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Models and methods for analysis of lymphocyte repertoire generation, development, selection and evolution

机译:淋巴细胞库生成,发育,选择和进化的分析模型和方法

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T and B cell receptor repertoires are diversified by variable region gene rearrangement and selected based on functionality and lack of self-reactivity. Repertoires can also be defined based on phenotype and function rather than receptor specificity - such as the diversity of T helper cell subsets. Natural killer (NK) cell repertoires, in which each cell expresses a randomly chosen subset of its inhibitory receptor genes, and is educated based on self-MHC recognition by yet unknown mechanisms, are also phenotypic repertoires. Studying the generation, development and selection of lymphocyte repertoires, and their functions during immune responses, is essential for understanding the function of the immune system in healthy individuals and in immune deficient, autoimmune or cancer patients. The study of lymphocyte repertoires will enable clinical immunologists to develop better therapeutic monoclonal antibodies, vaccines, transplantation donor-recipient matching protocols, and other immune intervention strategies. The recent development of high-throughput methods for repertoire data collection - from multicolor flow cytometry through single-cell imaging to deep sequencing - presents us now, for the first time, with the ability to analyze and compare large samples of lymphocyte repertoires in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of complex mathematical and computational models, covering processes on multiple scales, from the genetic and molecular to the cellular and system scales.
机译:通过可变区基因重排使T细胞和B细胞受体组成多样化,并根据功能和缺乏自我反应性进行选择。还可以基于表型和功能而不是受体特异性来定义库(例如T辅助细胞亚群的多样性)。天然杀伤(NK)细胞库也是表型库,其中每个细胞表达其抑制性受体基因的随机选择子集,并通过未知机制基于自身MHC识别进行教育。研究淋巴细胞库的产生,发展和选择及其在免疫反应过程中的功能,对于了解健康个体以及免疫缺陷,自身免疫或癌症患者的免疫系统功能至关重要。淋巴细胞库的研究将使临床免疫学家能够开发出更好的治疗性单克隆抗体,疫苗,移植供体-受体匹配方案以及其他免疫干预策略。从多色流式细胞术到单细胞成像再到深度测序,高通量数据收集方法的最新发展首次向我们展示了在健康方面能够分析和比较大量淋巴细胞库的能力,衰老和疾病。然而,这些数据集的指数增长挑战了理论免疫学界,以开发用于数据组织和分析的方法。此外,需要测试有关免疫功能的假设并生成有关医疗干预结果的预测,因此有必要开发复杂的数学和计算模型,涵盖从遗传,分子到细胞和系统等多个尺度的过程。

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