text
stringlengths 7
107k
|
|---|
This contrasts to chronic Q fever, where granulomas have not been described before. (17, 16 19) In particular, Lepidi described that resected valve specimens of patients with Q fever endocarditis 17 lacked well-formed granulomas. (12) In vascular Q fever, granulomatous responses consisting of 18 histiocytes surrounding necrotic areas have been reported in Q fever AAAs, however well-formed 19 granulomas were not found. (20) Thus, we would interpret the absence of organized granulomas as 20 the first clue for an immune-suppressed environment in AAA of Q fever patients that allows 21 persisting infection after the acute phase. 22 23
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 11 Secondly, our results demonstrate some similarities between Q fever AAAs and AAAs. Percentages of 1 CD3+ T cells, CD20+ B cells, CD1c+ cDC2, CD15+ neutrophils, and CD68+ macrophages are similar 2 between the groups with atherosclerotic AAA and Q fever AAA. This finding is supported by the PCA, 3 which shows overlapping populations of atherosclerotic and Q fever AAAs when entering these 4 inflammatory cell markers. This does not come as a surprise since it is well established that vascular 5 Q fever develops in preexisting atherosclerotic aneurysms. (5, 7, 20-22) 6 7 Despite the similarities, we discovered that atherosclerotic and Q fever AAAs do have important 8 differences, which emerge when investigating macrophage and T cell subset markers. Macrophages 9 in Q fever AAAs were found to be polarized into the less inflammatory M2 phenotype, which is 10 ‘tolerogenic’ and poorly microbicidal, in contrast to the M1 phenotype that possesses a machinery 11 that can clear an infection. Interestingly, in the AAAs we found less M2 polarization. This would 12 either indicate that macrophages polarize towards M2 in response to C. burnetii infection, or that the 13 presence of M2 polarization is a prerequisite for C. burnetii persistence. Previous studies have 14 demonstrated that C. burnetii inhabits and proliferates in monocytes and macrophages, and more 15 specifically, in resident vascular wall macrophages in case of vascular Q fever. (10, 12) It has been 16 shown by Benoit et al. that C. burnetii stimulates an atypical M2 activation program in monocyte-17 derived macrophages in vitro. (14) M2 polarization of macrophages was also observed in C. burnetii 18 infected transgenic mice constitutively expressing IL-10 in macrophage lineage, a mouse model for 19 chronic Q fever pathogenesis. (23) Spleens and livers of these mice showed increased expression of 20 arginase-1 and mannose receptor (CD206) and decreased expression of iNOS, IL-12 and IL-23 in 21 bone-marrow derived macrophages after infection with C. burnettii compared to C. burnetii-infected 22 wild type mice. |
These previous findings suggested that chronic Q fever is associated with M2 23 polarization of macrophages, but direct evidence in chronic Q fever patients was lacking. Our findings 24
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 12 establish that outgrowth and persistence of C. burnetii in AAAs is associated with the predominance 1 of M2 macrophages. 2 3 There are several possible explanations for the lack of macrophage activation. First, our results 4 demonstrate decreased expression of GM-CSF in Q fever AAAs compared to AAAs. GM-CSF is a pro-5 inflammatory cytokine that activates granulocytes and macrophages. (24) Its decreased expression in 6 Q fever AAAs may contribute to the immune suppressive environment in Q fever AAA. The role of 7 GM-CSF in the context of aneurysm formation has been investigated previously. (25) Strikingly, Son 8 et al described increased occurrence of aortic dissection and intramural hematoma in wild type mice 9 subjected to aortic inflammation (CaCl2 + Ang II administration) when also receiving GM-CSF. Only 10 administrating GM-CSF, without the prerequisite of aortic inflammation, did not result in aortic 11 dissection or intramural hematoma. Its potential clinical relevance was confirmed in human blood: 12 GM-CSF serum levels of patients suffering from acute dissection were higher than controls with 13 coronary artery disease, aortic aneurysms of healthy volunteers. (25) Additionally, in our cohort we 14 found that Q fever AAAs rupture at smaller diameter compared to atherosclerotic AAA. This finding, 15 combined with the GM-CSF paradox, suggests that the development of Q fever AAAs and 16 atherosclerotic AAAs follow different pathways, however strictly hypothetically. 17 18 Second, a key cytokine in activation is IFNg, a T-helper (Th)-1 cytokine that activates macrophages 19 and makes them more microbicidal. Previous studies from our group have demonstrated that 20 peripheral blood mononuclear cells from patients with chronic Q fever exhibit an abundant 21 production of IFNg when exposed to C. burnetii antigens. (8, 9) These findings were enigmatic since 22 there is an apparent inability of the patient’s immune system to kill C. burnetii at the infected sites. 23 The current findings would be compatible with a downregulated IFNg response at the infected site. 24
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 13 1 In addition to differences in macrophage subsets, differences in T cell subsets were also observed. |
2 First, the number of cytotoxic T cells was increased in both infiltrate and surrounding tissue of Q 3 fever AAA compared to AAA. Although the numbers of cytotoxic T cells were high, their function 4 might be compromised, resulting in defective elimination of C. burnetii. The increased numbers of 5 regulatory T cells we found in Q fever AAAs may play a role here. An increased number of circulating 6 regulatory T-cells has also been shown by Layez et al in Q fever endocarditis patients and in acute Q 7 fever patients. (13) Regulatory T cells can inhibit cytotoxic T cells directly or indirectly (26), with a 8 possible role for IL-10 produced by this T cell subset. An important role of IL-10 in chronic 9 development of Q fever has been postulated based on converging evidence from a series of in vitro 10 studies. IL-10 production by peripheral blood mononuclear cells from patients with Q fever 11 endocarditis and Q fever with valvulopathy who were at risk for developing chronic Q fever was high, 12 compared to control individuals. (27, 28) Moreover, IL-10 specifically increases C. burnetii replication 13 in naive monocytes (29) possibly by downregulating IFNg. Finally, low IL-10 production in monocytes 14 from patients with acute Q fever was associated with C. burnetii elimination, whereas C. burnetii 15 replicated in monocytes from patients with chronic Q fever and high IL-10 production. The 16 microbicidal activity of monocytes from patients with chronic Q fever was restored by neutralizing IL-17 10. (30) The murine model of chronic Q fever mentioned above, also confirmed a key role for IL-10 in 18 bacterial persistence. C. burnetii infection is persistent in mice that overexpress IL-10 in the 19 macrophage compartment. (23) Thus, IL-10 could play a crucial role in this immune-suppressed 20 environment. 21 22 The last major difference between Q fever AAA and atherosclerotic AAA is the extent of damage to 23 the vascular wall architecture in Q fever AAAs. This is demonstrated by extensive loss of elastin fibers 24 and increase of fibrosis present in the vascular wall. Fragmentation of elastin fibers has been 25
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 14 described for AAAs previously (16), however we found the loss of elastin fibers more evident in the 1 lesions from Q fever AAAs than atherosclerotic AAAs. Fibrosis is characterized by replacement of 2 normal tissue by excessive connective tissue, and usually follows chronic inflammation. This may be 3 the effect of persistent presence of growth factors, proteolytic enzymes, angiogenic factors, and 4 profibrotic cytokines. (31, 32) Previously, fibrosis was also observed in chronic Q fever endocarditis in 5 humans and cows. |
(12, 33-35) This indicates that our Q fever AAA cohort suffered from more 6 destructive disease than our AAA cohort. 7 8 These novel insights could lead to new clues for novel treatments and thus developments for clinical 9 care. Currently, Q fever AAA still leads to significant morbidity and mortality rates despite antibiotic 10 and surgical treatment. Epidemiological studies demonstrate the similar risk profile of Q fever and 11 non-Q fever infected AAAs, yet the risk of complications is higher in the Q fever infected group (7), 12 even up to 61% (6), and 25% of patients suffering from Q fever AAA had deceased with a 13 definitely/probably chronic Q fever related cause of death. (6) Here, we confirm that in vascular Q 14 fever, the local immune response is skewed towards an immunotolerant state. Hypothetically, the 15 decreased expression of GM-CSF suggests a possible role for immunomodulating treatment, for 16 example with administration of recombinant GM-CSF. This is already approved for neutropenia due 17 to myelosuppression (36), and has been suggested for treatment for pulmonary tuberculosis. (37) 18 There might be a role for immunomodulating adjuvant therapies in patients with Q fever AAA in 19 whom treatment failure is observed with antibiotics alone. 20 21 Our study was the first to use mIHC in Q fever AAA and thereby to gain information about the 22 number and proportion of immune cells, and simultaneously obtain spatial information. This 23 powerful technique and the access to rare Q fever AAA tissue are strengths of this study. While other 24 studies have tested for immune cell activation and recruitment in peripheral blood, we were able to 25
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 15 study the actual infected tissue. Interpreting our results in context of previous observations enables 1 us to increase our understanding of the pathophysiology of Q fever AAA. Still, several limitations 2 should be noted. First, our sample size is limited with only ten vascular Q fever samples. However, 3 this is still the largest study investigating local immune responses in Q fever AAA in humans. In 4 addition, in our quantification method we include entire slides up to 238 20x views per patient, 5 which minimizes the effects of the small sample size. Second, consistent with IHC studies in general, 6 we can only describe the immune cells we observe, without answering mechanistic questions. 7 Nevertheless, when interpreting our results in light of the current literature, we can reasonably 8 formulate hypotheses about the pathophysiology and test these in further research. 9 10 Taken together, this leads to the following model with a prominent role for immune suppression. |
11 First, macrophages that harbor C. burnetii are not effectively killing the organisms, probably due to a 12 lack of activation by proinflammatory cytokines like GM-CSF and IFN-g in a microenvironment with 13 excess IL-10. Second, effector T cells that attempt to eliminate the intracellular bacterium residing in 14 monocytes and macrophages, are hindered by regulatory T cells that are prominent IL-10 producers. 15 Third, there is a lack of microbicidal M1 macrophages, instead macrophages are polarized into the 16 tolerogenic M2 phenotype, which leads to insufficient attack of the pathogen, enabling persistent 17 infection. 18
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 16 Methods and materials 1 Abdominal aorta tissue samples from patients with Q fever infected aneurysms and control groups 2 were investigated with a novel mIHC method to study the involvement of the innate and adaptive 3 immune system in vascular Q fever. The data underlying this article will be shared upon reasonable 4 request to the corresponding author. 5 6 Patient samples 7 Tissue samples were collected from four groups of patients in two Dutch hospitals: Jeroen Bosch 8 Hospitals in ‘s Hertogenbosch and Radboud university medical center in Nijmegen. The first group 9 consisted of patients diagnosed with C. burnetii infected AAA (Q fever AAA) according to the Dutch 10 consensus guideline (38): all patients had an abdominal aneurysm (AAA) and IgG phase I was at least 11 1:1024 in combination with a positive PCR of aortic tissue. The second group consisted of patients 12 with atherosclerotic atherosclerotic AAA without clinical suspicion of Q fever. The third group 13 consisted of patients with an acutely infected AAA, with the same definition of AAA in combination 14 with positive cultures of Streptococcus pneumoniae and Streptococcus Agalactiae, respectively. In 15 these three groups AAA was defined as a CT proven abdominal aortic aneurysm with a diameter of at 16 least 3.0 cm. (39) All aneurysmatic tissue samples were either obtained from patients undergoing 17 elective surgical repair or emergency repair in case of aortic rupture. The fourth group consisted of 18 abdominal aorta samples from patients undergoing kidney explantation surgery for transplantation 19 purposes, with an aortic diameter smaller than 3.0 cm. The samples from Jeroen Bosch Hospital were 20 described in a previous study. (20) 21 The medical ethics committees of the institutions approved the study, in line with the principles 22 outlined in the Declaration of Helsinki (Radboudumc: 2017-3196; Jeroen Bosch Hospital: 23 2019.05.02.01). 24
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 17 1 Tissue Processing 2 During surgery, the ventral part of the abdominal aorta was removed. If necessary, adhering thrombi 3 were gently removed from the tissue before further processing. Directly after collection, samples 4 were fixed in buffered 4% formaldehyde for at least 24 hours and no longer than 72 hours. If large 5 amounts of calcification were present, samples were decalcified by storing them in EDTA solution for 6 another 24 hours. Subsequently, samples were carefully embedded in paraffin in an attempt to 7 include all aorta layers (formalin fixed and paraffin embedded (FFPE)). Of these tissues, full thickness 8 transverse sections of 4 µm were mounted on silane coated glass slides (New Silane III, MUTO PURE 9 CHEMICALS, Japan). 10 11 Multiplex Immunohistochemistry 12 Samples were stained with two mIHC panels, which enclosed the innate and adaptive immune 13 system (Table 2). Optimization and validation of mIHC panels were performed as described 14 previously. (40) Samples were stained with six consecutive tyramide signal amplification (TSA) stains 15 followed by antigen stripping after every staining. This resulted in the fluorophore remaining on the 16 target, thus enabling eight simultaneous colors on one slide (six markers, DAPI and 17 autofluorescence). Slides were stained automatically in a Leica Bond system (BOND-Rx Fully 18 Automated IHC and ISH, Leica Biosystems). After positioning in the machine, slides were 19 deparaffinized, rehydrated and washed with demi water. After this, samples underwent heat induced 20 antigen retrieval (HIER) in BOND Epitope Retrieval 2 (AR9640, Leica Biosystems) or BOND Epitope 21 Retrieval 1 (AR9961, Leica Biosystems) during 20 minutes for the adaptive and innate panel, 22 respectively. Then, protein blocking in Akoya Antibody Diluent/Block (Akoya biosciences, MA) took 23 place for 10 minutes, followed by incubation with the first primary antibody for 1 hour, subsequently 24 with the secondary antibody (Polymer HRP, Ms + Rb (Akoya biosciences, MA)) for 30 minutes and 25
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 18 finally with an Opal fluorophore ((Akoya biosciences, MA) dissolved 1:50 in 1 X Plus Amplification 1 Diluent (Akoya biosciences, MA) for 10 minutes. To facilitate multiplex staining with six markers, 2 samples were heated for 10 minutes which enabled antigen stripping. After this staining cycle, this 3 procedure was repeated for five different primary antibodies, the secondary antibody and 4 corresponding Opal fluorophores. Finally, DAPI was used as a nuclear counterstain and slides were 5 mounted with Fluoromount-G (0100-01; Southern Biotech, Birmingham, AL, USA). |
All incubations 6 steps were performed at room temperature. Please see Supplementary Table 2 for a more detailed 7 overview of the used reagents. 8 9 Imaging, multispectral unmixing and analysis 10 After staining, image acquisition and immune cell quantification were performed using an automated 11 approach. First, the PerkinElmer Vectra (Vectra 3.0.3; PerkinElmer, MA) scanned whole slides at 4x 12 magnification and 20x magnification, allowing precise cell segmentation incorporating the entire 13 sample. The average 20x views per slide was 283 resulting in an average tissue area of 59.0 ± 32.6 14 mm2, and this high number substantially reduces the chance of sampling bias. Spectral libraries and 15 inForm Advanced Image Analysis software (inForm 2.4.8; Akoya biosciences, MA) unmixed these 16 multispectral images (Supplementary Figures 1A and 2A). 17 Subsequently, inForm Advance Imaging Analysis software was used for segmentation of tissue and 18 cells. For tissue segmentation, tissue slides were divided into tissue, infiltrate, thrombus, blood, and 19 background (Supplementary Figure 1C). This segmentation was based on DAPI, autofluorescence 20 and, if present, also CD20 and CD3. For single cell segmentation, cells were identified with DAPI and 21 autofluorescence, and, depending on the panel, with membrane markers CD20 and CD3 22 (Supplementary Figure 1B) or CD68, CD206 and CD15. Requiring DAPI for cell segmentation ensured 23 the exclusion of artifact staining, in which DAPI is absent. The output of the software was 20x 24 magnification images and cell data (localization, tissue, phenotype, and marker) per slide. Images 25
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 19 were combined into single flow cytometry standard (fcs) files, allowing analysis in FlowJo (FlowJo 1 10.0.7, Becton Dickinson, NJ). In FlowJo, only cells in tissue and infiltrate were analyzed and gates 2 were drawn as shown in Supplementary Figure 1E for the adaptive panel and Supplementary Figure 3 2B for the innate panel by two observers with excellent interobserver correlation (Supplementary 4 Figure 1D and 2D). 5 These clear distinct positive cell populations were not found for CD45RO and MMP9 as their 6 expression is gradual. (41) For that matter, the gates for these markers were drawn in negative 7 populations, namely non-T cells and non-neutrophils, respectively. Following this, these gates were 8 copied to populations that could express these markers. GM-CSF fcs files did not show distinct 9 positive and negative populations although they were visible at the microscopy images. Therefore, 10 inForm Advance Imaging Analysis software was used for automatically thresholding for GM-CSF per 11 sample, providing the number of GM-CSF positive pixels per sample (Supplementary Figure 2C). |
12 13 Histology 14 To study vessel wall architecture, tissue samples were stained with hematoxylin-eosin (HE) and 15 Elastin von Gieson (EVG). 16 17 Statistical analysis 18 SPSS for Windows (IBM Corp, 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM 19 Corp) was used for statistical analysis. PRISM 8.0.2 (Graphpad, GSL Biotech LLC, CA) was used for 20 visualization of results. Continuous data were expressed as mean ± standard deviation (SD), or in 21 case of non-Gaussian distribution, as median (interquartile range) (IQR). Kruskal-Wallis test adjusted 22 with Bonferroni correction for multiple testing was used for testing continuous variables between 23
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 20 four groups. Binary variables were tested for differences using the Fisher exact test. Interobserver 1 variability was calculated with the intraclass correlation coefficient (ICC). Correlations between 2 continuous non-Gaussian distributed variables were studied with Kendall's tau because of low 3 numbers per group. P < 0.05 was considered statistically significant. Principal component analysis 4 was performed in RStudio 1.2.5033 (RStudio, inc. Boston, MA) and R (R Foundation for Statistical 5 Computing, Vienna, Austria) using singular value decomposition and the tidyverse (42) and factoextra 6 packages. (43) 7 8 Acknowledgements 9 The authors would like to acknowledge Anne van Duffelen and Kiek Verrijp for their help in 10 optimizing the staining procedure, Jelena Meek for assistance in staining, Inge Wortel, Shabaz Sultan, 11 and Johannes Textor for their help in data analysis, and Janneke Timmermans for her feedback. This 12 work was supported by SCAN consortium: European Research Area - CardioVascualar Diseases (ERA-13 CVD) grant [JTC2017-044] and TTW-NWO open technology grant [STW-14716]. 14 15 16 Competing interests 17 None declared. 18 19
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 21 References 1 1. Maurin M, Raoult D. Q fever. Clin Microbiol Rev. 1999;12(4):518-53. 2 2. Fournier PE, Marrie TJ, Raoult D. Diagnosis of Q fever. J Clin Microbiol. 1998;36(7):1823-34. 3 3. Kampschreur LM, Dekker S, Hagenaars JC, Lestrade PJ, Renders NH, de Jager-Leclercq MG, et 4 al. Identification of risk factors for chronic Q fever, the Netherlands. Emerg Infect Dis. 5 2012;18(4):563-70. 6 4. Wegdam-Blans MC, Vainas T, van Sambeek MR, Cuypers PW, Tjhie HT, van Straten AH, et al. |
7 Vascular complications of Q-fever infections. Eur J Vasc Endovasc Surg. 2011;42(3):384-92. 8 5. Botelho-Nevers E, Fournier PE, Richet H, Fenollar F, Lepidi H, Foucault C, et al. Coxiella 9 burnetii infection of aortic aneurysms or vascular grafts: report of 30 new cases and evaluation of 10 outcome. Eur J Clin Microbiol Infect Dis. 2007;26(9):635-40. 11 6. van Roeden SE, Wever PC, Kampschreur LM, Gruteke P, van der Hoek W, Hoepelman AIM, et 12 al. Chronic Q fever-related complications and mortality: data from a nationwide cohort. Clin 13 Microbiol Infect. 2019;25(11):1390-8. 14 7. Hagenaars JC, Wever PC, van Petersen AS, Lestrade PJ, de Jager-Leclercq MG, Hermans MH, 15 et al. Estimated prevalence of chronic Q fever among Coxiella burnetii seropositive patients with an 16 abdominal aortic/iliac aneurysm or aorto-iliac reconstruction after a large Dutch Q fever outbreak. J 17 Infect. 2014;69(2):154-60. 18 8. Schoffelen T, Sprong T, Bleeker-Rovers CP, Wegdam-Blans MC, Ammerdorffer A, Pronk MJ, et 19 al. A combination of interferon-gamma and interleukin-2 production by Coxiella burnetii-stimulated 20 circulating cells discriminates between chronic Q fever and past Q fever. Clin Microbiol Infect. 21 2014;20(7):642-50. 22 9. Schoffelen T, Textoris J, Bleeker-Rovers CP, Ben Amara A, van der Meer JW, Netea MG, et al. 23 Intact interferon-γ response against Coxiella burnetii by peripheral blood mononuclear cells in 24 chronic Q fever. Clin Microbiol Infect. 2017;23(3):209.e9-.e15. 25 10. Ghigo E, Pretat L, Desnues B, Capo C, Raoult D, Mege JL. Intracellular life of Coxiella burnetii 26 in macrophages. Annals of the New York Academy of Sciences. 2009;1166:55-66. 27 11. Lepidi H, Fournier P-E, Karcher H, Schneider T, Raoult D. Immunohistochemical detection of 28 Coxiella burnetii in an aortic graft. Clinical Microbiology and Infection. 2009;15(s2):171-2. 29 12. Lepidi H, Houpikian P, Liang Z, Raoult D. Cardiac valves in patients with Q fever endocarditis: 30 microbiological, molecular, and histologic studies. J Infect Dis. 2003;187(7):1097-106. 31 13. Layez C, Brunet C, Lépolard C, Ghigo E, Capo C, Raoult D, et al. Foxp3(+)CD4(+)CD25(+) 32 regulatory T cells are increased in patients with Coxiella burnetii endocarditis. FEMS Immunol Med 33 Microbiol. 2012;64(1):137-9. 34 14. Benoit M, Barbarat B, Bernard A, Olive D, Mege JL. Coxiella burnetii, the agent of Q fever, 35 stimulates an atypical M2 activation program in human macrophages. Eur J Immunol. 36 2008;38(4):1065-70. 37 15. Jana S, Hu M, Shen M, Kassiri Z. Extracellular matrix, regional heterogeneity of the aorta, and 38 aortic aneurysm. Experimental & Molecular Medicine. 2019;51(12):1-15. 39 16. Coady MA, Rizzo JA, Goldstein LJ, Elefteriades JA. Natural history, pathogenesis, and etiology 40 of thoracic aortic aneurysms and dissections. Cardiol Clin. 1999;17(4):615-35; vii. 41 17. Faugaret D, Ben Amara A, Alingrin J, Daumas A, Delaby A, Lépolard C, et al. Granulomatous 42 response to Coxiella burnetii, the agent of Q fever: the lessons from gene expression analysis. |
Front 43 Cell Infect Microbiol. 2014;4:172-. 44 18. Pellegrin M, Delsol G, Auvergnat JC, Familiades J, Faure H, Guiu M, et al. Granulomatous 45 hepatitis in Q fever. Hum Pathol. 1980;11(1):51-7. 46 19. Raoult D, Marrie T, Mege J. Natural history and pathophysiology of Q fever. Lancet Infect Dis. 47 2005;5(4):219-26. 48
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 22 20. Hagenaars JC, Koning OH, van den Haak RF, Verhoeven BA, Renders NH, Hermans MH, et al. 1 Histological characteristics of the abdominal aortic wall in patients with vascular chronic Q fever. 2 International journal of experimental pathology. 2014;95(4):282-9. 3 21. Broos PP, Hagenaars JC, Kampschreur LM, Wever PC, Bleeker-Rovers CP, Koning OH, et al. 4 Vascular complications and surgical interventions after world's largest Q fever outbreak. Journal of 5 vascular surgery. 2015;62(5):1273-80. 6 22. Eldin C, Mélenotte C, Mediannikov O, Ghigo E, Million M, Edouard S, et al. From Q Fever to 7 <span class="named-content genus-species" id="named-content-1">Coxiella burnetii</span> 8 Infection: a Paradigm Change. Clinical Microbiology Reviews. 2017;30(1):115-90. 9 23. Meghari S, Bechah Y, Capo C, Lepidi H, Raoult D, Murray PJ, et al. Persistent Coxiella burnetii 10 infection in mice overexpressing IL-10: an efficient model for chronic Q fever pathogenesis. PLoS 11 Pathog. 2008;4(2):e23. 12 24. Hercus TR, Broughton SE, Ekert PG, Ramshaw HS, Perugini M, Grimbaldeston M, et al. The 13 GM-CSF receptor family: mechanism of activation and implications for disease. Growth factors (Chur, 14 Switzerland). 2012;30(2):63-75. 15 25. Son B-K, Sawaki D, Tomida S, Fujita D, Aizawa K, Aoki H, et al. Granulocyte macrophage 16 colony-stimulating factor is required for aortic dissection/intramural haematoma. Nature 17 communications. 2015;6:6994. 18 26. Joosten SA, Ottenhoff TH. Human CD4 and CD8 regulatory T cells in infectious diseases and 19 vaccination. Hum Immunol. 2008;69(11):760-70. 20 27. Capo C, Zaffran Y, Zugun F, Houpikian P, Raoult D, Mege JL. Production of interleukin-10 and 21 transforming growth factor beta by peripheral blood mononuclear cells in Q fever endocarditis. 22 Infect Immun. 1996;64(10):4143-7. 23 28. Honstettre A, Imbert G, Ghigo E, Gouriet F, Capo C, Raoult D, et al. Dysregulation of cytokines 24 in acute Q fever: role of interleukin-10 and tumor necrosis factor in chronic evolution of Q fever. J 25 Infect Dis. 2003;187(6):956-62. 26 29. Ghigo E, Capo C, Raoult D, Mege JL. Interleukin-10 stimulates Coxiella burnetii replication in 27 human monocytes through tumor necrosis factor down-modulation: role in microbicidal defect of Q 28 fever. Infection and immunity. 2001;69(4):2345-52. 29 30. Ghigo E, Honstettre A, Capo C, Gorvel JP, Raoult D, Mege JL. |
Link between impaired 30 maturation of phagosomes and defective Coxiella burnetii killing in patients with chronic Q fever. J 31 Infect Dis. 2004;190(10):1767-72. 32 31. Wynn TA. Cellular and molecular mechanisms of fibrosis. The Journal of pathology. 33 2008;214(2):199-210. 34 32. Wynn TA. Common and unique mechanisms regulate fibrosis in various fibroproliferative 35 diseases. The Journal of clinical investigation. 2007;117(3):524-9. 36 33. Agerholm JS, Jensen TK, Agger JF, Engelsma MY, Roest HI. Presence of Coxiella burnetii DNA 37 in inflamed bovine cardiac valves. BMC Vet Res. 2017;13(1):69. 38 34. Brouqui P, Dumler JS, Raoult D. Immunohistologic demonstration of Coxiella burnetii in the 39 valves of patients with Q fever endocarditis. Am J Med. 1994;97(5):451-8. 40 35. De Biase D, Costagliola A, Del Piero F, Di Palo R, Coronati D, Galiero G, et al. Coxiella burnetii 41 in Infertile Dairy Cattle With Chronic Endometritis. Vet Pathol. 2018;55(4):539-42. 42 36. Dougan M, Dranoff G, Dougan SK. GM-CSF, IL-3, and IL-5 Family of Cytokines: Regulators of 43 Inflammation. Immunity. 2019;50(4):796-811. 44 37. Damiani G, McCormick TS, Leal LO, Ghannoum MA. Recombinant human granulocyte 45 macrophage-colony stimulating factor expressed in yeast (sargramostim): A potential ally to combat 46 serious infections. Clin Immunol. 2020;210:108292. 47 38. Kampschreur LM, Wegdam-Blans MCA, Wever PC, Renders NHM, Delsing CE, Sprong T, et al. 48 Chronic Q fever diagnosis— consensus guideline versus expert opinion. Emerging infectious diseases. 49 2015;21(7):1183-8. 50 39. Johnston KW, Rutherford RB, Tilson MD, Shah DM, Hollier L, Stanley JC. Suggested standards 51 for reporting on arterial aneurysms. Subcommittee on Reporting Standards for Arterial Aneurysms, 52
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 13 14 15
23 Ad Hoc Committee on Reporting Standards, Society for Vascular Surgery and North American 1 Chapter, International Society for Cardiovascular Surgery. Journal of vascular surgery. 2 1991;13(3):452-8. 3 40. Gorris MAJ, Halilovic A, Rabold K, van Duffelen A, Wickramasinghe IN, Verweij D, et al. Eight-4 Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint 5 Molecules within the Tumor Microenvironment. J Immunol. 2018;200(1):347-54. 6 41. Booth NJ, McQuaid AJ, Sobande T, Kissane S, Agius E, Jackson SE, et al. Different Proliferative 7 Potential and Migratory Characteristics of Human CD4<sup>+</sup> Regulatory T Cells That Express 8 either CD45RA or CD45RO. The Journal of Immunology. 2010;184(8):4317-26. 9 42. Wickham H, Averick M, Bryan J, Chang W, McGowan L, François R, et al. Welcome to the 10 Tidyverse. Journal of Open Source Software. |
2019;4:1686. 11 43. Alboukadel Kassambara FM. Visualize the Results of Multivariate Data Analyses 2020 12 [Available from: https://CRAN.R-project.org/package=factoextra. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 24 Figures with corresponding legends 1 2
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 25 1 Figure 1: Immune cell activation in atherosclerotic, Q fever infected and acutely infected AAAs. All scale bars represent 50 2 µm. A-P: Adaptive (A, B, E, F, I, J, M, N) and innate (C, D, G, H, K, L, O, P) immune cells in a representative normal abdominal 3 aorta, atherosclerotic AAA, Q fever AAA and acutely infected AAA. Arrows with corresponding colors indicate presence of 4 immune cells with red for CD3+ T cells, cyan for CD1c+ cDC2, green for CD20+ B cells in the adaptive panel (A, B, E, F, I, J, M, 5 N); and red for CD68+ macrophages and cyan for CD15+ neutrophils in the innate panel (C, D, G, H, K, L, O, P). Q: 6 quantification of percentages of different types of immune cells in the whole tissue sections, showing the increases in T and 7 B cells in atherosclerotic AAA and Q fever AAA compared to normal and increase in neutrophils in acute infection and 8 atherosclerotic AAA compared to normal. Note that there are no differences between atherosclerotic AAA and Q fever AAA. 9 * Represents P ≤ 0.05. 10
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 26 1 Figure 2: A: Principal component analysis (PCA) including CD3, CD20, CD68, CD15, and CD1c. There is a clear distinct 2 population consisting of normal abdominal aortas. There are two data points for acute infection, resulting in a line. 3 Intriguingly, atherosclerotic AAA and Q fever infected AAA are completely overlapping. This indicates that these populations 4 are similar when testing for these cell markers. B: PCA including all markers (CD68, CD15, MMP9, GMCSF, CD31, CD206, 5 CD3, CD1c, CD8, FoxP3, CD45RO, and CD20). Note the difference with figure 2A: here all groups form separate populations, 6 indicating that the newly added markers including subset markers describe the differences between atherosclerotic and Q 7 fever AAA. |
See Supplementary Table 1 for loadings of both PCAs. 8 9
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 27 1 Figure 3: Phenotype shift in macrophages in Q fever towards M2. A: Overview photo of atherosclerotic AAA, upper portion 2 is intima layer, lower portion adventitia. B: Composite of CD68 and CD206 with majority CD68. C, D: Separated channels for 3 CD68 and CD206 respectively. E: Overview of Q fever infected AAA, with the same orientation as A. F: Composite of CD68 4 and CD206, with mostly CD206+ cells which also express CD68, as supported by separated channels in G and H. I, J: 5 Quantification of percentages of macrophages in entire tissue sections (I) and of proportions of M1 and M2 macrophages in 6 these macrophages (J), showing the phenotype switch in Q fever AAAs towards M2. * Represents P ≤ 0.05. 7
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 28 1 Figure 4: Q fever infected AAAs express lower levels of GM-CSF. A-D: Representative composite image of atherosclerotic 2 AAA (A) and Q fever AAA (C) and corresponding GM-CSF channels (B, D). E: The expressed levels of GM-CSF corrected for 3 the number of macrophages and M2 macrophages are lower in Q fever infected AAAs, suggesting an immune suppressed 4 environment. 5 6
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 29 1 Figure 5: Q fever AAAs exhibit both pro-inflammatory and anti-inflammatory T cell subsets. Arrows with corresponding 2 colors indicate presence of immune cells, with orange for memory T cells, yellow for T helper cells, and cyane for cytotoxic T 3 cells. A-F: Overview of atherosclerotic AAA (A) and Q fever AAA with zoomed photos of tissue (B, E) and tertiary lymphoid 4 structures (TLS)(C, F). In both A and B the upper side of the photo is the intima layer. Note all the FoxP3+ (yellow) cells in Q 5 fever infected tissue. G: Percentage of T cells of all cells and T cells subsets out of T cells; G, H, I: Quantification shows a shift 6 in cytotoxic / helper T cell ratio and decrease in memory T cells in Q fever AAAs. Q fever AAAs show increased numbers of 7 cytotoxic and regulatory T cells, indicating both immune activation and suppression. |
8
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 30 1 Figure 6: HE and Elastin von Gieson (EVG) stainings demonstrate the disrupted architecture of Q fever infected AAAs. 2 Representative images of HE staining of AAA with 22x zoomed in sections (A, B, C) and EVG staining of adjacent slide (D, E, 3 F) demonstrate the atherosclerotic plaque, immune cells and infiltrates with relatively preserved vessel architecture as 4 shown by presence of elastin fibers (black arrows pointing at black lines). HE (G, H, I) and EVG (J, K, L) of adjacent Q fever 5 AAAs slides reveal pronounced atherosclerosis and immune cell infiltration, and loss of elastin fibers in the media layer (K). 6 In the adventitia (I, L) tissue is replaced by large amounts of fibrosis, indicated with asterisks. 7 8
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. 31 Tables 1
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
made available under a
CC-BY 4.0 International license
. Previous aorta surgery 0 (0.0%) 0 6 (50.0%) 0 0 (0.0%) 0 (0.0%) 1 0.034*
Length 1.80 (1.69-1.83) 0 1.77 (1.69-1.80) 0 1.78 (1.70-) 8 1.76-1.76-1.76) 1 0.923
Weight 80.0 (77.5-102.5) 0 82.6 (75.5-92.6) 0 88.5 (79-) 8 94.8 (94.8-94.8) 1 0.637
Artery disease 1 (20%) 4 11 (91.7%) 0 4 (40.0%) 2 1 (50.0%) 1 0.002*
Rupture 0 (0.0%) 0 0 (0.0%) 0 3 (30.0%) 0 0 (0.0%) 0 0.193
CRP 5 12 12.5 (12.0-65) 4 2 n/a
Table 1: Baseline characteristics. * Represents P ≤ 0.05. Numbers display numbers of patients with percentage, or median with interquartile range (IQR). 1 2
Beta blocker 1 (20%) 3 8 (66.7%) 0 3 (30.0%) 2 0 (0.0%) 1 0.567
Male 3 (60%) 2 10 (83.3%) 0 9 (90.0%) 1 1 (50.0%) 1 0.482
Packyears 27 (27-27) 4 33 (20-50) 2 45 (0-53) 1 0 (0-0) 1 0.819
Smoking 3 (60%) 5 11 (91.7%) 1 6 (60.0%) 1 1 (50.0%) 1 0.387
HDL 5 0.9 (0.8-1.1) 6 0.9 (0.9-1.3) 5 2 0.583
ARB / ACEi 2 (40%) 2 6 (50.0%) 0 3 (30.0%) 2 0 (0.0%) 1 0.789
Calciumblocker 0 (0%) 3 3 (25.0%) 0 0 (0.0%) 2 0 (0.0%) 1 0.439
Total cholesterol 5 3.6 (3.0-5.2) 5 4.7 (3.2-6.1) 5 2 0.371
DM 1 (20%) 0 3 (25.0%) 0 1 (10.0%) 2 0 (0.0%) 1 0.853
Diameter CT 5 57 (55-71) 0 60 (45-81) 1 46 (46-46) 1 0.397
Diuretics 0 (0%) 4 1 (8.3%) 0 2 (20.0%) 0 1 (50.0%) 1 0.009*
Age 65 (54-68) 0 72 (66-78) 0 71 (64-77) 0 71 (71-71) 1 0.318
Hypercholesterolemia 5 9 (75.0%) 0 6 (60.0%) 2 0 (0.0%) 1 0.426
32 Characteristic Normal (N=5) Missing data normal Atherosclerotic AAA (N=12) Missing data atherosclerotic Q fever AAA (N=10) Missing data Q fever Infectious AAA (N=2) Missing data infectious Significance
Hypertension 3 (60%) 0 8 (66.7%) 0 6 (60.0%) 2 1 (50.0%) 1 1.000
BMI 27.0 (22.1-34.7) 0 26.8 (24.0-29.4) 0 27.8 (27.3-) 8 30.6 (30.6-30.6) 1 0.651
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021. |
The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
made available under a
CC-BY 4.0 International license
. Cell phenotype T cell CD3+ Macrophage CD68+
Autofluoresence Elastin fibers Autofluoresence Elastin fibers
CD45RO (UCHL-1) GM-CSF (polyclonal)
1 Table 2: Overview of the used markers and clones per panel, including definition of each cell type as used for our analysis. 2
B cell CD20+ MMP9+ cell MMP9+ CD15-
33 Adaptive immune system Innate immune system
CD1c (2F4) CD31 (JC70A)
Memory T cell CD3+ CD45RO+ Endothelium CD31+
Helper T cell CD3+ CD8- M1-like macrophage CD68+ CD206-
CD8 (CD8/144B) CD206 (CL038+)
FoxP3 (236A/E7) MMP9 (polyclonal)
DAPI Nucleus DAPI Nucleus
CD20 (L26) CD15 (MMA)
Classic DC type 2 CD1c+ CD20- MMP9+ neutrophil MMP9+ CD15+
Cytotoxic T cell CD3+ CD8+ M2-like macrophage CD68+ CD206+
Autofluorescence Autofluorescence
CD3 (SP7) CD68 (PG-M1)
Markers (clone) DAPI DAPI
Regulatory T cell CD3+ CD8- FoxP3+ Neutrophil CD15+
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. |
bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. bioRxiv preprint
The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.08.27.457923
;
this version posted August 28, 2021.
