Mitogen-activated protein kinase 4 (MPK4) interacts with the (Mitogen-activated protein kinase kinase kinase 1) MEKK1/ Mitogenactivatedprotein kinase kinase 1 (MKK1)/ Mitogen-activated protein kinase kinase 2 (MKK2) complex to affect its function in plantdevelopment or against pathogen attacks. The KEGG (Kyoto Encyclopedia of Genes and Genomes) network analysis of Arabidopsisthaliana revealed close interactions between those four genes in the same plant-pathogen interaction pathway, which warrants furtherstudy of these genes due to their evolutionary conservation in different plant species. Through targeting the signature sequence inMPK4 of papaya using orthologs from Arabidopsis, the predicted sequence of MPK4 was studied using a comparative in silicoapproach between different plant species and the MAP cascade complex of MEKK1/MKK1/MKK2. This paper reported that MPK4was highly conserved in papaya with 93% identical across more than 500 bases compared in each species predicted. Slight variationsfound in the MEKK1/MKK1/MKK2 complex nevertheless still illustrated sequence similarities between most of the species.Localization of each gene in the cascade network was also predicted, potentiating future functional verification of these genesinteractions using knock out or/and gene silencing tactics. Defense mechanisms in plants towards pathogens infection lay ina complicated web of multiple genes interactions in the defenseresponse pathways. Mitogen-activated protein kinase (MAPkinase) cascades are critically involved in regulating plantdefense mechanisms including plant innate immune responses. StudiesStudy of the MPK4/MPK4-like gene is common in the modelplant, Arabidopsis. However, there is still lack of information innon-model plant species including papaya. Interestingly inpapaya, MPK4 was found to magnify the defense responsesagainst papaya dieback disease caused by Erwinia mallotivora . Based oThe unique and complex interaction of MPK4 within the MAPkinase cascade also warrants a crucial in silico study of the MPK4gene concomitantly with other genes in the cascade that interactdirectly with it. Activation and regulation of MPK4 in the MAPkinase cascade were noted to require MEKK1 for cell deathdefense response in Arabidopsis  and MKK1In this study, the MPK4 gene from papaya was extracted basedon Arabidopsis MPK4 (AtMPK4) orthologs and the sequence wasanalysed using bioinformatics approach to predict itscharacterized functions and interactions in the MAP kinasecascade in papaya in comparison to other plants. The MEKK1,MKK1 and MKK2 orthologs were also mined from theArabidopsis genes designated as AtMEKK1, AtMKK1 andAtMKK2, respectively. Homologs of MPK4 in soybean showedMPK4 functioned to negatively regulate defense responses butpositively control growth and development . AnotherSequences of AtMPK4, AtMEKK1, AtMKK1 and AtMKK2 wereobtained from the Arabidopsis Information Resource (TAIR)database  and orthThe base content percentage of each sequence was calculatedusing the GC Calculator from BiologicsCorps . The nucTranslated nucleotides sequences that matched with the databasewere assessed using the ScanProsite software  to prediThe evolutionary path of each gene in different plant species wasevaluated using the neighbour-joining phylogenetic treesconstructed using the Mega software version 6  withbooFurther study was carried out using the Pathway Studio softwareweb version  to prediThe papaya MPK4, MEKK1 and MKK1/MKK2 sequences wereblasted into Blast2GO version 3.2  for the Sequences were obtained from the Phytozome database for eachgene of each available plant, respectively, with nine sequences forMPK4, eight for MEKK1, nine for MKK1 and eight for MKK2.There were no available sequences of MEKK1 in grape andMKK2 in Japanese rice. The length of the MPK4 sequence fromeach plant shows a slight difference from each other,approximately 1100 base pairs (bp). The longest sequence ofMPK4 was from sorghum with 1167bp while the shortestsequence was from cucumber with 1113bp. The MEKK1sequences, however, were dissimilar in nucleotides sequencelength ranging from 663bp (Japanese rice) to 1998bp (tomato).While most of the sequences were approximately 2000bp inlength, only Japanese rice (663bp) were shorter by 1000bp. TheMKK1 sequences were relatively similar to each other with 50 to74bp larger than 1 kilo base pair (kb) length. In contrast, theMKK1 sequence from soybean was only 807bp. The longestsequence of MKK1 obtained was from tomato with 1074bp. Thelongest sequence of MKK2 mined was from the Arabidopsisgenome with 1119bp while the shortest sequence was in sorghumwith only 69bp differences. The least variation in sequence lengthbetween the species corresponded to higher chance of conservedregion within the particular gene. In the case of verification of theMPK4 gene in papaya, we concluded that the MPK4 sequence obtained was closely related to the AtMPK4, likewise maybe itsfunction too. Whereas in MEKK1 and MKK1, high variations oflength sequences were acquired in one to two species which wasout of the comparative range (±100bp).Comparing the base content analysis of each MPK4, MEKK1,MKK1 and MKK2 sequences, the lowest percentage of individualbase was cytosine while the highest was adenine, both in MKK1of soybean . GmMKK1 Diversity of the three types of stop codon in the CDS sequenceswas observed in MEKK1 and MKK1 sequences, while MPK4 andMKK2 sequences revealed only diversity in TGA and TAA. OnlyJapanese rice, corn and sorghum have TAA in the MPK4sequences while most other species consist of TGA. In the MKK2sequence, TAA is commonly found whereas only papaya andsorghum contain TGA. Almost half of the species have TAG inthe MKK1 gene while the remaining has distribution of 33.33%TAA and 22.22% TGA. Stop codons in MEKK1 are distributedwith only one TAG stop codon (sorghum), and respectively threeand four stop codons of TGA and TAA between plant species.The percentage of stop codon variations was diverged betweengenes as represented . From thAnalyses of peptide sequences from the translated genes of eachspecies via domain and motif predictions using the ScanPrositesoftware revealed similar domain of protein kinase. The featuresstudied from the conserved domains and motifs in the MPK4,MEKK1, MKK1 and MKK2 for each plant species.Thirty out of 35 sequences studied shared similar motif signatureregion of the protein kinase ATP-binding and serine/threonine protein kinase active-site signatures. The domain region in all theMPK4 from each species demonstrated the same 286bp length.These MPK4 sequences had the conserved MAP kinase signatureregion except in sorghum, which exhibited a glycine rich regionprofile and lipid cysteine motifs of S-diacylglycerol and Npalmitoyl.The MPK4 of sorghum contained tyrosine proteinkinase specific active site signature at positions 177-189bp. Incontrast, no MAP kinase signature was obtained from the otherthree genes sequences. These genes share the protein kinasedomain with minor distinction of locations and lengths ofbinding domain ranging from 117 to 286bp. Interestingly, MKK1and MKK2 in cotton were found with the presence of TonBdependentreceptor protein signature but lacking the kinase ATPbindingsite.Study of the predicted domains and motifs indicate variance inlength of the protein kinase ATP-binding site in different genes inwhich MPK4 had the longest region of 25bp, MEKK1 with theshortest region of 23bp while MKK1/MKK2 with 24bp. Theprediction analysis also found the absence of the proton acceptoractivesite in the MEKK1 sequence. Amino acids changes werenoted in D482F in the papaya MEKK1 protein sequence, D220S inthe Japanese rice MEKK1 protein sequence and K159R soybeanMKK1 protein sequence. These changes could be due toevolutionary mutation processes.The identity matrix of each genes sequence alignment calculatedusing the t-coffee software discovered the papaya MPK4 genehad the highest identical value (92.25%) with grape MPK4 genewhile the papaya MEKK1 gene had the highest identical value(59.02%) with cucumber MEKK1 gene. The papaya MKK1 andMKK2 also shared high sequence homology with the grape at77.90% and 78.19%, respectively. Although MEKK1 in grape wasundiscovered, other three genes studied in papaya showedclosest homology in term of sequence composition to thesequences in grape with 77% to 92%.The significant differences observed between each MPK4sequences across the plant species are postulated as a response toevolutionary pressure imposed on the gene to maintain its corefunction as a defense gene against certain host-specificpathogens. For each respective variation in the sequencesthroughout the plant species, they were grouped into two majorclusters consisting of dicotyledonous plants (Class:Magnoliopsida) versus monocotyledonous plants (Class:Liliopsida).The evolution of the MPK4 gene between the plant species wasdistinctive in those two clusters. The papaya MPK4 wasclustered under the same clade with Arabidopsis (96%), whiletomato MPK4 (67%) showed a distant lineage from those groupsas illustrated in . Within The phylogenetic analysis of MEKK1 showed high (71 to 100%)bootstrap support across the species . These vFurther phylogeny analysis for MKK1 suggested that thesequence was closely associated between rice’s and sorghum’s. In contTo sum the sequence analysis of corresponding genes, MPK4scored high in conservation and stability across the plant species.It had less variance of stop codons and GC content, containedspecific domain features, high conservation and sequencehomology identities, and close distance of phylogeny. TheMEKK1, however, lack domain features, and has low (below 60%homology) sequence identity. Nevertheless, its high bootstrap ofmore than 70% confidence is likely true across the cluster groupbetween the species analysed. Both the MKK1 and MKK2 lackedcertain features in some species but were conserved in papaya,with higher homology identity index for MKK2 disputed toMKK1, which had a closer distance referred to papaya sequence.Searches using the Pathway Studio software  successfBased on in silico study of MPK4 and MEKK1/MKK1/MKK2complex interaction using the Pathway Studio software, it wasreported that all four related genes were involved in theregulation of defense response. In a study of the geneticmanipulation of MAP kinase cascade in plants proposed that theMPK4, MEKK1, and MKK1/MKK2 complex negatively regulateddefense responses . Based oWithin the MAP kinase cascade, it was highlighted that themultiple levels of signaling pathway starting from the MAPkinase kinase kinase (MAPKKK) to the MAP kinase kinase(MAPKK), and then to the activation of the MAP kinase (MAPK),leading to signal plant defense modulation . This paUpon infection, the MEKK1 received signal from the receptor andtriggered the MKK1/MKK2 complex with consequent activationof MPK4 -42. The We postulated that signals from MEKK1 will lead to theexpression of MKK1 and MKK2 as these two complexes promoteprotein modification interaction to stimulate MPK4 expression.MKK1/MKK2 functions as an important intermediate, whichinteracts between MEKK1 and MPK4. Within Arabidopsis,MKK1/MKK2 was conveyed to have overlapping functions indefense signaling mediated by MEKK1 and MPK4 . It can Inactive MPK4 was described to be phosphorylated by MKK1 