Assessment of cold exposure-induced metabolic changes in mice using untargeted metabolomics

Linqiang Gong; Shiyuan Zhao; Xue Chu; Hui Yang; Yanan Li; Shanshan Wei; Fengfeng Li; Yazhou Zhang; Shuhui Li; Pei Jiang

doi:10.3389/fmolb.2023.1228771

Assessment of cold exposure-induced metabolic changes in mice using untargeted metabolomics

Front Mol Biosci. 2023 Aug 31:10:1228771. doi: 10.3389/fmolb.2023.1228771. eCollection 2023.

Authors

Linqiang Gong^#¹, Shiyuan Zhao^#^{2

3}, Xue Chu², Hui Yang¹, Yanan Li⁴, Shanshan Wei^{5

6}, Fengfeng Li¹, Yazhou Zhang¹, Shuhui Li¹, Pei Jiang^{2

3}

Affiliations

¹ Tengzhou Central People's Hospital, Tengzhou, China.
² Translational Pharmaceutical Laboratory, Jining First People's Hospital, Shandong First Medical University, Jining, China.
³ Institute of Translational Pharmacy, Jining Medical Research Academy, Jining, China.
⁴ College of Marine Life Sciences, Ocean University of China, Qingdao, China.
⁵ Department of Pharmacy, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
⁶ Graduate Department, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, China.

^# Contributed equally.

Abstract

Background: Cold exposure (CE) can effectively modulate adipose tissue metabolism and improve metabolic health. Although previous metabolomics studies have primarily focused on analyzing one or two samples from serum, brown adipose tissue (BAT), white adipose tissue (WAT), and liver samples, there is a significant lack of simultaneous analysis of multiple tissues regarding the metabolic changes induced by CE in mice. Therefore, our study aims to investigate the metabolic profiles of the major tissues involved. Methods: A total of 14 male C57BL/6J mice were randomly assigned to two groups: the control group (n = 7) and the CE group (n = 7). Metabolite determination was carried out using gas chromatography-mass spectrometry (GC-MS), and multivariate analysis was employed to identify metabolites exhibiting differential expression between the two groups. Results: In our study, we identified 32 discriminant metabolites in BAT, 17 in WAT, 21 in serum, 7 in the liver, 16 in the spleen, and 26 in the kidney, respectively. Among these metabolites, amino acids, fatty acids, and nucleotides emerged as the most significantly altered compounds. These metabolites were found to be associated with 12 differential metabolic pathways closely related to amino acids, fatty acids, and energy metabolism. Conclusion: Our study may provide valuable insights into the metabolic effects induced by CE, and they have the potential to inspire novel approaches for treating metabolic diseases.

Keywords: cold exposure; gas chromatography-mass spectrometry; main tissues; metabolite; multivariate analysis.

Grants and funding

This research was funded by the National Natural Science Foundation of China (81602846; 82272253) and Natural Science Foundation of Shandong Province (ZR2021MH145). Taishan Scholar Project of Shandong Province (tsqn201812159). Science and Technology Program of Traditional Chinese Medicine of Shandong Province (M-2022066); China International Medical Foundation (No. Z-2018-35-2002).