made available under a
CC-BY 4.0 International license
. |
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Clinically-relevant T cell expansion protocols activate distinct cellular metabolic programs and phenotypes
AUTHORS
Sarah MacPherson1, Sarah Keyes1, Marisa Kilgour1,2, Julian Smazynski1,2, Jessica Sudderth3, Tim Turcotte4, Adria Devlieger4, Jessie Yu5, Kimberly S. Huggler6,7, Jason R. Cantor6-9, Ralph J. DeBerardinis3,10, Christopher Siatskas5, and Julian J. Lum1,2*
Corresponding author: Julian J. Lum [email protected] RM 3307 - 2410 Lee Avenue, Victoria, BC, V8R6V5
Affiliations
1. Trev and Joyce Deeley Research Centre, BC Cancer, Victoria, BC, Canada 2. Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada 3. Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
4. BC Cancer, Victoria, BC, Canada 5. Stemcell Technologies Canada Inc., Vancouver, BC, Canada 6. Morgridge Institute for Research, Madison, WI, USA 7. Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA 8. Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA 9. University of Wisconsin Carbone Cancer Center, Madison, WI, USA 10. Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
Contact
Sarah Keyes: [email protected] ● Marisa Kilgour: [email protected] ● Sarah Macpherson: [email protected] ● Julian Smazynski: [email protected] ● Jessica Sudderth: [email protected] ● Tim Turcotte: [email protected] ● Adria Devlieger: [email protected] ● Jessie Yu: [email protected] ● Kimberly S. Huggler: [email protected] ● Jason R. Cantor: [email protected] ● Ralph J. DeBerardinis: [email protected] ● Christopher Siatskas: [email protected] ● Julian J. Lum: [email protected]
KEYWORDS T cell expansion, cell-based immunotherapy, culture media, phenotype, metabolism, 13C tracer analysis
1
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . LIST OF ABBREVIATIONS
CAR Chimeric antigen receptor CD CMM Corning Lymphocyte Serum-Free Medium KBM 581 (Corning) GC-MS Gas chromatography-mass spectrometry ICM IFN IL HPLM Human Plasma-like Medium (Dr. Jason Cantor, Gibco) MFI Median fluorescence intensity PBMC Peripheral blood mononuclear cell PD-1 Programmed cell death protein 1 PMA Phorbol 12-myristate 13-acetate REP Rapid expansion protocol ROS Reactive oxygen species SEM Standard error of the mean TAC TCA Tricarboxylic acid TCR T cell receptor TCM Central memory T cell Effector T cell TE Effector memory T cell TEM Tumor infiltrating lymphocyte TIL TN Naive T cell TNF Tumor necrosis factor Treg
Cluster of differentiation
ImmunoCultTM-XF T Cell Expansion Medium (STEMCELL Technologies) Interferon Interleukin
TexMACS™ medium (Miltenyi)
Regulatory T cell
2
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. |
The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Abstract
Ex vivo expansion conditions used to generate T cells for immunotherapy are thought to adopt metabolic
phenotypes that impede therapeutic efficacy in vivo. The comparison of five different culture media used
for clinical T cell expansion revealed unique optima based on different output variables including
proliferation, differentiation, function, activation and mitochondrial phenotypes. T cells adapted their
metabolism to match their media expansion condition as shown by glucose and glutamine uptake, and
patterns of glucose isotope labeling. However, adoption of these metabolic phenotypes was uncoupled to
T cell function. Furthermore, T cell products cultured in ascites from ovarian cancer patients displayed
suppressed mitochondrial activity and function irrespective of the ex vivo expansion media. In one case,
culturing in ascites resulted in increased glucose uptake which was insufficient to rescue T cell function. Thus, ex vivo T cell expansion conditions have profound impacts on metabolism and function. 3
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . INTRODUCTION
Cell-based immunotherapies are garnering considerable attention for their promise in treating
human cancers. These therapies involve isolating and expanding autologous human tumor-infiltrating
lymphocytes (TIL) or genetically modified chimeric antigen receptor (CAR) T cells. In particular, CAR T
cell therapy has achieved exceptional response rates in hematological cancers1,2. However several
barriers exist that impede the efficacy of cell based therapies targeting solid tumors3–5. These include but
are not limited to tumor antigen escape, restricted intraepithelial trafficking, limited persistence and an
inhospitable tumor microenvironment (TME)6–8. Another critical factor is the complex cell manufacturing
process that can generate products with undesirable metabolic phenotypes and ultimately hamper in vivo
functionality9–11. Culture methods that maintain metabolic profiles favoring central memory phenotypic
subsets have been shown to highly correlate with improved clinical outcomes12. A recent study identified
medium-dependent transcriptional responses in several metabolic pathways during early activation, which
may be crucial in programming T cells to a committed phenotype13–17. At the present time, there has yet
to be a universally accepted formulation to manufacture T cells making it a major challenge not only to
cross-compare different clinical trials, but also to understand the metabolic parameters that may be
responsible for the behavior of T cells post-transfer. |
The first synthetic complex medium used for in vitro expansion of lymphocytes was RPMI 164018,
and is widely used in the Rapid Expansion Protocol (REP) of TILs19. Improvements in formulations that
incorporate defined serum components have led to media formulations such as X-VIVO 15 and AIM-V. However, recent evidence has indicated that cells maintained under these non-physiological conditions
activate different signaling and metabolic pathways compared to analogous cells generated in vivo20. This
has led to the generation of culture media that recapitulate many physiological characteristics of human
plasma such as Human Plasma-like Medium (HPLM)21 and others22. However, these formulations may
not recapitulate all the nutritional environmental cues required to induce and sustain robust expansion
specific to T cells necessitating their supplementation with human AB serum. In contrast, ImmunoCultTM-
XF T Cell Expansion Medium (ICM) is a serum-free, xeno-free medium that supports robust T cell
expansion. 4
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Here we investigated the influence of five cell culture media conditions on T cell metabolism,
proliferation, differentiation, activation and function. Although each condition supported cell proliferation,
the extent of expansion varied as did differentiation, function, mitochondrial phenotypes and metabolism. The condition with the greatest proliferation and function (REP in CTL:AIM-V medium) displayed a
preference for glucose uptake over glutamine. This dominance for glucose uptake could be imposed as T
cells adopted the preference for glucose when switched in CTL:AIM-V irrespective of the condition used
for the initial expansion. However the change in metabolism did not appear to be linked to increased
function as the switch to CTL:AIM-V differentially impacted TNFa and IFNg production. Carbon tracing
revealed REP expanded T cells having increased labeled lactate whereas ICM expanded T cells
displayed increased labeling of one-carbon metabolism and entry into the TCA cycle. These patterns of
labeling were media dependent as switching ICM expanded T cells into CTL:AIM-V medium reverted T
cells back to higher lactate labeling as seen in the REP expanded T cells, which was associated with an
increase in CD25+ and PD-1+ populations. All five T cell products were exposed to the ascites derived
from ovarian cancer patients and experienced suppressed T cell function and mitochondrial activity that
could not be overcome by increased glucose uptake alone. Thus, our studies highlight the impact of cell
culture media on the metabolic programs, phenotypes and function of human T cells for potential use in
immunotherapy. |
RESULTS
Expansion conditions skew proliferation, differentiation and activation
To examine the influence of cell culture media on T cell products, we conducted a 12-day comparison of
5 expansion protocols (Table 1). We compared one of the earliest tumor infiltrating lymphocyte (TIL)
expansion methods commonly referred to as the rapid expansion protocol (REP)19 to platforms by:
STEMCELL (ICM), Miltenyi (TAC) and Corning (CMM). We also tested Human Plasma-like Medium
(HPLM), which was recently developed specifically to recapitulate the human plasma environment in
vitro13. Enriched CD3+ T cells were isolated from apheresis products of six different healthy donors and
expanded over the course of 12 days following the manufacturers’ recommended protocols using their
respective cell culture media (Table 1). Unlike the report by Leney-Greene et al.13, we were primarily
5
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . interested in the longitudinal changes after expansion and the T cell phenotypes produced after 12-14
days, a time course that is similar to most clinically-approved schemas used in manufacturing T cells for
cancer immunotherapy. Given the clinical importance of maximizing the number of T cells in the expansion product, the
proliferative capacity of all five of these culture medias were compared. Expansion differed significantly
across all of the conditions ranging from 40-860 fold (Fig. 1a). This difference in expansion appeared as
early as day 4 and was maintained throughout the entire expansion with the REP condition yielding the
largest number of T cells. While the CMM and HPLM expansion conditions used the same stimulation
method and only differed in media composition, CMM expanded cells produced a 2-fold greater
expansion compared to the same T cells expanded in HPLM. It has been reported that an equivalent ratio
of CD4+ and CD8+ T cells in the final infusion product is associated with better clinical responses to TIL
or CAR T cell therapy28,29. Although each condition resulted in a variable percentage of CD4+ and CD8+
T cells, the CD4:CD8 T cell ratio within each condition was consistent (Fig. 1b). For example, the REP
promoted a strong enrichment of CD4+ T cells and a concomitant reduction in CD8+ T cells that was
significantly different than the other conditions (Fig. 1b and Supplementary Fig. 1a). Of note, the TAC
and ICM expansion media did not appear to significantly alter the percentage of CD4+ and CD8+ T cells
from day 0, whereas CMM and HPLM media generated more CD8+ T cells over the same 12-day period
(Fig. 1b). The differentiation state of the post-expanded population correlates with long-term persistence of both TIL
and CAR T cells, and to a large extent tumor control30,31. |
For instance, the skewing towards CD8+ T
effector (TEFF) cells limits anti-tumor responses after adoptive cell therapy32. On the other hand, adoptive
transfer of CD8+ T central memory (TCM) cells has been shown to have a superior anti-tumor response
than CD8+ T effector memory (TEM) cells33. Across all of the conditions tested, expanded CD4+ and
CD8+ T cells displayed a predominant TEFF and/or TEM phenotype with the REP condition producing the
highest percentage of TEM cells (Fig. 1c,d,e). Overall, the five media conditions generated few (<10%)
CD4+ or CD8+ T cells displaying a TCM differentiated phenotype. 6
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Clonal variation, marked by a diverse TCR Vβ repertoire, enables T cells to recognize a wide array of
epitopes including those from tumors. Selective expansion of tumor reactive clones has been reported to
correlate with clinical responses34. It is unclear whether certain media conditions favor the outgrowth of
specific clonotypes. Therefore, we profiled TCR Vβ repertoires using flow cytometry to assess population
clonality for each condition. Overall the Vβ spectratyping revealed that TCR diversity is largely maintained
across all conditions (Supplementary Fig. 1b,c). To determine whether culture conditions influenced T cell activation, we measured the expression of
CD25 and CD137 by flow cytometry. Expression of CD137 was generally higher on CD8+ T cells than
CD4+ T cells across all conditions (Supplementary Fig. 1d). Although the REP produced the lowest
frequency of CD8+ T cells, it achieved the highest CD8+ CD137+ cells population compared to all other
conditions (Supplementary Fig. 1d). In contrast, CD25 expression was similar between CD4+ and CD8+
T cells, with the HPLM condition producing highest proportion of CD25+ cells compared to other
conditions (Fig. 1f). Since CD25 is also a marker of CD4+ regulatory T (Treg) cells35, we also measured
the proportion of CD4+ CD25+ FoxP3+ Treg cells in each condition. Treg cells comprised <5% of the
expanded T cells in all conditions (Supplementary Fig. 1e), indicating that the conditions used in this
study do not support the proliferation of FoxP3+ Treg. We also evaluated the expression of PD-1 as an
indicator of potential T cell exhaustion since its expression on expanded CAR T cells is correlated with
poorer patient outcomes36. PD-1 expression was generally low on cells from all conditions except for
CD4+ REP cells where 50% of the CD4+ T cell population expressed PD-1 (Fig. 1g). Moreover, upon
reactivation, REP expanded T cells displayed higher TNFa and IFNg production (Fig. 1h). Collectively,
these results establish that T cell products vary in proliferative capacity, differentiation (TEFF and TEM),
function (TNFa and IFNg) and expression of exhaustion makers (PD-1). |
7
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Mitochondria mass, activity and ROS vary across all conditions
Mitochondrial activity and biomass have been recognized in both pre-clinical and clinical models to be
indicators of improved CAR T cell therapeutic efficacy. Specifically, low mitochondrial activity and
increased mitochondrial biogenesis supports T cell persistence and anti-tumor function in chronic
lymphocyte leukemia patients37. Therefore, we assessed the impact of expansion conditions on
mitochondrial activity and mitochondrial mass as determined by flow cytometry analysis of cells stained
with MitoTracker Deep Red and MitoTracker Green, respectively. Overall, there was no consistent pattern
that emerged across conditions although statistical differences were observed depending on the pair-wise
comparisons (Fig. 2a,b and Supplementary Fig. 2a). We found that the REP expanded T cells produced
the highest cell number also had the highest mitochondrial activity (Fig. 2a). Notably, high mitochondrial
activity is associated with a terminal differentiation state and poor tumor killing capacity38. In contrast, T
cells maintained in ICM had the second largest expansion with lower mitochondrial activity compared to
the REP, but had significantly higher mitochondrial mass compared to all other conditions (Fig. 2b). The
substantial increase in mitochondrial biogenesis observed in the ICM condition was not due to a
difference in cell size (Supplementary Fig. 2b). Cells with elevated levels of mitochondrial activity often results in elevated mitochondrial reactive oxygen
species (ROS) production that can limit the cells functional capability in conditions of oxidative stress
such as the TME. Therefore, we investigated how the mitochondrial activity is associated with
mitochondrial ROS for each expansion product. We found that mitochondrial activity and mitochondrial
ROS were positively correlated in all conditions, although at varying degrees (Supplementary Fig. 2c). In
accordance with the elevated mitochondrial activity, REP expanded T cells had the highest ROS
production, where approximately 70% of mitochondria were positive for ROS (Fig. 2c). In contrast to the
REP, the ICM condition displayed higher mitochondrial mass and low levels of ROS (Fig. 2c). While the
conditions with the lowest proliferation and mitochondrial activity, TAC and HPLM appeared to produce
the lowest mitochondrial specific ROS. 8
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . Expansion conditions dictate nutrient uptake but is uncoupled from T cell function
Media conditions are often proprietary, so the precise composition of basic nutrient levels are not
available. Therefore, the concentration of two key nutrients, glucose and glutamine, was assessed as
both are well studied in terms of their regulation of T cells39–41. The concentrations of glucose and
glutamine varied significantly across conditions, 5.92-27.25 mM and 0.76-6.68 mM, respectively (Table
1). Thus, we investigated how the variation in nutrient levels influenced uptake between days 11-12. All
five conditions supported varying levels of both glucose and glutamine uptake (Fig. 3a,b and
Supplementary Fig. 3a,b). Overall, conditions with elevated glucose concentrations tended to have
increased uptake (Supplementary Fig. 3a), while glutamine concentrations did not appear to be
associated with the level of uptake (Supplementary Fig. 3b). Furthermore, glucose uptake appeared to
be independent of proliferation as both the highest (REP, ICM CMM) and lowest (HPLM) proliferative
conditions had significant changes in glucose concentration compared to their respective fresh media
condition (Fig. 3a). The elevated nutrient uptake observed in HPLM expanded cells may be due to the
differing proliferative state at day 11, as they were most proliferative at day 11 (Supplementary Fig. 3c). Furthermore, despite containing supraphysiological level of glucose and glutamine, the REP expanded T
cells resulted in no significant change in glutamine concentration in the media over 24 hours of culture,
indicative of low glutamine uptake and a preference for glucose as a carbon source. In contrast, the CMM
expansion condition produced significant differences in both glucose and glutamine concentrations in the
media after 24 hours (Fig. 3a,b). To gain insight into whether the dependence on glucose in the REP was
mediated by the cell culture media formulation, we expanded T cells using the respective 4 conditions
and on day 11 replaced the media with the REP media (CTL:AIM-V) for 24 hours. This switch resulted in
a significant change in glucose concentration in CTL:AIM-V with a concomitant no change in glutamine
across almost all expansion products (Fig. 3c,d). Thus, this media replacement phenocopied the glucose
metabolism of the REP expanded condition in the CTL:AIM-V. Although there was a modest reduction in
glutamine consumption by CMM expanded T cells that had been switched to CTL:AIM-V, the shift to
reduced glutamine uptake was the most dramatic of all conditions. These findings imply that T cells
exhibit metabolic flexibility and adapt to their surrounding nutrient environments, regardless of their
original metabolic state at the time of activation and/or expansion. 9
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . To uncover if the shift in metabolism in CTL:AIM-V was also linked to increased function as observed in
the REP expanded T cells, we reactivated all products in their respective conditions or in CTL:AIM-V for
2 days. Unlike glucose and glutamine uptake, T cell function was not universally influenced by the change
to CTL:AIM-V media across conditions (Fig. 3e,f). Although all T cell products were reactivated in
CTL:AIM-V, differences in IFNg and TNFa production was observed. While TAC significantly increased in
both IFNg and TNFa production in CTL:AIM-V, CMM cells displayed no change in either cytokine (Fig. 3e,f). This demonstrates that while metabolism adapts to the change in extracellular conditions, the
inherited impacts of the initial expansion conditions on T cell function cannot be universally overcome by
switching conditions. Glucose utilization and phenotype is influenced by media
To gain further insight into the influence of media on T cell metabolism, we investigated the difference in
glucose utilization pathways between the REP and ICM condition. These conditions produced the largest
cell expansions with similar glucose uptake levels regardless of glucose concentrations in the media
(Table 1 and Supplementary Fig. 4a). Therefore, stable isotope labeling was performed using [U-
13C]glucose to delineate how carbon utilization differed in REP and ICM conditions (Fig. 4a). Current in
vitro models suggest that the rate of glycolysis is matched to the rate of proliferation. Indeed, we found
that aerobic glycolysis was active in both conditions, producing high extracellular and intracellular lactate
M+3 fractions in both CD4+ and CD8+ T cells (Fig. 4b and Supplementary Fig. 4b). However, the REP
condition produced significantly more extracellular lactate compared to ICM (Supplementary Fig. 4c),
consistent with a more glycolytic and activated phenotype (Fig. 1f,g). Furthermore, the ICM condition
produced roughly 30% less extracellular glucose derived lactate M+3, indicating that other carbon
sources support lactate production (Fig. 4b). To assess if glucose utilization was dependent on the
culture medium, the day 11 ICM expanded T cell products were placed in CTL:AIM-V. After 24 hours in
CTL:AIM-V, the ICM expanded T cell products did not increase in lactate production (Supplementary
Fig. 4c), however their carbon utilization pathways shifted resulting in a significantly higher fraction of
lactate M+3 similar to the REP condition (Fig. 4b). A similar enrichment in the 13C labeling pattern was
observed for alanine M+3. There was a higher level of alanine M+3 enrichment in the REP and ICM
10
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . |
switched to CTL:AIM-V compared to ICM cells in their respective condition (Fig. 4c). Interestingly, ICM
contains approximately 7 times more alanine than CTL:AIM-V (Supplementary Fig. 4d), which was
associated with higher intracellular levels (Supplementary Fig. 4e). Therefore, the reduced fraction of
alanine M+3 in the ICM condition could be due to a combination of increased de novo production and/or
uptake. Due to the decrease in lactate and alanine labeling in ICM conditions, we interrogated other upstream
glucose-derived metabolites. Serine is a non-essential amino acid that contributes to nucleotide
biosynthesis. Recent evidence indicates that serine is necessary to support CD8+ T cell expansion and
effector function42,43. The [U-13C]glucose metabolite isotope analysis revealed a greater fractional
enrichment of labeled serine and glycine in ICM expanded T cells compared to REP expanded T cells. More specifically, CD8+ T cells from the ICM expansion had significant enrichment of serine M+1 and
M+3 and glycine M+2 compared to CD8+ T cells from the REP expansion (Fig. 4d,e and Supplementary
Fig. 4f). Although the relative serine labeling was reduced in ICM expanded T cells that were switched to
the CTL:AIM-V, there were detectable levels of serine M+3 enrichment. This suggests that relative to the
REP expansion conditions, ICM expansion conditions promote one-carbon metabolism pathways in CD8+
T cells and that changes in one-carbon metabolism may be less susceptible to fluctuations in the levels of
extracellular nutrients. At the peak of an effector response, T cells undergo a metabolic switch from glycolysis to OXPHOS
supporting mitochondrial biogenesis and T cell memory development. Therefore, we assessed the fate of
the [U-13C]glucose carbons into the mitochondria (Fig. 4a). Citrate M+2/Pyruvate M+3 and Citrate M+3/
Pyruvate M+3 ratios serve as surrogates for pyruvate dehydrogenase (PDH) and pyruvate carboxylase
(PC) activity respectively44,45. Between conditions, both CD4+ and CD8+ T cells from the ICM expansion
had higher PC and PDH activity than CD4+ and CD8+ T cells from the REP expansion (Fig. 4f,g). The
ICM-mediated contribution of glucose-derived carbons into the TCA cycle is consistent with the observed
increase in mitochondrial biogenesis (Fig. 2b). However, CD4+ T cells seem to be more influenced by the
switch to CTL:AIM-V condition than the CD8+ T cells which maintained the PDH and PC labeling patterns
11
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . regardless of condition. Furthermore, the ICM expanded T cells diverted roughly 50% of α-ketoglutarate
M+2 from citrate M+2 (Fig. 4h). This reduction in α-ketoglutarate M+2 was corroborated by the reduction
in glutamate M+2 and malate M+2 fractional enrichment in the ICM expansion condition (Supplementary
Fig. |
4g,h). The loss in α-ketoglutarate M+2 enrichment was likely due to entry of unlabeled carbons from
glutamine catabolism, both of which were reversed in CTL:AIM-V conditions (Fig. 4h,i). These results
imply that REP and ICM expansion conditions differentially control the source of carbons entering the
TCA cycle. ICM expanded T cells direct glucose-derived carbons preferentially into citrate via PC and
PDH, and likely use glutaminolysis as an alternative carbon source to support synthesis of TCA cycle
metabolites. The REP condition supports increased glycolysis, glucose dependence, elevated mitochondrial activity
and ROS generation, many of which are hallmarks of T cell exhaustion. Indeed the REP cells resulted in
greater than 50% of the expanded T cells expressing PD-1 (Fig. 1g). Therefore, we investigated if
conditioning ICM expanded T cells in CTL:AIM-V would also influence exhaustion. On day 12, REP and
ICM expanded T cells were reactivated in their respective conditions or in CTL:AIM-V for an additional 2
days. The REP expanded T cells showed a significantly higher proportion of cells that were PD-1 and
CD25 positive compared to ICM expanded T cells (Fig. 4j,k). However, the ICM expanded cells that were
reactivated in CTL:AIM-V conditions also significantly increased in activation and exhaustion markers
resembling the exhaustion state of the REP expanded T cells (Fig. 4j,k). This suggests that while ICM
expanded T cells do not increase glycolysis when switched to CTL:AIM-V, the nutrient conditions in the
CTL:AIM-V media resulted in changes to both glucose and glutamine metabolism that were sufficient to
impart alterations in activation and exhaustion phenotypes. The tumor microenvironment imposes different metabolic constraints on T cell products
Given the observed changes in T cell metabolism and phenotypes when expanded T cells are placed into
different media, it is possible that T cells manufactured under these parameters may also be affected by
the TME. There is a growing appreciation that ex vivo clinical manufacturing conditions used to expand T
cells for adoptive cell therapies may impact the effectiveness of the final T cell product when the infused T
12
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . cells encounter the nutrient depleted TME46,47. To test this possibility, patient-derived ovarian cancer
ascites fluid was used as a proxy for the TME. We expanded T cells in all five conditions and on day 12 of
the expansion, T cell products were cultured and reactivated in 100% ascites fluid for 2 days (Fig. 5a). Four of the five expanded T cell conditions maintained their viability in the presence of ascites (Fig. 5b). However, the REP expanded T cells showed a consistent and noticeable decrease in viability compared
to the remaining four conditions. |
The ascites environment has been reported to be immune suppressive owing to reduced levels of critical
nutrients such as glucose and glutamine48,49. Consistent with this, analysis of the ascites supernatant
revealed significantly lower levels of both glucose and glutamine compared to levels in all of the media
formulations except for HPLM (Table 1 and Supplementary Fig. 5a,b). The HPLM was developed to
more closely resemble the metabolic conditions in normal human plasma. Using the fluorescent glucose
analog 2-NBDG, we found that despite containing similar levels of glucose to that found in the ascites, the
HPLM expanded T cells had significantly higher 2-NBDG uptake in ascites (Fig. 5c). The other four
