Temporal variations in the gut microbial diversity in response to high-fat diet and exercise.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
08 Feb 2024
Historique:
received: 16 05 2023
accepted: 24 01 2024
medline: 9 2 2024
pubmed: 9 2 2024
entrez: 8 2 2024
Statut: epublish

Résumé

High-fat diet-induced obesity is a pandemic caused by an inactive lifestyle and increased consumption of Western diets and is a major risk factor for diabetes and cardiovascular diseases. In contrast, exercise can positively influence gut microbial diversity and is linked to a decreased inflammatory state. To understand the gut microbial variations associated with exercise and high-fat diet over time, we conducted a longitudinal study to examine the effect of covariates on gut microbial diversity and composition. Young mice were divided into four groups: Chow-diet (CHD), high-fat diet (HFD), high-fat diet + exercise (HFX), and exercise only (EXE) and underwent experimental intervention for 12 weeks. Fecal samples at week 0 and 12 were collected for DNA extraction, followed by 16S library preparation and sequencing. Data were analyzed using QIIME 2, R and MicrobiomeAnalyst. The Bacteroidetes-to-Firmicutes ratio decreased fivefold in the HFD and HFX groups compared to that in the CHD and EXE groups and increased in the EXE group over time. Alpha diversity was significantly increased in the EXE group longitudinally (p < 0.02), whereas diversity (Shannon, Faith's PD, and Fisher) and richness (ACE) was significantly reduced in the HFD (p < 0.005) and HFX (p < 0.03) groups over time. Beta diversity, based on the Jaccard, Bray-Curtis, and unweighted UniFrac distance metrics, was significant among the groups. Prevotella, Paraprevotella, Candidatus arthromitus, Lactobacillus salivarius, L. reuteri, Roseburia, Bacteroides uniformis, Sutterella, and Corynebacterium were differentially abundant in the chow-diet groups (CHD and EXE). Exercise significantly reduced the proportion of taxa characteristic of a high-fat diet, including Butyricimonas, Ruminococcus gnavus, and Mucispirillum schaedleri. Diet, age, and exercise significantly contributed to explaining the bacterial community structure and diversity in the gut microbiota. Modulating the gut microbiota and maintaining its stability can lead to targeted microbiome therapies to manage chronic and recurrent diseases and infections.

Identifiants

pubmed: 38332014
doi: 10.1038/s41598-024-52852-4
pii: 10.1038/s41598-024-52852-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3282

Subventions

Organisme : National Research Foundation of Korea
ID : 2019S1A2A2030980

Informations de copyright

© 2024. The Author(s).

