Bouhifd Mounir, Beger Richard, Flynn Thomas, Guo Lining, Harris Georgina, Hogberg Helena, Kaddurah-Daouk Rima, Kamp Hennicke, Kleensang Andre, Maertens Alexandra, Odwin-DaCosta Shelly, Pamies David, Robertson Donald, Smirnova Lena, Sun Jinchun, Zhao Liang, Hartung Thomas
Johns Hopkins University, Bloomberg School of Public Health, Center for Alternatives to Animal Testing, Baltimore, MD, USA.
US Food and Drug Administration, National Center for Toxicological Research, Division of Systems Biology, Jefferson, AR, USA.
ALTEX. 2015;32(4):319-26. doi: 10.14573/altex.1509161.
Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.
代谢组学有望对生物对毒物的反应进行全面的表型特征描述。这项技术基于具有合理通量的先进化学分析工具，包括质谱和核磁共振。然而，从实验设计、样品制备、代谢物鉴定到生物信息学数据挖掘，都迫切需要质量保证，以确保代谢组学数据的质量和生物模型的可重复性。与基于微阵列的转录组学不同，在过去二十年里，转录组学在质量保证和报告标准方面已经达成了共识，而代谢组学的质量保证才刚刚兴起。在安全科学中的监管应用，甚至这些技术的正确科学使用，都需要质量保证。为了推动这一讨论，一个专家研讨会讨论了代谢组学的质量保证需求。本次研讨会的目标是：1）考虑代谢组学作为一门新兴科学所面临的挑战，重点是其在毒理学中的应用；2）确定在基于代谢组学的毒理学中建立和实施质量保证程序需要解决的关键问题。关于如何确保从这些新工具中获得可靠、有用和相关信息的最佳实践，仍有待达成共识。
