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Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
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Systematic evaluation of label-free and super-SILAC quantification for proteome expression analysis
Andreas Tebbe1, Martin Klammer1, Stefanie Sighart1
1Evotec (München) GmbH, Am Klopferspitz 19a, 82152, Martinsried, Germany.
Rapid Communications in Mass Spectrometry : RCM
|September 18, 2015
Summary
Label-free proteome quantification on advanced mass spectrometry is effective for biomarker discovery. Additional replicate analyses and peptide fractionation enhance its precision and robustness for high-coverage proteome profiling.
Area of Science:
- Proteomics
- Mass Spectrometry
- Biomarker Discovery
Background:
- Mass spectrometry (MS)-based proteomics enables comprehensive proteome profiling.
- Accurate quantification is crucial for high-coverage proteome analysis on modern instruments like quadrupole orbitrap mass spectrometers.
Purpose of the Study:
- To systematically compare label-free proteome quantification with stable isotope labeling using amino acids in cell culture (super-SILAC).
- To evaluate label-free quantification strategies for high-coverage proteome analysis on ultra-high-performance liquid chromatography (UHPLC)/MS.
Main Methods:
- UHPLC/MS experiments were performed on a Q Exactive instrument.
- Label-free quantification was compared against super-SILAC using six human cancer cell lines.
- Peptide fractionation using high pH reversed-phase chromatography was investigated.
Main Results:
- Label-free methods identified more proteins (approx. 5000) than super-SILAC (approx. 3500).
- Label-free quantification showed slightly lower precision than super-SILAC but was improved by replicate analyses and peptide fractionation.
- More significant differences in cell line comparisons were detected using label-free quantification.
Conclusions:
- Label-free proteome quantification is a valuable tool for target and biomarker discovery.
- State-of-the-art UHPLC/MS workflows benefit from robust label-free quantification strategies.
- Optimized label-free approaches enhance proteome coverage and precision.