conditions showed no change in glucose uptake between their respective cultured conditions and ascites
fluid (Supplementary Fig. 5c). In contrast to the lack of changes in glucose uptake, mitochondrial
metabolism was lower in all of the expanded T cell products in ascites fluid (Supplementary Fig. 5d). However, similar to what was seen in the media conditions, the REP had the highest mitochondrial
activity in ascites fluid compared to the other conditions (Fig. 5d). Although the REP condition had high
levels of PD-1 expression in the ascites across all conditions (Fig. 5e), the expression of PD-1 was
reduced in the ascites (Supplementary Fig. 5e). Since PD-1 is also a marker of activation, reduced PD-1
expression could be a reflection of the suppressed activation state of T cells in ascites. Indeed, the T cell
activation marker CD25 was also reduced across conditions in the ascites further supporting the
contention that ascites is an immune suppressive environment (Supplementary Fig. 5f). Consistent with
the reduction in mitochondrial activity, expanded T cells cultured in ascites resulted in a decrease in IFNg
and TNFa production regardless of the expansion condition (Supplementary Fig. 5g,h). While the REP
expanded T cells produced the largest proportion of IFNg positive cells, there was no significant difference
in TNFa expression across conditions in ascites fluid (Fig. 5f). 13
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . DISCUSSION
Clinical grade T cells are manufactured under stringent and defined conditions yet to date there is no
universal media formulation or standardized protocols in the field. Moreover, the release criteria do not
take into account how different expansion conditions alter T cell metabolism or how these conditions may
impact T cell function post-infusion. Recent work has highlighted important differences in how T cells
metabolize glucose in vitro versus in vivo20. During CD8+ T cell responses to physiological infection, T
cells adopt an oxidative metabolic phenotype with greater flux of glucose-derived carbons into serine and
other biosynthetic pathways. |
This is consistent with another study showing that glucose pre-conditioning
can metabolically enhance adoptive T cell anti-tumor immunity potentially by shifting cells into a
temporary oxidative state47. These studies suggest that the nutrient conditions during the ex vivo
manufacturing could be tailored to enhance the fitness of T cells following infusion into patients. We evaluated how five commonly used ex vivo expansion culturing conditions alter the metabolic state
and phenotypes of CD4+ and CD8+ T cells. Across these conditions, there were pervasive differences in
metabolism that resulted in shifts in differentiation and function. We used the REP formulation as a
benchmark given its early use in the first adoptive T cell trials for the treatment of late-stage metastatic
melanoma. Although all conditions resulted in T cell proliferation, the extent of expansion was markedly
different and ranged from 40 to 860-fold. However, the baseline concentration of glucose present in each
media did not correlate with the degree of expansion. The CTL:AIM-V media used in the REP contained
11 mM glucose but yielded the highest fold expansion despite the ICM, TAC and CMM media containing
twice the concentration of glucose. Although REP and ICM T cells resulted in a similar level of expansion,
[U-13C]glucose isotope tracing studies revealed that T cells expanded in the ICM culture medium had
lower levels of extracellular lactate and lactate M+3 enrichment, suggesting that glycolysis was less
engaged in these cells. The reduction in lactate was associated with a greater proportion of CD8+ TEFF
cells and decreased the proportion of TEM. This observation was unexpected given that TEFF cells have
been shown to be highly glycolytic and the transition to TEM cells is associated with a switch to oxidative
metabolism. These results suggest that during ex vivo expansion, metabolites other than glucose that are
found in the ICM media play a role supporting TEFF cell differentiation and proliferation. Moreover, the
14
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . differences in proliferation as well as differentiation phenotypes could not be fully attributed to the
metabolism of T cells implying that these phenomena are disconnected under the ex vivo conditions
tested in our study. It is also possible that the specific TCR stimulation method activates unique signaling
programs that could contribute to the different metabolic responses. However this was not observed in
the CMM and HPLM conditions. Furthermore, this is independent from the TCR clonality as no major
biases were seen in the outgrowth of TCR diversity. Due to the implications of mitochondrial metabolism in the context of CAR and TIL therapy, we assessed
the mitochondrial phenotype produced from all 5 conditions. |
ICM expanded T cells had significantly
higher mitochondrial mass compared to all other conditions. This was surprising as the majority of ICM
cells had a TEFF phenotype and increases in mitochondrial biogenesis is commonly associated with T
memory subsets. The REP expanded T cells also showed high mitochondrial activity, which correlated
with increased production of mitochondrial specific ROS. Although ROS production is required for T cell
activation, elevated production of free radicals can induce mitochondrial stress and trigger cell apoptosis. This mitochondrial phenotype may explain the poor persistence in vivo, and poor survival and cytotoxic
efficacy under oxidative stress, an observation that has been previously reported for T cells expanded
using the REP formulation50. In contrast, the ICM medium produced cells with increased mitochondrial
mass and reduced activity and ROS production compared to the REP. Based on previous clinical
findings, a product with this mitochondrial profile may be most advantageous for cell based therapies37. However, in our TME model used here, no expansion condition supported sustained mitochondrial activity
in the presence of ascites fluid. To further understand how culture medium influences T cell metabolism, we traced [U-13C]glucose
utilization in T cells that were expanded using the REP and ICM condition, as well as ICM expanded T
cells and subsequently switched into CTL:AIM-V. These results revealed that the elevated glycolysis
labeling and reduced of TCA cycle intermediate labeling was media dependent. Of note, 13C enrichment
was reduced in metabolites downstream of citrate M+2 in ICM expanded T cells compared to REP T cells
and ICM T cells switched in CTL:AIM-V for 24 hours. This is likely due to the increased uptake of
15
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . glutamine in ICM conditions, while REP and T cells switched to CTL:AIM-V media preferentially utilize
glucose over glutamine as a carbon source. These patterns were also associated with a corresponding
increase in both intracellular and extracellular alanine M+3. Alanine has been shown to be essential for T
cell activation and can be produced from a transamination reaction with pyruvate and glutamate via
alanine aminotransferase. However, this increased proportion of fractional enrichment of alanine M+3 is
also a reflection of the lower proportions of unlabeled extracellular and intracellular alanine in T cells
expanded under CTL:AIM-V compared to T cells expanded under ICM media. When ICM expanded T
cells were switched into CTL:AIM-V, the total intracellular alanine levels decrease (Supplementary Fig. 4e) supporting the idea that REP expanded T cells may have reduced alanine uptake. |
This implies that
exogenous alanine in the ICM medium is sufficient to meet cellular demands, while T cells expanded with
the REP medium appear to require synthesis of alanine. However, further studies are needed to formally
demonstrate this possible scenario. Isotope tracing studies also revealed metabolic pathways that are less susceptible to reprogramming due
to fluctuations in extracellular nutrient conditions. For example, some metabolic phenotypes of the ICM
expanded T cells persisted even when the T cells were switched to CTL:AIM-V medium, including the
increased PDH and PC activity in CD8+ T cells and enrichment of 13C to one carbon metabolism
pathways. These data provide an example of how T cells adapt their metabolism based on extracellular
levels of nutrients and the plasticity of certain metabolic pathways. This also further supports the idea that
some metabolic pathways may have a more permanent inheritability throughout the expansion, while the
utilization of other metabolic pathways such as glycolysis may change rapidly depending on precise
conditions at the time. It will be important to consider which metabolic pathways and cell phenotypes will
be maintained after the expanded T cells are administered and subsequently traffic into the TME. Lastly, we tested how all five expansion conditions supported T cell metabolism and function when
transferred to patient-derived ovarian cancer ascites fluid, a known immunosuppressive TME. Due to the
elevated level of ROS and PD-1 expression in the REP expanded T cells, we speculated that this state
may contribute to activation-induced T cell death upon reactivation in ascites52. As expected, the REP
16
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . condition had significantly reduced T cell viability after reactivation compared to the other media
conditions. Interestingly, glucose uptake was not suppressed across all conditions and actually increased
in T cells expanded under the HPLM conditions. This result further highlights the notion that the ex vivo
metabolism of T cells is not necessarily coupled to their functional behavior when subjected to the TME. The increase in glucose uptake could be associated with higher CD28 expression as it has been shown
that CD28 supports Akt activation53. It is tempting to speculate that HPLM may be more suited for
expansion of second or third generation CAR T cells that encode for CD28 co-stimulatory domains versus
4-1BB co-stimulatory domains. HPLM contains similar glucose levels to that found in ascites suggesting
that initial expansion of T cells in low glucose conditions programmed T cells to subsist under
environments where glucose levels are limited47. On the other hand, mitochondrial activity was
significantly suppressed across all conditions, which is commonly observed in the TME and could
contribute to the observed suppression of T cell function. |
Similar to other reports, we observed that T cell
products with elevated mitochondrial activity showed a tendency to have higher PD-1 expression52. This
demonstrates that the impact of the media formulations extends beyond nutrient uptake and glucose
utilization in that they directly affect T cell activation. In conclusion, we uncovered distinct metabolic programs activated by ex vivo clinical expansion
protocols. The observed differences under various media formulations contributed to the skewed patterns
of T cell differentiation and effector function, outputs that could be uncoupled with their metabolic profiles. Most T cell-based immunotherapies focus on applications to improve cell expansion and to produce
phenotypes that enable in vivo persistence and maximal cytolytic function. Here we demonstrate that
media formulations may influence metabolic fidelity of the final immunotherapeutic product. Further
studies will be required to determine whether these metabolic states imparted by different ex vivo
expansion conditions ultimately impact the in vivo anti-tumor ability of T cells and their long-term
persistence. 17
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . METHODS
Cell culture reagents
Five media conditions were interrogated in this study. (1) Complete CTL:AIM-V media, used in rapid
expansion T cell protocol (REP), consisted of equal parts of supplemented RPMI 1640 and AIM-V media. To a 1X RPMI 1640 Medium basal, the following components were added: 2 mM L-Glutamine (Fisher),
10% heat-inactivated (56oC, 60 min) human AB serum (Sigma), 12.5 mM HEPES (Fisher), 1X Penicillin
Streptomycin solution (Fisher), and 50 μM β-Mercaptoethanol (Sigma). AIM-V Medium (Invitrogen) was
supplemented with 20 mM HEPES and 2 mM L-glutamine (CTL:AIM-V). (2) ImmunoCult™-XF T Cell
Expansion Medium (STEMCELL Technologies) was supplemented with 1X Penicillin Streptomycin
solution (ICM). (3) TexMACS™ medium (Miltenyi) was supplemented with 3% heat-inactivated human AB
serum (Sigma) and 1X Penicillin Streptomycin solution (TAC). (4) Corning media consisted of
Lymphocyte Serum-Free Medium KBM 581 (Corning) supplemented with 3% heat-inactivated human AB
serum (CMM). (5) Basal Human Plasma-like Medium (HPLM) (kindly provided by Dr. Jason Cantor)21
was prepared with four additional components (5 μM acetylcarnitine, 5 μM α-ketoglutarate, 5 μM malate,
and 3 μM uridine) as recently reported23, and then further supplemented with 3% heat-inactivated human
AB serum (HPLM). All complete media were filtered through a 0.22 μM filter prior to use. Patient ascites collection
Patient specimens and clinical data were obtained through the BC Cancer Tumour Tissue Repository,
certified by the Canadian Tissue Repository Network. |
All specimens and clinical data were obtained with
either informed written consent or a formal waiver of consent under protocols approved by the Research
Ethics Board of BC Cancer and the University of British Columbia (H07-00463). Patient ascites were
centrifuged at 1500 rpm for 10 min at 4°C to pellet cells and supernatant was frozen at -80°C. The
preserved supernatants were thawed for the functional assays as described below. T cell expansions
PBMCs were isolated from six human peripheral blood leukapheresis packs (STEMCELL Technologies)
using Ficoll gradient density centrifugation. CD3+ T cells were isolated from cryopreserved PBMCs using
18
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . human CD3 MicroBeads (Miltenyi) according to the manufacturer's instructions. Specific details about
stimulation protocols used can be found in Table 1. All media were supplemented with 300 IU/ml IL-2
(Novartis) before cell culture. REP CD3+ T cells (1.0 x 105) were stimulated with 50 Gy-irradiated feeder
PBMCs (2.0 x 107) and soluble CD3 (30 ng/ml; OKT3) in complete CTL:AIM-V media. Other expansion
methods were seeded using 1.0 x 106 CD3+ T cells in 1 ml of media in a 48-well plate. ICM T cells were
stimulated with ImmunoCult™ Human CD3/CD28 T Cell Activators (25 μl/ml, STEMCELL Technologies). TAC T cells were stimulated with T Cell CD3/CD28 TransAct™, human (10 μl/ml, Miltenyi). CMM and
HPLM T cells were stimulated with plate-bound CD3 (5 μg/ml; OKT3) and soluble CD28 (2 μg/ml; 15EB). On day 2-3, the media from TAC cells was replaced with fresh media as per manufacturer’s instructions. T cells were first split either on day 3 (ICM) or day 4 (other conditions) of the expansion, and
subsequently split as needed to maintain a concentration of 100,000-600,000 cells/ml (ICM) or 500,000-
1,000,000 cells/ml (other conditions). During the expansion, cells were isolated, diluted in trypan blue,
and counted using a hemocytometer. Cell counts were measured throughout the expansion to ensure
protocol-recommended densities were maintained. T cell reactivation in their respective condition, or
ascites, was performed using plate-bound CD3 (5 μg/ml; OKT3) and soluble CD28 (2 μg/ml; 15EB) for 2
days. Phenotypic and metabolic profiling by flow cytometry
Prior to expansion (day 0), cells were collected from CD3+ magnetic bead isolation. Cells were stained
with viability dye (eFlour506, Thermo) diluted in PBS (Invitrogen) at 4°C for 15 minutes. Cells were
stained with a panel of antibodies (Supplementary Table 1) in flow cytometry staining buffer for 30
minutes at 4°C. After staining, cells were washed twice and resuspended in flow cytometry staining buffer
prior to flow cytometry analysis. |
Following expansion, separate flow cytometry panels were used on day
12, for cell phenotyping and mitochondrial analysis (Supplementary Table 1). For mitochondrial analysis,
cells were stained with MitoTracker Deep Red (10 nM), MitoTracker Green (100 nM) or MitoSOX Red (2.5
uM) for 30 minutes at 37°C. Cells were then washed twice with PBS, and then stained with viability dye at
4°C for 15 minutes. For cell phenotype analysis, cells were then washed with flow cytometry staining
buffer before being fixed and permeabilized using Fixation/Permeabilization Solution Kit (Biosciences) as
19
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . per the manufacturer’s instructions. Cells were stained with a panel of antibodies (Supplementary Table
1) in 1X BD Perm/Wash™ buffer (Biosciences) for 30 minutes at 4°C. After staining, cells were washed
twice in 1X BD Perm/Wash™ buffer (Biosciences) and resuspended in flow cytometry staining buffer prior
to flow cytometry analysis. Flow cytometry analysis was carried out using a Cytek Aurora spectral flow
cytometer (3L-16V- 14B-8R configuration). Data were unmixed using SpectroFlo Software (Cytek), and
manually gated and analyzed using FlowJo V10.6.1. Figures were created using GraphPad Prism 8.1.2. To assess phenotype, cells were classified as naïve (TN; CCR7+CD45RO–), effector (TEFF; CCR7–
CD45RO–), effector memory (TEM; CCR7–CD45RO+), or central memory (TCM; CCR7+CD45RO+)24. To
assess effector function following expansion, on day 12 in their respective condition or ascites, T cells
were reactivated for 2 days using plate-bound CD3 (5 μg/ml; OKT3) and soluble CD28 (2 μg/ml; 15EB). Six hours prior to staining, cells were treated with BD GolgiStop™ (1 μl/ml, Biosciences) to assess TNFa
and INFg production. Cells that underwent metabolic analysis (Supplementary Table 1) with 2-NBDG
(100 uM) and MitoTracker Deep Red (10 nM) were not treated with BD GolgiStop™. Vβ spectratyping by flow cytometry
To assess T cell receptor (TCR) diversity following expansion (day 12), cell surface TCR Vβ repertoires
were profiled using the IOTest Beta Mark Kit (Beckman Coulter) as per the manufacturer’s guidelines. Cells were washed in PBS (Invitrogen) and blocked with Anti-Hu Fc Receptor Binding Inhibitor
(eBiosciences) for 10 minutes at room temperature. Cells were stained with a panel of antibodies
(Supplementary Table 1) in flow cytometry staining buffer with BD Horizon Brilliant Stain Buffer Plus (BD
Biosciences) for 30 minutes at 4°C. Cell viability was assessed using the Zombie NIR™ Fixable Viability
Kit (Biolegend) as per the manufacturer’s guidelines. After staining, cells were washed once in flow
cytometry staining buffer and resuspended in flow cytometry staining buffer prior to flow cytometry
analysis using a Cytek Aurora spectral flow cytometer (3L-16V-14B-8R configuration). |
Data was unmixed
using SpectroFlo Software (Cytek), manually gated and analyzed using FlowJo V10.6.1, and figures were
created using GraphPad Prism 8.1.2. Manual gating was carried out following the manufacturer’s
guidelines (Beckman Coulter). 20
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Isotope tracing analysis by GC-MS using [U-13C]glucose
For metabolic labeling experiments, complete CTL:AIM-V labeling medium consisted of glucose-free
CTL:AIM-V with 5% heat-inactivated human AB serum supplemented with 11 mM uniformly labeled 13C-
glucose ([U-13C]glucose) (Cambridge Isotope Laboratories). Glucose-free ImmunoCult™-XF T Cell
Expansion Medium (STEMCELL Technologies) was supplemented with 24 mM [U-13C]glucose. On day
12 of expansion, CD4+ T cells maintained under CTL:AIM-V or ICM were isolated using human CD4
MicroBeads (Miltenyi) and a MACS LS magnetic column according to the manufacturer's instructions;
CD8+ T cells were collected from the flow through. Separately, the cells were incubated in complete [U-
13C]glucose CTL:AIM-V or complete [U-13C]glucose ICM media supplemented with 300 IU/ml IL-2
(Novartis) for 24 hours at 5% CO2 and 37°C. Metabolic steady state was confirmed on day 12 with 2-
NBDG and isotope steady state was confirmed at 24 hours. To prepare cells for GC-MS analysis, 4 million cells per condition were washed once with ice-cold saline
solution (0.9% NaCl solution filtered through a 0.22 μm membrane filter) and resuspended in 1 ml of 50%
(vol/vol) methanol (Sigma) (0.22 μm-filtered) cooled at –80°C. Cells were snap frozen at –80°C for 20
minutes and the resulting lysate/methanol mixtures were frozen in liquid nitrogen. Samples were thawed
on ice, vortexed, and subject to three freeze-thaw cycles using liquid nitrogen and 37°C water bath. Samples were centrifuged at 10,000 rpm for 10 minutes at 4°C, and then the metabolite-containing
supernatant collected. The supernatant was evaporated until dry using a SpeedVac and no heat, and
stored at –80°C. Before running GC-MS, norvaline (1 μl) internal standard was added to each sample. Samples were resuspended in 40 μl pyridine containing methoxyamine (10 mg/ml), transferred to GC-MS
vials, and heated at 70°C for 15 minutes. 70 μl N-tert-Butyldimethylsilyl-N-methyltrifluoroacetamide
(MTBSTFA) was added, samples vortexed, and heated at 70°C for 1 hour before analyzing with GC-MS.
To prepare media for GC-MS analysis, cells were centrifuged and 1 ml of supernatant collected. The
samples were frozen at –80°C, thawed on ice, vortexed, and then 25 μl was transferred to a borosilicate
tube. Before running GC-MS, 1 μl of norvaline internal standard was added to each sample. Then, 400 μl
of methanol, chloroform, and Milli-Q purified water was added to samples. |
Samples were vortexed and
21
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . centrifuged at 2,000 rpm for 5 minutes to separate phases. The aqueous phase was collected and
evaporated until dry at 42°C using a SpeedVac. The samples were transferred to GC-MS vials and
heated at 70°C for 15 minutes before 70 μl MTBSTFA was added. Samples were vortexed and heated at
70°C for 1 hour before analyzing with GC-MS.
Metabolites were analyzed using an Agilent 6970 gas chromatograph and an Agilent 5973 mass selective
detector as previously described25. GC-MS data was analyzed using Chemstation (Aglient) and Skyline26,
and graphs were created using GraphPad Prism 8.1.2. The measured distribution of mass isotopomers
was corrected for natural abundance of 13C27. The fractional enrichment of isotopologues were then
compared against the fractional enrichment of glucose M+6 for the respective condition. Metabolites with
a fractional enrichment of below 0.05 were not considered a significant finding. Separately, 600 μl media was collected from cells, frozen at –80°C. Glucose and glutamine
concentrations in the media were measured using a NOVA BioProfile4 or by colorimetric assay
(Biovision). Statistical analysis
Statistical analysis was carried out using GraphPad Prism 8.1.2. An unpaired Student’s t-test was used
when comparing means of two groups, and one-way ANOVA was used when comparing more than two
groups. Differences were considered significant at * p<0.05, ** p<0.01, *** p<0.001, and **** p<0.001. Data availability
Processed metabolomics data files are available at https://github.com/vicDRC/metaboData.git. Flow
cytometry data will be deposited at flowrepository. 22
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . REFERENCES 1. Maude, S. L. et al. Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic
Leukemia. N. Engl. J. Med. 378, 439–448 (2018). 2. Neelapu, S. S. et al. Axicabtagene Ciloleucel CAR T-Cell Therapy in Refractory Large B-Cell
Lymphoma. N. Engl. J. Med. 377, 2531–2544 (2017). 3. Schubert, M.-L., Hoffmann, J.-M., Dreger, P., Müller-Tidow, C. & Schmitt, M. Chimeric antigen
receptor transduced T cells: Tuning up for the next generation. Int. J. Cancer 142, 1738–
1747 (2018). 4. Martinez, M. & Moon, E. K. CAR T Cells for Solid Tumors: New Strategies for Finding,
Infiltrating, and Surviving in the Tumor Microenvironment. Front. Immunol. 10, (2019). |
5. Radvanyi, L. G. et al. Specific lymphocyte subsets predict response to adoptive cell therapy
using expanded autologous tumor-infiltrating lymphocytes in metastatic melanoma
patients. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 18, 6758–6770 (2012). 6. Pavlova, N. N. & Thompson, C. B. THE EMERGING HALLMARKS OF CANCER METABOLISM. Cell
Metab. 23, 27–47 (2016). 7. Kilgour, M. K. et al. 1-Methylnicotinamide is an immune regulatory metabolite in human
ovarian cancer. Sci. Adv. 7, eabe1174 (2021). 8. Marofi, F. et al. CAR T cells in solid tumors: challenges and opportunities. Stem Cell Res. Ther. 12, 81 (2021). 9. O’Sullivan, G. M., Velickovic, Z. M., Keir, M. W., Macpherson, J. L. & Rasko, J. E. J. Cell and
gene therapy manufacturing capabilities in Australia and New Zealand. Cytotherapy 21,
1258–1273 (2019). 23
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 10. Stock, S., Schmitt, M. & Sellner, L. Optimizing Manufacturing Protocols of Chimeric Antigen
Receptor T Cells for Improved Anticancer Immunotherapy. Int. J. Mol. Sci. 20, (2019). 11. Geltink, R. I. K., Kyle, R. L. & Pearce, E. L. Unraveling the Complex Interplay Between T Cell
Metabolism and Function. Annu. Rev. Immunol. 36, 461–488 (2018). 12. Fraietta, J. A. et al. Determinants of response and resistance to CD19 chimeric antigen
receptor (CAR) T cell therapy of chronic lymphocytic leukemia. Nat. Med. 24, 563–571
(2018). 13. Leney-Greene, M. A., Boddapati, A. K., Su, H. C., Cantor, J. R. & Lenardo, M. J. Human
Plasma-like Medium Improves T Lymphocyte Activation. iScience 23, 100759 (2020). 14. Cantor, J. R. The Rise of Physiologic Media. Trends Cell Biol. 29, 854–861 (2019). 15. MacPherson, S., Kilgour, M. & Lum, J. J. Understanding lymphocyte metabolism for use in
cancer immunotherapy. FEBS J. 285, 2567–2578 (2018). 16. Fucà, G., Reppel, L., Landoni, E., Savoldo, B. & Dotti, G. Enhancing Chimeric Antigen
Receptor T Cell Efficacy in Solid Tumors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 26,
2444–2451 (2020). 17. Sato, K. et al. Impact of culture medium on the expansion of T cells for immunotherapy. Cytotherapy 11, 936–946 (2009). 18. Moore, G. E., Gerner, R. E. & Franklin, H. A. Culture of Normal Human Leukocytes. JAMA
199, 519–524 (1967). 19. Dudley, M. E., Wunderlich, J. R., Shelton, T. E., Even, J. & Rosenberg, S. A. Generation of
tumor-infiltrating lymphocyte cultures for use in adoptive transfer therapy for melanoma
patients. J. Immunother. Hagerstown Md 1997 26, 332–342 (2003). 24
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . 20. Ma, E. H. et al. Metabolic Profiling Using Stable Isotope Tracing Reveals Distinct Patterns of
Glucose Utilization by Physiologically Activated CD8+ T Cells. Immunity 51, 856-870.e5
(2019). 21. Cantor, J. R. et al. Physiologic Medium Rewires Cellular Metabolism and Reveals Uric Acid as
an Endogenous Inhibitor of UMP Synthase. Cell 169, 258-272.e17 (2017). 22. Medvec, A. R. et al. Improved Expansion and In Vivo Function of Patient T Cells by a Serum-
free Medium. Mol. Ther. Methods Clin. Dev. 8, 65–74 (2017). 23. Rossiter, N. J. et al. CRISPR screens in physiologic medium reveal conditionally essential
genes in human cells. Cell Metab. 33, 1248-1263.e9 (2021). 24. Golubovskaya, V. & Wu, L. Different Subsets of T Cells, Memory, Effector Functions, and
CAR-T Immunotherapy. Cancers 8, (2016). 25. Mullen, A. R. et al. Reductive carboxylation supports growth in tumour cells with defective
mitochondria. Nature 481, 385–388 (2012). 26. Adams, K. J. et al. Skyline for Small Molecules: A Unifying Software Package for Quantitative
Metabolomics. J. Proteome Res. 19, 1447–1458 (2020). 27. Fernandez, C. A., Rosiers, C. D., Previs, S. F., David, F. & Brunengraber, H. Correction of 13C
Mass Isotopomer Distributions for Natural Stable Isotope Abundance. J. Mass Spectrom. 31,
255–262 (1996). 28. Wang, J. et al. CAR-T cells targeting CLL-1 as an approach to treat acute myeloid leukemia. J.
