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Hudson D, Lubbock A, Basham M, Koohy H. A comparison of clustering models for inference of T cell receptor antigen specificity. IMMUNOINFORMATICS (AMSTERDAM, NETHERLANDS) 2024; 13:None. [PMID: 38525047 PMCID: PMC10955519 DOI: 10.1016/j.immuno.2024.100033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 01/23/2024] [Indexed: 03/26/2024]
Abstract
The vast potential sequence diversity of TCRs and their ligands has presented an historic barrier to computational prediction of TCR epitope specificity, a holy grail of quantitative immunology. One common approach is to cluster sequences together, on the assumption that similar receptors bind similar epitopes. Here, we provide the first independent evaluation of widely used clustering algorithms for TCR specificity inference, observing some variability in predictive performance between models, and marked differences in scalability. Despite these differences, we find that different algorithms produce clusters with high degrees of similarity for receptors recognising the same epitope. Our analysis strengthens the case for use of clustering models to identify signals of common specificity from large repertoires, whilst highlighting scope for improvement of complex models over simple comparators.
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Affiliation(s)
- Dan Hudson
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- The Rosalind Franklin Institute, Didcot, UK
| | | | | | - Hashem Koohy
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Alan Turning Fellow in Health and Medicine, UK
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2
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Tranter E, Frentsch M, Hütter-Krönke ML, Vuong GL, Busch D, Loyal L, Henze L, Rosnev S, Blau IW, Thiel A, Beule D, Bullinger L, Obermayer B, Na IK. Comparable CD8 + T-cell responses to SARS-CoV-2 vaccination in single-cell transcriptomics of recently allogeneic transplanted patients and healthy individuals. J Med Virol 2024; 96:e29539. [PMID: 38516755 DOI: 10.1002/jmv.29539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 03/23/2024]
Abstract
Despite extensive research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination responses in healthy individuals, there is comparatively little known beyond antibody titers and T-cell responses in the vulnerable cohort of patients after allogeneic hematopoietic stem cell transplantation (ASCT). In this study, we assessed the serological response and performed longitudinal multimodal analyses including T-cell functionality and single-cell RNA sequencing combined with T cell receptor (TCR)/B cell receptor (BCR) profiling in the context of BNT162b2 vaccination in ASCT patients. In addition, these data were compared to publicly available data sets of healthy vaccinees. Protective antibody titers were achieved in 40% of patients. We identified a distorted B- and T-cell distribution, a reduced TCR diversity, and increased levels of exhaustion marker expression as possible causes for the poorer vaccine response rates in ASCT patients. Immunoglobulin heavy chain gene rearrangement after vaccination proved to be highly variable in ASCT patients. Changes in TCRα and TCRβ gene rearrangement after vaccination differed from patterns observed in healthy vaccinees. Crucially, ASCT patients elicited comparable proportions of SARS-CoV-2 vaccine-induced (VI) CD8+ T-cells, characterized by a distinct gene expression pattern that is associated with SARS-CoV-2 specificity in healthy individuals. Our study underlines the impaired immune system and thus the lower vaccine response rates in ASCT patients. However, since protective vaccine responses and VI CD8+ T-cells can be induced in part of ASCT patients, our data advocate early posttransplant vaccination due to the high risk of infection in this vulnerable group.
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Affiliation(s)
- Eva Tranter
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Marco Frentsch
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- BIH Center for Regenerative Therapies, Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Marie Luise Hütter-Krönke
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Giang Lam Vuong
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - David Busch
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Lucie Loyal
- Si-M/"Der Simulierte Mensch", A Science Framework of Technische Universität Berlin and Charité-Universitätsmedizin Berlin, Berlin, Germany
- BIH Center of Immunomics-Regenerative Immunology and Aging, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Larissa Henze
- Si-M/"Der Simulierte Mensch", A Science Framework of Technische Universität Berlin and Charité-Universitätsmedizin Berlin, Berlin, Germany
- BIH Center of Immunomics-Regenerative Immunology and Aging, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stanislav Rosnev
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Igor-Wolfgang Blau
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Thiel
- Si-M/"Der Simulierte Mensch", A Science Framework of Technische Universität Berlin and Charité-Universitätsmedizin Berlin, Berlin, Germany
- BIH Center of Immunomics-Regenerative Immunology and Aging, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Dieter Beule
- Core Unit Bioinformatics, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Lars Bullinger
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
- ECRC Experimental and Clinical Research Center, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Benedikt Obermayer
- Core Unit Bioinformatics, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Il-Kang Na
