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Dahal-Koirala S, Balaban G, Neumann RS, Scheffer L, Lundin KEA, Greiff V, Sollid LM, Qiao SW, Sandve GK. TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. Brief Bioinform 2022; 23:6513728. [PMID: 35062022 PMCID: PMC8921636 DOI: 10.1093/bib/bbab566] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 12/02/2021] [Accepted: 12/11/2021] [Indexed: 01/19/2023] Open
Abstract
T-cell receptor (TCR) sequencing has enabled the development of innovative diagnostic tests for cancers, autoimmune diseases and other applications. However, the rarity of many T-cell clonotypes presents a detection challenge, which may lead to misdiagnosis if diagnostically relevant TCRs remain undetected. To address this issue, we developed TCRpower, a novel computational pipeline for quantifying the statistical detection power of TCR sequencing methods. TCRpower calculates the probability of detecting a TCR sequence as a function of several key parameters: in-vivo TCR frequency, T-cell sample count, read sequencing depth and read cutoff. To calibrate TCRpower, we selected unique TCRs of 45 T-cell clones (TCCs) as spike-in TCRs. We sequenced the spike-in TCRs from TCCs, together with TCRs from peripheral blood, using a 5′ RACE protocol. The 45 spike-in TCRs covered a wide range of sample frequencies, ranging from 5 per 100 to 1 per 1 million. The resulting spike-in TCR read counts and ground truth frequencies allowed us to calibrate TCRpower. In our TCR sequencing data, we observed a consistent linear relationship between sample and sequencing read frequencies. We were also able to reliably detect spike-in TCRs with frequencies as low as one per million. By implementing an optimized read cutoff, we eliminated most of the falsely detected sequences in our data (TCR α-chain 99.0% and TCR β-chain 92.4%), thereby improving diagnostic specificity. TCRpower is publicly available and can be used to optimize future TCR sequencing experiments, and thereby enable reliable detection of disease-relevant TCRs for diagnostic applications.
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Affiliation(s)
- Shiva Dahal-Koirala
- Corresponding authors: Gabriel Balaban, Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway. Tel.: +4767828200; E-mail: . Shiva Dahal-Koirala, Department of Immunology, University of Oslo, Norway. Tel.: +4723072721; E-mail: ; Geir Kjetil Sandve, Department of Informatics, University of Oslo, Norway. Tel.: +4722840861; E-mail: ; Shuo-Wang Qiao, Department of Immunology, University of Oslo, Norway. Tel.: +4722850533; E-mail:
| | - Gabriel Balaban
- Corresponding authors: Gabriel Balaban, Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway. Tel.: +4767828200; E-mail: . Shiva Dahal-Koirala, Department of Immunology, University of Oslo, Norway. Tel.: +4723072721; E-mail: ; Geir Kjetil Sandve, Department of Informatics, University of Oslo, Norway. Tel.: +4722840861; E-mail: ; Shuo-Wang Qiao, Department of Immunology, University of Oslo, Norway. Tel.: +4722850533; E-mail:
| | - Ralf Stefan Neumann
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
| | - Lonneke Scheffer
- Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway
| | - Knut Erik Aslaksen Lundin
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Gastroenterology, Oslo University Hospital-Rikshospitalet, 0372, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Ludvig Magne Sollid
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Shuo-Wang Qiao
- Corresponding authors: Gabriel Balaban, Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway. Tel.: +4767828200; E-mail: . Shiva Dahal-Koirala, Department of Immunology, University of Oslo, Norway. Tel.: +4723072721; E-mail: ; Geir Kjetil Sandve, Department of Informatics, University of Oslo, Norway. Tel.: +4722840861; E-mail: ; Shuo-Wang Qiao, Department of Immunology, University of Oslo, Norway. Tel.: +4722850533; E-mail:
| | - Geir Kjetil Sandve
- Corresponding authors: Gabriel Balaban, Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway. Tel.: +4767828200; E-mail: . Shiva Dahal-Koirala, Department of Immunology, University of Oslo, Norway. Tel.: +4723072721; E-mail: ; Geir Kjetil Sandve, Department of Informatics, University of Oslo, Norway. Tel.: +4722840861; E-mail: ; Shuo-Wang Qiao, Department of Immunology, University of Oslo, Norway. Tel.: +4722850533; E-mail:
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AIRR Community Guide to Planning and Performing AIRR-Seq Experiments. Methods Mol Biol 2022; 2453:261-278. [PMID: 35622331 PMCID: PMC9761540 DOI: 10.1007/978-1-0716-2115-8_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The development of high-throughput sequencing of adaptive immune receptor repertoires (AIRR-seq of IG and TR rearrangements) has provided a new frontier for in-depth analysis of the immune system. The last decade has witnessed an explosion in protocols, experimental methodologies, and computational tools. In this chapter, we discuss the major considerations in planning a successful AIRR-seq experiment together with basic strategies for controlling and evaluating the outcome of the experiment. Members of the AIRR Community have authored several chapters in this edition, which cover step-by-step instructions to successfully conduct, analyze, and share an AIRR-seq project.
