ( Figure S21 ) . Although morphologically normal , thrombopoiesis was completely abolished in these embryos ( Figure 6 A ) . Interestingly , the decrease in the number of thrombocytes appeared more prominent in the presence of ( + ) -JQ1 inhibitor compared to brd3a MO knock down . This opened the possibility that other members of the BET family might be contributing to the observed phenotype . To investigate this further , we performed MO knock down of zebrafish brd2a , brd2b and brd4 and assessed the number of thrombocytes at 3 dpf . Single MO knock down of all three genes resulted in a severe decrease in the number of thrombocytes . These data strongly suggested that , indeed , other members of BET family of proteins ( i . e . brd2 and brd4 ) play an important role in thrombopoiesis ( Figure S22 A–C ) . Both MO knock down and treatment with ( + ) -JQ1 inhibitor from 24 hpf resulted in a severe reduction in the number of thrombocytes at 3 dpf , suggesting an essential role for brd3a in the differentiation of thrombocytes as opposed to a requirement for their maintenance and survival . To address this question we incubated Tg ( cd41:EGFP ) embryos with ( + ) -JQ1 inhibitor starting from 3 dpf , when there is already a considerable number of thrombocytes in CHT , and assessed their number 24 hours later , at 4 dpf . We found that in untreated and ( − ) -JQ1 treated embryos the number of thrombocytes markedly increased between 3 and 4 dpf . However , in ( + ) -JQ1 treated embryos we observed no change in the number of thrombocytes ( Figure 6C ) . Moreover we found that ( + ) -JQ1 had no adverse effect on the number of HSCs during this 24 h period of treatment ( Figure 6D ) . Taken together this strongly suggests that brd3a is important in differentiation of thrombocytes from HSCs , however , once differentiated , brd3a was dispensable for their maintenance and survival .
GWAS meta-analysis of platelet size and number has been successful in identifying SNPs associated with the mass ( volume x count ) of platelets . In contrast with the results of GWAS in common diseases , more than 80% of SNPs associated with hematological traits are localized within 10 Kb of genes providing a sound argument to infer biologically relevant candidate genes [3] , [4] . Canonical pathway analyses detected a highly significant over-representation of “core genes” ( the sentinel SNP is within the gene or within 10 kb from the gene ) in relevant biological functions such as hematological disease , cancer and cell cycle [3] . However , three quarters of regions proximal to the platelet GWAS SNPs harbor unfamiliar genes or known genes not previously implicated in hematopoiesis that merit extensive follow-up analysis . Therefore , this study was set up to address the need for a medium-throughput method in zebrafish to dissect the functional roles of these assumed novel regulators of hematopoiesis . In total , our screen identified 15 genes ( corresponding to 12 human genes ) required for distinct stages of specification or differentiation of HSCs in zebrafish . A detailed review of the content of databases and literature revealed limited knowledge about the functional role of Satb1 , Rcor1 and Brd3 [21]–[24] in hematopoiesis and for the remaining nine genes our work represents the first study on their putative role in hematopoiesis . Importantly , our results are well in line with some of the findings reported by others . One example is RCOR1 - lineage-restricted deployment of RCOR1 and LSD1 cofactors , through interaction with Gfi proteins , controls hematopoietic differentiation [23] . Knock down of rcor1 in zebrafish resulted in completely blocked differentiation of erythroid , thrombocytic , myeloid and lymphoid lineages . These findings strongly support the hypothesis that the published platelet GWAS [3] enriched for functional regulators of the hematopoiesis and further support previous assumptions that a large proportion of the genes uncovered by the aforementioned GWAS also have a conserved role in zebrafish . In this study , we followed a two step screening approach: in the first instance , we used the Tg ( cd41:EGFP ) line in conjunction with a panel of hematopoietic in situ hybridization probes and histochemical staining to create a heat map with distinct “phenotype signatures” of each gene knock-down . We then positioned the candidate genes on the hematopoietic cell lineage tree and assigned them a potential role in hematopoietic differentiation . Interestingly , our screen revealed that , although initially selected based on their effect on the platelet size and/or number , none of the candidates exerted a thrombocyte specific effect . These results should be interpreted within the context of several major differences between the effect of the SNPs and whole embryo MO knock down on hematological traits . First , the majority of associated SNPs identified in platelet GWAS are in non-transcribed regions and it is likely that the underlying mechanism linking them to the phenotype is regulatory . Thus , the functional effects of SNPs are subtler compared to the knock down of transcripts achieved by MOs in our screening . Secondly , although GWAS provided a list of SNPs associated with the platelet size and number , there is no evidence about the biological processes that link the associated SNP to the phenotype . Indeed , it has been shown that in most cases the reported SNP is not the functional SNP itself but is in linkage disequilibrium with the SNP overlapping a functional region [25] . Experimental evidence shows that open chromatin profiles of megakaryocytes and erythroblasts differ and thus cell type-restricted regions of open chromatin could influence the penetrability of the functional SNP [26] , [27] in a lineage specific manner . In contrast , MO knock down in zebrafish is not spatially restricted and thus offers the opportunity to determine the functional role of candidate genes in all blood lineages . To further verify the hematopoietic role of genes identified in GWAS , we performed a more extensive evaluation of the effect of brd3a on thrombopoiesis . It has been shown that BRD3 interacts with acetylated GATA1 and stabilizes its chromatin occupancy [21] . A pharmacologic compound , JQ1 , that occupies the acetyl-lysine binding pockets of Brd3 bromodomains disrupts the BRD3-GATA1 interaction , diminishes the chromatin occupancy of both proteins , and inhibits erythroid maturation [21] . Although GATA1 and BRD3 co-occupancy on GATA1 target genes was also observed in a megakaryocytic cell line [21] , the biological relevance of this binding was never confirmed . Here we report on the important role of brd3a in thrombopoiesis . Indeed , knock-down of brd3a with two independent MOs as well as treatment of zebrafish embryos with the JQ1 inhibitor starting from 24 hpf severely reduced the number of thrombocytes in 3 days old embryos . Interestingly , incubation of embryos with JQ1 inhibitor between 3- and 4 dpf , that is after the onset of thrombopoiesis , did not have any effect on the already differentiated thrombocytes . However , the number of thrombocytes failed to increase compared to control embryos within this 24-hour period . These results strongly support the idea that brd3a is critical for establishing but not maintaining thrombopoietic compartment . Some previous studies suggest that BRD3 , as well as some other mitotically retained factors , functions as a molecular “bookmark” by enabling post-mitotic transcription re-initiation of its target genes [13] , [28] . It is plausible to assume that a similar mechanism is employed during thrombopoiesis . In that scenario , retention of Brd3 on chromatin during mitosis of thrombocyte precursors or erythroid-thrombocyte progenitor cells would contribute to the maintenance of transcription patterns necessary for establishment of thrombocyte identity . However , further work will be necessary to identify the precise molecular mechanisms by which brd3a exerts its effect on thrombopoiesis . Taken together , our study provides a paradigm of the usefulness of zebrafish for efficient translation of GWAS findings into relevant biological information in an objective and unbiased manner . GWAS have mapped many novel , convincingly associated loci in the proximity of genes where functional significance is expected . So far , functional validation of such genes has remained confined to single gene approaches . Here we utilized the powerful genetics and translucency of zebrafish larvae to undertake a medium-throughput screen of genes implicated in human hematopoietic variation . The results of this screen will help us to tentatively place novel genes in molecular pathways and thus close the ever-increasing knowledge gap on the biological function of gene candidates identified by genomic technologies .