- Medizinische Klinik m. S. Hämatologie, Onkologie und Tumorimmunologie, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- BIH Center for Regenerative Therapies, Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
- Si-M/"Der Simulierte Mensch", A Science Framework of Technische Universität Berlin and Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
- ECRC Experimental and Clinical Research Center, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany
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3
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Saidi A, Safaeizadeh M, Hajibarat Z. Differential expression of the genes encoding immune system components in response to Pseudomonas syringae and Pseudomonas aeruginosa in Arabidopsis thaliana. 3 Biotech 2024; 14:11. [PMID: 38098678 PMCID: PMC10716095 DOI: 10.1007/s13205-023-03852-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 11/08/2023] [Indexed: 12/17/2023] Open
Abstract
In innate immunity, the first layer of defense against any microbial infection is triggered by the perception of pathogen-associated molecular patterns by highly specific pattern recognition receptors. The Pseudomonas syringae pv. tomato and Pseudomonas aeruginosa are plant-pathogenic bacterial species that include pathogenic strains in a wide range of different plant species. In the current study, extensive analysis including gene expression of 12 hub genes, gene ontology, protein-protein interaction, and cis-element prediction to dissect the Arabidopsis response to above-mentioned bacteria were performed. Further, we evaluated weighted co-expression network analysis (WGCNA) in the wild-type plants and coi-1 mutant line and determined changes in responsive genes at two time-points (4 and 8 h) of post-treatment with P. syringae and P. aeruginosa. Compared to the wild-type plants, coi-1 mutant showed significant expression in most of the genes involved, indicating that their protein products have important role in innate immunity and RNA silencing pathways. Our findings showed that 12 hub genes were co-expressed in response to P. syringae and P. aeruginosa infections. Based on the network analysis, transcription factors, receptors, protein kinase, and pathogenesis-related protein (PR1) were involved in the immunity system. Gene ontology related to each module was involved in defense response, protein serine kinase activity, and primary miRNA processing. Based on the cis-elements prediction, MYB, MYC, WRE3, W-box, STRE, and ARE contained the most number of cis-elements in co-expressed network genes. Also, in coi-1 mutant, most responsive genes against theses pathogens were up-regulated. The knowledge gained in the gene expression analysis in response to P. syringae and P. aeruginosa in the model plant, i.e., Arabidopsis, is essential to allow us to gain more insight about the innate immunity in other crops.
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Affiliation(s)
- Abbas Saidi
- Department of Cell and Molecular Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Mehdi Safaeizadeh
- Department of Cell and Molecular Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Zohreh Hajibarat
- Department of Cell and Molecular Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
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Ma X, Zhuo Y, Huang Y, He P, Huang Z, Jiang L, Tong L, Yao X, Wen X, Zhong X, Yang S, Li C, Liu Y, Zhang Z. Reduced Diversities and Clonally Expanded Sequences of T-Cell Receptors in Patients With Essential Hypertension and Subclinical Carotid Atherosclerosis. Hypertension 2023; 80:2318-2329. [PMID: 37551594 DOI: 10.1161/hypertensionaha.123.21112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 07/23/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND It has long been hypothesized that the abnormal immune responses contribute to the essential hypertension (EH) and its subclinical target organ damage (STOD). However, the mechanism is unclear. This study aimed at exploring the potential association with abnormal T-cell responses and EH, STOD, and early atherosclerosis in patients with EH. METHODS This cross-sectional study included 146 patients with EH and 73 age-matched normotensive individuals. The expressed peripheral TCR (T-cell receptor) β repertoire was analyzed by high through-put sequencing. RESULTS The TCRβ repertoires of the patients with EH were significantly different, with significantly elevated certain TCR beta variable (TRBV) and joint (TRBJ) gene usages, significantly reduced TCRβ diversity indexes (diversity 50s) and numbers of total TCRβ clonal types, significantly elevated percentages of the biggest TCRβ clones and numbers of clones accounting >0.1% sequences, compared with those in the normotensive controls. Decreased diversity 50s and increased biggest TCRβ clone percentages were independently correlated with carotid intima-media thickness and subclinical carotid atherosclerosis (SCA) in the patients with EH. Moreover, the diversity 50s were further significantly reduced and the biggest TCRβ clone percentages were significantly increased in the patients with EH with SCA (n=89) comparing to the patients with EH/patients without SCA (n=57), and in patients with EH/SCA with carotid plaque (n=22) comparing to patients with EH/SCA/patients without carotid plaque (n=67). Importantly, specific TCRβ clones were identified in different subgroups of the patients with EH. CONCLUSIONS These results reveal that abnormal T-cell responses may play important roles in the progression of EH and its SCA, especially the formation of carotid plaque. REGISTRATION URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100054414.