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Wang Q, Zeng H, Zhu Y, Wang M, Zhang Y, Yang X, Tang H, Li H, Chen Y, Ma C, Lan C, Liu B, Yang W, Yu X, Zhang Z. Dual UMIs and Dual Barcodes With Minimal PCR Amplification Removes Artifacts and Acquires Accurate Antibody Repertoire. Front Immunol 2021; 12:778298. [PMID: 35003093 PMCID: PMC8727365 DOI: 10.3389/fimmu.2021.778298] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/25/2021] [Indexed: 12/03/2022] Open
Abstract
Antibody repertoire sequencing (Rep-seq) has been widely used to reveal repertoire dynamics and to interrogate antibodies of interest at single nucleotide-level resolution. However, polymerase chain reaction (PCR) amplification introduces extensive artifacts including chimeras and nucleotide errors, leading to false discovery of antibodies and incorrect assessment of somatic hypermutations (SHMs) which subsequently mislead downstream investigations. Here, a novel approach named DUMPArts, which improves the accuracy of antibody repertoires by labeling each sample with dual barcodes and each molecule with dual unique molecular identifiers (UMIs) via minimal PCR amplification to remove artifacts, is developed. Tested by ultra-deep Rep-seq data, DUMPArts removed inter-sample chimeras, which cause artifactual shared clones and constitute approximately 15% of reads in the library, as well as intra-sample chimeras with erroneous SHMs and constituting approximately 20% of the reads, and corrected base errors and amplification biases by consensus building. The removal of these artifacts will provide an accurate assessment of antibody repertoires and benefit related studies, especially mAb discovery and antibody-guided vaccine design.
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Affiliation(s)
- Qilong Wang
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Huikun Zeng
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yan Zhu
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Minhui Wang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yanfang Zhang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Xiujia Yang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Haipei Tang
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hongliang Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Yuan Chen
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Cuiyu Ma
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Chunhong Lan
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Bin Liu
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Wei Yang
- Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- *Correspondence: Wei Yang, ; Xueqing Yu, ; Zhenhai Zhang, ;
| | - Xueqing Yu
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Division of Nephrology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Wei Yang, ; Xueqing Yu, ; Zhenhai Zhang, ;
| | - Zhenhai Zhang
- Center for Precision Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
- *Correspondence: Wei Yang, ; Xueqing Yu, ; Zhenhai Zhang, ;
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Wei H, Xie H, Qu J, Xie A, Xie S, Huang H, Li J, Fang C, Shi F, Qiu H, Qi Y, Tian X, Yang Q, Huang J. TLR7 modulating B-cell immune responses in the spleen of C57BL/6 mice infected with Schistosoma japonicum. PLoS Negl Trop Dis 2021; 15:e0009943. [PMID: 34788282 PMCID: PMC8598019 DOI: 10.1371/journal.pntd.0009943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/21/2021] [Indexed: 11/19/2022] Open
Abstract
B cells played an important role in Schistosoma infection-induced diseases. TLR7 is an intracellular member of the innate immune receptor. The role of TLR7 on B cells mediated immune response is still unclear. Here, C57BL/6 mice were percutaneously infected by S. japonicum for 5-6 weeks. The percentages and numbers of B cells increased in the infected mice (p < 0.05), and many activation and function associated molecules were also changed on B cells. More splenic cells of the infected mice expressed TLR7, and B cells were served as the main cell population. Moreover, a lower level of soluble egg antigen (SEA) specific antibody and less activation associated molecules were found on the surface of splenic B cells from S. japonicum infected TLR7 gene knockout (TLR7 KO) mice compared to infected wild type (WT) mice (p < 0.05). Additionally, SEA showed a little higher ability in inducing the activation of B cells from naive WT mice than TLR7 KO mice (p < 0.05). Finally, the effects of TLR7 on B cells are dependent on the activation of NF-κB p65. Altogether, TLR7 was found modulating the splenic B cell responses in S. japonicum infected C57BL/6 mice.
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Affiliation(s)
- Haixia Wei
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongyan Xie
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiale Qu
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Anqi Xie
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shihao Xie
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - He Huang
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiajie Li
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chao Fang
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Feihu Shi
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huaina Qiu
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yanwei Qi
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xu Tian
- Key Laboratory of Molecular Target & Clinical Pharmacology and the State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
- * E-mail: (XT); (QY); (JH)
| | - Quan Yang
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- * E-mail: (XT); (QY); (JH)
| | - Jun Huang
- Key Laboratory of Immunology, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- China Sino-French Hoffmann Institute, Guangzhou Medical University, Guangzhou, China
- * E-mail: (XT); (QY); (JH)
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5
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Pedrioli A, Oxenius A. Single B cell technologies for monoclonal antibody discovery. Trends Immunol 2021; 42:1143-1158. [PMID: 34743921 DOI: 10.1016/j.it.2021.10.008] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/11/2021] [Accepted: 10/11/2021] [Indexed: 11/18/2022]
Abstract
Monoclonal antibodies (mAbs) are often selected from antigen-specific single B cells derived from different hosts, which are notably short-lived in ex vivo culture conditions and hence, arduous to interrogate. The development of several new techniques and protocols has facilitated the isolation and retrieval of antibody-coding sequences of antigen-specific B cells by also leveraging miniaturization of reaction volumes. Alternatively, mAbs can be generated independently of antigen-specific B cells, comprising display technologies and, more recently, artificial intelligence-driven algorithms. Consequently, a considerable variety of techniques are used, raising the demand for better consolidation. In this review, we present and discuss the major techniques available to interrogate antigen-specific single B cells to isolate antigen-specific mAbs, including their main advantages and disadvantages.
