Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego , La Jolla, California 92093, United States.
Department of Pediatrics, University of California, San Diego , La Jolla, California 92093, United States.
Anal Chem. 2017 Jul 18;89(14):7549-7559. doi: 10.1021/acs.analchem.7b01381. Epub 2017 Jul 6.
Increasing appreciation of the gut microbiome's role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).
人们越来越认识到肠道微生物组在健康中的作用，这促使人们了解人类粪便的分子组成。为了分析如此复杂的样本，我们开发了一种将靶向和非靶向代谢组学相结合的平台。该方法通过从一个 UPLC 分流、接触闭合继电器触发的联合定时以及检索数据的脚本得到促进。它旨在以高灵敏度检测特定的感兴趣代谢物，允许对靶向信息进行校正，从而更好地定量，为探索性研究提供先进的分析工具。普罗克汝斯分析显示，非靶向方法与微生物组数据相关性更好，将特定代谢物与产生或处理它们的微生物相关联。在来自美国肠道计划的一百多个人类粪便样本的子集中，所描述的耦合工作流程的实施表明，使用化合物的单个跃迁与保留时间组合进行靶向分析会错误识别 30%的靶向数据，并可能导致错误的解释。同时，靶向分析根据化合物的不同，在检测限和动态范围上扩展了几个数量级。作为工作流程的一部分，已经开发了一个软件应用程序，以允许基于校准曲线进行定量评估。使用这种方法，我们可以检测到预期的微生物修饰分子，如次级胆汁酸，以及意想不到的微生物分子，包括粪便中的假单胞菌相关喹诺酮类和鼠李糖脂，为代谢组-微生物组全关联研究（MMWAS）奠定了基础。
