OCT 29, 2014 12:00 PM PDT

Improving the Robustness and Reproducibility of Quantitative Proteomics

Speakers
  • Professor of Genome Sciences, University of Washington, School of Medicine
    Biography
      Michael MacCoss has been working with mass spectrometry instrumentation since 1994 when he was an undergraduate in a stable isotope geochemistry lab at the University of Vermont.  He became interested in biomedical applications working in Dr. Patrick Griffins protein mass spectrometry lab at Merck Research Laboratories during two summer internships in 1995 and 1996.  In 2001, he completed a Ph.D. in Analytical Chemistry with Professor Dwight Matthews in the development of stable isotope and mass spectrometry methodologies for the measurement of human amino acid and protein metabolism.  After completing his degree, Dr. MacCoss moved to The Scripps Research Institute to work with Professor John R. Yates III as a postdoctoral fellow.  During his postdoctoral training, Dr. MacCoss worked on methodology and software for many areas of proteomics, ranging from the improved characterization of post-translational modifications and the quantitative analysis of complex protein mixtures.  Dr. MacCoss moved to the University of Washington in 2004 as an Assistant Professor of Genome Sciences, where his lab has focused on the development and application of mass spectrometry based technologies for the high throughput characterization of complex protein mixtures.  In 2009 he was promoted to Associate Professor and in 2014 he was promoted to full professor.

    Abstract:

    Proteomics technology has improved dramatically over the last decade. The technology developments have largely been directed around instrument hardware, where instruments have been developed that scan faster, are more sensitive, and have greater mass measurement accuracy. However, the basic workflow has remained largely unchanged -- mass spectrometers are directed toward the acquisition of tandem mass spectra on the most abundant molecular species eluting from a chromatography column. More recently, efforts have been focused on the acquisition of mass spectrometry data on target peptides of interest. With improvements in instrument hardware and instrument control software, the practical experimental difference between a targeted and discovery proteomics is beginning to become blurred. These analyses are a significant change from the traditional proteomics workflow and have required the development of novel computational strategies to analyze, visualize, and interpret these data. We will present work illustrating our efforts in the development of targeted proteomics and provide a vision for challenges that still need to be overcome before these analyses become routine and replace more traditional discover proteomics methodology.


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