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Affiliation(s)
- Alessandro Pedrioli
- Institute of Microbiology, ETH Zürich, Vladimir-Prelog-Weg 4, 8093 Zürich, Switzerland
| | - Annette Oxenius
- Institute of Microbiology, ETH Zürich, Vladimir-Prelog-Weg 4, 8093 Zürich, Switzerland.
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Ghraichy M, von Niederhäusern V, Kovaltsuk A, Galson JD, Deane CM, Trück J. Different B cell subpopulations show distinct patterns in their IgH repertoire metrics. eLife 2021; 10:73111. [PMID: 34661527 PMCID: PMC8560093 DOI: 10.7554/elife.73111] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/17/2021] [Indexed: 12/11/2022] Open
Abstract
Several human B cell subpopulations are recognised in the peripheral blood, which play distinct roles in the humoral immune response. These cells undergo developmental and maturational changes involving VDJ recombination, somatic hypermutation and class switch recombination, altogether shaping their immunoglobulin heavy chain (IgH) repertoire. Here, we sequenced the IgH repertoire of naïve, marginal zone, switched and plasma cells from 10 healthy adults along with matched unsorted and in silico separated CD19+ bulk B cells. Using advanced bioinformatic analysis and machine learning, we show that sorted B cell subpopulations are characterised by distinct repertoire characteristics on both the individual sequence and the repertoire level. Sorted subpopulations shared similar repertoire characteristics with their corresponding in silico separated subsets. Furthermore, certain IgH repertoire characteristics correlated with the position of the constant region on the IgH locus. Overall, this study provides unprecedented insight over mechanisms of B cell repertoire control in peripherally circulating B cell subpopulations.
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Affiliation(s)
- Marie Ghraichy
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | - Valentin von Niederhäusern
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | | | - Jacob D Galson
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland.,Alchemab Therapeutics Ltd, London, United Kingdom
| | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Johannes Trück
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
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Kibler A, Budeus B, Homp E, Bronischewski K, Berg V, Sellmann L, Murke F, Heinold A, Heinemann FM, Lindemann M, Bekeredjian-Ding I, Horn PA, Kirschning CJ, Küppers R, Seifert M. Systematic memory B cell archiving and random display shape the human splenic marginal zone throughout life. J Exp Med 2021; 218:211756. [PMID: 33538775 PMCID: PMC7868796 DOI: 10.1084/jem.20201952] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/02/2020] [Accepted: 12/21/2020] [Indexed: 12/19/2022] Open
Abstract
Human memory B cells (MBCs) are generated and diversified in secondary lymphoid tissues throughout the organism. A paired immunoglobulin (Ig)-gene repertoire analysis of peripheral blood (PB) and splenic MBCs from infant, adult, and elderly humans revealed that throughout life, circulating MBCs are comprehensively archived in the spleen. Archive MBC clones are systematically preserved and uncoupled from class-switching. Clonality in the spleen increases steadily, but boosts at midlife, thereby outcompeting small clones. The splenic marginal zone (sMZ) represents a primed MBC compartment, generated from a stochastic exchange within the archive memory pool. This is supported by functional assays, showing that PB and splenic CD21+ MBCs acquire transient CD21high expression upon NOTCH2-stimulation. Our study provides insight that the human MBC system in PB and spleen is composed of three interwoven compartments: the dynamic relationship of circulating, archive, and its subset of primed (sMZ) memory changes with age, thereby contributing to immune aging.
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Affiliation(s)
- Artur Kibler
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Bettina Budeus
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Ekaterina Homp
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Kevin Bronischewski
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Victoria Berg
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Ludger Sellmann
- Department of Haematology, University Hospital Essen, Essen, Germany
| | - Florian Murke
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Andreas Heinold
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Falko M Heinemann
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Monika Lindemann
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Peter A Horn
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Ralf Küppers
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Marc Seifert
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
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Trück J, Eugster A, Barennes P, Tipton CM, Luning Prak ET, Bagnara D, Soto C, Sherkow JS, Payne AS, Lefranc MP, Farmer A, Bostick M, Mariotti-Ferrandiz E. Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling. eLife 2021; 10:e66274. [PMID: 34037521 PMCID: PMC8154019 DOI: 10.7554/elife.66274] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 05/15/2021] [Indexed: 12/15/2022] Open
Abstract
Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community's Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.
