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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Updated: Jun 11, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Options and considerations when selecting a quantitative proteomics strategy.

Bruno Domon¹, Ruedi Aebersold

¹Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland. bruno.domon@crp-santa.lu

Nature Biotechnology

|July 13, 2010

Summary

This summary is machine-generated.

This study compares three mass spectrometry (MS) proteomic strategies: shotgun, directed, and targeted. It provides a framework for selecting the best MS proteomic approach based on research needs and sample composition.

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Area of Science:

Proteomics
Analytical Chemistry
Biochemistry

Background:

Proteomic studies predominantly use mass spectrometry (MS) for peptide identification and quantification.
Existing MS-based proteomic methods vary in instrumentation, performance, biological integration, and data requirements.

Purpose of the Study:

To review and compare the three primary MS-based proteomic approaches: shotgun, directed, and targeted.
To offer a guide for selecting the most appropriate proteomic strategy for specific research questions.

Main Methods:

Discussion of the principles, strengths, and weaknesses of shotgun, directed, and targeted MS proteomic strategies.
Analysis of how sample composition influences the performance of each MS proteomic approach.

Main Results:

Each MS proteomic strategy (shotgun, directed, targeted) has distinct advantages and limitations.
The effectiveness of each method is significantly influenced by the characteristics of the biological sample being analyzed.

Conclusions:

A clear understanding of different MS proteomic strategies is crucial for effective experimental design.
Selecting the optimal strategy depends on the research objective and the specific biological sample, enabling more robust proteomic insights.