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Affiliation(s)
- Xiaoxiang Ma
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Yue Zhuo
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Yu Huang
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Pengming He
- Chengdu ExAb Biotechnology LTD, Chengdu, Sichuan, China (P.H., X.W., X.Z., S.Y., C.L.)
| | - Zhaoyi Huang
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Li Jiang
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Luyao Tong
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Xiaoqin Yao
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Xueping Wen
- Chengdu ExAb Biotechnology LTD, Chengdu, Sichuan, China (P.H., X.W., X.Z., S.Y., C.L.)
| | - Xuemei Zhong
- Chengdu ExAb Biotechnology LTD, Chengdu, Sichuan, China (P.H., X.W., X.Z., S.Y., C.L.)
| | - Shihan Yang
- Chengdu ExAb Biotechnology LTD, Chengdu, Sichuan, China (P.H., X.W., X.Z., S.Y., C.L.)
| | - Changqiong Li
- Chengdu ExAb Biotechnology LTD, Chengdu, Sichuan, China (P.H., X.W., X.Z., S.Y., C.L.)
| | - Yuping Liu
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
| | - Zhixin Zhang
- Department of Health Management & Institute of Health Management, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan (X.M., Y.Z., Y.H., Z.H., L.J., L.T., X.Y., Y.L., Z.Z.)
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Feng B, Zheng D, Yang L, Su Z, Tang L, Zhu Y, Xu X, Wang Q, Lin Q, Hu J, Lin M, Huang L, Zhou X, Liu H, Li S, Pan W, Shi R, Lu Y, Wu B, Ding B, Wang Z, Guo J, Zhang Z, Zheng G, Liu Y. Post-hospitalization rehabilitation alleviates long-term immune repertoire alteration in COVID-19 convalescent patients. Cell Prolif 2023; 56:e13450. [PMID: 36938980 PMCID: PMC10542649 DOI: 10.1111/cpr.13450] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/27/2023] [Accepted: 03/02/2023] [Indexed: 03/21/2023] Open
Abstract
The global pandemic of Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an once-in-a-lifetime public health crisis. Among hundreds of millions of people who have contracted with or are being infected with COVID-19, the question of whether COVID-19 infection may cause long-term health concern, even being completely recovered from the disease clinically, especially immune system damage, needs to be addressed. Here, we performed seven-chain adaptome immune repertoire analyses on convalescent COVID-19 patients who have been discharged from hospitals for at least 6 months. Surprisingly, we discovered lymphopenia, reduced number of unique CDR3s, and reduced diversity of the TCR/BCR immune repertoire in convalescent COVID-19 patients. In addition, the BCR repertoire appears to be activated, which is consistent with the protective antibody titres, but serological experiments reveal significantly lower IL-4 and IL-7 levels in convalescent patients compared to those in healthy controls. Finally, in comparison with convalescent patients who did not receive post-hospitalization rehabilitation, the convalescent patients who received post-hospitalization rehabilitation had attenuated immune repertoire abnormality, almost back to the level of healthy control, despite no detectable clinic demographic difference. Overall, we report the potential long-term immunological impairment for COVID-19 infection, and correction of this impairment via post-hospitalization rehabilitation may offer a new prospect for COVID-19 recovery strategy.
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T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer. Int J Mol Sci 2022; 23:ijms23158590. [PMID: 35955721 PMCID: PMC9369427 DOI: 10.3390/ijms23158590] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/28/2022] [Accepted: 07/29/2022] [Indexed: 11/17/2022] Open
Abstract
The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.
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Kockelbergh H, Evans S, Deng T, Clyne E, Kyriakidou A, Economou A, Luu Hoang KN, Woodmansey S, Foers A, Fowler A, Soilleux EJ. Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19. Diagnostics (Basel) 2022; 12:diagnostics12051222. [PMID: 35626377 PMCID: PMC9140453 DOI: 10.3390/diagnostics12051222] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 01/27/2023] Open
Abstract
Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.
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Affiliation(s)
- Hannah Kockelbergh
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK;
| | - Shelley Evans
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Tong Deng
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Ella Clyne
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Anna Kyriakidou
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 1QP, UK; (A.K.); (A.E.)
| | - Andreas Economou
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 1QP, UK; (A.K.); (A.E.)
| | - Kim Ngan Luu Hoang
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Stephen Woodmansey
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
- Department of Respiratory Medicine, University Hospitals of Morecambe Bay, Kendal LA9 7RG, UK
| | - Andrew Foers
- Kennedy Institute of Rheumatology, University of Oxford, Oxford OX3 7YF, UK;
| | - Anna Fowler
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK;
- Correspondence: (A.F.); (E.J.S.)
| | - Elizabeth J. Soilleux
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
- Correspondence: (A.F.); (E.J.S.)
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