Abstract
Background: One of the current problems in the field of metabolomics is the difficulty in integrating data collected using different equipment at different facilities, because many metabolomic methods have been developed independently and are unique to each laboratory. Methods: In this study, we examined whether different analytical methods among 12 different laboratories provided comparable relative quantification data for certain metabolites. Identical samples extracted from two cell lines (HT-29 and AsPc-1) were distributed to each facility, and hydrophilic and hydrophobic metabolite analyses were performed using the daily routine protocols of each laboratory. Results: The results indicate that there was no difference in the relative quantitative data (HT-29/AsPc-1) for about half of the measured metabolites among the laboratories and assay methods. Data review also revealed that errors in relative quantification were derived from issues such as erroneous peak identification, insufficient peak separation, a difference in detection sensitivity, derivatization reactions, and extraction solvent interference. Conclusion: The results indicated that relative quantification data obtained at different facilities and at different times would be integrated and compared by using a reference materials shared for data normalization.
Highlights
Metabolomics using mass spectrometry (MS) is a promising tool for the life science and biotechnology fields [1,2,3,4,5]
We focused on the relative comparisons of 206 hydrophilic and 584 hydrophobic different metabolome analysis methods, and several reasons leading to the incomparable results were metabolite levels among samples and performed an inter-laboratory comparison study of metabolite successfully identified
The majority voting is not always correct and there are still many outliers, the results demonstrated that identical relative quantitation data was produced by the targeted metabolomics methods throughout various laboratories
Summary
Metabolomics using mass spectrometry (MS) is a promising tool for the life science and biotechnology fields [1,2,3,4,5]. Relative quantification data produced mainly by the targeted metabolomics approach were integrated into large datasets for researches in medical biotechnology, precision medicine, cohort studies, epidemiological studies, and genome-wide association studies [6,7,8]. One of the biggest problems that must be addressed is that the targeted metabolome methods have not been well validated to guarantee the production of reliable and comparable data. Method validation using a similar approach seems to be quite a difficult task. This is because true values are unclear due to a lack of suitable blank matrix as well as many standard materials [10]. Identical samples extracted from two cell lines (HT-29 and AsPc-1) were distributed to each facility, and hydrophilic and hydrophobic metabolite analyses were performed using the daily routine protocols of each laboratory
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