atthe threonine site of MPK4 to trigger defense response .PhosphoThe interaction of MPK4 in the MAPK cascade together with theupstream components, MKK1/MKK2 and MEKK1, was found tobe involved in the phosphorylation pathway as a negativeregulator of systemic-acquired resistance (SAR) . While tAnalysis of the MPK4 cascade via the Cytoscape software  revealedThe detailed studied interactions between genes extracted fromthe Cytoscape database whereby two different interaction typeswere performed to study the genes interaction. The two hybridand two hybrid array detection methods related a physicalassociation type of interaction, while the protein kinase assay andin-gel kinase assay showed a phosphorylation reaction type ofinteraction. The overall data shown supports the interaction ofMEKK1-MKK1/MKK2-MPK4 as proposed in Additional analysis performed using the Blast2GO software withMEKK1, MKK1/MKK2 and MPK4 sequences in papaya to studythe potential functions as indicated in the gene ontology datashowed a transferring phosphorus-containing group of enzyme(Enzyme code (EC): 2.7.11) with 20 hits and 0.0e0 e-value. Theattained gene ontologies of each sequence are summarised.CpMEKK1 showed the highest possibility of classes in signaltransduction and cellular protein modification ; ion binding and kinase activity (molecular functionaspect); and intracellular related function (cellular componentsaspect). CpMPK4 also portrayed five possible gene ontologyclasses of functions including cellular protein modificationprocess ; ion binding, signal transduceractivity and kinase activity (molecular function); and intracellularrelated function (cell components aspect). Both of the postulatedCpMKK1/MKK2 from the single sequence showed a group ofeight classes of functions: cell death, signal transduction, cellularprotein modification process, cell cycle and response to stress; ion binding and kinase activity (molecularfunctions); and cytoplasm related function (cellular component).As gene ontology study of MEKK1, MKK1/MKK2 and MPK4 inpapaya emanated mainly in signal transduction, ion binding andkinase activity, interaction between each gene seemed essentialespecially in the MAP kinase cascade studied. Biological processof response to stress discovered in CpMKK1/MKK2 maydemonstrate more direct approach of the gene to play its functionagainst stress. This result might also hypothesise the lesserinteraction as proposed in MKK2 interaction of the Cytoscaperesult . The simConsidering the MEKK1-MKK1/MKK2-MPK4 module wasexpected to negatively regulate the defense response in papaya, agood suggestion put forth by Bigeard et al. (2015) that a mutantof this cascade be created using knock-out gene approach torepresent a constitutive defense responses including aconstitutive expression of the pathogenesis-related (PR) defensegenes, would indeed elucidate the intricacies of the playersinvolved in conferring resistance of plants against potentialpathogens . Here, oThe analysis of the conserved regions and signature motifs ofMPK4 and MEKK1/MKK1/MKK2 complex genes support therole each gene plays in the MAP kinase cascade in promotingdefense response. Overall, MPK4 indicates high conservation andstability in papaya and other plant species investigated. Theprotein kinase domain and motifs of MPK4 justified with highestimates of the conservation, homology and sequencepropositions across the plant species analysed. The findings fromthis in silico study revealed that the conservation of the candidategenes analysed particularly MPK4 within each plant species arefunctionally reliable as compared to the referenced sequencesvalidated through knock out gene study of MPK4 in Arabidopsis.The in silico study of the MPK4 gene in the MAP kinase cascadeand the MEKK1/MKK1/MKK2 complex showed wide variationsin stop codons, GC-content and homology identity but yetconserved in their respective signature domains to assume theirbasic functional role, and thus to make use of these interactionsbehaviour between genes isolated for future references.


Up to 30% of HIV infected patients who are receiving HAART do not exhibit a marked increase in the CD4+ T cell count. There is still a concern that immune recovery may not be complete once CD4+ T cells have decreased below 200 cells/μl. The objective is to assess CD4+ cell recovery in HIV+ patients with CD4 count below 200 cells/μl) at HAART initiation.This was a retrospective cohort study among 110 HIV+ patients with initial CD4 count < 200 cells/μl. Baseline Age, sex, CD4 count and viral load were extracted from the patient’s database. After12 months of HAART; CD4 count was done using flow cytometry and viremia by COBAS AmpliPrep/COBAS TaqMan HIV-1 test v 2.0 technology.The mean age of the respondents was 35 years; males being 57% and females were 43%. The mean CD4 count before HAART was 110.18 cells/μl whereas at 12 months of HAART; this was 305.01 cells/μl. Though some patients did not achieve a CD4 count of more than 200 cells/μl or a drop in viral load; there was a significant recovery of CD4+ cells  and viremia following HAART . Participants aged 18-30 years were likely to have less than 200 cells/μl CD4 count (46.4%)  than participants aged above 40 years (16.7%).HAART was associated with viremia suppression but many patients failed to achieve a CD4 count >200 cells/μl. HAART before severe immunosuppression is a key factor for immune restoration among HIV+ patients. Human immunodeficiency virus (HIV) is a lentivirus; a member of the retrovirus family that causes Acquired Immunodeficiency Syndrome (AIDS) . Human I+ patients biological follow up that aims at assessing the infection progression as well as response to HAART [Work undertaken by the National Institute of statistics of Rwanda (NISR), in the 2010 RDHS, indicated that in Rwanda, HIV prevalence was 3.7% and 2.2% among women and men, respectively. The city of Kigali, Capital of Rwanda had the highest prevalence (7.3%) in the country . Periodito HAART . The besto HAART –10. A loto HAART  and studto HAART . HIV+ arto HAART .CD4 count has been reported to be one of the best surrogate markers for monitoring the progression of HIV infection and low CD4 counts are associated with increased risk of developing AIDS or death . The absThis was a retrospective cohort study that started from March 2015 to February 2016. The study aimed at looking at how CD4+ cells recover when HIV+ patients initiate HAART with a severe immunosuppression. Baseline data including demographic (age and sex), CD4 count, and viral load were collected from HIV+ patient’s database . The inclusion criteria were HIV+ patients who had initiated HAART with a CD4 count of less than 200 cells/μl.The study was conducted at Centre Medico-Social Cor-Unum located in Kigali; the capital city of Rwanda. This health facility is a member of public health facilities in Rwanda that host voluntary counseling and testing (VCT), antiretroviral treatment services and follow up for many HIV+ patients. In addition, the area is near the National Reference Laboratory of Rwanda where viral load was to be measured and this has facilitated easy and cheap sample transportation at 12 months of HAART. Blood samples were collected from 110 study participants who had been on HAART for 12 months. The CD4 count was done using flow cytometry (BD FACSCount™ system) while viral load was determined using COBAS AmpliPrep/COBAS TaqMan HIV-1 test v2.0 technology.Paired and independent t test were used to compare means between baseline CD4 cell; viremia and at 12 months of HAART initiation; as well as between demographics and CD4 cell/viral load respectively. Moreover, chi square test was used to determine the association between demographics and CD4 count level. The significance level was set at P value <0.005. This study was reviewed and approved by Mount Kenya University (MKU04/DPA/16/2015/3007) and Congregations Around Richmond Involved to Assure Shelter (CARITAS)-Rwanda as Centre Medico-Social Cor-Unum operates under CARITAS in partnership with the Rwanda Ministry of Health. All the patients signed the informed consent before participation to the study.As shown in Viral load median was computed at both time points as shown in Before HAART initiation males had a mean rank viral load 59.9 compared to 49.5 among females but this was not significant . Following HAART mean rank of drop in viral load achieved by males was 55.3 and by females 55.8 . Similarly, there was no significant difference between the age and mean rank of viral load before HAART initiation  as well as age and mean rank of viral load after 12 months of HAART initiation  .CD4 Count and viral load levels were analyzed based on whether a patient achieved a CD4 count of ≥ 200 cells/μl at 12 months of HAART initiation. Despite HAART, 29 (26.4%) of study participants were still having CD4 count below 200 cells/μl compared to 81 (73.6%) participants who had a CD4 count of more than 200 cells/μl as CD4 count. As for viral load, 106 (96.4%) patients achieved a net decrease in viremia to 20 RNA copies/ml while 4 (3.6%) had an increase in their viremia .The World Health Organization recommends a limit CD4 count of 350 cells/μl or clinical stage based decision for HAART initiation; particularly in countries where viral load cannot be easily determined , 17 and A significant recovery of CD4 positive cells and a drop in viremia following 12 months of HAART among study participants were documented and this is in agreement with findings by  and a stSome patients saw a decrease in their viral load after 12 months of treatment. However; this was not associated with a net recovery of CD4+ cells to reach more than 200 cells/μl; as following the 12 months of HAART considerable percentage (26.4%) of participants were still having CD4 count below 200 cells/μl compared to 73.6% of participants who achieved more than 200 cells/μl as CD4 count. This finding highlights the importance of viral load for the biological follow up of HIV+ patients both before and following HAART compared to CD4 count. Several studies have reported a poor prognosis prediction by CD4 count as it sometimes does not correlate with viral load in what is known as discordant response  and slowPoor immunologic response has been attributed to patient factors like age, the regimen as well as viral factors. However; this was not the case in the present study where young patients were likely to have a poor immune recovery compared to old patients . The preWe conclude that immune recovery is slow among HIV+ patients who start HAART with severe immunosuppression. Early HAART intervention is necessary for achieving effective CD4+ T cell responses and optimal immunological function in HIV+ patients.Several researchers have focused their attention on CD4+ cells recovery among HIV+ patients following HAART in general.This study has enriched the knowledge on how CD4+ cells recover among HIV+ patients when they initiate HAART after a severe immunosuppression;The study has again pointed out the importance of early HAART initiation among HIV+ patients particularly in the context of Rwanda where such data were scarce;The present study will also raise more interests among researchers on host cellular and molecular as well as viral factors behind this poor recovery in CD4+ cells.


