Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 2627 2022-03-31 16:25:37 |
2 Add references -1283 word(s) 1344 2022-03-31 16:49:12 | |
3 format corrected. + 4 word(s) 1348 2022-04-01 03:18:18 | |
4 words italicized. Meta information modification 1348 2022-04-01 04:09:59 |

Video Upload Options

Do you have a full video?


Are you sure to Delete?
If you have any further questions, please contact Encyclopedia Editorial Office.
Fu, L.; , . Gut Microbiota Feature of Senile Osteoporosis. Encyclopedia. Available online: (accessed on 24 June 2024).
Fu L,  . Gut Microbiota Feature of Senile Osteoporosis. Encyclopedia. Available at: Accessed June 24, 2024.
Fu, Lingjie, . "Gut Microbiota Feature of Senile Osteoporosis" Encyclopedia, (accessed June 24, 2024).
Fu, L., & , . (2022, March 31). Gut Microbiota Feature of Senile Osteoporosis. In Encyclopedia.
Fu, Lingjie and . "Gut Microbiota Feature of Senile Osteoporosis." Encyclopedia. Web. 31 March, 2022.
Gut Microbiota Feature of Senile Osteoporosis

Senile osteoporosis is defined as an age-related bone metabolic disorder, which is characterized by bone loss and decreased bone fragility. Gut microbiota (GM) could regulate the bone metabolic process and be closely related to senile osteoporosis. Several genus-level GM were found to increase in osteoporotic animals and patients. However, to reveal the pathogenic bacteria in senile osteoporosis, further studies are still needed to investigate the complete characteristics of bacteria species. GM are defined as the collection of commensal bacteria living in the digestive tract, which regulates host metabolism and performs various functions. GM of humans consist of over 1000 distinct bacterial species, about two-thirds of which are unique to each individual. GM have an impact on many chronic diseases, such as obesity, diabetes, neurological disorders, inflammatory bowel disease (IBD), and cardiovascular disease. As a member of the chronic disease category, osteoporosis is also associated with GM.

senile osteoporosis gut microbiota bacteria species shallow shotgun functional metabolic pathway

1. Introduction

Senile osteoporosis is a primary, age-related bone metabolic disease, which is characterized by bone loss and decreased bone fragility[1]. Commonly, primary osteoporosis mainly affects postmenopausal females and aged males. Commonly, postmenopausal females have a higher incidence of fragility fractures, while aged people, especially aged males, have a higher rate of mortality related to osteoporosis[2]. Emerging evidence demonstrated that aging plays a critical role in the development of osteoporosis[3]. With the gradual rise of an aging population, senile osteoporosis has brought a higher burden on the public health system[4].
Recent studies suggested that senile osteoporosis was closely related to gut microbiota (GM). Several clinical studies reported that the osteoporotic patients showed altered GM, richness, diversity, relative GM abundance, and functional metabolic pathways[5][6][7][8][9]. However, due to the distinct geographical location, sample size, gender distribution, and dietary habits of patients, these clinical studies have not reached a consistent conclusion on the regulation of GM alteration in osteoporotic people. In an animal study, senile osteoporotic rats showed decreased α diversity, altered β diversity, and increased relative abundance of Helicobacter, Rothia, Clostridium IV, Alistipes, and H. rodentium using 16S rRNA, and the whole metagenome sequencing (WMS)[10]. Furthermore, another study found that GM derived from feces of aged rats led to bone loss, and increased the genus-level relative abundance of Romboutsia, Faecalibacterium, and Lachnospiraceae_incertae_sedis in young rats[11]. On the contrary, GM derived from young rats could restore the bone mass of senile osteoporotic rats and decrease the genus-level relative abundance of Helicobacter and Prevotella[12]. GM features at the genus level of senile osteoporosis were revealed by 16S rRNA sequencing using rats model.
Shallow shotgun sequencing is a high-accuracy microbiological technology, which could annotate the microbial taxonomy to the species level [13][14]. In addition, it could reach nearly the same sequencing depth and accuracy as WMS technology with fewer data[15]. To date, studies based on 16S rRNA sequencing about GM and senile osteoporosis only revealed genus-level GM taxonomic features. Although some GM strains such as H. rodentium were found to increase in the osteoporotic rats[10], the complete species-level characteristics of GM were still unknown.