Hematol. Oncol.J Hematol Oncol 11, 7 (2018). 25
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 29. Sommermeyer, D. et al. Chimeric antigen receptor-modified T cells derived from defined
CD8+ and CD4+ subsets confer superior antitumor reactivity in vivo. Leukemia 30, 492–500
(2016). 30. Kawalekar, O. U. et al. Distinct Signaling of Coreceptors Regulates Specific Metabolism
Pathways and Impacts Memory Development in CAR T Cells. Immunity 44, 380–390 (2016). 31. Jac, van B. et al. Chronic lymphocytic leukemia cells impair mitochondrial fitness in CD8 + T
cells and impede CAR T-cell efficacy. Blood vol. 134
https://pubmed.ncbi.nlm.nih.gov/31076448/ (2019). 32. Gattinoni, L. et al. Acquisition of full effector function in vitro paradoxically impairs the in
vivo antitumor efficacy of adoptively transferred CD8+ T cells. J. Clin. Invest. 115, 1616–1626
(2005). 33. Klebanoff, C. A. et al. Central memory self/tumor-reactive CD8+ T cells confer superior
antitumor immunity compared with effector memory T cells. Proc. Natl. Acad. Sci. U. S. A. 102, 9571 (2005). 34. Chandran, S. S. & Klebanoff, C. A. T cell receptor-based cancer immunotherapy: Emerging
efficacy and pathways of resistance. Immunol. Rev. 290, 127–147 (2019). 35. |
Pitoiset, F. et al. A standardized flow cytometry procedure for the monitoring of regulatory
T cells in clinical trials. Cytometry B Clin. Cytom. 94, 777–782 (2018). 36. Finney, O. C. et al. CD19 CAR T cell product and disease attributes predict leukemia
remission durability. J. Clin. Invest. 129, 2123–2132 (2019). 37. van Bruggen, J. A. C. et al. Chronic lymphocytic leukemia cells impair mitochondrial fitness
in CD8+ T cells and impede CAR T-cell efficacy. Blood 134, 44–58 (2019). 26
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 38. Sukumar, M. et al. Mitochondrial Membrane Potential Identifies Cells with Enhanced
Stemness for Cellular Therapy. Cell Metab. 23, 63–76 (2016). 39. Chang, C.-H. et al. Posttranscriptional Control of T Cell Effector Function by Aerobic
Glycolysis. Cell 153, 1239–1251 (2013). 40. Blagih, J. et al. The Energy Sensor AMPK Regulates T Cell Metabolic Adaptation and Effector
Responses In Vivo. Immunity 42, 41–54 (2015). 41. Carr, E. L. et al. Glutamine Uptake and Metabolism Are Coordinately Regulated by
ERK/MAPK during T Lymphocyte Activation. J. Immunol. 185, 1037–1044 (2010). 42. Ma, E. H. et al. Serine Is an Essential Metabolite for Effector T Cell Expansion. Cell Metab. 25, 345–357 (2017). 43. Ron-Harel, N. et al. Mitochondrial biogenesis and proteome remodeling promotes one
carbon metabolism for T cell activation. Cell Metab. 24, 104–117 (2016). 44. Comte, B., Vincent, G., Bouchard, B. & Rosiers, C. D. Probing the Origin of Acetyl-CoA and
Oxaloacetate Entering the Citric Acid Cycle from the 13 C Labeling of Citrate Released by
Perfused Rat Hearts. J. Biol. Chem. 272, 26117–26124 (1997). 45. Courtney, K. D. et al. Isotope Tracing of Human Clear Cell Renal Cell Carcinomas
Demonstrates Suppressed Glucose Oxidation In Vivo. Cell Metab. 28, 793-800.e2 (2018). 46. Sukumar, M. et al. Inhibiting glycolytic metabolism enhances CD8+ T cell memory and
antitumor function. https://www.jci.org/articles/view/69589/pdf (2013)
doi:10.1172/JCI69589. 47. Klein Geltink, R. I. et al. Metabolic conditioning of CD8 + effector T cells for adoptive cell
therapy. Nat. Metab. 2, 703–716 (2020). 27
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 48. Gong, Y., Yang, J., Wang, Y., Xue, L. & Wang, J. Metabolic factors contribute to T-cell
inhibition in the ovarian cancer ascites. Int. J. Cancer 147, 1768–1777 (2020). 49. Kim, S., Kim, B. & Song, Y. S. Ascites modulates cancer cell behavior, contributing to tumor
heterogeneity in ovarian cancer. |
Cancer Sci. 107, 1173–1178 (2016). 50. Jin, C. et al. Allogeneic lymphocyte-licensed DCs expand T cells with improved antitumor
activity and resistance to oxidative stress and immunosuppressive factors. Mol. Ther. Methods Clin. Dev. 1, 14001 (2014). 51. Tkachev, V. et al. Programmed death-1 controls T cell survival by regulating oxidative
metabolism. J. Immunol. Baltim. Md 1950 194, 5789–5800 (2015). 52. Frauwirth, K. A. et al. The CD28 Signaling Pathway Regulates Glucose Metabolism. Immunity
16, 769–777 (2002). 28
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . DECLARATIONS
Ethics approval and consent to participate Patient specimens and clinical data were obtained through the BC Cancer Tumour Tissue Repository, certified by the Canadian Tissue Repository Network. All specimens and clinical data were obtained with either informed written consent or a formal waiver of consent under protocols approved by the Research Ethics Board of BC Cancer and the University of British Columbia (H07-00463). Samples are stored in a certified BioBank (BRC-00290). Consent for publication Not applicable. Availability of data and material Processed metabolomics data files will be deposited to github.com. Flow cytometry data will be deposited at flowrepository. Competing interests RJD is a member of the Scientific Advisory Boards of Vida Ventures and Agios Pharmaceuticals and is a founder of Atavistik Biosciences. JRC is an inventor on a patent application for HPLM (PCT/US2017/061377) assigned to the Whitehead Institute. CS is a Principal Scientist at STEMCELL Technologies. JY is a Scientist at STEMCELL Technologies. STEMCELL Technologies provided reagents in-kind for the study but were not involved in funding the study, performing experiments, or analyzing the data. Funding This study was supported by the research grants to JJL from the Canadian Institutes of Health Research (PJT 162279). SK is supported by a BioCanRx Studentship Award and BC Cancer Studentship Award. MK is supported by a University of Victoria Graduate Award. JS is supported by a Canadian Institutes of Health Research Banting and Best Doctoral Award. Authors’ contributions SM, SK and MK designed and performed experiments, analyzed the data, and wrote the manuscript. JS helped design and performed experiments. JS and RJD ran the mass spectrometry samples and analyzed the raw data. TT and AD irradiated the PBMCs. KSH, JRC, JY, and CS provided reagents and contributed to experimental design. JJL conceived the project and wrote the manuscript. 29
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . Table 1: List of culture formulations and expansion conditions Glucose and glutamine concentrations measured using colorimetric assay. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 1: Expansion conditions skew proliferation, differentiation and activation (a-g) T cells from six healthy donors were expanded in 5 different conditions for 12 days: CTL:AIM-V (REP), ImmunoCult-XF (ICM), TexMACS (TAC), Complete Corning media (CMM) and Human Plasma- like Medium (HPLM) (a) Log fold increase in cell number throughout the 11-day expansion (b) Proportion of CD4+ and CD8+ T cells of live CD3+ cells, pre- and post-expansion from six healthy donors. (c-e) Representative plot (c) and tabulated data for CD8+ (d) and CD4+ (e) T cells following expansion: naïve (TN), central memory (TCM), effector (TEFF), and effector memory (TEM). (f) Percentage of CD25 and (g) PD-1 positive CD4+ and CD8+ T cells. (h) Percentage of IFNγ and TNFα positive cells after CD3/CD28 reactivated following expansion (n=3). Bar graphs represent mean of n=6 (a-g) and (h) n=3 +SEM from healthy donors. Statistical significance was calculated using a Student’s t-test (b) or a one-way ANOVA (d-h) (* p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 2: T cell products exhibit different mitochondrial phenotypes (a-c) T cells from three healthy donors were expanded in 5 different conditions for 12 days. (a,b) Representative plot (left) and tabulated data (right) for median fluorescence intensity (MFI) of mitochondrial activity (MitoTracker Deep Red) and (b) mitochondrial mass (MitoTracker Green) (c). Representative plot (left) and tabulated data (right) for percentage of mitochondrial mass high and mitochondrial ROS high (MitoSOX) live populations. Bar graphs represent mean of n=3 +SEM from healthy donors. Statistical significance was calculated by one-way ANOVA (* p <0.05, ** p <0.01, *** p <0.001, **** p <0.0001). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 3: Expansion conditions dictate nutrient uptake but is uncoupled to T cell function (a-d) T cells from three healthy donors were expanded in 5 different conditions for 11 days. |
Glucose and glutamine concentrations in the media were measured between days 11-12. (a) Extracellular glucose and (b) glutamine concentrations in the fresh media (white bars) and spent media after culture for 24 hours (solid bars). (c, d) On day 11, expanded T cells from all 5 conditions were switched to the REP media (CTL:AIM-V) for 24 hours. (c) Extracellular glucose and (d) glutamine concentrations in fresh CTL:AIM-V (white bar), and spent media after culture for 24 hours with REP expanded cells (blue bar) and the four other expansion products in CTL:AIM-V (blue dashed bar). (e,f) On day 12, T cells from all 5 conditions underwent CD3/CD28 reactivation for 2 days in their respective conditions (solid bars) or were switched to CTL:AIM-V (blue dashed bars). Percentage of (e) IFNγ and (f) TNFα positive cells. Bar graphs represent mean n=3 +SEM from healthy donors. Statistical significance was calculated by one-way ANOVA (a,b,e,f) or Student’s t-test (c,d) (* p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 4: Culture media influences glucose utilization and the metabolic profile of T cells. (a) Schematic of [U-13C]glucose metabolism, circles represent the carbons for each metabolite. (b-k) Three healthy donors were expanded in REP and ICM for 11 days. On day 11, CD4+ and CD8+ cells were isolated and incubated in the following [U-13C]glucose conditions for 24 hours: REP cells in CTL:AIM-V (blue bar), ICM cells in ImmunoCult-XF (red bar) and ICM cells cultured in CTL:AIM-V (red and blue dashes). (b) Extracellular lactate M+3 relative to extracellular glucose M+6 enrichment. (c) Intracellular alanine M+3 relative to intracellular glucose M+6 enrichment. CD8+ intracellular enrichment of (d) serine M+3, and (e) glycine M+2 relative to intracellular glucose M+6 enrichment. (f) Pyruvate carboxylase activity (Citrate M+3/Pyruvate M+3) and (g) Pyruvate dehydrogenase activity (Citrate M+2/Pyruvate M+3). (h) Proportion of intracellular α-ketoglutarate M+2 to citrate M+2 enrichment. (i) Glutamine uptake (mM) from day 11-12 in CD4+ and CD8+ T cells. Percentage of PD-1 (j) and CD25 (k) positive cells. Data are shown as mean of n=3 +SEM from healthy donors. Statistical significance was calculated by Student’s t-tests (* p<0.05, ** p<0.01, *** p<0.001). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.24.457536
;
this version posted August 26, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 5: T cell products exhibit different metabolic and functional phenotypes in the ascites tumour microenvironment (a-f) T cells from three healthy donors were expanded in 5 different conditions over 12 days. |
On day 12 T cell products were reactivated (CD3/CD28) in ascites, T cell metabolism and function was assessed after 2 days. (a) Schematic of experimental timeline. (b) Percentage of live cells in ascites supernatant. Median fluorescence intensity (MFI) of (c) glucose uptake (2-NBDG) and (d) mitochondrial activity (Mitotracker DeepRed) in the ascites. (e) Percentage of PD-1, (f) IFNγ and TNFα positive cells in the ascites. Data are shown as mean of n=3 +SEM from healthy donors. Statistical significance was calculated by one-way ANOVA (* p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001). |
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Regional Differences in Brain Plasticity and Behaviour as a
Function of Sex and Enrichment Type: Oxytocin Matters
Authors & Affiliations: Jamshid Faraji1, 2*, Hamid Lotfi3*, Alireza Moharrerie4, S. Yaghoob Jafari2, Nasrin Soltanpour1, Rosa Tamannaiee5, Kameran Marjani5, Shabnam Roudaki5*, Farhad Naseri6, Reza Moeeini5 & Gerlinde A.S. Metz1,7#
1University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Lethbridge, Canada; 2Golestan University of Medical Sciences, Faculty of Nursing & Midwifery, Gorgan, Iran; 3Islamic Azad University, Department of Psychology, Tonekabon Branch, Tonekabon, Iran; 4Golestan University of Medical Sciences, Department of Anatomy, Gorgan, Iran; 5Avicenna Institute of Neuroscience, Department of Behavioural Studies, Yazd, Iran; 6Peyman Medical Laboratory, 186 Ayatollah Yazdi Blvd., PC 27004186, Yazd, Iran; 7University of Lethbridge, Southern Alberta Genome Sciences Centre, Lethbridge, Canada. Authors contributed equally. Abbreviated Title: Environmental Enrichment and Oxytocin
Number of Pages: 39 Number of Figures: 7 Number of Tables: 0 Number of Words in Abstract: 175 Number of Words in Introduction: 439 Number of Words in Discussion: 1048
# Corresponding author:
Gerlinde A.S. Metz, PhD Canadian Centre for Behavioural Neuroscience University of Lethbridge 4401 University Drive Lethbridge, Alberta T1K 3M4 Canada Email: [email protected]
1
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Abstract
The early environment is critical to brain development, but the relative contribution
of physical vs. social stimulation is unclear. Here, we investigated in male and female rats
the response to early physical and social environmental enrichment in relation to oxytocin
(OT) and brain-derived neurotrophic factor (BDNF) expression. The findings show that
males and females respond differently to prolonged sensorimotor stimulation from
postnatal day 21-110 in terms of functional, structural and molecular changes in the
hippocampus vs. medial prefrontal cortex (mPFC). Physical enrichment promoted motor
and cognitive functions and hippocampal BDNF mRNA and protein expression in both
sexes. Combined physical and social enrichment, however, promoted functional and
structural gain predominantly in females. These changes were accompanied by elevated
plasma oxytocin (OT) levels and BDNF mRNA expression in the mPFC while the
hippocampus was not affected. |
Administration of an OT antagonist in females blocked the
beneficial effects of enrichment and led to reduced cortical BDNF signaling. These
findings suggest that an OT-based mechanism selectively stimulates a region-specific
BDNF response which is dependent on the type of experience. Keywords: Social enrichment, Environmental enrichment, Oxytocin, BDNF, Brain-
derived neurotrophic factor, Hippocampus, Medial prefrontal cortex, Motor function,
Learning and Memory
2
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Introduction
Environmental enrichment (EE) involving sensorimotor and social stimulation is
recognized as one of the most powerful influences on neuronal plasticity (1-6). Hence, EE
has become a classic experimental paradigm to study the impact of experiences on the brain,
and the treatment of psychiatric and neurological diseases (7, 8) and stress (5, 6, 9, 10). Social interaction represents an integral component of EE and reveals pronounced sex
differences (11, 12). Females in general respond more prominently to social enrichment
than males (3, 4), with some exceptions (13). Neurohormonal disparities and procedural
variables contribute to these sexual dimorphisms (14, 15). The impact of EE is particularly reflected by the hippocampus (HPC) (16-19). The HPC,
in conjunction with the medial prefrontal cortex (mPFC), contributes to the processing of
emotional and social memories (19-21), and is intimately involved in movement (22) and
stress response (23). Moreover, the HPC is particularly responsive to social context (24,
25) and receptors for oxytocin (OT), a neuropeptide that promotes social behaviours and
bonding (25, 26), are abundantly expressed by hippocampal neurons (27, 28). The pathway
linking social support and OT may be involved in stress response regulation (29), cortical
plasticity induced by sensory stimulation (30, 31) and activation of the dopamine reward
systems (32). Especially in females, social enrichment was shown to increase hypothalamic
OT production along with increased brain-derived neurotrophic factor (BDNF) expression
in the mPFC (3, 4, 33). BDNF expression responds to both sensorimotor and social enrichment. It is expressed
in response to voluntary physical exercise (34, 35) and is essential for synaptic plasticity
and HPC neurogenesis induced by sensorimotor stimulation (36, 37). BDNF was suggested
3
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . |
to be the critical factor linking the benefits of social enrichment to neural plasticity and
synaptogenesis (3, 38). This association was confirmed by studies of social isolation, which
reduces circulating OT levels (39) and activity of OT-related neural circuits (40), along
with reduced HPC volume and BDNF expression (41). Thus, social stimulation produced
by EE paradigms may occur through a close dialogue between the brain’s OT system and
BDNF signaling cascades. The differential impacts of sensorimotor vs. social stimulation
and their links to OT and BDNF are not yet known, however. Here, we investigated in rats
the response to sensorimotor and social enrichment in relation to OT and BDNF expression. We hypothesized that prolonged sensorimotor enrichment from early life to adulthood
promotes sex-specific HPC and mPFC development via an OT-BDNF pathway. We
anticipated that OT initiates a sexually dimorphic response to social support which then
triggers BDNF. The results suggest that an OT-based mechanism selectively stimulates
region-specific BDNF expression in the mPFC that is different from the HPC changes. Results
Prolonged Physical Enrichment Promotes Brain Growth and Sensorimotor
Performance
Body and brain weight. Male and female rats were assigned to Standard Environment
(SE), Simple Enriched Environment (sEE) and Complex Enriched Environment (cEE)
(n=10-11) (Figure 1A-D). Body weight among males showed a main effect of Group
(F2,29=54.79, p<0.001, η2=0.79; R-M ANOVA) and a significant interaction between
Group and Day (p<0.001) where cEE rats weighed less than SE and sEE rats
(227˂249.97˂249.43g, all p<0.05, post-hoc Tukey HSD). Furthermore, post-mortem brain
4
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . weight indicated significant group differences (F2,29=6.70, p<0.05) where cEE rats
displayed higher brain weight than other groups (1.703˃1.645˃1.641g, all p<0.05, post-
hoc Tukey, Figure 1E). Females did not show significant group differences in terms of
body and brain weight (Figure 1F). Thus, sensorimotor stimulation promoted the ratio of
brain/body weight in males but not females. Also, there was no significant correlation
between body and brain weights (all p≥0.05, Figure 1G&H). Sensorimotor function. All animals were able to navigate the BBT (Figure 2A). Males
(n=9-10) showed a significant effect of Group (F2,25=19.11, p<0.001, η2=0.605; R-M
ANOVA), Trial (p<0.001) and interaction between Group and Trial (p<0.05) when latency
(i.e., the time spent to traverse the bar) on the BBT was considered. cEE rats were able to
cross
the bar with shorter
latency when compared
to SE and sEE animals
(6.90˂10.70˂11.84 s, all p<0.05, post-hoc Tukey HSD). |
There was no difference between
SE and sEE groups (Figure 2B). Also, a significant effect of Group (F 2,25=7.92, p<0.05,
η2=0.38; R-M ANOVA) indicated that male cEE rats displayed a longer stride length than
other groups (4.86˃4.11˃4.03 cm), particularly on trials 2 and 3 (all p<0.05, post-hoc
Tukey HSD). More importantly, the average stride length in cEE increased across three
trials (4.41<4.98<5.18 cm) suggesting that rats gradually gained better balance and
performed longer steps. SE and sEE rats did not show these improvements across trials
(Figure 2C). Housing conditions in females (n=10-11) also resulted in a significant effect
of Group (F2,28=7.71, p<0.05, η2=0.35; R-M ANOVA), Trial (p<0.05) and Group by Trial
(p<0.01) where cEE rats displayed significantly lower latency during beam walking than
SE and sEE groups (7.12˂9.98˃9.77s, all p<0.05, post-hoc Tukey HSD, Figure 2D). Also,
female cEE rats showed a larger stride length than SE and sEE groups in trial 2
5
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . (3.20˃2.78˂2.81 cm; F2,28=4.82, p<0.05, η2=0.25; R-M ANOVA, Figure 2E). Thus,
sensorimotor stimulation promoted balance and sensorimotor integration in males and
females. Prolonged Physical Enrichment Facilitates Sex-specific Hippocampal Plasticity and
Spatial Learning
HPC volume. The HPC volume for each rat was estimated based on 9–10 cross-sections
of the hippocampal area (Figure 3A). In males (n=7-8) there was no impact of cEE on HPC
volume (p>0.42, Figure 3B). In females (n=6-8) however, cEE housing led to larger HPC
volume compared to sEE and SE groups (F2,23=5.23, p<0.05; O-W ANOVA, Figure 3C). Spatial learning. In male rats (n=7-8), spatial performance in the MWT was tested using
a one-day assessment protocol (10 trials/animal). All groups acquired and retrieved the
location of the hidden platform in a similar manner (Figure 3D). However, cEE animals
swam significantly faster
than sEE and SE groups during spatial navigation
(20.12˂28.04˂32.20 s; F2,19=17.65, p<0.001, η2=0.65; R-M ANOVA). A main effect of
Trial (p<0.001) but no interaction between Group and Trial (p=0.92) was observed. Overall,
cEE rats located the hidden platform more quickly than other groups. Analysis of swim
speed during the 10-trial-acquisition period also showed a relatively flat speed profile
across all groups. SE rats navigated more slowly than other groups as testing proceeded. However, no significant changes were observed in swim speed. Furthermore, probe
function indicated that cEE rats, in comparison with sEE and SE groups, spent a
considerable proportion of their time (48.96˃35.27˃30.82%; F2,19=10.82, p<0.001; O-W
ANOVA, Figure 3E) searching in the target quadrant (quadrant 3) in which the hidden
6
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. |
The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . platform had previously been located. Representative plots of paths are shown in Figure
3E-right panels. No significant group difference was observed when corridor percent time
or swim error in trials 1 and 10 were investigated (Figure 3F). Female rats (n=7-8), regardless of their group identity, were also able to acquire and
retrieve the spatial information at a similar rate than males. R-M ANOVA, however,
showed a significant main effect of Group (F2,20=17.07, p<0.001, η2=0.63) suggesting that
cEE female rats required less time to find the hidden platform than other groups
(19.58˂26.21˂27.42 s; Figure 3G). The main effect of Trial (p<0.001) but not Group by
Trial interaction (p>0.72) was significant. Thus, although all female rats showed a gradual
decrease in latency across trials, the cEE group located the platform more quickly than SE
and sEE animals. No difference was found in swim speed among groups. Moreover, the
probe trial (30-s duration) showed that while all rats spent more time in the target quadrant
(quadrant 2), cEE rats still spent more time here than sEE and SE groups
(49.41˃38.46˃38.05%; F2,20=12.02, p<0.001; O-W ANOVA, Figure 3H). Also, analysis
of corridor percent time in the first and last trials (trial 1 and 10) indicated inaccurate swims
relative to the platform location in trial 10 only in sEE and SE rats (F2,20=4.57, p<0.05; O-
W ANOVA, Figure 3I). The representative swim paths show corridor errors in the first and
last trials made by one rat from each group (Figure 3I-Right panels). Overall, results in the
MWT indicated enhanced working memory in rats that were raised in the cEE-housing
condition. Dwell time in the quadrant that formerly contained the platform, indicating
enhanced reference memory, was also significantly higher for male and female cEE rats. 7
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Prolonged Physical Enrichment Promotes Hippocampal BDNF mRNA and Protein
Expression
BDNF mRNA. Analysis of BDNF mRNA expression in the HPC was based on 3-4 tissue
sections per animal and region (~−1.60 to −4.52 mm relative to bregma, Figure 4A). In
males (n=4), in situ hybridization revealed that BDNF mRNA in the HPC was abundant
and expressed differentially in the CA1, CA3, and DG, but not in the CA2. SE and sEE
animals displayed a marked decrease in BDNF mRNA in the CA1 (F2,9=6.88, p<0.01; O-
W ANOVA), CA2 (F2,9=24.69, p<0.001) and DG (F2,29=13.61, p<0.01). No differences
were found in the CA3 (p=0.07, Figure 4B). |
The only difference between SE and sEE
groups was found in BDNF mRNA expression in the CA2 (p<0.05; post-hoc Tukey HSD). In females (n=4), BNDF mRNA in all four HPC sub-regions showed a significant increase
in cEE compared to the other two groups (CA1: F2,11=12.89, p<0.001; CA2:
F2,11=30.56, p<0.001; CA3: F2,11=8.67, p<0.05; F2,11=22.09, p<0.001; O-W ANOVA,
Figure 4C). Thus, prolonged cEE housing had a noticeable impact on mRNA expression
in all HPC sub-regions in females. BDNF protein. BDNF protein expression in males (n=4) revealed no differences
between the left and right HPC. However, O-W ANOVA indicated group differences in
terms of BDNF protein (F2,9=18.11, p<0.001), where rats raised in the cEE condition
showed higher BDNF protein expression in the HPC compared to sEE and SE groups
(233.25˃188˃184 ng/g; Figure 4D). No difference was observed between sEE and SE
groups (p=0.90). In females (n=4), the impact of cEE-housing on BDNF protein expression
was replicated (F2,9= 6.56, p<0.05) indicating that cEE housing increased BDNF protein
expression relatively to sEE and SE conditions (164.75˃145.25˃143.75 ng/g; Figure 4E). 8
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Overall, HPC BDNF mRNA and protein expression was raised by cEE housing in both
males and females. Oxytocin Reflects Synergistic Benefits of Social and Physical Enrichment
Body and brain weight. Female rats were housed in groups of 13-14 in csEE and ssEE
units for approximately 81 days (Figure 5A-B). Despite higher body weights in csEE rats
compared to ssEE rats in the course of experiment, R-M ANOVA did not show significant
group differences (p=0.058; Figure 5C). However, there was a significant group difference
in terms of brain weights (F1,25=4.65, p<0.05; O-W ANOVA) where the csEE rats
displayed higher brain weights than ssEE rats (1.60˃1.53g; Figure 5D). Body and brain
weights showed no correlation (all p<0.05; Figure 5E). Brain volume and cortical thickness. The synergy between social experience and
sensorimotor stimulation in females caused a trend in larger HPC (p=0.361) and brain
volumes (p=0.054) (n=5-6), with slightly larger brains in csEE compared to ssEE rats. However, csEE rats showed significantly greater volumes in the rostro-caudal sections 2-
15, mostly corresponding to the medial prefrontal cortex (mPFC) and primary motor cortex
(M1; all p<0.05; O-W ANOVA; Figure 6A). Thus, brain volume was partially impacted by
csEE indicating local sensitivity of the brain to the synergy between social experience and
sensorimotor stimulation. Furthermore, cortical thickness revealed growth in the medial
(left: 1.67˃1.46 mm, 1,11=11.03, p<0.01; right: 1.65˃1.48 mm, F1,11=6.37, p<0.05) and
lateral (left: 1.50˃1.30 mm, F1,11=7.59, p<0.05; right: 1.55˃1.32 mm, F1,11=13.91, p<0.01)
portions of the cortex in the csEE compared ssEE rats. |
The ventrolateral portion in both
hemispheres remained unaffected (all p<0.05; Figure 6B). Hence, cortical thickness
9
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . confirmed the regional susceptibility of the female brain to social and sensorimotor
experiences. Exploratory activity. Figure 6C depicts the OFT along with paths taken by ssEE and
csEE rats. Analysis of corner time (time spent in the corners) and thigmotaxis (repetitive
pattern of exploration near to the wall) indicated that csEE rats spent less time in the corners
(n=8-9,
F1,15=4.70, p<0.05;
O-W
ANOVA)
and
thigmotactic
behaviour (F1,15=6.01, p<0.05; O-W ANOVA) when compared with ssEE rats (Figure
6D&E). Also, both groups displayed similar profiles of stop time in the OFT (p=0.189),
although the average number of stops in the csEE group was significantly lower than in
ssEE rats (F1,15=5.18 , p<0.05; O-W ANOVA; Figure 6F&G). Furthermore, path length
indicated that the csEE group traveled significantly longer distances than ssEE rats
(F1,15=11.36, p<0.01, O-W ANOVA). Compared to ssEE animals, csEE rats explored the
OFT faster (F1,15=7.05, p<0.05, O-W ANOVA; Figure 6H&I). Thus, social experience
associated with sensorimotor stimulation impacted both motivational and emotional
aspects of exploratory activity. BDNF mRNA expression. BDNF mRNA levels in the HPC (n=5) were not affected by
housing conditions (dorsal: p=0.40, ventral: p=0.93). However, the ssEE rats expressed
less BDNF signal (~21%) in the mPFC when compared with the csEE group
(F1,8=13.52, p<<0.05; Figure 6J). There was no difference between the right and left mPFC
(p=0.08). Plasma OT levels. Figure 6K illustrates changes in plasma OT concentrations in both
groups (n=11-13) as a function of housing condition. csEE rats displayed higher levels of
circulating OT than ssEE rats (F1,22=16.38, p<0.001; O-W ANOVA) suggesting a
10
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . significant impact of social stimulation on plasma OT (105.48˃81.81 pmol/L). There were
no correlations between circulating OT concentration and OFT measures. In summary, prolonged social and sensorimotor experiences are associated with
alterations in cortical anatomy, BDNF expression in the mPFC, and circulating OT levels
in females. Oxytocin Antagonist Prevents Cortical BDNF Expression and Benefits of Enrichment
OT antagonist effects in OFT. Figure 7A&B illustrates the experimental design where
one of two groups (n=5-6) raised in csEE units for 81-85 days intermittently received an
OT antagonist (L-366,509). |
OT antagonist treatment significantly impacted locomotion
and anxiety-related behaviour (Figure 7C-E). csEE+OTa rats made more stops particularly
in the third (p<0.01) and fourth (p<0.01) time bins than csEE animals (57.66˃37.80;
F1,9=8.27, p<0.05; O-W ANOVA) along with enhanced thigmotactic behaviours
(60.50˃37.20%; F1,9=7.26, p<0.05) during exploration in the OFT. Thus, the OT antagonist
influenced especially emotional aspects of OFT exploration. Plasma OT levels. Circulating OT concentration (n=11-12) showed significant
differences between groups (F1,21=4.88, p<0.05; O-W ANOVA), indicating that the OT
antagonist significantly reduced the circulating OT concentration in csEE+OTa rats
(106.49˃97.06 pmol/L; Figure 7F). BDNF mRNA expression. HPC BDNF mRNA expression (n=5) revealed no significant
group differences (dorsal: p=0.091, ventral: p=0.063). However, the BDNF mRNA signals
in the mPFC in csEE+OTa rats was significantly reduced (~19%) compared to untreated
csEE-only animals (F1,8=25.86, p<0.001; Figure 7G&H). No significant differences were
11
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . found between the right and left hemispheres (p>0.05). These findings suggest that OT
antagonist administration blocked the synergistic effects of prolonged social and
sensorimotor experiences on BDNF mRNA signals in the mPFC only. The observed
differences were further supported by a significant correlation between OT concentration
and BDNF mRNA expression in mPFC of csEE+OTa rats (n=5, r=.88, p<0.05; Figure 7I);
similar correlations were not found in the HPC. Discussion
The present study demonstrated that prolonged sensorimotor and social stimulation
promotes hippocampal-cortical plasticity, cognitive and motor function, in association with
BDNF mRNA expression. Both males and females benefited from the cEE condition in
terms of sensorimotor integration and spatial learning, with females being slightly more
receptive. Moreover, physical enrichment by cEE also raised hippocampal BDNF mRNA
and protein expression in both males and females. Females displayed regional
susceptibility to combined social and sensorimotor experiences with largest effects in
mPFC and motor cortex, which were linked to elevated BDNF expression. Importantly,
enhanced mPFC BDNF signals were mediated by OT levels in females in response to the
synergy between sensorimotor and social enrichment. These changes, however, were
abolished by OT antagonist treatment, suggesting an OT-mediated pathway linking
sensorimotor and social context to regional brain plasticity. Early-life experiences in rodents have a profound impact on motor and cognitive
development and maturation (42-44) and involve BDNF signaling to shape HPC-mPFC
projections in response to psychosocial experiences (45-48). |
The robust projections from
12
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . the HPC to the mPFC (49-51) and the motor cortex (22, 52) propose a dynamic process of
brain reorganization based on sensorimotor inputs, especially experiences in early life (53,
54). Previous insights mainly stem from the classic EE paradigm, which generally involves
aerobic exercise (AE) on running wheels in rodents (19, 55-59). AE comprises components
of aerobic exercise such as cardiovascular stimulation, motivational aspects of behaviour,
and general arousal. Reports show that the physiological aspects of AE (e.g. increased
cerebral blood volume and blood flow, blood-brain-barrier permeability, angiogenesis and
neurogenesis, glucose utilization and increased hormone and growth factor circulation)
may explain its robust effects on brain structures such as the HPC and mPFC (60-62). By
contrast, the present physical EE protocol lacks an apparatus to induce AE, but still
encourages musculoskeletal activity through behaviours such as free horizontal and
vertical exploration, climbing, and turning. Although hippocampal interactions with the motor system have been extensively
investigated (22, 52), hippocampal reliance on sensorimotor inputs during development
has received little attention. The present study therefore compared the impact of
sensorimotor vs. social context on the maturation of HPC and mPFC and on cognitive vs.
