We describe a largely unbiased method for rapid and large-scale proteome analysis by multidimensional liquid chromatography, tandem mass spectrometry, and database searching by the SEQUEST algorithm, named multidimensional protein identification technology (MudPIT). MudPIT was applied to the proteome of the Saccharomyces cerevisiae strain BJ5460 grown to mid-log phase and yielded the largest proteome analysis to date. A total of 1,484 proteins were detected and identified. Categorization of these hits demonstrated the ability of this technology to detect and identify proteins rarely seen in proteome analysis, including low-abundance proteins like transcription factors and protein kinases. Furthermore, we identified 131 proteins with three or more predicted transmembrane domains, which allowed us to map the soluble domains of many of the integral membrane proteins. MudPIT is useful for proteome analysis and may be specifically applied to integral membrane proteins to obtain detailed biochemical information on this unwieldy class of proteins.
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The authors thank Jimmy Eng, David Schieltz, David Tabb, and Laurence Florens for valuable discussions during the preparation of this manuscript. The authors acknowledge funding from the National Institutes of Health R33CA81665-01 and RR11823-03. M.P.W. acknowledges support from genome training grant T32HG000035-05. Saccharomyces cerevisiae strain BJ5460 was a generous gift from Steve Hahn of the Fred Hutchinson Cancer Research Center (Seattle, WA).
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Washburn, M., Wolters, D. & Yates, J. Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat Biotechnol 19, 242–247 (2001). https://doi.org/10.1038/85686
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