Department of Chemistry, Washington University, School of Medicine, St. Louis, MO 63110, USA.
J Sep Sci. 2011 Dec;34(24):3460-9. doi: 10.1002/jssc.201100532. Epub 2011 Oct 4.
Metabolomics has rapidly become a profiling technique of choice for biomarker elucidation and molecular diagnostics in addition to studies focused on understanding disease pathogenesis. Key to the success of metabolomics in these areas has been the techniques to separate and analyze the chemically diverse group of compounds comprising the metabolome by using global and untargeted approaches. Untargeted metabolomic efforts have the goal of examining as many metabolites as possible simultaneously and most frequently use an LC/MS-based approach. Here, the importance of LC in an untargeted metabolomic workflow is outlined and separation strategies for optimization are reviewed within the context of these criteria.
代谢组学已经迅速成为生物标志物阐明和分子诊断的首选分析技术,除了专注于了解疾病发病机制的研究外。代谢组学在这些领域取得成功的关键在于使用全局和非靶向方法分离和分析组成代谢组的化学多样性化合物的技术。非靶向代谢组学的目标是同时检查尽可能多的代谢物,并且最常使用基于 LC/MS 的方法。在这里,概述了 LC 在非靶向代谢组学工作流程中的重要性,并根据这些标准审查了优化的分离策略。