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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Interference-free proteome quantification with MS/MS-based isobaric isotopologue detection.

Casimir Bamberger1, Sandra Pankow, Sung Kyu Robin Park

  • 1Department of Chemical Physiology, The Scripps Research Institute , 10550 North Torrey Pines Road, California 92037, United States.

Journal of Proteome Research
|January 15, 2014
PubMed
Summary

This study introduces a new method for peptide quantification in proteomics. By measuring fragment isotopologues, it overcomes interference issues in mass spectrometry for more accurate protein measurements.

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Biochemistry

Background:

  • Chemical labeling of peptides is crucial for relative protein quantification in shotgun proteomics.
  • Existing isobaric labeling methods suffer from distorted ratio measurements due to co-selected interfering peptides.

Purpose of the Study:

  • To develop a novel method for accurate peptide quantification by reducing precursor interference.
  • To improve the reliability of relative protein quantification in complex biological samples.

Main Methods:

  • Quantification of isobaric peptide fragment isotopologues in tandem mass spectra.
  • Utilizing relative quantification of dimethylated peptide fragments after higher-energy collisional dissociation (HCD).

Main Results:

  • The novel method significantly reduces precursor interference in quantitative proteomics.
  • Achieved precise proteome quantification down to single spectra per protein.
  • Quantified over 90% of proteins in a MudPIT experiment and accurately measured proteins in a cystic fibrosis cell model.

Conclusions:

  • Quantitation of isobaric peptide fragment isotopologues offers a more accurate approach to relative protein quantification.
  • This method enhances the precision and scope of proteomic analysis, even in challenging samples.
  • The technique has direct applications in understanding disease mechanisms, such as in cystic fibrosis research.