Dw1-Dw4). Subsequent research showed that Dw3 encodes an ABCB1 auxin transporter and Dw1 encodes a highly conserved protein involved in the regulation of cell proliferation. In this study, Dw2 was identified by fine-mapping and further confirmed by sequencing the Dw2 alleles in Dwarf Yellow Milo and Double Dwarf Yellow Milo, the progenitor genotypes where the recessive allele of dw2 originated. The Dw2 locus was determined to correspond to Sobic.006G067700, a gene that encodes a protein kinase that is homologous to KIPK, a member of the AGCVIII subgroup of the AGC protein kinase family in Arabidopsis.Sorghum is an important C4 grass crop grown for grain, forage, sugar, and bioenergy production. While tall, late flowering landraces are commonly grown in Africa, short early flowering varieties were selected in US grain sorghum breeding programs to reduce lodging and to facilitate machine harvesting. Four loci have been identified that affect stem length ( Additionally, shorter grain varieties were selected to reduce lodging and to aid mechanical harvesting. In contrast, sorghum genotypes with longer stems and delayed flowering enhance biomass and sugar production3. In sweet sorghum, stem length is associated with higher sugar yield because stems accumulate high levels of sucrose post floral initiation5. In energy sorghum, 83% of the shoot biomass accumulates in the stem6. Therefore, increasing our knowledge of stem growth will aid the improvement of sorghum hybrids for bioenergy production.Sorghum is the fifth most widely grown cereal crop worldwide (faostat.fao.org). Its drought and heat tolerance make this crop especially important in semi-arid regions. Sorghum is a C4 grass with a diverse germplasm that has been selected for many uses including production of grain, forage, sugar, and biomass for bioenergy. In its native Africa, sorghum grows 4–5 meters tall and many genotypes are photoperiod sensitive, resulting in delayed flowering in long day environments. Upon introduction to temperate locations, photoperiod insensitive varieties that flower early were selected for production of grain7 identified four loci (Dw1-Dw4) that control internode length by measuring the height of the stem from the ground to the flag leaf. At each Dw locus the dominant allele increased internode length. Recessive alleles of Dw1 and Dw2 were identified in Milo lines, while recessive alleles of Dw3 were identified in Kafir backgrounds, and dominant alleles at Dw4 were only found in broomcorns7. Dw2 was shown to have pleiotropic effects on panicle length, seed weight, and leaf area9. In addition to internode length, Dw3 influences grain yield, tiller number10, and leaf angle11.Plant height is determined primarily by the length and number of stem internodes. The number of internodes produced by a plant is a consequence of growth duration and the rate of internode production. Quinby and KarperDw3 was the first dwarfing gene to be cloned in sorghum12. Dw3 encodes a homolog of the maize Br2 gene and is an ATP-binding cassette type B1 (ABCB1) auxin efflux transporter. This is in contrast to dwarfing or semi-dwarfing genes in other important crops, such as rice and wheat, which have mutations in genes involved in the gibberellin pathway14. Dw1 was mapped to a region on chromosome 9 between 56.8–57.1 Mb15. The gene corresponding to Dw1 was recently identified as Sobic.009G229800 by map-based cloning17. This gene regulates internode cell proliferation17 and encodes a putative membrane protein not previously assigned a function16. The recessive dw1 allele in Dwarf Yellow Milo (DYM), first identified by Quinby and Karper7, contains a stop codon in exon 2 that results in protein truncation16. The dw1 allele originating from Dwarf Yellow Milo has been used extensively in grain sorghum breeding programs.Dw2 has also been used extensively in grain sorghum breeding programs to reduce plant height. Dw2 is linked to Ma1, an important flowering time gene that confers photoperiod sensitivity1. Ma1 is located on chromosome 6 at ~40.3 Mb and encodes PRR3718. Dw2 was previously mapped to a location near Ma1 at ~42 Mb in several QTL mapping studies22 and was associated with a SNP marker at 42.7 Mb in a GWAS study23. In another study, Dw2 was suggested to be a histone deacetylase (Sobic.006G067600) based on GWAS analysis21. Recessive alleles of Ma1 and the dwarfing genes were used in the Sorghum Conversion Program to convert tall late flowering landraces from Africa into short, early flowering genotypes that are useful for grain sorghum breeding. The landraces were crossed to BTx406 (dw1dw2dw3dw4) to introduce one or more of the recessive alleles at the Dw loci into landrace backgrounds19. Recent analysis of the sorghum conversion lines has shown that large portions of chromosome 6 have been introgressed from BTx406 into landrace accessions during conversion and that the peak of introgression frequency aligned with Dw224.Dw2 was map-based cloned using two RIL populations: BTx623 (dw1Dw2dw3dw4) x IS3620c (dw1dw2Dw3dw4) and BTx642 (dw1dw2dw3dw4) x Tx7000 (dw1Dw2dw3dw4). Dw2 was identified as a protein kinase whose closest homolog in Arabidopsis is the kinesin-like calmodulin-binding protein (KCBP)-interacting protein kinase (KIPK), a member of the AGCVIII subfamily that also includes PINOID (PID) and PHOTOTROPIN1 and 2 (PHOT1 and 2).In the current study, dw2 allele present in Double Dwarf Yellow Milo (DDYM), the original source of dw2, arose as a mutation in Dwarf Yellow Milo (DYM)25. Comparison of DYM and DDYM stem internode lengths at anthesis showed that the recessive allele of dw2 in DDYM caused a reduction in the length of every elongated internode compared to the corresponding internodes in DYM  and for Dw3 on chromosome 7 (~59.8 Mb) and these loci affected both total stem length and internode length. An additional QTL (Dw03_67.5) at ~67.5 Mb on chromosome 3 affected total stem length  near Dw2 segregating for the length of the sixth internode below the peduncle. However, the peaks for the fifth and sixth internode are broad and the 2-LOD interval for the peak on chromosome 6 for both internodes includes both Dw2 and Dw06_48.6  analysis (Supplementary Table Dw3 (chromosome 7 at 59.8 Mb) and another between a QTL on chromosome 1 and a QTL close to Dw3 (10.7 cM from Dw3 at 61.2 Mb)  that decreases function; therefore, all of the genes in the delimited Dw2 locus  and Tx7000 (Dw2)  from DDYM (dw2), the source of the recessive allele of dw2.The gene corresponding to Dw2 alleles in historically important sorghum genotypes was investigated by sequencing Sobic.006G067700 from the genotypes listed in Tables 7 as dw2 contain the indel in Sobic.006G067700 derived from DDYM. For example, 80 M is a maturity standard with the reported genotype dw1dw2Dw3dw41. 80 M and the other maturity standards were selected from a cross of Early White Milo (Dw2) and DDYM (dw2) and contain the DDYM dw2 allele  were also crossed to genotypes containing the DDYM dw2 allele during their construction26. Several genotypes contained polymorphisms in exons that changed the protein sequence encoded by Sobic.006G067700. However, SIFT27 analysis predicted that those polymorphisms would be tolerated and not disrupt function  are members of the AGC1 group. A BLAST search of the Arabidopsis AGCVIII kinase gene family to the sorghum genome identified 21 sorghum homologs  and Sobic.008G096200 (SbKIPK-like) . Genes in other plants with the greatest sequence similarity to Sobic.006G067700 include LOC_Os12g29580 (rice), GRMZM2G412524 (maize), GRMZM2G128319 (maize), and At3G52890 (Arabidopsis) (Phytozome). At3G52890 encodes an ACGVIII kinase called KIPK, a KCBP-interacting protein kinaseke) Fig. .Figure 432. A comparison of Dw2 (Sobic.006G067700) with KIPK and other members of the AGC1-kinase group showed that Dw2 contains a conserved GxGxxG sequence in the P-loop of sub-domain I of the N-lobe, an activation segment in the C-lobe that includes the Mg++ binding sequence DFDLS, an insertion domain typical of plant AGC-kinases, and a T-loop and activation domain [SxxSFVGTxYxAPE] that is a site of phosphorylation32 , it aligned best with the N-terminal domain of KIPK and next best to KIPK2 (AGC1-9). Multiple sequence alignment of Dw2, rice and maize homologs of Dw2, and Arabidopsis KIPK showed regions of sequence similarity throughout the N-terminal domain and several deletions relative to Arabidopsis KIPK that explain the difference in overall length of the N-terminal protein sequences (423 versus 545 amino acids)  by analysis of RNAseq profiles that are part of the sorghum RNA Atlas (Phytozome). Dw2 is annotated as having two transcripts that differ in the 5′UTR. The primary transcript (Sobic.006G067700.2) has a UTR with no introns that extends 537 bp before the start codon, while the secondary transcript (Sobic.006G067700.1) has one intron and extends 923 bp. The analysis of Dw2 expression shown in Fig. Dw2 was relatively high in developing panicles, peduncles, growing internodes and leaf sheaths, with lower expression in fully expanded internodes, leaf blades and the lower portion of the root system that includes root tips and fully elongated roots  locus segregating in the second population derived from BTx642 x Tx7000, genotypes recessive for dw1dw3dw4. Indeed, the only QTL segregating for total height in this population was a QTL corresponding to Dw2 (~43.2 Mb). The location of the Dw2 QTL mapped in this study corresponds to most previous reports of the location of Dw221. Higgins et al.22 also identified QTL for plant height in this region of chromosome 6 with peaks at 44.3–44.5 Mb or 42.1 Mb depending on the population and QTL model. The authors suggested that variation in QTL location was due to the linkage between Dw2 and Ma1 since both influence plant height22. In the current study, the influence of Ma1 alleles is minimal because the BTx642 x Tx7000 RIL population is segregating for a weak allele and null allele of Ma1, respectively33, and BTx623 and IS3620c each contain null alleles of Ma119. During the analysis of Dw2 a nearby QTL located at 48.6 Mb on chromosome 6 was identified that modified the length of internode 6 according to single QTL mapping. MQM revealed that this QTL also affected the length of internodes 4–7; however, Dw2 had a greater impact on the length of the fourth and fifth internode. This additional QTL could also have confounded the location of Dw2 in the study of Higgins et al.22.Dw2 and Dw3 influence internode length differentially during development. Dw2 had the greatest additive effect on the length of the internode immediately below the peduncle. The additive effects of Dw2 and Dw3 on the length of this internode were similar. The influence of Dw2 gradually decreased in the internodes below the top internode and there was no detectable impact of Dw2 on the length of internodes 7–8 below the peduncle in this population. Dw3 had a much greater effect than Dw2 on internodes 2–5 below the peduncle with reduced but significant impact on the length of internodes 6–8  showed that Dw2 has an effect on the length of all of the ~12 internodes produced by plants grown in the greenhouse during the fall under short day conditions , a gene located near Dw2 on chromosome 6 (40.3 Mb), was also more effective in one of the three populations used in that study18. The reason for differences in recombination efficiency among populations used to map Ma1 and Dw2 is unknown. However, it is possible that sequence divergence or differences in chromatin/DNA methylation in this region of chromosome 6 between parental genotypes affects local recombination frequency. In