The maintenance , embryo collection and staging of the wild type ( Tubingen Long Fin ) and transgenic zebrafish lines ( Tg ( cd41:GFP ) , Tg ( fli1:GFP ) , Tg ( c-myb:EGFP ) were performed in accordance with EU regulations on laboratory animals , as previously described [29] , [30] . Morpholinos ( GeneTools , LLC ) were re-suspended in sterile water and diluted to chosen concentration . Approximately 1 nl was injected into embryos at 1- to 2-cell stage . MOs used are summarized in Table S2 . Plasmid with full-length human hBRD3 cDNA was purchased from Source Bioscience ( Nottingham , UK ) . hBRD3 was cloned into pCS2 expression vector using gene-specific primers: AATTACATCGATACCATGTCCACCGCCACGACAGT ( forward ) and CCCGAGTCTAGACTATTCTGAGTCACTGCTGTCAGA ( reverse ) and AAATTAGAATTCACCATGTCCACCGCCACGACAGT ( forward ) and ATGTTAACCGGTAGTTCTGAGTCACTGCTGTCAGA ( reverse ) for cloning into the pCS2-EGFP vector . Restriction enzyme sites ( ClaI/XbaI and EcoRI/AgeI respectively ) used for cloning are underlined . Zebrafish full-length rcor1 cDNA was cloned into pCS2 vector using gene-specific primers: GTTATAGAATTCATGCCCGCAATGTTAGAGAAG ( forward ) and AGGCGCCTCGAGTCAGGAAACCGAAGGGTTCTG ( reverse ) . Restriction enzyme sites ( EcoRI and XhoI , respectively ) are underlined . hBRD3 , hBRD3-GFP and rcor1 mRNA was synthesized with mMESSAGE mMACHINE kit ( Ambion ) , according to the manufacturer's protocol . In the rescue experiment , 100 pg of hBRD3 mRNA or 125 pg rcor1 RNA was injected into the one cell stage control and MO-injected Tg ( cd41:EGFP ) embryos . In the hBRD3 localization experiment , 300 pg of hBRD3-GFP mRNA was injected into Tubingen Long Fin embryos at 1-cell stage . In order to verify the effectiveness of MOs in affecting their target transcripts , RT-PCR was performed . RNA was subjected to reverse transcription using Superscript II Reverse Transcriptase ( Invitrogen ) . PCR was performed using gene-specific primers ( listed in Table S2 ) and KOD Hot Start DNA Polymerase ( Novagen ) . In situ hybridization was performed with riboprobes specific for c-myb , αe1-globin , mpx , mpeg and rag1 as previously described [31] , as well as for brd3a , brf1b , kalrn1 , waspla and wdr66 . Primers used for PCR amplification of candidate genes for probe synthesis are listed in Table S3 . Photomicrographs were taken with a Zeiss camera AxioCam HRC attached to a LeicaMZ16 FA dissecting microscope ( Leica Microsystems , Germany ) using the AxioVision software . O-dianisidine staining was performed as previously described [32] . Sudan Black staining was performed as previously described [33] . Clotting time assay was performed as previously described [7] . In short , 5 dpf larvae were anaesthetized in 0 . 02% tricaine solution in embryonic water and transferred onto a Petri dish in a small drop of liquid . Caudal veins of the larvae were wounded with the tip of a Microlance needle ( 0 . 4 mm×13 mm , Becton Dickinson ) in the anal area . For each larva the time passing between inflicting the wound and the stop of bleeding was recorded . Genomic DNA was isolated from 5 dpf larvae , which were individually loaded into wells of a 96-well plate . Fish were incubated in 25 µl of lysis buffer ( 25 mM NaOH with 0 . 2 mM EDTA ) at 95°C for 30 min . Afterwards 25 µl of neutralization buffer ( 40 mM Tris-HCl ) was added . Genotyping was carried out using the KASP genotyping assays ( KBioscience ) . Each reaction consisted of 4 µl of genomic DNA and 5 µl of PCR mix , according to the manufacturer's protocol ( KBioscience ) . PCR products were analyzed using PHERAstar plus ( BMGlabtech ) and KlusterCaller software ( KBioscience ) . Images were captured with the use of a Leica TCS SP5 confocal microscope with Leica LAS AF software ( Leica Microsystems ) , using a 40× immersion lens or with Axio Zoom . V16 fluorescent microscope with AxioCam MRm camera using 260× magnification . Selective inhibitor of human BET family of bromodomain-containing proteins , thieno-triazolo-1 , 4-diazepine , named JQ1 , was kindly provided by Dr Chas Bountra , Structural Genomics Consortium , University of Oxford , Oxford , UK . Both the active inhibitor , ( + ) -JQ1 , and its inactive stereoisomer , ( − ) -JQ1 , were dissolved in dimethylsulfoxide ( DMSO ) to 10 mg/ml and stored in aliquots at −20°C . For zebrafish embryo treatment , ( + ) -JQ1 and ( − ) -JQ1 were diluted in egg water to desired concentration and added to the embryos at ∼6 hpf , 24 hpf or 3 dpf and afterwards replaced daily . Control embryos were incubated in the equal concentration of DMSO in egg water as inhibitor-treated embryos .
|
In this manuscript we report on a follow-up study of the GWAS loci associated with the platelet size and number . A GWAS meta-analysis identified 68 genetic loci controlling platelet size and number . Only a quarter of those genes , however , are known regulators of hematopoiesis . To determine function of the remaining genes we performed a medium-throughput genetic screen in zebrafish using morpholinos ( MOs ) to knock down selected candidate genes . Here , we report on two major findings . First we identified 15 genes ( corresponding to 12 human genes ) required for distinct stages of specification or differentiation of HSCs in zebrafish . A detailed review of databases and literature revealed limited knowledge about the functional role of Satb1 , Rcor1 and Brd3 in hematopoiesis and for the remaining nine genes our work represents the first study on their putative role in hematopoiesis . And secondly , we demonstrate that brd3a is critical for establishing , but not maintaining thrombopoietic compartment . Importantly , our study introduces zebrafish as a model system for functional follow-up of GWAS loci and generates a valuable resource for prioritization of platelet size and number associated genes for future in-depth mechanistic analyses . Following this route of investigation new regulatory molecules of hematopoiesis will be added to critical pathways .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"medicine",
"and",
"health",
"sciences",
"body",
"fluids",
"blood",
"anatomy",
"platelets",
"biology",
"and",
"life",
"sciences",
"hematology"
] |
2014
|
A Loss of Function Screen of Identified Genome-Wide Association Study Loci Reveals New Genes Controlling Hematopoiesis
|
In eukaryotes , the spatial and temporal organization of genome duplication gives rise to distinctive profiles of replication origin usage along the chromosomes . While it has become increasingly clear that these programs are important for cellular physiology , the mechanisms by which they are determined and modulated remain elusive . Replication initiation requires the function of cyclin-dependent kinases ( CDKs ) , which associate with various cyclin partners to drive cell proliferation . Surprisingly , although we possess detailed knowledge of the CDK regulators and targets that are crucial for origin activation , little is known about whether CDKs play a critical role in establishing the genome-wide pattern of origin selection . We have addressed this question in the fission yeast , taking advantage of a simplified cell cycle network in which cell proliferation is driven by a single cyclin-CDK module . This system allows us to precisely control CDK activity in vivo using chemical genetics . First , in contrast to previous reports , our results clearly show that distinct cyclin-CDK pairs are not essential for regulating specific subsets of origins and for establishing a normal replication program . Importantly , we then demonstrate that the timing at which CDK activity reaches the S phase threshold is critical for the organization of replication in distinct efficiency domains , while the level of CDK activity at the onset of S phase is a dose-dependent modulator of overall origin efficiencies . Our study therefore implicates these different aspects of CDK regulation as versatile mechanisms for shaping the architecture of DNA replication across the genome .
