Inter-Laboratory Comparison of Metabolite Measurements for Metabolomics Data Integration

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. In this study, we examined whether differe...

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Bibliographic Details
Published in:Metabolites 2019-10, Vol.9 (11), p.257
Main Authors: Izumi, Yoshihiro, Matsuda, Fumio, Hirayama, Akiyoshi, Ikeda, Kazutaka, Kita, Yoshihiro, Horie, Kanta, Saigusa, Daisuke, Saito, Kosuke, Sawada, Yuji, Nakanishi, Hiroki, Okahashi, Nobuyuki, Takahashi, Masatomo, Nakao, Motonao, Hata, Kosuke, Hoshi, Yutaro, Morihara, Motohiko, Tanabe, Kazuhiro, Bamba, Takeshi, Oda, Yoshiya
Format: Article
Language:English
Subjects:
Amino acids
Cell lines
Chromatography
data integration
Datasets
Hydrophobicity
inter-laboratory comparison
Laboratories
Lipids
Mass spectrometry
Metabolites
Metabolomics
method validation
Methods
Plasma
quality control sample
Reference materials
relative quantification
Reproducibility
Scientific imaging
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Summary: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. 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. 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. 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.
ISSN:2218-1989
2218-1989
DOI:10.3390/metabo9110257