Human Biology Core, Project 10 of 10

TORS的主要目标之一是整合新的代谢、遗传和分子细胞生物学数据， 在小鼠模型和人类受试者中使用多种技术收集，形成机械理解 肥胖症和II型糖尿病的关键方面。为了推进这一目标，我们成立了一个公私合作的研究机构 四个Tors团队与NIH支持的软件和动力学建模公司之间的合作伙伴关系， 综合生物信息学公司(IBI)。IBI的软件产品ProcessDB是用于管理开发的工具 大规模量化力学模型，并同时针对多个实验进行测试 协议使用不同的测量技术。费尔博士，前生物医学工程教授和 约翰·霍普金斯医学院的生理学博士和他在IBI的同事们有多年的经验 利用这些技术，从整个人类受试者到培养细胞的生物组织水平上。他们 在许多相关领域发表了论文，包括脂类和脂蛋白代谢、内分泌学/营养学，以及 分子细胞生物学。为了实现长期目标，即建立一个综合机制模型， 肥胖症的生理学和病理生理学，建模工作将从每一个 TORS子项目。然而，我们最初计划将重点放在整合两个Tors团队的信息上： 帕克斯和马洛伊(伯吉斯，布朗宁)。据我们所知，这将是新陈代谢的第一次整合 在相同的人类受试者和患者中，来自成熟的核磁共振和GC/MS技术的信息。 利用两种稳定同位素方法的独特优势是史无前例的。在02-05年度，我们计划 扩大这些团队间项目以包括：1)从以下项目中选择信息丰富的人类对象(科恩/霍布斯) 达拉斯心脏研究将使用GC/MS(帕克斯)和核磁共振(马洛伊)技术进行分析，并适用于我们的 利用这些个体的已知遗传缺陷的约束条件，开发综合模型。2)发展 为小鼠生理学和病理生理学的相关方面建立一个平行代谢模型。这是一条平行路线 发展将有助于将小鼠模型中的基础研究转化为可在人类身上验证的假说 受试者和病人。3)完成包括线粒体功能在内的骨骼肌代谢模型 (Malloy)，它可以与肝脏模型相结合，产生两个主要的综合模型 参与摄食和胰岛素代谢反应的器官/组织。通过将ProcessDB软件安装在 每个PI的桌面、所有TORS组都将能够持续访问正在开发的集成模型，并将 能够提出待测试的修改和添加建议。他们还可以向ProcessDB数据库添加新的 实验方案和数据。因此，ProcessDB将成为一个有重点的机械性“知识环境” 对于TORS计划，遵循与信号转导知识环境(STKE)相同的思路 由AAAS/Science开发。(http://stke.sciencemag.org/).)

One of the principal TORS goals is integration of new metabolic, genetic, and molecular cell biological data, collected using multiple technologies in mouse models and human subjects, into a mechanistic understanding of key aspects of obesity and type II diabetes. To advance this goal, we have formed a public-private research partnership between the four TORS teams and an NIH-supported software and kinetic modeling company, Integrative Bioinformatics Inc (IBI). IBI's software product, ProcessDB, is a tool for managing the development of large scale quantitative mechanistic models and testing these simultaneously against multiple experimental protocols using diverse measurement technologies. Dr. Phair, a former professor of biomedical engineering and physiology at the Johns Hopkins School of Medicine, and his colleagues at IBI have many years of experience with these techniques at levels of biological organization from whole human subjects to cultured cells. They have published in many relevant areas including lipid and lipoprotein metabolism, endocrinology/nutrition, and molecular cell biology. To reach the long term goal of an integrated mechanistic model of key aspects of the physiology and pathophysiology of obesity, the modeling effort will draw from and contribute to each of the TORS subprojects. Initially, however, we plan to focus on integration of information from two TORS teams: Parks and Malloy (Burgess, Browning). To our knowledge, this will be the first integration of metabolic information from well-established NMR and G.C/MS techniques in the same human subjects and patients. Leveraging the unique strengths of both stable isotope methods is unprecedented. In years 02-05 we plan to expand these inter-team projects to include: 1) Selection of informative human subjects (Cohen/Hobbs) from the Dallas Heart Study to be analyzed using the GC/MS (Parks) and NMR (Malloy) technologies, and fitted to our developing integrated model using constraints from known genetic defects in these individuals. 2) Development of a parallel metabolic model for relevant aspects of mouse physiology and pathophysiology. This parallel development will facilitate translation of basic research in the mouse model to testable hypotheses in human subjects and patients. 3) Completion of a model of skeletal muscle metabolism including mitochondrial function (Malloy), that can be combined with the hepatic model to produce an integrated model of two major organs/tissues involved in the metabolic response to feeding and insulin. By putting the ProcessDB software on each Pi's desktop, all TORS groups will have constant access to the developing integrated models and will be able to propose modifications and additions to be tested. They can also add to the ProcessDB database new experimental protocols and data. ProcessDB will thus serve as a focused mechanistic "knowledge environment" for the TORS program, along the same lines as the signal transduction knowledge environment (STKE) developed by AAAS/Science. (http://stke.sciencemag.org/).