Application of Benchtop NMR for Metabolomics Study Using Feces of Mice with DSS-Induced Colitis

Author:

Song Zihao1ORCID,Ohnishi Yuki1,Osada Seiji2,Gan Li1ORCID,Jiang Jiaxi1,Hu Zhiyan1,Kumeta Hiroyuki3ORCID,Kumaki Yasuhiro4,Yokoi Yuki5ORCID,Nakamura Kiminori5,Ayabe Tokiyoshi5ORCID,Yamauchi Kazuo6,Aizawa Tomoyasu13ORCID

Affiliation:

1. Laboratory of Protein Science, Graduate School of Life Science, Hokkaido University, Sapporo 060-0808, Japan

2. Nakayama Co., Ltd., Tsukuba 300-2651, Japan

3. Advanced NMR Facility, Faculty of Advanced Life Science, Hokkaido University, Sapporo 060-0808, Japan

4. High-Resolution NMR Laboratory, Graduate School of Science, Hokkaido University, Sapporo 060-0810, Japan

5. Innate Immunity Laboratory, Graduate School of Life Science, Hokkaido University, Sapporo 060-0808, Japan

6. Instrumental Analysis Section, Okinawa Institute of Science and Technology, Onna 904-0495, Japan

Abstract

Nuclear magnetic resonance (NMR)-based metabolomics, which comprehensively measures metabolites in biological systems and investigates their response to various perturbations, is widely used in research to identify biomarkers and investigate the pathogenesis of underlying diseases. However, further applications of high-field superconducting NMR for medical purposes and field research are restricted by its high cost and low accessibility. In this study, we applied a low-field, benchtop NMR spectrometer (60 MHz) employing a permanent magnet to characterize the alterations in the metabolic profile of fecal extracts obtained from dextran sodium sulfate (DSS)-induced ulcerative colitis model mice and compared them with the data acquired from high-field NMR (800 MHz). Nineteen metabolites were assigned to the 60 MHz 1H NMR spectra. Non-targeted multivariate analysis successfully discriminated the DSS-induced group from the healthy control group and showed high comparability with high-field NMR. In addition, the concentration of acetate, identified as a metabolite with characteristic behavior, could be accurately quantified using a generalized Lorentzian curve fitting method based on the 60 MHz NMR spectra.

Funder

Center of Innovation Program

Center of Innovation NEXT Program

SPRING of the Japan Science and Technology Agency

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry,Endocrinology, Diabetes and Metabolism

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