The accurate duplication of the genetic material relies on a multilayered control of the initiation of DNA synthesis at replication origins . Origins fire at characteristic times during S phase and are activated with particular frequencies , or efficiencies , in a population of cells . Together with the distribution of origins along the chromosomes , these parameters define the genome-wide program of DNA replication . This organization of genome duplication in replication timing and efficiency domains is a conserved feature among eukaryotes , and these programs are remarkably sensitive to developmental states as well as to external stimuli [1–4] . Interestingly , although there is accumulating evidence that the spatiotemporal pattern of DNA synthesis has consequences for cellular function beyond simply duplicating the genome [4 , 5] , we still do not understand the mechanisms by which cells establish and modulate specific replication programs . Central to the regulation of replication initiation are members of the cyclin-dependent kinase ( CDK ) family , which phosphorylate key components of the pre-replicative ( pre-RC ) and pre-initiation ( pre-IC ) complexes [6–10] . CDK functions require interactions with various cyclin partners , and oscillations in CDK activity drive cell cycle progression [6 , 11–13] . In particular , S phase onset occurs when a low threshold of CDK activity is attained during G1 [13] . Furthermore , proper regulation of CDK is critical for origin firing and genome maintenance [14–16] . However , despite the essential functions of CDK as well as our detailed knowledge of its regulators and targets , we know surprisingly little about how it may contribute to determining the genome-wide program of DNA replication . For instance , there is conflicting evidence from a variety of systems regarding the roles of multiple cyclin-CDK pairs in regulating replication initiation . On one hand , distinct cyclin-CDK complexes appear to have non-overlapping functions for genome duplication and to modulate particular subsets of origins in organisms ranging from budding yeast to mouse [17–22] . In contrast , a number of studies have questioned the absolute requirement for specific CDKs or cyclins in sustaining genome duplication [12 , 13 , 21 , 23 , 24] . Indeed , Cdk1 is sufficient to support cell proliferation in the early mouse embryo in the absence of all interphase CDKs [24] , and in budding yeast cells lacking the S phase cyclins , both early and late replication origins are fired during a delayed S phase [17] . Previous reports have also presented paradoxical outcomes of altering CDK function: both lowering CDK activity through chemical inhibition [21 , 25] and increasing activity via elevated cyclin levels or loss of a CDK inhibitor [14–16] result in reductions in replication initiation . Collectively , these findings highlight the complex and unresolved question of how the regulation of CDK activity , from the time it takes to reach the S phase threshold to its level at S phase entry , may shape the organization of genome duplication along the chromosomes . In the present study , we aimed to investigate the functions of these critical parameters of CDK activity in establishing the program of DNA replication . One impediment to addressing this question in vivo is the presence of multiple cyclin-CDK complexes , which makes it difficult to dissociate potential qualitative differences in substrate phosphorylation provided by different cyclin-CDK pairs from quantitative changes in the dynamics and levels of overall CDK activity . To circumvent this issue , we have applied a synthetic biology approach in the fission yeast , taking advantage of a system that replaces the endogenous cell cycle circuit with a simplified CDK module [13 , 26] . In wild-type Schizosaccharomyces pombe , cell cycle progression is controlled by oscillations in CDK activity that rely on the association of CDK ( Cdc2 ) with distinct cyclins ( Cig1 , Cig2 , and Puc1 for G1 and S; Cdc13 for mitosis ) . In contrast , the synthetic CDK module consists of a fusion between Cdc13 and Cdc2 that can autonomously drive cell proliferation in the absence of all other cell cycle cyclins [13] . These “minimal” cells display no detectable phenotypes , presenting the same length of S phase and cell cycle distribution as wild-type cells [13] . Critical to our investigations , the Cdc13-Cdc2 fusion protein harbors a mutation in its Cdc2 moiety that allows for reversible and dose-dependent modulation of its kinase activity by non-hydrolyzable ATP analogs [13 , 27] . Importantly , previous studies using this system have demonstrated a tight quantitative relationship between CDK activity and the level of inhibitor to which cells are exposed . These notably reported differences in substrate phosphorylation [28] , periodic gene expression [29] , cell cycle progression [13] , and cell size at division [30] that were dependent on the concentration of inhibitor applied . This powerful approach thus allows us to impose precise changes in a single CDK activity in vivo in order to explore the roles of the dynamics and levels of CDK activity in origin selection . Using this unique model , we began by evaluating whether qualitative inputs from multiple cyclin-CDK complexes are required to generate a normal profile of replication initiation . Our results revealed that the regional domains of origin timing and efficiency that are established by a single cyclin-CDK activity are virtually identical to those in wild-type cells . Next , we specifically manipulated two key parameters of CDK activity: 1 ) the timing at which sufficient activity is available for triggering S phase entry and 2 ) the level of CDK activity at the G1/S transition . First , we showed that the timing when CDK activity crosses the S phase threshold is critical for regulating the organization of origin firing in distinct domains along the chromosomes . Indeed , we demonstrated that prolonging G1 phase through transient CDK inhibition leads to a genome-wide redistribution of the Cdc45 replication factor and a reprogramming of replication initiation . Second , we found that CDK function has a clear quantitative impact on origin firing throughout the genome . Cells are exquisitely sensitive to changes in CDK activity at the G1/S transition , which result in dose-dependent alterations in replication initiation that affect the entire spectrum of origin efficiencies . Collectively , our results therefore demonstrate that the temporal and quantitative controls of CDK activity provide separate inputs whose integration is crucial for determining specific genome-wide programs of DNA replication .
While there is clear redundancy between distinct cyclin-CDK combinations in providing sufficient activity to trigger S phase [13 , 17 , 23 , 24] , evidence suggests that cyclin-CDK diversity may in fact be critical for origin selection [19 , 21 , 22] . Given these contrasting observations , we investigated the importance of operating with multiple cyclin-CDK pairs for the establishment of a wild-type profile of origin usage along the chromosomes . To this end , we used a simplified cell cycle control network in the fission yeast that consists of a fusion between the mitotic cyclin Cdc13 and the CDK Cdc2 ( referred to as Cdc13-Cdc2 ) . Oscillations in the activity of this Cdc13-Cdc2 module are sufficient to drive cell proliferation in the absence of other cell cycle cyclins , with no apparent changes in S phase onset or duration [13] . We first assessed the consequences of undergoing S phase in the absence of the G1/S cyclins Cig1 , Cig2 , and Puc1 , comparing the genome-wide pattern of origin usage in Cdc13-Cdc2 cells with that of cells containing the full complement of cyclins ( referred to as Control ) . For these experiments , we determined the program of origin selection in each background by synchronizing cells in G2 and allowing them to progress through mitosis and enter S phase in the presence of 12 mM hydroxyurea ( HU ) . HU limits the extent of replication around the sites of initiation , permitting the identification of origins and an assessment of their efficiencies [4 , 31] . For Cdc13-Cdc2 cells , G2 arrest was achieved by addition of 1 μM of the ATP analog 3-MBPP1 for 2 h 45 min at 32°C [13] . The inhibitor was then washed off to induce cells to synchronously re-enter the cycle ( Fig 1A , top panel and Fig 1B , left panel; see also [13] ) . Control cells were synchronized using the cdc25-22 temperature sensitive mutation [32]: cells were shifted to the non-permissive temperature of 36 . 5°C for 4 h , followed by a return to permissive temperature ( 25°C ) , resulting in a resumption of the cell cycle ( Fig 1A , bottom panel and Fig 1B , right panel ) . Genomic DNA was isolated prior to the release from G2 arrest ( unreplicated DNA ) and during S phase in HU-treated cells . For the latter , samples were collected at a time when bulk S phase is complete in the absence of HU ( Fig 1B ) . Replication origins were then mapped by competitive hybridization of differentially-labelled G2 and S phase samples to microarrays containing probes that cover the fission yeast genome [4] . Initiation sites were identified as peaks of increased copy number in the S phase samples , with the amplitude of the signal reflecting origin efficiency ( for instance , a copy number of 1 . 1 represents 10% efficiency ) [4 , 31] . This method has been previously validated [4 , 31] and generates profiles that are similar to those obtained with other approaches [33 , 34] . Remarkably , our results revealed highly comparable genome-wide profiles of origin usage in Control and Cdc13-Cdc2 cells ( Fig 1C and 1D , S1A Fig ) . Using a 10% efficiency cutoff , we identified similar numbers of origins , with over 91% of these sites being shared between the two programs ( S1B Fig , S1 Table ) . We then asked whether the absence of G1 and S cyclins specifically alters the efficiencies of particular origin subsets , as suggested by previous studies [17 , 21 , 22] . While we found a modest average difference of 4 . 