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Research

In-depth Analysis of the Adipocyte Proteome by Mass Spectrometry and Bioinformatics^*,S

Jun Adachi^,,¶,||, Chanchal Kumar^,¶, Yanling Zhang^,** and Matthias Mann^,,

From the Department of Proteomics and Signal Transduction, Max Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany, Center for Experimental Bioinformatics, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark, and ^** Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 101300, China

Adipocytes are central players in energy metabolism and the obesity epidemic, yet their protein composition remains largely unexplored. We investigated 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 identified 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 with microarray data showed that the mRNA abundance of detected versus non-detected proteins differed by less than 2-fold and that proteomics covered as large a proportion of the insulin signaling pathway. We used 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 as supplemental material and from the Max-Planck Unified Proteome database.

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