Inter-laboratory comparison of metabolite measurements for metabolomics data integration

Yoshihiro Izumi, Fumio Matsuda, Akiyoshi Hirayama, Kazutaka Ikeda, Yoshihiro Kita, Kanta Horie, Daisuke Saigusa, Kosuke Saito, Yuji Sawada, Hiroki Nakanishi, Nobuyuki Okahashi, Masatomo Takahashi, Motonao Nakao, Kosuke Hata, Yutaro Hoshi, Motohiko Morihara, Kazuhiro Tanabe, Takeshi Bamba, Yoshiya Oda

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

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.

Original languageEnglish
Article number257
JournalMetabolites
Volume9
Issue number11
DOIs
Publication statusPublished - 2019 Nov

Keywords

  • Data integration
  • Inter-laboratory comparison
  • Metabolomics
  • Method validation
  • Quality control sample
  • Relative quantification

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

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