Références

WHO European Regional Obesity Report 2022, (2022).
Abumweis, S., Alrefai, W. & Alzoughool, F. Association of obesity with COVID-19 diseases severity and mortality: A meta-analysis of studies. Obes. Med. 33, 100431. https://doi.org/10.1016/j.obmed.2022.100431 (2022).
doi: 10.1016/j.obmed.2022.100431 pubmed: 35702736 pmcid: 9181395
Singh, R. et al. Association of obesity with COVID-19 severity and mortality: An updated systemic review, meta-analysis, and meta-regression. Front. Endocrinol. (Lausanne) 13, 780872. https://doi.org/10.3389/fendo.2022.780872 (2022).
doi: 10.3389/fendo.2022.780872 pubmed: 35721716
Yates, T. et al. A population-based cohort study of obesity, ethnicity and COVID-19 mortality in 12.6 million adults in England. Nat. Commun. 13, 624. https://doi.org/10.1038/s41467-022-28248-1 (2022).
doi: 10.1038/s41467-022-28248-1 pubmed: 35110546 pmcid: 8810846
Paravidino, V. B. et al. Association between obesity and COVID-19 mortality and length of stay in intensive care unit patients in Brazil: A retrospective cohort study. Sci. Rep. 12, 13737. https://doi.org/10.1038/s41598-022-17197-w (2022).
doi: 10.1038/s41598-022-17197-w pubmed: 35962010 pmcid: 9372981
Schulz, M. D. et al. High-fat-diet-mediated dysbiosis promotes intestinal carcinogenesis independently of obesity. Nature 514, 508–512. https://doi.org/10.1038/nature13398 (2014).
doi: 10.1038/nature13398 pubmed: 25174708 pmcid: 4233209
Budreviciute, A. et al. Management and prevention strategies for non-communicable diseases (NCDs) and their risk factors. Front Public Health 8, 574111. https://doi.org/10.3389/fpubh.2020.574111 (2020).
doi: 10.3389/fpubh.2020.574111 pubmed: 33324597 pmcid: 7726193
Muscogiuri, G. et al. Gut microbiota: A new path to treat obesity. Int. J. Obes. Suppl. 9, 10–19. https://doi.org/10.1038/s41367-019-0011-7 (2019).
doi: 10.1038/s41367-019-0011-7 pubmed: 31391921 pmcid: 6683132
Klassen, J. L. Defining microbiome function. Nat. Microbiol. 3, 864–869. https://doi.org/10.1038/s41564-018-0189-4 (2018).
doi: 10.1038/s41564-018-0189-4 pubmed: 30046174
Belkaid, Y. & Hand, T. W. Role of the microbiota in immunity and inflammation. Cell 157, 121–141. https://doi.org/10.1016/j.cell.2014.03.011 (2014).
doi: 10.1016/j.cell.2014.03.011 pubmed: 24679531 pmcid: 4056765
Hou, K. et al. Microbiota in health and diseases. Signal Transduct. Target Ther. 7, 135. https://doi.org/10.1038/s41392-022-00974-4 (2022).
doi: 10.1038/s41392-022-00974-4 pubmed: 35461318 pmcid: 9034083
Kurilshikov, A. et al. Large-scale association analyses identify host factors influencing human gut microbiome composition. Nat. Genet 53, 156. https://doi.org/10.1038/s41588-020-00763-1 (2021).
doi: 10.1038/s41588-020-00763-1 pubmed: 33462485 pmcid: 8515199
Shi, N., Li, N., Duan, X. W. & Niu, H. T. Interaction between the gut microbiome and mucosal immune system. Military Med. Res. https://doi.org/10.1186/s40779-017-0122-9 (2017).
doi: 10.1186/s40779-017-0122-9
Zheng, D., Liwinski, T. & Elinav, E. Interaction between microbiota and immunity in health and disease. Cell Res. 30, 492–506. https://doi.org/10.1038/s41422-020-0332-7 (2020).
doi: 10.1038/s41422-020-0332-7 pubmed: 32433595 pmcid: 7264227
Clauss, M., Gérard, P., Mosca, A. & Leclerc, M. Interplay between exercise and gut microbiome in the context of human health and performance. Front Nutr. 8, 637010. https://doi.org/10.3389/fnut.2021.637010 (2021).
doi: 10.3389/fnut.2021.637010 pubmed: 34179053 pmcid: 8222532
