Bone loss with aging is independent of gut microbiome in mice

Abstract

Emerging evidence suggests a significant role of gut microbiome in bone health. Aging is well recognized as a crucial factor influencing the gut microbiome. In this study, we investigated whether age-dependent microbial change contributes to age-related bone loss in CB6F1 mice. The bone phenotype of 24-month-old germ-free (GF) mice was indistinguishable compared to their littermates colonized by fecal transplant at 1-month-old. Moreover, bone loss from 3 to 24-month-old was comparable between GF and specific pathogen-free (SPF) mice. Thus, GF mice were not protected from age-related bone loss. 16S rRNA gene sequencing of fecal samples from 3-month and 24-month-old SPF males indicated an age-dependent microbial shift with an alteration in energy and nutrient metabolism potential. An integrative analysis of 16S predicted metagenome function and LC-MS fecal metabolome revealed an enrichment of protein and amino acid biosynthesis pathways in aged mice. Microbial S-adenosyl methionine metabolism was increased in the aged mice, which has previously been associated with the host aging process. Collectively, aging caused microbial taxonomic and functional alteration in mice. To demonstrate the functional importance of young and old microbiome to bone, we colonized GF mice with fecal microbiome from 3-month or 24-month-old SPF donor mice for 1 and 8 months. The effect of microbial colonization on bone phenotypes was independent of the microbiome donors’ age. In conclusion, our study indicates age-related bone loss occurs independent of gut microbiome.

References

[1.] SözenT, ÖzışıkL, BaşaranNÇ. An overview and management of osteoporosis. Eur. J. Rheumatol., 2017, 4: 46

[2.] ClynesMA, et al. . The epidemiology of osteoporosis. Br. Med. Bull., 2020, 133: 105-117

[3.] ShaneE, et al. . Atypical subtrochanteric and diaphyseal femoral fractures: second report of a task force of the American Society for Bone and Mineral Research. J. Bone Miner. Res., 2014, 29: 1-23

[4.] AliT, JayRH. Spontaneous femoral shaft fracture after long-term alendronate. Age Ageing, 2009, 38: 625-626

[5.] GirgisCM, SherD, SeibelMJ. Atypical femoral fractures and bisphosphonate use. N. Engl. J. Med., 2010, 362: 1848-1849

[6.] SampalisJS, et al. . Long‐term impact of adherence to oral bisphosphonates on osteoporotic fracture incidence. J. Bone Miner. Res., 2012, 27: 202-210

[7.] YanJ, et al. . Gut microbiota induce IGF-1 and promote bone formation and growth. Proc. Natl. Acad. Sci., 2016, 113: E7554-E7563

[8.] CastanedaM, SmithKM, NixonJC, HernandezCJ, RowanS. Alterations to the gut microbiome impair bone tissue strength in aged mice. Bone Rep., 2021, 14

[9.] LunaM, et al. . Components of the gut microbiome that influence bone tissue‐level strength. J. Bone Miner. Res., 2021, 36: 1823-1834

[10.] LiJY, et al. . Sex steroid deficiency–associated bone loss is microbiota dependent and prevented by probiotics. J. Clin. Investig., 2016, 126: 2049-2063

[11.] SchepperJD, et al. . Involvement of the gut microbiota and barrier function in Glucocorticoid‐Induced osteoporosis. J. Bone Miner. Res., 2020, 35: 801-820

[12.] YuM, et al. . PTH induces bone loss via microbial-dependent expansion of intestinal TNF+ T cells and Th17 cells. Nat. Commun., 2020, 11

[13.] SchwarzerM, et al. . Lactobacillus plantarum strain maintains growth of infant mice during chronic undernutrition. Science, 2016, 351: 854-857

[14.] SchepperJD, et al. . Probiotic Lactobacillus reuteri prevents postantibiotic bone loss by reducing intestinal dysbiosis and preventing barrier disruption. J. Bone Miner. Res., 2019, 34: 681-698

[15.] ZhangJ, et al. . Loss of bone and Wnt10b expression in male type 1 diabetic mice is blocked by the probiotic Lactobacillus reuteri. Endocrinology, 2015, 156: 3169-3182

[16.] YatsunenkoT, et al. . Human gut microbiome viewed across age and geography. Nature, 2012, 486: 222-227

[17.] RodríguezJM, et al. . The composition of the gut microbiota throughout life, with an emphasis on early life. Microb. Ecol. Health Dis., 2015, 26: 26050

[18.] VakiliB, FatehA, AghdaeiHA, SotoodehnejadnematalahiF, SiadatSD. Intestinal microbiota in elderly inpatients with Clostridioides difficile infection. Infect. Drug Resist., 2020, 13: 2723

[19.] ClaessonMJ, et al. . Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proc. Natl. Acad. Sci., 2011, 108: 4586-4591

[20.] MaffeiVJ, et al. . Biological aging and the human gut microbiota. J. Gerontol. Ser. A Biomed. Sci. Med. Sci., 2017, 72: 1474-1482

