Establishment of protocols for global metabolomics by LC-MS for biomarker discovery

Daisuke Saigusa, Yasunobu Okamura, Ikuko N. Motoike, Yasutake Katoh, Yasuhiro Kurosawa, Reina Saijyo, Seizo Koshiba, Jun Yasuda, Hozumi Motohashi, Junichi Sugawara, Osamu Tanabe, Kengo Kinoshita, Masayuki Yamamoto

Research output: Contribution to journalArticlepeer-review

61 Citations (Scopus)

Abstract

Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' preanalytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

Original languageEnglish
Article numbere0160555
JournalPLoS ONE
Volume11
Issue number8
DOIs
Publication statusPublished - 2016 Aug

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