both studies, the most useful population for fine mapping involved parental lines of the durra race that were crossed to parental lines of the kafir race (BTx642 (durra) xTx7000 (kafir) (Dw2); 100 M (durra) x Blackhull kafir (Ma1)). Larger populations and additional crosses will be required to determine if the association between genetic background and local recombination frequency is significant.Fine mapping narrowed the region encoding Dw2 locus encoded a histone deacetylase that was previously suggested to be a candidate for Dw221. However, the deacetylase did not contain polymorphisms in the coding regions that distinguish the parental genotypes used for fine mapping, or DYM (Dw2) and DDYM (dw2). DDYM was reported to have originated as a shorter mutant in a field of DYM25. Thus, these two yellow milos should be isogenic except at Dw2. All of the other genes in the delimited Dw2 region were sequenced from DYM and DDYM. Only the kinase encoded by Sobic.006G067700 had a polymorphism that distinguished DDYM from DYM in the delimited Dw2 locus. This polymorphism resulted in a frameshift mutation and a premature stop codon in the first exon. This results in a protein of only 190 amino acids instead of 809 amino acids found in DYM. The kinase domain is located between 424–763 amino acids; therefore, the mutant protein found in DDYM would lack kinase activity.One of the ten genes in the delimited 34. Each of these kinases has been shown to regulate auxin efflux transporters, including ABCB1 and PIN1, with PHOT1 and 2 doing so in a blue-light dependent manner35. In Arabidopsis, KIPK has a close homolog, KIPK2  and the closely related kinase, AGC1-836. In sorghum, Dw2 has one closely related homolog, Sobic.008G096200, and these two genes form their own branch on the phylogenetic tree 40. While KIPK did not phosphorylate the N-terminal end of KCBP under experimental conditions, it is possible that it phosphorylates KCBP under other conditions, and it is possible that KCBP transports KIPK within the cell28.In Arabidopsis KIPK was so named due to its interaction with KCBP, a plant-specific kinesin-like calmodulin binding protein that functions in cell division and trichome formation36. Other PERK-genes, such as PERK1, mediate growth inhibition, possibly in response to cell wall signals41. In Arabidopsis, KIPK1 and 2 double mutants did not produce shoot phenotypes although there were differences in root elongation when plants were grown on elevated sucrose36. Different parts of the N-terminal domain of KIPK1 and 2 mediate the direct interactions with KCBP and the various PERKs36. The 423 amino acid N-terminal sequence of Dw2 aligned well with the ~545 amino acid N-terminus of KIPK despite several deletions that account for the difference in overall length of this domain. The sequence similarity of the N-terminal domains of KIPK and Dw2 indicates that Dw2 has likely retained the ability to interact with one or more members of the PERK family. The best BLAST hits to Arabidopsis PERK8 and 10  in sorghum  were expressed in stem internodes (Phytozome). Therefore, it will be of interest to determine if Dw2 interacts with sorghum PERK8 or 10 homologs.Subsequent work has also shown that Arabidopsis KIPK1 and 2 directly interact with members of the proline-rich extensin-like receptor-like kinase (PERK) family, specifically PERK8, 9, 10, and 1338 potential Dw2 interactions with PERKs and KCBP in sorghum could regulate growth and the flow of materials to the cell wall during and after organ elongation. Alternatively, in trichomes KCBP has been found to organize cytoskeleton components37, thus KIPK may be involved cytoskeletal regulation that is associated with cell elongation. This more general coordinating function may explain why Dw2 is expressed in growing zones of leaf blades, leaf sheaths, stems, and panicles. Lack of growth phenotypes in all organs where Dw2 is expressed  could be due to the presence of a second KIPK-like gene in sorghum (Sobic.008G096200). In fact, Sobic.008G096200 is more highly expressed than Dw2 in the roots, and both genes are highly expressed in the panicle, peduncle, and internodes , another important gene in grain sorghum and energy sorghum development18. In addition to its historical significance, a better understanding of Dw2 function may enable the design of improved sorghum crops.Dw2) and Double Dwarf Yellow Milo  were grown to examine the internode length phenotypes caused by the two Dw2 alleles. For each genotype, three plants were individually grown in 3.8-gallon pots (Custom2000) containing Metro Mix 900 (Sun Gro Horticulture) with supplemental fertilizer (Peters 20-20-20) in the greenhouse in short days during the fall. At anthesis, the plants were harvested and the total stem length and length of each internode were measured.The progenitor genotypes Dwarf Yellow Milo . BTx623 is dw1Dw2dw3dw4 and IS3620c is dw1dw2Dw3dw4; therefore, the population segregated for both Dw2 and Dw3. The population (n = 380) was grown in the greenhouse in the summer of 2013 with natural day lengths. Three plants of each RIL were grown per pot, one pot per line in the same manner as DYM and DDYM. Plants were harvested at grain maturity. For each plant, the total length of the plant (base of the plant to the base of the panicle) and the length of each internode and peduncle were measured. Internodes were numbered from the peduncle. Plants differed for flowering time, with earlier flowering lines producing fewer elongated internodes. As a consequence, the 6th, 7th, and 8th internodes below the peduncle had smaller sample sizes than the other traits measured . Genotyping and genetic map construction (n = 398) were performed as described in Truong et al.46 except the DG marker sequences were mapped to version 3 of the sorghum reference genome assembly , using BWA47, and INDEL realignment and joint variant calling were performed with the GATK using the naive pipeline of the RIG workflow51. QTL mapping was performed in R/qtl using interval mapping (IM) with 1000 permutations and an α = 0.0552. Both the genetic map and QTL mapping were performed as an F7 instead of a RIL population due to excess heterozygosity.The BTx623 x IS3620c RIL population was used for mapping 54. Penalties  for all normalized phenotypes were calculated from 25,000 permutations of two-dimensional genome scans using the TIGGS-HPC cluster at Texas A&M; penalties calculated were negligibly different between phenotypes (i.e. same to the tenths place). Significant QTL identified from an initial IM analysis  were used to seed multiple-QTL model selection analysis 54. The best scoring multiple-QTL model from model selection of each phenotype was then merged into a composite multiple-QTL model. The composite multiple-QTL model was generated by merging all overlapping 2-LOD intervals into one QTL and designating the position of the MLOD (maximum LOD) marker as the QTL position55, where loci with an epistatic interaction were merged independently of strictly additive loci.MQM was performed using the same phenotypes, except peduncle length, and genotypes that were used for IM, except the genetic map was thinned to obtain a marker set with at least 1 cM spacing between markers. Also, measurements of the length of each internode, average internode length, and total internode length were normalized using Empirical Quantile Normal Transformation prior to QTL mapping with R/qtldw1dw2dw3dw4 and Tx7000 is dw1Dw2dw3dw4; therefore, the population derived from a cross of these genotypes will segregate for alleles of Dw2. The BTx642 x Tx7000 RIL population (n = 89) was grown in the field in the spring and summer of 2009. It was planted in a Norwood silty clay loam , thermic Typic Udifluvent) in duplicate in a randomized block design at the Texas A&M Research Farm located near Snook, TX on 03/04/2009. The blocks were arrayed in 20 rows 4.6 m long and spaced 76 cm apart with two buffer rows on each end of the block. Each block was offset from the next by approximately 1.5 m. The plants emerged on 08/04/2009 and were thinned to a within-row spacing of 10 cm at 16 days after emergence (DAE). The average daily maximum temperature was 33.3 °C and the average daily minimum temperature was 21.1 °C. The population received 24.9 cm of natural rainfall during the growing season with supplemental flood irrigation as needed. The population was harvested on 23/06/2009 (76 DAE), approximately at anthesis for the population. Three plants of each RIL and parental lines from each of two replicates were harvested. For QTL mapping, the average of the two replications was used. Plants were phenotyped for total height, which was measured from the base of the plant to the top of the panicle.BTx642 is 20 using the enzyme NgoMIV to digest genomic DNA. Reads were mapped to the reference genome and variants were processed as described for the BTx623 x IS3620c RIL population. The genetic map was constructed using R/qtl (n = 93) after removing any markers that did not define a recombination breakpoint. QTL mapping was also performed in R/qtl using IM with 1000 permutations and an α = 0.0552.DNA was extracted from leaf tissue harvested from each RIL and processed using ZR Plant/Seed DNA MiniPrep (Zymo Research). Digital Genotyping (DG) was performed as previously describedDw2. Lines that had recombination breakpoints in or near Dw2 were used to delimit the locus to the extent possible using additional DG genotypes and SNPs identified by Sanger sequencing genes in the region. Primers used for Sanger sequencing are listed in Supplementary Table © High-Fidelity DNA Polymerase  using the standard conditions. The PCR product was gel purified using QIAquick Gel Extraction Kit (Qiagen) and prepared for capillary sequencing with BigDye© Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems) using standard reaction conditions. Sequencing was performed with the ABI 3130xl Genetic Analyzer (Applied Biosystems) and the results were analyzed with Sequencher v4.8 (Gene Codes Corp.).The BTx642 x Tx7000 RIL population was used for fine mapping Dw2 region were grown to confirm stem and internode length phenotypes. Two pots containing two plants from each RIL were grown in two different greenhouses for a total of eight plants per RIL; otherwise the RILs were grown in the same manner as DYM and DDYM. At anthesis, the plants were harvested and the total length of the stem (measured from the base of the plant to the base of the panicle) and the length of each internode were recorded.RILs with recombination breakpoints in the delimited Dw2 was delimited to the extent possible with available genetic resources, the genes in this region were sequenced to search for functional mutations that distinguish DYM (Dw2) from DDYM (dw2). The genes in the Dw2 locus were identified using the sorghum reference genome version 3.1 gene set . The primers for sequencing the genes are listed in Supplementary Table Dw2 differentiate the two genotypes25. For Sobic.006G067600 only the exons were sequenced, for all other genes, the entire gene was sequenced. Sobic.006G067700 was further sequenced in the other important breeding lines to examine the distribution and extent of allelic variation in Dw2.Once the region encoding Dw2. Tx7000 and BTx642 seeds were obtained from Dr. W.L. Rooney . IS3620c seed (PI 659986 MAP) was obtained from the USDA-ARS Plant Genetic Resources Conservation Unit . Seeds were soaked in 20% bleach for 20 minutes and washed extensively in distilled water for one hour. Seeds were germinated on water-saturated germination paper in a growth chamber . Genomic DNA was isolated from 8-day old root tissue using a FastPrep DNA Extraction kit and FastPrep24 Instrument , according to the manufacturer’s specifications. DNA template (350 bp average insert size) was prepared using a TruSeq® DNA PCR-Free LT Kit, according to the manufacturer’s directions. Paired-end sequencing (125 × 125 bases) was performed on an Illumina HiSeq2500. Sequence reads were mapped to version 3 of the sorghum reference genome assembly , using BWA v0.7.1247. Base quality score recalibration, INDEL realignment, duplicate removal, joint variant calling, and variant quality score recalibration were performed using GATK v3.3 with the RIG workflow51. Whole genome sequence of Tx7000, BTx6424, and IS3620c are available at the Sequence Read Archive (www.ncbi.nlm.nih.gov/sra).Whole genome sequencing was used to identify polymorphisms that distinguish the parents of the two populations used to map 56. The sequences were aligned using the MUSCLE algorithm58. The tree was estimated using maximum likelihood with the substitution model developed by Le & Gascuel59 and the Gamma distribution. To estimate the reliability of the branches, 1000 boostraps were performed. Protein alignments were performed in Jalview v2.060 using the TCoffee algorithm61 with defaults.Each of the AGCVIII proteins in Arabidopsis was aligned with the sorghum genome using BLAST and the best hits were recorded. The resulting sorghum AGCVIII protein family was used to make a phylogenetic tree in MEGA6Supplementary InformationSupplementary Table S4Supplementary Table S5Supplementary Table S7


