The University at Buffalo (UB) and regional partners Roswell Park Cancer Inst. (RPCI) and Hauptman-Wood- ward Research Inst. (HWI) are joined in a major continuing investment in infrastructure to support proteomic research directed toward basic, applied, and clinical biomedical applications. A distributed regional network of instrumentation provides access to state-of-the-art liquid chromatography/mass spectrometry (LC/MS) instrumentation. Key instruments generating proteomics data for our consortium of investigators include a Waters LC-QTOF Premier (RPCI), a Thermo LTQ-XL linear ion trap equipped with Electron Transfer Dissociation and multidimensional nano-flow LC (UB Pharmaceutical Sciences Instrumentation Core), and a Thermo LTQ Orbitrap with ion chromatography fractionation and nano-flow LC in UB's new NY State Center of Excellence in Bioinformatics &Life Sciences (CBLS), located physically contiguous to the RPCI campus. Additional LC/MS instruments support the ongoing proteomics research and provide enhanced quantitative capabilities. These include four LC/triple-quadrupole MS (2 API3000 and two Thermo Quantum Ultra EMR) in the UB Pharmaceutical Sciences Core, an API3000 and Thermo Quantum Ultra at RPCI. For this multi-institutional consortium of NIH-supported laboratories, computational analysis of the large proteomics data sets acquired from basic and clinical research samples presents a severe bottleneck. Because of the nature of the research, analyses of experimental data using SEQUEST can require hours to days of computation on standard high-end workstations, depending on the matrix complexity and peptide modifications expected, the use of reagents such as ICAT or iTRAQ to quantify relative expression, and the proteome under study. To alleviate this bottleneck, we propose to acquire a dedicated high-performance computing (HPC) cluster specifically designed to accelerate LC/MS proteomic data analysis. Cluster-enabled software is in hand or committed for acquisition, and includes SEQUEST, X!Tandem, Mascot, and Scaffold. The proposed grid- enabled computing system will be housed in the UB Center for Computational Research (CCR), an established HPC research center located in close proximity to the LC/MS proteomics facilities. Adequate mass storage and backup facilities will be integrated into the proposed HPC cluster. Workstations placed strategically at the sites of data acquisition will provide decentralized access to the HPC system for investigators. Benchmarking of the proteomics software reveals that a considerable acceleration of MS data analysis can be achieved by acquisition of the proposed system, which exploits advances in quad-core processor technology and leverages very substantial existing CCR infrastructure. Given the emphasis of our investigators in both basic and clinical sciences, the proposed equipment will have direct, major impact on the development of new therapies for life-threatening diseases, as well as on our understanding of basic biochemical and physiological processes. PUBLIC HEALTH RELEVANCE: The analysis of protein expression and post-translational modifications (PTMs) on a proteome-wide scale represents an important emerging technique that will assist in our understanding of fundamental biochemical processes, networks of cellular responses, and the impact of disease processes upon them. This information can also contribute to the development of new, mechanistically-targeted drugs. Current and pending NIH-supported research projects are hampered by bottlenecks in the computational analysis of the large data sets and/or complex PTMs that are encountered in proteomics research. The proposed grid-enable high-performance computing cluster and distributed processing network will effectively address this computational bottleneck for our regional proteomics research consortium, and thereby directly advance the numerous NIH- supported projects aimed at improving the therapy of serious diseases such as AIDS, cardiovascular disease, and cancer.
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NIH ExPorter