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采用 AIMS(自动化免疫分子分离器)对免疫受体库进行特征分析的综合方法。

An integrated approach to the characterization of immune repertoires using AIMS: An Automated Immune Molecule Separator.

机构信息

Computational Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.

出版信息

PLoS Comput Biol. 2023 Oct 20;19(10):e1011577. doi: 10.1371/journal.pcbi.1011577. eCollection 2023 Oct.

DOI:10.1371/journal.pcbi.1011577
PMID:37862356
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10619816/
Abstract

The adaptive immune system employs an array of receptors designed to respond with high specificity to pathogens or molecular aberrations faced by the host organism. Binding of these receptors to molecular fragments-collectively referred to as antigens-initiates immune responses. These antigenic targets are recognized in their native state on the surfaces of pathogens by antibodies, whereas T cell receptors (TCR) recognize processed antigens as short peptides, presented on major histocompatibility complex (MHC) molecules. Recent research has led to a wealth of immune repertoire data that are key to interrogating the nature of these molecular interactions. However, existing tools for the analysis of these large datasets typically focus on molecular sets of a single type, forcing researchers to separately analyze strongly coupled sequences of interacting molecules. Here, we introduce a software package for the integrated analysis of immune repertoire data, capable of identifying distinct biophysical differences in isolated TCR, MHC, peptide, antibody, and antigen sequence data. This integrated analytical approach allows for direct comparisons across immune repertoire subsets and provides a starting point for the identification of key interaction hotspots in complementary receptor-antigen pairs. The software (AIMS-Automated Immune Molecule Separator) is freely available as an open access package in GUI or command-line form.

摘要

适应性免疫系统采用了一系列受体,这些受体旨在高度特异性地响应宿主生物体所面临的病原体或分子异常。这些受体与分子片段(统称为抗原)结合,引发免疫反应。这些抗原靶标在病原体表面以其天然状态被抗体识别,而 T 细胞受体 (TCR) 则将加工过的抗原识别为 MHC 分子上的短肽。最近的研究产生了大量的免疫库数据,这些数据是探究这些分子相互作用性质的关键。然而,现有的这些大型数据集的分析工具通常侧重于单一类型的分子集,迫使研究人员分别分析相互作用分子的强耦合序列。在这里,我们引入了一个用于免疫库数据综合分析的软件包,该软件包能够识别 TCR、MHC、肽、抗体和抗原序列数据中独特的物理差异。这种综合分析方法允许在免疫库亚群之间进行直接比较,并为识别互补受体-抗原对中的关键相互作用热点提供了起点。该软件(AIMS-Automated Immune Molecule Separator)以 GUI 或命令行形式免费提供,作为开放访问包。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/7534d284de72/pcbi.1011577.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/9263f326a263/pcbi.1011577.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/6a3120c88213/pcbi.1011577.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/befb01a40a38/pcbi.1011577.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/e25228158825/pcbi.1011577.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/0df4ab93023e/pcbi.1011577.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/7534d284de72/pcbi.1011577.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/9263f326a263/pcbi.1011577.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/6a3120c88213/pcbi.1011577.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/befb01a40a38/pcbi.1011577.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/e25228158825/pcbi.1011577.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/0df4ab93023e/pcbi.1011577.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e625/10619816/7534d284de72/pcbi.1011577.g006.jpg

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