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A more recent version of this article appeared on July 1, 2007. Originally published In Press as doi:10.1074/mcp.M600476-MCP200 on April 4, 2007.
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Submitted on December 20, 2006
Revised on March 19, 2007
Accepted on April 4, 2007

In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics

Jun Adachi, Chanchal Kumar, Yanling Zhang, and Matthias Mann

Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Martinsried 82152

Corresponding Author: mmann{at}biochem.mpg.de

Adipocytes are central players in energy metabolism and the obesity epidemic, yet their protein composition remains largely unexplored. We investigate the adipocyte proteome by combining high accuracy, high sensitivity protein identification technology with subcellular fractionation of nuclei, mitochondria, membrane and cytosol of 3T3-L1 adipocytes. We identify 3,287 proteins while essentially eliminating false positives, making this one of the largest high-confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized role, is very complex. Comparison to microarray data shows that the mRNA abundance of detected vs. non-detected proteins differ by less than two-fold and that proteomics covered as large a proportion of the insulin signaling pathway. We use the Endeavour gene prioritization algorithm to associate a number of factors with vesicle transport in response to insulin stimulation – a key function of adipocytes. Our data and analysis can serve as a model for cellular proteomics. The adipocyte proteome is available with the article and at the MAPU database (http://proteome.biochem.mpg.de/adipo/).


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