sensorimotor functions. Rats typically develop many movement skills by the time they are
weaned from their mother at postnatal day 21, but some remain immature by that time (63,
64). The present study provided animals with low-intensity sensorimotor stimulation in the
cEE condition throughout their adolescence to facilitate ongoing neural plasticity. Interestingly, females displayed more susceptibility to the impact of early sensorimotor
stimulation in HPC volume and BDNF expression than males. The cEE paradigm also led
to greater accuracy in females’ spatial learning indicated by an increased in-corridor
13
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . swimming in the last trial. The anatomical measures of brain weight and volume, and
cortical thickness in females were most affected by the combination of sensory and social
stimulation, however. Interestingly, brain weight in females was not affected by
sensorimotor stimulation only. Accordingly, as previously shown by this team (3), social
stimulation critically influences neuroanatomy and behaviour in females. |
Results in the present experiment offer new insights on the dynamic interaction between
early sensorimotor and social enrichment that regulates brain structure and function in
females via intensified OT action. Previously, we have found that social enrichment is
causally associated with increased OT levels and telomere lengths in females (4). The
neuropeptide OT, which is primarily synthesized in the paraventricular nucleus (PVN) and
supraoptic nucleus of the hypothalamus (65), mediates early experience-dependent
plasticity in the brain (31). Moreover, OT not only responds to the activation of sensory
circuits (66), but also is a key hormonal correlate of social behaviours in mammals (67, 68)
and regulates brain responses to environmental stimulation in both sexes (4). OT may
reduce stress and exert anxiolytic consequences particularly when released in response to
haptic contact via skin (Uvnas-Moberg et al., 2014). However, a robust effect of sex was
reported in OT receptor density throughout the brain (69) and in OT receptor signaling in
the mPFC of rats (70, 71), which may explain why males and females respond differently
to social experiences. In the present experiment, the csEE female rats displayed a
prominent OT response to the housing condition where sensorimotor and social
stimulations were combined for 3 months. Both structural and functional alterations in the
presence of increased OT levels disappeared once the endogenous OT was interrupted by
an antagonist. This causal, behaviour-to-hormone approach supports the majority of
14
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . correlational data that link OT to social experiences (33, 72). Social cues typically cause
OT release in brain regions that are important for triggering or regulating social behaviours. Conversely, the OT may take part in functional changes due to its capacity to modulate
emotional and social behaviours. In light of these reciprocal effects which extend to HPC
and mPFC, one can hypothesize that the OT system maintains a close dialogue with sensory
processing that is critical for detecting and interpreting social cues (73). Furthermore, the
present findings expand earlier studies in which OT can be released by non-noxious
stimulation through stimulation of cutaneous nerves (74). Moreover, prolonged
sensorimotor and social stimulation in the csEE, as reflected in enhanced BDNF signaling
in the mPFC and exploration in the OFT, is arguably also linked to OT-mediated anxiolytic
effects (4, 75, 76). The present study suggests that cEE promoted BDNF mRNA signaling in all HPC sub-
regions which in turn indicates that both granule cells of the DG and pyramidal cells of
areas CA1 and CA3 were receptive to physical activity. |
Greater susceptibility to the cEE
paradigm in females can also be attributed to interactions between 17β-estradiol, BDNF
and the HPC mossy fiber pathway (77) as it was also shown that 17β-estradiol upregulates
mossy fiber BDNF synthesis in female rats (78). Although the signaling pathway linking OT to BDNF regulation is not entirely known,
robust OT-induced regulation of BDNF expression and associated neuronal plasticity has
been shown in various contexts. OT is able to enhance BDNF protein expression (79-81),
increase neurogenesis and brain volume (80), and modulate behavior via BDNF-TrkB
signaling in OT neurons (82). Functionally, OT acts via the cAMP/PKA-CREB signaling
pathway to gate BDNF actions (83, 84). Moreover, OT-enriched mRNAs encode proteins
15
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . critical for structural and functional plasticity, including cytoskeletal and postsynaptic
organization and pathways involved in rapid activity-induced, experience-dependent
plasticity (82). Conclusion
Social context represents a critical determinant of lifetime health and brain function (4). The present study compared the impact of sensorimotor vs. social stimulation and for the
first time propose a causal link between social stimulation, OT action and subsequent
BDNF expression. The data show that early sensorimotor stimulation and social
enrichment combined are most powerful in inducing a region-specific response in the
mPFC, and that OT is essential to brain maturation and neurodevelopment. The findings
suggest combining sensorimotor and social enrichment have synergistic and long-term
benefits for brain development and maturation through an OT-BDNF axis. Given that
women are particularly vulnerable to various types of neurological and psychiatric disease
(85), the present findings are relevant for the design of early intervention through physical
and social experiences. Understanding the molecular correlates of activity-dependent brain
development will advance such approaches to better support lifetime brain health and
resilience. Materials and Methods
This study involved male and female Wistar rats, bred and raised at the local vivarium. Animals were housed at room temperature (21–24°C) on a 12-hour light/dark cycle (lights
on at 7:30 h) with ad libitum access to food and water. Body weight was recorded every
16
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . |
five days. Prior to behavioural testing rats were handled for approximately 3 min daily for
2-3 consecutive days. All behavioural training and testing was performed during the light
phase of the circadian cycle at the same time of day by four male and four female
experimenters blind to the experimental groups. All procedures in this study were carried
out in accordance with the National Institute of Health Guide to the Care and Use of
Laboratory Animals and were approved by the Avicenna Institute of Neuroscience (AINS)
Animal Care Committee. Experimental Design
Experiment 1 (Males and Females): After weaning at post-natal day 21 (PND 21), 38
male and 32 female pups gathered from 13 different litters were randomly allocated to one
of three housing conditions: (i) Standard Environment (SE), (ii) Simple Enriched
Environment (sEE), and (iii) Complex Enriched Environment (cEE). All animals were
raised either in SE, sEE or cEE in groups of 2 for approximately 91 days. Once behavioural
assessments were completed on day 98-99, all rats were euthanized for morphological
assessment. Based on the results and our earlier work which revealed the largest effects of
social support in females (3, 4), follow-up work in Experiments 2 and 3 focused on female
animals. Experiment 2 (Females): At weaning (PND 21), 27 female pups were randomly selected. Based on the hypothesis, female pups were randomly split into two groups: (i) Simple-
Socially Enriched Environment (ssEE) and (ii) Complex-Socially Enriched Environment
(csEE). Both groups were housed in groups of 14 and 13 animals, respectively, for
17
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . approximately 81 days. After behavioural testing was completed on day 89, all rats were
euthanized for morphological and molecular assessments. Experiment 3 (Females): At weaning (PND 21), 24 female pups were randomly selected
from 4 different litters and split into two groups: (i) Complex-Socially Enriched
Environment (csEE; n=12) and (ii) Complex-Socially Enriched Environment in which an
Oxytocin (OT) antagonist was administered (csEE+OTa). All rats were euthanized on days
91-92 for structural and molecular assessments. For all experiments, only litters consisting of 8–12 pups were used in order to control
for the effect of litter size on early dam-offspring relationships. Animals were constantly
living in their units until completion of the experiment. Rats in all experiments were
randomly assigned to one of the morphological and molecular assays. Housing Conditions: Physical and Social Enrichment
Experiment 1: (i) Standard Environment (SE): Rats assigned to the SE condition were
housed and raised in standard sized Polycarbonate cages (43 cm × 29 cm × 19 cm). |
(ii)
Simple Enriched Environment (sEE): The sEE unit was a larger Polycarbonate cage
(97 cm × 97 cm × 60 cm) with no additional enrichment except for a staircase by which
animals were able to reach the water bottle (Figure 1A-D). (iii) Complex Enriched
Environment (cEE): In the large Polycarbonate cage (97 cm × 97 cm × 60 cm), the cEE was
equipped with multiple objects wrapped in wire mesh (bird screen) to provide enriched
sensorimotor stimulation (Figure 1A-D). Males (n=38) and females (n=32) were housed
and raised in non-sibling pairs in all three experimental housing conditions. 18
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Experiment 2: (i) Simple-Socially Enriched Environment (ssEE): Rats in ssEE housing
were exposed
to a social housing condition
in
large Polycarbonate cages
(97 cm × 97 cm × 60 cm) for 79 days in groups of 14 with no additional enrichment
provided. (ii) Complex-Socially Enriched Environment (csEE): Rats assigned to csEE
housing were raised in groups of 13 for 81 days in large Polycarbonate cages
(97 cm × 97 cm × 60 cm) equipped with various objects for sensorimotor stimulation. Experiment 3: To accommodate OT antagonist (OT ANT) administration, animals were
split into two complex social housing groups (n = 12/group): (i) the csEE, and (ii)
csEE+OTa where only the latter received an OT antagonist. Animals were housed in large
Polycarbonate cages (97 cm × 97 cm × 60 cm) equipped with various objects for 85 days. Both groups were subjected to blood sampling on days 86-87. EE in the present study on purpose did not include running wheels or other contraptions
designed to specifically encourage physical activity. Aspen wood mixed with shredded
paper bedding was used in all types of environments and changed once per week. Behavioural Assessment
Balance beam task (BBT). The BBT was used to test sensorimotor integration, motor
coordination and balance (86). Animals were placed on one end of an aluminum square bar
(2×2 cm diameter, 130 cm long, and 75 cm high) and their home cage was located at the
other end of the bar. A foam pad was placed underneath to cushion a potential fall. The
animals were required to cross the bar at least three times, and their movements were video
recorded from a lateral view using a digital camcorder (Sony HDR-CX675) at 60 frames/s
with an exposure rate of 1 ms. The latency to traverse the bar, the number of times the hind
19
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . |
feet slipped off the bar and stride length were recorded. Each stride was defined as the
distance between the lift and landing positions of the hind limb. A high-contrast point with
proper vertical and horizontal edge definition was chosen on the back of the hind limb
(Sony Vegas Pro 11, Japan). Stride length (cm) on the beam was measured by the number
of pixels in the tracked frames traced between the lift and landing positions. Also, a suitable
target region for tracking was determined based on a pattern that was clearly visible in
every frame. If the target point did not contain a high-contrast point to track, the preprocess
parameters (e.g. increasing the contrast) were adjusted to make the source image easier to
track. Morris Water Task (MWT). Spatial performance was assessed by a 1-day testing
protocol (10 trials per animal) in the hidden platform version of the MWT (155 cm diameter)
as previously described (41). Briefly, animals were taught to escape from the water (21 ±
1°C) by climbing onto the hidden platform (12 cm diameter). Each trial began with the rat
being placed in one quadrant of the pool around the perimeter of the pool in a pseudo-
random sequence. The maximum duration of each swim trial was 60 s. The location of the
hidden platform remained constant from trial to trial to assess trial-independent spatial
learning. A no-platform probe trial was also performed approximately three hours after the
completion of the single session hidden platform testing as a measure for reference memory. In the probe trial the platform was removed from the pool and the rats were allowed to
swim freely for 30 s. The percentage of time that the animals spent in each quadrant was
recorded. The latency to find the hidden platform, swim speed and error index (swim error
or corridor percent time) were recorded and analyzed by a tracking system (HVS Image
2020, UK). The error index refers to the accuracy of an animal’s swim trajectory within a
20
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 12-cm-wide corridor from the start point to the platform. Any deviation from this corridor
during swimming was scored as an error (87). Open-Field Task (OFT). The OFT was used to assess locomotion and anxiety-related
behaviour (9). The task made of opaque black Plexiglas consisted of a square arena
(135×135 cm) surrounded by walls (33 cm height). Each rat was individually placed at the
centre of the arena and video recorded under dim illumination for 8 min with a camera
mounted above the open field. Video recordings were analysed for path length and path
speed, corner behaviour, stop time (speed of 0.0 m/s lasting at least 1 s), and thigmotaxis
(percent time spent close to the walls) by the computer tracking system. |
Stops and
thigmotaxis were measured as an indicator of emotion level. Path length and speed in the
OFT were considered as indicators of motivation (9). The apparatus was cleaned after each
animal with 70% alcohol. Oxytocin Antagonist Treatment
OT antagonist (OT ANT) was administered to the csEE+OTa group based on earlier
descriptions (4). The non-peptidyl OT antagonist L-366,509 (MedKoo Biosciences, Inc.,
Morrisville, USA) (88, 89) was administered (60 mg/kg) subcutaneously into the scruff of
the neck. Administration occurred every other day (between 11:00 h and 12:00 h noon) for
38–39 days (in total, 38–39 doses/rat) to intermittently inhibit or reduce OT secretion. Administration of L-366,509 started within the first week of the experiment (day 4) and
ended 10-13 h before perfusion. The L-366,509 dosage was chosen based on previous
reports by this team (4) and Kobayashi et al. (90). Physiologic saline solution was injected
21
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . subcutaneously in the csEE group (approximately 37 doses/rat) to control for confounding
stress resulting from repeated OT ANT injections. Plasma Oxytocin Assay
Blood samples (0.5–0.7 mL) were taken the day after terminating EE housing
to measure OT plasma concentration using solid phase radioimmunoassay (RIA) (4). All
samples were collected in the morning hours between 9:00 h and 11:00 h and no
behavioural testing was performed on blood sampling days. Briefly, blood sample tubes
containing aprotinin (500 kallikrein inactivation units/mL blood) were centrifuged at 3000
rpm (1700 g) for 15 min at 4°C. Plasma was stored at –70°C until analysis. Sample
extraction and processing were performed according to the manufacturer’s manual
(Phoenix Pharmaceuticals, Burlingame, CA), and a method previously described by
Kobayashi et al. (90). Intra- and inter-assay variability was 7% and 15%, respectively, as
reported by the manufacturer. BDNF Expression and Morphological Analyses
In Situ Hybridization. Animals (n= 4-5/group) were euthanized with an overdose of
sodium pentobarbital and brains were rapidly removed. All in situ hybridization was
carried out as previously described [(41, 91), with modifications)] and all sections were
run under identical experimental conditions. Briefly, brains were sectioned with a cryostat
(10-15 µm) approximately from −1.60 to −4.52 mm relative to bregma. The fixed, air-dried
sections were incubated overnight with two 33P-labelled 48-mer oligonucleotide probes in
hybridization buffer, and excess and unbound probe was washed off. Brain sections were
22
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . exposed to BioMax MR-1 X-ray films for 25-30 days. Three to four comparable tissue
sections per animal and region were considered for further analysis. Levels of BDNF
mRNA were analyzed and masked by optical densitometry of autoradiographic films using
a computerized image analysis system (MCID, Canada) and ImageJ 1.49p (NIH, USA). BDNF mRNA data in this experiment are represented as percent of cEE group. BDNF Protein Analysis. An enzyme-linked immunosorbent assay (ELISA) was used to
quantify BDNF protein levels (41, 92). Briefly, the tissues were homogenized in 100 × (w/v)
ice-cold homogenization buffer containing a protease-inhibitor cocktail and then diluted to
1:9 in this buffer and then further to a total dilution of 1000×37. ELISA was performed on
the homogenate using the BDNF Emax Immuno Assay Systems (Promega KK, Tokyo,
Japan). The hippocampus (HPC; ~−3.80 mm relative to bregma) was analysed for BDNF
mRNA and protein (n= 3–4 per group) in Experiment 1. Brain Volume and Cortical Thickness Analyses. Procedures for brain volumetry and
cortical thickness were adopted and modified from (93). Brain volume: Briefly, for each
animal, a set of 35-37 cross sections of the whole brain except olfactory bulb and
cerebellum stained with cresyl violet was considered for volumetric analysis. Images of the
stained sections were captured using an AxioCam (Zeiss, Jena, Germany). The most rostral
section measured was located at ~4.70 mm anterior to bregma and the most caudal section
at ~-6.80 mm posterior to bregma. For each section (R.1x), the contours of the bilateral
hemispheres were traced, and their areas were measured using ImageJ 1.47b (NIH, USA). Brain volume averages were calculated by dividing the sum of measures obtained from
each brain by the total number of sections (Lost Brain Area in mm2). The approximate
23
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . volume of the brain (Lost Brain Volume in mm3) was determined by multiplying the total
area in mm2 by both the thickness of each slice (40 mm) and the sampling interval (3):
Lost Brain Volume (mm3) = Area mm2 × 0.04 × 3
Cortical thickness: Three points (medial, lateral and ventrolateral) on 7-8 coronal
sections (AP 3.70, 2.70, 2.20, 1.70, 1.60, 1.20, 0.48, and −0.26 mm) from each brain (n=5-
6/g) were selected based on Paxinos and Watson (94). Therefore, the most rostral section
measured was located at ~3.70 mm anterior to bregma and the most caudal section at ~
−0.26 mm posterior to bregma. For each point, a vector was considered from the tangent
of the outer edge to the inner edge of the cortex. The NDP.view2 viewing software U-
12388-01 (Hamamatsu, Japan) was used to record up to six measurements of cortical
thickness from each coronal section, three from each hemisphere. |
Hippocampal (HPC) Volumetry. Three to six hours after behavioural testing, animals
were euthanized as described previously (95). A series of tissue sections (n= 6–8 per group)
were stained with Cresyl violet. HPC volume in each rat was estimated according to the
Cavalieri method (96) using a set of 9–10 cross-sections of the hippocampal area, starting
from −1.40 mm and terminating at −6.80 mm relative to bregma. In the case of missing or
damaged sections (less than 9 sections per rat) data were calculated as the average area
values from the preceding and following sections. Statistical Analysis
The results were subject to analysis of variance (ANOVA; IBM SPSS Statistics, version
21, SPSS Inc., USA). Repeated measures (R-M), one-way (O-W) ANOVA, and dependent
and independent sample t-tests were conducted as necessary. Also, post-hoc test (Tukey
24
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . HSD) was used to adjust for multiple comparisons. In all cases, means of values were
compared. Behavioural, morphological and molecular data were analysed by separate
ANOVAs with a main between-subject factor of Group. Within-subject factors were
designated for each test as appropriate, for example, Body Weight (days 1-80), Trial (1–
10) and Quadrant (target/other quadrants) in the MWT, Trial (1-3) in the BBT, Number of
Stops and Time Bins for the OFT, and Regions (HPC and cortex). In order to evaluate the
magnitude of the effects of experimental manipulation, effect sizes (η2 for ANOVA) were
calculated. Values of η2=0.14, 0.06 and 0.01 were considered for large, medium and small
effects, respectively. Correlation coefficients were calculated to examine the relationship
between OT levels, BDNF expression, etc. In all statistical analyses, a p-value of <0.05
(two-tailed) was chosen as the significance level, and results are presented as mean ±
standard error. Acknowledgements
The authors thank colleagues at the research ethics board at the Avicenna Institute of
Neuroscience (AINS) for suggestions and comments, and Dr. M. Fakhamati for his
suggestions and assistance with statistical analysis. We gratefully acknowledge the animal
care staff at the AINS vivarium for assistance with animal husbandry. We thank S. Saberi,
K. Nosrat-abadi, G.R. Farimani and F. Nejad-Ghorban for their assistance with behavioural
testing, and N. Schatz for editorial assistance. Funding for this study was provided by a
basic science research program-AINS (#41108-010) to RM, and by Discovery Grant #5628
from Natural Sciences and Engineering Research Council of Canada to GM. 25
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. |
It is made
available under a
CC-BY-NC-ND 4.0 International license . Conflict of Interest
The sponsors had no role in the planning or conducting the study or in the interpretation
of the results. The authors declare no potential conflicts of interest with respect to the
authorship and/or publication of this article. 26
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license
. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 1: (A-D) Male and female rats were raised and housed for 87–91 days in either (B)
Complex Enriched Environment (cEE) which was equipped with multiple different
contraptions (stepped ziggurat, bilateral smooth and high stairs, bilateral ladder, wavy and
smooth slopes, low balance beam) surrounded by wire-mesh covering; (C) Simple
Enriched Environment (sEE); and (D) Standard Environment (SE) units. (E) Both body
and brain weights in males were significantly impacted by prolonged sensorimotor
stimulation. (F) Females raised in the cEE condition did not reveal changes in the body
and brain weights when compared with SE- and sEE-raised rats. (G&H) No significant
correlation was found between body and brain weights in males and females. Asterisks
indicate
significant differences: *p < 0.05, **p < 0.01; One-Way and/or Repeated-
measures ANOVA. Error bars show ± SEM. 27
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 2: (A) Illustration of motion tracks in the balance beam task constructed from four
animals in sEE and cEE groups. Each colored motion track represents one animal. Inset
pictures display takeoff and landing positions in each stride. Note that stride length, the
pixel-based distance between takeoff and landing positions of the left hindlimb, was shorter
and more irregular in sEE than in cEE animals. (B) Males: Latency, the traverse time,
indicated a difference between groups across trials where cEE rats were able to cross the
bar with shorter latency than other groups. |
Average latency (s) in all groups is shown in
bar graphs. (C) cEE animals showed significantly longer stride length on the BBT
compared with SE and sEE animals in trials 2 and 3. Average stride length (cm) is shown
in bar graphs. (D) Females: The cEE condition significantly reduced latency on the task in
all trials. (E) cEE female rats made larger stride lengths than other groups only in trial 2. Average latency (s) and stride length (cm) are shown in bar graphs. Asterisks indicate
significant differences: *p < 0.05, **p < 0.01; One-Way and/or Repeated-measures
ANOVA. Error bars show ± SEM. 28
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 3: (A) A set of 9–10 cross sections of whole hippocampus (AP: −1.40 mm −6.80
mm) that were considered for volumetric analysis along with a coronal view of a right
dorsal hippocampus illustrating the area that was considered for hippocampal volumetrics. (B) HPC size in males was not impacted by the cEE-housing condition. (C) Females raised
in cEE showed larger HPC sizes compared to the sEE and SE groups. (D) cEE male rats
displayed enhanced spatial working and (E) reference memory shown by more focal search
within the target quadrant (T) of the Morris water maze when compared to sEE and SE
groups. (Right panels) Representative probe trial trajectories illustrating search patterns of
one rat from each group and multipath from four rats within the target quadrant. (F) All
groups showed similar rates of corridor errors in trials 1 and 10. (G) cEE females acquired
and retrieved the spatial location of the hidden platform more quickly than sEE and SE
groups. (H) cEE female rats spent more time than other groups searching in the target
quadrant (T) in which the hidden platform had previously been located. (I) Analysis of path
in corridor (12 cm) for the first and last trials showed that cEE rats swam in the corridor in
trial 10 more than other groups. (Right panels) Representative swim paths show corridor
errors in the first and last trials made by one rat from each group during spatial navigation. Grey strips in plots represent required swim corridor to the platform (Yellow squares in the
bar graphs represent individual animals). Asterisks indicate significant differences:
p < 0.05, **p < 0.0; One-Way and/or Repeated-measures ANOVA. Error bars
show ± SEM. 29
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. |
The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 4: (A) Representative autoradiographs (unsharp mask-HK1-RSZII2.60 filter-Green
& Red) of the hippocampal BDNF mRNA expression from all groups in males (top) and
females (bottom) illustrate differences in BDNF mRNA expression between groups. Autoradiographs of BDNF mRNA in the dHPC (CA1, CA2, CA3, and DG) indicate that
only the cEE housing condition enhanced BDNF mRNA expression in CA1, CA2 and DG
in male and female rats. (B&C) Male and female cEE rats showed the highest BDNF
mRNA expression in HPC sub-regions across all groups. (D&E) Both males and females
raised in cEE expressed more BDNF protein in the HPC compared to other groups. (Yellow
squares in the bar graphs represent individual animals). Asterisks indicate significant
differences: *p < 0.05, **p < 0.01; One-way ANOVA. Error bars show ± SEM. 30
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 5: (A&B) Female pups were housed for approximately 81 days in groups of 14 and
13 in two conditions: (i) Simple Socially Enriched Environment (ssEE) and (ii) Complex
Socially Enriched Environment (csEE) within the environments. (C&D) Housing
condition had no effect on body weight, but csEE did increase brain weight. (E) There was
no significant correlation between body and brain weights. Asterisk indicate significant
differences: *p < 0.05, One-Way ANOVA. Error bars show ± SEM. 31
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license
. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. |
The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 6: (A) Brain volumetric analysis in females considered 36-37 cross sections of the
brain except olfactory bulb and cerebellum (n=5-6/g). Brains of the csEE group were larger
than those of the ssEE group on the second to fifteenth rostro-caudal brain sections. (B)
Coronal-sagittal views of the brain illustrate anatomical location of the sections
investigated for cortical thickness and the three cortical points (medial, lateral, ventrolateral)
used for cortical thickness measurements in both hemispheres. csEE rats showed greater
cortical thickness in medial and lateral but ventrolateral portions compared to ssEE rats in
both hemispheres. (C) Schematic representation of the open field task along with path
taken by one representative rat (top) from each group and also multipath from four rats
(bottom). (D&E) csEE rats spend longer time in the corners and thigmotaxis area than ssEE
rats. (F&G) Despite a similar profile of stop time in both groups, csEE rats made fewer
stops than ssEE rats, particularly in the last time bin (the last 2-min). (H&I) Motivational
measures of exploration, such as path length and speed, were influenced by csEE housing. (J-left panel) mPFC BDNF mRNA signal (scale bar = 500 μm) in the ssEE (a) and csEE
(b) groups. BDNF mRNA data (n = 5/g, right panel) are represented as percent of the csEE
group where the ssEE rats displayed less mRNA expression in the mPFC when compared
with their csEE counterparts (~21%). (K) csEE housing raised plasma OT levels (n=13). Blue columns in panel A represent significant differences between groups. Squares in the
bar graphs represent individual animals. Asterisks indicate significant differences:
p < 0.05, **p < 0.01; One-way ANOVA. Error bars show ± SEM. M: medial, L: lateral,
VL: ventrolateral. 32
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license
. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Figure 7: (A&B) A group of csEE females (csEE+OTa, n=12) intermittently received an
OT antagonist (L-366,509). (C) Representative exploration paths of one csEE and
csEE+OTa rat (top) and multipath taken by three rats from each group (bottom) in the open
field task. Note the differences between paths in the thigmotaxis area in both groups. |
(D)
csEE+OTa rats displayed significantly higher number of stops than their csEE counterparts
in the third and fourth time bins of an 8-min test session. (E) csEE+OTa rats spent more
times in the thigmotaxis area when compared with csEE rats. (F) OT antagonist
administration reduced plasma OT concentration
in
the csEE+OTa rats. (G)
Autoradiographs (unsharp mask-HK1-RSZII2.60 filter-Green) represent BDNF mRNA
signals in the mPFC in four rats from each group. (H) csEE+OTa rats that displayed
reduced OT concentration also showed reduced BDNF mRNA expression levels in the
mPFC when compared with untreated csEE-only rats. Note that BDNF mRNA data (n= 5/g)
are represented as percent of the csEE group. (I) csEE+OTa rats showed a significant
correlation between plasma OT levels and mPFC BDNF signal. Red squares in the bar
graphs
represent
individual animals. Asterisks
indicate significant differences:
p < 0.05; One-way ANOVA. Cg1: Cingulate cortex, area 1; PrL: Prelimbic cortex; IL:
Infralimbic cortex. 33
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . References
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. M. R. Rosenzweig, D. Krech, E. L. Bennett, M. C. Diamond, Effects of environmental complexity and training on brain chemistry and anatomy: a replication and extension. Journal of comparative and physiological psychology 55, 429-437 (1962). E. L. Bennett, M. C. Diamond, D. Krech, M. R. Rosenzweig, Chemical and anatomical plasticity of brain. 1964. The Journal of neuropsychiatry and clinical neurosciences 8, 459-470 (1996). J. Faraji, M. Karimi, N. Soltanpour, Z. Rouhzadeh, S. Roudaki, S. A. Hosseini, S. Y. Jafari, A. A. Abdollahi, N. Soltanpour, R. Moeeini, G. A. S. Metz, Intergenerational Sex-Specific Transmission of Maternal Social Experience. Scientific reports 8, 10529 (2018). J. Faraji, M. Karimi, N. Soltanpour, A. Moharrerie, Z. Rouhzadeh, H. Lotfi, S. A. Hosseini, S. Y. Jafari, S. Roudaki, R. Moeeini, G. A. Metz, Oxytocin-mediated social enrichment promotes longer telomeres and novelty seeking. eLife 7, (2018). J. K. McCreary, Z. T. Erickson, G. A. Metz, Environmental enrichment mitigates the impact of ancestral stress on motor skill and corticospinal tract plasticity. Neuroscience letters 632, 181-186 (2016). J. K. McCreary, Z. T. Erickson, Y. Hao, Y. Ilnytskyy, I. Kovalchuk, G. A. Metz, Environmental Intervention as a Therapy for Adverse Programming by Ancestral Stress. Scientific reports 6, 37814 (2016). N. M. Jadavji, B. Kolb, G. A. Metz, Enriched environment improves motor function in intact and unilateral dopamine-depleted rats. Neuroscience 140, 1127- 1138 (2006). M. Knieling, G. A. Metz, I. Antonow-Schlorke, O. W. Witte, Enriched environment promotes efficiency of compensatory movements after cerebral ischemia in rats. |
Neuroscience 163, 759-769 (2009). J. Faraji, N. Soltanpour, S. Y. Jafari, R. Moeeini, S. Pakdel, A. Moharreri, G. A. Metz, Stress inhibits psychomotor performance differently in simple and complex open field environments. Hormones and behavior 65, 66-75 (2014). J. K. McCreary, G. A. S. Metz, Environmental enrichment as an intervention for adverse health outcomes of prenatal stress. Environmental epigenetics 2, dvw013 (2016). A. Stack, N. Carrier, D. Dietz, F. Hollis, J. Sorenson, M. Kabbaj, Sex differences in social interaction in rats: role of the immediate-early gene zif268. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 35, 570-580 (2010). E. Bobrov, J. Wolfe, R. P. Rao, M. Brecht, The representation of social facial touch in rat barrel cortex. Current biology : CB 24, 109-115 (2014). B. Mason, L. G. Rollins, E. Asumadu, C. Cange, N. Walton, S. T. Donaldson, Nesting Environment Provides Sex-Specific Neuroprotection in a Rat Model of Neonatal Hypoxic-Ischemic Injury. Frontiers in behavioral neuroscience 12, 221 (2018). 13. 34
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 14. 15. 16. 17. 18. 19. B. M. Elliott, N. E. Grunberg, Effects of social and physical enrichment on open field activity differ in male and female Sprague-Dawley rats. Behavioural brain research 165, 187-196 (2005). E. J. Lin, E. Choi, X. Liu, A. Martin, M. J. During, Environmental enrichment exerts sex-specific effects on emotionality in C57BL/6J mice. Behavioural brain research 216, 349-357 (2011). G. Kempermann, H. G. Kuhn, F. H. Gage, More hippocampal neurons in adult mice living in an enriched environment. Nature 386, 493-495 (1997). A. Garthe, I. Roeder, G. Kempermann, Mice in an enriched environment learn more flexibly because of adult hippocampal neurogenesis. Hippocampus 26, 261- 271 (2016). K. M. Frick, N. A. Stearns, J. Y. Pan, J. Berger-Sweeney, Effects of environmental enrichment on spatial memory and neurochemistry in middle-aged mice. Learning & memory (Cold Spring Harbor, N.Y.) 10, 187-198 (2003). T. Y. Zhang, C. L. Keown, X. Wen, J. Li, D. A. Vousden, C. Anacker, U. Bhattacharyya, R. Ryan, J. Diorio, N. O'Toole, J. P. Lerch, E. A. Mukamel, M. J. Meaney, Environmental enrichment increases transcriptional and epigenetic differentiation between mouse dorsal and ventral dentate gyrus. Nature communications 9, 298 (2018). J. Jin, S. Maren, Prefrontal-Hippocampal Interactions in Memory and Emotion. Frontiers in systems neuroscience 9, 170 (2015). 20. 21. M. L. Phillips, H. A. Robinson, L. Pozzo-Miller, Ventral hippocampal projections to the medial prefrontal cortex regulate social memory. eLife 8, (2019). D. D. Burman, Hippocampal connectivity with sensorimotor cortex during volitional finger movements: Laterality and relationship to motor learning. |
PloS one 14, e0222064 (2019). E. R. de Kloet, S. F. de Kloet, C. S. de Kloet, A. D. de Kloet, Top-down and bottom-up control of stress-coping. Journal of neuroendocrinology 31, e12675 (2019). 21. M. L. Phillips, H. A. Robinson, L. Pozzo-Miller, Ventral hippocampal projections to the medial prefrontal cortex regulate social memory. eLife 8, (2019). D. D. Burman, Hippocampal connectivity with sensorimotor cortex during volitional finger movements: Laterality and relationship to motor learning. PloS one 14, e0222064 (2019). E. R. de Kloet, S. F. de Kloet, C. S. de Kloet, A. D. de Kloet, Top-down and bottom-up control of stress-coping. Journal of neuroendocrinology 31, e12675 (2019). 22. 24. M. Kodama, T. Ono, F. Yamashita, H. Ebata, M. Liu, S. Kasuga, J. Ushiba, Structural Gray Matter Changes in the Hippocampus and the Primary Motor Cortex on An-Hour-to-One- Day Scale Can Predict Arm-Reaching Performance Improvement. Frontiers in human neuroscience 12, 209 (2018). S. M. Ohline, W. C. Abraham, Environmental enrichment effects on synaptic and cellular physiology of hippocampal neurons. Neuropharmacology 145, 3-12 (2019). P. S. Churchland, P. Winkielman, Modulating social behavior with oxytocin: how does it work? What does it mean? Hormones and behavior 61, 392-399 (2012). Y. T. Lin, C. C. Chen, C. C. Huang, K. Nishimori, K. S. Hsu, Oxytocin stimulates hippocampal neurogenesis via oxytocin receptor expressed in CA3 pyramidal neurons. Nature communications 8, 537 (2017). Y. T. Lin, K. S. Hsu, Oxytocin receptor signaling in the hippocampus: Role in regulating neuronal excitability, network oscillatory activity, synaptic plasticity and social memory. Progress in neurobiology 171, 1-14 (2018). 28. 27. 35
25. 26.
