1 Metabolon, Morrisville, NC, USA. aevans@metabolon.com.
2 European Molecular Biology Laboratory (EMBL), The European Bioinformatics Institute, Cambridgeshire, UK.
3 University of Utah, Salt Lake City, Utah, USA.
4 IROA Technologies, Chapel Hill, NC, USA.
5 National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA.
6 College of Veterinary Medicine, University of Florida, Gainesville, FL, USA.
7 Centre for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, Joondalup, WA, Australia.
8 Broad Institute, Cambridge, MA, USA.
9 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
10 School of Biosciences, Phenome Centre Birmingham and Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
11 Department of Biochemistry, University of Cambridge, Cambridge, UK.
12 Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
13 Center for Alternatives To Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
14 University of Arkansas for Medical Sciences, Little Rock, AR, USA.
15 Department of Chemistry, University of British Columbia, Vancouver, Canada.
16 University Medical Center Utrecht, Utrecht, Netherlands.
17 Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
18 University of Michigan, Ann Arbor, MI, USA.
19 National Phenome Centre, Imperial College London, London, UK.
20 Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), C1425FQD, Ciudad de Buenos Aires, Argentina.
21 Center for Environmental Measurement and Modeling, Environmental Protection Agency, Washington, DC, USA.
22 University of Iowa, Iowa City, Iowa, USA.
23 Department of Internal Medicine, Metabolomics Core, The University of Iowa, Iowa City, Iowa, USA.
24 Aristotle University, Thessaloniki, Greece.
25 Singapore Lipidomics Incubator, Department of Biochemistry, Life Sciences Institute and Yong Loo Lin School of Medicine, National University of Singapore, Kent Ridge, Singapore.
26 Sciex, Redwood, USA.
27 Concordia University, Montreal, QC, Canada.

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.