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Lan ZF, Yao W, Xie YC, Chen W, Zhu YY, Chen JQ, Zhou XY, Huang JQ, Wu MS, Chen JX. Oral Troxerutin Alleviates Depression Symptoms in Mice by Modulating Gut Microbiota and Microbial Metabolism. Mol Nutr Food Res 2024; 68:e2300603. [PMID: 38072646 DOI: 10.1002/mnfr.202300603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
SCOPE A growing body of evidence suggests that the harmful gut microbiota in depression patients can play a role in the progression of depression. There is limited research on troxerutin's impact on the central nervous system (CNS), especially in depression. The study finds that troxerutin effectively alleviates depression and anxiety-like behavior in mice by increasing the abundance of beneficial bacteria like Lactobacillus and Firmicutes while decreasing the abundance of harmful bacteria like Proteobacteria, Bacteroides, and Actinobacteria in the gut. Furthermore, the research reveals that troxerutin regulates various metabolic pathways in mice, including nucleotide metabolism, caffeine metabolism, purine metabolism, arginine biosynthesis, histidine metabolism, 2-oxocarboxylic acid metabolism, biosynthesis of amino acids, glycine, serine and threonine metabolism, and Arginine and proline metabolism. CONCLUSIONS In conclusion, the study provides compelling evidence for the antidepressant efficacy of troxerutin. Through the investigation of the role of intestinal microorganisms and metabolites, the study identifies these factors as key players in troxerutin's ability to prevent depression. Troxerutin achieves its neuroprotective effects and effectively prevents depression and anxiety by modulating the abundance of gut microbiota, including Proteobacteria, Bacteroides, and Actinobacteria, as well as regulating metabolites such as creatine.
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Affiliation(s)
- Zhi-Fang Lan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Wei Yao
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Yi-Ci Xie
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Wushisi Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Yin-Ying Zhu
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Jia-Qi Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Xing-Yi Zhou
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Jun-Qing Huang
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
| | - Man-Si Wu
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
- School of Food and Biotechnology, Guangdong Industry Polytechnic, Guangzhou, 510300, China
| | - Jia-Xu Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632, China
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