2% in origin usage , this effect was observed across the entire range of origin activities ( Fig 1E ) . This pointed to a slight overall reduction in efficiencies in Cdc13-Cdc2 cells , rather than a targeted alteration of specific sites . Strikingly , regional analyses of origin usage assessing average efficiencies in continuous ~250 kb windows showed that the domains of low and high origin activity in Cdc13-Cdc2 are virtually identical to those in the Control ( Fig 1F ) . Our results therefore indicate that cyclin diversity is not required for the activation of specific groups of origins . Moreover , we provide the first demonstration , to our knowledge , that a single cyclin-CDK pair is sufficient for establishing an organization of replication initiation that is almost indistinguishable from that produced by the full complement of cyclins . Importantly , these data show that the Cdc13-Cdc2 background represents an ideal system for investigating the consequences of modulating CDK activity on the program of genome duplication . We next determined the impact of the temporal regulation of CDK on the replication program , ascertaining if the timing at which CDK activity reaches the S phase threshold plays a role in origin selection . To this end , Cdc13-Cdc2 cells initially arrested in G2 using 1 μM 3-MBPP1 were released to synchronously re-enter the cell cycle . After mitotic exit , these cells were exposed to 2 μM 3-MBPP1 for increasing periods of time ( Fig 2A ) : this concentration of inhibitor reduces CDK activity to a sufficiently low level to extend G1 and delay the onset of DNA replication ( Fig 2B ) . Cells were then released from this transient G1 arrest upon removal of the inhibitor and allowed entered S phase in the presence of HU . To assess the programs of origin efficiency associated with prolonged G1 phases , genomic DNA from the HU-treated cells in S phase was then competitively hybridized against unreplicated DNA samples collected just before the release from G1 ( see Fig 2B and the Materials and Methods section for details on the timings ) . Note that for these and all subsequent origin mapping experiments , we used 24 mM HU to prevent further extension of DNA synthesis around initiation sites . As a control for these conditions , we determined origin usage in Cdc13-Cdc2 cells synchronized in G2 as in Fig 1A but treated with 24 mM HU upon release ( referred to as G2B ) ; these data served as the reference for all analyses presented below . Our results uncovered striking changes in the profile of replication initiation upon alteration of the timing at which CDK activity crosses the S phase threshold ( Fig 2C and S2A Fig ) . First , we observed that increasing the length of G1 by 15 min led to both increases and decreases in origin usage ( S2B Fig , left panel ) in different regions of the genome ( Fig 2D; note that 15 min corresponds to a doubling of the duration of G1 , see Materials and Methods ) . To determine whether these changes in origin selection are specific to particular chromosomal domains , we compared the regional efficiency profile of G1+15 with that of cells released from G2 and progressing through a normal G1 ( G2B ) , assessing the differences in origin efficiencies in continuous ~250 kb windows across the genome . This identified a signature alteration of the replication program: origin activity was increased in regions of low efficiency , while origin usage in efficient domains was unchanged or modestly reduced ( Fig 2E , top panel ) . Even a 5 min extension of G1 displayed a reduction in the differences between high and low efficiency domains , although to a lesser extent ( G1+5; Fig 2E , bottom panel and S2B Fig , right panel ) . Consistent with these observations , we found strong negative correlations between the replication program in G2B and the changes in origin efficiencies that result from an extended G1 ( Fig 2E ) . Finally , to confirm our findings and rule out the possibility that these alterations in origin selection were due to differences in the duration of HU exposure between G2B and the G1 extensions , we ascertained origin usage in cells as for the G2B condition but maintained for an additional 30 min in HU ( see Materials and Methods for details ) . Our data established that origin efficiencies are not affected by the length of the HU treatment ( S2C Fig; see also S2 Table ) , confirming that a prolonged G1 phase leads to distinct changes in origin usage . All together , our results demonstrate a gradual equalization of origin activities between genomic regions when G1 is extended ( Fig 2F ) . Our findings thus provide evidence that the replication program is extremely responsive to delays in CDK function and that even modest changes in the timing of CDK availability have significant effects on the organization of DNA replication . We and others have previously shown that the timing and efficiency of origin usage is regulated by the recruitment of limiting initiation factors [35–37] . Therefore , in light of our results above , we evaluated the impact of delaying the availability of CDK activity on the formation of the pre-initiation complex . Cdc13-Cdc2 cells undergoing a synchronous S phase in the absence of HU after G2 arrest ( G2B ) or upon release from a 15 min G1 extension ( G1+15 ) were sampled from G1 through S phase , and the binding of the pre-IC component Cdc45 was assessed . For this assay , we tested three representative origins: ori2004 ( referred to as oriJW2084 in S1 Table ) , an efficient origin in G2B ( 45% ) and G1+15 ( 38% ) , as well as oriJW1072 and oriJW1088 , which are inefficient origins in G2B ( both 21% ) that become more efficient in G1+15 ( 29% and 36% , respectively ) . As expected , in cells undergoing a synchronous S phase after release from G2 arrest , we observed that Cdc45 binds to the efficient origin ori2004 at an earlier time than to the inefficient origins oriJW1072 and oriJW1088 ( Fig 3A , left panel ) . However , this was not the case in the G1+15 condition , where Cdc45 bound similarly to all three origins ( Fig 3A , right panel ) . These data suggest that extending G1 results in a redistribution of limiting replication components . We then asked whether these alterations in pre-IC formation occur throughout the genome and contribute to the changes in efficiencies that are observed after a G1 extension . To this end , we performed chromatin immunoprecipitation followed by microarray analysis ( ChIP-chip ) of Cdc45 in the G2B and G1+15 conditions . For these experiments , cells were collected at the G1/S transition , when Cdc45 recruitment reaches a maximum at early-firing origins ( Fig 3A ) . First , we observed that Cdc45 is bound at initiation sites in both situations ( S3A–S3D Fig ) and that the levels of Cdc45 at origins are strongly correlated with origin efficiencies ( Fig 3B ) . Next , we performed regional analyses of Cdc45 binding and demonstrated that there is a striking equalization of Cdc45 recruitment between distinct genomic regions ( Fig 3C and S3E Fig ) : the differences in the levels of Cdc45 at origins between replication domains are reduced , similar to what we observed for efficiencies . This is also illustrated in S3F Fig , which shows very different distributions for the deviations of the regional profiles of origin efficiencies and Cdc45 from their corresponding means in G1+15 compared to G2B . Furthermore , we established a remarkable correspondence between the regional profiles of origin efficiencies and Cdc45 binding ( Fig 3D ) , with Spearman’s rank correlation coefficients that showed very strong positive relationships between these parameters in both the G2B and G1+15 conditions . Our results therefore indicate that the temporal control of CDK activity alters the competition between initiation sites for limiting replication factors , thereby regulating pre-IC assembly and subsequent origin usage . As short delays in the timing of CDK availability ( 5 and 15 min in our assays ) are sufficient to induce alterations in the genome-wide profile of origin usage , we next addressed the extent to which an increase in G1 length can affect the replication program . For this experiment , we modified the procedure for the CDK delay conditions described above ( Fig 2A ) and treated a synchronized population of Cdc13-Cdc2 cells that have undergone mitotic exit with 2μM 3-MBPP1 for 30 min , followed by further incubation with 20 μM 3-MBPP1 ( Fig 4A ) . This enabled us to keep CDK activity below the S phase threshold for a much longer period of time . Cells were maintained in these conditions for a total of 180 min after mitotic exit , during which replication did not occur , and then released from this high concentration of 3-MBPP1 ( Fig 4B; this represents a 165 min extension of G1 , referred to as G1+165 ) . As previously characterized , the Cdc13-Cdc2 protein accumulates during a long G1 arrest , and rapid change to inhibitor-free medium leads to simultaneous entry into S and M phases due to the rapid increase of CDK activity to mitotic levels [13] . To prevent this lethal phenotype , we triggered cells cycle re-entry in our assay by switching from 20 μM to 1 μM 3-MBPP1 , which permits S phase onset while inhibiting mitosis . We emphasize that in all of the following experiments , cells undergo S phase without subsequent mitotic entry . To assess origin efficiencies , the cells released from this long G1 extension were allowed to enter S phase in the presence of HU . Genomic DNA from cells collected before the release from G1 was then hybridized against that from the HU-treated cells in S phase ( see Fig 4B and the Materials and Methods section for details on the timing of sampling ) . Intriguingly , our data demonstrate that even with a substantially longer delay of 165 min in S phase onset , the pattern of origin efficiencies along the chromosomes was similar to that of G1+15 ( Fig 4C and S4A Fig ) . Regional analyses of the changes in replication induced by the G1+165 vs . G1+15 conditions showed a comparable reorganization of genome duplication ( Fig 4D ) , with only a slightly greater equalization between efficiency domains and higher overall efficiencies in G1+165 ( Figs 4E and S4B and S4C ) . In these conditions , we also observed an alteration in Cdc45 recruitment to representative origins , similar to what we found for G1+15 ( S4D Fig ) . These data indicate that the dramatic reprogramming of DNA replication that results from regulating the timing of CDK activity is largely completed in a short period of time , implying a high degree of versatility in generating different replication profiles upon relatively limited alterations in G1 length . Collectively , our results demonstrate that the timing at which CDK activity reaches the threshold for S phase entry is a sensitive parameter that can be finely modulated to induce major changes in the regional organization of DNA replication . Finally , we ascertained the quantitative effect of CDK activity on the replication program . Our unique system enables us to uncouple the timing of CDK function from its activity level , inducing cells to initiate DNA synthesis with a range of CDK activities while maintaining the same G1 length . This contrasts with previous studies in which increasing CDK activity during G1 did not necessarily result in greater activity at the start of S phase but rather in advanced S phase entry [14 , 16] . For our experiments , origin usage was assessed in cells released from a 165 min G1 arrest ( as in Fig 4A ) into different concentrations of the 3-MBPP1 inhibitor ( 1 , 2 . 