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Updated: Feb 9, 2026
09:00
A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
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Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics.
J Astor Ankney1, Adil Muneer1, Xian Chen1,2
1Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599, USA;
Summary
Quantitative proteomics using mass spectrometry aids biological system analysis. This review covers label-free and labeling strategies for accurate protein quantitation, comparing their strengths and weaknesses for diverse applications.
Area of Science:
- Proteomics
- Mass Spectrometry
- Quantitative Biology
Background:
- Mass spectrometry-based quantitative proteomics offers insights into biological systems.
- Peptide ionization efficiency varies, affecting direct abundance correlation in mass spectra.
- Comparative proteomic experiments are crucial for identifying differentially expressed proteins.
Purpose of the Study:
- To review widely used label-free and labeling-based proteomic quantitation strategies.
- To compare the strengths and weaknesses of various techniques.
- To present applications for addressing biological complexities.
Main Methods:
- Discussion of label-free quantitative proteomic strategies.
- Analysis of metabolic-, enzymatic-, and chemical labeling-based proteomic strategies.
- Evaluation of techniques based on quantification accuracy, proteome coverage, multiplexing, and robustness.
Main Results:
- Label-free and labeling strategies enable nonbiased identification of differentially expressed proteins.
- Each technique presents specific advantages and limitations.
- The choice of strategy depends on the biological question and desired accuracy.
Conclusions:
- Various proteomic quantitation strategies exist, each with unique trade-offs.
- Understanding these methods is key to selecting the most appropriate approach for specific research.
- These techniques are vital for advancing our understanding of biological systems in health and disease.
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