Leveraging high-dimensional flow cytometry to reveal the human immune system at a population-wide scale

Abstract

Abstract Population-wide assessment of the human immune system is needed to better understand immune homeostasis, immune responses against pathogens or the efficacy of vaccines. High-dimensional flow cytometry is the gold standard for in-depth immunophenotyping but the assessment of large cohorts requires multiple experiments over a prolonged period of time and bear multiple sources of error, reducing precision required for sensitive analyses. We performed a large immunophenotyping study using 28-color flow cytometry to investigate the heritability and homeostasis of the immune system and T cell functions in 3000 individuals. Here, we describe our high-throughput sample and data processing pipeline (200 samples/day) in combination with high dimensional flow cytometry to dramatically reduce the number of experiment-days in our study, resulting in low variation and high reproducibility. We demonstrate several carefully optimized strategies to reduce experimental errors and inter-assay variation at every level. In addition, we discuss strategies for pre-processing and analysis of large flow cytometry datasets using manual gating and unsupervised clustering analyses, such as FlowSOM, in view of the fact that most current strategies are highly limited for large datasets. In conclusion, we established a high-throughput high-dimensional flow cytometry pipeline enabling the analysis of thousands of samples with low technical and experimental variation. Our pipeline in combination with our three 28-color flow cytometry panels is adaptable to other large cohort studies for which precision and accuracy over time are important.