5 , 4 , and 6 μM; these will be referred to as S1—the same as G1+165 , S2 . 5 , S4 , and S6 ) . Note that the higher the inhibitor concentration , the lower the CDK activity . As mentioned earlier , these conditions result in S phase entry but do not permit mitosis , allowing us to evaluate origin efficiencies in cells that undergo DNA replication with different levels of CDK activity . First , we observed that while S phase onset occurred at similar times in all conditions , decreasing CDK activity was associated with a progressive extension of S phase duration ( Fig 5A ) . For origin efficiency assessments , cells were then released from G1 arrest as above but in the presence of HU . Unreplicated DNA from samples collected before G1 release were then hybridized against those from the HU-treated cells in S phase ( see Fig 5A and the Materials and Methods section for details on the timing of sampling in the different conditions ) . Our genome-wide studies of replication initiation in these assays showed that origin efficiencies are highly responsive to the levels of CDK activity: lowering this activity at the G1/S transition led to a dose-dependent reduction in overall origin usage ( Figs 5B and S5A ) . Importantly , we demonstrated that replication initiation across the entire range of efficiencies was affected ( Figs 5C and S5B ) , with progressively greater reductions as CDK activity is further inhibited ( S5C Fig ) . These findings are supported by DNA combing experiments that showed an increase in interorigin distances in S6 compared to S1 , consistent with the decrease in origin efficiencies ( S5D Fig ) . Finally , in contrast to the effects of altering the timing of CDK function , all chromosomal regions responded similarly to the changes in CDK activity levels , and the replication pattern along the chromosomes was maintained ( Fig 5D ) . We thus conclude that the level of CDK activity at S phase onset is a direct and quantitative regulator of absolute origin efficiencies throughout the genome . All together , our results imply that specific replication programs are brought about by a combination of 1 ) the timing at which CDK activity triggers S phase onset and 2 ) the level of CDK activity at this critical transition . Independent modulation of these two parameters could therefore allow for the generation of a spectrum of replication patterns . Conversely , the same profile may be produced by different combinations of CDK timing and activity . To test this possibility , we compared the replication program after a short G1 prolongation ( G1+15 ) with that obtained by modulating the level of CDK activity at G1/S after an extended G1 delay ( in particular S2 . 5 ) . Our analysis showed that origin efficiencies in these two conditions are highly comparable ( S5E Fig ) and that the regional replication profiles are virtually identical ( Fig 5E ) , despite the vastly different experimental setup . This observation raises the intriguing possibility that depending on the environmental and physiological conditions , similar programs may be achieved by integrating different quantitative and temporal settings for CDK activity .
While CDK activity is undoubtedly the essential driver of cell cycle progression , remarkably little is known about how the regulation of this activity may affect the organization of genome duplication along the chromosomes . In this study , we have investigated the impact of two key features of CDK function—when it triggers S phase entry and how much activity is present at the onset of S phase—on the genome-wide program of DNA replication . Using a unique system in the fission yeast , we first show that different combinations of cyclin-CDK pairs are not required to regulate particular groups of origins and that a single qualitative CDK activity is sufficient to produce a normal profile of origin usage . Importantly , we then take advantage of this model to demonstrate that the timing at which CDK activity crosses the S phase threshold is a critical input for the organization of replication in distinct efficiency domains along the chromosomes ( Fig 6 , top ) . Notably , we find that prolonging the length of G1 induces alterations in pre-IC formation that are linked to an equalization in origin usage between genomic regions . Next , our results establish that the level of CDK activity as cells enter S phase is an extremely sensitive dose-dependent modulator of genome-wide origin efficiencies ( Fig 6 , bottom ) . Our work therefore provides evidence for CDK regulation as a versatile mechanism by which cells program DNA replication , uncovering a fundamental link between the central player in cell cycle progression and the architecture of genome duplication . Our findings imply that the timing and level of CDK activity can be independently controlled to achieve a broad spectrum of origin usage profiles . Although we have modulated these parameters through the use of a targeted CDK inhibitor in our experiments , such regulation in a natural context may be conferred in part by cyclin and CDK diversity . Thus , the presence of multiple cyclin-CDK pairs , which have different expression , degradation , and activation programs [6] , may in fact provide the precise timing and overall CDK activity levels that shape DNA replication . Our model would therefore reconcile the contrasting observations from previous reports regarding the requirement for multiple cyclin-CDK pairs in origin selection [17–22]: the specific effects of distinct cyclin-CDK combinations described in these studies may result from changes in the overall timing and level of CDK function rather than from qualitative differences in the phosphorylation of particular substrates by non-redundant complexes . Interestingly , the natural diversity in cyclin-CDKs may provide flexibility to produce complex activity profiles , leading to context-specific modulations of DNA replication . This may for instance enable cells to rapidly adapt to changes in environmental conditions or internal physiological states , potentially inducing alterations in the organization of genome duplication as part of these responses . Given the importance of ensuring the high fidelity duplication of the genetic material , why would the program of replication be so flexible and sensitive to alteration ? One possibility is that it may not be particularly important for cells to undergo DNA synthesis in specific ways as long as the genome is fully copied and transmitted . On the other hand , replication domains are a general feature of eukaryotic replication , and cell-type specific conservation of replication timing has been observed in syntenic regions in mouse and human cells [38] . This suggests a functional importance for the organization of DNA replication , an idea that is supported by our earlier work which revealed a role for the replication program in determining the pattern of meiotic recombination in the fission yeast [4] . Furthermore , flexibility in origin usage may promote the coordination of genome duplication with other processes . This may , for instance , act in parallel with mechanisms that prevent and resolve conflicts between the replication and transcription machineries [39 , 40] . As CDK activity has been shown to drive the waves of gene expression that are associated with different cell cycle phases [29 , 41] , it may be a particularly appropriate input for co-regulating origin selection and transcription during G1/S . Intriguingly , the three-dimensional organization of the chromosomes in complex eukaryotes is remodeled in early G1 , when topologically associating domains ( TADs ) are established [42 , 43] . The concomitant organization of the replication timing program as well as the overlap between replication domains and TADs in these systems highlight chromosome conformation as a potential regulator of origin selection . Interestingly , changes in chromosomal organization during the cell cycle have also been reported in the fission yeast [44] . In the context of our study , modulating CDK activity to prolong G1 , when large-scale changes in chromosome structure occur , may render particular genomic regions more accessible for assembling replication complexes . This may facilitate a redistribution of replication factors between domains and lead to an equalization of genome-wide origin usage . The overall CDK activity at S phase onset would then represent an additional layer of control that sets the level of efficiencies across the genome . As G1 phase is a sensitive period during which pivotal cell fate decisions are made [45] , one appealing suggestion is that the role of CDK in organizing DNA replication may be a vital element in these physiological transitions . CDK regulation is highly conserved throughout eukaryotes and central to a variety of cellular and developmental processes , including the response to environmental challenges [46] . It is therefore uniquely positioned to integrate the external conditions and intrinsic signals that establish the cellular state , and the capacity of CDK activity to organize genome duplication may be a crucial aspect of its function .
