A correlation algorithm for the automated quantitative analysis of shotgun proteomics data

Anal Chem. 2003 Dec 15;75(24):6912-21. doi: 10.1021/ac034790h.

Abstract

Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 +/- 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Automation
  • Databases as Topic*
  • Mass Spectrometry / methods
  • Molecular Sequence Data
  • Peptides / analysis
  • Peptides / chemistry
  • Proteins / analysis
  • Proteins / chemistry
  • Proteomics / methods*
  • Saccharomyces cerevisiae / chemistry

Substances

  • Peptides
  • Proteins