Quantitation and Identification of Thousands of Human Proteoforms below 30 kDa

Kenneth R. Durbin, Luca Fornelli, Ryan T. Fellers, Peter F. Doubleday, Masashi Narita, Neil L. Kelleher*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

Abstract

Top-down proteomics is capable of identifying and quantitating unique proteoforms through the analysis of intact proteins. We extended the coverage of the label-free technique, achieving differential analysis of whole proteins <30 kDa from the proteomes of growing and senescent human fibroblasts. By integrating improved control software with more instrument time allocated for quantitation of intact ions, we were able to collect protein data between the two cell states, confidently comparing 1577 proteoform levels. To then identify and characterize proteoforms, our advanced acquisition software, named Autopilot, employed enhanced identification efficiency in identifying 1180 unique Swiss-Prot accession numbers at 1% false-discovery rate. This coverage of the low mass proteome is equivalent to the largest previously reported but was accomplished in 23% of the total acquisition time. By maximizing both the number of quantified proteoforms and their identification rate in an integrated software environment, this work significantly advances proteoform-resolved analyses of complex systems.

Original languageEnglish (US)
Pages (from-to)976-982
Number of pages7
JournalJournal of Proteome Research
Volume15
Issue number3
DOIs
StatePublished - Mar 4 2016

Keywords

  • Fourier transform mass spectrometry
  • GELFrEE
  • cellular senescence
  • differential mass spectrometry
  • label-free
  • proteoform
  • quantitative proteomics
  • top-down proteomics

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

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