Abstract

Single-cell proteomics has attracted a lot of attention in recent years because it offers more functional relevance than single-cell transcriptomics. However, most work to date focused on cell typing, which has been widely accomplished by single-cell transcriptomics. Here we report the use of single-cell proteomics to measure the correlations between the translational levels of any pair of proteins in a single mammalian cell. In measuring pairwise correlations among [~]1,000 proteins in a population of homogeneous K562 cells in a steady-state condition, we observed multiple correlated protein modules (CPMs), each containing a group of highly positively correlated proteins that are functionally interacting and collectively involved in certain biological functions, such as protein synthesis and oxidative phosphorylation. Some CPMs are shared across different cell types while others are cell-type specific. Widely studied in omics analyses, pairwise correlations are often measured by introducing perturbations to bulk samples. However, some correlations of gene or protein expression in steady-state condition would be masked by perturbation. The single-cell correlations probed in our experiment reflect intrinsic steady-state fluctuations in the absence of perturbation. We note that observed correlations between proteins are experimentally more distinct and functionally more relevant than those between corresponding mRNAs measured in single-cell transcriptomics. By virtue of single-cell proteomics, functional coordination of proteins is manifested through CPMs. Table of Contents Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/520903v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@10e27corg.highwire.dtl.DTLVardef@857044org.highwire.dtl.DTLVardef@8d9731org.highwire.dtl.DTLVardef@1c149a4_HPS_FORMAT_FIGEXP M_FIG C_FIG