STTR Phase I: Analysis of Comprehensive Two Dimensional Gas Chromatography with Mass Spectrometry for High-Throughput Metabolomics

这项小型企业技术转移（STTR）第一阶段项目将研究一种使用新型仪器和软件分析代谢物的新方法。目前，代谢组学为制药和其他生物学研究提供了重要的新信息。然而，很少有研究人员能够利用代谢组学，因为没有合适的方法。最近，气相色谱法已成功地应用于代谢组学，尽管峰值容量不足。该项目将结合领先的多维气相色谱研究设施和经验丰富的软件专家团队，为代谢组学带来多维气相色谱的力量。综合二维气相色谱-飞行时间质谱检测（GC x GC xTOF-MS）将与模式识别相结合，分析甲基营养细菌代谢物对扰动的反应。华盛顿大学Synovec实验室和该公司的合作将产生一个分析GC x GC x TOF-MS数据的软件平台。该平台将使用以前未用于GC × GC × TOF-MS的商业数据管理和分析技术，并使GC × GC × TOF-MS能够进行高通量代谢物分析。其结果将是一种阐明生物功能的使能技术。该项目的商业应用包括代谢组学和蛋白质组学。目前，蛋白质组学的全球市场规模每年超过10亿美元，并以每年34%的速度增长。代谢组学的市场规模为3800万美元，并以每年46%的速度增长。该项目将解决当前代谢组学和蛋白质组学中多维分离软件的未满足需求。

This Small Business Technology Transfer (STTR) Phase I project will investigate a new method for analyzing metabolites using novel instrumentation and software. Currently, metabolomics offers critical new information to pharmaceutical and other biological research. However, few researchers can exploit metabolomics, because appropriate methods have not been developed. Recently, gas chromatography has been successfully applied to metabolomics, although peak capacities have been insufficient. This project will combine a leading multidimensional gas chromatography research facility with a seasoned team of software experts, to bring the power of multidimensional GC to metabolomics. Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection (GC x GC xTOF-MS) will be combined with pattern recognition to analyze the reaction of metabolites of methylotrophic bacteria to perturbations. The collaborative effort between the Synovec Laboratory at the University of Washington and the Company will produce a software platform for analysis of GC x GC x TOF-MS data. This platform will use data management and analysis technologies that have not previously been commercially available for GC x GC x TOF-MS, and enable GC x GC x TOF-MS for high throughput metabolite analysis. The result will be an enabling technology for the elucidation of biological function.The commercial applications of this project include metabolomics and proteomics. The current market for proteomics is over $1 billion per year worldwide and growing at the rate of 34% per year. The market for metabolomics is $38 million, and growing at the rate of 46% per year. This project will address the current unmet need for multidimensional separations software in both metabolomics and proteomics.