A pepducin is a lipopeptide containing a peptide sequence that is identical to one of the intracellular domains of the G-protein coupled receptor (GPCR) assumed to be the target. Neutrophils express two closely related formyl peptide receptors belonging to the family of GPCRs; FPR1 and FPR2 in human and their respective orthologue Fpr1 and Fpr2 in mouse. By applying the pepducin concept, we have earlier identified FPR2 activating pepducins generated from the third intracellular loop of FPR2. The third intracellular loop of FPR2 differs in two amino acids from that of FPR1, seven from Fpr2 and three from Fpr1. Despite this, we found that pepducins generated from FPR1, FPR2, Fpr1 and Fpr2 all targeted FPR2 in human neutrophils and Fpr2 in mouse, but with different modulating outcomes. Whereas the FPR1/Fpr1 derived pepducins inhibited the FPR2 function in human neutrophils, they activated Fpr2 in mouse. The FPR2 derived pepducin activated FPR2/Fpr2, whereas the pepducin generated from Fpr2 inhibited both FPR2 and Fpr2. In summary, our data demonstrate that pepducins generated from the third intracellular loop of human FPR1/2 and mouse Fpr1/2, all targeted FPR2 in human and Fpr2 in mouse. With respect to the modulating outcomes, pepducin inhibitors identified for FPR2 are in fact activators for Fpr2 in mouse neutrophils. Our data thus questions the validity of pepducin concept regarding their receptor selectivity but supports the notion that FPR2/Fpr2 may recognize a lipopeptide molecular pattern, and highlight the differences in ligand recognition profile between FPR2 and its mouse orthologue Fpr2. The members of the formyl peptide receptor (FPR) family expressed by neutrophil phagocytes belong to the large group of G-protein coupled receptors (GPCRs) and play key roles in proper recruitment and activation of neutrophils at sites of infection/inflammation –3. NeutrStaphylococcus aureus bacteria that potently and selectively activate Fpr1 (fMIFL) and Fpr2 (PSMα2), respectively [10 being prominent examples [When looking at the FPRs in different species it is clear that the receptor family has a complex evolutionary history, as illustrated by the fact that the number of genes in the family vary markedly in mouse and man . Human pectively . We alsoexamples . We haveexamples , 14. Thith century, a unique class of lipopeptide ligands (pepducins) was introduced. The proposed concept for interaction suggested that pepducins modulate receptor signaling through a direct interaction between the peptide part of the pepducins and intracellular signaling active parts of the targeted receptors [2R) all have in common that they modulate FPR2 function [When searching for new mechanistic concepts for allosteric modulation of GPCRs in the early 21eceptors –17. Pepdeceptors –18. The eceptors . Over theceptors –22. It sfunction –25. The function . Even th16) and FPR2  on mouse neutrophils [16) and Fpr2  on mouse and human neutrophils were also investigated. We show that the FPR2 derived pepducin activated both FPR2 and Fpr2, whereas the corresponding Fpr2 pepducin potently inhibited FPR2/Fpr2. The FPR1- as well as the Fpr1-derived pepducins interacted with FPR2 and Fpr2, but the outcome of this interaction differed as they activated Fpr2 but inhibited FPR2 function. Taken together, we describe pepducins that inhibit FPR2 activity in one species activate the receptor orthologue in another species, and that all the modulating pepducins studied selectively targeted FPR2/Fpr2 irrespectively from which the receptor the peptide sequence was derived. Although our results disagree with the proposed molecular mechanism for how pepducins achieve their receptor specificity, this group of FPR2 selective ligands clearly serve as excellent tools for further studies of FPR2/Fpr2 functions.In this study, we applied the pepducin approach in an attempt to gain more insights into similarities and differences in the ligand recognition profiles of the human neutrophil FPRs and their mouse orthologous. We have determined the effects of two earlier described human FPR pepducins generated from the third intracellular loop of FPR1 . The pepducins were synthesized by Fmoc solid-phase peptide synthesis and the fatty acid were N-terminally linked on the resin as the last step before deprotection of side chains, followed by HPLC purification on a C18 column and further verification by MALTI-TOF Mass Spectrometry. All peptides and pepducins were dissolved in dimethyl sulfoxide to a concentration of 10 mM and stored at -80°C until use. Further dilutions were made in Krebs-Ringer phosphate buffer that was supplemented with glucose (10 mM), Ca2+ (1 mM), and Mg2+ (1.5 mM) .Percoll was obtained from Amersham Pharmacia . Dextran and Ficoll-Paque were obtained from GE-Healthcare Bio-Science . The peptides were synthesized and purified by high-pressure liquid chromatography (HPLC) by Alta Bioscience . Cyclosporin H (CysH) was kindly provided by Novartis Pharma  and the peptidomimetic activator F2M2 and inhibitor were kindly provided by Henrik Franzyk . Boc-FLFLF (Boc2) and isoluminol were purchased from Sigma Chemical Co. . The phenol-soluble modulin  was obtained in its N-formylated form from EMC . Recombinant murine tumor necrosis factor alpha (TNF-α) was from R&D Systems Europe Ltd. . Horseradish peroxidase (HRP) was from Boehringer Mannheim . Pepducins and the FPR2 inhibitor PBP−/− mice generated as described previously [ad libitum, at the Department of Rheumatology and Inflammation Research, University of Gothenburg. Sex matched WT and Fpr2-/- animals (age 8–10 weeks) were used to isolated bone marrow derived neutrophils. The studies performed were approved by the Ethical Committee for Animal Experimentation, Göteborg, Sweden.C57BL/6 wild-type mice were purchased from Charles River Laboratories and Fpr2eviously , were geHuman peripheral blood neutrophils were isolated from buffy coats from healthy blood donors using dextran sedimentation and Ficoll-Paque gradient centrifugation as described . The rem2+ and Mg2+ (KRG-) was forced through the bone by using a 1-mL syringe with a 27-gauge needle. After dispersing cell clumps and removing the debris, the bone marrow granulocytes were isolated according to an earlier described procedure [Mice (8–12 weeks of age) were killed by cervical dislocation, the femurs and tibias were removed and freed of soft tissue attachments, and the extreme distal tip of each extremity was cut off. KRG without Carocedure  with som-6) as a function of time (min). The activity before stimulus addition was recorded as basal line and this activity was not changed in vehicle control samples. Since the FPR/Fpr-mediated superoxide production with respect to the onset and decline are very similar, the peak activities were used to compare the responses induced.NADPH-oxidase activity was determined using an isoluminol and HRP-enhanced chemiluminescence (CL) system that allow for the determination of superoxide production , 30. TheNaïve bone marrow cells produce very low levels of superoxide upon stimulation and to increase this production the cells were routinely primed for one hour at RT followed by TNF-α  priming for a period of 20 min at 37°C , allowin50/IC50 values were determined from experiments in which the activities were normalized to the response induced by maximal response or induced by agonist in the absence of inhibitor. The statistical analysis was performed on raw data using Student’s t-test when two groups were compared or one-way ANOVA with Dunnett’s multiple comparisons test in comparison to the control response when three groups were compared. * p ≤ 0.05 was considered significant.Data analysis was performed using Graph Pad Prism 7.0. The EC16, Pal-KIHKKGMIKSSRPLRV), with a peptide sequence identical to the entire third intracellular loop of FPR2 (spanning from amino acid K227 to V242), activates human neutrophils  and PSMα2 (Fpr2) derived from S.aureus  rather than Fpr2  mice and the recently described selective ligands for mouse Fprs [16-induced response was significantly lower in neutrophils isolated from Fpr2-/- mice compared to that from WT cells (16. This suggestion gained further support from receptor desensitization experiments using the Fpr2 selective agonist PSMα2 [16 (16 response in WT cells was significantly reduced by the earlier described Fpr2 selective peptidomimetic inhibitor (Lau-(Lys-βNSpe)6-NH2) but not the Fpr1 antagonist Boc2 . No activation of mouse neutrophils was obtained using mF2Pal16, however, since pepducins may negatively modulate the targeted receptor, we examined the effects also in "inhibitory mode experiments". Our data show that mF2Pal16 potently inhibited the response induced by the Fpr2 specific agonist PSMα2 with an IC50 ~ 30 nM  interacts with FPR2 and inhibits this receptor specifically [16 inhibit the response induced by the FPR2 agonist WKYMVM  is obviously not critical for pepducin action as the two pepducins induced very similar activities but with somewhat different potency. Human neutrophils were not activated by mF1Pal16  but not the Fpr1 inhibitor Boc2 .The mF1Pal F1Pal16 . Similar/- cells . Receptotrophils . In additor Boc2 . Very siThe formyl peptide receptors play important roles in host defense and as immune regulator , 2, suggth century as a novel concept for allosteric modulation of GPCR signaling [Pepducins with a peptide sequence identical to one of the intracellular domains or cytoplasmic tail of a GPCR were introduced in the early 21ignaling , 16, 33.ignaling . The sugignaling . Accordiignaling , 25. Sevignaling . Neverthignaling .16) targets this receptor  indicates that there is no fundamental difference in signaling profile between human and mouse derived peptides, as these two pepducins are almost identical (one amino acid difference) and they have the same effects, i.e., they negatively target human FPR2 and positively target the mouse Fpr2. This suggests that their effects can only be explained by the differences between FPR2 and Fpr2 across species. More importantly, they don’t target the receptor FPR1/Fpr1 predicted by