Our core expertise is in mass spectrometry (MS)-based proteomics and we are located in the University of Washington, Seattle, at the Department of Pharmacology. We come from diverse fields of interest including chemistry, biology, molecular genetics, and applied math and are most excited about incorporating different methodologies to yield new biological insights in our research; specifically, we have developed novel approaches to study functional roles of protein complexes; particularly the dynamics of their formation and recruitment, abundances and post-translational modifications in cellular signaling, growth and proliferation.
MS-based proteomics is a uniquely powerful and versatile tool in biology as it allows unbiased, comprehensive and sensitive detection of proteins in complex mixtures. With the ability to identify thousands of proteins in a single experiment, MS-based proteomics makes it easy to generate lengthy protein catalogs, but qualitative comparisons of lists of proteins is less informative. Instead, the ability to measure abundances of specific proteins and observe these changing over time in response to a defined perturbation is extremely powerful. Such information can be obtained with quantitative proteomics, which greatly enhances the power and utility of MS-based methods.
We use chemical labeling methods, like iTRAQ or metabolic labeling with SILAC, to quantify changes in protein abundance, enabling functional assays to compare protein expression levels in perturbed and control cell states. In SILAC, proteins from two cell populations labeled with normal isotope abundance or stable isotope labeled amino acids are observable in the same mass spectrum and distinguishable by their respective "light" and "heavy" peptide signals. This transforms the proteomic experiment into a format akin to a microarray experiment: when samples are mixed in equal proportions, signals from both populations are detectable unless the absence of either the light or heavy member is a direct result of the experimental perturbation. With this method, protein expression changes can be modeled and significant changes called with high confidence. Issues related to stochastic sampling of control-experiment pairs that plague classical proteomic approaches are avoided altogether. Along with dramatic improvements in the speed and sensitivity of MS instruments over the last decade, these quantitative methods have enabled impressive proteomics studies like the comprehensive identification of proteins in sub-cellular organelles like mitochondria and nucleoli, and quantification of subtle changes in whole proteomes induced by microRNA overexpression.
Our new review with the Leung lab @ Johns Hopkins University is out now in Molecular Cell! Check it out in Molecular Cell's special issue on '50 Years of PARP'.
We welcome Takeshi Masuda, a new post-doctoral fellow, to the lab in June 2015!
Shao-En will be attending ABRF 2015 in St. Louis MO. He will chair a Workshop and a Roundtable discussion on SILAC and other quantitative labeling approaches on March 30, 2015. Our recent JPR paper on the comparison of SILAC with stable isotope dimethyl-labeling will be presented.
Our new paper in collaboration with Marcel Van Vugt is just out in EMBO J!
Our new paper is out in the Journal of Proteome Research! We analyze mixtures of SILAC-labeled and stable isotope dimethyl-labeled proteins and peptides from unfractionated lysates or pull-downs in single LC-MS runs, allowing the direct comparison of quantitative accuracy and recovery of peptides. We also describe a StageTip stable isotope dimethyl labeling protocol that can be applied to in-gel digests of proteins excised from SDS-PAGE gels. This provides an easy way to incorporate stable isotope labels after the fact.