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Affiliation(s)
- Johannes Trück
- University Children’s Hospital and the Children’s Research Center, University of ZurichZurichSwitzerland
| | - Anne Eugster
- CRTD Center for Regenerative Therapies Dresden, Faculty of Medicine, Technische Universität DresdenDresdenGermany
| | - Pierre Barennes
- Sorbonne Université U959, Immunology-Immunopathology-Immunotherapy (i3)ParisFrance
- AP-HP Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi)ParisFrance
| | - Christopher M Tipton
- Lowance Center for Human Immunology, Emory University School of MedicineAtlantaUnited States
| | - Eline T Luning Prak
- Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Davide Bagnara
- University of Genoa, Department of Experimental MedicineGenoaItaly
| | - Cinque Soto
- The Vanderbilt Vaccine Center, Vanderbilt University Medical CenterNashvilleUnited States
- Department of Pediatrics, Vanderbilt University Medical CenterNashvilleUnited States
| | - Jacob S Sherkow
- College of Law, University of IllinoisChampaignUnited States
- Center for Advanced Studies in Biomedical Innovation Law, University of Copenhagen Faculty of LawCopenhagenDenmark
- Carl R. Woese Institute for Genomic Biology, University of IllinoisUrbana, IllinoisUnited States
| | - Aimee S Payne
- Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Marie-Paule Lefranc
- IMGT, The International ImMunoGeneTics Information System (IMGT), Laboratoire d'ImmunoGénétique Moléculaire (LIGM), Institut de Génétique Humaine (IGH), CNRS, University of MontpellierMontpellierFrance
- Laboratoire d'ImmunoGénétique Moléculaire (LIGM) CNRS, University of MontpellierMontpellierFrance
- Institut de Génétique Humaine (IGH), CNRS, University of MontpellierMontpellierFrance
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9
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A single donor is sufficient to produce a highly functional in vitro antibody library. Commun Biol 2021; 4:350. [PMID: 33742103 PMCID: PMC7979914 DOI: 10.1038/s42003-021-01881-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/19/2021] [Indexed: 01/31/2023] Open
Abstract
Antibody complementarity determining region diversity has been considered to be the most important metric for the production of a functional antibody library. Generally, the greater the antibody library diversity, the greater the probability of selecting a diverse array of high affinity leads. According to this paradigm, the primary means of elevating library diversity has been by increasing the number of donors. In the present study we explored the possibility of creating an in vitro antibody library from a single healthy individual, showing that the number of lymphocytes, rather than the number of donors, is the key criterion in the production of a diverse and functional antibody library. We describe the construction of a high-quality phage display library comprising 5 × 109 human antibodies by applying an efficient B cell extraction protocol from a single donor and a targeted V-gene amplification strategy favoring specific antibody families for their improved developability profiles. Each step of the library generation process was followed and validated by next generation sequencing to monitor the library quality and diversity. The functionality of the library was tested using several therapeutically relevant targets for which a vast number of different antibodies with desired biophysical properties were obtained.
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10
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Barennes P, Quiniou V, Shugay M, Egorov ES, Davydov AN, Chudakov DM, Uddin I, Ismail M, Oakes T, Chain B, Eugster A, Kashofer K, Rainer PP, Darko S, Ransier A, Douek DC, Klatzmann D, Mariotti-Ferrandiz E. Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases. Nat Biotechnol 2021; 39:236-245. [PMID: 32895550 DOI: 10.1038/s41587-020-0656-3] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 07/28/2020] [Indexed: 12/13/2022]
Abstract
Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.
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Affiliation(s)
- Pierre Barennes
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Valentin Quiniou
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Mikhail Shugay
- Center of Life Sciences, Skoltech, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Evgeniy S Egorov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Alexey N Davydov
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia
| | - Dmitriy M Chudakov
- Center of Life Sciences, Skoltech, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia
| | - Imran Uddin
- Division of Infection and Immunity, University College London, London, UK
| | - Mazlina Ismail
- Division of Infection and Immunity, University College London, London, UK
| | - Theres Oakes
- Division of Infection and Immunity, University College London, London, UK
| | - Benny Chain
- Division of Infection and Immunity, University College London, London, UK
| | - Anne Eugster
- DFG-Centre for Regenerative Therapies Dresden, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Karl Kashofer
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Peter P Rainer
- Division of Cardiology, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Samuel Darko
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Amy Ransier
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Daniel C Douek
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - David Klatzmann
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Encarnita Mariotti-Ferrandiz
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France.
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France.
