Optimizing single cell proteomics using trapped ion mobility spectrometry for label-free experiments
Dong‐Gi Mun, Firdous Ahmad Bhat, Husheng Ding, Benjamin J. Madden, Sekar Natesampillai, Andrew D. Badley, Kenneth L. Johnson, Ryan Kelly, Akhilesh Pandey
Abstract
resulted in a substantial gain in the depth of proteome coverage and in detecting proteins with low abundance. We used these optimized conditions for proteome profiling of sorted human primary T cells, which yielded an average of 365, 804, 1116, and 1651 proteins from single, five, ten, and forty T cells, respectively. Notably, we demonstrated that the depth of proteome coverage from a low number of cells was sufficient to delineate several essential metabolic pathways and the T cell receptor signaling pathway. Finally, we showed the feasibility of detecting post-translational modifications including phosphorylation and acetylation from single cells. We believe that such an approach could be applied to label-free analysis of single cells obtained from clinically relevant samples.