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

Detection of trace-sensitive signals is a current challenge in 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 (μ_ef) in the liquid phase are transferred into the gas phase, essentially temporally sorting the peptide ions into charge-dependent ion mobility (IM, 1/K₀) trends (ρ > 0.97). Rather than sampling the entire IM region broadly, we pursued these predictable correlations to schedule narrower frames. Compared to classical data-dependent (dda) PASEF, Eco-framing significantly enhanced the resolution of IM MS (IMS) on a trapped IM 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-IMS to detect 1157 proteins by analyzing <4% of the total proteome content in single, yolk-laden embryonic stem cells (∼80-μm) that were isolated from the animal cap of the South African clawed frog (Xenopus laevis). Quantitative profiling of nine different blastomeres revealed detectable differences among these cells, which are normally fated to form the ectoderm but retain pluripotentiality. Eco-framing in the IM dimension effectively deepens the proteome sensitivity in IMS using ddaPASEF, facilitating the proteome-driven classification of differentiating cells, as demonstrated in the chordate frog embryo in this report.