Electrophoresis-Correlative Ion Mobility Deepens Single-cell Proteomics in Capillary Electrophoresis Mass Spectrometry

Abstract

Detection of trace-sensitive signals is a current challenge is single-cell mass spectrometry (MS) proteomics. Separation prior to detection improves the fidelity and depth of proteome identification and quantification. We recently recognized capillary electrophoresis (CE) electrospray ionization (ESI) for ordering peptides into mass-to-charge (m/z)-dependent series, introducing electrophoresis-correlative (Eco) data-independent acquisition. Here, we demonstrate that these correlations based on electrophoretic mobility ({micro}ef) in the liquid phase are transferred into the gas phase, essentially temporally ordering the peptide ions into charge-dependent ion mobility (IM, 1/K0) trends ({rho} > 0.97). Rather than sampling the entire IM region broadly, we pursued these predictable correlations to schedule narrower frames. Compared to classical ddaPASEF, Eco-framing significantly enhanced the resolution of IM on a trapped ion mobility mass spectrometer (timsTOF PRO). This approach returned [~]50% more proteins from HeLa proteome digests approximating to one-to-two cells, identifying [~]962 proteins from [~]200 pg in <20 min of effective electrophoresis, without match-between-runs. As a proof of principle, we deployed Eco-ddaPASEF on 1,157 proteins by analyzing <4% of the total proteome in single, yolk-laden embryonic stem cells ([~]80-{micro}m) that were isolated from the animal cap of the South African clawed frog (Xenopus laevis). Quantitative profiling of 9 different blastomeres revealed detectable differences among these cells, which are normally fated to form the ectoderm but retain pluripotentiality. Eco-framing effectively deepens the proteome sensitivity in IMS using ddaPASEF, raising the possibility of a proteome-driven classification of embryonic cell differentiation.