A novel alignment method and multiple filters for exclusion of unqualified peptides to enhance label-free quantification using peptide intensity in LC-MS/MS

J Proteome Res. 2011 Oct 7;10(10):4799-812. doi: 10.1021/pr2005633. Epub 2011 Sep 21.


Though many software packages have been developed to perform label-free quantification of proteins in complex biological samples using peptide intensities generated by LC-MS/MS, two critical issues are generally ignored in this field: (i) peptides have multiple elution patterns across runs in an experiment, and (ii) many peptides cannot be used for protein quantification. To address these two key issues, we have developed a novel alignment method to enable accurate peptide peak retention time determination and multiple filters to eliminate unqualified peptides for protein quantification. Repeatability and linearity have been tested using six very different samples, i.e., standard peptides, kidney tissue lysates, HT29-MTX cell lysates, depleted human serum, human serum albumin-bound proteins, and standard proteins spiked in kidney tissue lysates. At least 90.8% of the proteins (up to 1,390) had CVs ≤ 30% across 10 technical replicates, and at least 93.6% (up to 2,013) had R(2) ≥ 0.9500 across 7 concentrations. Identical amounts of standard protein spiked in complex biological samples achieved a CV of 8.6% across eight injections of two groups. Further assessment was made by comparing mass spectrometric results to immunodetection, and consistent results were obtained. The new approach has novel and specific features enabling accurate label-free quantification.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Calibration
  • Chromatography, Liquid / methods*
  • Computational Biology / methods
  • HT29 Cells
  • Humans
  • Mass Spectrometry / methods*
  • Peptides / chemistry*
  • Proteomics / methods
  • Reproducibility of Results
  • Serum Albumin / metabolism
  • Software
  • Staining and Labeling / methods
  • Tandem Mass Spectrometry / methods
  • Time Factors


  • Peptides
  • Serum Albumin