101
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Luo G, Gao Q, Zhang S, Yan B. Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives. Comput Struct Biotechnol J 2020; 18:2962-2971. [PMID: 33106757 PMCID: PMC7577221 DOI: 10.1016/j.csbj.2020.10.016] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/12/2020] [Accepted: 10/13/2020] [Indexed: 02/07/2023] Open
Abstract
The increasing application of single-cell RNA sequencing (scRNA-seq) technology in life science and biomedical research has significantly increased our understanding of the cellular heterogeneities in immunology, oncology and developmental biology. This review will summarize the development of various scRNA-seq technologies; primarily discussing the application of scRNA-seq on infectious diseases, and exploring the current development, challenges, and potential applications of scRNA-seq technology in the future.
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Key Words
- 3C, Chromosome Conformation Capture
- ACE2, Angiotensin-Converting Enzyme 2
- ARDS, acute respiratory distress syndrome
- ATAC-seq, Assay for Transposase-Accessible Chromatin using sequencing
- BCR, B cell receptor
- CEL-seq, Cell Expression by Linear amplification and Sequencing
- CLU, clusterin
- COVID-19, corona virus disease 2019
- CRISPR, Clustered Regularly Interspaced Short Palindromic Repeats
- CytoSeq, gene expression cytometry
- DENV, dengue virus
- FACS, fluorescence-activated cell sorting
- GNLY, granulysin
- GO analysis, Gene Ontology analysis
- HIV, Human Immunodeficiency Virus
- IAV, Influenza A virus
- IGHV/HD/HJ/HC, Immune globulin heavy V/D/J/C/ region
- IGLV/LJ/LC, Immune globulin light V/J/C/ region
- ILC, Innate Lymphoid Cell
- Infectious diseases
- LIGER, Linked Inference of Genomics Experimental Relationships
- MAGIC, Markov Affinity-based Graph Imputation of Cells
- MARS-seq, Massively parallel single-cell RNA sequencing
- MATCHER, Manifold Alignment To CHaracterize Experimental Relationships
- MCMV, mouse cytomegalovirus
- MERFISH, Multiplexed, Error Robust Fluorescent In Situ Hybridization
- MLV, Moloney Murine Leukemia Virus
- MOFA, Multi-Omics Factor Analysis
- MOI, multiplicity of infection
- PBMCs, peripheral blood mononuclear cells
- PLAC8, placenta-associated 8
- SARS-CoV-2, severe acute respiratory syndrome coronavirus 2
- SAVER, Single-cell Analysis Via Expression Recovery
- SPLit-seq, split pool ligation-based tranome sequencing
- STARTRAC, Single T-cell Analysis by RNA sequencing and TCR TRACking
- STRT-seq, Single-cell Tagged Reverse Transcription sequencing
- Single-cell RNA sequencing
- TCR, T cell receptor
- TSLP, thymic stromal lymphopoietin
- UMAP, Uniform Manifold Approximation and Projection
- UMI, Unique Molecular Identifier
- mcSCRB-seq, molecular crowding single-cell RNA barcoding and sequencing
- pDCs, plasmacytoid dendritic cells
- scRNA-seq, single cell RNA sequencing technology
- sci-RNA-seq, single-cell combinatorial indexing RNA sequencing
- seqFISH, sequential Fluorescent In Situ Hybridization
- smart-seq, switching mechanism at 5′ end of the RNA transcript sequencing
- t-SNE, t-Distributed stochastic neighbor embedding
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Affiliation(s)
- Geyang Luo
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
- Shanghai Public Health Clinical Center and Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Medical College and School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Qian Gao
- Shanghai Public Health Clinical Center and Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Medical College and School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Shuye Zhang
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Bo Yan
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
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102
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Ribeiro MM, Okawa S, Del Sol A. TransSynW: A single-cell RNA-sequencing based web application to guide cell conversion experiments. Stem Cells Transl Med 2020; 10:230-238. [PMID: 33125830 PMCID: PMC7848352 DOI: 10.1002/sctm.20-0227] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/03/2020] [Accepted: 08/16/2020] [Indexed: 12/16/2022] Open
Abstract
Generation of desired cell types by cell conversion remains a challenge. In particular, derivation of novel cell subtypes identified by single‐cell technologies will open up new strategies for cell therapies. The recent increase in the generation of single‐cell RNA‐sequencing (scRNA‐seq) data and the concomitant increase in the interest expressed by researchers in generating a wide range of functional cells prompted us to develop a computational tool for tackling this challenge. Here we introduce a web application, TransSynW, which uses scRNA‐seq data for predicting cell conversion transcription factors (TFs) for user‐specified cell populations. TransSynW prioritizes pioneer factors among predicted conversion TFs to facilitate chromatin opening often required for cell conversion. In addition, it predicts marker genes for assessing the performance of cell conversion experiments. Furthermore, TransSynW does not require users' knowledge of computer programming and computational resources. We applied TransSynW to different levels of cell conversion specificity, which recapitulated known conversion TFs at each level. We foresee that TransSynW will be a valuable tool for guiding experimentalists to design novel protocols for cell conversion in stem cell research and regenerative medicine.