Singh, R. K. et al. Influence of diet on the gut microbiome and implications for human health. J. Transl. Med. 15, 73. https://doi.org/10.1186/s12967-017-1175-y (2017).
doi: 10.1186/s12967-017-1175-y pubmed: 28388917 pmcid: 5385025
Bajinka, O., Tan, Y., Abdelhalim, K. A., Ozdemir, G. & Qiu, X. Extrinsic factors influencing gut microbes, the immediate consequences and restoring eubiosis. AMB Express 10, 130. https://doi.org/10.1186/s13568-020-01066-8 (2020).
doi: 10.1186/s13568-020-01066-8 pubmed: 32710186 pmcid: 7381537
Si, J. et al. Long-term life history predicts current gut microbiome in a population-based cohort study. Nat. Aging 2, 885–895. https://doi.org/10.1038/s43587-022-00286-w (2022).
doi: 10.1038/s43587-022-00286-w pubmed: 37118287 pmcid: 10154234
Imdad, S., Lim, W., Kim, J. H. & Kang, C. Intertwined relationship of mitochondrial metabolism, gut microbiome and exercise potential. Int. J. Mol. Sci. 23, 2679. https://doi.org/10.3390/ijms23052679 (2022).
doi: 10.3390/ijms23052679 pubmed: 35269818 pmcid: 8910986
Aldars-García, L., Marin, A. C., Chaparro, M. & Gisbert, J. P. The interplay between immune system and microbiota in inflammatory bowel disease: A narrative review. Int. J. Mol. Sci. 22, 3076. https://doi.org/10.3390/ijms22063076 (2021).
doi: 10.3390/ijms22063076 pubmed: 33802883 pmcid: 8002696
Valitutti, F., Cucchiara, S. & Fasano, A. Celiac disease and the microbiome. Nutrients 11, 2403. https://doi.org/10.3390/nu11102403 (2019).
doi: 10.3390/nu11102403 pubmed: 31597349 pmcid: 6835875
Lazar, V. et al. Gut microbiota, host organism, and diet trialogue in diabetes and obesity. Front. Nutr. https://doi.org/10.3389/fnut.2019.00021 (2019).
doi: 10.3389/fnut.2019.00021 pubmed: 30931309 pmcid: 6424913
Liu, B.-N., Liu, X.-T., Liang, Z.-H. & Wang, J.-H. Gut microbiota in obesity. World J. Gastroenterol. 27, 3837–3850. https://doi.org/10.3748/wjg.v27.i25.3837 (2021).
doi: 10.3748/wjg.v27.i25.3837 pubmed: 34321848 pmcid: 8291023
López-Cepero, A. A. & Palacios, C. Association of the intestinal microbiota and obesity. Puerto Rico health sciences journal 34 (2015).
Geng, J., Ni, Q., Sun, W., Li, L. & Feng, X. The links between gut microbiota and obesity and obesity related diseases. Biomed. Pharmacother. 147, 112678. https://doi.org/10.1016/j.biopha.2022.112678 (2022).
doi: 10.1016/j.biopha.2022.112678 pubmed: 35134709
Xu, Z. et al. Gut microbiota in patients with obesity and metabolic disorders—a systematic review. Genes Nutr. 17, 2. https://doi.org/10.1186/s12263-021-00703-6 (2022).
doi: 10.1186/s12263-021-00703-6 pubmed: 35093025 pmcid: 8903526
Cunningham, A. L., Stephens, J. W. & Harris, D. A. A review on gut microbiota: A central factor in the pathophysiology of obesity. Lipids Health Dis. 20, 65. https://doi.org/10.1186/s12944-021-01491-z (2021).
doi: 10.1186/s12944-021-01491-z pubmed: 34233682 pmcid: 8262044
Dali-Youcef, N., Mecili, M., Ricci, R. & Andres, E. Metabolic inflammation: Connecting obesity and insulin resistance. Ann. Med. 45, 242–253. https://doi.org/10.3109/07853890.2012.705015 (2013).
doi: 10.3109/07853890.2012.705015 pubmed: 22834949
Wu, H. & Ballantyne, C. M. Metabolic inflammation and insulin resistance in obesity. Circ. Res. 126, 1549–1564. https://doi.org/10.1161/CIRCRESAHA.119.315896 (2020).
doi: 10.1161/CIRCRESAHA.119.315896 pubmed: 32437299 pmcid: 7250139
Basak, S., Banerjee, A., Pathak, S. & Duttaroy, A. K. Dietary fats and the gut microbiota: Their impacts on lipid-induced metabolic syndrome. J. Funct. Foods 91, 105026. https://doi.org/10.1016/j.jff.2022.105026 (2022).
