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利用 T 细胞受体库来理解适应性免疫识别的原理。

Using T Cell Receptor Repertoires to Understand the Principles of Adaptive Immune Recognition.

机构信息

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; email:

Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA.

出版信息

Annu Rev Immunol. 2019 Apr 26;37:547-570. doi: 10.1146/annurev-immunol-042718-041757. Epub 2019 Jan 30.

Abstract

Adaptive immune recognition is mediated by antigen receptors on B and T cells generated by somatic recombination during lineage development. The high level of diversity resulting from this process posed technical limitations that previously limited the comprehensive analysis of adaptive immune recognition. Advances over the last ten years have produced data and approaches allowing insights into how T cells develop, evolutionary signatures of recombination and selection, and the features of T cell receptors that mediate epitope-specific binding and T cell activation. The size and complexity of these data have necessitated the generation of novel computational and analytical approaches, which are transforming how T cell immunology is conducted. Here we review the development and application of novel biological, theoretical, and computational methods for understanding T cell recognition and discuss the potential for improved models of receptor:antigen interactions.

摘要

适应性免疫识别是由 B 细胞和 T 细胞上的抗原受体介导的,这些受体是在谱系发育过程中通过体细胞重组产生的。这种过程产生的高度多样性带来了技术限制,以前限制了对适应性免疫识别的全面分析。过去十年的进展产生了数据和方法,使我们能够深入了解 T 细胞的发育、重组和选择的进化特征,以及介导表位特异性结合和 T 细胞激活的 T 细胞受体的特征。这些数据的规模和复杂性需要生成新的计算和分析方法,这正在改变 T 细胞免疫学的研究方式。在这里,我们回顾了用于理解 T 细胞识别的新型生物学、理论和计算方法的发展和应用,并讨论了改进受体:抗原相互作用模型的潜力。

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