Standard media and methods for fission yeast were used [47 , 48] . All experiments were carried out in minimal medium plus supplements ( EMM6S ) at 32°C , except when otherwise noted . The 3-MBPP1 inhibitor ( A602960 , Toronto Research Chemicals Inc . , Canada ) was dissolved in DMSO at a stock concentration of 10 mM and added to cultures at the indicated concentrations . The Schizosaccharomyces pombe strains used in this study are shown in Table 1 . Synchronization of cells operating with the analog-sensitive fusion protein ( Cdc13-Cdc2 ) was performed as previously described [13] . Specifically , exponentially growing cultures were treated with 1 μM 3-MBPP1 for 2 h 45 min at 32°C , which results in a G2 block . Synchronous entry into the cell cycle was then achieved by removing the inhibitor through filtration of the cultures and 3 successive washes with pre-warmed EMM6S . For the Control experiments ( Fig 1 , S1 Fig ) , temperature-sensitive cdc25-22 mutants were grown at permissive temperature ( 25°C ) , shifted to restrictive temperature ( 36 . 5°C ) for 4 h for G2 arrest , and then released to 25°C for re-entry into the cell cycle [32] . Note that the lengths of cell cycle phases , including the duration of S phase , cannot be directly compared between the Cdc13-Cdc2 and Control backgrounds as they re-enter the cell cycle after G2 block at very different temperatures ( 32°C and 25°C , respectively ) . For the short G1 delay experiments ( G1+5 and G1+15; Figs 2 and 3 , S2 and S3 Figs ) , analog-sensitive Cdc13-Cdc2 cells were synchronized as above and then treated with 2 μM 3-MBPP1 16 min after the initial release from the G2 block , once cells have passed the metaphase to anaphase transition [13] . This treatment arrests cells in G1 , preventing S phase onset . The cultures were then released from this G1 block by washing off the inhibitor after 20 min ( G1+5 ) and 30 min ( G1+15 ) of treatment . To estimate the length of the G1 extensions , we considered that in non-G1-arrested cells , mitotic exit has occurred by 15 min after the release from G2 and that S phase starts another 15 min later [13] . Thus , the 20 min treatment with 3-MBPP1 represents a ~5 min extension of G1 ( G1+5 ) , while the 30 min condition results in a ~15 min prolongation ( G1+15 ) . To induce a longer delay in G1 ( G1+165 , Fig 4 ) as well as to allow cells to enter S phase with different CDK activities ( Fig 5 ) , a variation of the above protocol was used . As cells accumulate the Cdc13-Cdc2 fusion protein during a prolonged G1 arrest [13] , the cultures initially released from G2 were kept in 2 μM 3-MBPP1 for 30 min and subsequently treated with 20 μM inhibitor . This enabled us to maintain CDK activity below the S phase threshold for much longer periods of time . For our assays , cells were grown in these conditions for another 150 min ( 165 min extension of G1 ) , during which replication did not occur ( Figs 4B and 5A ) , and then released by filtration in medium containing various concentrations of inhibitor ( 1 , 2 . 5 , 4 , or 6 μM ) . Importantly , it was previously shown that rapid change to inhibitor-free medium after a long G1 block leads to simultaneous entry into S and M phases due to the high level of CDK activity; however , releasing cells into 1 μM 3-MBPP1 prevented this from occurring [13] . Thus , by allowing cells to re-enter the cycle with 1 , 2 . 5 , 4 , or 6 μM 3-MBPP1 in these conditions , we permitted S phase entry while inhibiting mitosis . Note that in these experiments , cells enter S phase after G1 and therefore undergo a normal round of genome duplication . For DNA content analysis , cells were fixed in 70% cold ethanol , washed in 50 mM sodium citrate and treated with RNase A ( 0 . 1 mg/ml ) . Samples were then stained using 2 mg/ml propidium iodide , sonicated , and analyzed using a BD Accuri C6 flow cytometer ( BD Biosciences , Franklin Lakes , NJ , USA ) and the Flowjo analysis software ( FlowJo LLC , Ashland , OR , USA ) . Note that in contrast to a number of model systems , the fission yeast cell cycle displays a short G1 phase , with S phase occurring prior to cytokinesis . Cells therefore have a 2C DNA content during most of their life cycle: in proliferating cells , genome duplication takes place in binucleated cells , giving rise to a transient 4C peak that is then resolved upon cytokinesis . In asynchronous cultures , this 4C peak is barely detectable due to the low percentage of cells undergoing DNA replication at any given time in such populations . Conversely , an elongation of G1 / delay in S phase onset leads to cytokinesis taking place prior to DNA replication and produces a 1C peak . For the flow cytometry profiles in this study , the time points when cells were considered to be undergoing bulk S phase were assessed based on 1 ) the position of the peak of the major population of cells and 2 ) the presence of a shoulder to the left of the main peak . For Fig 1B ( release from G2 arrest ) , this shoulder corresponds to cells with DNA contents between 2C and 4C , indicating ongoing DNA synthesis; note that cell division gives rise to 2C cells . For Figs 2B , 4B and 5A ( G1 extension ) , cells with DNA contents between 1C and 2C indicate ongoing DNA synthesis . Origin mapping was performed using Agilent 4x44k S . pombe arrays ( 60-mer oligonucleotides every ~250 nucleotides; Agilent Technologies , Santa Clara , CA , USA ) as previously described [4] . Competitive hybridization of differentially labeled samples of non-replicating cells vs . cells undergoing DNA synthesis in hydroxyurea ( HU; Sigma-Aldrich , St . Louis , MO , USA ) was used to determine copy number . The use of HU limits DNA synthesis around the initiation sites , thus permitting the identification of replication origins . Previous studies have validated this method [4 , 31] , which generates origin maps that are comparable to those obtained with other approaches [33 , 34] . Cells in HU were harvested at a time when bulk S phase would normally be completed in the absence of HU . This was determined for each condition , as shown in Figs 1B , 2B , 4B and 5A . In the Control , 12 mM HU was added when cells were released from the cdc25-22 G2 arrest , and samples were collected 90 min later . Cells were harvested at the release from G2 for the unreplicated DNA sample . For initial mapping of origins in Cdc13-Cdc2 cells ( Fig 1 ) , 12 mM HU was added 10 min after the release from a G2 block , and cells were collected 60 min later ( a total of 70 min after the release ) . For the unreplicated DNA sample , Cdc13-Cdc2 cells were collected 5 min before the release from G2 . For all experiments in which the length of G1 was prolonged ( Figs 2–5 , S2–S5 Figs ) , cells were treated with 24 mM HU . Indeed , when 12 mM HU was used in initial G1 extension experiments , we observed broader peaks around initiation sites and the merging of origins; the use of 24 mM HU prevented this further extension of DNA synthesis . As a control for these analyses , we synchronized Cdc13-Cdc2 cells in G2 as above , added 24 mM HU 10 min after the release from G2 , and collected samples for origin mapping 60 min after addition of HU ( this condition is referred to as G2B; samples for unreplicated DNA were collected 5 min before the release from G2 ) . For the G1+5 and G1+15 conditions , 1 ) 24 mM HU was added 10 min before the G1 release , 2 ) samples for unreplicated DNA were collected 5 min later , 3 ) cells were then released from G1 in the presence of 24 mM HU , and 4 ) cells were harvested after 60 min . For the G1+165 arrest ( identical to the S1 condition ) , we used a similar protocol as for G1+5 and G1+15 except that cells were released from G1 in the presence of 24 mM HU + 1 μM 3-MBPP1 to prevent mitosis [13] . S phase samples were collected 30 min later . For S2 . 5 , S4 , and S6 , the same protocol was used with the indicated concentrations of 3-MBPP1 . Samples were then collected at the following times after G1 release: 2 . 