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Camaglia F, Ryvkin A, Greenstein E, Reich-Zeliger S, Chain B, Mora T, Walczak AM, Friedman N. Quantifying changes in the T cell receptor repertoire during thymic development. eLife 2023; 12:81622. [PMID: 36661220 PMCID: PMC9934861 DOI: 10.7554/elife.81622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 01/18/2023] [Indexed: 01/21/2023] Open
Abstract
One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4+ and CD8+ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.
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Affiliation(s)
- Francesco Camaglia
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Arie Ryvkin
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | - Erez Greenstein
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | | | - Benny Chain
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Thierry Mora
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Aleksandra M Walczak
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Nir Friedman
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
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Ashkenazy H, Avram O, Ryvkin A, Roitburd-Berman A, Weiss-Ottolenghi Y, Hada-Neeman S, Gershoni JM, Pupko T. Motifier: An IgOme Profiler Based on Peptide Motifs Using Machine Learning. J Mol Biol 2021; 433:167071. [PMID: 34052285 DOI: 10.1016/j.jmb.2021.167071] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 04/26/2021] [Accepted: 05/22/2021] [Indexed: 11/26/2022]
Abstract
Antibodies provide a comprehensive record of the encounters with threats and insults to the immune system. The ability to examine the repertoire of antibodies in serum and discover those that best represent "discriminating features" characteristic of various clinical situations, is potentially very useful. Recently, phage display technologies combined with Next-Generation Sequencing (NGS) produced a powerful experimental methodology, coined "Deep-Panning", in which the spectrum of serum antibodies is probed. In order to extract meaningful biological insights from the tens of millions of affinity-selected peptides generated by Deep-Panning, advanced bioinformatics algorithms are a must. In this study, we describe Motifier, a computational pipeline comprised of a set of algorithms that systematically generates discriminatory peptide motifs based on the affinity-selected peptides identified by Deep-Panning. These motifs are shown to effectively characterize antibody binding activities and through the implementation of machine-learning protocols are shown to accurately classify complex antibody mixtures representing various biological conditions.
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Affiliation(s)
- Haim Ashkenazy
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Oren Avram
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Arie Ryvkin
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Anna Roitburd-Berman
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yael Weiss-Ottolenghi
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Smadar Hada-Neeman
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Jonathan M Gershoni
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Tal Pupko
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
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Ryvkin A, Ashkenazy H, Weiss-Ottolenghi Y, Piller C, Pupko T, Gershoni JM. Phage display peptide libraries: deviations from randomness and correctives. Nucleic Acids Res 2018; 46:e52. [PMID: 29420788 PMCID: PMC5961013 DOI: 10.1093/nar/gky077] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 12/25/2017] [Accepted: 01/31/2018] [Indexed: 12/14/2022] Open
Abstract
Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications.
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Affiliation(s)
- Arie Ryvkin
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Haim Ashkenazy
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yael Weiss-Ottolenghi
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Chen Piller
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Tal Pupko
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Jonathan M Gershoni
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
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Ryvkin A, Ashkenazy H, Smelyanski L, Kaplan G, Penn O, Weiss-Ottolenghi Y, Privman E, Ngam PB, Woodward JE, May GD, Bell C, Pupko T, Gershoni JM. Deep Panning: steps towards probing the IgOme. PLoS One 2012; 7:e41469. [PMID: 22870226 PMCID: PMC3409857 DOI: 10.1371/journal.pone.0041469] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2012] [Accepted: 06/21/2012] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Polyclonal serum consists of vast collections of antibodies, products of differentiated B-cells. The spectrum of antibody specificities is dynamic and varies with age, physiology, and exposure to pathological insults. The complete repertoire of antibody specificities in blood, the IgOme, is therefore an extraordinarily rich source of information-a molecular record of previous encounters as well as a status report of current immune activity. The ability to profile antibody specificities of polyclonal serum at exceptionally high resolution has been an important and serious challenge which can now be overcome. METHODOLOGY/PRINCIPAL FINDINGS Here we illustrate the application of Deep Panning, a method that combines the flexibility of combinatorial phage display of random peptides with the power of high-throughput deep sequencing. Deep Panning is first applied to evaluate the quality and diversity of naïve random peptide libraries. The production of very large data sets, hundreds of thousands of peptides, has revealed unexpected properties of combinatorial random peptide libraries and indicates correctives to ensure the quality of the libraries generated. Next, Deep Panning is used to analyze a model monoclonal antibody in addition to allowing one to follow the dynamics of biopanning and peptide selection. Finally Deep Panning is applied to profile polyclonal sera derived from HIV infected individuals. CONCLUSIONS/SIGNIFICANCE The ability to generate and characterize hundreds of thousands of affinity-selected peptides creates an effective means towards the interrogation of the IgOme and understanding of the humoral response to disease. Deep Panning should open the door to new possibilities for serological diagnostics, vaccine design and the discovery of the correlates of immunity to emerging infectious agents.
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Affiliation(s)
- Arie Ryvkin
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Haim Ashkenazy
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Larisa Smelyanski
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Gilad Kaplan
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Osnat Penn
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | | | - Eyal Privman
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Peter B. Ngam
- National Center for Genome Resources, Santa Fe, New Mexico, United States of America
| | - James E. Woodward
- National Center for Genome Resources, Santa Fe, New Mexico, United States of America
| | - Gregory D. May
- National Center for Genome Resources, Santa Fe, New Mexico, United States of America
| | - Callum Bell
- National Center for Genome Resources, Santa Fe, New Mexico, United States of America
| | - Tal Pupko
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
| | - Jonathan M. Gershoni
- Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv, Israel
- * E-mail:
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