Journal
METABOLOMICS
Volume 16, Issue 10, Pages -Publisher
SPRINGER
DOI: 10.1007/s11306-020-01728-5
Keywords
Quality assurance; Quality control; Untargeted metabolomics; Metabolomics quality assurance and quality control consortium (mQACC); LC-MS
Categories
Funding
- MRC [MR/P01836X/1, MR/P011705/1, MC_PC_13030, MC_UP_A090_1006] Funding Source: UKRI
- Medical Research Council [MR/P01836X/1, MC_UP_A090_1006, MC_PC_13030, MR/M009157/1, MR/P011705/1, MR/S019669/1] Funding Source: Medline
- NCI NIH HHS [R00 CA218694] Funding Source: Medline
- NIDDK NIH HHS [R01 DK104998] Funding Source: Medline
- Intramural EPA [EPA999999] Funding Source: Medline
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Introduction 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. Objectives 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. Methods 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. Results 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%). Conclusions 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.
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