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Affiliation(s)
- Mariana Messias Ribeiro
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, Luxembourg
| | - Satoshi Okawa
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, Luxembourg.,Integrated BioBank of Luxembourg, Dudelange, Luxembourg
| | - Antonio Del Sol
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Belvaux, Luxembourg.,CIC bioGUNE, Bizkaia Technology Park, Derio, Spain.,IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
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103
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Niu X, Li S, Li P, Pan W, Wang Q, Feng Y, Mo X, Yan Q, Ye X, Luo J, Qu L, Weber D, Byrne-Steele ML, Wang Z, Yu F, Li F, Myers RM, Lotze MT, Zhong N, Han J, Chen L. Longitudinal Analysis of T and B Cell Receptor Repertoire Transcripts Reveal Dynamic Immune Response in COVID-19 Patients. Front Immunol 2020; 11:582010. [PMID: 33117392 PMCID: PMC7561365 DOI: 10.3389/fimmu.2020.582010] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 09/15/2020] [Indexed: 01/08/2023] Open
Abstract
Severe COVID-19 is associated with profound lymphopenia and an elevated neutrophil to lymphocyte ratio. We applied a novel dimer avoidance multiplexed polymerase chain reaction next-generation sequencing assay to analyze T (TCR) and B cell receptor (BCR) repertoires. Surprisingly, TCR repertoires were markedly diminished during the early onset of severe disease but recovered during the convalescent stage. Monitoring TCR repertoires could serve as an indicative biomarker to predict disease progression and recovery. Panoramic concurrent assessment of BCR repertoires demonstrated isotype switching and a transient but dramatic early IgA expansion. Dominant B cell clonal expansion with decreased diversity occurred following recovery from infection. Profound changes in T cell homeostasis raise critical questions about the early events in COVID-19 infection and demonstrate that immune repertoire analysis is a promising method for evaluating emergent host immunity to SARS-CoV-2 viral infection, with great implications for assessing vaccination and other immunological therapies.
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Affiliation(s)
- Xuefeng Niu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Song Li
- Jiangsu Industrial Technology Research Institute (JITRI), Applied Adaptome Immunology Institute, Nanjing, China.,iRepertoire Inc., Huntsville, AL, United States
| | - Pingchao Li
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Wenjing Pan
- iRepertoire Inc., Huntsville, AL, United States.,HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Qian Wang
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Ying Feng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaoneng Mo
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Qihong Yan
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Xianmiao Ye
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Jia Luo
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Linbing Qu
- Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | | | | | - Zhe Wang
- Jiangsu Industrial Technology Research Institute (JITRI), Applied Adaptome Immunology Institute, Nanjing, China
| | - Fengjia Yu
- Jiangsu Industrial Technology Research Institute (JITRI), Applied Adaptome Immunology Institute, Nanjing, China
| | - Fang Li
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Michael T Lotze
- Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
| | - Nanshan Zhong
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jian Han
- Jiangsu Industrial Technology Research Institute (JITRI), Applied Adaptome Immunology Institute, Nanjing, China.,iRepertoire Inc., Huntsville, AL, United States.,HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Ling Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.,Guangzhou Regenerative Medicine and Health-Guangdong Laboratory (GRMH-GDL), Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
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104
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Abstract
Advances in reading, writing, and editing DNA are providing unprecedented insights into the complexity of immunological systems. This combination of systems and synthetic biology methods is enabling the quantitative and precise understanding of molecular recognition in adaptive immunity, thus providing a framework for reprogramming immune responses for translational medicine. In this review, we will highlight state-of-the-art methods such as immune repertoire sequencing, immunoinformatics, and immunogenomic engineering and their application toward adaptive immunity. We showcase novel and interdisciplinary approaches that have the promise of transforming the design and breadth of molecular and cellular immunotherapies.
