The fate and physiology of individual cells are controlled by proteins. Yet, our ability to quantitatively analyze proteins in single cells has remained limited. To overcome this barrier, we developed SCoPE2. It substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enabled us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiated into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantified over 3,042 proteins in 1,490 single monocytes and macrophages in ten days of instrument time, and the quantified proteins allowed us to discern single cells by cell type. Furthermore, the data uncovered a continuous gradient of proteome states for the macrophage-like cells, suggesting that macrophage heterogeneity may emerge even in the absence of polarizing cytokines. Parallel measurements of transcripts by 10x Genomics scRNA-seq suggest that our measurements sampled 20-fold more protein copies than RNA copies per gene, and thus SCoPE2 supports quantification with improved count statistics. Joint analysis of the data illustrates how variability across single cells can reveal transcriptional and post-transcriptional gene regulation. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass-spectrometry.Competing Interest StatementThe authors have declared no competing interest.
slavovLabThe monthly video of the lecture series 𝑺𝒕𝒂𝒕𝒊𝒔𝒕𝒊𝒄𝒔 𝒇𝒐𝒓 𝒑𝒓𝒐𝒕𝒆𝒐𝒎𝒊𝒄𝒔 is focused on non-ignorable missing data.
Ignoring non-ignorable missingness leads to survivor bias & other artifacts t.co/v4rlCT2lust.co/HHmH8qVBbw