5 μM—40 min , 4 μM—45 min , and 6 μM—60 min . These different timings accommodate the changes in S phase length in these experiments ( Fig 5A ) . To exclude the possibility of a bias in our method due to maintaining cells for different periods of time in HU , we assessed whether the duration of HU exposure has an effect on origin efficiencies . To this end , we collected samples from Cdc13-Cdc2 cells released from G2 arrest and maintained in 24 mM HU for 30 min longer than the time indicated for G2B above ( cells were therefore collected 90 min after HU addition; referred to as G2B+30 ) . Our data showed that this does not alter the replication program and that any differences in origin efficiencies between G2B and G2B+30 are not statistically significant ( S2 Table , S2C Fig ) . Our results are consistent with previously published data showing that the length of HU treatment does not alter origin usage profiles [31] . These findings therefore demonstrate that the changes in origin usage that we observe in our study are not due to differences in the duration of HU exposure . For microarray experiments , genomic DNA was extracted [49] and purified using the Qiagen Genomic DNA kit ( Qiagen , Hilden , Germany ) . Samples were labeled using the BioPrime Plus Array CGH Indirect Genome Labeling Kit ( Invitrogen , Carlsbad , CA , USA ) with either Alexa 555/647 ( Thermo Fisher Scientific , Waltham , MA , USA ) or Cy3/Cy5 ( GE Healthcare , Little Chalfont , UK ) dyes , and 1–2 μg of DNA from the unreplicated and S phase samples were hybridized onto the microarrays . To determine copy number , the geometric means over five consecutive probes were determined throughout the genome for two independent hybridizations of the same samples using a dye-swap , thereby limiting noise and dye bias . The datasets were averaged , and the outliers removed . For each experiment , two biological repeats were performed and averaged . For analysis and comparison of origin efficiencies , the baselines between different conditions , representing unreplicated DNA , were matched and set to 1 . For this correction , we surmised that 1 ) as cells are in HU , there are genomic regions that remain unreplicated in our S phase samples and 2 ) the unreplicated regions of the genome have the lowest values in each dataset . Thus , for each averaged dataset of biological repeats , we took the lowest 10% of the ratios of replicated/unreplicated DNA , calculated their median , and normalized the dataset to this value . The following correction factors were applied: Control , 0 . 17; Cdc13-Cdc2 , 0 . 13; G2B , 0 . 1; G2B+30 , 0 . 12; G1+5 , 0 . 18; G1+15 , 0 . 18; G1+165/S1 , 0 . 18; S2 . 5 , 0 . 2; S4 , 0 . 15; S6 , 0 . 15 . S1 Table provides the list of origins and efficiencies in all analyzed conditions . For origin identification in Control ( cdc25-22 ) and Cdc13-Cdc2 cells ( Fig 1 , S1 Table ) , we determined the moving geometric means over five consecutive probes along the chromosomes for each dataset representing the average of two biological repeats . This procedure was then repeated on the resulting datasets for a total of 10 rounds of smoothing . Origins were then identified by the peaks where the copy number ratio of replicated ( in HU ) vs . unreplicated was greater than 1 . 05 , representing a clear increase over the background after smoothing . Their positions were attributed based on the local maxima followed by visual confirmation . Once the coordinates of the origins were determined , their efficiencies were obtained from the non-smoothed datasets , and a threshold of 1 . 1 for the copy number was applied . This was further confirmed by visual analysis of the data . When two origins were less than 5 kb apart , they were considered as a single origin and assigned to the position with the higher copy number . This approach is validated by the observation that the extent of replication surrounding an origin in HU can reach 10–15 kb [31] . To compare origin numbers , efficiencies , and positions between two experiments , peaks identified in each dataset were matched in position [4] . Indeed , the precise location of the same origin can vary slightly between experiments , due in part to the resolution of the microarrays and to the extension of replication beyond the initiation sites in these assays . Therefore , when peaks in two different datasets were within a distance of less than 5 kb , they were considered to be the same origin . For the comparisons of origin efficiencies in Figs 2–5 and S2–S5 Figs , we further refined our origin list . Indeed , as we observed an induction of some inefficient origins in the presented conditions , we visually inspected the averaged and baseline-corrected G1+165/S1 dataset and noted origins with a copy number ≥ 1 . 1 that were not in our initial list . This resulted in an additional 48 origins that were then added to the list identified in Cdc13-Cdc2 above ( S1 Table ) . For the analyses in Figs 2–5 , we therefore used the positions of this larger set of 670 origins and assigned the local maximum values in regions of 5 probes surrounding each origin as their efficiencies . To determine the regional profiles of origin usage ( Figs 1F , 2E , 2F , 3D , 4D , 4E , 5D , 5E , S2D and S5F ) , the averages of origin efficiencies were determined for continuous windows of ~250 kb ( 1000 probes ) along each chromosome . To evaluate the regional differences in origin usage between different conditions ( Figs 2E and 4E , S2D Fig ) , the differences of the averages in origin efficiencies were determined for continuous windows of ~250 kb ( 1000 probes ) . In addition to the controls described above , we further demonstrated the reproducibility of our methodology for the determination of origin efficiencies and the analysis of differences between the replication program in distinct conditions . First , we established that the individual repeats performed for each condition were highly reproducible ( S6 Fig ) . To this end , we calculated the Spearman’s rank correlation coefficient for each pairwise comparison of repeats and found very strong positive correlations ( p-value < 0 . 001 ) . Complementary to this , we conducted independent samples T-tests ( two-sided ) and showed no differences between repeats for all of the conditions used in this study ( S2 Table ) except for S6 ( see below ) . Second , we demonstrated using independent samples T-tests that in contrast to repeat experiments , origin efficiencies in distinct conditions were significantly different ( S2 Table ) . Finally , we determined the regional profiles of origin usage for all of the conditions presented in Figs 2–5 using origin mapping data from individual repeats . These results are displayed in S2D and S5F Figs and reveal virtually identical profiles for both experiments of each condition . We note that a modest difference is observed between the two repeats of S6; this is also suggested by the statistical tests in S2 Table . In this condition , the low level of CDK activity after release from G1 may only be slightly above the S phase threshold , making cells more sensitive to minor experimental variations . All together , we conclude that our methodology for determining origin efficiencies is highly reproducible and robust . Chromatin immunoprecipitation experiments were performed as previously described [35] . Cells were fixed with 1% formaldehyde , lysed in a FastPrep cell disruptor ( MP Biomedicals , Santa Ana , CA , USA ) and sonicated with a Bioruptor Plus ( Diagenode , Seraing , Belgium ) to obtain chromatin fragments of ~400–500 bp . The immunoprecipitations ( IP ) of Cdc45 were carried out overnight at 4°C using an α-GFP antibody ( gift from the Nurse lab , diluted 1/2500 ) . Protein G sepharose beads ( GE Healthcare , Little Chalfont , UK ) or protein G Dynabeads ( Thermo Fisher Scientific , Waltham , MA , USA ) were then added to the samples and incubated for 4 h at 4°C . IPs were then washed and eluted , and crosslinking was reversed for both IP and Input samples by overnight incubation at 65°C . For quantitative PCR assays , IP and Input DNA were mixed with SYBR Green qPCR Master Mix ( Agilent Technologies , Santa Clara , CA , USA ) and processed with an ABI 7900 HT ( Applied Biosystems , Foster City , CA , USA ) . A biological repeat was performed for each experiment . Primers used in this study are listed in Table 2 . For Cdc45 ChIP-chip assays , 100 mL of cells were collected at G1/S in the G2B and G1+15 conditions; this was determined as the time when peak Cdc45 binding was observed at early-firing origins ( Fig 3A ) . For G2B , this corresponds to 30 min after release from G2 arrest; for G1+15 , cells were collected 3 min after release from the prolonged