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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
An exclusion list based label-free proteome quantification approach using an LTQ Orbitrap.
Jan Muntel1, Michael Hecker, Dörte Becher
1Institute for Microbiology, Ernst Moritz Arndt University Greifswald, Friedrich-Ludwig-Jahn-Str. 15, D-17489, Greifswald, Germany.
Rapid Communications in Mass Spectrometry : RCM
|February 14, 2012
Summary
This study introduces an optimized label-free liquid chromatography/tandem mass spectrometry (LC/MS/MS) workflow. The enhanced method improves protein identification and quantification, offering a viable alternative to label-based approaches for complex samples.
Area of Science:
- Proteomics
- Analytical Chemistry
- Biochemistry
Background:
- Label-based mass spectrometry is effective for protein identification and quantification.
- Challenges exist in labeling scarce or non-cultivable samples.
- A need for efficient label-free methods is apparent.
Purpose of the Study:
- To develop and validate an efficient label-free liquid chromatography/tandem mass spectrometry (LC/MS/MS) workflow.
- To enhance protein identification and quantification sensitivity and resolution.
- To provide an alternative to label-based quantification.
Main Methods:
- Optimized instrument settings for LTQ Orbitrap.
- Incorporation of incremental exclusion lists.
- Comparison with control (no exclusion lists) and in vivo metabolic labeling (GeLC/MS/MS) experiments.
- Analysis of Staphylococcus aureus whole cell lysates under different stress conditions.
Main Results:
- The new workflow increased the number of identified peptides.
- Enabled label-free quantification of over 990 S. aureus proteins.
- Results were consistent with metabolic labeling experiments for protein quantification and differential expression.
Conclusions:
- Optimized LC/MS/MS with exclusion lists significantly improves label-free protein quantification.
- This workflow is a powerful alternative to label-based methods.
- Enhances sensitivity and resolution for proteomic analyses.