2. Current Insights

Using shallow shotgun sequencing technology, the researchers found that the senile osteoporotic rats showed decreased species numbers, distinct β diversity, and low α diversity. Furthermore, the senile osteoporotic rats had markedly distinct GM compositions at the genus and species levels. At the genus level, Prevotella, Acinetobacter, and Salinispora significantly increased in osteoporotic group. At the species level, A. baumannii, Lachnospiraceae bacterium M18 1, and P. copri significantly increased in the osteoporotic group. In addition, KEGG functional pathways analysis found that fatty acid biosynthesis, Valine/isoleucine biosynthesis, GABA biosynthesis, and ubiquinone biosynthesis were enriched in the osteoporotic rats.
The GM structure was markedly changed between senile osteoporotic rats and young rats, which could be revealed by the distinct ecological distance in β diversity. Furthermore, the OP group had fewer unique species numbers than the control group, reflecting a decreased GM richness at the species level in the OP group. Several studies reported that disease statuses were related to decreased α diversity, such as type II diabetes and Alzheimer’s disease[16][17]. In this research, though there was no significant difference, ACE and Chao indexes suggested that the senile osteoporotic rats had lower α diversity, which was consistent with the previous study[10]. These results suggested that the species-level GM structure and richness markedly changed in the senile osteoporotic rats.
The relative abundance of GM could reflect the GM composition at the different taxonomic levels. At the genus level, the proportions of Bacteroide, Parabacteroides, Escherichia, and Prevotella were higher in the osteoporotic group, while the proportions of Corynebacterium and Akkermansia were higher in the control group. The increased proportion of Prevotella was consistent with the previous study[12]. At the species level, the proportion of B. coprocola, A. baumannii, P. distasonis, and Lachnospiraceae bacterium A4 were higher in the OP group, while C. stationis, A. muciniphila, and A. indistinctus were more abundant in the control group. To identify significantly different GM, the researchers performed LEfSe analysis and found that Prevotella, Acinetobacter, and Salinispora at the genus level and A. baumannii, Lachnospiraceae bacterium M18 1, and P. copri at the species level were enriched in the osteoporotic group. These results suggested that altered GM species were in accordance with the alteration of GM genus. Some GM species such as P. copri and A. muciniphila were proved to be linked to bone metabolism.
P. copri, which belongs to the Prevotella genus that also increased, was associated with a number of autoimmune diseases, such as colitis and rheumatoid arthritis[18][19][20]. Furthermore, P. copri was correlated with an increase in trimethylamine oxide (TMAO), a byproduct caused by dietary choline, which has an impact on cardiovascular disease and chronic kidney disease[21]. In addition, an increased level of TMAO has a negative correlation with the degree of bone mineral density (BMD) in osteoporosis patients[22]. In the research, P. copri was also found to be significantly enriched in the senile osteoporotic rats. A. muciniphila is a newly identified beneficial species in the phylum Verrucomicrobia. Previous studies reported that the abundance of A. muciniphila was reduced in aged humans and mice[23][24]. In an animal study, A. muciniphila was found to restore the bone mass of osteoporotic mice[25]. Consistently, the researchers identified that A. muciniphila was decreased in the senile osteoporotic rats. Therefore, the researchers suggested that the increased abundance of P. copri and decreased amount of A. muciniphila were closely related to the pathogenesis of senile osteoporosis. Furthermore, A. baumannii, which belongs to the Acinetobacter genus, is a major pathogenic factor of nosocomial infections[26]. Salinispora is a marine actinomycete genus that produces structurally diverse and biologically active secondary metabolites[27]. Lachnospiraceae bacterium M18 and Lachnospiraceae bacterium A4 belong to the Lachnospiraceae family, which could produce short-chain fatty acids and were beneficial for bone health[28]. The increase in these bacteria in aged rats could be attributed to the dysbiosis of gut microbiota. However, the association of these bacteria with the pathogenesis of senile osteoporosis needs further study.
KEGG functional pathway analysis found that metabolic pathways of fatty acid biosynthesis, Valine/isoleucine biosynthesis, GABA biosynthesis, and ubiquinone biosynthesis were enriched in the senile osteoporotic rats. Fatty acids metabolism and oxidative stress and production of ROS may impact each other and further influence bone metabolism[29]. As reported, oxidative stress was closely associated with aging[30]. Therefore, the enrichment of fatty acids biosynthesis might be related to aging-induced oxidative stress. Furthermore, GABA treatment could positively regulate osteogenic differentiation[31]. The enriched GABA biosynthesis in senile osteoporotic rats might be due to a compensatory effect after bone loss. These results suggested that fatty acid biosynthesis, Valine/isoleucine biosynthesis, GABA biosynthesis, and ubiquinone biosynthesis were related to senile osteoporosis.