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11
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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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12
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Li H, Dement-Brown J, Liao PJ, Mazo I, Mills F, Kraus Z, Fitzsimmons S, Tolnay M. Fc receptor-like 4 and 5 define human atypical memory B cells. Int Immunol 2020; 32:755-770. [DOI: 10.1093/intimm/dxaa053] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/04/2020] [Indexed: 11/14/2022] Open
Abstract
Abstract
Atypical memory B cells accumulate in chronic infections and autoimmune conditions, and commonly express FCRL4 and FCRL5, respective IgA and IgG receptors. We characterized memory cells from tonsils on the basis of both FCRL4 and FCRL5 expression, defining three subsets with distinct surface proteins and gene expression. Atypical FCRL4+FCRL5+ memory cells had the most discrete surface protein expression and were enriched in cell adhesion pathways, consistent with functioning as tissue-resident cells. Atypical FCRL4−FCRL5+ memory cells expressed transcription factors and immunoglobulin genes that suggest poised differentiation into plasma cells. Accordingly, the FCRL4−FCRL5+ memory subset was enriched in pathways responding to endoplasmic reticulum stress and IFN-γ. We reconstructed ongoing B-cell responses as lineage trees, providing crucial in vivo developmental context. Each memory subset typically maintained its lineage, denoting mechanisms enforcing their phenotypes. Classical FCRL4−FCRL5− memory cells were infrequently detected in lineage trees, suggesting the majority were in a quiescent state. FCRL4−FCRL5+ cells were the most represented memory subset in lineage trees, indicating robust participation in ongoing responses. Together, these differences suggest FCRL4 and FCRL5 are unlikely to be passive markers but rather active drivers of human memory B-cell development and function.
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Affiliation(s)
- Huifang Li
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Jessica Dement-Brown
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Pei-Jyun Liao
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Ilya Mazo
- Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
- Argentys Informatics LLC, Gaithersburg, MD, USA
| | - Frederick Mills
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Zachary Kraus
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Sean Fitzsimmons
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Mate Tolnay
- Office of Biotechnology Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
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13
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Prechl J. Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model. Antibodies (Basel) 2020; 9:antib9020013. [PMID: 32384800 PMCID: PMC7345901 DOI: 10.3390/antib9020013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/09/2020] [Accepted: 04/15/2020] [Indexed: 02/06/2023] Open
Abstract
Adaptive immunity in vertebrates is a complex self-organizing network of molecular interactions. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper, a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RAdial ADjustment of System Resolution (RADARS), is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction corresponding to particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power law distribution of antibody-free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees, and B1 cells function as nodes with minimal degree. Overall, the RADARS model implies that a finite number of antibody structures can interact with an infinite number of antigens by immunologically controlled adjustment of interaction energy distribution. Understanding quantitative network properties of the system should help the organization of sequence-derived predicted structural data.
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Affiliation(s)
- József Prechl
- Diagnosticum Zrt., 126. Attila u., 1047 Budapest, Hungary
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14
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Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes. Immunogenetics 2020; 72:279-294. [PMID: 32367185 DOI: 10.1007/s00251-020-01164-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 04/13/2020] [Indexed: 10/24/2022]
Abstract
Protection and neutralization of a vast array of pathogens is accomplished by the tremendous diversity of the B cell receptor (BCR) repertoire. For jawed vertebrates, this diversity is initiated via the somatic recombination of immunoglobulin (Ig) germline elements. While it is clear that the number of these germline segments differs from species to species, the extent of cross-species sequence diversity remains largely uncharacterized. Here we use extensive computational and statistical methods to investigate the sequence diversity and evolutionary relationship between Ig variable (V), diversity (D), and joining (J) germline segments across nine commonly studied species ranging from zebrafish to human. Metrics such as guanine-cytosine (GC) content showed low redundancy across Ig germline genes within a given species. Other comparisons, including amino acid motifs, evolutionary selection, and sequence diversity, revealed species-specific properties. Additionally, we showed that the germline-encoded diversity differs across antibody (recombined V-D-J) repertoires of various B cell subsets. To facilitate future comparative immunogenomics analysis, we created VDJgermlines, an R package that contains the germline sequences from multiple species. Our study informs strategies for the humanization and engineering of therapeutic antibodies.
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15
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Bhardwaj V, Franceschetti M, Rao R, Pevzner PA, Safonova Y. Automated analysis of immunosequencing datasets reveals novel immunoglobulin D genes across diverse species. PLoS Comput Biol 2020; 16:e1007837. [PMID: 32339161 PMCID: PMC7295240 DOI: 10.1371/journal.pcbi.1007837] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 06/15/2020] [Accepted: 04/01/2020] [Indexed: 12/30/2022] Open
Abstract
Immunoglobulin genes are formed through V(D)J recombination, which joins the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics focuses on finding alleles of germline genes across various patients. Although reconstruction of V and J genes is a well-studied problem, the more challenging task of reconstructing D genes remained open until the IgScout algorithm was developed in 2019. In this work, we address limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstruction, apply it to hundreds of immunosequencing datasets from multiple species, and validate the newly inferred D genes by analyzing diverse whole genome sequencing datasets and haplotyping heterozygous V genes. Antibodies provide specific binding to an enormous range of antigens and represent a key component of the adaptive immune system. Immunosequencing has emerged as a method of choice for generating millions of reads that sample antibody repertoires and provides insights into monitoring immune response to disease and vaccination. Most of the previous immunogenomics studies rely on the reference germline genes in the immunoglobulin locus rather than the germline genes in a specific patient. This approach is deficient since the set of known germline genes is incomplete (particularly for non-European humans and non-human species) and contains alleles that resulted from sequencing and annotation errors. The problem of de novo inference of diversity (D) genes from immunosequencing data remained open until the IgScout algorithm was developed in 2019. We address limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstruction and infer multiple D genes across multiple species that are not present in standard databases.
