Proteomics, Metabolomics and Lipidomics Core

PNW RCE蛋白质组学，代谢组学和脂质组学（PML）核心提供所需的资源 对于蛋白质组学、代谢组学和脂质组学分析的平行应用， 由RCE合作者。将这些PML核心方法生成的数据与 由各个项目和子项目进行的基因组分析（项目3（P01）Dr.MichaelKatze， 项目4（P01）Michael Gale博士和项目5（R01）Fred Heffron博士）创造了一个独特的机会， 模型疾病相关的途径（见生物统计学和生物信息学核心）与感染有关， 严重急性呼吸道综合征（SARS）病毒、流感病毒、埃博拉病毒、西尼罗河病毒（WNV）、登革热病毒 （DENV）和Francisella novidica。PML核心将利用蛋白质组学正在进行的技术进步 （包括磷酸化蛋白质组学），代谢组学，脂质组学和信息学资源， 通过执行高通量、灵敏和可再现的系统生物学数据生成独特的套件 比较和纵向样品的蛋白质、代谢物和脂质丰度测量， 计算建模和实验验证的迭代循环。PML核心提供了 通过蛋白质组学、代谢组学和脂质组学数据采集的多个阶段提供资源和支持， 从参考精确质量和时间标签（AMT）标签数据库的构建/增强， 比较定量分析。AMT标签数据库中的肽和脂质覆盖率将通过以下方式提高： PNNL率先采用先进的液相色谱分离方法，以降低样品的复杂性。在 皇家通信工程（PML核心）将充分利用太平洋国家实验室已经建立和正在进行的技术进步 在其他支持下完成，以执行大规模测量所需的 中心合作。

The PNW RCE Proteomics, Metabolomics, and Lipidomics (PML) Core provides the resources required for the parallel application of proteomic, metabolomic, and lipidomic analyses to diverse sample sets provide by the RCE collaborators. The integration of data generated by these PML Core approaches with the genomic analyses performed by individual Projects and sub-projects (Project 3 (P01) Dr. Michael Katze, Project 4 (P01) Dr. Michael Gale, and Project 5 (R01) Dr. Fred Heffron), creates a unique opportunity to model disease-related pathways (see Biostatistics and Bioinformatics Core) associated with infection by severe acute respiratory syndrome (SARS) virus, flu virus, Ebola virus, West Nile virus (WNV), Dengue virus (DENV), and Francisella novidica. The PML Core will leverage ongoing technical advances in proteomics (including phosphoproteomics), metabolomics, lipidomics, and informatics resources available at PNNL to generate unique suites of systems biology data by performing high throughput, sensitive, and reproducible protein, metabolite, and lipid abundance measurements on comparative and longitudinal samples for iterative cycles of computational modeling and experimental validation. The PML Core provides both resources and support through multiple stages of proteomics, metabolomics, and lipidomics data acquisition, from construction/augmentation of reference accurate mass and time tag (AMT) tag databases through comparative quantitative analyses. Peptide and lipid coverage in AMT tag databases will be enhanced by advanced liquid chromatography separation methods pioneered at PNNL to reduce sample complexity. In the RCE the PML Core will leverage established and ongoing technological advancements at PNNL accomplished under other support in order to perform the large-scale measurements demanded by the Center collaborations.