[21.] Saint-CriqV, Lugo-VillarinoG, ThomasM. Dysbiosis, malnutrition and enhanced gut-lung axis contribute to age-related respiratory diseases. Ageing Res. Rev., 2021, 66

[22.] WilmanskiT, et al. . Gut microbiome pattern reflects healthy ageing and predicts survival in humans. Nat. Metab., 2021, 3: 274-286

[23.] YouX, DadwalUC, LenburgME, KacenaMA, CharlesJF. Murine gut microbiome meta-analysis reveals alterations in carbohydrate metabolism in response to aging. Msystems, 2022, 7: e01248-21

[24.] CreecyA, et al. . The age-related decrease in material properties of BALB/c mouse long bones involves alterations to the extracellular matrix. Bone, 2020, 130

[25.] PiemonteseM, et al. . Old age causes de novo intracortical bone remodeling and porosity in mice. JCI Insight, 2017, 2: e93771

[26.] FergusonVL, AyersRA, BatemanTA, SimskeSJ. Bone development and age-related bone loss in male C57BL/6J mice. Bone, 2003, 33: 387-398

[27.] WillinghammMD, et al. . Age-related changes in bone structure and strength in female and male BALB/c mice. Calcif. Tissue Int., 2010, 86: 470-483

[28.] ShimJ, IwayaC, AmbroseCG, SuzukiA, IwataJ. Micro-computed tomography assessment of bone structure in aging mice. Sci. Rep., 2022, 12

[29.] MetgesCC. Contribution of microbial amino acids to amino acid homeostasis of the host. J. Nutr., 2000, 130: 1857S-1864SS

[30.] CabreiroF, et al. . Metformin retards aging in C. elegans by altering microbial folate and methionine metabolism. Cell, 2013, 153: 228-239

[31.] TyagiAM, et al. . The gut microbiota is a transmissible determinant of skeletal maturation. Elife, 2021, 10

[32.] TurnbaughPJ, et al. . An obesity-associated gut microbiome with increased capacity for energy harvest. Nature, 2006, 444: 1027-1031

[33.] SprockettD, FukamiT, RelmanDA. Role of priority effects in the early-life assembly of the gut microbiota. Nat. Rev. Gastroenterol. Hepatol., 2018, 15: 197-205

[34.] WangS, et al. . Gut microbiota mediates the anti-obesity effect of calorie restriction in mice. Sci. Rep., 2018, 8

[35.] YangYW, et al. . Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in mouse feces. Appl. Environ. Microbiol., 2015, 81: 6749-6756

[36.] YouX, et al. . Food-grade cationic antimicrobial ε-polylysine transiently alters the gut microbial community and predicted metagenome function in CD-1 mice. NPJ Sci. Food, 2017, 1

[37.] YuM, et al. . Ovariectomy induces bone loss via microbial-dependent trafficking of intestinal TNF+ T cells and Th17 cells. J. Clin. Investig., 2021, 131: e143137

[38.] NilssonA, SundhD, BäckhedF, LorentzonM. Lactobacillus reuteri reduces bone loss in older women with low bone mineral density: a randomized, placebo‐controlled, double‐blind, clinical trial. J. Intern. Med., 2018, 284: 307-317

[39.] LeeCC, et al. . Lactobacillus plantarum TWK10 attenuates aging-associated muscle weakness, bone loss, and cognitive impairment by modulating the gut microbiome in mice. Front. Nutr., 2021, 8

[40.] BolyenE, et al. . Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol., 2019, 37: 852-857

[41.] DouglasGM, et al. . PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol., 2020, 38: 685-688

[42.] RobinsonMD, McCarthyDJ, SmythGK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010, 26: 139-140

[43.] SegataN, et al. . Metagenomic biomarker discovery and explanation. Genome Biol., 2011, 12

[44.] De GregorisTB, AldredN, ClareAS, BurgessJG. Improvement of phylum-and class-specific primers for real-time PCR quantification of bacterial taxa. J. Microbiol. Methods, 2011, 86: 351-356

[45.] YurektenO, et al. . MetaboLights: open data repository for metabolomics. Nucleic Acids Res., 2024, 52: D640-D646

[46.] PangZ, et al. . Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nat. Protoc., 2022, 17: 1735-1761

[47.] Villanueva R. A. M., Chen Z. J. ggplot2: elegant graphics for data analysis. Taylor & Francis; 2019.

[48.] LiS, et al. . Predicting network activity from high throughput metabolomics. PLoS Comput. Biol., 2013, 9: e1003123

[49.] SubramanianA, et al. . Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci., 2005, 102: 15545-15550

[50.] DixonP. VEGAN, a package of R functions for community ecology. J. Veg. Sci., 2003, 14: 927-930

Funding

U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)(R01-AG046257); U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)(P30-AR070253); U.S. Department of Health & Human Services | National Institutes of Health (NIH)(P40-OD010995); U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)(P30-DK034987); Crohn's and Colitis Foundation (Crohn's & Colitis Foundation)(997397)