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Affiliation(s)
- Vinnu Bhardwaj
- Electrical and Computer Engineering Department, University of California San Diego, San Diego, California, United States of America
| | - Massimo Franceschetti
- Electrical and Computer Engineering Department, University of California San Diego, San Diego, California, United States of America
| | - Ramesh Rao
- Electrical and Computer Engineering Department, University of California San Diego, San Diego, California, United States of America
- Qualcomm Institute, University of California San Diego, San Diego, California, United States of America
| | - Pavel A. Pevzner
- Computer Science and Engineering Department, University of California San Diego, San Diego, California, United States of America
- * E-mail:
| | - Yana Safonova
- Computer Science and Engineering Department, University of California San Diego, San Diego, California, United States of America
- Center for Information Theory and Applications, University of California San Diego, San Diego, California, United States of America
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16
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Ohlin M, Scheepers C, Corcoran M, Lees WD, Busse CE, Bagnara D, Thörnqvist L, Bürckert JP, Jackson KJL, Ralph D, Schramm CA, Marthandan N, Breden F, Scott J, Matsen IV FA, Greiff V, Yaari G, Kleinstein SH, Christley S, Sherkow JS, Kossida S, Lefranc MP, van Zelm MC, Watson CT, Collins AM. Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming. Front Immunol 2019; 10:435. [PMID: 30936866 PMCID: PMC6431624 DOI: 10.3389/fimmu.2019.00435] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 02/19/2019] [Indexed: 11/13/2022] Open
Abstract
Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC-focusing, to begin with, on human IGHV genes-with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.
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Affiliation(s)
- Mats Ohlin
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Cathrine Scheepers
- Center for HIV and STIs, National Institute for Communicable Diseases, Johannesburg, South Africa
- Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Martin Corcoran
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - William D. Lees
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, United Kingdom
| | - Christian E. Busse
- Division of B Cell Immunology, German Cancer Research Center, Heidelberg, Germany
| | - Davide Bagnara
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | | | | | | | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Chaim A. Schramm
- Vaccine Research Center, National Institutes of Health, Washington, DC, United States
| | - Nishanth Marthandan
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
| | - Felix Breden
- Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Jamie Scott
- Department of Molecular Biology and Biochemistry, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | - Victor Greiff
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
| | | | - Scott Christley
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Jacob S. Sherkow
- Innovation Center for Law and Technology, New York Law School, New York, NY, United States
| | - Sofia Kossida
- IMGT, The International ImMunoGenetics information system (IMGT), Laboratoire d'ImmunoGénétique Moléculaire (LIGM), CNRS, Institut de Génétique Humaine, Université de Montpellier, Montpellier, France
| | - Marie-Paule Lefranc
- IMGT, The International ImMunoGenetics information system (IMGT), Laboratoire d'ImmunoGénétique Moléculaire (LIGM), CNRS, Institut de Génétique Humaine, Université de Montpellier, Montpellier, France
| | - Menno C. van Zelm
- Department of Immunology and Pathology, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, VIC, Australia
| | - Corey T. Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, United States
| | - Andrew M. Collins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
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17
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Sesterhenn F, Galloux M, Vollers SS, Csepregi L, Yang C, Descamps D, Bonet J, Friedensohn S, Gainza P, Corthésy P, Chen M, Rosset S, Rameix-Welti MA, Éléouët JF, Reddy ST, Graham BS, Riffault S, Correia BE. Boosting subdominant neutralizing antibody responses with a computationally designed epitope-focused immunogen. PLoS Biol 2019; 17:e3000164. [PMID: 30789898 PMCID: PMC6400402 DOI: 10.1371/journal.pbio.3000164] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 03/05/2019] [Accepted: 02/08/2019] [Indexed: 12/20/2022] Open
Abstract
Throughout the last several decades, vaccination has been key to prevent and eradicate infectious diseases. However, many pathogens (e.g., respiratory syncytial virus [RSV], influenza, dengue, and others) have resisted vaccine development efforts, largely because of the failure to induce potent antibody responses targeting conserved epitopes. Deep profiling of human B cells often reveals potent neutralizing antibodies that emerge from natural infection, but these specificities are generally subdominant (i.e., are present in low titers). A major challenge for next-generation vaccines is to overcome established immunodominance hierarchies and focus antibody responses on crucial neutralization epitopes. Here, we show that a computationally designed epitope-focused immunogen presenting a single RSV neutralization epitope elicits superior epitope-specific responses compared to the viral fusion protein. In addition, the epitope-focused immunogen efficiently boosts antibodies targeting the palivizumab epitope, resulting in enhanced neutralization. Overall, we show that epitope-focused immunogens can boost subdominant neutralizing antibody responses in vivo and reshape established antibody hierarchies. A computationally designed epitope-focused immunogen presenting a single neutralization epitope from Respiratory Syncytial Virus elicits superior epitope-specific responses compared to the viral fusion protein. Furthermore, epitope-focused immunogens can reshape established antibody hierarchies. Vaccines are one of the most valuable instruments to prevent and control infectious diseases. Their primary correlate of protection is the level of