3. Conclusions

The researchers first manifested the complete information of species-level GM in senile osteoporotic rats. GM was significantly altered in structure and composition in senile osteoporotic rats. B. coprocola, A. baumannii, P. distasonis, and Lachnospiraceae bacterium A4 and P. copri were higher in the senile osteoporotic group, while C. stationis, A. muciniphila, and A. indistinctus were decreased. Furthermore, KEGG function analysis revealed that metabolic pathways of fatty acid biosynthesis, Valine/isoleucine biosynthesis, GABA biosynthesis, and ubiquinone biosynthesis were enriched in the senile osteoporotic rats.


  1. Akkawi, I.; Zmerly, H. Osteoporosis: Current Concepts. Joints 2018, 6, 122–127, doi:10.1055/s-0038-1660790.
  2. Laurent, M.R.; Dedeyne, L.; Dupont, J.; Mellaerts, B.; Dejaeger, M.; Gielen, E. Age-Related Bone Loss and Sarcopenia in Men. Maturitas 2019, 122, 51–56, doi:10.1016/j.maturitas.2019.01.006.
  3. Almeida, M.; Han, L.; Martin-Millan, M.; Plotkin, L.I.; Stewart, S.A.; Roberson, P.K.; Kousteni, S.; O’Brien, C.A.; Bellido, T.; Parfitt, A.M.; et al. Skeletal Involution by Age-Associated Oxidative Stress and Its Acceleration by Loss of Sex Steroids. J Biol Chem 2007, 282, 27285–27297, doi:10.1074/jbc.M702810200.
  4. Khosla, S.; Hofbauer, L.C. Osteoporosis Treatment: Recent Developments and Ongoing Challenges. Lancet Diabetes Endocrinol 2017, 5, 898–907, doi:10.1016/S2213-8587(17)30188-2.
  5. Das, M.; Cronin, O.; Keohane, D.M.; Cormac, E.M.; Nugent, H.; Nugent, M.; Molloy, C.; O’Toole, P.W.; Shanahan, F.; Molloy, M.G.; et al. Gut Microbiota Alterations Associated with Reduced Bone Mineral Density in Older Adults. Rheumatology (Oxford) 2019, 58, 2295–2304, doi:10.1093/rheumatology/kez302.
  6. He, J.; Xu, S.; Zhang, B.; Xiao, C.; Chen, Z.; Si, F.; Fu, J.; Lin, X.; Zheng, G.; Yu, G.; et al. Gut Microbiota and Metabolite Alterations Associated with Reduced Bone Mineral Density or Bone Metabolic Indexes in Postmenopausal Osteoporosis. Aging (Albany NY) 2020, 12, doi:10.18632/aging.103168.
  7. Li, C.; Huang, Q.; Yang, R.; Dai, Y.; Zeng, Y.; Tao, L.; Li, X.; Zeng, J.; Wang, Q. Gut Microbiota Composition and Bone Mineral Loss-Epidemiologic Evidence from Individuals in Wuhan, China. Osteoporos Int 2019, 30, 1003–1013, doi:10.1007/s00198-019-04855-5.
  8. Wang, J.; Wang, Y.; Gao, W.; Wang, B.; Zhao, H.; Zeng, Y.; Ji, Y.; Hao, D. Diversity Analysis of Gut Microbiota in Osteoporosis and Osteopenia Patients. PeerJ 2017, 5, e3450, doi:10.7717/peerj.3450.
  9. Xu, Z.; Xie, Z.; Sun, J.; Huang, S.; Chen, Y.; Li, C.; Sun, X.; Xia, B.; Tian, L.; Guo, C.; et al. Gut Microbiome Reveals Specific Dysbiosis in Primary Osteoporosis. Front. Cell. Infect. Microbiol. 2020, 10, 160, doi:10.3389/fcimb.2020.00160.