doi: 10.1016/j.jff.2022.105026
Monda, V. et al. Exercise modifies the gut microbiota with positive health effects. Oxidative Med. Cell. Longevity 2017, 3831972–3831972. https://doi.org/10.1155/2017/3831972 (2017).
doi: 10.1155/2017/3831972
Mohr, A. E. et al. The athletic gut microbiota. J. Int. Soc. Sports Nutr. 17, 24–24. https://doi.org/10.1186/s12970-020-00353-w (2020).
doi: 10.1186/s12970-020-00353-w pubmed: 32398103 pmcid: 7218537
Mailing, L. J., Allen, J. M., Buford, T. W., Fields, C. J. & Woods, J. A. Exercise and the gut microbiome: A review of the evidence, potential mechanisms, and implications for human health. Exerc. Sport Sci. Rev. 47, 75–85. https://doi.org/10.1249/jes.0000000000000183 (2019).
doi: 10.1249/jes.0000000000000183 pubmed: 30883471
Sylow, L., Kleinert, M., Richter, E. A. & Jensen, T. E. Exercise-stimulated glucose uptake—regulation and implications for glycaemic control. Nat. Rev. Endocrinol. 13, 133–148. https://doi.org/10.1038/nrendo.2016.162 (2017).
doi: 10.1038/nrendo.2016.162 pubmed: 27739515
Dziewiecka, H. et al. Physical activity induced alterations of gut microbiota in humans: A systematic review. BMC Sports Sci. Med. Rehabil. 14, 122. https://doi.org/10.1186/s13102-022-00513-2 (2022).
doi: 10.1186/s13102-022-00513-2 pubmed: 35799284 pmcid: 9264679
Yun, E. J. et al. Diet is a stronger covariate than exercise in determining gut microbial richness and diversity. Nutrients 14, 2507. https://doi.org/10.3390/nu14122507 (2022).
doi: 10.3390/nu14122507 pubmed: 35745235 pmcid: 9229834
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857. https://doi.org/10.1038/s41587-019-0209-9 (2019).
doi: 10.1038/s41587-019-0209-9 pubmed: 31341288 pmcid: 7015180
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17(3), 2011. https://doi.org/10.14806/ej.17.1.200 (2011).
doi: 10.14806/ej.17.1.200
Janssen, S. et al. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems https://doi.org/10.1128/mSystems.00021-18 (2018).
doi: 10.1128/mSystems.00021-18 pubmed: 29795809 pmcid: 5954204
McDonald, D. et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618. https://doi.org/10.1038/ismej.2011.139 (2012).
doi: 10.1038/ismej.2011.139 pubmed: 22134646
Pedregosa, F. et al. Scikit-learn: Machine learning in python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Bokulich, N. A. et al. q2-sample-classifier: Machine-learning tools for microbiome classification and regression. J. Open Res. Softw. 3, 934. https://doi.org/10.21105/joss.00934 (2018).
doi: 10.21105/joss.00934 pubmed: 31552137 pmcid: 6759219
Chong, J., Liu, P., Zhou, G. & Xia, J. Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat. Protoc. 15, 799–821. https://doi.org/10.1038/s41596-019-0264-1 (2020).
doi: 10.1038/s41596-019-0264-1 pubmed: 31942082
Dhariwal, A. et al. MicrobiomeAnalyst: A web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 45, W180–W188. https://doi.org/10.1093/nar/gkx295 (2017).
doi: 10.1093/nar/gkx295 pubmed: 28449106 pmcid: 5570177
Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome. Biol. 12, R60. https://doi.org/10.1186/gb-2011-12-6-r60 (2011).
doi: 10.1186/gb-2011-12-6-r60 pubmed: 21702898 pmcid: 3218848
Dewhirst, F. E. et al. “Flexispira rappini” strains represent at least 10 Helicobacter taxa. Int. J. Syst. Evol. Microbiol. 50(Pt 5), 1781–1787. https://doi.org/10.1099/00207713-50-5-1781 (2000).
doi: 10.1099/00207713-50-5-1781 pubmed: 11034487
