Population variability in the generation and selection of T-cell repertoires.
Population variability in the generation and selection of T-cell repertoires.
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DOI：
10.1371/journal.pcbi.1008394
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发表时间：
2020-12
影响因子：
4.3
通讯作者：
Elhanati Y
中科院分区：
文献类型：
--
作者：
Sethna Z;Isacchini G;Dupic T;Mora T;Walczak AM;Elhanati Y
t细胞受体（TCR）库的多样性是通过两个本质上随机的步骤的组合来实现的：通过VDJ重组随机产生受体，以及基于识别主要组织相容性复合体上的随机自肽来选择。这些过程导致个体内部和个体之间的受体差异很大。然而，可变性的表征受到采样曲目的有限大小的阻碍。我们引入了一个新的软件工具SONIA，以促进从651个个体的测序库中产生和选择TCR β链（TRB）的个体特异性计算模型的推断，分离和量化群体中产生和选择两个过程的可变性。我们发现，不仅大多数变异是由VDJ生成过程驱动的，而且个体之间也存在很大程度的一致性，曲目的个体间方差约为个体内方差的2%。已知的病毒特异性TCRs遵循与所有TCRs相同的生成和选择统计。适应性免疫系统是一组自然多样的T细胞，具有激活生物体防御特定威胁的潜力。T细胞表达不同的表面受体，可以特异性地结合来自病毒、细菌或癌细胞的分子。利用统计模型，我们了解了从651个个体中产生这种多样性的过程的统计数据，包括随机产生和选择T细胞及其受体。我们确定了观察到的变异的不同来源，分离了产生和选择效应。为此，我们开发了一种新的计算工具SONIA，通过比较统计数据和背景样本来量化任何T细胞样本中的选择模式。我们发现群体中变异的共同来源，表明与单个T细胞的多样性相比，群体中的变异是次要的。我们描述了变异及其来源，因此它可以在未来的研究中用于反应性T细胞群体。
The diversity of T-cell receptor (TCR) repertoires is achieved by a combination of two intrinsically stochastic steps: random receptor generation by VDJ recombination, and selection based on the recognition of random self-peptides presented on the major histocompatibility complex. These processes lead to a large receptor variability within and between individuals. However, the characterization of the variability is hampered by the limited size of the sampled repertoires. We introduce a new software tool SONIA to facilitate inference of individual-specific computational models for the generation and selection of the TCR beta chain (TRB) from sequenced repertoires of 651 individuals, separating and quantifying the variability of the two processes of generation and selection in the population. We find not only that most of the variability is driven by the VDJ generation process, but there is a large degree of consistency between individuals with the inter-individual variance of repertoires being about ∼2% of the intra-individual variance. Known viral-specific TCRs follow the same generation and selection statistics as all TCRs. The adaptive immune system is a naturally diverse set of many T cells with the potential to activate the organisms defense against specific threats. T cells express different surface receptors that can specifically bind molecules from viruses, bacteria or cancer cells. Using statistical models we learned the statistics of the processes generating this diversity from a large cohort of 651 individuals, including random generation and selection of T cells and their receptors. We identify the different sources of the observed variability, separating generation and selection effects. For this purpose, we developed a new computational tool SONIA that quantifies selection patterns in any sample of T cells by comparing statistics to background samples. We find common sources of variability in the population, showing that the variability in the population is secondary compared to the diversity of T cells in one individual. We characterize the variability and its sources so it can be used in future studies in reactive T cell populations.
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影响因子：
30.8
作者：
Emerson, Ryan O.;DeWitt, William S.;Robins, Harlan S.
通讯作者：
Robins, Harlan S.
影响因子：
5.8
作者：
Sethna, Zachary;Elhanati, Yuval;Mora, Thierry
通讯作者：
Mora, Thierry
DOI：
10.1073/pnas.1809642115
发表时间：
2018-12-11
影响因子：
11.1
作者：
Pogorelyy, Mikhail V.;Minervina, Anastasia A.;Lebedev, Yuri B.
通讯作者：
Lebedev, Yuri B.
影响因子：
7.3
作者：
Six A;Mariotti-Ferrandiz ME;Chaara W;Magadan S;Pham HP;Lefranc MP;Mora T;Thomas-Vaslin V;Walczak AM;Boudinot P
通讯作者：
Boudinot P
影响因子：
56.9
作者：
Altman, JD;Moss, PAH;Davis, MM
通讯作者：
Davis, MM