  10. Ma, S.; Qin, J.; Hao, Y.; Fu, L. Association of Gut Microbiota Composition and Function with an Aged Rat Model of Senile Osteoporosis Using 16S RRNA and Metagenomic Sequencing Analysis. Aging (Albany NY) 2020, 12, doi:10.18632/aging.103293.
  11. Wang, N.; Ma, S.; Fu, L. Gut Microbiota Dysbiosis as One Cause of Osteoporosis by Impairing Intestinal Barrier Function. Calcif Tissue Int 2021, doi:10.1007/s00223-021-00911-7.
  12. Ma, S.; Wang, N.; Zhang, P.; Wu, W.; Fu, L. Fecal Microbiota Transplantation Mitigates Bone Loss by Improving Gut Microbiome Composition and Gut Barrier Function in Aged Rats. PeerJ 2021, 9, e12293, doi:10.7717/peerj.12293.
  13. Jovel, J.; Patterson, J.; Wang, W.; Hotte, N.; O’Keefe, S.; Mitchel, T.; Perry, T.; Kao, D.; Mason, A.L.; Madsen, K.L.; et al. Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics. Front Microbiol 2016, 7, 459, doi:10.3389/fmicb.2016.00459.
  14. Xu, W.; Chen, T.; Pei, Y.; Guo, H.; Li, Z.; Yang, Y.; Zhang, F.; Yu, J.; Li, X.; Yang, Y.; et al. Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes. Front Microbiol 2021, 12, 678319, doi:10.3389/fmicb.2021.678319.
  15. Ma, S.; Qin, J.; Hao, Y.; Shi, Y.; Fu, L. Structural and Functional Changes of Gut Microbiota in Ovariectomized Rats and Their Correlations with Altered Bone Mass. Aging (Albany NY) 2020, 12, 10736–10753, doi:10.18632/aging.103290.
  16. Bostanciklioğlu, M. The Role of Gut Microbiota in Pathogenesis of Alzheimer’s Disease. J Appl Microbiol 2019, 127, 954–967, doi:10.1111/jam.14264.
  17. Wen, L.; Duffy, A. Factors Influencing the Gut Microbiota, Inflammation, and Type 2 Diabetes. J Nutr 2017, 147, 1468S-1475S, doi:10.3945/jn.116.240754.
  18. Alpizar-Rodriguez, D.; Lesker, T.R.; Gronow, A.; Gilbert, B.; Raemy, E.; Lamacchia, C.; Gabay, C.; Finckh, A.; Strowig, T. Prevotella Copri in Individuals at Risk for Rheumatoid Arthritis. Ann Rheum Dis 2019, 78, 590–593, doi:10.1136/annrheumdis-2018-214514.
  19. Bajer, L.; Kverka, M.; Kostovcik, M.; Macinga, P.; Dvorak, J.; Stehlikova, Z.; Brezina, J.; Wohl, P.; Spicak, J.; Drastich, P. Distinct Gut Microbiota Profiles in Patients with Primary Sclerosing Cholangitis and Ulcerative Colitis. World J Gastroenterol 2017, 23, 4548–4558, doi:10.3748/wjg.v23.i25.4548.
  20. Bernard, N.J. Rheumatoid Arthritis: Prevotella Copri Associated with New-Onset Untreated RA. Nat Rev Rheumatol 2014, 10, 2, doi:10.1038/nrrheum.2013.187.
  21. Brusca, S.B.; Abramson, S.B.; Scher, J.U. Microbiome and Mucosal Inflammation as Extra-Articular Triggers for Rheumatoid Arthritis and Autoimmunity. Curr Opin Rheumatol 2014, 26, 101–107, doi:10.1097/BOR.0000000000000008.
