The number of metabolomics studies have increased dramatically in recent years, spanning from basic/mechanistic research to the identification and validation of clinical biomarkers. Developments in analyte separation techniques and the growth of databases are largely responsible for the rapid growth of metabolomics, although broad differences in analytical workflows can result in difficulty when comparing data across studies. The establishment of baseline metabolomics data for human reference materials using complementary/orthogonal data acquisition strategies can help to alleviate some of these challenges. To this end, we report nontargeted semiquantitative metabolomics data for 22 commercially available materials including plasma (healthy, diabetic, hypertriglyceridemic, African-American), serum (female, male, pregnant, among others), feces (meconium, vegan, omnivore), urine (smokers' and nonsmokers'), breast milk, saliva, and vaginal fluid, using ultrahigh-performance liquid chromatography-tandem mass spectrometry in positive and negative electrospray ionization, as well as gas chromatography-electron ionization-mass spectrometry. Significant differences were observed in the metabolomic fingerprints between all sample types. Post hoc comparisons between relevant sample types support the relevance of these materials and the validity of nontargeted strategies in global metabolomics. As the number and variety of reference materials continues to increase, it is imperative that their adoption is matched. The results of this study may inform future biomedical research by highlighting several metabolites across matrixes and treatments/states that could serve as clinical biomarkers or important biochemical pathway intermediates. Furthermore, our work can serve as a metric for systems suitability, quality assurance, and quality control across the community via the dissemination of high-quality and publicly available annotated metabolomics data.

中文翻译：

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使用多平台高分辨率质谱方法对生物参考材料进行代谢组学分析。

近年来，代谢组学研究的数量急剧增加，从基础/机制研究到临床生物标志物的鉴定和验证。分析物分离技术的发展和数据库的增长是代谢组学快速增长的主要原因，尽管分析工作流程的广泛差异可能导致在比较研究数据时遇到困难。使用互补/正交数据采集策略为人类参考物质建立基线代谢组学数据有助于缓解其中一些挑战。为此，我们报告了 22 种市售材料的非靶向半定量代谢组学数据，包括血浆（健康、糖尿病、高甘油三酯血症、非裔美国人）、血清（女性、男性、孕妇等），粪便（胎粪、素食、杂食动物）、尿液（吸烟者和非吸烟者）、母乳、唾液和阴道液，在正负电喷雾电离中使用超高效液相色谱-串联质谱法，以及气相色谱法-电子电离质谱法。在所有样品类型之间的代谢组学指纹中观察到显着差异。相关样本类型之间的事后比较支持这些材料的相关性以及全球代谢组学中非靶向策略的有效性。随着参考资料的数量和种类不断增加，它们的采用必须与之相匹配。这项研究的结果可能会通过强调跨基质和治疗/状态的几种代谢物来为未来的生物医学研究提供信息，这些代谢物可以作为临床生物标志物或重要的生化途径中间体。此外，我们的工作可以通过传播高质量和公开可用的注释代谢组学数据，作为整个社区的系统适用性、质量保证和质量控制的衡量标准。