Hänninen, M. L., Kärenlampi, R. I., Koort, J. M. K., Mikkonen, T. & Björkroth, K. J. Extension of the species Helicobacter bilis to include the reference strains of Helicobacter sp. flexispira taxa 2, 3 and 8 and Finnish canine and feline flexispira strains. Int. J. Syst. Evol. Microbiol. 55, 891–898. https://doi.org/10.1099/ijs.0.63245-0 (2005).
doi: 10.1099/ijs.0.63245-0 pubmed: 15774681
Gentile, C. L. & Weir, T. L. The gut microbiota at the intersection of diet and human health. Science 362, 776–780. https://doi.org/10.1126/science.aau5812 (2018).
doi: 10.1126/science.aau5812 pubmed: 30442802
Cani, P. D. et al. Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut 58, 1091–1103. https://doi.org/10.1136/gut.2008.165886 (2009).
doi: 10.1136/gut.2008.165886 pubmed: 19240062
Chassaing, B. et al. Lack of soluble fiber drives diet-induced adiposity in mice. Am. J. Physiol. -Gastrointestinal Liver Physiol. 309(7), G528–G541. https://doi.org/10.1152/ajpgi.00172.2015 (2015).
doi: 10.1152/ajpgi.00172.2015
van Moorsel, D. et al. Demonstration of a day-night rhythm in human skeletal muscle oxidative capacity. Mol. Metab. 5, 635–645. https://doi.org/10.1016/j.molmet.2016.06.012 (2016).
doi: 10.1016/j.molmet.2016.06.012 pubmed: 27656401 pmcid: 5021670
Schönke, M. et al. Time to run: Late rather than early exercise training in mice remodels the gut microbiome and reduces atherosclerosis development. FASEB J. 37, e22719. https://doi.org/10.1096/fj.202201304R (2023).
doi: 10.1096/fj.202201304R pubmed: 36562708
Le Chatelier, E. et al. Richness of human gut microbiome correlates with metabolic markers. Nature 500, 541–546. https://doi.org/10.1038/nature12506 (2013).
doi: 10.1038/nature12506 pubmed: 23985870
Ortiz-Alvarez, L., Xu, H. & Martinez-Tellez, B. Influence of exercise on the human gut microbiota of healthy adults: A systematic review. Clin. Transl. Gastroenterol. 11, e00126. https://doi.org/10.14309/ctg.0000000000000126 (2020).
doi: 10.14309/ctg.0000000000000126 pubmed: 32463624 pmcid: 7145029
Hintikka, J. E. et al. Aerobic exercise training and gut microbiome-associated metabolic shifts in women with overweight: A multi-omic study. Sci. Rep. 13, 11228. https://doi.org/10.1038/s41598-023-38357-6 (2023).
doi: 10.1038/s41598-023-38357-6 pubmed: 37433843 pmcid: 10336137
Corbin, K. D. et al. Host-diet-gut microbiome interactions influence human energy balance: A randomized clinical trial. Nat. Commun. 14, 3161. https://doi.org/10.1038/s41467-023-38778-x (2023).
doi: 10.1038/s41467-023-38778-x pubmed: 37258525 pmcid: 10232526
Olesen, S. W. & Alm, E. J. Dysbiosis is not an answer. Nat. Microbiol. 1, 16228. https://doi.org/10.1038/nmicrobiol.2016.228 (2016).
doi: 10.1038/nmicrobiol.2016.228 pubmed: 27886190
Magne, F. et al. The firmicutes/bacteroidetes ratio: A relevant marker of gut dysbiosis in obese patients?. Nutrients 12, 1474. https://doi.org/10.3390/nu12051474 (2020).
doi: 10.3390/nu12051474 pubmed: 32438689 pmcid: 7285218
Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Microbial ecology: Human gut microbes associated with obesity. Nature 444, 1022–1023. https://doi.org/10.1038/4441022a (2006).
doi: 10.1038/4441022a pubmed: 17183309
Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Nat. Acad. Sci. 102, 11070–11075. https://doi.org/10.1073/pnas.0504978102 (2005).
doi: 10.1073/pnas.0504978102 pubmed: 16033867 pmcid: 1176910
