PXD017265

PXD017265 is an original dataset announced via ProteomeXchange.

Title	Predicting electrophoretic mobility of proteoforms for large-scale top-down proteomics
Description	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.
HostingRepository	PRIDE
AnnounceDate	2020-02-18
AnnouncementXML	Submission_2020-02-17_22:48:41.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Liangliang Sun
SpeciesList	scientific name: Escherichia coli; NCBI TaxID: 562;
ModificationList	phosphorylated residue; acetylated residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2020-01-23 06:20:38	ID requested
⏵ 1	2020-02-17 22:48:43	announced

Chen D, Lubeckyj RA, Yang Z, McCool EN, Shen X, Wang Q, Xu T, Sun L, Predicting Electrophoretic Mobility of Proteoforms for Large-Scale Top-Down Proteomics. Anal Chem, 92(5):3503-3507(2020) [pubmed]

submitter keyword: electrophoretic mobility, proteoform, top-down proteomics, CZE-MS

Liangliang Sun
contact affiliation	Michigan State University
contact email	lsun@chemistry.msu.edu
lab head
Liangliang Sun
contact affiliation	Michigan State University
contact email	lsun@chemistry.msu.edu
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD017265
     1. Label: PRIDE project
     2. Name: Predicting electrophoretic mobility of proteoforms for large-scale top-down proteomics