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Affiliation(s)
- Lucia Csepregi
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Roy A. Ehling
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Bastian Wagner
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
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105
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Amato M, Werba JP, Frigerio B, Coggi D, Sansaro D, Ravani A, Ferrante P, Veglia F, Tremoli E, Baldassarre D. Relationship between Influenza Vaccination Coverage Rate and COVID-19 Outbreak: An Italian Ecological Study. Vaccines (Basel) 2020; 8:E535. [PMID: 32947988 PMCID: PMC7563271 DOI: 10.3390/vaccines8030535] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 09/11/2020] [Accepted: 09/12/2020] [Indexed: 12/21/2022] Open
Abstract
Background: The lack of specific vaccines or drugs against coronavirus disease 2019 (COVID-19) warrants studies focusing on alternative clinical approaches to reduce the spread of this pandemic disease. In this study, we investigated whether anti-influenza vaccination plays a role in minimizing the diffusion of COVID-19 in the Italian population aged 65 and over. Methods: Four COVID-19 outcomes were used: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence, hospitalizations for COVID-19 symptoms, admissions to intensive care units for reasons related to SARS-CoV-2, and deaths attributable to COVID-19. Results: At univariate analyses, the influenza vaccination coverage rates correlated negatively with all COVID-19 outcomes (Beta ranging from -134 to -0.61; all p < 0.01). At multivariable analyses, influenza vaccination coverage rates correlated independently with SARS-CoV-2 seroprevalence (Beta (95% C.I.): -130 (-198, -62); p = 0.001), hospitalizations for COVID-19 symptoms (Beta (95% C.I.): -4.16 (-6.27, -2.05); p = 0.001), admission to intensive care units for reasons related to SARS-CoV-2 (Beta (95% C.I.): -0.58 (-1.05, -0.12); p = 0.017), and number of deaths attributable to COVID-19 (Beta (95% C.I.): -3.29 (-5.66, -0.93); p = 0.010). The R2 observed in the unadjusted analysis increased from 82% to 159% for all the considered outcomes after multivariable analyses. Conclusions: In the Italian population, the coverage rate of the influenza vaccination in people aged 65 and over is associated with a reduced spread and a less severe clinical expression of COVID-19. This finding warrants ad hoc studies to investigate the role of influenza vaccination in preventing the spread of COVID-19.
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Affiliation(s)
- Mauro Amato
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - José Pablo Werba
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Beatrice Frigerio
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Daniela Coggi
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, 20133 Milan, Italy
| | - Daniela Sansaro
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Alessio Ravani
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Palma Ferrante
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Fabrizio Veglia
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Elena Tremoli
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
| | - Damiano Baldassarre
- Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy; (M.A.); (J.P.W.); (B.F.); (D.C.); (D.S.); (A.R.); (P.F.); (F.V.); (E.T.)
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, 20129 Milan, Italy
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106
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Horns F, Quake SR. Cloning antibodies from single cells in pooled sequence libraries by selective PCR. PLoS One 2020; 15:e0236477. [PMID: 32756607 PMCID: PMC7406036 DOI: 10.1371/journal.pone.0236477] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/06/2020] [Indexed: 11/19/2022] Open
Abstract
Antibodies function by binding to antigens. Antibodies must be cloned and expressed to determine their binding characteristics, but current methods for high-throughput antibody sequencing yield antibody DNA pooled from many cells and do not readily permit cloning of antibodies from single B cells. We present a strategy for retrieving and cloning antibody DNA from single cells within a pooled library of cells. Our strategy, called selective PCR for antibody retrieval (SPAR), takes advantage of the unique sequence barcodes attached to individual cDNA molecules during sample preparation to enable specific amplification by PCR of antibody heavy- and light-chain cDNA originating from a single cell. We show through computational analysis that most human antibodies sequenced using typical high-throughput methods can be retrieved using SPAR, and experimentally demonstrate retrieval of full-length antibody variable region cDNA from three cells within pools of ~5,000 cells. SPAR enables rapid low-cost cloning and expression of native human antibodies from pooled single-cell sequence libraries for functional characterization.