  22. Lin, H.; Liu, T.; Li, X.; Gao, X.; Wu, T.; Li, P. The Role of Gut Microbiota Metabolite Trimethylamine N-Oxide in Functional Impairment of Bone Marrow Mesenchymal Stem Cells in Osteoporosis Disease. Ann Transl Med 2020, 8, 1009, doi:10.21037/atm-20-5307.
  23. Bodogai, M.; O’Connell, J.; Kim, K.; Kim, Y.; Moritoh, K.; Chen, C.; Gusev, F.; Vaughan, K.; Shulzhenko, N.; Mattison, J.A.; et al. Commensal Bacteria Contribute to Insulin Resistance in Aging by Activating Innate B1a Cells. Sci Transl Med 2018, 10, eaat4271, doi:10.1126/scitranslmed.aat4271.
  24. Wang, F.; Yu, T.; Huang, G.; Cai, D.; Liang, X.; Su, H.; Zhu, Z.; Li, D.; Yang, Y.; Shen, P.; et al. Gut Microbiota Community and Its Assembly Associated with Age and Diet in Chinese Centenarians. J Microbiol Biotechnol 2015, 25, 1195–1204, doi:10.4014/jmb.1410.10014.
  25. Liu, J.; Chen, C.; Liu, Z.; Luo, Z.; Rao, S.; Jin, L.; Wan, T.; Yue, T.; Tan, Y.; Yin, H.; et al. Extracellular Vesicles from Child Gut Microbiota Enter into Bone to Preserve Bone Mass and Strength. Adv. Sci. 2021, 2004831, doi:10.1002/advs.202004831.
  26. Ayoub Moubareck, C.; Hammoudi Halat, D. Insights into Acinetobacter Baumannii: A Review of Microbiological, Virulence, and Resistance Traits in a Threatening Nosocomial Pathogen. Antibiotics (Basel) 2020, 9, E119, doi:10.3390/antibiotics9030119.
  27. Zhang, J.J.; Moore, B.S.; Tang, X. Engineering Salinispora Tropica for Heterologous Expression of Natural Product Biosynthetic Gene Clusters. Appl Microbiol Biotechnol 2018, 102, 8437–8446, doi:10.1007/s00253-018-9283-z.
  28. D’Amato, A.; Di Cesare Mannelli, L.; Lucarini, E.; Man, A.L.; Le Gall, G.; Branca, J.J.V.; Ghelardini, C.; Amedei, A.; Bertelli, E.; Regoli, M.; et al. Faecal Microbiota Transplant from Aged Donor Mice Affects Spatial Learning and Memory via Modulating Hippocampal Synaptic Plasticity- and Neurotransmission-Related Proteins in Young Recipients. Microbiome 2020, 8, 140, doi:10.1186/s40168-020-00914-w.
  29. Wauquier, F.; Léotoing, L.; Philippe, C.; Spilmont, M.; Coxam, V.; Wittrant, Y. Pros and Cons of Fatty Acids in Bone Biology. Prog Lipid Res 2015, 58, 121–145, doi:10.1016/j.plipres.2015.03.001.
  30. Vitale, G.; Salvioli, S.; Franceschi, C. Oxidative Stress and the Ageing Endocrine System. Nat Rev Endocrinol 2013, 9, 228–240, doi:10.1038/nrendo.2013.29.
  31. Li, H.; Wu, Y.; Huang, N.; Zhao, Q.; Yuan, Q.; Shao, B. γ-Aminobutyric Acid Promotes Osteogenic Differentiation of Mesenchymal Stem Cells by Inducing TNFAIP3. Curr Gene Ther 2020, 20, 152–161, doi:10.2174/1566523220999200727122502.
Subjects: Microbiology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to : ,
View Times: 486
Revisions: 4 times (View History)
Update Date: 01 Apr 2022
Video Production Service