Kapoor, P. et al. Effect of anthocyanins on gut health markers, Firmicutes–Bacteroidetes ratio and short-chain fatty acids: a systematic review via meta-analysis. Sci. Rep. 13, 1729. https://doi.org/10.1038/s41598-023-28764-0 (2023).
doi: 10.1038/s41598-023-28764-0 pubmed: 36720989 pmcid: 9889808
Clauss, M., Gérard, P., Mosca, A. & Leclerc, M. Interplay between exercise and gut microbiome in the context of human health and performance. Front. Nutr. https://doi.org/10.3389/fnut.2021.637010 (2021).
doi: 10.3389/fnut.2021.637010 pubmed: 34179053 pmcid: 8222532
Clarke, S. F. et al. Exercise and associated dietary extremes impact on gut microbial diversity. Gut 63, 1913–1920. https://doi.org/10.1136/gutjnl-2013-306541 (2014).
doi: 10.1136/gutjnl-2013-306541 pubmed: 25021423
Evans, C. C. et al. Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity. PLoS One 9, e92193. https://doi.org/10.1371/journal.pone.0092193 (2014).
doi: 10.1371/journal.pone.0092193 pubmed: 24670791 pmcid: 3966766
Mika, A. et al. Exercise is more effective at altering gut microbial composition and producing stable changes in lean mass in juvenile versus adult male F344 rats. PloS one 10, e0125889 (2015).
doi: 10.1371/journal.pone.0125889 pubmed: 26016739 pmcid: 4446322
Biddle, A., Stewart, L., Blanchard, J. & Leschine, S. Untangling the genetic basis of fibrolytic specialization by lachnospiraceae and ruminococcaceae in diverse gut communities. Diversity 5, 627–640 (2013).
doi: 10.3390/d5030627
Anand, S., Kaur, H. & Mande, S. S. Comparative in silico analysis of butyrate production pathways in gut commensals and pathogens. Front. Microbiol. https://doi.org/10.3389/fmicb.2016.01945 (2016).
doi: 10.3389/fmicb.2016.01945 pubmed: 27994578 pmcid: 5133246
Singh, R. P., Halaka, D. A., Hayouka, Z. & Tirosh, O. High-fat diet induced alteration of mice microbiota and the functional ability to utilize fructooligosaccharide for ethanol production. Front. Cell. Infect. Microbiol. https://doi.org/10.3389/fcimb.2020.00376 (2020).
doi: 10.3389/fcimb.2020.00376 pubmed: 33614527 pmcid: 7738612
Hamilton, M. K., Boudry, G., Lemay, D. G. & Raybould, H. E. Changes in intestinal barrier function and gut microbiota in high-fat diet-fed rats are dynamic and region dependent. Am. J. Physiol. Gastrointest Liver Physiol. 308, G840-851. https://doi.org/10.1152/ajpgi.00029.2015 (2015).
doi: 10.1152/ajpgi.00029.2015 pubmed: 25747351 pmcid: 4437018
Picca, A. et al. Gut microbial, inflammatory and metabolic signatures in older people with physical frailty and sarcopenia: results from the BIOSPHERE study. Nutrients 12, 65. https://doi.org/10.3390/nu12010065 (2019).
doi: 10.3390/nu12010065 pubmed: 31887978 pmcid: 7019826
Davis, C. P. & Savage, D. C. Habitat, succession, attachment, and morphology of segmented, filamentous microbes indigenous to the murine gastrointestinal tract. Infect. Immun. 10, 948–956. https://doi.org/10.1128/iai.10.4.948-956.1974 (1974).
doi: 10.1128/iai.10.4.948-956.1974 pubmed: 4426712 pmcid: 423041
Jonsson, H., Hugerth, L. W., Sundh, J., Lundin, E. & Andersson, A. F. Genome sequence of segmented filamentous bacteria present in the human intestine. Commun. Biol. 3, 485. https://doi.org/10.1038/s42003-020-01214-7 (2020).
doi: 10.1038/s42003-020-01214-7 pubmed: 32887924 pmcid: 7474095
Ivanov, I. I. et al. Induction of intestinal Th17 cells by segmented filamentous bacteria. Cell 139, 485–498. https://doi.org/10.1016/j.cell.2009.09.033 (2009).
doi: 10.1016/j.cell.2009.09.033 pubmed: 19836068 pmcid: 2796826
