Metabolon, Morrisville, NC, USA.
European Molecular Biology Laboratory (EMBL), The European Bioinformatics Institute, Cambridgeshire, UK.
Metabolomics. 2020 Oct 12;16(10):113. doi: 10.1007/s11306-020-01728-5.
The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics.
In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics.
All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach.
For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%).
Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.
代谢组学质量保证和质量控制联盟(mQACC)是从提高和系统化靶向代谢组学质量保证(QA)和质量控制(QC)实践的社区共识的需要演变而来的。
在这项工作中,我们试图确定和分享使用液相色谱-质谱(LC-MS)进行靶向代谢组学的 mQACC 成员和合作者之间共同的和不同的 QA 和 QC 实践。
所有作者都自愿参与了这个合作研究项目,提供了他们实验室使用的 QA 和 QC 实践的细节和见解。通过这份六页的问卷,实现了这一共享,问卷由超过 120 个问题和评论字段组成,是这项工作的一部分,也是 mQACC 持续外联的基础。
在 QA 方面,许多实验室报告记录了维护、校准和调谐(82%);建立了数据存储和存档流程(71%);将数据存入公共存储库(55%);为所有实验室流程制定了标准操作程序(SOP)(68%),并对员工进行了实验室流程培训(55%)。在 QC 方面,普遍的做法包括使用系统适用性程序(100%)和使用稳健的鉴定系统(代谢组学标准倡议 1 级鉴定标准)对至少部分检测到的化合物进行鉴定。大多数实验室使用 QC 样品(86%);使用内部标准(91%);使用具有随机实验样本的指定分析采集模板(91%);并在数据采集后手动审查峰积分(86%)。少数实验室在其工作流程中包括实验样本的技术重复(36%)。
尽管 23 位贡献者是来自学术界、工业界和政府的具有不同国际背景的研究人员,但由于参与者的招募方法及其自愿性质,他们不一定能代表全球从业人员。然而,问卷和这里呈现的发现已经为 mQACC 在会议和其他外联活动中的其他数据收集工作提供了信息和指导,并将继续发展,以便指导社区内最佳实践的讨论,并建立国际公认的报告标准。我们非常欢迎读者对此文提出进一步的反馈。