Research Paper Volume 16, Issue 2 pp 1192—1217
Gut microbial community and fecal metabolomic signatures in different types of osteoporosis animal models
- 1 Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- 2 Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
- 3 Department of Orthopedics, Jinzhong Hospital Affiliated to Shanxi Medical University, Jinzhong 030600, Shanxi, P.R. China
- 4 Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan 030013, Shanxi, P.R. China
- 5 Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan 030032, Shanxi, China
- 6 Department of Orthopedics, Third People’s Hospital of Datong City, Datong 037006, Shanxi, P.R. China
Received: August 29, 2023 Accepted: November 13, 2023 Published: January 26, 2024
https://doi.org/10.18632/aging.205396How to Cite
Copyright: © 2024 Qiao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: The gut microbiota (GM) constitutes a critical factor in the maintenance of physiological homeostasis. Numerous studies have empirically demonstrated that the GM is closely associated with the onset and progression of osteoporosis (OP). Nevertheless, the characteristics of the GM and its metabolites related to different forms of OP are poorly understood. In the present study, we examined the changes in the GM and its metabolites associated with various types of OP as well as the correlations among them.
Methods: We simultaneously established rat postmenopausal, disuse-induced, and glucocorticoid-induced OP models. We used micro-CT and histological analyses to observe bone microstructure, three-point bending tests to measure bone strength, and enzyme-linked immunosorbent assay (ELISA) to evaluate the biochemical markers of bone turnover in the three rat OP models and the control. We applied 16s rDNA to analyze GM abundance and employed untargeted metabolomics to identify fecal metabolites in all four treatment groups. We implemented multi-omics methods to explore the relationships among OP, the GM, and its metabolites.
Results: The 16S rDNA sequencing revealed that both the abundance and alterations of the GM significantly differed among the OP groups. In the postmenopausal OP model, the bacterial genera g__Bacteroidetes_unclassified, g__Firmicutes_unclassified, and g__Eggerthella had changed. In the disuse-induced and glucocorticoid-induced OP models, g__Akkermansia and g__Rothia changed, respectively. Untargeted metabolomics disclosed that the GM-derived metabolites significantly differed among the OP types. However, a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that it was mainly metabolites implicated in lipid and amino acid metabolism that were altered in all cases. An association analysis indicated that the histidine metabolism intermediate 4-(β-acetylaminoethyl) imidazole was common to all OP forms and was strongly correlated with all bone metabolism-related bacterial genera. Hence, 4-(β-acetylaminoethyl) imidazole might play a vital role in OP onset and progression.
Conclusions: The present work revealed the alterations in the GM and its metabolites that are associated with OP. It also disclosed the changes in the GM that are characteristic of each type of OP. Future research should endeavor to determine the causal and regulatory effects of the GM and the metabolites typical of each form of OP.