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. S. Neal, M. Kent, M. Bardi, K. G. Lambert, Enriched Environment Exposure Enhances Social Interactions and Oxytocin Responsiveness in Male Long-Evans Rats. Frontiers in behavioral neuroscience 12, 198 (2018). F. C. Zucchi, Y. Yao, Y. Ilnytskyy, J. C. Robbins, N. Soltanpour, I. Kovalchuk, O. Kovalchuk, G. A. Metz, Lifetime stress cumulatively programs brain transcriptome and impedes stroke recovery: benefit of sensory stimulation. PloS one 9, e92130 (2014). J. J. Zheng, S. J. Li, X. D. Zhang, W. Y. Miao, D. Zhang, H. Yao, X. Yu, Oxytocin mediates early experience-dependent cross-modal plasticity in the sensory cortices. Nature neuroscience 17, 391-399 (2014). J. Rilling, D. Gutman, T. Zeh, G. Pagnoni, G. Berns, C. Kilts, A neural basis for social cooperation. Neuron 35, 395-405 (2002). J. A. Barraza, P. J. Zak, Empathy toward strangers triggers oxytocin release and subsequent generosity. |
Annals of the New York Academy of Sciences 1167, 182- 189 (2009). P. A. Adlard, C. W. Cotman, Voluntary exercise protects against stress-induced decreases in brain-derived neurotrophic factor protein expression. Neuroscience 124, 985-992 (2004). H. van Praag, T. Shubert, C. Zhao, F. H. Gage, Exercise enhances learning and hippocampal neurogenesis in aged mice. The Journal of neuroscience : the official journal of the Society for Neuroscience 25, 8680-8685 (2005). C. Rossi, A. Angelucci, L. Costantin, C. Braschi, M. Mazzantini, F. Babbini, M. E. Fabbri, L. Tessarollo, L. Maffei, N. Berardi, M. Caleo, Brain-derived neurotrophic factor (BDNF) is required for the enhancement of hippocampal neurogenesis following environmental enrichment. The European journal of neuroscience 24, 1850-1856 (2006). B. E. Dong, H. Chen, K. Sakata, BDNF deficiency and enriched environment treatment affect neurotransmitter gene expression differently across ages. Journal of neurochemistry 154, 41-55 (2020). P. Kowiański, G. Lietzau, E. Czuba, M. Waśkow, A. Steliga, J. Moryś, BDNF: A Key Factor with Multipotent Impact on Brain Signaling and Synaptic Plasticity. Cellular and molecular neurobiology 38, 579-593 (2018). B. H. Harvey, W. Regenass, W. Dreyer, M. Möller, Social isolation rearing- induced anxiety and response to agomelatine in male and female rats: Role of corticosterone, oxytocin, and vasopressin. Journal of psychopharmacology (Oxford, England) 33, 640-646 (2019). R. T. Han, Y. B. Kim, E. H. Park, J. Y. Kim, C. Ryu, H. Y. Kim, J. Lee, K. Pahk, C. Shanyu, H. Kim, S. K. Back, H. J. Kim, Y. I. Kim, H. S. Na, Long-Term Isolation Elicits Depression and Anxiety-Related Behaviors by Reducing Oxytocin-Induced GABAergic Transmission in Central Amygdala. Frontiers in molecular neuroscience 11, 246 (2018). J. Faraji, N. Soltanpour, H. Lotfi, R. Moeeini, A. R. Moharreri, S. Roudaki, S. A. Hosseini, D. M. Olson, A. A. Abdollahi, N. Soltanpour, M. H. Mohajerani, G. A. S. Metz, Lack of Social Support Raises Stress Vulnerability in Rats with a History of Ancestral Stress. Scientific reports 7, 5277 (2017). 41. 36
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . T. A. Kosten, D. A. Karanian, J. Yeh, C. N. Haile, J. J. Kim, P. Kehoe, B. A. Bahr, Memory impairments and hippocampal modifications in adult rats with neonatal isolation stress experience. Neurobiology of learning and memory 88, 167-176 (2007). T. A. Kosten, H. J. Lee, J. J. Kim, Neonatal handling alters learning in adult male and female rats in a task-specific manner. Brain research 1154, 144-153 (2007). A. Vogel Ciernia, B. I. Laufer, K. W. Dunaway, C. E. Mordaunt, R. L. Coulson, T. S. Totah, D. S. Stolzenberg, J. C. Frahm, A. Singh-Taylor, T. Z. Baram, J. M. LaSalle, D. H. Yasui, Experience-dependent neuroplasticity of the developing hypothalamus: integrative epigenomic approaches. |
Epigenetics 13, 318-330 (2018). Y. H. Hsiao, H. C. Hung, S. H. Chen, P. W. Gean, Social interaction rescues memory deficit in an animal model of Alzheimer's disease by increasing BDNF- dependent hippocampal neurogenesis. The Journal of neuroscience : the official journal of the Society for Neuroscience 34, 16207-16219 (2014). D. S. Rivera, C. B. Lindsay, C. A. Oliva, J. F. Codocedo, F. Bozinovic, N. C. Inestrosa, Effects of long-lasting social isolation and re-socialization on cognitive performance and brain activity: a longitudinal study in Octodon degus. Scientific reports 10, 18315 (2020). J. Liu, F. Meng, J. Dai, M. Wu, W. Wang, C. Liu, D. Zhao, H. Wang, J. Zhang, C. Li, The BDNF-FoxO1 Axis in the medial prefrontal cortex modulates depressive- like behaviors induced by chronic unpredictable stress in postpartum female mice. Molecular brain 13, 91 (2020). L. E. Rosas-Vidal, V. Lozada-Miranda, Y. Cantres-Rosario, A. Vega-Medina, L. Melendez, G. J. Quirk, Alteration of BDNF in the medial prefrontal cortex and the ventral hippocampus impairs extinction of avoidance. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 43, 2636-2644 (2018). T. M. Jay, M. P. Witter, Distribution of hippocampal CA1 and subicular efferents in the prefrontal cortex of the rat studied by means of anterograde transport of Phaseolus vulgaris-leucoagglutinin. The Journal of comparative neurology 313, 574-586 (1991). A. M. Thierry, Y. Gioanni, E. Degenetais, J. Glowinski, Hippocampo-prefrontal cortex pathway: anatomical and electrophysiological characteristics. Hippocampus 10, 411-419 (2000). C. Varela, S. Kumar, J. Y. Yang, M. A. Wilson, Anatomical substrates for direct interactions between hippocampus, medial prefrontal cortex, and the thalamic nucleus reuniens. Brain structure & function 219, 911-929 (2014). J. F. Disterhoft, M. Segal, Neuron activity in rat hippocampus and motor cortex during discrimination reversal. Brain research bulletin 3, 583-588 (1978). 53. M. Delcour, M. Russier, F. Castets, N. Turle-Lorenzo, M. H. Canu, F. Cayetanot, M. F. Barbe, J. O. Coq, Early movement restriction leads to maladaptive plasticity in the sensorimotor cortex and to movement disorders. Scientific reports 8, 16328 (2018). 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 37
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 54. K. Rosenkranz, J. C. Rothwell, The effect of sensory input and attention on the sensorimotor organization of the hand area of the human motor cortex. The Journal of physiology 561, 307-320 (2004). 55. M. Leger, E. Paizanis, K. Dzahini, A. Quiedeville, V. Bouet, J. C. Cassel, T. Freret, P. Schumann-Bard, M. Boulouard, Environmental Enrichment Duration Differentially Affects Behavior and Neuroplasticity in Adult Mice. |
Cerebral cortex (New York, N.Y. : 1991) 25, 4048-4061 (2015). H. van Praag, G. Kempermann, F. H. Gage, Neural consequences of environmental enrichment. Nature reviews. Neuroscience 1, 191-198 (2000). X. Li, S. Li, W. Zheng, J. Pan, K. Huang, R. Chen, T. Pan, G. Liao, Z. Chen, D. Zhou, W. Shen, W. Zhou, Y. Liu, Environmental enrichment and abstinence attenuate ketamine-induced cardiac and renal toxicity. Scientific reports 5, 11611 (2015). 55. M. Leger, E. Paizanis, K. Dzahini, A. Quiedeville, V. Bouet, J. C. Cassel, T. Freret, P. Schumann-Bard, M. Boulouard, Environmental Enrichment Duration Differentially Affects Behavior and Neuroplasticity in Adult Mice. Cerebral cortex (New York, N.Y. : 1991) 25, 4048-4061 (2015). H. van Praag, G. Kempermann, F. H. Gage, Neural consequences of environmental enrichment. Nature reviews. Neuroscience 1, 191-198 (2000). X. Li, S. Li, W. Zheng, J. Pan, K. Huang, R. Chen, T. Pan, G. Liao, Z. Chen, D. Zhou, W. Shen, W. Zhou, Y. Liu, Environmental enrichment and abstinence attenuate ketamine-induced cardiac and renal toxicity. Scientific reports 5, 11611 (2015). 56. 58. M. Huttenrauch, G. Salinas, O. Wirths, Effects of Long-Term Environmental Enrichment on Anxiety, Memory, Hippocampal Plasticity and Overall Brain Gene Expression in C57BL6 Mice. Frontiers in molecular neuroscience 9, 62 (2016). T. A. Forbes, E. Z. Goldstein, J. L. Dupree, B. Jablonska, J. Scafidi, K. L. Adams, Y. Imamura, K. Hashimoto-Torii, V. Gallo, Environmental enrichment ameliorates perinatal brain injury and promotes functional white matter recovery. Nature communications 11, 964 (2020). R. P. Fares, A. Belmeguenai, P. E. Sanchez, H. Y. Kouchi, J. Bodennec, A. Morales, B. Georges, C. Bonnet, S. Bouvard, R. S. Sloviter, L. Bezin, Standardized environmental enrichment supports enhanced brain plasticity in healthy rats and prevents cognitive impairment in epileptic rats. PloS one 8, e53888 (2013). S. H. Richter, P. Gass, J. Fuss, Resting Is Rusting: A Critical View on Rodent Wheel-Running Behavior. The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry 20, 313-325 (2014). S. F. Sleiman, J. Henry, R. Al-Haddad, L. El Hayek, E. Abou Haidar, T. Stringer, D. Ulja, S. S. Karuppagounder, E. B. Holson, R. R. Ratan, I. Ninan, M. V. Chao, Exercise promotes the expression of brain derived neurotrophic factor (BDNF) through the action of the ketone body beta-hydroxybutyrate. eLife 5, (2016). J. Altman, K. Sudarshan, Postnatal development of locomotion in the laboratory rat. Animal behaviour 23, 896-920 (1975). A. M. Shriner, F. R. Drever, G. A. Metz, The development of skilled walking in the rat. Behavioural brain research 205, 426-435 (2009). B. Jurek, I. D. Neumann, The Oxytocin Receptor: From Intracellular Signaling to Behavior. Physiological reviews 98, 1805-1908 (2018). S. Stock, K. Uvnas-Moberg, Increased plasma levels of oxytocin in response to afferent electrical stimulation of the sciatic and vagal nerves and in response to touch and pinch in anaesthetized rats. |
Acta physiologica Scandinavica 132, 29-34 (1988). A. M. Anacker, A. K. Beery, Life in groups: the roles of oxytocin in mammalian sociality. Frontiers in behavioral neuroscience 7, 185 (2013). H. S. Knobloch, V. Grinevich, Evolution of oxytocin pathways in the brain of vertebrates. Frontiers in behavioral neuroscience 8, 31 (2014). 59. 60. 61. 62. 63. 64. 65. 66. 67. 68. 38
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 69. 70. 71. 72. 73. 74. 75. 76. 77. 78. 79. C. J. Smith, M. L. Poehlmann, S. Li, A. M. Ratnaseelan, R. Bredewold, A. H. Veenema, Age and sex differences in oxytocin and vasopressin V1a receptor binding densities in the rat brain: focus on the social decision-making network. Brain structure & function 222, 981-1006 (2017). S. Sabihi, N. E. Durosko, S. M. Dong, B. Leuner, Oxytocin in the prelimbic medial prefrontal cortex reduces anxiety-like behavior in female and male rats. Psychoneuroendocrinology 45, 31-42 (2014). S. Sabihi, S. M. Dong, N. E. Durosko, B. Leuner, Oxytocin in the medial prefrontal cortex regulates maternal care, maternal aggression and anxiety during the postpartum period. Frontiers in behavioral neuroscience 8, 258 (2014). S. Bernaerts, J. Prinsen, E. Berra, G. Bosmans, J. Steyaert, K. Alaerts, Long-term oxytocin administration enhances the experience of attachment. Psychoneuroendocrinology 78, 1-9 (2017). V. Grinevich, R. Stoop, Interplay between Oxytocin and Sensory Systems in the Orchestration of Socio-Emotional Behaviors. Neuron 99, 887-904 (2018). K. Uvnas-Moberg, L. Handlin, M. Petersson, Self-soothing behaviors with particular reference to oxytocin release induced by non-noxious sensory stimulation. Frontiers in psychology 5, 1529 (2014). S. Yao, W. Zhao, Y. Geng, Y. Chen, Z. Zhao, X. Ma, L. Xu, B. Becker, K. M. Kendrick, Oxytocin Facilitates Approach Behavior to Positive Social Stimuli via Decreasing Anterior Insula Activity. The international journal of neuropsychopharmacology 21, 918-925 (2018). L. W. Ayers, G. Missig, J. Schulkin, J. B. Rosen, Oxytocin reduces background anxiety in a fear-potentiated startle paradigm: peripheral vs central administration. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 36, 2488-2497 (2011). S. Dieni, T. Matsumoto, M. Dekkers, S. Rauskolb, M. S. Ionescu, R. Deogracias, E. D. Gundelfinger, M. Kojima, S. Nestel, M. Frotscher, Y. A. Barde, BDNF and its pro-peptide are stored in presynaptic dense core vesicles in brain neurons. The Journal of cell biology 196, 775-788 (2012). H. E. Scharfman, N. J. MacLusky, Differential regulation of BDNF, synaptic plasticity and sprouting in the hippocampal mossy fiber pathway of male and female rats. |
Neuropharmacology 76 Pt C, 696-708 (2014). T. Havranek, M. Zatkova, Z. Lestanova, Z. Bacova, B. Mravec, J. Hodosy, V. Strbak, J. Bakos, Intracerebroventricular oxytocin administration in rats enhances object recognition and increases expression of neurotrophins, microtubule- associated protein 2, and synapsin I. Journal of neuroscience research 93, 893- 901 (2015). 80. M. Mansouri, H. Pouretemad, M. Roghani, G. Wegener, M. Ardalan, Autistic-like behaviours and associated brain structural plasticity are modulated by oxytocin in maternally separated rats. Behavioural brain research 393, 112756 (2020). S. Momenabadi, A. A. Vafaei, A. R. Bandegi, M. Zahedi-Khorasani, Z. Mazaheri, A. Vakili, Oxytocin Reduces Brain Injury and Maintains Blood-Brain Barrier Integrity After Ischemic Stroke in Mice. Neuromolecular medicine 22, 557-571 (2020). 81. 39
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 82. K. R. Maynard, J. W. Hobbs, B. N. Phan, A. Gupta, S. Rajpurohit, C. Williams, A. Rajpurohit, J. H. Shin, A. E. Jaffe, K. Martinowich, BDNF-TrkB signaling in oxytocin neurons contributes to maternal behavior. eLife 7, (2018). Y. Ji, P. T. Pang, L. Feng, B. Lu, Cyclic AMP controls BDNF-induced TrkB phosphorylation and dendritic spine formation in mature hippocampal neurons. Nature neuroscience 8, 164-172 (2005). Y. Luo, S. Kuang, H. Li, D. Ran, J. Yang, cAMP/PKA-CREB-BDNF signaling pathway in hippocampus mediates cyclooxygenase 2-induced learning/memory deficits of rats subjected to chronic unpredictable mild stress. Oncotarget 8, 35558-35572 (2017). F. Mauvais-Jarvis, N. Bairey Merz, P. J. Barnes, R. D. Brinton, J. J. Carrero, D. L. DeMeo, G. J. De Vries, C. N. Epperson, R. Govindan, S. L. Klein, A. Lonardo, P. M. Maki, L. D. McCullough, V. Regitz-Zagrosek, J. G. Regensteiner, J. B. Rubin, K. Sandberg, A. Suzuki, Sex and gender: modifiers of health, disease, and medicine. Lancet (London, England) 396, 565-582 (2020). J. Faraji, M. Karimi, C. Lawrence, M. H. Mohajerani, G. A. S. Metz, Non- diagnostic symptoms in a mouse model of autism in relation to neuroanatomy: the BTBR strain reinvestigated. Translational psychiatry 8, 234 (2018). I. Q. Whishaw, A comparison of rats and mice in a swimming pool place task and matching to place task: some surprising differences. Physiology & behavior 58, 687-693 (1995). B. E. Evans, J. L. Leighton, K. E. Rittle, K. F. Gilbert, G. F. Lundell, N. P. Gould, D. W. Hobbs, R. M. DiPardo, D. F. Veber, D. J. Pettibone, et al., Orally active, nonpeptide oxytocin antagonists. Journal of medicinal chemistry 35, 3919-3927 (1992). D. J. Pettibone, B. V. Clineschmidt, M. T. Kishel, E. V. Lis, D. R. Reiss, C. J. Woyden, B. E. Evans, R. M. Freidinger, D. F. Veber, M. J. Cook, et al., Identification of an orally active, nonpeptidyl oxytocin antagonist. |
The Journal of pharmacology and experimental therapeutics 264, 308-314 (1993). 90. M. Kobayashi, M. Akahane, K. Minami, M. Moro, Y. Ajisawa, Y. Inoue, T.
83. 84. 85. 86. 87. 88. 89. Kawarabayashi, Role of oxytocin in the initiation of term and preterm labor in rats: changes in oxytocin receptor density and plasma oxytocin concentration and the effect of an oxytocin antagonist, L-366,509. American journal of obstetrics and gynecology 180, 621-627 (1999). J. P. Jacobsen, A. Mork, The effect of escitalopram, desipramine, electroconvulsive seizures and lithium on brain-derived neurotrophic factor mRNA and protein expression in the rat brain and the correlation to 5-HT and 5- HIAA levels. Brain research 1024, 183-192 (2004). J. P. Jacobsen, A. Mork, Chronic corticosterone decreases brain-derived neurotrophic factor (BDNF) mRNA and protein in the hippocampus, but not in the frontal cortex, of the rat. Brain research 1110, 221-225 (2006). J. Faraji, N. Soltanpour, M. Ambeskovic, F. C. R. Zucchi, P. Beaumier, I. Kovalchuk, G. A. S. Metz, Evidence for Ancestral Programming of Resilience in a Two-Hit Stress Model. Frontiers in behavioral neuroscience 11, 89 (2017). 94. W. C. Paxinos G., The Rat Brain in Stereotaxic Coordinates. San Diego, CA:
91. 92. 93. Academic Press. (Academic Press. , San Diego, CA, 1997). 40
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.05.26.445890
;
this version posted May 27, 2021. The copyright holder for this preprint (which
was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . 95. 96. J. Faraji, M. Ejaredar, G. A. Metz, R. J. Sutherland, Chronic stress prior to hippocampal stroke enhances post-stroke spatial deficits in the ziggurat task. Neurobiology of learning and memory 95, 335-345 (2011). A. M. Barr, C. H. Wu, C. Wong, C. Hercher, E. Topfer, H. N. Boyda, R. M. Procyshyn, W. G. Honer, C. L. Beasley, Effects of chronic exercise and treatment with the antipsychotic drug olanzapine on hippocampal volume in adult female rats. Neuroscience 255, 147-157 (2013). 41 |
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Metagenomic identification of viral sequences in laboratory reagents
1.1 Author names
Ashleigh F. Porter1, Joanna Cobbin2, Cixiu Li3, John-Sebastian Eden2,4, Edward C. Holmes2*
1.2 Affiliations
1
The Peter Doherty Institute of Immunity and Infection, Department of Microbiology
and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia. 2
Marie Bashir Institute for Infectious Diseases and Biosecurity, School of Life and
Environmental Sciences and School of Medical Sciences, The University of Sydney,
Sydney, NSW 2006, Australia. 3
Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in
Universities of Shandong, Shandong First Medical University & Shandong Academy of
Medical Sciences, Taian 271000, China. 4
Centre for Virus Research, Westmead Institute for Medical Research, Westmead,
Australia. 1.3 Corresponding author
Edward C. Holmes, [email protected]
1.4 Keywords
Reagent contamination, virology, metatranscriptomics, Circoviridae, Totiviridae,
Tombusviridae, Lentiviridae
1.5 Repositories
The viral genome sequence data generated in this study has been deposited in the NCBI
database under accession numbers MZ824225-MZ824237. Sequence reads are available at
the public Sequence Read Archive (SRA) database with accession SRX6803604 and under
the BioProject accession PRJNA735051 reference numbers SRR14737466-71 and
BioSample numbers SAMN20355437-40. 29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 2. Abstract
Metagenomic next-generation sequencing has transformed the discovery and diagnosis of
infectious disease, with the power to characterize the complete ‘infectome’ (bacteria, viruses,
fungi, parasites) of an individual host organism. However, the identification of novel
pathogens has been complicated by widespread microbial contamination in commonly used
laboratory reagents. Using total RNA sequencing (“metatranscriptomics”) we documented
the presence of contaminant viral sequences in multiple libraries of ‘blank’ negative control
sequencing libraries that comprise a sterile water and reagent mix. Accordingly, we identified
14 viral sequences in 7 negative control sequencing libraries. As in previous studies, several
circular replication-associated protein encoding (CRESS) DNA virus-like sequences were
recovered in the blank libraries, as well as contaminating sequences from the RNA virus
families Totiviridae, Tombusviridae and Lentiviridae. |
These data suggest that the
contamination of common laboratory reagents is likely widespread and can comprise a wide
variety of viruses. 3. Data summary
The authors confirm all supporting data, code and protocols have been provided within the
article or through supplementary data files. 4. Introduction
Culture-independent methods, particularly metagenomic next-generation sequencing
(mNGS), have revolutionised pathogen discovery, streamlined pathways of clinical diagnosis,
and have enhanced our ability to track infectious disease outbreaks [1], including the current
COVID-19 pandemic [2, 3]. These methods can reveal the complete profile of pathogenic
and commensal microorganisms within a host, comprising viruses, bacteria, fungi and
eukaryotic parasites. As mNGS, particularly total RNA sequencing (i.e. metatranscriptomics),
enables the identification of diverse and divergent viral sequences, it has been widely utilised
for virus discovery [4-8]. Although the data generated by mNGS is bountiful and cost-effective, it comes with several
inherent limitations, central of which is the possibility of reagent contamination [9]. Indeed,
the contamination of mNGS data can be problematic when identifying microbes in the
context of disease association and creates issues when attempting to identify the true host of a
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. novel microbe. The experimental preparation of samples for sequencing necessarily involves
treatment with a variety of reagents, many of which have been shown to carry contaminating
nucleic acids, including viral sequences [10-15]. Previous work has illuminated the extent of
viral contamination in commonly used laboratory components, particularly those with small
single-stranded (ss) DNA genomes [9, 14, 16-18]. Accordingly, there is a clear need for
appropriate controls when characterizing novel viruses from metagenomic data. For example,
metagenomic analysis of human plasma samples revealed the presence of sequences of
Kadipiro virus, a double-stranded positive-sense RNA virus [19, 20]. However, the presence
of these sequences was not confirmed via PCR, suggesting that they were contaminant in
origin [19, 20]. An additional complication is that reagent-associated viral sequences are
often not shared nor widespread across samples, only appearing intermittently [9]. Although mNGS has identified many novel viruses, diverse species of circular replication-
associated protein encoding (CRESS) ssDNA viruses have been particularly prominent [21-
25]. However, as noted above, ssDNA viruses, particularly CRESS viruses and their relatives
including circoviruses, are common contaminants of reagents, leading to incorrect inferences
of host associations [9, 26]. |
As well as DNA viruses, a variety of other microbial sequences
are present in laboratory reagents, including bacteria, RNA viruses, and eukaryotic parasites
[9, 27-30]. To further explore the diversity of contaminant sequences in laboratory components,
particularly those derived from viruses, we used metatranscriptomics to investigate seven
libraries of blank RNA sequencing samples representing sterile water extractions and library
preparation reagents. 5. Methods
When generating total RNA sequencing libraries, we regularly utilise negative or ‘blank’
samples as experimental controls to assess the extent of reagent contamination. These
controls are derived from extractions of the sterile water used at the elution step, and
importantly, are expected to contain no nucleic acid material. In theory, these negative
controls should generate no sequencing reads, however they can capture contamination
during the DNA/RNA extraction or library preparation steps. 93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Herein, we analysed negative control sequencing libraries under different experimental
conditions to identify likely contaminant sequences (Table 1). Total RNA was extracted
using either the RNeasy Plus Universal Kit (Qiagen), RNeasy Plus Mini Kit (Qiagen) or the
Total RNA purification Kit (Norgen BioTek Corp), as described in Table 1. RNA libraries
were prepared with the Trio RNA-seq + UDI Library Preparation Kit (NuGEN) or the
SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Clontech) and
sequenced on the MiSeq, NextSeq or NovaSeq Illumina platforms, producing between
0.63Gb and 8.7Gb of data per library. Analysis of virus-like sequences in laboratory reagents
Each sequencing library underwent trimming and de novo assembly of reads, completed
using either the Trinity software with default settings [31] or MEGAHIT [32]. Sequence
similarity searches using Diamond BLASTX were performed on the de novo assembled
contigs against the GenBank non-redundant (nr) database [33, 34]. Specifically, we used a
combination of e-value, hit length, and percentage similarity to determine the potential of a
contig to be a viral sequence. The abundance of reagent-associated reads was calculated by
comparing the number of contig reads to the total number of library reads (via mapping
trimmed reads back to the contigs) as performed in previous studies [5, 8]. After initial identification, all potential contaminant sequences were subjected to
phylogenetic analysis. To ensure high quality amino acid sequence alignments, only
conserved sequence contigs that were >800 bp (>200 amino acids) in length were used in
downstream analysis. |
Reference proteins including the highly conserved replicase, DNA
polymerase and RNA-dependent RNA polymerase (RdRp) proteins were downloaded from
the NCBI RefSeq database (Table 2). Contig and reference proteins were aligned using the
L-INS-I algorithm in MAFFT v7 [35], with ambiguously aligned regions removed using
Gblocks [36] which resulted in final sequence alignments of between 150-1000 amino acids
in length (Table 2). Phylogenetic trees of all alignments were then estimated using the
maximum likelihood method in IQ-TREE [37], using the model testing option and bootstrap
resampling with 500 replications. 123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 6. Results
In total, we identified 14 reagent-associated viral sequences in the negative (blank) control
samples tested, including seven CRESS-like viral sequences, four novel Tombusviridae-like
viral sequences, and single Lentivirus-like and Totiviridae-like viral sequences. The abundance of reads in each library was calculated to compare the percentage of reads
associated with viruses (Figure 1). This revealed that the virus-associated contigs identified
were predominantly CRESS-like (Figure 1b-e). The L5 library only contained one virus-
associated contig, associated with Escherichia coli phage PhiX 174 DNA: this was
intentionally added into the sequencing run to add complexity and improve signal in the
library. Both the L4 and L6 libraries did not contain long (>800bp) virus-associated contigs. Novel reagent-associated virus-like sequences were identified in four of the seven libraries
(Table 3). Seven novel circo-like viruses (termed Reagent-associated CRESS-like virus 1-7),
four novel tombusvirus-like viruses (termed Reagent-associated tombus-like virus 1-4), and
one totivirus-like and lentivirus-like sequence (termed Reagent-associated toti-like virus and
Reagent-associated lenti-like virus, respectively) were identified in the L1, L2 and L3
libraries. The contigs ranged from 828-3878 bp in length and comprised 0.004-9.66% of
reads in their associated libraries. Because of the extensive genetic diversity within the Circoviridae we inferred two separate
sequence alignments and hence two phylogenetic trees, representing the CRESS viruses and
circoviruses taken independently, although both were based on the Rep protein sequence
(Figure 3). All seven of the novel reagent-associated circovirus-like sequences exhibited
greater sequence similarity to the CRESS viruses, and therefore were included in the CRESS
virus phylogeny and termed reagent-associated CRESS-like viruses 1-7. |
These viruses
occupied diverse locations across the phylogeny, although they were closely related to some
previously identified reagent-associated viruses: Avon-Heathcote estuary associated circular
viruses, Circoviridae sp. subtypes, Dromedary stool-associated circular virus subtypes, and
Sandworm circovirus [5, 9] (Figure 2). It is notable that the CRESS viruses analysed derive
from a variety of environments, and there is no clear pattern according to the host species of
sample origin, which is anticipated in the case of contaminant sequences. The seven novel
CRESS-like viruses identified also varied in abundance in the L1 and L3 libraries (0.01-
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 9.66%). In contrast, a phylogenetic analysis of the Rep protein of other members of
Circoviridae (Table 2), containing what we hypothesise are bona fide viruses, reveals a
pattern of host-based clustering (Figure 3). In particular, this phylogeny was characterised by
two distinct clades of circoviruses: circoviruses, associated with vertebrate hosts, and
cycloviruses associated with invertebrates. Aside from ssDNA viruses, we identified an additional seven novel reagent-associated viral
sequences in the blank control libraries. The first of these was a novel lentivirus-like
sequence that we then used in an alignment of the retroviral Pol protein (Table 2). A
phylogenetic tree was inferred from the alignment and the novel reagent-associated lenti-like
virus was shown to cluster closely to Equine infectious anaemia viruses (EIAV), although
occupying a relatively long branch within this clade (Figure 4). Similarly, we identified four novel tombus-like sequences in the blank control samples: these
were termed Reagent-associated tombus-like virus 1-4. A sequence alignment of the RNA-
dependent RNA polymerase (RdRp) protein was used to infer a phylogenetic tree of these
tombusvirus-like sequences that are commonly associated with plants (Table 2). Three of the
novel tombus-like viruses cluster together in the same divergent clade that falls basal to
majority of the tombus-like viruses (Figure 5). Only two tombus-like virus sequences fall in
more divergent positions – Wenzhou tombus-like virus 11 and Sclerotinia sclerotiorum
umbra-like virus 1. As these were both identified in metatranscriptomic studies [8, 39] it is
possible that they reflect reagent contamination, although Sclerotinia sclerotiorum umbra-like
virus 1 was found in two samples of Sclerotinia sclerotiorum (a fungus) compatible with its
status as a true mycovirus [39, 40]. Additionally, Plasmopara viticola lesion associated
tombus-like virus 2, which is also suggested to be a mycovirus, falls nearby (Figure 5). |
This
virus sequence falls basal to a clade within the broader tombusvirus tree that includes a
