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Probabilistic approaches to the adaptive immune repertoire : a data-driven approach

Abstract : An individual’s adaptive immune system needs to face repeated challenges of a constantly evolving environment with a virtually infinite number of threats. To achieve this task, the adaptive immune system relies on large diversity of B-cells and T-cells, each carrying a unique receptor specific to a small number of pathogens. These receptors are initially randomly built through the process of V(D)J recombination. This initial generated diversity is then narrowed down by a step of functional selection based on the receptors' folding properties and their ability to recognize self antigens. Upon recognition of a pathogen the B-cell will divide and its offsprings will undergo several rounds of successive somatic hypermutations and selection in an evolutionary process called affinity maturation. This work presents principled probabilistic approaches to infer the probability distribution underlying the recombination and somatic hypermutation processes from high throughput sequencing data using IGoR - a flexible software developed throughout the course of this PhD. IGoR has been developed as a versatile research tool and can encode a variety of models of different biological complexity to allow researchers in the field to characterize evermore precisely immune receptor repertoires. To motivate this data-driven approach we demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization. Finally, using obtained model predictions, we show potential applications of these methods by demonstrating that homozygous twins share T-cells through cord blood, that the public core of the T cell repertoire is formed in the pre-natal period and finally estimate naive T cell clone lifetimes in human.
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https://tel.archives-ouvertes.fr/tel-01775123
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Submitted on : Tuesday, April 24, 2018 - 1:09:07 PM
Last modification on : Thursday, March 26, 2020 - 9:46:01 PM
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  • HAL Id : tel-01775123, version 1

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Quentin Marcou. Probabilistic approaches to the adaptive immune repertoire : a data-driven approach. Immunology. Université Sorbonne Paris Cité, 2017. English. ⟨NNT : 2017USPCB029⟩. ⟨tel-01775123⟩

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