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Affiliation(s)
- Felix Horns
- Biophysics Graduate Program, Stanford University, Stanford, California, United States of America
| | - Stephen R. Quake
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
- Department of Applied Physics, Stanford University, Stanford, California, United States of America
- Chan Zuckerberg Biohub, Stanford, California, United States of America
- * E-mail:
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107
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Dangerous Liaisons: Gammaherpesvirus Subversion of the Immunoglobulin Repertoire. Viruses 2020; 12:v12080788. [PMID: 32717815 PMCID: PMC7472090 DOI: 10.3390/v12080788] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 02/06/2023] Open
Abstract
A common biologic property of the gammaherpesviruses Epstein–Barr Virus and Kaposi sarcoma herpesvirus is their use of B lymphocytes as a reservoir of latency in healthy individuals that can undergo oncogenic transformation later in life. Gammaherpesviruses (GHVs) employ an impressive arsenal of proteins and non-coding RNAs to reprogram lymphocytes for proliferative expansion. Within lymphoid tissues, the germinal center (GC) reaction is a hub of B cell proliferation and death. The goal of a GC is to generate and then select for a pool of immunoglobulin (Ig) genes that will provide a protective humoral adaptive immune response. B cells infected with GHVs are detected in GCs and bear the hallmark signatures of the mutagenic processes of somatic hypermutation and isotype class switching of the Ig genes. However, data also supports extrafollicular B cells as a reservoir engaged by GHVs. Next-generation sequencing technologies provide unprecedented detail of the Ig sequence that informs the natural history of infection at the single cell level. Here, we review recent reports from human and murine GHV systems that identify striking differences in the immunoglobulin repertoire of infected B cells compared to their uninfected counterparts. Implications for virus biology, GHV-associated cancers, and host immune dysfunction will be discussed.
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108
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Yermanos A, Sandu I, Pedrioli A, Borsa M, Wagen F, Oetiker N, Welten SPM, Pallmer K, Reddy ST, Oxenius A. Profiling Virus-Specific Tcf1+ T Cell Repertoires During Acute and Chronic Viral Infection. Front Immunol 2020; 11:986. [PMID: 32547546 PMCID: PMC7272574 DOI: 10.3389/fimmu.2020.00986] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 04/27/2020] [Indexed: 12/19/2022] Open
Abstract
CD8 T cells play a crucial role in providing protection from viral infections. It has recently been established that a subset of CD8 T cells expressing Tcf1 are responsible for sustaining exhausted T cells during chronic lymphocytic choriomeningitis virus (LCMV) infection. Many of these studies, however, have been performed using T cell receptor (TCR) transgenic mice, in which CD8 T cells express a monoclonal TCR specific for the LCMV glycoprotein. To investigate whether the Tcf1+ and Tcf1- repertoires are naturally composed of similar or different clones in wild-type mice exposed to acute or chronic LCMV infection, we performed TCR repertoire sequencing of virus-specific CD8 T cells, including Tcf1+ and Tcf1- populations. Our analysis revealed that the Tcf1+ TCR repertoire is maintained at an equal or higher degree of clonal diversity despite harboring fewer cells. Additionally, within the same animal, there was extensive clonal overlap between the Tcf1+ and Tcf1- repertoires in both chronic and acute LCMV infection. We could further detect these virus-specific clones in longitudinal blood samples earlier in the infection. With respect to common repertoire parameters (clonal overlap, germline gene usage, and clonal expansion), we found minor differences between the virus-specific TCR repertoire of acute and chronic LCMV infection 40 days post infection. Overall, our results indicate that the Tcf1+ population emerging during chronic LCMV infection is not clonally distinct from the Tcf1- population, supporting the notion that the Tcf1+ pool is indeed a fuel for the more exhausted Tcf1- population within the heterogenous repertoire of LCMV-specific CD8 T cells.
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Affiliation(s)
- Alexander Yermanos
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | - Ioana Sandu
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | | | - Mariana Borsa
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland
| | | | | | | | | | - Sai T. Reddy
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
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109
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Yermanos A, Kräutler NJ, Pedrioli A, Menzel U, Greiff V, Stadler T, Oxenius A, Reddy ST. IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status. Front Cell Infect Microbiol 2020; 10:254. [PMID: 32547966 PMCID: PMC7270205 DOI: 10.3389/fcimb.2020.00254] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 04/30/2020] [Indexed: 01/11/2023] Open
Abstract
Antibody repertoire sequencing provides a molecular fingerprint of current and past pathogens encountered by the immune system. Most repertoire studies in humans require measuring the B cell response in the blood, resulting in a large bias to the IgM isotype. The extent to which the circulating IgM antibody repertoire correlates to lymphoid tissue-resident B cells in the setting of viral infection remains largely uncharacterized. Therefore, we compared the IgM repertoires from both blood and bone marrow (BM) plasma cells (PCs) following acute or chronic lymphocytic choriomeningitis virus (LCMV) infection in mice. Despite previously reported serum alterations between acute and chronic infection, IgM repertoire signatures based on clonal diversity metrics, public clones, network, and phylogenetic analysis were largely unable to distinguish infection cohorts. Our findings, however, revealed mouse-specific repertoire fingerprints between the blood and PC repertoires irrespective of infection status.