variety of plant viruses, including Groundnut rosette virus, Carrot mottle virus and Tobacco
mottle virus. Reagent-associated tombus-like virus 3 was identified in blank library L3 at a
relatively high abundance (1% of total reads), although it had a shorter (1574 bp) and likely
incomplete genome compared to most tombusviruses (~4-5 kb). Finally, the remaining novel sequence was related to the totiviruses, a family of double-strand
RNA viruses commonly associated with fungi. The novel totivirus-like sequence was termed
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Reagent-associated toti-like virus. It was used in an alignment of the RdRp protein (Table 2),
from which a phylogenetic tree was estimated (Figure 6). This revealed that the sequence
appears to be related to Scheffersomyces segobiensis virus (83% amino acid identity)
associated with the fungus Scheffersomyces segobiensis. 7. Discussion
Viral sequences, particularly those with single-stranded DNA genomes, have previously been
associated with common laboratory components [9], and these contaminant viral sequences
have sometimes led to erroneous disease associations [14, 17, 18, 41]. Herein, using a series
of blank controls comprising sterile water and commonly used laboratory reagents, we
identified a diverse range of viral sequences. Few laboratory reagents appear to be entirely free from contamination, particularly by
ssDNA viruses, predominantly circoviruses [5, 9, 26]. Indeed, approximately half of the viral
sequences identified here were CRESS-like members of the Circoviridae. Unfortunately,
high levels of sequence diversity prevented us from obtaining a meaningful alignment of the
Rep protein for the novel CRESS-like virus sequences obtained here and known
Circoviridae. Accordingly, we divided the family into sub-groups, termed here as “host-
associated circoviruses” (Figure 3) and “CRESS and CRESS-like viruses” and performed
phylogenetic analyses on each (Figure 2). Notably, in the “host-associated circovirus”
phylogeny viruses clustered based on broad host species of origin. In contrast, within the
“CRESS and CRESS-like” phylogeny, clades could not be defined based on specific hosts or
environments, and while many samples were originally derived from marine- or faeces-
associated environments, these sequences did not cluster together. Interestingly, however, one
of viruses identified in this study, reagent-associated CRESS-like virus 4, is most closely
related to Avon-Heathcote Estuary associated circular virus 3, previously identified as a
reagent-associated virus [42]. |
In addition, the seven novel CRESS-like sequences identified
here were related to previously identified reagent-associated viruses, including those
identified by Asplund et al. (highlighted in blue, Figure 2) [9], as well as Sandworm
circovirus similarly proposed to be a reagent contaminant [43]. This strongly suggests that all
these sequences are likely associated with laboratory reagents. 221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. It is therefore clear that CRESS-like viruses are common experimental reagent contaminants,
with widespread reagent-associated sequences dispersed throughout the CRESS phylogeny. This, along with the range of CRESS viruses of undetermined host origin, create major
difficulties in determining the origin of novel CRESS viruses. Although there have been
many new members of Circoviridae characterized in recent years, particularly novel
cycloviruses [5, 44, 45], we suggest that current and future characterizations of novel
circovirus- and CRESS-like genomes should be completed cautiously with additional
confirmation steps. We also identified several tombusvirus-like sequences in this study, as well as a totivirus- and
lentivirus-like sequence. The Tombusviridae are a family of single-strand positive-sense
RNA viruses are usually associated with mosaic diseases in plants. We identified four novel
tombusvirus-like sequences associated with laboratory reagents, calling into question the
provenance of other novel tombusviruses identified in some meta-transcriptomic studies [46]. The identification of reagent-associated tombusvirus-like sequences suggests that additional
care should be taken when characterizing novel tombusvirus sequences, particularly when
associating novel or previously identified tombusviruses with a host or disease. Similarly,
although the natural hosts of the Totiviridae are fungi, other Totiviridae are associated with
human-infecting protozoa, such as Trichomonasvirus associated with Trichomonas vaginalis
[47] and Giardiavirus that likely infects Giardia lamblia protozoa [48, 49]. The novel
reagent-associated totivirus identified in this study is distantly related to known totiviruses. We recommend that caution be taken when identifying novel totiviruses, especially if they
are related to reagent-associated toti-like virus. Lentiviruses are a genus within the Retroviridae and well documented in a wide range of
vertebrate species. The novel sequence identified in this study – reagent-associated lenti-like
virus – is closely related to several known sequences of equine infectious anemia virus
(EIAV) that cause the chronic disease, equine infectious anemia (EIA) in horses. |
EIAV is
transmissible through bodily secretions [50, 51], and has been suggested to be vector-borne
through biting flies [52]. Although the novel reagent-associated lenti-like virus was
genetically distinct from known EIAV sequences, care should obviously be taken to ensure
that any EIAV-like virus is a true viral infection rather than a reagent contaminant. 254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. In sum, this study further highlights the extent of viral sequences in commonly used
laboratory reagents [9], and the power of mNGS to monitor contamination in microbiological
laboratories [53]. Although the source of these contaminants is unknown and needs further
scrutiny, we tentatively suggest that viral vectors (for example, in the Lentiviridae) represent
a likely source. Factors to consider when assessing the presence of reagent contaminants
include genome coverage, read depth and distribution of read alignments across genomes,
and that potential contaminant sequences are often only present at low abundance and in
multiple libraries. Importantly, reagent-associated viruses are often more prevalent in
sequencing reads than assembled contigs, emphasising the importance of careful assessment
when relying on read data alone for characterizing novel viruses and other microbial genomes
[9, 26]. Finally, our work highlights the importance of employing additional steps such as
PCR or cell culture to confirm the presence of the pathogen after initial metagenomic
identification [9, 26]. Clearly, sequencing negative controls, such as that using sterile water
and reagent mix as performed here, should become normal procedure in quality control. 8. Author statements
8.1 Authors and contributors
Conceptualization, E.C.H. ; methodology, A.F.P, J.C, C.L and J.- S.E. ; formal analysis,
A.F.P. ; writing―original draft preparation, A.F.P. and E.C.H..; writing―review and editing,
A.F.P., E.C.H., C.L, J.C, J.-S.E. ; funding acquisition, E.C.H. 8.2 Conflicts of interest
The authors declare that there are no conflicts of interest. 8.3 Funding information
This research was funded by an Australian Research Council Australian Laureate Fellowship
to E.C.H (grant FL170100022). 8.4 Ethical approval
Not applicable. 285
286
287
288
289
290 291
292 293 294
295 296 297
298 299
300 301 302
303 304
305 306
307 308
309 310 311
312 313 314
315 316 317
318 319 320
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. |
It is made available under a
CC-BY 4.0 International license
. 8.5 Acknowledgements
We acknowledge the University of Sydney high performance computing cluster Artemis and
Sydney Informatics Hub which was used for the analyses in this study. 9. References
1. Grubaugh ND, Ladner JT, Lemey P, Pybus OG, Rambaut A, Holmes EC, et al. Tracking virus outbreaks in the twenty-first century. Nat Microbiol. 2019;4:10-9. 2. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet. 2020;395:565-74. 3. Gudbjartsson DF, Helgason A, Jonsson H, Magnusson OT, Melsted P, Norddahl GL, et al. Spread of SARS-CoV-2 in the Icelandic Population. New Eng J Med. 2020; 382:2302-15. 4. Zhang Y-Z, Chen Y-M, Wang W, Qin X-C, Holmes EC. Expanding the RNA virosphere by unbiased metagenomics. Annu Rev Virol. 2019;6:119-39. 5. Porter AF, Pettersson JHO, Chang W-S, Harvey E, Rose K, Shi M, et al. Novel hepaci- and pegi-like viruses in native Australian wildlife and non-human primates. Virus Evol. 2020;6:veaa064. 6. Geoghegan JL, Di Giallonardo F, Cousins K, Shi M, Williamson JE, Holmes EC. Hidden diversity and evolution of viruses in market fish. Virus Evol. 2018;4:vey031. 7. Harvey E, Rose K, Eden JS, Lo N, Abeyasuriya T, Shi M, et al. Extensive diversity of RNA viruses in Australian ticks. J Virol. 2019;93; e01358-18. 8. Shi M, Lin XD, Tian JH, Chen LJ, Chen X, Li CX, et al. Redefining the invertebrate RNA virosphere. Nature. 2016;540:539-43. 9. Asplund M, Kjartansdóttir KR, Mollerup S, Vinner L, Fridholm H, Herrera JA, et al. Contaminating viral sequences in high-throughput sequencing viromics: a linkage study of 700 sequencing libraries. Clin Microbiol Infect. 2019;25:1277-85. 10. Kjartansdóttir KR, Friis-Nielsen J, Asplund M, Mollerup S, Mourier T, Jensen RH, et al. Traces of ATCV-1 associated with laboratory component contamination. Proc Natl Acad Sci USA. 2015;112:E925-E6. 11. Laurence M, Hatzis C, Brash DE. Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes. PLoS ONE. 2014;9:e97876. 12. Friis-Nielsen J, Kjartansdóttir KR, Mollerup S, Asplund M, Mourier T, Jensen RH, et al. Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers. Viruses. 2016;8:53. 321 322 323
324 325 326
327 328
329 330 331
332 333 334
335 336
337 338 339
340 341 342
343 344 345
346 347 348
349 350
351 352 353
354 355
356 357
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 13. Lysholm F, Wetterbom A, Lindau C, Darban H, Bjerkner A, Fahlander K, et al. Characterization of the viral microbiome in patients with severe lower respiratory tract infections, using metagenomic sequencing. |
PLoS ONE. 2012;7:e30875. 14. Smuts H, Kew M, Khan A, Korsman S. Novel hybrid parvovirus-like virus, NIH- CQV/PHV, contaminants in silica column-based nucleic acid extraction kits. Journal of Virology. 2014;88:1398. 15. Lusk RW. Diverse and widespread contamination evident in the unmapped depths of high throughput sequencing Data. PLoS ONE. 2014;9:e110808. 16. Knox K, Carrigan D, Simmons G, Teque F, Zhou Y, Hackett J, et al. No evidence of murine-like gammaretroviruses in CFS patients previously identified as XMRV-infected. Science. 2011;333:94-7. 17. Naccache SN, Greninger AL, Lee D, Coffey LL, Phan T, Rein-Weston A, et al. The perils of pathogen discovery: origin of a novel parvovirus-like hybrid genome traced to nucleic acid extraction spin columns. J Virol. 2013;87:11966-77. 18. Paprotka T, Delviks-Frankenberry KA, Cingöz O, Martinez A, Kung H-J, Tepper CG, et al. Recombinant origin of the retrovirus XMRV. Science. 2011;333:97-101. 19. Ngoi CN, Siqueira J, Li L, Deng X, Mugo P, Graham SM, et al. The plasma virome of febrile adult Kenyans shows frequent parvovirus B19 infections and a novel arbovirus (Kadipiro virus). J Gen Virol. 2016;97:3359-67. 20. Ngoi CN, Siqueira J, Li L, Deng X, Mugo P, Graham SM, et al. Corrigendum: the plasma virome of febrile adult Kenyans shows frequent parvovirus B19 infections and a novel arbovirus (Kadipiro virus). J GenVirol. 2017;98:517. 21. Kerr M, Rosario K, Baker CCM, Breitbart M. Discovery of four novel circular single-stranded DNA viruses in fungus-farming termites. Microbiol Resour Ann. 2018;6:e00318-18. 22. Kazlauskas D, Dayaram A, Kraberger S, Goldstien S, Varsani A, Krupovic M. Evolutionary history of ssDNA bacilladnaviruses features horizontal acquisition of the capsid gene from ssRNA nodaviruses. Virology. 2017;504:114-21. 23. Krupovic M, Ghabrial SA, Jiang D, Varsani A. Genomoviridae: a new family of widespread single-stranded DNA viruses. Arch Virol. 2016;161:2633-43. 24. Rosario K, Breitbart M, Harrach B, Segales J, Delwart E, Biagini P, et al. Revisiting the taxonomy of the family Circoviridae: establishment of the genus Cyclovirus and removal of the genus Gyrovirus. Arch Virol. 2017;162:1447-63. 25. Varsani A, Krupovic M. Smacoviridae: a new family of animal-associated single- stranded DNA viruses. Arch Virol. 2018;163:3213-4. 26. Holmes EC. Reagent contamination in viromics: all that glitters is not gold. Clin Microbiol Infect. 2019;25:1167-8. 358 359
360 361 362
363 364 365
366 367 368
369 370 371
372 373 374
375 376
377 378
379 380
381 382
383 384 385
386 387
388 389 390 391
392 393
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 27. de Goffau MC, Lager S, Salter SJ, Wagner J, Kronbichler A, Charnock-Jones DS, et al. |
Recognizing the reagent microbiome. Nat Microbiol. 2018;3:851-3. 28. Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 2014;12:87. 29. Zinter M, Mayday M, Ryckman K, Jelliffe-Pawlowski L, DeRisi J. Towards precision quantification of contamination in metagenomic sequencing experiments. Microbiome. 2019;7:1-5. 30. Stinson LF, Keelan JA, Payne MS. Identification and removal of contaminating microbial DNA from PCR reagents: impact on low‐biomass microbiome analyses. Lett Appl Microbiol. 2019;68:2-8. 31. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full- length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotech. 2011;29:644-52. 32. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;3:1674-6. 33. Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Meth. 2015;12:59-60. 34. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421. 35. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in performance and usability. Mol Biol Evol. 2013;30:772-80. 36. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17:540-52. 37. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268-74. 38. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Meth. 2012;9:357-9. 39. Marzano S-YL, Nelson BD, Ajayi-Oyetunde O, Bradley CA, Hughes TJ, Hartman GL, et al. Identification of diverse mycoviruses through metatranscriptomics characterization of the viromes of five major fungal plant pathogens. J Virol. 2016;90:6846-63. 40. Mu F, Xie J, Cheng S, You MP, Barbetti MJ, Jia J, et al. Virome characterization of a collection of S. sclerotiorum from Australia. Front. Microbiol. 2017;8:2540. 394 395
396 397 398
399 400 401
402 403 404
405 406 407
408 409
410 411
412 413 414
415
416 417
418 419 420
421 422
423 424 425
426
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 41. Erlwein O, Robinson MJ, Dustan S, Weber J, Kaye S, McClure MO. DNA extraction columns contaminated with murine sequences. PLoS ONE. 2011;6:e23484. 42. Dayaram A, Goldstien S, Arguello-Astorga GR, Zawar-Reza P, Gomez C, Harding JS, et al. Diverse small circular DNA viruses circulating amongst estuarine molluscs. |
Infect Genet Evol. 2015;31:284-95. 43. Porter AF, Shi M, Eden J-S, Zhang Y-Z, Holmes EC. Diversity and evolution of novel invertebrate DNA viruses revealed by meta-transcriptomics. Viruses. 2019;11:1092. 44. Rosario K, Dayaram A, Marinov M, Ware J, Kraberger S, Stainton D, et al. Diverse circular ssDNA viruses discovered in dragonflies (Odonata: Epiprocta). J Gen Virol. 2012;93:2668-81. 45. Islam SU, Lin W, Wu R, Lin C, Islam W, Arif M, et al. Complete genome sequences of three novel cycloviruses identified in a dragonfly (Odonata: Anisoptera) from China. Arch Virol. 2018;163:2569-73. 46. Culley AI, Lang AS, Suttle CA. Metagenomic analysis of coastal RNA virus communities. Science. 2006;312:1795-8. 47. Goodman RP, Ghabrial SA, Fichorova RN, Nibert ML. Trichomonasvirus: a new genus of protozoan viruses in the family Totiviridae. Arch Virol. 2011;156:171-9. 48. Wang AL, Yang HM, Shen KA, Wang CC. Giardiavirus double-stranded RNA genome encodes a capsid polypeptide and a gag-pol-like fusion protein by a translation frameshift. Proc Natl Acad Sci USA. 1993;90:8595-9. 49. Wang AL, Wang CC. Viruses of the protozoa. Annu Rev Microbiol. 1991;45:251-63. 50. Sellon DC, Fuller FJ, McGuire TC. The immunopathogenesis of equine infectious anemia virus. Virus Res. 1994;32:111-38. 51. Issel CJ, Adams WV, Jr., Meek L, Ochoa R. Transmission of equine infectious anemia virus from horses without clinical signs of disease. J Am Vet Med Assoc. 1982;180:272- 5. 52. Hawkins JA, Adams WV, Jr., Wilson BH, Issel CJ, Roth EE. Transmission of equine infectious anemia virus by Tabanus fuscicostatus. J Am Vet Med Assoc. 1976;168:63-4. 53. Xiao Y, Zhang L, Yang B, Li M, Ren L, Wang J. Application of next generation sequencing technology on contamination monitoring in microbiology laboratory. Biosafety Health. 2019;1:25-31. 427
428
429
430 431 432 433 434 435
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. 10. Figures and tables
Figure 1. Abundance of viral reads in libraries L1, L2, L3, and L7. (A-D) Visual representation of the virus-associated reads in respective libraries, with the pie chart depicting the total number of long (>800 bp) virus-associated contigs (orange) compared to all the virus-associated reads (blue). The bar chart on the right denotes the proportion of contigs of associated with different virus families in the respective libraries. 436
437
438 439 440 441 442 443 444 445
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. |
Figure 2. Phylogenetic relationships of CRESS (ssDNA) viruses, including the seven novel CRESS-like viruses identified here and highlighted in red (reagent-associated CRESS-like viruses 1-7). Reagent-associated sequences determined previously are highlighted in blue. The clades that included the novel CRESS-like viruses identified here (A, B and G) are magnified on the right. The tree and other clades (C, D, E and F) are shown in higher resolution in Supplementary Figure 1. The tree was mid-point rooted for clarity purposes only. Bootstrap values greater than 70% are represented by asterisks next to nodes. All horizontal branch lengths are scaled according to number of amino acid substitutions per site. 446
447 448 449 450 451 452 453
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Figure 3. Phylogenetic relationships of ssDNA virus family Circoviridae, based on hypothesised “host-associated” circoviruses. The tree has two major clades, comprising the circovirus clade (highlighted in blue), associated with vertebrate hosts, and the cyclovirus clade (highlighted in green), previously associated with invertebrate hosts. For clarity, the tree is mid-point rooted. Bootstrap values greater than 70% are represented by asterisks next to nodes. All horizontal branch lengths are scaled according to number of amino acid substitutions per site. 454
455 456 457
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Figure 4. Phylogenetic relationships of RNA virus family Lentiviridae including the novel virus identified in this study, the novel sequence reagent-associated lenti-like virus. This virus is highlighted in red and falls within the Equine infectious anemia virus clade. 458
459 460 461 462 463
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Figure 5. Phylogenetic relationships of RNA virus family Tombusviridae including the seven novel viruses identified in this study (highlighted in red). The phylogeny was mid-point rooted for clarity purposes only. Bootstrap values greater than 70% are represented by asterisks next to nodes. All horizontal branch lengths are scaled according to number of amino acid substitutions per site. |
464 465
466 467 468 469 470
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Figure 6. Phylogenetic relationships of RNA virus family Totiviridae, including the novel virus identified in this study - Reagent-associated toti-like virus (highlighted in red). For clarity, the tree was mid-point rooted. Bootstrap values greater than 70% are represented by asterisks next to nodes. All horizontal branch lengths are scaled according to number of amino acid substitutions per site. 471
472
473
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Table 1. Experimental conditions of each blank negative control sample utilised here. Library
Sequencing
RNA extraction
Library preparation
Data
Library
name
platform
generated
accession1
L1
Illumina Novaseq
RNeasy Plus
Trio RNA-seq +UDI
11,940,824
SRR14737471
6000 150 cycle kit
Universal Kits
(NuGEN)
paired reads
(2x75nt reads)
(Qiagen)
(1.8Gb)
L2
Illumina Novaseq
RNeasy Plus
Trio RNA-seq +UDI
57,606,392
SRR14737470
6000 150 cycle kit
Universal Kits
(NuGEN)
paired reads
(2x75nt reads)
(Qiagen)
(8.7Gb)
L3
Illumina MiSeq, v3
RNeasy Plus Mini
SMARTer Stranded
4,156,504
SRX6803604
150 cycle kit
Kit (Qiagen)
Total RNA-Seq Kit v2
paired reads
(2x75nt reads)
Pico Input
(0.63 Gb)
Mammalian (Clontech)
L4
Illumina NextSeq
Total RNA
SMARTer Stranded
32,279,914
SRR14737469
500, mid-output
Purification Kit
Total RNA-Seq Kit v2
paired reads
150 cycle kit
(Norgen Biotek)
Pico Input
(4.91 Gb)
(2x75nt reads)
Mammalian (Clontech)
L5
Illumina MiSeq 150
cycle kit (2x75nt
Total RNA
purification Kit
SMARTer Stranded
Total RNA-Seq Kit v2
7,342,876 paired reads (1.10 Gb)
SAMN20355437
reads)
(Norgen BioTek
Pico Input
Corp)
Mammalian (Clontech)
L6
Illumina MiSeq 150
cycle kit (2x75nt
Total RNA
purification Kit
SMARTer Stranded
Total RNA-Seq Kit v2
10,978,253 paired reads (1.65 Gb)
SAMN20355438
reads)
(Norgen BioTek
Pico Input
Corp)
Mammalian (Clontech)
L7
Illumina MiSeq 150
cycle kit (2x75nt
Total RNA
purification Kit
SMARTer Stranded
Total RNA-Seq Kit v2
8,564,269 1.28 Gb
SRR14737466
reads)
(Norgen BioTek
Pico Input
Corp)
Mammalian (Clontech)
1The sequencing data for each library can be accessed via the sequence read archive (SRA) using the associated
accession numbers. 474
475
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. |
It is made available under a
CC-BY 4.0 International license
. Table 2. Reference proteins for each sequence alignment performed in this analysis. Reference
Number of
Reference protein
acronym
Taxonomy
sequences
Alignment length
in analysis
(amino acid, AA)
Viral replicase protein Rep
CRESS
221
672 AA
Viral replicase protein Rep
Circoviridae
69
161 AA
Polymerase peptide Pol
Lentiviridae
11
478 AA
RNA-dependent RNA
RdRp
Totiviridae
95
125 AA
polymerase
RNA-dependent RNA
RdRp
Tombusviridae 87
256 AA
polymerase
476
477
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.10.459871
;
this version posted September 11, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in
perpetuity. It is made available under a
CC-BY 4.0 International license
. Table 3. Novel reagent-associated viral sequences identified in this study. Virus name
Accession
Abundance in library (%) of total reads, rRNA removed)
Length (bp)
Library
Reagent-associated tombus-like virus 1 MZ824229
1.28
1204
L3
Reagent-associated tombus-like virus 2 MZ824228
0.46
828
L3
Reagent-associated tombus-like virus 3 MZ824227
1.08
1574
L3
Reagent-associated tombus-like virus 4 MZ824226
1.29
1410
L3
Reagent-associated toti-like virus MZ824225
0.001
920
L2
Reagent-associated lenti-like virus MZ824230
0.004
962
L2
Reagent-associated CRESS-like virus 1 MZ824237
0.78
3878
L1
Reagent-associated CRESS-like virus 2 MZ824236
0.24
2377
L1
Reagent-associated CRESS-like virus 3 MZ824235
0.02
1592
L1
Reagent-associated CRESS-like virus 4 MZ824234
2.89
2663
L3
Reagent-associated CRESS-like virus 5 MZ824233
9.66
3027
L3
Reagent-associated CRESS-like virus 6 MZ824232
4.98
3517
L3
Reagent-associated CRESS-like virus 7 MZ824231
0.01
1124
L1 |
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Magnetic fluctuations affect circadian patterns of locomotor activity in zebrafish
Viacheslav V. Krylov*, Evgeny I. Izvekov, Vera V. Pavlova, Natalia A. Pankova and Elena A. Osipova
Papanin Institute for Biology of Inland Waters Russian Academy of Sciences, Borok, Nekouz, Yaroslavl Oblast, 152742, Russia
Correspondence to: Viacheslav V. Krylov, Papanin Institute for Biology of Inland Waters Russian Academy of Sciences, Borok, Nekouz, Yaroslavl Oblast 152742, Russia. E‐mail: [email protected]
Abstract The locomotor activity of zebrafish (Danio rerio) has a pronounced, well-studied circadian rhythm. Under constant illumination, the period of free-running locomotor activity in this species usually becomes less than 24 hours. To evaluate the entraining capabilities of slow magnetic variations, zebrafish locomotor activity was evaluated at constant illumination and fluctuating magnetic field with a period of 26.8 hours. Lomb-Scargle periodogram revealed significant free- running rhythms of locomotor activity and related behavioral endpoints with a period close to 27 hours. Obtained results reveal the potential of slow magnetic fluctuations for entrainment of the circadian rhythms in zebrafish. The putative mechanisms responsible for the entrainment are discussed, including the possible role of cryptochromes. Keywords: Danio rerio, magnetic field, circadian rhythm, swimming speed, meandering, angular velocity, cryptochrome
INTRODUCTION
Circadian rhythms play a significant role in the physiology of the majority of living beings. They provide effective use of energy and resources in ever-changing natural and artificial environments [1]. Based on the endogenous rhythms of intracellular circadian oscillators, an organism adjusts its internal processes to the anticipated conditions for a given time of day [2]. Briefly, these circadian clocks in cells are described as transcription-translation feedback loops. In most vertebrates, positive components of this loop are the transcription factors CLOCK and BMAL that modulate the expression of Period (Per) and Cryptochrome (Cry) genes as negative components. These negative components repress transcription and induce the body's circadian clock to reset, thus starting a new cycle of the feedback loop [1, 3, 4]. In birds and mammals, this endogenous circadian oscillator (located in the brain's suprachiasmatic nucleus) provides the main rhythm transferred to peripheral tissues via pineal gland produced melatonin [5]. A decentralized to varying degree circadian system can be found throughout the evolutionary tree [6, 7]. The endogenous circadian rhythms adjust to external environmental cues (zeitgebers) with the primary external pacemaker being light/dark cycles. |
In general terms, the endogenous circadian oscillator synchronizes to local daytime via photic cues transmitted from the retina to neurons of the suprachiasmatic nucleus [8]. Some findings suggest the diurnal geomagnetic variation may be a secondary external zeitgeber affecting biological circadian rhythms [9, 10]. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. This variation results from the dynamo-current process within the ionospheric E-region and represents a distinguishable daily magnetic oscillation from approximately a few tens of nanoTeslas (nT) at mid-latitudes to 200 nT near the magnetic equator [11]. Diurnal geomagnetic variation is suggested to act as a potential circadian zeitgeber via cytochromes possibly being able to perceive magnetic fields through radical pair reactions [12, 13]. Though indirect evidence supports this theory [14, 15, 16, 17, 18, 19, 20], no direct experimentation has been carried out studying the entrainment of circadian rhythms to slow magnetic fluctuations. The issue of whether slow changes in the magnetic field affect circadian oscillators remains open. In the present study, we used wild-type zebrafish (Danio rerio) to answer this question. The brain of this species contains the pineal gland driving the rhythmic production of melatonin [21, 22]. However, the circadian oscillators in different zebrafish tissues can keep unrelated rhythms that are entrained directly by an external light-dark zeitgeber [23, 24, 25]. The lack of a centralized pacemaker subjugating all other oscillators in zebrafish could increase the chance to detect changes in circadian rhythms caused by a magnetic influence. The influence of different light and magnetic exposures on zebrafish rhythms was analyzed through locomotor activity and several related endpoints known as precise indicators of circadian rhythmicity in this species [26]. METHODS
All animal experiments were carried out in accordance with relevant guidelines and regulations. The study was carried out in compliance with the ARRIVE guidelines. All experimental protocols have been approved by the Institutional Animal Care and Use Committee Waters at (https://ibiw.ru/index.php?p=downloads&id=46180). Papanin
Institute
for
Biology
of
Inland
Zebrafish maintenance Wild-type zebrafish (AB strain) were obtained from the commercial distributer and maintained in the Laboratory of physiology and toxicology (Papanin Institute for Biology of Inland Waters, Russian Academy of Sciences). Prior to experimentation, zebrafish were kept together for two months in 70 L aquaria at 24◦C under a 16:8 h light/dark cycle. Zebrafish were fed daily at different times between 12:00 and 16:30. Males and females at the age of approximately four months (mean body length 2.99 cm, SD = 0.17 cm, n = 24) were used for experimentation. |
Timed backlight
