Spectral averaging with outlier rejection algorithms to increase identifications in top-down proteomics

Intact Mass Proteomics Using a Proteoform Atlas

Top-down proteomics, the characterization of intact proteoforms by tandem mass spectrometry, is the principal method for proteoform characterization in complex samples. Top-down proteomics relies on precursor isolation and subsequent gas-phase fragmentation to make proteoform identifications. While this strategy can produce highly detailed molecular information, the reliance on time-intensive tandem MS limits the speed with which proteoforms can be identified. We suggest that once proteoforms have been identified by top-down analysis in a system of interest, and archived in a system-specific Proteoform Atlas, subsequent analyses in that system can utilize the Atlas information to enable simpler and faster MS1-only identifications. We explore this idea here, using the E. coli ribosome as a model system of limited complexity. We used deep top-down analysis to construct an E. coli ribosomal Proteoform Atlas containing 2099 proteoforms from 52 of the 54 proteins that make up the E. coli ribosome. We show that using the Atlas enables confident MS1-only identifications of E. coli ribosomal proteoforms from E. coli that were perturbed by exposure to cold. Furthermore, this Atlas strategy identifies proteoforms up to 77% more rapidly compared to top-down identifications that require acquisition of both MS1 and MS2 spectra.