Open Access Highly Accessed Research article

Initial characterization of the human central proteome

Thomas R Burkard, Melanie Planyavsky, Ines Kaupe, Florian P Breitwieser, Tilmann Bürckstümmer, Keiryn L Bennett, Giulio Superti-Furga and Jacques Colinge*

Author Affiliations

CeMM - Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 19/3, A-1090 Vienna, Austria

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BMC Systems Biology 2011, 5:17  doi:10.1186/1752-0509-5-17

Published: 26 January 2011

Abstract

Background

On the basis of large proteomics datasets measured from seven human cell lines we consider their intersection as an approximation of the human central proteome, which is the set of proteins ubiquitously expressed in all human cells. Composition and properties of the central proteome are investigated through bioinformatics analyses.

Results

We experimentally identify a central proteome comprising 1,124 proteins that are ubiquitously and abundantly expressed in human cells using state of the art mass spectrometry and protein identification bioinformatics. The main represented functions are proteostasis, primary metabolism and proliferation. We further characterize the central proteome considering gene structures, conservation, interaction networks, pathways, drug targets, and coordination of biological processes. Among other new findings, we show that the central proteome is encoded by exon-rich genes, indicating an increased regulatory flexibility through alternative splicing to adapt to multiple environments, and that the protein interaction network linking the central proteome is very efficient for synchronizing translation with other biological processes. Surprisingly, at least 10% of the central proteome has no or very limited functional annotation.

Conclusions

Our data and analysis provide a new and deeper description of the human central proteome compared to previous results thereby extending and complementing our knowledge of commonly expressed human proteins. All the data are made publicly available to help other researchers who, for instance, need to compare or link focused datasets to a common background.