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De novo peptide sequencing and quantitative profiling of complex protein mixtures using mass-coded abundance tagging

Nature Biotechnology volume 20, pages 163170 (2002) | Download Citation

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Abstract

Proteomic studies require efficient, robust, and practical methods of characterizing proteins present in biological samples. Here we describe an integrated strategy for systematic proteome analysis based on differential guanidination of C-terminal lysine residues on tryptic peptides followed by capillary liquid chromatography–electrospray tandem mass spectrometry. The approach, termed mass-coded abundance tagging (MCAT), facilitates the automated, large-scale, and comprehensive de novo determination of peptide sequence and relative quantitation of proteins in biological samples in a single analysis. MCAT offers marked advantages as compared with previously described methods and is simple, economic, and effective when applied to complex proteomic mixtures. MCAT is used to identify proteins, including polymorphic variants, from complex mixtures and measure variation in protein levels from diverse cell types.

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Acknowledgements

We thank Hassan Qureshi, Andy Link, Richard Newitt, John Yates III, David Schieltz, Hayes McDonald, and Mike Washburn for providing reagents, technical advice, and/or comments; Matthew Francis for expert technical assistance; Jimmy Eng for generous use of software; and Shiva Amiri, Thanuja Premawaradena, Alia Qureshi-Emili, Duy Mai, and Mike Lindo for programming expertise. This work was supported in part by a grant from the National Science and Engineering Research Council of Canada to A.E.

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Affiliations

  1. Program in Proteomics and Bioinformatics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.

    • Gerard Cagney
    •  & Andrew Emili
  2. Department of Medical Genetics and Microbiology, University of Toronto, Toronto, ON, Canada.

    • Andrew Emili

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Competing interests

G.C. and A.E. have submitted a provisional patent application for the MCAT methodology/process.

Corresponding author

Correspondence to Andrew Emili.

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DOI

https://doi.org/10.1038/nbt0202-163

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