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Proteomics and Metabolomics Studies of Type 1 Diabetes

Richard Smith, Principal Investigator

Funding Agency: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases

In this four-year, two-phase project, the Proteomics and Metabolomics Studies of Type 1 Diabetes project team at Pacific Northwest National Laboratory (PNNL) is applying advanced proteomic and metabolomic nanoflow liquid chromatography-Fourier transform ion cyclotron resonance (LC-FTICR) mass spectrometry technologies to study plasma and serum from Type 1 diabetes patients and isolated human pancreatic islets. The overall approach endeavors to advance the study of Type 1 diabetes and human islet transplantation by identifying biomarkers at the level of the proteome and metabolome that are predictive of both Type 1 diabetes and islet performance in vivo. Our approach uses proteome-wide stable isotope labeling of peptides as well as quantitative cysteine-peptide enrichment technology (QCET) and N-linked glycopeptide enrichment strategies to obtain broad proteome coverage and enhance quantitation. We are also using very low nanoflow LC separations to minimize ionization suppression and eliminate background ions originating from the solvent, thereby improving normalization of metabolite peak intensities and improving quantitation.

With this approach, we can rapidly identify and measure expression levels for thousands of peptides or concentrations of metabolites in a single analysis. In Phase 1 of this project, we are (a) defining the sample processing and LC separation conditions necessary for broad metabolome and proteome coverage in human plasma and/or serum and pancreatic islets, (b) establishing accurate mass and time tag databases for both peptides and metabolites detected in human plasma and/or serum and pancreatic islets, and (c) demonstrating the ability of the technology to distinguish plasma and/or serum from healthy control or recently diagnosed Type 1 diabetic patients. The refinement of this technological approach will provide the basis for high-throughput studies of large numbers of samples. The application of this technology in Phase 2 of the project will involve (a) the high-throughput studies of complete sample sets from the Diabetes Autoantibody Standardization Program (DASP), (b) validation of potential biomarkers via analysis of a blind DASP sample set, and (c) comparative studies of multiple human pancreatic islet preparations to identify potential biomarkers predictive of islet performance in vivo.

Systems Biology at PNNL

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