Predicting electrophoretic mobility of proteoforms for large-scale top-down proteomics

ABSTRACT: Large-scale top-down proteomics characterizes proteoforms in cells globally with high confidence and high throughput using reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) or capillary zone electrophoresis (CZE)-MS/MS. The false discovery rate (FDR) from the target-decoy database search is typically deployed to filter identified proteoforms to ensure high-confidence identifications (IDs). It has been demonstrated that the FDRs in top-down proteomics can be drastically underestimated. An alternative approach to the FDR can be useful for further evaluating the confidence of proteoform IDs after database search. We argue that predicting retention/migration time of proteoforms from the RPLC/CZE separation accurately and comparing their predicted and experimental separation time could be a useful and practical approach. Based on our knowledge, there is still no report in the literature about predicting separation time of proteoforms using large top-down proteomics datasets. In this pilot study, for the first time, we evaluated various semi-empirical models for predicting proteoforms’ electrophoretic mobility (µef) using large-scale top-down proteomics datasets from CZE-MS/MS. We achieved a linear correlation between experimental and predicted µef of E. coli proteoforms (R2=0.98) with a simple semi-empirical model, which utilizes the number of charges and molecular mass of each proteoform as the parameters. Our modeling data suggest that the complete unfolding of proteoforms during CZE separation benefits the prediction of their µef. Our results also indicate that N-terminal acetylation and phosphorylation both decrease proteoforms’ charge by roughly one charge unit.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Escherichia Coli

SUBMITTER: Liangliang Sun  

LAB HEAD: Liangliang Sun

PROVIDER: PXD017265 | Pride | 2020-02-17

REPOSITORIES: Pride