In order to provide backlit illumination for the experiments, a lightbox was constructed from a series of LEDs, aluminum plates, and matte plexiglass. LED plates were created by adhering 32 LEDs to an aluminum plate so as each aquarium would be backlit by 4 infrared LEDs (3W, 940nm) and 4 white-color LEDs ( 3W, 4500K). Each LED plate was mounted 10 cm under a lightbox cover (constructed from matte plexiglass) which serves to diffuse light. Lighting modes were controlled via time relays (DH-48S-S, Omron, Japan) which used KMI-10910 (IEK, Russia) contactors to supply power, by Qh-60LP18 power suppliers (Shenzhen Chanzon Technology, China), to the LEDs. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Magnetic fluctuations Zebrafish were exposed to the following magnetic fluctuations: 1. The natural diurnal geomagnetic variation. It is represented by magnetic fluctuations of about 30 nT with a 24 h period. This variation was recorded in X-, Y-, and Z-directions throughout the experiment using an NV0302A magnetometer (ENT, St Petersburg, Russia). Six geomagnetic disturbances with a k-index of 4 that corresponds to weak geomagnetic storms occurred during the experiments under natural diurnal geomagnetic variation (08/02/2020 from 12:00 to 18:00; 08/31/2020 from 00:00 to 03:00, from 09:00 to 12:00, and from 15:00 to 21:00; 09/14/2020 from 00:00 to 03:00). The natural diurnal geomagnetic variation was accompanied by a 16: 8 h light / dark photoperiod. 2. Experimental magnetic fluctuations simulating increased diurnal geomagnetic variation with an average period of 26.8 h. We used a sample record of diurnal geomagnetic variation in X-, Y- and Z-directions made close to the laboratory to generate these magnetic oscillations. The sample record intensity was enhanced to about 100-150 nT for each X-, Y-, and Z-directions. This exposure allows for more pronounced periodic changes in the magnetic background but not exceeding the level of natural geomagnetic storms. The period of sample diurnal geomagnetic variation was also increased to 26.8 h by a signal prolongation. This value was chosen for the experiments because the free-running rhythm of locomotor activity in zebrafish became shorter than 24 h under constant illumination. Hence the magnetic zeitgeber with a period longer than 26 h can manifest itself under constant illumination. At the same time, the period of 26.8 h is quite close to the circadian 24 h period. That is, the endogenous oscillator does not require drastic changes in order to be entrained by this external zeitgeber. The experimental magnetic fluctuations were generated under constant light conditions. Signals of the natural diurnal geomagnetic variation and experimental magnetic fluctuations in the horizontal direction are shown in Figure 1. |
In order to compare these signals with behavioral endpoints, they are also presented as actograms and periodograms (Fig. 2 a, b). Fig 1. Natural diurnal geomagnetic variation (red line) and experimental magnetic fluctuations (green line) in the horizontal direction. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A setup, described in detail by Krylov et al. [27], was used to generate experimental magnetic fluctuations. It was assembled on a PC workstation and consisted of the following items:
1) A three‐component fluxgate magnetometer NV0302A (ENT, St Petersburg, Russia providing analogous signals proportional to the strength of the geomagnetic field and its variations;
2) An LTR11 analog‐to‐digital and an LTR34‐4 digital‐to‐analog signal converter (L‐card,
Moscow, Russia);
3) A coil system consisting of three pairs of mutually orthogonal Helmholtz coils (0.5 m in diameter, 700 turns of 0.2 mm copper wire in each coil) made by the Schmidt Institute of Physics of the Earth (www.ifz.ru). The direction of each Helmholtz coils pair was the same as the direction of the geomagnetic field components. Natural fluctuations of the geomagnetic field, including diurnal variation, were compensated within the Helmholtz coil systems in the frequency range up to 5 Hz based on a signal from NV0302A magnetometer (ENT). The industrial alternating magnetic fields of 50 Hz were less than 10 nT and did not appear in the harmonics. Parameters of the generated signals in the Helmholtz coils system's working volume were checked using a control magnetometer NV0599C (ENT). Experimental conditions and procedure All experimentation was conducted in a remote laboratory free of working staff in order to eliminate possible circadian rhythm influences caused by daily human activities. Four fish were placed in four custom glass aquaria (15 x 20 cm, height 23 cm) filled with 10 cm of water, with one fish per aquarium. Water temperature during the experiments was 21oC as adult zebrafish show the most robust rhythm of locomotor activity at the temperatures of 20-21 oC (Hurd et al., 1998; López‐Olmeda et al., 2006). The aquaria were installed above a lightbox. Screens made of opaque white plastic were placed between the adjacent aquaria so that fish could not see conspecifics. The lightbox with the aquaria was located in a system of Helmholtz coils. During the first 4.5 days, a 16: 8 h light / dark cycle was maintained, and no voltage was supplied to Helmholtz coils. Then from 13:00 of the 5th to 00:00 of the 10th day of the experiments, constant lighting conditions were maintained, and experimental magnetic fluctuations were generated within Helmholtz coils. The water was constantly renewed via two 4 mm openings in the wall of each aquarium at 3 and 10 cm height from the bottom. |
Water flowed by gravity from a 200 L plastic barrel placed one floor above through the silicone hoses connected to the bottom openings of aquaria. Water aeration and temperature control for all aquaria were carried out in the barrel. Excess water was drained to the sewer through the top opening to ensure a constant level of 10 cm. Water from different aquaria has never been mixed or reused. At the beginning of the experiment, a 1 cm3 piece of slow-release gel food block “Tetra Holiday” (Tetra GmbH, Melle, Germany) was placed on the bottom of each aquarium to prevent the influence of the feeding schedule on circadian behavior. Thereby zebrafish had free access to food during the whole study. Fish movements in the horizontal plane were registered with IP-cameras (TR-D1140, Trassir, Shenzhen, China) equipped with IR corrected varifocal lenses (TR-L4M2.7D2.7-13.5IR, Trassir, Shenzhen, China) and mounted above the aquaria. Night and day video was recorded in
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. black and white at 25 frames per second with a resolution of 2592 × 1520 pixels. The video signals were transmitted through a switch (T1500-28PCT, TP-Link, Shenzhen, China) to a video recorder server (MiniNVR AF16, Trassir, Shenzhen, China). The experiment was performed in 3 independent and time-separated replications between July 31, 2020 and September 17, 2020. Each zebrafish was used only for a single replication. Thereby 216-h video records obtained from 12 zebrafish were then processed. Data processing An approach proposed by Audira et al. [28] was used for data processing. One-minute video files were cut from the primary video record for every half of an hour (from the 15th to the 16th and 45th to 46th min of each hour). Such duration has proved to be sufficient for statistical analysis of locomotor activity with the data appropriately describing circadian rhythms [28, 29, 30]. The open-source software idTracker [31] was used to process each one-minute video file. The software provided X and Y coordinates reflecting the center of the fish body for each frame. Before the processing, the trajectory data were filtered using the "minimal distance moved" method to eliminate slight "apparent" movements of the fish [32, 33]. The minimal distance threshold was set at 2.6 mm. Then, based on this information, several quantitative measures of fish behavior that reveal pronounced circadian rhythms in zebrafish [28] were calculated using the Microsoft Excel formulae. The parameters included:
1. Average swimming speed, cm/s (total distance travelled divided by total observation
time)
2. Meandering, °/cm, reflecting the trajectories irregularity and calculated as the sum of all
turning angles (absolute values) divided by total distance
3. Average angular velocity, °/s (total turning angle divided by total test time) 4. |
Freezing time, % (the total time when speed is less than 1 cm/s) 5. Swimming time, % (the total time when speed ranges from 1 to 10 cm/s) 6. Rapid movement time, % (the total time when speed exceeds 10 cm/s) 7. Wall preference index (relative time spent within a 3-cm-wide area close to the walls) ), where Tw and Tc denote + 𝑇c 𝑆c /(𝑇w 𝑆w
3. Average angular velocity, °/s (total turning angle divided by total test time) 4. Freezing time, % (the total time when speed is less than 1 cm/s) 5. Swimming time, % (the total time when speed ranges from 1 to 10 cm/s) 6. Rapid movement time, % (the total time when speed exceeds 10 cm/s) 7. Wall preference index (relative time spent within a 3-cm-wide area close to the walls) ), where Tw and Tc denote + 𝑇c 𝑆c /(𝑇w 𝑆w
Differences between the average values of studied parameters during the light and dark phases were evaluated with a t-test as all data had a normal distribution (Shapiro–Wilk W-test, p > 0.05). Time series were analyzed with RhythmicAlly software [34]. The linear trend was subtracted from the time series, and the data were smoothed with a moving average window of 7 samples before analysis. Circadian periods under 16: 8 h light / dark cycle and free-running periods under constant illumination were analyzed using the Lomb-Scargle periodogram [35]. We also used cosinor-analysis [36] based on the approximation of a time series by a cosine wave to identify a mesor (or a rhythm-adjusted mean that represents the average level of the cosine wave) and an amplitude (a measure of half the extent of predictable variation within a cycle) of studied rhythms. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Fig 2. Diurnal geomagnetic variation (a), experimental magnetic fluctuations (b), and dynamics of zebrafish behavioral endpoints (c–j) given as a set of double plotted actograms and periodograms. Both natural geomagnetic variation used at the first stage of experiments under a 16:8 LD cycle (a) and experimental magnetic fluctuations with a 26.8 h period under constant illumination at the second stage (b) were horizontally directed. Behavioral endpoints measured at these two stages respectively included: average swimming speed (c, d), meandering (e, f), angular velocity (g, h), and wall preference index (i, j). Significant periods on Lomb-Scargle periodograms (p < 0.05) are above the solid red line. The dotted line on the actograms denotes the trends that determine a significant free-running period of about 27 hours. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. RESULTS
Zebrafish displayed a robust circadian rhythm of locomotor activity and related behavioral endpoints at the first stage of the experiments under 16:8 h light / dark cycle. |
Most of the endpoints (swimming speed, angular velocity, wall preference index, swimming time, and rapid movement time) were higher during the light phase and lower in the dark, while meandering and freezing time followed the reversed pattern (Suppl. 1). The circadian period in the dynamics of studied endpoints was 24 h (Fig. 2 c, e, g, i). The average angular velocity and wall preference index had an additional weaker rhythm with a 15.84 h period (Fig. 2 g, i). Natural geomagnetic disturbances with a k-index of 4 did not affect circadian patterns of behavioral endpoints at the first stage of the experiments. At the second stage of the experiments, the zebrafish were held at constant lighting and magnetic variation with a 26.8-h period (Fig 2 b). In the absence of the photic zeitgeber, the studied endpoints, except for meandering, showed significant free-running rhythms with periods close to 27 h (Fig. 2 d, f, h, j). These free-running rhythms were dominant for angular velocity, wall preference index, and rapid movement time (Table 1). However, in the case of swimming speed, freezing time, and swimming time, these 27 h rhythms, while present, were less pronounced than those with 20 h periodicity (Table 1). Generally, the amplitudes of behavioral rhythms found within the second stage of the experiments were reduced compared to the first stage through the emergence of additional rhythms manifested in several peaks on periodograms. Such a multiple-peaked pattern results from different individuals with a predominance of one or another rhythm in the studied group (Suppl. 2). However, even in individuals with a predominance of one of the most pronounced periods (20 ± 1 h or 27 ± 1 h), a secondary, less prominent peak was often present. In two individuals, these two peaks had almost equal amplitude. At the same time, several individuals in the group retained a rhythm with a period close to 24 h (Suppl. 2). The diurnal changes in studied behavioral endpoints significantly correlated with the experimentally generated magnetic fluctuations and were not related to the natural geomagnetic variation except for a couple of weak correlations (Table 2). DISCUSSION
The circadian rhythms in the dynamics of the studied parameters at the first stage of the experiment correspond to the known patterns of zebrafish circadian behavior governed by daily changes in illumination [26]. Additional peaks at 15.84 h on the periodograms for the wall preference index and angular velocity are associated with a well-documented phenomenon of visual-motor response in zebrafish [37]. In the present case, fish preferred walls to the inner area of the aquarium and showed increased angular velocity at the moments of abrupt changes in illumination. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. |
Table 1. Lomb-Scargle periods, mesors, and amplitudes for the rhythms of studied behavioral endpoints in zebrafish. All presented rhythms are
significant (p <0.05, Lomb-Scargle periodogram analysis). First stage of experiments, circadian period mesor 1.852 46.781 67.711 0.494 41.746 57.445 0.809
Second stage of experiments, primary free-running period mesor 1.998 33.405 62.181 0.571 25.526 73.985 0.515
Second stage of experiments, secondary free-running period mesor 2.020 33.441 61.794 0.570 25.119 74.390 0.496
Parameter
period 24 24 24 24 24 24 24
amplitude period 20.211 20.211 27.429 28.444 20.211 19.948 27.927
amplitude period 26.947 17.067 20.211 16.000 26.947 26.947 20.480
amplitude 0.100 1.021 3.309 0.010 1.673 1.610 0.101
Average swimming speed Meandering Average angular velocity Wall preference index Freezing time Swimming time Rapid movement time
0.635 19.021 12.045 0.030 23.703 23.529 0.625
0.103 1.245 2.417 0.011 1.566 1.488 0.094
Table 2. Spearman rank-order correlations between the behavioral endpoints in zebrafish and magnetic fluctuations in X, Y, and Z directions during
the second stage of experiments (n = 3348 for each correlation). The correlation coefficients between the behavioral endpoints and natural diurnal
geomagnetic variation are also given for comparison. This geomagnetic variation would have been if the magnetic field had not been modified in the
experiment. Significant correlations at p < 0.001 (after correction for multiple pairwise correlations) are marked with asterisks. Experimental magnetic fluctuations Y
Natural diurnal geomagnetic variation Y
Parameter
X
Z
X –0.064 –0.027 –0.026 –0.049 0.033 –0.029 –0.066
Z –0.047 0.033 –0.043 –0.014 0.000 –0.002 –0.064
Average swimming speed Meandering Average angular velocity Wall preference index Freezing time Swimming time Rapid movement time
–0.204* 0.182* –0.031 –0.235* 0.182* –0.178* –0.107*
0.116* 0.333* –0.582* 0.415* –0.207* 0.219* –0.049
–0.114* –0.160* 0.386* –0.355* 0.191* –0.195* 0.050
–0.113* 0.028 –0.043 –0.040 0.046 –0.046 –0.111*
bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. It is known that the period of free-running rhythms in zebrafish locomotor activity under constant illumination and not-modified geomagnetic conditions usually becomes shorter than 24 h. Thus, Hurd et al. [38] reported that such free-running periods vary in the range of 23.5-24.5 h depending on the water temperature. Another study revealed the shortening of daily rhythms in zebrafish locomotor activity to 22.9-23.6 h under constant dim light [39]. The free-running rhythm of locomotor activity in zebrafish also became shorter (22.9 ± 0.5 h) under ultradian 45:45 min light/dark cycles [40]. We found no mention of the zebrafish locomotor activity rhythms with a period longer than 26 h maintained under constant illumination without additional zeitgebers. |
Significant 27 h peaks found on the fish periodograms in the present study coincide with the period of experimental magnetic fluctuations. These data strongly suggest that the slow changes in the external magnetic field may entrain the free-running behavioral rhythms in zebrafish. This is also evidenced by significant correlations between the studied here behavioral endpoints and experimental magnetic fluctuations. Earlier, it was reported that magnetic influence could affect circadian rhythms in different organisms [41, 42]. However, until the present study, there were no direct experimental data in support of the entrainment of endogenous circadian oscillators to slow magnetic fluctuations. At the same time, zebrafish showed pronounced individuality of the entrainment. These results are in accordance with previously reported data on the variability of zebrafish behavioral responses in general [38, 43] and marked individuality of their reactions to magnetic fields in particular [44, 45]. Our results also indicate that under constant illumination in the presence of a 26.8-hour magnetic zeitgeber, competition likely occurs between the two free-running rhythms found in zebrafish. One of these rhythms follows the magnetic zeitgeber and has a visible period of about 27-h. Apparently, cryptochromes could participate in the entrainment of locomotor activity rhythms with magnetic fluctuations. On the one hand, it was suggested that cryptochromes are responsible for the biological effects of geomagnetic storms [10] and magnetic-compass orientation [13]. On the other hand, cryptochromes are involved in the transcription-translation feedback loop as the main elements of the molecular circadian oscillator [1, 46]. Some investigations revealed a direct link between the magnetic field intensity and expression levels of cryptochromes [16] and other clock genes [18]. A possible mechanism of magnetic influence on cryptochromes is based on changes of the singlet-triplet state of electrons in cryptochrome’s radical pairs, modulating the functional state of these proteins [12]. These magnetic-field- induced changes in the functional state of cryptochromes may, in turn, affect the repressor functions of the CRY:PER dimers. At the same time, other elements of the complex molecular circadian oscillator network [46, 47] may continue to function in a usual mode, which would shorten the free-running period under constant illumination. Due to these processes, two or more free-running rhythms with different periods can arise under the experimental magnetic influence. In addition, zebrafish possess various independent cellular oscillators with diverse rhythms in different tissues [7, 23, 48]. It can also be the reason for several periodogram peaks found in the present experiments. Circadian patterns of behavioral endpoints at the first stage of the experiments depended on the light-dark cycle. They were not affected by natural disruptions of diurnal geomagnetic variation with a k-index of 4. |
The magnetic zeitgeber manifested itself only in the absence of a light-dark cycle in the second stage of the experiment. Hence changes in illumination have a greater impact on circadian patterns of zebrafish locomotor activity than magnetic fluctuations. bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. It needs to be emphasized that the present results are significant for the time series obtained in this experiment. Further research needs to be performed considering the individuality in zebrafish responses to magnetic influence under constant illumination. The present results indicate a high possibility of the entrainment of circadian rhythms to slow magnetic fluctuations. More experiments from different scientific groups are needed to clarify this issue and expand our knowledge of non-photic cues for periodic biological processes. It can opens prospects for manipulating circadian oscillators via magnetic fields. Further research in the field can focus on studying the effects of slow magnetic fluctuations on circadian genes' rhythmic expression. Some recommendations for generation of slow magnetic fluctuations are given in Supplementary 3. The datasets analyzed during the current study are available in the “Open Science
Framework” repository, https://osf.io/4by9t/
ACKNOWLEDGMENTS
The authors express their sincere gratitude to G.M. Chuiko for the provided wild-type zebrafish. We thank O.D. Zotov and B.I. Kline for help in preparing experimental signals and processing time-series data, M.A. Tyumin for technical support, and O.V. Solovieva for her help in the data processing. This research received support from the Russian Foundation for Basic Research (project No. 20-04-00175) to V.V.K., E.I.I., V.V.P., and N.A.P. E.A.O. was supported by the Ministry of Education and Science of the Russian Federation (State Assignment No. 121051100109-1). AUTHOR CONTRIBUTIONS
V.K. conceived and planned the experiments. V.K. and E.I. carried out the experiments. All authors processed the experimental data and performed the analysis. V.K. and E.I. wrote the paper with input from all authors. Competing interests The authors declare no competing interests. REFERENCES
1. Finger, A. M., Dibner, C. & Kramer, A. Coupled network of the circadian clocks: a driving force of rhythmic physiology. FEBS Lett. 594, 2734–2769 https://doi.org/10.1002/1873- 3468.13898 (2020). 2. Patke, A., Young, M. W. & Axelrod, S. Molecular mechanisms and physiological 67–84 rhythms. Nat. Rev. Mol. Cell Biol. 21, of
2. Patke, A., Young, M. W. & Axelrod, S. Molecular mechanisms and physiological 67–84 rhythms. Nat. Rev. Mol. Cell Biol. 21, of
3. Wager-Smith, K. & Kay, S. A. Circadian rhythm genetics: from flies to mice to humans. Nat. Genet. 26, 23–27 (2000). 4. Idda, M. L. et al. Circadian clocks: lessons from fish. |
Prog. Brain Res. 199, 41–57
(2012). 5. Dibner, C., Schibler, U. & Albrecht, U. The mammalian circadian timing system: organization and coordination of central and peripheral clocks. Annu. Rev. Physiol. 72, 517–549 (2010). 6. Bell-Pedersen, D. et al. Circadian rhythms from multiple oscillators: lessons from diverse organisms. Nature reviews. Genetics 6(7), 544–556 https://doi.org/10.1038/nrg1633 (2005). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 7. Frøland Steindal, I. A. & Whitmore, D. Circadian clocks in fish – what have we learned
so far? Biology 8, 17 https://doi.org/10.3390/biology8010017 (2019). 8. LeGates, T., Fernandez, D. & Hattar, S. Light as a central modulator of circadian rhythms, sleep and affect. Nat. Rev. Neurosci. 15, 443–454 https://doi.org/10.1038/nrn3743 (2014). 9. Brown, F. A. Biological clocks: endogenous cycles synchronized by subtle geophysical
rhythms. Biosystems 8, 67–81 (1976). 10. Krylov, V. V. Biological effects related to geomagnetic activity and possible
mechanisms. Bioelectromagnetics 38, 497–510 (2017). 11. Yamazaki, Y. & Maute, A. Sq and EEJ – a review on the daily variation of the geomagnetic field caused by ionospheric dynamo currents. Space Sci. Rev. 206, 299–405 (2017). 12. Solov’yov, I. A., Chandler, D. E. & Schulten, K. Magnetic field effects in Arabidopsis thaliana cryptochrome-1. Biophys. J. 92, 2711–2726 (2007). 13. Hore, P. J., & Mouritsen, H. The radical-pair mechanism of magnetoreception. Annu. Rev. Biophys. 45, 299–344 (2016). 14. Brown, F. A. & Scow, K. M. Magnetic induction of a circadian cycle in hamsters. J.
Interdiscipl. Cycle Res. 9, 137–145 (1978). 15. Welker, H. A. et al. Effects of an artificial magnetic-field on serotonin-n- acetyltransferase activity and melatonin content of the rat pineal gland. Exp. Brain Res. 50, 426– 432 (1983). 16. Wan, G. J. et al. Cryptochromes and hormone signal transduction under near-zero magnetic fields: new clues to magnetic field effects in a rice planthopper. PLOS one 10(7), e0132966 https://doi.org/10.1371/journal.pone.0132966 (2015). 17. Krylov, V. V. et al. The effect of a temporal shift in diurnal geomagnetic variation on roach Rutilus rutilus L. embryos: a comparison with effects of simulated geomagnetic storms. Biophysics 62, 675–681 https://doi.org/10.1134/S0006350917040121 (2017). 18. Agliassa, C., Maffei, M. E. Reduction of geomagnetic field (GMF) to near null magnetic field (NNMF) affects some Arabidopsis thaliana clock genes amplitude in a light independent manner. J. Plant Physiol. 232, 23–26 https://doi.org/10.1016/j.jplph.2018.11.008 (2019). 19. Krylov, V. V., Kantserova, N. P., Lysenko, L. A. & Osipova, E. A. A simulated geomagnetic storm unsynchronizes with diurnal geomagnetic variation affecting calpain activity in 241–246 Int. |
great https://doi.org/10.1007/s00484-018-01657-y (2019). Biometeorol. 63(2), roach snail. pond and J. 20. Krylov, V. V., Papchenkova, G. A. & Osipova, E. A. The influence of changes in traits of Daphnia magna. life‐history
20. Krylov, V. V., Papchenkova, G. A. & Osipova, E. A. The influence of changes in traits of Daphnia magna. life‐history
21. Cahill, G. M. Circadian regulation of melatonin production in cultured zebrafish pineal
and retina. Brain Res. 708(1–2), 177–181 (1996). 22. Lima-Cabello, E. et al. A review of the melatonin functions in zebrafish physiology. J.
Pineal Res. 57, 1–9 (2014). 23. Whitmore, D., Foulkes, N., Strähle, U. & Sassone-Corsi, P. Zebrafish Clock rhythmic expression reveals independent peripheral circadian oscillators. Nat. Neurosci. 1, 701–707 (1998). 24. Cermakian, N., Whitmore, D., Foulkes, N. S. & Sassone-Corsi, P. Asynchronous oscillations of two zebrafish CLOCK partners reveal differential clock control and function. PNAS 97(8), 4339–4344 (2000). 25. Khan, Z. A. et al. Melatonin biosynthesizing enzyme genes and clock genes in ovary and whole brain of zebrafish (Danio rerio): Differential expression and a possible interplay. Gen. Comp. Endocrinol. 233, 16–31 (2016). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 26. Krylov, V. V., Izvekov, E. I., Pavlova, V. V., Pankova, N. A. & Osipova, E. A. Circadian rhythms in zebrafish (Danio rerio) behaviour and the sources of their variability. Biol. Rev. 96(3), 785–797 https://doi.org/10.1111/brv.12678 (2021). 27. Krylov, V. V. et al. An experimental study of the biological effects of geomagnetic disturbances: The impact of a typical geomagnetic storm and its constituents on plants and animals. J. Atmos. Sol.-Terr. Phys. 110-111, 28–36 https://doi.org/10.1016/j.jastp.2014.01.020 (2014). 28. Audira, G. et al. Establishing simple image-based methods and a cost-effective instrument for toxicity assessment on circadian rhythm dysregulation in fish. Biol. Open 8, bio041871 https://doi.org/10.1242/bio.041871 (2019). 29. Sarasamma, S. et al. Evaluation of the effects of carbon 60 nanoparticle exposure to adult zebrafish: a behavioral and biochemical approach to elucidate the mechanism of toxicity. Int. J. Mol. Sci. 19, e3853 https://doi.org/10.3390/ijms19123853 (2018). 30. Malhotra, N. et al. Ecotoxicity assessment of Fe3O4 magnetic nanoparticle exposure in adult zebrafish at an environmental pertinent concentration by behavioral and biochemical testing. Nanomaterials 9, e873 https://doi.org/10.3390/nano9060873 (2019). 31. Pérez-Escudero, A., Vicente-Page, J., Hinz, R. C., Arganda, S. & de Polavieja, G. G. idTracker: tracking individuals in a group by automatic identification of unmarked animals. Nat. Methods 11, 743–748 https://doi.org/10.1038/nmeth.2994 (2014). 32. |
Noldus, L. P., Spink, A. J. & Tegelenbosch, R. A. EthoVision: a versatile video tracking system for automation of behavioral experiments. Behav. Res. Methods Instrum. Comput. 33, 398–414 https://doi.org/10.3758/bf03195394 (2001). 33. Shenk, J., Lohkamp, K. J., Wiesmann, M. & Kiliaan, A. J. Automated analysis of 518 Neurosci. trajectory Front. Traja. with data 14,
stroke mouse https://doi.org/10.3389/fnins.2020.00518 (2020). 34. Abhilash, L. & Sheeba, V. RhythmicAlly: your R and Shiny-based open-source ally for 551–561 J. analysis biological rhythms. Rhythms 34(5), Biol. of
the https://doi.org/10.1177/0748730419862474 (2019). 35. Tackenberg, M. C. & Hughey, J. J. The risks of using the chi-square periodogram to rhythms. PLOS Comput. Biol. 17(1), e1008567 the period of biological
35. Tackenberg, M. C. & Hughey, J. J. The risks of using the chi-square periodogram to rhythms. PLOS Comput. Biol. 17(1), e1008567 the period of biological
36. Cornelissen, G. Cosinor-based rhythmometry. Theor. Biol. Med. Model. 11, 16
https://doi.org/10.1186/1742-4682-11-16 (2014). 37. Burton, C. E., Zhou, Y., Bai, Q. & Burton, E. A. Spectral properties of the zebrafish
visual motor response. Neurosci. Lett. 646, 62–67 (2017). 38. Hurd, M. W., Debruyne, J., Straume, M. & Cahill, G. M. Circadian rhythms of
locomotor activity in zebrafish. Physiol. Behav. 65, 465–472 (1998). 39. López‐Olmeda, J. F., Madrid, J. A. & Sánchez‐Vázquez, F. J. Light and temperature cycles as zeitgebers of zebrafish (Danio rerio) circadian activity rhythms. Chronobiol. Int. 23(3), 537–550 https://doi.org/10.1080/07420520600651065 (2006). 40. del Pozo, A., Sánchez-Férez, J. A. & Sánchez-Vázquez, F. J. Circadian rhythms of self- feeding and locomotor activity in zebrafish (Danio rerio). Chronobiol. Int. 28(1), 39–47 https://doi.org/10.3109/07420528.2010.530728 (2011). 41. Bliss, V. L. & Heppner, F. H. Circadian activity rhythm influenced by near zero
magnetic field. Nature 261(5559), 411–412 (1976). 42. Bartos, P. et al. Weak radiofrequency fields affect the insect circadian clock. J. R. Soc. Interface 16, 20190285 http://dx.doi.org/10.1098/rsif.2019.0285 (2019). 43. Demin, K.A. et al. The role of intraspecies variation in fish neurobehavioral and
neuropharmacological phenotypes in aquatic models. Aquat. Toxicol. 210, 44–55 (2019). 44. Osipova, E. A., Pavlova, V. V., Nepomnyashchikh, V. A. & Krylov, V. V. Influence of magnetic field on zebrafish activity and orientation in a plus maze. Behav. Processes 122, 80–86 (2016). bioRxiv preprint
doi:
https://doi.org/10.1101/2021.09.08.459369
;
this version posted September 8, 2021. The copyright holder for this
preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 45. Cresci, A. et al. Zebrafish “personality” influences sensitivity to magnetic fields. Acta
Ethol. 21, 195–201 (2018). 46. Chiou, Y. Y. et al. Mammalian Period represses and de-represses transcription by displacing CLOCK–BMAL1 from promoters in a Cryptochrome-dependent manner. |
Subsets and Splits