the pepducin specificity concept. Instead, our data strongly suggests that some specific motif in FPR2/Fpr2 may recognize a lipopeptide pattern, as suggested by the fact that this receptor seems to be the primary target for pepducins derived also from other, sometimes totally unrelated, GPCRs [In agreement with the pepducin concept regarding origin and receptor specificity, the pepducin derived from the third intracellular loop of FPR2 targets FPR2, and the one derived from Fpr2  in the FPR2 pepducins is of prime importance for FPR2 activation; the K5 residue could be replaced by an R  without any activity major change, but when replaced by Q  the agonistic effect is completely lost [-/- cells strongly suggests that Fpr1 is not targeted by these pepducins. Although according to the pepducin concept an extracellular receptor antagonist, including Boc2, should not affect the pepducin activity, our earlier studies have demonstrated that this rule does not apply to FPR2 activating pepducins [All activating pepducins examined in this study target not only FPR2 in human neutrophils but also the mouse neutrophil Fpr2. The C-terminus in these pepducins contain 6 amino acids that are identical in all of them, and our data from this and earlier published studies show that this part is of prime importance for activity. This is illustrated by the fact that upon a removal of this part from F1Palon Fpr2  as important regulators of the physiological processes leading to resolution of inflammation [Fpr genes in mice and humans and an incomplete understanding of the evolutionary relationship between human FPRs and their animal counterparts, also the fine-tuning of receptor ligands has obvious implications for how the results obtained should be interpreted [16 or mF1Pal16) can act as an agonist for Fpr2, and our data demonstrate new agonistic and antagonistic pepducins that might be useful tools for future translational studies in mouse models. These two FPR1/Fpr1-derived pepducins are almost identical in sequence (one amino acid difference) and exert similar effects, i.e., they both negatively target human FPR2 and positively target the mouse Fpr2. This suggests that there is no pharmacological profile difference between the two pepducins and the difference must be due to differences between the human and mouse receptors. More importantly, our data puts the pepducin specificity concept into question as these two pepducins don’t target FPR1/Fpr1 as expected. Availability of these well-characterized cross-species ligands is important to advance mouse disease models aimed at understanding the role of human FPRs in immune defense and inflammation. Our data reveal clearly that even small structural variations may abolish cross-species ligand recognition and this holds true for both agonists and antagonists. Cross-species receptor ligands for members of the FPR family, possessing a high degree of receptor-selectivity, are required for translation of activation/inhibition experiments performed with different animal disease models. Using mouse models for innate immune research always raises questions about species-specific differences that have to be considered when extrapolating results from the models to human diseases, but also there are reports describing differences in neutrophil biology between species. For example, mouse neutrophils do not produce defensins, an important group of microbial peptides produced by human neutrophils [Genetically modified mouse strains and mouse disease models provide excellent tools to study the function of neutrophil FPRs ammation . Howeverammation . In addierpreted . A largeerpreted . We now trophils .in vivo studies related to the pathophysiologic functions of FPR2. With its complexity in ligand binding and signaling modulation FPR2 provides an excellent model receptor for our understanding of GPCR signaling and modulation in general, and the potent and unique FPR2/Fpr2 modulating pepducins presented in this study could be excellent tools in future mechanistic and functional studies.In conclusion, we have identified both activating and inhibiting pepducins for mouse neutrophils and these pepducins display a receptor preference for Fpr2. Our data also highlight differences in ligand recognition between FPR2 and Fpr2 that have to be taken into account when choosing receptor specific ligands for translational studies across species. A better understanding of Fpr2 pharmacology is needed and will facilitate S1 Fig4 cells) were pre-incubated without (solid line) or with mF2Pal16 (250 nM) for 5 min before stimulation with the pepducin F1Pal16  and the release of superoxide anions was continuously measured. One representative experiment out of three performed with individual buffy coats is shown.WT mouse neutrophils (5 x 10(TIF)Click here for additional data file.S2 Fig5 cells) were pre-incubated with HRP and isoluminol followed by stimulation with the FPR2 specific agonist WKYMVM  or the pepducin mF1Pal16 . Arrow indicates the addition. The release of superoxide anions was continuously measured. One representative experiment out of five independent experiments performed with individual buffy coats is shown.Human neutrophils (10(TIF)Click here for additional data file.


Gallus gallus). Broiler breeder hens were exposed to two maternal temperatures (21°C and 32°C) × three maternal dietary zinc treatments  for 8 weeks. Maternal hyperthermia increased the embryonic mortality and induced oxidative damage evidenced by the elevated mRNA expressions of heat shock protein genes. Maternal dietary zinc deficiency damaged the embryonic development associated with the global DNA hypomethylation and histone 3 lysine 9 hyperacetylation in the embryonic liver. Supplementation of zinc in maternal diets effectively eliminated the embryonic mortality induced by maternal hyperthermia and enhanced antioxidant ability with the increased mRNA and protein expressions of metallothionein IV in the embryonic liver. The increased metallothionein IV mRNA expression was due to the reduced DNA methylation and increased histone 3 lysine 9 acetylation of the metallothionein IV promoter regardless of zinc source. These data demonstrate that maternal dietary zinc addition as an epigenetic modifier could protect the offspring embryonic development against maternal heat stress via enhancing the epigenetic-activated antioxidant ability.The role of maternal dietary zinc supplementation in protecting the embryos from maternal hyperthermia-induced negative effects via epigenetic mechanisms was examined using an avian model ( Maternal heat stress impairs the fetal and embryonic development in mammalian and avian species , 2. MateMT mRNA expression  × 3  factorial arrangement of treatments was adopted. Thus, a total of 6 treatment groups  were included. All eggs collected from the above 6 maternal treatments were incubated for 21 d.This study with all experimental procedures was approved by Animal Welfare Committee of the Institute of Animal Science, Chinese Academy of Agricultural Sciences. A total of 144 18-wk-old female broiler breeders  were randomly allotted to 1 of 6 treatments with 6 replicates (4 birds per replicate) for each treatment according to the experimental design. All broiler breeder hens were initially adapted from 18 to 29 wk of age using a conventional corn-soybean meal diet. The body Zn stores were deleted for all the birds from 30 to 32 wk of age using a corn starch-isolated soybean protein purified diet without Zn addition. After that, the birds in 3 dietary Zn treatments from the NT group were housed at 21 ± 1°C, while those in 3 dietary Zn treatments from the HT group were reared at 32 ± 1°C for the experimental period from 33 to 42 wk of age. All hens were provided free access to tap water and the experimental diets. Semen was collected from male broiler breeders from 27 to 29 wk of age and mixed, and the volume and numbers of semen and sperm motility were determined before insemination. Artificial insemination was performed for twice a week.4·7H2O) and the Zn proteinate with a moderate chelation strength  ×100.The MeDIP analysis for gene promoter was performed as previously described  with sompG sites . The relMT4 by real-time PCR with the same specific primers as described in MeDIP analysis. ChIP with antibodies against AcH3K9, nonspecific IgG as a negative control (NC) and blank control (BC) was used to determine the fidelity of the ChIP protocol (GAPDH promoter region. The fold enrichment of each target sequence was determined using the following formula [fold enrichment=2−(Ct IpAcH3K9–Ct input)] [The preparation of sonicated chromatin from the embryonic liver tissue samples was performed according to previous publication . The cruprotocol . The qPC input)] .P ≤ 0.05 and at 0.05 < P < 0.10 for a trend.Data were analysed by 2-way ANOVA using the general linear model procedure of the SAS 9.2 , and the model included the main effects of maternal environmental temperature, maternal dietary Zn, and their interaction, and treatment comparisons for significant differences were tested by the LSD method. Embryonic mortality data were transformed to arcsine values before statistical analysis. Each replicate served as the experimental unit for all statistical analyses. Significant differences were set at


Thus far, these oxygenation and metabolic parameters have been measured independently by different techniques in separate animals, precluding a comprehensive and correlative assessment of retinal oxygenation and metabolism dynamics. The purpose of the current study is to report an innovative optical system for dual oxyphor phosphorescence lifetime imaging to near-simultaneously measure retinal vascular PO2 and tPO2 in rats. The use of a new oxyphor with different spectral characteristics allowed differentiation of phosphorescence signals from the retinal vasculature and tissue. Concurrent measurements of retinal arterial and venous PO2, tPO2 through the retinal depth, inner retinal OEF, and outer retinal QO2 were demonstrated, permitting a correlative assessment of retinal oxygenation and metabolism. Future application of this method can be used to investigate the relations among retinal oxygen content, extraction and metabolism under pathologic conditions and thus advance knowledge of retinal hypoxia pathophysiology.The retina requires adequate oxygenation to maintain cellular metabolism and visual function. Inner retinal oxygen metabolism is directly related to retinal vascular oxygen tension (PO Furthermore, inadequate oxygen availability can lead to hypoxic injury and eventual cell death. Therefore, assessment of retinal oxygenation is essential to improve knowledge of disease pathophysiology and advance treatments that target alleviation of hypoxia-induced pathologies.The retinal tissue requires an adequate supply of oxygen for cellular metabolism and function. Retinal ischemia due to reduced blood flow has been implicated in the development of vision threatening pathologies such as neovascularization and macular edema2) has been performed by spectrophotometry5, photoacoustic ophthalmoscopy6, and visible optical coherence tomography8. Additionally, retinal vascular oxygen tension (PO2) has been reported using phosphorescence lifetime imaging11. Direct depth-resolved measurements of retinal tissue oxygen tension (tPO2) have been provided by the oxygen-sensitive microelectrode technique at single point locations14 and by phosphorescence lifetime imaging at multiple contiguous locations15. Furthermore, information about the metabolic activity of the retinal tissue has become available by calculation