Department of Computing Science, University of Alberta, Edmonton, Canada.
PLoS One. 2011 Feb 16;6(2):e16957. doi: 10.1371/journal.pone.0016957.
Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.
随着分析技术的不断改进以及对全面、定量代谢组学分析的兴趣日益增加,代谢组学领域越来越需要针对某些重要的临床生物体液(如脑脊液、尿液和血液)开发集中的代谢物参考资源。作为通过人类代谢组计划系统地描述人类代谢组的工作的一部分,我们承担了描述人类血清代谢组的任务。在这样做的过程中,我们将靶向和非靶向 NMR、GC-MS 和 LC-MS 方法与计算机辅助文献挖掘相结合,以识别和定量通常在人类血清代谢组中检测到和定量(使用当今技术)的全面的(如果不是绝对完整的)一组代谢物。我们使用多种代谢组学平台和技术,在批判性地评估这些平台或技术的相对优势和劣势的同时,大大提高了代谢组覆盖水平。包含完整的 4229 种确认和高度可能的人类血清化合物及其浓度、相关文献参考文献以及与已知疾病关联的链接的表格可在 http://www.serummetabolome.ca 上免费获得。