Michael MacCoss, PhD
Professor, Genome Sciences
The focus of the MacCoss laboratory is in the development and application of cutting edge mass spectrometry based technologies for the analysis of complex protein mixtures. The focus of our research is in the development of stable isotope and mass spectrometry based approaches to improve our understanding of biology on a molecular, cellular, and whole organism level. Presently, individuals in the laboratory are working on technology for
Automating biochemical sample preparation methods for the analysis of protein mixtures
Developing in vivo stable isotope methods for studying protein metabolism
Increasing the dynamic range of liquid chromatography-mass spectrometry for the analysis of peptides
Developing computational tools for the automated conversion of mass spectrometry data into biologically meaningful results
Honors and awards
2007 – Presidential Early Career Award for Scientists and Engineers (PECASE)
2006 – Genome Technology, Rising Young Investigator
2004 – American Society for Mass Spectrometry Research Award
2001-2003 – National Institutes of Health, National Research Service Award
2000 – American Society for Clinical Nutrition, Young Investigator Award
2000 – Endocrinology and Metabolism Section of the American Physiological Society, Research Award
MacCoss MJ, Fukagawa NK, Matthews DE. (1999). Measurement of homocysteine concentrations and stable isotope tracer enrichments in human plasma. Anal Chem, 71: 4527-33.
MacCoss MJ, Fukagawa NK, Matthews DE. (2001). Measurement of intracellular sulfur amino acid metabolism in humans. Am J Physiol Endocrinol Metab, 280 (6): E947-55.
Wu CC, MacCoss MJ, Howell KE, Matthews DE, Yates JR 3rd. (2004). Metabolic labeling of mammalian organisms for quantitative proteomics analysis. Anal Chem, 76: 4951-9.
Dai DF, Santana LF, Vermulst M, Tomazela DM, Emond MJ, MacCoss MJ, Gollahon K, Martin GM, Loeb LA, Ladiges WC, Rabinovitch PS. (2009). Overexpression of catalase targeted to mitochondria attenuates murine cardiac aging. Circulation, 21: 2789-97.
MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ. (2010). Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics, 26 (7): 966-8.