Wang, Y. et al. Induction of intestinal Th17 cells by flagellins from segmented filamentous bacteria. Front. Immunol. 10, 2750. https://doi.org/10.3389/fimmu.2019.02750 (2019).
doi: 10.3389/fimmu.2019.02750 pubmed: 31824516 pmcid: 6883716
Zhu, Q., Jiang, S. & Du, G. Effects of exercise frequency on the gut microbiota in elderly individuals. Microbiologyopen 9, e1053. https://doi.org/10.1002/mbo3.1053 (2020).
doi: 10.1002/mbo3.1053 pubmed: 32356611 pmcid: 7424259
Palmas, V. et al. Gut microbiota markers associated with obesity and overweight in Italian adults. Sci. Rep. 11, 5532. https://doi.org/10.1038/s41598-021-84928-w (2021).
doi: 10.1038/s41598-021-84928-w pubmed: 33750881 pmcid: 7943584
Liang, R. et al. Characteristics of the gut microbiota in professional martial arts athletes: A comparison between different competition levels. PLoS One 14, e0226240. https://doi.org/10.1371/journal.pone.0226240 (2019).
doi: 10.1371/journal.pone.0226240 pubmed: 31881037 pmcid: 6934331
Natividad, J. M. et al. Bilophila wadsworthia aggravates high fat diet induced metabolic dysfunctions in mice. Nat. Commun. 9, 2802. https://doi.org/10.1038/s41467-018-05249-7 (2018).
doi: 10.1038/s41467-018-05249-7 pubmed: 30022049 pmcid: 6052103
Wei, B. et al. Gut microbiota-mediated xanthine metabolism is associated with resistance to high-fat diet-induced obesity. J. Nutr. Biochem. 88, 108533. https://doi.org/10.1016/j.jnutbio.2020.108533 (2021).
doi: 10.1016/j.jnutbio.2020.108533 pubmed: 33250443
Henke, M. T. et al. Ruminococcus gnavus, a member of the human gut microbiome associated with Crohn’s disease, produces an inflammatory polysaccharide. Proc. Natl. Acad. Sci. USA 116, 12672–12677. https://doi.org/10.1073/pnas.1904099116 (2019).
doi: 10.1073/pnas.1904099116 pubmed: 31182571 pmcid: 6601261
Toya, T. et al. Coronary artery disease is associated with an altered gut microbiome composition. PLoS One 15, e0227147. https://doi.org/10.1371/journal.pone.0227147 (2020).
doi: 10.1371/journal.pone.0227147 pubmed: 31995569 pmcid: 6988937
Petriz, B. A. et al. Exercise induction of gut microbiota modifications in obese, non-obese and hypertensive rats. BMC Genomics 15, 511. https://doi.org/10.1186/1471-2164-15-511 (2014).
doi: 10.1186/1471-2164-15-511 pubmed: 24952588 pmcid: 4082611
Chua, H. H. et al. Intestinal dysbiosis featuring abundance of Ruminococcus gnavus associates with allergic diseases in infants. Gastroenterology 154, 154–167. https://doi.org/10.1053/j.gastro.2017.09.006 (2018).
doi: 10.1053/j.gastro.2017.09.006 pubmed: 28912020
Hall, A. B. et al. A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients. Genome Med. 9, 103. https://doi.org/10.1186/s13073-017-0490-5 (2017).
doi: 10.1186/s13073-017-0490-5 pubmed: 29183332 pmcid: 5704459
Vacca, M. et al. The controversial role of human gut lachnospiraceae. Microorganisms 8, 573. https://doi.org/10.3390/microorganisms8040573 (2020).
doi: 10.3390/microorganisms8040573 pubmed: 32326636 pmcid: 7232163
Ottosson, F. et al. Connection between BMI-related plasma metabolite profile and gut microbiota. J. Clin. Endocrinol. Metab. 103, 1491–1501. https://doi.org/10.1210/jc.2017-02114 (2018).
doi: 10.1210/jc.2017-02114 pubmed: 29409054
Sanguinetti, E. et al. Microbiome-metabolome signatures in mice genetically prone to develop dementia, fed a normal or fatty diet. Sci. Rep. 8, 4907. https://doi.org/10.1038/s41598-018-23261-1 (2018).
doi: 10.1038/s41598-018-23261-1 pubmed: 29559675 pmcid: 5861049