of inner retinal oxygen extraction fraction (OEF) based on retinal vascular oxygen content16 and by estimation of outer retinal oxygen consumption (QO2) from retinal tPO2 depth profiles18.Several techniques have become available for quantitative assessment of oxygen content within the retinal vasculature or tissue. Specifically, retinal oximetry for measurement of hemoglobin oxygen saturation  was administered intravenously (20 mg/kg) for retinal vascular PO2 imaging. Before imaging, pupils were dilated with 2.5% phenylephrine and 1% tropicamide, and a glass cover slip with 1% hydroxypropyl methylcellulose was placed on the cornea to minimize corneal refractive power and prevent dehydration. Rats were placed on an animal holder with a closed-loop water heater to maintain body temperature at 37 °C and were spontaneously breathing during imaging. One eye of each rat was imaged in temporal or nasal regions within three-disk diameters (600 microns) from the edge of the optic nerve head.All experimental procedures were in compliance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research and approved by the Animal Care Committee of the University of Illinois at Chicago. The study was performed in 10 Long Evans pigmented rats. Rats were anesthetized with intraperitoneal injections of ketamine (100 mg/kg) and xylazine (5 mg/kg) and additional injections were given as required to maintain anesthesia. One day prior to imaging, oxyphor G2  was constituted at 1.5 μM and administered as a 5 μL intravitreal bolus injection for retinal tPO15 for either retinal vascular PO2 or tPO2 measurement was modified for near-simultaneous measurement of both parameters by dual oxyphor phosphorescence lifetime imaging  and three repeated phase-delayed optical section phosphorescence images from the retinal vasculature were acquired at exactly the same retinal location. The total time for image acquisition was less than 60 seconds.2 in major retinal arteries and veins was measured from the phosphorescence lifetime using the Stern-Volmer equation and the R0 oxyphor’s quenching constant and lifetime in a zero-oxygen environment, as previously described20. PO2 in each blood vessel was calculated by averaging three repeated measurements. A mean arterial and venous PO2 (PO2A and PO2V) was determined for each rat by averaging measurements in each vessel type. Inner retinal OEF was calculated from PO2A and PO2V and using the oxyhemoglobin dissociation curve in rat21, as previously described16. Inner retinal OEF is the fraction of oxygen supplied by the retinal circulation that is extracted by the inner retinal tissue for metabolism, or equivalently, the ratio of inner retinal oxygen metabolism to inner retinal oxygen delivery.Vascular PO2 image was generated from the phosphorescence lifetime measured at each pixel using the Stern-Volmer equation and the G2 oxyphor’s quenching constant and lifetime in a zero-oxygen environment22, as previously described15. A mean depth-resolved retinal tPO2 image was generated from three repeated images.Retinal tissue optical section phosphorescence images were first processed to minimize retinal curvature, then smoothed in vertical (y-axis) and axial (z-axis) dimensions using a 2D anisotropic averaging filter (6 × 4 pixels), corresponding to 18 μm in both axes. A depth-resolved tPO2 image (superior to inferior), 35 contiguous tPO2 depth profiles were generated by vertically averaging tPO2 over 10 pixels (30 microns) and plotting tPO2 as a function of retinal depth, as previously described15. The outer and inner retina were defined as 50% to 100% and 0% to 50% of the retinal depth, respectively. Maximum outer retinal tPO2, minimum outer retinal tPO2, and mean inner retinal tPO2 were calculated from each tPO2 depth profile. Mean inner retinal tPO2 was plotted along the vertical dimension of the image to demonstrate changes in this parameter with respect to retinal arteries and veins. Furthermore, mean values for each parameter were calculated from all profiles along the tPO2 image.Along the vertical dimension of each retinal tPO2 depth profile, outer retinal QO2 was calculated by fitting a three-layer, one-dimensional, steady-state oxygen diffusion model using a non-linear least squares technique, as previously described23. In this model, oxygen diffuses in one dimension from the choroidal circulation across the outer retinal depth, which is divided into three layers14, based on their oxygen consumption properties. QO2 has been shown to be negligible in layers 1 and 323, which correspond to the photoreceptor outer segments and outer nuclear layer, respectively. In contrast, oxygen is consumed in layer 2 by mitochondria of the photoreceptor inner segments, yielding a quadratic relationship between tPO2 and retinal depth. A mean outer retinal QO2 was calculated by averaging measurements obtained from all tPO2 depth profiles along the vertical dimension of the tPO2 image.From each retinal tPOThe data generated are available from the corresponding author on reasonable request.2 and tPO2 image obtained at the same location overlaid on the retinal reflectance image is shown in Fig. 2 image displays measurements in two arteries and one vein, demonstrating higher PO2A than PO2V, as expected. The tPO2 image shows higher tPO2 near the chorioretinal interface compared to inner retina. Mean inner retinal tPO2 plotted along the vertical dimension (superior to inferior) is shown in Fig. 2 near arteries than the vein.A representative example of a retinal vascular PO2 and tPO2 measurements in all rats are presented in Fig. 2A and PO2V were 41 ± 5 mmHg and 25 ± 4 mmHg, respectively . Inner retinal tPO2, minimum outer retinal PO2, maximum outer retinal PO2 were 23 ± 7 mm Hg, 22 ± 5 mm Hg and 33 ± 8 mm Hg, respectively. There was no significant difference between PO2V and mean inner retinal tPO2 (P = 0.4). Inner retinal OEF was 0.58 ± 0.11 and outer retinal QO2 was 0.57 ± 0.27 mLO2/100 g*min. There was no significant correlation between inner retinal OEF and mean inner retinal tPO2 . As demonstrated in Fig. 2 and maximum outer retina tPO2 .Compiled retinal vascular PO2 and tPO2 was demonstrated by phosphorescence lifetime imaging of dual oxyphors delivered intravenously and intravitreally. For the first time, concurrent assessment of oxygen content across the retinal depth and oxygen metabolism metrics of the inner and outer retina was demonstrated. Future application of this method can provide knowledge of relations among these parameters under experimental pathologic conditions and thus yield a comprehensive understanding of retinal oxygenation and metabolism dynamics.A novel optical imaging method for near-simultaneous imaging of retinal vascular PO2A and PO2V were in general agreement with those from previous studies25. Depth-resolved retinal tPO2 images displayed maximum tPO2 near the choroid, consistent with normal physiology. Inner retinal tPO2 measurements using the G2 oxyphor were similar to our previously published data with the R2 oxyphor15 and those reported by the oxygen microelectrode technique14. Alterations in inner retinal tPO2 were consistent with the nearby presence of arteries and veins. Inner retinal OEF was 0.58, on average, indicating 58% of the oxygen delivered by the retinal circulation was extracted for metabolism by the inner retinal tissue. The mean inner retinal OEF was higher as compared to our previous study16 and maximum outer retinal tPO2 in the current study was slightly lower than previous reports15. Both of these results are consistent with the presence of reduced systemic oxygenation26, which likely resulted from the effect of anesthesia while the rats were under spontaneous breathing conditions27. Furthermore, the variability of tPO2 adjacent to the chorioretinal interface along the tPO2 image may, at least in part, be attributed to presumed anesthesia-induced systemic hypotension. This may have resulted in reduced choroidal blood flow, thus altering tPO2 gradients within the retinal depth. Overall, the results demonstrate the ability of the optical imaging system to measure retinal vascular PO2, tPO2 and inner retinal OEF.Measurements of retinal PO2 obtained in the current study were similar to our previously reported values17, but lower than those obtained by the oxygen microelectrode technique in light-adapted rats18. This difference is likely due to intraretinal phosphorescence scattering which decreases the depth resolution, minimizes the curvature of tPO2 profiles and calculated values of QO2. Nevertheless, outer retinal QO2 was significantly associated with maximum outer retinal tPO2, in agreement with a previous study14, though a small portion of oxygen utilized by the photoreceptors is supplied by the retinal vasculature14. This result suggests a dependence of the photoreceptor metabolic function on the level of oxygen supplied by the choroidal circulation.Measurements of outer retinal QO2 and tPO2 coupled with derivation of inner retina OEF and outer retinal QO2 can advance knowledge of retinal oxygen dynamics. For example, we demonstrated here, for the first time, that there was no significant correlation between inner retinal OEF and mean inner retinal tPO2 under healthy condition. This result suggests that despite physiological variations, tPO2 is well-maintained due to compensatory alterations in OEF and oxygen delivery, and implies the presence of highly effective regulatory mechanisms. Previous studies have shown alterations in OEF under experimental hypoxia in rats16. In future studies, by relating inner retinal tPO2 with OEF under graded hypoxia/ischemia, diabetes or light flicker stimulation, the OEF threshold necessary to sustain tPO2 may be identified. Additionally, data obtained under graded levels of ischemia may be used to establish a relationship between inner retinal tPO2 and PO2V. Furthermore, combined retinal blood flow measurements with the current method can be used to determine the inner retinal oxygen delivery threshold necessary to maintain retinal tPO2 with direct relevance to retinal ischemic diseases. These thresholds can only be accurately determined with concurrent retinal vascular PO2 and tPO2 measurements in the same animal.Simultaneous measurements of retinal vascular PO2 were obtained from literature and may be different within the retinal tissue environment. Phototoxicity may affect data derived from images acquired repeatedly at the same location with R0 oxyphor28, but any effect of phototoxicity on measurements derived using the G2 oxyphor is not known. Although, the laser irradiance was below the threshold for tissue damage, repeatability of measurements obtained at the same location with the use of dual oxyphors will need further evaluation. The feasibility of the method was demonstrated in a limited number of rats and future studies using larger sample sizes are needed to fully establish the utility of the method.One potential limitation of this method is the scattering of phosphorescence light within the retina and vitreous which can degrade image quality. However, compared to the R2 oxyphor, less scattering is expected from the G2 oxyphor due to its longer phosphorescence emission wavelength. The quenching constants used to calculate POIn conclusion, for the first time, near-simultaneous measurement of retinal vascular and tissue oxygen tension by phosphorescence lifetime imaging was demonstrated. Future application of this method under challenged physiologic or pathologic conditions permits correlation of retinal vascular and tissue oxygen content and can potentially elucidate retinal oxygenation dynamics.