induction of neutralizing antibodies that target critical antigenic sites and thereby block infection. Natural infections with pathogens such as the respiratory syncytial virus (RSV) or influenza induce a broad repertoire of antibodies that target multiple epitopes. Among those, functional antibodies with key specificities are often subdominant (present in low titers). Thus, a central goal for vaccine development is to focus antibody responses on such neutralization epitopes. Here, we show that a computationally designed, epitope-focused immunogen mimicking an important RSV neutralization epitope (site II) can focus antibodies onto this well-defined epitope. In a scenario of preexisting immunity, in which site II–specific antibodies were subdominant, the epitope-focused immunogen selectively boosted site II–specific antibodies, resulting in an increased viral neutralization through this epitope. We propose that rationally designed immunogens spotlighting defined epitopes have a unique potential to focus antibody responses on functionally conserved sites in cases of preexisting immunity. Our results have broad implications for vaccine design as a strategy to steer preexisting antibody responses away from immunodominant, variable epitopes and toward subdominant epitopes that confer broad and potent neutralization.
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MESH Headings
- Animals
- Antibodies, Monoclonal, Humanized/chemistry
- Antibodies, Monoclonal, Humanized/immunology
- Antibodies, Neutralizing/biosynthesis
- Antibodies, Neutralizing/genetics
- Antibodies, Viral/biosynthesis
- Antibodies, Viral/genetics
- Cloning, Molecular
- Computer-Aided Design
- Epitopes/chemistry
- Epitopes/immunology
- Escherichia coli/genetics
- Escherichia coli/metabolism
- Female
- Gene Expression
- Genetic Vectors/chemistry
- Genetic Vectors/metabolism
- Immunization/methods
- Immunogenicity, Vaccine
- Mice
- Mice, Inbred BALB C
- Nanoparticles/administration & dosage
- Nanoparticles/chemistry
- Palivizumab/chemistry
- Palivizumab/immunology
- Receptors, Antigen, B-Cell/chemistry
- Receptors, Antigen, B-Cell/genetics
- Receptors, Antigen, B-Cell/immunology
- Recombinant Fusion Proteins/administration & dosage
- Recombinant Fusion Proteins/chemistry
- Recombinant Fusion Proteins/genetics
- Recombinant Fusion Proteins/immunology
- Respiratory Syncytial Virus Vaccines/administration & dosage
- Respiratory Syncytial Virus Vaccines/biosynthesis
- Respiratory Syncytial Virus Vaccines/genetics
- Respiratory Syncytial Viruses/immunology
- Structural Homology, Protein
- Viral Fusion Proteins/administration & dosage
- Viral Fusion Proteins/chemistry
- Viral Fusion Proteins/genetics
- Viral Fusion Proteins/immunology
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Affiliation(s)
- Fabian Sesterhenn
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Marie Galloux
- Unité de Virologie et Immunologie Moléculaires (UR892), INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Sabrina S. Vollers
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Lucia Csepregi
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Che Yang
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Delphyne Descamps
- Unité de Virologie et Immunologie Moléculaires (UR892), INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Jaume Bonet
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Simon Friedensohn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Pablo Gainza
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Patricia Corthésy
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Man Chen
- Viral Pathogenesis Laboratory, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Stéphane Rosset
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Marie-Anne Rameix-Welti
- UMR1173, INSERM, Université de Versailles St. Quentin, Montigny le Bretonneux, France
- AP-HP, Laboratoire de Microbiologie, Hôpital Ambroise Paré, Boulogne-Billancourt, France
| | - Jean-François Éléouët
- Unité de Virologie et Immunologie Moléculaires (UR892), INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Barney S. Graham
- Viral Pathogenesis Laboratory, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sabine Riffault
- Unité de Virologie et Immunologie Moléculaires (UR892), INRA, Université Paris-Saclay, Jouy-en-Josas, France
| | - Bruno E. Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
- * E-mail:
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18
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Kovaltsuk A, Krawczyk K, Kelm S, Snowden J, Deane CM. Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2018; 201:3694-3704. [PMID: 30397033 PMCID: PMC6485405 DOI: 10.4049/jimmunol.1800669] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 10/02/2018] [Indexed: 01/29/2023]
Abstract
Next-generation sequencing of the Ig gene repertoire (Ig-seq) produces large volumes of information at the nucleotide sequence level. Such data have improved our understanding of immune systems across numerous species and have already been successfully applied in vaccine development and drug discovery. However, the high-throughput nature of Ig-seq means that it is afflicted by high error rates. This has led to the development of error-correction approaches. Computational error-correction methods use sequence information alone, primarily designating sequences as likely to be correct if they are observed frequently. In this work, we describe an orthogonal method for filtering Ig-seq data, which considers the structural viability of each sequence. A typical natural Ab structure requires the presence of a disulfide bridge within each of its variable chains to maintain the fold. Our Ab Sequence Selector (ABOSS) uses the presence/absence of this bridge as a way of both identifying structurally viable sequences and estimating the sequencing error rate. On simulated Ig-seq datasets, ABOSS is able to identify more than 99% of structurally viable sequences. Applying our method to six independent Ig-seq datasets (one mouse and five human), we show that our error calculations are in line with previous experimental and computational error estimates. We also show how ABOSS is able to identify structurally impossible sequences missed by other error-correction methods.
