仿形(计算机编程)
计算生物学
基因表达谱
细胞
人细胞
细胞生物学
计算机科学
生物
细胞培养
基因
遗传学
基因表达
操作系统
作者
Jonas Nørskov Søndergaard,Janyerkye Tulyeu,David G. Priest,Shimon Sakaguchi,James B. Wing
标识
DOI:10.1038/s41467-024-55746-1
摘要
Regulatory T cells (Treg) play an important role in regulating immune homeostasis in health and disease. Traditionally their suppressive function has been assayed by mixing purified cell populations, which does not provide an accurate picture of a physiologically relevant response. To overcome this limitation, we here develop 'single cell suppression profiling of human Tregs' (scSPOT). scSPOT uses a 52-marker CyTOF panel, a cell division detection algorithm, and a whole PBMC system to assess the effect of Tregs on all other cell types simultaneously. In this head-to-head comparison, we find Tregs having the clearest suppressive effects on effector memory CD8 T cells through partial division arrest, cell cycle inhibition, and effector molecule downregulation. Additionally, scSPOT identifies a Treg phenotypic split previously observed in viral infection and propose modes of action by the FDA-approved drugs Ipilimumab and Tazemetostat. scSPOT is thus scalable, robust, widely applicable, and may be used to better understand Treg immunobiology and screen for therapeutic compounds. Traditional regulatory T cell (Tregs) assays utilize mixture of purified cell population. Here the authors develop a 'single cell suppression profiling of human Tregs' (scSPOT) with 52-marker CyTOF panel, a cell division detection algorithm, and a whole PBMC system to assess Treg suppressive function on all cell types simultaneously.
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