An Integrated Experimental and Informatics Strategy Enables Large Proteoform Identification in Top-Down Proteomics

Abstract

Top-down proteomics enables identification and characterization of intact proteoforms, preserving information on co-occurring sequence variations and post-translational modifications. However, identifying large proteoforms remains challenging due to an exponential decrease in signal-to-noise ratio with increasing molecular weight, interference from coeluting smaller species, unresolved precursor isotopic envelopes, difficulty obtaining informative MS/MS spectra, and limitations of current informatics tools. To address these challenges, here we present an integrated experimental and informatics strategy combining protein separation, data acquisition, precursor mass assignment, and MS/MS interpretation. First, we demonstrate that online two-dimensional liquid chromatography coupling size-exclusion and reversed-phase separations enables facile detection of large proteoforms. We then utilize a precursor mass correction strategy to enable conventional database searching of data-dependent acquisition (DDA) data containing isotopically unresolved precursors. Finally, we use data-independent acquisition (DIA) optimized for large proteins to enhance fragment signal and enable identification through intact-mass-guided candidate discovery and MS/MS validation. Applied to human heart tissue, the integrated strategy identified 703 nonredundant proteoforms from 236 unique proteins, including 65 proteins >30 kDa and 22 proteins >50 kDa, with identifications extending to 223 kDa. This integrated strategy bridges the detection-to-identification gap for large proteins and expands the accessible mass range of discovery top-down proteomics.