Systematic Metabolic Profiling of Mice with Dextran Sulfate Sodium-Induced Colitis

Dadi Xie; Fengfeng Li; Deshui Pang; Shiyuan Zhao; Meihua Zhang; Zhongfa Ren; Chunmei Geng; Changshui Wang; Ning Wei; Pei Jiang

doi:10.2147/JIR.S313374

Systematic Metabolic Profiling of Mice with Dextran Sulfate Sodium-Induced Colitis

J Inflamm Res. 2021 Jul 2:14:2941-2953. doi: 10.2147/JIR.S313374. eCollection 2021.

Authors

Dadi Xie^#¹, Fengfeng Li^#¹, Deshui Pang¹, Shiyuan Zhao², Meihua Zhang¹, Zhongfa Ren¹, Chunmei Geng², Changshui Wang³, Ning Wei⁴, Pei Jiang²

Affiliations

¹ Tengzhou Central People's Hospital, Tengzhou, 277500, People's Republic of China.
² Jining First People's Hospital, Jining Medical University, Jining, 272000, People's Republic of China.
³ Affiliated Hospital of Jining Medical University, Jining Medical University, Jining, 272000, People's Republic of China.
⁴ Shanting District People's Hospital, Zaozhuang, 277200, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Inflammatory bowel diseases (IBD) are a chronic inflammatory disease, which affects almost all tissues in the body. Previous studies mainly focused on breathing, fecal, and urine samples of patients with IBD. However, there is no comprehensive metabolomic analysis of the serum, colon, heart, liver, kidney, cortex, hippocampus, and brown fat tissues. Therefore, the aim of our study is to evaluate the utility metabolomic analysis of target tissues in the pathogenesis of IBD in exploring new biomarkers for early diagnosis and treatment.

Methods: Male Sprague-Dawley rats were randomly allocated to control and DSS-treated groups (n = 7). Dextran sulfate sodium (DSS) was orally administered for 6 weeks. Gas chromatography-mass spectrometry (GC-MS) was used for metabolite determination, multivariate statistical analysis was used to identify metabolites that were differentially expressed in two groups.

Results: Our results showed that 3, 11, 12, 6, 5, 13, 13, and 11 metabolites were differentially expressed between the DSS treatment group and the control group in the serum, colon, heart, liver, kidney, cortex, hippocampus, and brown fat tissues, respectively. The most significant change of metabolites in the study was amino acid (L-alanine, L-glutamic acid, L-phenylalanine, L-proline, L-lysine, L-isoleucine, L-tryptophan, L-norleucine, L-valine, glycine, serine, L-threonine), organic acid (citric acid, 3-hydroxybutyric acid, propanoic acid), glucide (D-arabinose, D-fructose) and purine (9H-purin-6-ol, D-ribose) profiles. Several pathways were affected according to the integrated pathway analysis. These pathways ranged from amino acid metabolism (such as alanine, aspartate, and glutamate metabolism, glutathione metabolism) to purine metabolism (aminoacyl-tRNA biosynthesis).

Conclusion: Using GC-MS-based profiling of metabolite changes, these results may provide a more comprehensive view for IBD and IBD-related diseases and improve the understanding of IBD pathogenesis.

Keywords: GC-MS; biomarker; dextran sodium sulfate; inflammatory bowel disease; metabolite.

Grants and funding

This work was supported by the Key Research and Development Program of Jining Science and Technology (2019SMNS012); Taishan Scholar Project of Shandong Province (tsqn201812159); National Natural Science Foundation of China (81602846).