化学
代谢组学
色谱法
尿
代谢组
生物标志物发现
亲水作用色谱法
质谱法
样品制备
液相色谱-质谱法中的离子抑制
毛细管电泳
蛋白质组学
串联质谱法
代谢物
高效液相色谱法
液相色谱-质谱法
生物化学
基因
作者
Mona M. Khamis,Darryl J. Adamko,Anas El‐Aneed
摘要
Urine metabolomics has recently emerged as a prominent field for the discovery of non‐invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non‐biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid‐liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze‐thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high‐performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)‐MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC‐MS, other MS‐based technologies have been utilized in urine metabolomics. These include direct injection (infusion)‐MS, capillary electrophoresis‐MS and gas chromatography‐MS. In this article, the current progresses of different MS‐based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115–134, 2017.
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