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KENNETH R. WILLIAMS

Research in the Williams laboratory focuses on improving genomic and proteomic technologies. The poor correlation between mRNA and protein expression prompted the Williams laboratory to bring protein profiling technologies within reach of Yale investigators. Hence, differential fluorescence 2D gel electrophoresis (DIGE), biomarker discovery, isotope-coded affinity tag (ICAT), multiplexed isobaric tagging (iTRAQ), 2D protein LC, multi-dimensional protein identification technology (MudPIT), and antibody-spotted glass slide microarray technologies have been initiated. Technologies that have been optimized (e.g., DIGE, MudPIT, ICAT, iTRAQ) are available through the Keck Laboratory.

Although protein profiling lags far behind mRNA expression analysis, since the biological effector molecule is usually the protein, there is considerable interest in quantitative protein profiling. DIGE and iTRAQ are the most powerful and complementary technologies. When samples are analyzed by both approaches, we usually find little overlap in the identified proteins. Compared to conventional 2D gel electrophoresis, DIGE has the major advantage that both the control and experimental samples are run in the same gel. These samples are imaged separately but because they were run in the same gel, the images can be perfectly overlaid without "warping". This reduces the number of gels that must be run to make statistically valid comparisons and raises the confidence with which protein changes between samples can be quantified. Spots that meet a user-defined criterion (e.g., differential control versus experimental expression of >1.5-fold) are automatically excised for in gel trypsin digestion and MALDI-MS/MS protein identification. In the case of iTRAQ, tryptic digests of 4 samples are each labeled with one of 4 iTRAQ reagents - which produces a 114, 115, 116, or 117 Da MS/MS reporter ion that provides the basis for quantifying the parent tryptic peptide ion. While DIGE can detect differential extents of posttranslational modifications that change the charge (e.g., phosphorylation) or MW (e.g., carbohydrate) and that likely would be missed by iTRAQ, the latter benefits from isolating multiple tryptic peptides/protein. The multiple peptides isolated from each protein detected with iTRAQ allow averaging and statistical analysis which provides more confidence in the resulting ratios. Research is directed towards increasing the fraction of the proteome quantified by DIGE and iTRAQ.

Other areas of research are optimization of antibody glass slide microarray and improvement of peptide biomarker (Wu et al, 2006) protein profiling. One project is transferring our biomarker discovery technology, which is based on a Random Forest algorithm patented by the Keck Lab, from a MALDI-MS to an FT-ICR-LC/MS platform. Rather than analyzing one MALDI-MS spectrum/sample, the new approach will analyze thousands of spectra/sample - which will require the use of high performance computing.           

Another research area is phosphoproteomics. Protein phosphorylation plays important roles in many cellular processes including signal transduction, cell cycle progression, differentiation, and transformation. This widespread posttranslational modification often occurs at low stoichiometry. To obviate this challenge we are optimizing strong cation exchange and metal oxide affinity phosphopeptide enrichment methodologies and have developed a probabilistic computational method that improves MS detection of phosphopeptides (Bruce et al., 2006). As new biotechnologies are implemented in Centers associated with the Williams laboratory:

W.M. Keck Foundation Biotechnology Laboratory

Northeast Biodefense Center Proteomics Core of the Northeast Biodefense Center

Yale Life Sciences High Performance Computing Center

Yale Microarray Center for Research on the Nervous System

Yale NHLBI Proteomics Center

Yale NIDA Neuroproteomics Center

they are rapidly brought to bear on research supported by the Keck Laboratory.

Selected Publications

Klein, R.J., Zeiss, C., Chew, E.Y., Sackler, R.R., Haynes, C., Henning, A.K., Mane, S.M., Mayne, S.T., Bracken, F.L., Ott, J, Barnstable, C. and Hoh, J. Complement factor H is associated with age-related macular degeneration. Science 308, 309-452 (2005)

Bruce, C., Shifman, M., Miller, P. and Gulcicek, E.E. Probabilistic enrichment of phosphopeptides by their mass defect. Anal. Chem. 78, 4374-4382 (2006)

Patterson, T.A., Lobenhofer, E.K., Fulmer-Smentek, S.B., Collins, P., Chu, T-M., Bao, W., Fang, H., Kawasaki, E.S., Hager, J., Tikhonova, I.R., Walker, S.J., Zhang, L., Hurban, P., de Longueville, F., Fuscoe, J.C., Tong, W., Shi, L. and Wolfinger, R.D. Performance comparison of one-color and two-color platforms within the microarray quality control (MAQC) Project. Nature Biotechnology 24, 1140-1150 (2006)

Kidd, M., Modlin, I.M., Mane, S.M., Camp, R.L., Latic, I. and Zikusoka, M.N. The utility of molecular genetic signatures in the delineation of gastric neoplasia. Cancer 106, 480-488 (2006)

Wu, B., Abbott, T., Fishman, D., McMurray, W., Mor, G., Stone, K., Ward, D., Williams, K. and Zhao, H. Ovarian cancer classification based on mass spectrometry analysis of sera. Cancer Informatics 2, 123-132 (2006)