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To recognize and react against unknown proteins, B and T lymphocytes express unique, randomly generated receptors capable of evolving to refine their specificity. These receptors form the immune repertoire, a dynamic and highly diverse library, specific to each individual. The sequencing of these genes now makes it possible to map this repertoire, which provides information both on the individual's immunological history and on their future response capabilities.

But analyzing the repertoire remains a major challenge: each human being has 10^{11} unique receptors, the majority of which are exclusive to them. Above all, the interactions between these receptors and their target antigens are complex with current tools. In fact, the vast majority of antibody-antigen pairs are unknown, a veritable immunological “dark matter,” which our team is working to clarify by combining experimental and computational methods.

Experimental methods for measuring interactions : Our team develops high-throughput technologies, combining sequencing and molecular biology, to quantify the affinities between thousands of antibodies and their potential targets. These approaches make it possible to identify recognized antigens, discover antibodies of therapeutic or diagnostic interest, and study affinity maturation and antibody evolution.

Representation of the affinity landscape of 65536 variants of a broad-spectrum antibody against influenza H1 hemagluttinin, see here.

Computational models to decipher the repertoire In parallel, we design statistical models to analyze the diversity of repertoires, predict the receptors active against a given target, and simulate their evolution. By integrating experimental data and theories from physics and population genetics, we seek to understand the rules of immune recognition and generate virtual repertoires to test hypotheses.

Phylogenetic tree of an antibody family. When they encounter an antigen, antibodies evolve and form these sometimes very large antibody families. We seek to determine the parameters of this evolution and to what extent it can influence it.

Publications

2024
Natanael Spisak, Gabriel Athens, Thomas Dupic, Thierry Mora, Aleksandra Walczak, Combining mutation and recombination statistics to infer clonal families in antibody repertoires, <i>eLife</i>, 2024, 13, pp.e86181. <a target="_blank" href="https://dx.doi.org/10.7554/eLife.86181">⟨10.7554/eLife.86181⟩</a>.
2024
Abbate MF, Dupic T, Vigne E, Shahsavarian MA, Walczak AM, Mora T, Computational detection of antigen-specific B cell receptors following immunization. Proc Natl Acad Sci USA 2024 Aug; 121(35): e2401058121.
2024
Dupic T, Phillips AM, Desai MM, Protein sequence landscapes are not so simple: on reference-free versus reference-based inference. bioRxiv 2024 Jan; (): .
2023
Moulana A, Dupic T, Phillips AM, Desai MM, Genotype-phenotype landscapes for immune-pathogen coevolution. Trends Immunol 2023 May; 44(5): 384-396.
2023
Moulana A, Dupic T, Phillips AM, Chang J, Roffler AA, Greaney AJ, Starr TN, Bloom JD, Desai MM, The landscape of antibody binding affinity in SARS-CoV-2 Omicron BA.1 evolution., Elife 2023 Feb; 12(): .
2023
Phillips AM, Maurer DP, Brooks C, Dupic T, Schmidt AG, Desai MM, Hierarchical sequence-affinity landscapes shape the evolution of breadth in an anti-influenza receptor binding site antibody. Elife 2023 Jan; 12(): .
2022
Moulana A, Dupic T, Phillips AM, Chang J, Nieves S, Roffler AA, Greaney AJ, Starr TN, Bloom JD, Desa..., Compensatory epistasis maintains ACE2 affinity in SARS-CoV-2 Omicron BA.1., Nat Common 2022 Nov; 13(1): 7011.
2021
Phillips AM, Lawrence KR, Moulana A, Dupic T, Chang J, Johnson MS, Cvijovic I, Mora T, Walczak AM, D..., Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies. Elife 2021 Sep; 10(): .
2021
Paul Gueguen, Christina Metoikidou, Thomas Dupic, Myriam Lawand, Christel Goudot, Sylvain Baulande, ..., Contribution of resident and circulating precursors to tumor-infiltrating CD8 + T cell populations in lung cancer, <i>Science Immunology</i>, 2021, 6 (55), pp.eabd5778. <a target="_blank" href="https://dx.doi.org/10.1126/sciimmunol.abd5778">⟨10.1126/sciimmunol.abd5778⟩</a>.
2021
Dupic T, Bensouda Koraichi M, Minervina AA, Pogorelyy MV, Mora T, Walczak AM, Immune fingerprinting through repertoire similarity. PLoS Genet 2021 Jan; 17(1): e1009301.
2020
Zachary Sethna, Giulio Isacchini, Thomas Dupic, Thierry Mora, Aleksandra Walczak, Yuval Elhanati, Population variability in the generation and thymic selection of T-cell repertoires, <i>PLoS Computational Biology</i>, 2020, 16 (12), pp.e1008394. <a target="_blank" href="https://dx.doi.org/10.1371/journal.pcbi.1008394">⟨10.1371/journal.pcbi.1008394⟩</a>.
2019
Thomas Dupic, Quentin Marcou, Aleksandra M. Walczak, Thierry Mora, Genesis of the αβ T-cell receptor, <i>PLoS Computational Biology</i>, 2019, 15 (3), pp.e1006874. <a target="_blank" href="https://dx.doi.org/10.1371/journal.pcbi.1006874">⟨10.1371/journal.pcbi.1006874⟩</a>.