Metabolomics Technologies to Advance Biomedical Research

项目摘要 代谢组学是一项相对较新的技术，正在经历指数级的增长，机会 与之相关的是它几乎无限的潜力。然而，有许多障碍限制了 充分发挥其潜力。需要开发生物信息学工具，如XCMS Online，以 简化从原始代谢数据分析到其解释的过程。进一步的一些例子 开发包括广泛整合来自正交法的数据、自主代谢产物 注释和标识，我们刚刚开始在XCMS Online和Metline中解决这些问题 站台。然而，也许最有趣的挑战是利用 代谢组学和系统生物学战略，这一研究领域将对 生物医学社区。我的首要目标不仅是解决这些众多的障碍，因为我们有一个 做的跟踪记录，也是为了使我们的开发免费提供和方便使用，并允许整个 来自所有领域的社区和非代谢组学专家(如癌症、神经疾病、糖尿病、 病毒学、环境暴露等)，以利用代谢组学的巨大机会。 这笔资金将用于开发与代谢有关的多个相互关联的战略领域。 代表代谢组学关键空白的领域的生物医学研究，包括：自主代谢组学 数据分析、代谢物注释和鉴定、代谢引导系统生物学数据集成、 表型调节代谢物的鉴定和全球协作定量质谱学 分析。作为所述研究的一部分，它包括两名初级教职调查人员(莱尔森和特贾罗) 作为合作伙伴，他们的专业知识是开发神经退行性变治疗方法和 免疫疗法。例如，我们将专注于寻找更有效的代谢物来诱导少突胶质细胞 前体细胞成熟！用于治疗多发性硬化症，识别能够改善的代谢物 T细胞耗竭模型中的免疫反应，仅举几例。更广泛地说，我们的努力将是 继续在总体上促进生物医学研究，在这方面，我们通过基于云的 技术，目前为全球22,000多名注册用户提供服务。我们的主要目标是 努力发展代谢组学以促进生物医学研究。 除了开发测量和分析新陈代谢数据的技术之外，将这些 通过活动进行测量是我们的主要目标之一。生物标记物的发现、途径分析和系统 生物学数据集成和认知计算是成功识别能够 积极地调节系统，从本质上用生物学来固定生物学。这一努力的结果是在进一步 新陈代谢组学的发展是潜在的兴奋，作为技术专家，我们不再是 只是被动的观察者，而是解决生物医学问题的积极参与者。 ！1！

Project Summary Metabolomics is a relatively new -omic technology experiencing exponential growth, and the opportunities associated with it allude to its almost limitless potential. There are however numerous obstacles that limit reaching its full potential. The development of bioinformatics tools such as XCMS Online, are needed to streamline the process from raw metabolic data analysis to its interpretation. Some examples of further development include the broad integration of data from orthogonal methods, autonomous metabolite annotation and identification, which we have just begun to address within the XCMS Online and METLIN platforms. Yet, perhaps the most interesting challenge is the identification of active metabolites using metabolomics and systems biology strategies, an area of research that will have a profound effect on the biomedical community. My overarching goal is not only to address these numerous obstacles, as we have a track record of doing, but also to make our developments freely available and user-friendly and allow the entire community and non-metabolomics experts from all fields (e.g. cancer, neurological disorders, diabetes, virology, environmental exposure, and so on) to harness the enormous opportunity of metabolomics. The funding will provide for the development of multiple connected strategic areas of metabolism-related biomedical research in areas that represent key gaps in metabolomics including: autonomous metabolomics data analysis, metabolite annotation and identification, metabolic guided system biology data integration, identification of phenotype modulating metabolites and global cooperative quantitative mass spectrometry analysis. As a part of the research described, it includes two junior faculty investigators (Lairson and Teijaro) as collaborators whose expertise are in developing approaches for neurodegeneration treatment and immunotherapy. For example, we will focus on identifying more potent metabolites to induce oligodendrocyte precursor cells maturation!for the treatment of multiple sclerosis, identifying metabolites capable of improving the immunological response in a T cell exhaustion model, to name a few. More broadly, our efforts will be to continue facilitating biomedical research in general, in this we are uniquely positioned through our cloud-based technologies, which currently serve over 22,000 registered users worldwide. The primary objective of our efforts is to develop metabolomics to advance biomedical research. Beyond developing the technology of measuring and analyzing metabolic data, correlating these measurements with activity is one of our prime goals. Biomarker discovery, pathway analysis and systems biology data integration, and cognitive computing are integral to the success of identifying metabolites that can actively modulate the system, essentially fixing biology with biology. A result of this effort in the further development of metabolomics is the underlying excitement, where, as technologists, we are no longer simply passive observers but active participants in solving biomedical problems. ! 1!