Insights into protein post-translational modification landscapes of individual human cells by trapped ion mobility time-of-flight mass spectrometry

Single-cell proteomics is an emerging approach to study cellular heterogeneity but its coverage is still limited. Here, the authors develop a single-cell proteomics approach with improved protein sequence coverage, allowing them to quantify PTMs and characterize effects of inhibitor treatment in single human cells. Single cell proteomics is a powerful tool with potential for markedly enhancing understanding of cellular processes. Here we report the development and application of multiplexed single cell proteomics using trapped ion mobility time-of-flight mass spectrometry. When employing a carrier channel to improve peptide signal, this method allows over 40,000 tandem mass spectra to be acquired in 30 min. Using a KRAS(G12C) model human-derived cell line, we demonstrate the quantification of over 1200 proteins per cell with high relative sequence coverage permitting the detection of multiple classes of post-translational modifications in single cells. When cells were treated with a KRAS(G12C) covalent inhibitor, this approach revealed cell-to-cell variability in the impact of the drug, providing insight missed by traditional proteomics. We provide multiple resources necessary for the application of single cell proteomics to drug treatment studies including tools to reduce cell cycle linked proteomic effects from masking pharmacological phenotypes.

Automated summary

Single-cell proteomics is a powerful tool for studying cellular heterogeneity and quantifying post-translational modifications. The authors developed a method with improved protein sequence coverage and demonstrated its application in characterizing the effects of inhibitor treatment in single human cells. This approach allows for the detection of multiple classes of post-translational modifications and provides insight into cell-to-cell variability in drug response that is missed by traditional proteomics.