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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...

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Related Experiment Video

Updated: Apr 30, 2026

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

Comparison at the peptide level with post-translational modification consideration reveals more differences between

Jianrui Yin¹, Chen Shao, Lulu Jia

¹Department of Pathophysiology, National Key Laboratory of Medical Molecular Biology Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.

Rapid Communications in Mass Spectrometry : RCM

|May 7, 2014

Summary

Comparing peptide data with post-translational modifications (PTMs) reveals differences between leukemia cell lines. This approach uncovers more information lost in traditional protein inference methods.

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Last Updated: Apr 30, 2026

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Area of Science:

Proteomics
Biochemistry
Mass Spectrometry

Background:

Shotgun proteomics infers protein presence from peptide data.
Traditional protein inference methods can lead to errors and information loss.
Post-translational modifications (PTMs) significantly impact protein function and are often overlooked.

Purpose of the Study:

To compare proteomic data at the peptide level between two leukemia cell lines (Jurkat and K562).
To investigate information loss in traditional protein inference by considering PTMs.
To identify differences in peptide modifications between cell lines.

Main Methods:

Raw proteomic files from Jurkat and K562 cell lines were searched against the IPI-human database.
Observed peptide modifications were manually matched to the Unimod database.
Only peptides with post-translational modifications were compared between the cell lines.

Main Results:

A total of 44,046 non-redundant peptides were identified across both cell lines.
11.43% of identified peptides exhibited different PTM forms between the Jurkat and K562 cell lines.
1.73% of peptides were modified in both cell lines, but with different modifications or on different sites.

Conclusions:

Comparing proteomic data at the peptide level, including PTMs, reveals more differences between samples than traditional methods.
This peptide-centric approach enhances the understanding of proteomic variations, especially in unenriched samples.
Considering PTMs at the peptide level is crucial for a comprehensive proteomic analysis.