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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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Related Experiment Video

Updated: Jun 23, 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

Longitudinal Large-Scale Semiquantitative Proteomic Data Stability Across Multiple Instrument Platforms.

Congcong Lu¹, Tina Glisovic-Aplenc^2,3, Kathrin M Bernt^2,3

¹Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104, United States.

Journal of Proteome Research

|October 20, 2021

Summary

Label-free proteomics is reproducible across different mass spectrometry platforms and over multiple years. This study demonstrates consistent quantification of over 2300 cell surface proteins, supporting multiyear and multiplatform proteomic study designs.

Keywords:

label-free quantification large-scale mass spectrometry quantitative proteomics reproducibility surfaceome target discovery

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Last Updated: Jun 23, 2026

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

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Published on: November 15, 2017

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Area of Science:

Proteomics
Mass Spectrometry
Cell Biology

Background:

Label-free semiquantitative proteomics is widely used for protein abundance profiling.
Reproducibility of label-free proteomics data across different platforms and over time is not well understood.

Purpose of the Study:

To evaluate the reproducibility of label-free semiquantitative proteomics across three liquid chromatography-mass spectrometry (LC-MS) platforms over a six-year period.
To assess the performance of these platforms for cell surface protein quantification.

Main Methods:

Utilized three LC-MS platforms: Orbitrap Elite, Q Exactive HF, and Orbitrap Fusion.
Employed sucrose gradient ultracentrifugation for surfaceome enrichment followed by gel separation for protein identification.
Applied label-free semiquantitative analysis to profile protein abundances.

Main Results:

Consistently detected and reproducibly quantified over 2300 putative cell surface proteins in a human acute myeloid leukemia (AML) cell line.
Achieved high reproducibility across all three platforms and over the six-year study period.
This is the first study to report highly reproducible semiquantitative proteomic data collection across multiple years and LC-MS platforms.

Conclusions:

Provides experimental validation for using label-free semiquantitative proteomics in multiyear and multiplatform study designs.
Supports the feasibility of large-scale and longitudinal proteomic studies, even with limited access to high-throughput facilities.
Data are publicly available via ProteomeXchange (PXD022721).