Porcine circovirus type 2 (PCV2) diagnostics in live pigs often involves pooled serum and/or oral fluid samples for group-level determination of viral load by quantitative real-time polymerase chain reaction (qPCR). The purpose of the study was to compare the PCV2 viral load determined by qPCR of paired samples at the pen level of pools of sera (SP) from 4 to 5 pigs and the collective oral fluid (OF) from around 30 pigs corresponding to one rope put in the same pen. Pigs in pens of 2 finishing herds were sampled by cross-sectional (Herd 1) and cross-sectional with follow-up (Herd 2) study designs. In Herd 1, 50 sample pairs consisting of SP from 4 to 5 pigs and OF from around 23 pigs were collected. In Herd 2, 65 sample pairs consisting of 4 (SP) and around 30 (OF) pigs were collected 4 times at 3-week intervals.A higher proportion of PCV2-positive pens (86% vs. 80% and 100% vs. 91%) and higher viral loads (mean difference: 2.10 and 1.83 log(10) PCV2 copies per ml) were found in OF versus SP in both herds. The OF cut-off value corresponding to a positive SP (>3 log(10) PCV2 copies per ml) was estimated to 6.5 and 7.36 log(10) PCV2 copies per ml for Herds 1 and 2, respectively. Significant correlations between SP and OF results were found in Herd 1 (rho = 0.69) and the first sampling in Herd 2 (rho = 0.39), but not for the subsequent consecutive 3 samplings in Herd 2.The proportion and viral loads of PCV2 positive pens were higher in collective OF (including up to 30 pigs) compared to SP (including 4–5 pigs) of the same pens. Also, OF seemed to detect the PCV2 infection earlier with OF values just below 6.5 (Herd 1) and 7.36 (Herd 2) log(10) being associated with a negative SP for the same pen. Nevertheless, a statistically significant correlation between SP and OF could not be found for all sampling time points, probably due to a high within-pen variation in individual pig viral load becoming very evident in SP of only four or five pigs. Consequently, the results imply that OF is well suited for detecting presence of PCV2 but less so for determining the specific viral load of pigs in a pen. Porcine circovirus type 2 (PCV2), a circular, single-stranded, non-enveloped DNA virus has been demonstrated to be present in almost all commercial swine herds worldwide , 2. PCV2Vaccination provides an effective tool to control PCV2 infections –17 but iHaemophilus parasuis and Streptococcus suis has since been demonstrated [In the last 10 years, oral fluid sampling has gained growing interest as an even more cost and time-saving method while also considering animal welfare. The sampling procedure consists of hanging a cotton rope in a pen for the pigs to chew on, followed by wringing of the rope to release the oral fluid. The method was initially described in 2008 , 20, andnstrated . Also fonstrated , 24–26.r = 0.76) between viral loads in the two sample types [r = 0.78) between viral loads in oral fluid (20–30 pigs per pen) and pooled serum (5 pigs) was found to be significant in another study [Some previous studies have compared detection and load of PCV2 by PCR in serum and oral fluid. A fair agreement between individual PCV2-positive serum and oral fluid samples (kappa = 0.24) but a poor agreement between pooled serum and oral fluid collected from pen-housed pigs  has been found . Anotherle types . A similer study .The inconclusive and limited number of studies regarding the association between viral loads in pooled serum and oral fluid at pen level and possible differences between PCR-assays require further elucidation by including additional herds/samples for the comparison. Moreover, since both oral fluid and pooled serum sampling are done with the purpose of diagnosing PCV2 infection in a group of pigs, determination of the oral fluid viral load corresponding to a positive serum pool is relevant for practical validation of oral fluid as a substitute for serum pools. Consequently, the objectives of this study were to: 1) determine the oral fluid viral load cut-off agreeing best with a PCV2-positive serum pool and 2) compare viral loads of PCV2 in serum pools and collective oral fluid from pigs in the same pen.Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae type 2 + 6 + 12 and PRRSv) and samples were collected between September 2014 and July 2015 as a part of a larger field trial. None of the herds vaccinated against PCV2 prior to initiation of sampling, but in the field trial in Herd 2, half of the finishers were vaccinated during sample collection as a part of a PCV2 vaccine trial. However, only PCV2-qPCR results from the non-vaccinated group were included in the present study and an overview of the serum results have been presented briefly elsewhere [Serum and oral fluid samples were collected in 2 PCV2-infected finishing herds (Herd 1 and 2). Neither of the herds experienced clinical signs attributable to PCV2 infection  . Herd 1 lsewhere .At the time of sampling in Herd 1 (August 2010), no previous studies had estimated the correlation coefficient between serum pools and oral fluid samples and the interest of the study was therefore to determine whether or not a correlation existed. Therefore, the sample size calculation was based on detecting a correlation coefficient equal to or higher than 0.4 at a significance level of 95% and a power of 0.8 corresponding to a sample size of 47 . In HerdThe study design in Herd 1 was cross-sectional with all samples collected from pigs of 3 different age groups in one day. The study design in Herd 2 was cross-sectional with follow-up consisting of totally 4 repeated samplings of the same pigs/pens at 3-week intervals. Serum and oral fluid were collected simultaneously at each sampling.th pig in the pen depending on the number of pigs per pen, assuring that 5 or 4 pigs per pen were selected in Herd 1 and 2, respectively. In Herd 2, the same 4 pigs per pen were bled at the 4 consecutive sampling time points .The study unit was the pen. Herd 1 had a total of 64 pens of which 50 were randomly (with age-stratification) selected for sampling . In HerdBlood samples were collected from the cranial vena cava in plain tubes. In Herd 1, the blood samples were transported directly to the laboratory after sampling and refrigerated overnight. In Herd 2, samples were kept refrigerated overnight and were shipped to the laboratory by mail the following day.At the laboratory, blood samples were centrifuged to separate serum. Equal amounts of serum from each of the 4/5 pigs per pen were pooled prior to PCV2-qPCR analysis, resulting in one serum PCV2 copy number  per pen. Thus, serum viral loads refer to qPCR-results from pooled serum samples.Sampling of oral fluid was performed as previously described . BrieflyThe oral fluids collected in both herds were grey and dirty in appearance, probably reflecting fecal contamination. Feces as well as saliva can contain PCR inhibitors –36 and i1. DNA extraction from serum from Herd 1 was performed differentlyDNA extraction from all oral fluid samples and the serum samples from Herd 2 was performed with a commercially available extraction kit1 to avoid false negative test results. Oral fluid viral loads were subsequently corrected according to the extra dilutions. The qPCR-assay had a detection limit of 103 and a quantification range of 3.3 × 104–3.3 × 109 PCV2 copies per ml [4 versus 103). Samples were considered positive when the viral load was above the detection limit.The serum and oral fluid samples were tested for PCV2-DNA by qPCR essentially as previously described . During s per ml . BecauseAll PCV2 viral loads were analyzed on a log-transformed scale. Comparison of PCV2 viral loads in serum and oral fluid was made separately for Herd 1 and 2, and because the same pens were repeatedly sampled in Herd 2, and hence could not be considered independent, each sampling time point in Herd 2 was also analyzed separately. Viral loads below the assay detection limit were included in the statistical analyses with a value of 0, since the true distribution of these was unknown and excluding the observations would reduce the actual variation and thereby bias the results.Descriptive statistics consisted of frequency distributions, graphical illustrations and summary statistics. Evaluation of agreement between serum and oral fluid PCV2 viral loads was done both on a dichotomous (PCV2-positive/negative) and a quantitative scale. On a dichotomous scale, the oral fluid cut-off value for obtaining the best agreement with a PCV2-positive serum result (above the test detection limit of 3 log(10) PCV2-copies per ml serum) was estimated by drawing a receiver operating characteristic (ROC)-curve for all possible oral fluid cut-off values against a serum value fixed at the assay detection limit. Best agreement was defined as the oral fluid cut-off value where relative sensitivity and relative specificity were maximized simultaneously. The terms ‘relative sensitivity’ and ‘relative specificity’ were used, since the serum result could not be considered ‘gold standard’ in the classical sense but rather a ‘reference standard’ (as in a study from 2003 ). All saIn total, 310 serum and oral fluid sample pairs were collected. Of these, 50 sample pairs were from Herd 1 with 4–5 pigs bled per pen with a mean of 23 pigs per pen (range: 5–33) and 260 sample pairs (65 pens sampled 4 times) were from Herd 2 with 4 pigs bled per pen with a mean of 29 pigs per pen (range: 9–32). The number of pigs per pen reflects the maximum number of pigs contributing to the oral fluid sample.Classification of sample pairs into PCV2 positive and PCV2 negative based on the test detection limit is shown in Table The 2 ROC-curves (one for Herd 1 and one for the first sampling in Herd 2) for evaluation of best agreement between serum and oral fluid concerning a PCV2-positive serum result are displayed in Fig. Figure Results from the linear regression models showed that oral fluid viral load was not significantly influenced by the number of pigs per pen when the viral load in serum (Herd 1 and 2) and sampling number (Herd 2) were also included in the models.Overall, both herds had a widespread PCV2 infection with moderate viral loads resulting in relatively few serum pools and even fewer oral fluid samples being negative. A relatively small number of serum pools had viral loads above 7 log(10), which fits well with the observation that no clinical signs clearly related to PCV2 infection were present in either of the 2 herds. This, however, also implies that generalizing results to herds with high viral loads and/or clinical signs of PCV2 infection should be done with caution. Only one sample pair had a positive serum PCV2 result (5.59 log(10) PCV2 copies per ml serum) and a negative oral fluid PCV2 result, which may reflect that not all blood-sampled pigs chewed on the rope. The estimated contribution to the oral fluid sample of more than 80% of the pigs in a pen is supported by a study reporting that 94% of pigs in a pen (pen size: 17–24 pigs) had chewed on the presented rope after 30 min .As expected, a slightly higher proportion of oral fluid samples compared to serum were PCV2 positive which probably reflects that the likelihood of a positive result is higher when more animals are tested . This is similar to previous findings concerning PCV2 , 29 and The estimated oral fluid cut-offs for best agreement (the highest possible relative sensitivity and specificity) with a PCV2-positive serum pool were fairly similar for Herd 1 and 2 (first sampling) with 6.5 and 7.36 log(10) PCV2 copies per ml oral fluid, respectively. However, the oral fluid cut-off was determined with a higher accuracy in terms of relative sensitivity and specificity for Herd 1 than for Herd 2, probably due to the lower variation between individual oral fluid results in Herd 1 compared to Herd 2 (first sampling)  PCV2 copies per ml sample was found in both herds, hence, substantially higher than the 1 log(10) reported by others , 30. WheSecondly, higher PCV2 viral loads may be present in oral fluid compared to the viral loads found in serum. Previous comparisons of serum and oral/tonsillar swabs found either no difference concerning prevalence of PCV2 positives , 45 and A significant correlation between serum and oral fluid viral loads was found for Herd 1 and the first sampling in Herd 2, whereas no significant correlations were found for samplings 2, 3 and 4 in Herd 2. For Herd 1, the estimated correlation coefficient of 0.69 was comparable to the 0.76 and 0.78 previously reported , 29. HowFor the first sampling in Herd 2, the correlation coefficient, even though significant, was only estimated to 0.39, which may be due to the high number of negative serum pools. For samplings 2, 3 and 4 in Herd 2, no statistically significant correlations were found between serum pools and oral fluid. A higher proportion of pigs in the pen were blood sampled in Herd 1 (~ 20%) compared to Herd 2 (~14%), which would seem like a plausible explanation, but the results from the linear regression models showed that the number of pigs per pen at sampling did not influence the oral fluid viral load when the serum viral load (Herd 1 and 2) and sampling number (Herd 2) were accounted for. Another explanation could be the higher variation in positive serum viral loads for all samplings in Herd 2 compared to Herd 1  being associated with a negative serum pool for the same pen. Nevertheless, a statistically significant correlation between serum pools and oral fluid samples could not be found for all sampling time points, probably due to a high within-pen variation in individual pig viral load becoming very evident in serum pools including only four or five pigs in a pen of around 30. Hence, from a practitioner’s point of view, oral fluid might be better suited to identify presence or not of the pathogen than to determine the specific viral load.