仿形(计算机编程)
高通量筛选
细胞
化学
抗原
计算生物学
计算机科学
生物
生物化学
免疫学
操作系统
作者
Shiyu Wang,Yan Zhou,Keyang Ding,Zhihao Ding,Wenjie Zhang,Yang Liu
标识
DOI:10.1016/j.bios.2024.116815
摘要
Identifying antigen-specific T cells from tumor-infiltrating lymphocytes is essential for designing effective T cell immunotherapies. Traditional methods can detect antigen-specific T cells but struggle with high-throughput screening and multimodal profiling simultaneously. To address this issue, we developed DropCCI, a new strategy that transfers antigen information to co-incubated T cells for high-throughput, non-contaminated multimodal profiling. In DropCCI, droplets encapsulated DNA barcodes and antigen-loaded antigen-presenting cells (APCs), while click chemistry-modified T cells were injected into these droplets to capture free barcodes and acquire the corresponding antigen information. Following cell-cell interaction, APCs were removed via streptavidin-biotin conjugation, to prevent contamination. The resulting T cells underwent single-cell omics sequencing for comprehensive profiling of their antigen specificity, transcriptome, and genomics accurately. This click-chemistry method allowed detection of antigen-specific T cells without lysing APCs, avoiding cross-cell contamination and enabling low-noise multimodal profiling of primary T cells. With a completion time within 12 h and no requirement for complex equipment, DropCCI provides unbiased single-cell sequencing results that offer a comprehensive understanding of anti-tumor T cell responses. The concept of DropCCI holds great promise not only for advancing the field of T cell immunotherapy but also for its potential application in studying other cell-cell interactions.
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