高通量高内涵免疫表型分析的稳健流程揭示了血液白细胞随年龄和遗传的变化。
A robust pipeline for high-content, high-throughput immunophenotyping reveals age- and genetics-dependent changes in blood leukocytes.
机构信息
ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD, USA.
Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
出版信息
Cell Rep Methods. 2023 Oct 23;3(10):100619. doi: 10.1016/j.crmeth.2023.100619.
High-dimensional flow cytometry is the gold standard to study the human immune system in large cohorts. However, large sample sizes increase inter-experimental variation because of technical and experimental inaccuracies introduced by batch variability. Our high-throughput sample processing pipeline in combination with 28-color flow cytometry focuses on increased throughput (192 samples/experiment) and high reproducibility. We implemented quality control checkpoints to reduce technical and experimental variation. Finally, we integrated FlowSOM clustering to facilitate automated data analysis and demonstrate the reproducibility of our pipeline in a study with 3,357 samples. We reveal age-associated immune dynamics in 2,300 individuals, signified by decreasing T and B cell subsets with age. In addition, by combining genetic analyses, our approach revealed unique immune signatures associated with a single nucleotide polymorphism (SNP) that abrogates CD45 isoform splicing. In summary, we provide a versatile and reliable high-throughput, flow cytometry-based pipeline for immune discovery and exploration in large cohorts.
高维流式细胞术是研究大样本人群人类免疫系统的金标准。然而，由于批次变化带来的技术和实验误差，大样本量会增加实验间的变异性。我们的高通量样本处理流水线结合 28 色流式细胞术，侧重于提高通量（每个实验 192 个样本）和高重复性。我们实施了质量控制检查点，以减少技术和实验变异性。最后，我们整合了 FlowSOM 聚类，以方便自动化数据分析，并在一项包含 3357 个样本的研究中证明了我们的流水线的重现性。我们揭示了与年龄相关的免疫动态，表现为随着年龄的增长 T 和 B 细胞亚群减少。此外，通过结合遗传分析，我们的方法揭示了与一种单核苷酸多态性（SNP）相关的独特免疫特征，该 SNP 会破坏 CD45 同工型的剪接。总之，我们提供了一种通用且可靠的高通量、基于流式细胞术的流水线，用于在大样本中进行免疫发现和探索。
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