High Performance Computational System to Support LCMS/Proteomics Analysis

描述（由申请人提供）：布法罗大学 (UB) 和区域合作伙伴罗斯威尔公园癌症研究所。 (RPCI) 和豪普特曼伍德沃德研究所。 （HWI）参与对基础设施的重大持续投资，以支持针对基础、应用和临床生物医学应用的蛋白质组学研究。分布式区域仪器网络提供最先进的液相色谱/质谱 (LC/MS) 仪器。为我们的研究人员联盟生成蛋白质组学数据的关键仪器包括 Waters LC-QTOF Premier (RPCI)、配备电子转移解离和多维纳流 LC（UB 制药科学仪器核心）的 Thermo LTQ-XL 线性离子阱，以及配备离子色谱分馏和纳流 LC 的 Thermo LTQ Orbitrap，位于 UB 新的纽约州生物信息学和生命科学卓越中心 (CBLS)，物理位置毗邻 RPCI 园区。其他 LC/MS 仪器支持正在进行的蛋白质组学研究并提供增强的定量能力。其中包括 UB Pharmaceutical Sciences Core 中的四台 LC/三重四极杆 MS（2 台 API3000 和两台 Thermo Quantum Ultra EMR）、RPCI 中的一台 API3000 和 Thermo Quantum Ultra。对于这个由 NIH 支持的实验室组成的多机构联盟来说，从基础和临床研究样本中获取的大型蛋白质组数据集的计算分析存在严重的瓶颈。由于研究的性质，使用 SEQUEST 分析实验数据可能需要在标准高端工作站上进行数小时到数天的计算，具体取决于预期的基质复杂性和肽修饰、使用 ICAT 或 iTRAQ 等试剂来量化相对表达，以及所研究的蛋白质组。为了缓解这一瓶颈，我们建议购买专门设计用于加速 LC/MS 蛋白质组数据分析的专用高性能计算 (HPC) 集群。支持集群的软件已在手或已承诺购买，包括 SEQUEST、X!Tandem、Mascot 和 Scaffold。拟议的网格计算系统将设在 UB 计算研究中心 (CCR)，这是一个靠近 LC/MS 蛋白质组学设施的成熟 HPC 研究中心。充足的海量存储和备份设施将集成到拟议的 HPC 集群中。战略性地放置在数据采集站点的工作站将为研究人员提供对 HPC 系统的分散访问。蛋白质组学软件的基准测试表明，通过收购所提出的系统可以显着加速 MS 数据分析，该系统利用了四核处理器技术的进步并充分利用了现有的 CCR 基础设施。鉴于我们的研究人员对基础科学和临床科学的重视，拟议的设备将对危及生命的疾病的新疗法的开发以及我们对基本生化和生理过程的理解产生直接的重大影响。公共健康相关性：在蛋白质组范围内对蛋白质表达和翻译后修饰 (PTM) 进行分析代表了一项重要的新兴技术，它将有助于我们了解基本生化过程、细胞反应网络以及疾病过程对其的影响。这些信息还有助于开发新的机械靶向药物。当前和待决的 NIH 支持的研究项目受到蛋白质组学研究中遇到的大数据集和/或复杂 PTM 计算分析瓶颈的阻碍。所提出的支持网格的高性能计算集群和分布式处理网络将有效解决我们区域蛋白质组学研究联盟的这一计算瓶颈，从而直接推进众多NIH支持的旨在改善艾滋病、心血管疾病和癌症等严重疾病治疗的项目。

DESCRIPTION (provided by applicant): 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.