On site metabolome analysis using ordinal temp and low-field nuclear polarization and deeplearning

2021 Fiscal Year Final Research Report

• Project/Area Number: 20K21873
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 90:Biomedical engineering and related fields
• Research Institution: Hokkaido University
• Principal Investigator: Matsumoto Shingo 北海道大学, 情報科学研究院, 准教授 (90741041)
• Project Period (FY): 2020-07-30 – 2022-03-31
• Keywords: NMR / 核偏極 / 代謝 / メタボローム

Outline of Final Research Achievements

We have developed a high-speed NMR-based metabolome analysis system that collectively polarized metabolites obtained by biopsy and measured by increasing the NMR signals by tens of thousands of times using ordinal temperature and low magnetic field nuclear polarization technology. The 13C NMR signal in the 1.5T NMR apparatus was significantly increased up to 70,000 times, and metabolites with a concentration of several tens of μM could be detected by 13C NMR. On the other hand, due to the delay caused by equipment failure in the first year, the identification of disease-specific metabolic changes by LC/TOF-MS remained in the group of known disease marker metabolites. We constructed an automated system using an embedded microcomputer for all processes from sample injection, hyperpolarization induction, polarization transfer, and post-process to the metabolites containing derivatized carboxylic acid by the flow method.

Free Research Field

情報科学

Academic Significance and Societal Importance of the Research Achievements

多くの疾患は何からの代謝変容を伴い、血液や尿中に含まれる数百種類の代謝物濃度を網羅的に計測するメタボローム解析により、多様な疾患が特定できることは無数の臨床研究報告からも自明である。一般にメタボローム解析には質量分析や高分解能NMRなどの大掛かりな装置と、数時間に及ぶ測定時間、煩雑なデータ解析が必要であり汎用の臨床検査ツールとしての利用には至っていない。本研究は、臨床現場で網羅的な疾患検出に繋がる高速メタボローム診断法の基盤技術を創出する。