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Affiliation(s)
- Aleksandr Kovaltsuk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Konrad Krawczyk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | | | | | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
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Roth L, Grzeschik J, Hinz SC, Becker S, Toleikis L, Busch M, Kolmar H, Krah S, Zielonka S. Facile generation of antibody heavy and light chain diversities for yeast surface display by Golden Gate Cloning. Biol Chem 2018; 400:383-393. [DOI: 10.1515/hsz-2018-0347] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 11/11/2018] [Indexed: 01/03/2023]
Abstract
Abstract
Antibodies can be successfully engineered and isolated by yeast or phage display of combinatorial libraries. Still, generation of libraries comprising heavy chain as well as light chain diversities is a cumbersome process involving multiple steps. Within this study, we set out to compare the output of yeast display screening of antibody Fab libraries from immunized rodents that were generated by Golden Gate Cloning (GGC) with the conventional three-step method of individual heavy- and light-chain sub-library construction followed by chain combination via yeast mating (YM). We demonstrate that the GGC-based one-step process delivers libraries and antibodies from heavy- and light-chain diversities with similar quality to the traditional method while being significantly less complex and faster. Additionally, we show that this method can also be used to successfully screen and isolate chimeric chicken/human antibodies following avian immunization.
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Affiliation(s)
- Lukas Roth
- Institute for Organic Chemistry and Biochemistry , Technische Universität Darmstadt , Alarich-Weiss-Strasse 4 , D-64287 Darmstadt , Germany
| | - Julius Grzeschik
- Institute for Organic Chemistry and Biochemistry , Technische Universität Darmstadt , Alarich-Weiss-Strasse 4 , D-64287 Darmstadt , Germany
| | - Steffen C. Hinz
- Institute for Organic Chemistry and Biochemistry , Technische Universität Darmstadt , Alarich-Weiss-Strasse 4 , D-64287 Darmstadt , Germany
| | - Stefan Becker
- Protein Engineering and Antibody Technologies, Merck KGaA , Frankfurter Strasse 250 , D-64293 Darmstadt , Germany
| | - Lars Toleikis
- Protein Engineering and Antibody Technologies, Merck KGaA , Frankfurter Strasse 250 , D-64293 Darmstadt , Germany
| | - Michael Busch
- Discovery Pharmacology, Merck KGaA , Frankfurter Strasse 250 , D-64293 Darmstadt , Germany
| | - Harald Kolmar
- Institute for Organic Chemistry and Biochemistry , Technische Universität Darmstadt , Alarich-Weiss-Strasse 4 , D-64287 Darmstadt , Germany
| | - Simon Krah
- Protein Engineering and Antibody Technologies, Merck KGaA , Frankfurter Strasse 250 , D-64293 Darmstadt , Germany
| | - Stefan Zielonka
- Protein Engineering and Antibody Technologies, Merck KGaA , Frankfurter Strasse 250 , D-64293 Darmstadt , Germany
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20
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Rosenfeld AM, Meng W, Chen DY, Zhang B, Granot T, Farber DL, Hershberg U, Luning Prak ET. Computational Evaluation of B-Cell Clone Sizes in Bulk Populations. Front Immunol 2018; 9:1472. [PMID: 30008715 PMCID: PMC6034424 DOI: 10.3389/fimmu.2018.01472] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 06/13/2018] [Indexed: 12/27/2022] Open
Abstract
B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size-copy numbers, instances, and unique sequences-and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data.
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Affiliation(s)
- Aaron M. Rosenfeld
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Wenzhao Meng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Dora Y. Chen
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Bochao Zhang
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Tomer Granot
- Columbia Center for Translational Immunology, Columbia University, New York, NY, United States
| | - Donna L. Farber
- Columbia Center for Translational Immunology, Columbia University, New York, NY, United States
| | - Uri Hershberg
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
- Department of Microbiology and Immunology, Drexel College of Medicine, Drexel University, Philadelphia, PA, United States
| | - Eline T. Luning Prak
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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