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Affiliation(s)
- Alexander Yermanos
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland.,Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | | | | | - Ulrike Menzel
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Tanja Stadler
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | | | - Sai T Reddy
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
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110
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Cao Y, Su B, Guo X, Sun W, Deng Y, Bao L, Zhu Q, Zhang X, Zheng Y, Geng C, Chai X, He R, Li X, Lv Q, Zhu H, Deng W, Xu Y, Wang Y, Qiao L, Tan Y, Song L, Wang G, Du X, Gao N, Liu J, Xiao J, Su XD, Du Z, Feng Y, Qin C, Qin C, Jin R, Xie XS. Potent Neutralizing Antibodies against SARS-CoV-2 Identified by High-Throughput Single-Cell Sequencing of Convalescent Patients' B Cells. Cell 2020; 182:73-84.e16. [PMID: 32425270 PMCID: PMC7231725 DOI: 10.1016/j.cell.2020.05.025] [Citation(s) in RCA: 973] [Impact Index Per Article: 194.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 05/07/2020] [Accepted: 05/13/2020] [Indexed: 12/28/2022]
Abstract
The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here, we report the rapid identification of SARS-CoV-2-neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients. From 8,558 antigen-binding IgG1+ clonotypes, 14 potent neutralizing antibodies were identified, with the most potent one, BD-368-2, exhibiting an IC50 of 1.2 and 15 ng/mL against pseudotyped and authentic SARS-CoV-2, respectively. BD-368-2 also displayed strong therapeutic and prophylactic efficacy in SARS-CoV-2-infected hACE2-transgenic mice. Additionally, the 3.8 Å cryo-EM structure of a neutralizing antibody in complex with the spike-ectodomain trimer revealed the antibody’s epitope overlaps with the ACE2 binding site. Moreover, we demonstrated that SARS-CoV-2-neutralizing antibodies could be directly selected based on similarities of their predicted CDR3H structures to those of SARS-CoV-neutralizing antibodies. Altogether, we showed that human neutralizing antibodies could be efficiently discovered by high-throughput single B cell sequencing in response to pandemic infectious diseases.
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Affiliation(s)
- Yunlong Cao
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Bin Su
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Xianghua Guo
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Wenjie Sun
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Yongqiang Deng
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China
| | - Linlin Bao
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Qinyu Zhu
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences (CLS), Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Xu Zhang
- Singlomics (Beijing DanXu Pharmaceuticals), Beijing 102206, China
| | - Yinghui Zheng
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Chenyang Geng
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Xiaoran Chai
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Runsheng He
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | - Xiaofeng Li
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China
| | - Qi Lv
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Hua Zhu
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Wei Deng
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Yanfeng Xu
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Yanjun Wang
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Luxin Qiao
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Yafang Tan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China
| | - Liyang Song
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China; State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Guopeng Wang
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Xiaoxia Du
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China; State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Ning Gao
- Peking-Tsinghua Center for Life Sciences (CLS), Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
| | - Jiangning Liu
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | - Junyu Xiao
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China; Peking-Tsinghua Center for Life Sciences (CLS), Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Xiao-Dong Su
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China; State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China
| | - Zongmin Du
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China
| | - Yingmei Feng
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Chuan Qin
- Key Laboratory of Human Disease Comparative Medicine, Chinese Ministry of Health, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China.
| | - Chengfeng Qin
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
| | - Ronghua Jin
- Beijing Youan Hospital, Capital Medical University, Beijing 100069, China.
| | - X Sunney Xie
- Beijing Advanced Innovation Center for Genomics (ICG) & Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China; Peking-Tsinghua Center for Life Sciences (CLS), Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; School of Life Sciences, Peking University, Beijing 100871, China.
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Salem ML, El-Hennawy D. The possible beneficial adjuvant effect of influenza vaccine to minimize the severity of COVID-19. Med Hypotheses 2020; 140:109752. [PMID: 32361099 PMCID: PMC7194943 DOI: 10.1016/j.mehy.2020.109752] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 04/21/2020] [Indexed: 02/07/2023]
Affiliation(s)
- Mohamed Labib Salem
- Immunology and Biotechnology Unit, Department of Zoology, Faculty of Science, Tanta University, Tanta, Egypt; Center of Excellence in Cancer Research, Tanta University Teaching Hospital, Tanta University, Tanta, Egypt.
| | - Dina El-Hennawy
- Center of Excellence in Cancer Research, Tanta University Teaching Hospital, Tanta University, Tanta, Egypt; First Health Office, Basyun Central Hospital, Basyun, AlGharbiya, Egypt.
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