TY - JOUR
T1 - Inter-laboratory comparison of metabolite measurements for metabolomics data integration
AU - Izumi, Yoshihiro
AU - Matsuda, Fumio
AU - Hirayama, Akiyoshi
AU - Ikeda, Kazutaka
AU - Kita, Yoshihiro
AU - Horie, Kanta
AU - Saigusa, Daisuke
AU - Saito, Kosuke
AU - Sawada, Yuji
AU - Nakanishi, Hiroki
AU - Okahashi, Nobuyuki
AU - Takahashi, Masatomo
AU - Nakao, Motonao
AU - Hata, Kosuke
AU - Hoshi, Yutaro
AU - Morihara, Motohiko
AU - Tanabe, Kazuhiro
AU - Bamba, Takeshi
AU - Oda, Yoshiya
N1 - Funding Information:
Conflicts of Interest: The authors declare the following competing financial interest(s) and role of the company in composing this paper: Y.O. receives financial support from Eisai Co., Ltd.; K.H. (Kanta Horie) works for Eisai Co., Ltd. (experiments and data analysis, and writing—original draft preparation); Y.H. works for Ono Pharmaceutical Co., Ltd. (experiments and data analysis); M.M. works for Ono Pharmaceutical Co., Ltd. (experiments and data analysis, and writing—original draft preparation); and K.T. works for LSI Medience Corporation (experiments and data analysis, and writing—original draft preparation).
Funding Information:
Funding: This study was supported in part by a Grant-in-Aid for Scientific Research on Innovative Areas (17H06304 for Y.I. and T.B., and 17H06303 for F.M. and N.O.) from Japan Society for the Promotion of Science (JSPS), a Grant-in-Aid for Scientific Research (C) (19K05167 for Y.I.) from JSPS, the Japan Agency for Medical Research and Development (AMED) projects (the Research on Development of New Drugs, GAPFREE for A.H., JP18gm5910001 for K.I., and 19ak0101043j0605 for K.S.) from AMED, and the Tohoku Medical Megabank Projects (JP19km0105001 and JP19km0105002 for D.S.) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and AMED.
Funding Information:
Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; izumi@bioreg.kyushu-u.ac.jp (Y.I.); m-takahashi@bioreg.kyushu-u.ac.jp (M.T.); nakao@bioreg.kyushu-u.ac.jp (M.N.); k-hata@bioreg.kyushu-u.ac.jp (K.H.) Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan; n-okahashi@ist.osaka-u.ac.jp Institute for Advanced Biosciences, Keio University, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan; hirayama@ttck.keio.ac.jp Laboratory for Metabolomics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-Ku, Yokohama, Kanagawa 230-0045, Japan; kazutaka.ikeda@riken.jp Department of Lipidomics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; kita@m.u-tokyo.ac.jp (Y.K.); yoda@m.u-tokyo.ac.jp (Y.O.) Translational Science, Neurology Business Group, Eisai Co., Ltd., 5-1-3 Tokodai, Tsukuba, Ibaraki 300-2635, Japan; k2-horie@hhc.eisai.co.jp Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan; saigusa@m.tohoku.ac.jp Division of Medical Safety Science, National Institute of Health Science, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan; saitok2@nihs.go.jp RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan; yuji.sawada@riken.jp 10 Research Center for Biosignal, Akita University, 1-1-1 Hondo, Akita-city, Akita 010-8543, Japan; hnakani@med.akita-u.ac.jp 11 Pharmacokinetic Research Laboratories, Ono Pharmaceutical Co., Ltd., 17-2 Wadai, Tsukuba, Ibaraki 300-4247, Japan; y.hoshi@ono.co.jp 12 Translational Research Laboratories, Ono Pharmaceutical Co., Ltd., 3-1-1 Sakurai Shimamoto-cho, Mishima-gun, Osaka 618-8585, Japan; morihara@ono.co.jp 13 Medical Solution Promotion Department, Medical Solution Segment, LSI Medience Corporation, 3-30-1, Shimura, Itabashi-ku, Tokyo 174-8555, Japan; tanabe.kazuhiro@mp.medience.co.jp
Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
KW - Data integration
KW - Inter-laboratory comparison
KW - Metabolomics
KW - Method validation
KW - Quality control sample
KW - Relative quantification
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U2 - 10.3390/metabo9110257
DO - 10.3390/metabo9110257
M3 - Article
AN - SCOPUS:85074420213
SN - 2218-1989
VL - 9
JO - Metabolites
JF - Metabolites
IS - 11
M1 - 257
ER -