Direct comparison of mass cytometry and single-cell RNA sequencing of human peripheral blood mononuclear cells. Direct comparison of mass cytometry and single-cell RNA sequencing of human peripheral blood mononuclear cells

Single-cell methods offer a high-resolution approach for characterizing cell populations. Many studies rely on single-cell transcriptomics to draw conclusions regarding cell state and behavior, with the underlying assumption that transcriptomic readouts largely parallel their protein counterparts and subsequent activity. However, the relationship between transcriptomic and proteomic measurements is imprecise, and thus datasets that probe the extent of their concordance will be useful to refine such conclusions. Additionally, novel single-cell analysis tools often lack appropriate gold standard datasets for the purposes of assessment. Integrative (combining the two data modalities) and predictive (using one modality to improve results from the other) approaches in particular, would benefit from transcriptomic and proteomic data from the same sample of cells. For these reasons, we performed single-cell RNA sequencing, mass cytometry, and flow cytometry on a split-sample of human peripheral blood mononuclear cells. We directly compare the proportions of specific cell types resolved by each technique, and further describe the extent to which protein and mRNA measurements correlate within distinct cell types. Overall design: We perform single-cell RNA-sequencing on a split-sample of human peripheral blood mononuclear cells.

单细胞分析技术（single-cell methods）为细胞群体的特征表征提供了高分辨率的研究手段。诸多研究依托单细胞转录组学（single-cell transcriptomics）推导与细胞状态及行为相关的研究结论，其潜在前提假设为：转录组读数在很大程度上与对应的蛋白质组结果及后续生物活性保持一致。然而，转录组与蛋白质组的测量结果之间的关联并不精准，因此能够探究二者一致性程度的数据集，将有助于优化此类研究结论。此外，新型单细胞分析工具通常缺乏适用于性能评估的金标准数据集（gold standard datasets）。尤其是整合（结合两种数据模态）与预测（利用一种数据模态优化另一模态的分析结果）类分析方法，将可从同一细胞样本的转录组与蛋白质组数据中获得显著增益。基于上述原因，我们对人外周血单个核细胞（peripheral blood mononuclear cells）的分样样本开展了单细胞RNA测序（single-cell RNA sequencing）、质谱流式细胞术（mass cytometry）与流式细胞术（flow cytometry）实验。我们直接对比了各技术所解析的特定细胞类型的占比，并进一步阐明了不同细胞类型内蛋白质与mRNA测量值的相关程度。整体实验设计：我们对人外周血单个核细胞的分样样本实施了单细胞RNA测序。