G1 . Note that for these experiments , cells were released into medium without HU . ChIPs were performed as described above using a 1:1000 dilution of the α-GFP antibody and Protein G Dynabeads ( Thermo Fisher Scientific , Waltham , MA , USA ) . For amplification of the ChIP material and labeling for hybridization , the protocol from [50] was used according to [4] . Each ChIP was then hybridized against its reciprocally labeled Input sample ( IP/Input ) . Two biological repeats were performed for each experiment . For all quantitative analyses , probe values were directly used . For visual representation in S3 Fig , the moving geometric means of five consecutive probes were calculated across the genome , and the average of the two experiments were plotted . These profiles show that the sites of Cdc45 binding coincide with origins . For the analyses of Cdc45 binding in Fig 3B–3D , the Cdc45 levels at origins were determined as follows: for each origin , we took the highest Cdc45 value within a distance of 3 probes of the origin position . To determine the regional profiles of Cdc45 binding ( Fig 3C and 3D ) , we averaged the Cdc45 values assigned to origins over continuous windows of ~250 kb ( 1000 probes ) along each chromosome . Samples for DNA combing were collected for the S1 and S6 conditions . For these experiments , cells containing the nucleotide transporter ( hENT ) and thymidine kinase ( hsvTK ) that allow for incorporation of BrdU into replicating DNA [51] were used ( JW1045 ) . Culture conditions were as in Fig 4A , except that 2 μM BrdU ( Sigma-Aldrich , St . Louis , MO , USA ) was added to the culture medium at the same time as 24 mM HU , 10 min before the release from G1 into the corresponding 3-MBPP1 concentrations . Cells were then collected at the same time as for the microarray experiments , at 30 min and 60 min after the release from a long G1 block for S1 and S6 , respectively . The protocol for the preparation of fibers for DNA combing was as described in [52] . Briefly , cells were treated with 0 . 1% NaN3 and washed with 50mM EDTA pH = 8 and 0 . 1% NaN3 . Cells were then recovered in SP1 ( 1 . 2 M D-Sorbitol , 50 mM Citrate phosphate pH 5 . 6 , 40 mM EDTA pH 8 ) containing 1 μg/μL Zymolyase ( AMS Biotechnology , Abingdon , UK ) and 0 . 3 μg/μL Lysing enzymes ( Sigma-Aldrich , St . Louis , MO , USA ) . This mixture was combined with 2% Low Melting Agarose ( Bio-Rad , Hercules , CA , USA ) in SP1 with 0 . 2% NaN3 , poured into plug molds for pulsed-field gel electrophoresis , and digested at 37°C for 30 min . Agarose plugs were then incubated twice for 30 min at 50°C in DB250X ( 10 mg/mL N-Lauroylsarcosine sodium salt ( Sigma-Aldrich , St . Louis , MO , USA ) , 1 mg/mL Proteinase K ( Roche , Basel , Switzerland ) , 0 . 25 M EDTA pH 9 . 5 , 10 mM Tris-HCl pH 9 . 5 ) , followed by two overnight incubations in DB500X ( 10 mg/mL N-Lauroylsarcosine sodium salt , 1 mg/mL Proteinase K , 0 . 5 M EDTA pH 9 . 5 , 10 mM Tris-HCl pH 9 . 5 ) at 50°C . They were then washed twice in TE 100X pH 7 . 5 with 100 mM NaCl , three times in TE 1X pH 7 . 5 , 100 mM NaCl , and once in MES 50 mM pH 5 . 5 with 100 mM NaCl . Plugs were melted in MES 50 mM pH 5 . 5 with 100 mM NaCl in Teflon combing receptacles ( Genomic Vision , Bagneux , France ) at 70°C for 1 h , followed by β-agarase ( New England Biolabs , Ipswich , MA , USA ) digestion overnight at 42°C . DNA was combed on silanized coverslips using the Genomic Vision Molecular Combing System ( Genomic Vision , Bagneux , France ) . The immunodetection protocol used was as described in [53] . Fibers were fixed to coverslips at 65°C overnight , dehydrated using ethanol , and denatured in NaOH . Coverslips were incubated in PBST ( Phosphate buffered saline , 0 . 1% Triton X-100 ) with 1% BSA , followed by sequential incubation with the following antibodies diluted at the indicated concentrations in PBST + 1% BSA: α-BrdU , mouse , IgG1 ( 1:20; Becton Dickinson , Franklin Lakes , NJ , USA ) ; goat anti-mouse IgG1 , Alexa 546 ( 1:50; Molecular Probes , Eugene , Oregon , USA ) ; α-ssDNA , mouse , IgG2a ( 1:50; Merck , Darmstadt , Germany ) ; goat anti-mouse IgG2 , Alexa 488 ( 1:50; Molecular Probes , Eugene , Oregon , USA ) . Coverslips were washed 5 times for 2 min with PBST between antibody incubations . Dako fluorescence mounting medium ( Agilent Technologies , Santa Clara , CA , USA ) was then added to samples prior to imaging . Imaging was performed using a 63x objective on an inverted Zeiss Axio Observer ( Carl Zeiss AG , Oberkochen , Germany ) equipped with a Lumencor Spectra X illumination system ( Lumencor Inc . , Beaverton , OR , USA ) . Images were acquired with a Hamamatsu Orca Flash 4 . 0V2 sCMOS camera ( Hamamatsu Photonics , Hamamatsu City , Japan ) via the VisiView software ( Visitron Systems GmbH , Puchheim , Germany ) . Fibers were analyzed using Fiji and the Pointpicker plugin . Based on previous studies [54] and our control experiments , a threshold of 0 . 6 kb ( 3 pixels ) was used as a minimum for positive BrdU staining , and a cutoff of 3 kb ( 15 pixels ) was used to identify stretches of non-BrdU labelled DNA . For S1 , we analysed 281 interorigin distances ( IODs ) in 30 fibers totaling 8351 kb; for S6 , we analyzed 242 IODs in 32 fibers totaling 10539 kb ( S5D Fig ) . Statistics were performed using R Studio . Differences in origin usage between repeats of a given condition and datasets for distinct conditions were analyzed by conducting independent-samples T-tests ( two-sided ) ( S2 Table ) . These assessments showed that the alterations in origin usage observed upon modulating CDK timing and activity are statistically significant , while this is not the case for individual repeats of a given condition . The Spearman’s rank correlation coefficient was evaluated for the comparisons in Figs 1F and 2E , Figs 3B , 3D and S6 . For DNA combing analysis , differences in interorigin distances between conditions were evaluated by conducting independent-samples T-tests ( two-sided ) ( S5D Fig ) . The array data reported in this paper have been deposited in the NIH GEO database and has been assigned the accession number GSE88714 .
|
The duplication of the genetic material is a highly conserved and tightly regulated process that is essential for cell proliferation . DNA synthesis initiates at sites called origins that are distributed throughout the genome . Replication origins are not all used equivalently , and their patterns of activation along the chromosomes give rise to specific profiles , or programs , of DNA replication . These programs change during development and in response to external stimuli , and we have previously shown that they have important consequences for cellular function . However , we still do not understand the mechanisms by which cells establish different replication patterns . Here we investigate the role of the cyclin-dependent kinase ( CDK ) family of proteins , whose activities are critical for cell cycle progression , in regulating the organization of genome duplication . Taking advantage of a system that allows us to precisely modulate CDK activity levels in living cells , we demonstrate that both the temporal and quantitative controls of CDK function are crucial for determining distinct programs of DNA replication . Our work therefore uncovers a fundamental link between CDK activity , a central input in a variety of cellular and developmental processes , and the architecture of genome duplication .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"nucleic",
"acid",
"synthesis",
"cell",
"cycle",
"and",
"cell",
"division",
"cell",
"processes",
"fungi",
"model",
"organisms",
"dna",
"replication",
"experimental",
"organism",
"systems",
"dna",
"mammalian",
"genomics",
"synthesis",
"phase",
"schizosaccharomyces",
"dna",
"synthesis",
"chemical",
"synthesis",
"research",
"and",
"analysis",
"methods",
"genome",
"complexity",
"schizosaccharomyces",
"pombe",
"animal",
"genomics",
"biosynthetic",
"techniques",
"yeast",
"biochemistry",
"eukaryota",
"cell",
"biology",
"nucleic",
"acids",
"genetics",
"biology",
"and",
"life",
"sciences",
"yeast",
"and",
"fungal",
"models",
"genomics",
"computational",
"biology",
"organisms",
"cyclins"
] |
2018
|
CDK activity provides temporal and quantitative cues for organizing genome duplication
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.