Kulkarni, P., Devkumar, P. & Chattopadhyay, I. Could dysbiosis of inflammatory and anti-inflammatory gut bacteria have an implications in the development of type 2 diabetes? A pilot investigation. BMC Res. Notes 14, 52. https://doi.org/10.1186/s13104-021-05466-2 (2021).
doi: 10.1186/s13104-021-05466-2 pubmed: 33549142 pmcid: 7868023
Murga-Garrido, S. M. et al. Gut microbiome variation modulates the effects of dietary fiber on host metabolism. Microbiome 9, 117. https://doi.org/10.1186/s40168-021-01061-6 (2021).
doi: 10.1186/s40168-021-01061-6 pubmed: 34016169 pmcid: 8138933
Li, Y., Liu, Q., Peng, C. & Ruan, B. Both gut microbiota and differentially expressed proteins are relevant to the development of obesity. Biomed. Res. Int. 2020, 5376108–5376108. https://doi.org/10.1155/2020/5376108 (2020).
doi: 10.1155/2020/5376108 pubmed: 33029514 pmcid: 7533028
Herp, S., Durai Raj, A. C., Salvado Silva, M., Woelfel, S. & Stecher, B. The human symbiont mucispirillum schaedleri: Causality in health and disease. Med. Microbiol. Immunol. 210, 173–179. https://doi.org/10.1007/s00430-021-00702-9 (2021).
doi: 10.1007/s00430-021-00702-9 pubmed: 34021796
Caruso, R. et al. A specific gene-microbe interaction drives the development of Crohn’s disease–like colitis in mice. Sci. Immunol. 4, eaaw4341. https://doi.org/10.1126/sciimmunol.aaw4341 (2019).
doi: 10.1126/sciimmunol.aaw4341 pubmed: 31004013 pmcid: 8882361
Duan, Y. et al. Inflammatory links between high fat diets and diseases. Front. Immunol. https://doi.org/10.3389/fimmu.2018.02649 (2018).
doi: 10.3389/fimmu.2018.02649 pubmed: 30519236 pmcid: 6251325
Han, M. S. et al. Regulation of adipose tissue inflammation by interleukin 6. Proc. Nat. Acad. Sci. 117, 2751–2760. https://doi.org/10.1073/pnas.1920004117 (2020).
doi: 10.1073/pnas.1920004117 pubmed: 31980524 pmcid: 7022151
Loy, A. et al. Lifestyle and horizontal gene transfer-mediated evolution of Mucispirillum schaedleri, a core member of the murine gut microbiota. MSystems 2, e00171-00116. https://doi.org/10.1128/mSystems.00171-16 (2017).
doi: 10.1128/mSystems.00171-16 pubmed: 28168224 pmcid: 5285517
Fernandez, J. et al. Resistance and endurance exercise training induce differential changes in gut microbiota composition in murine models. Front. Physiol. 12, 748854. https://doi.org/10.3389/fphys.2021.748854 (2021).
doi: 10.3389/fphys.2021.748854 pubmed: 35002754 pmcid: 8739997
Hwang, L.-L. et al. Sex differences in high-fat diet-induced obesity, metabolic alterations and learning, and synaptic plasticity deficits in mice. Obesity 18, 463–469. https://doi.org/10.1038/oby.2009.273 (2010).
doi: 10.1038/oby.2009.273 pubmed: 19730425

Auteurs

Saba Imdad (S)

Molecular Metabolism in Health and Disease, Exercise Physiology Laboratory, Sport Science Research Institute, Inha University, Incheon, 22212, South Korea.
Department of Biomedical Laboratory Science, College of Health Science, Cheongju University, Cheongju, 28503, South Korea.

Byunghun So (B)

Molecular Metabolism in Health and Disease, Exercise Physiology Laboratory, Sport Science Research Institute, Inha University, Incheon, 22212, South Korea.

Junho Jang (J)

Molecular Metabolism in Health and Disease, Exercise Physiology Laboratory, Sport Science Research Institute, Inha University, Incheon, 22212, South Korea.

Jinhan Park (J)

Molecular Metabolism in Health and Disease, Exercise Physiology Laboratory, Sport Science Research Institute, Inha University, Incheon, 22212, South Korea.

Sam-Jun Lee (SJ)

Department of Sport Rehabilitation, College of Health, Welfare, and Education, Tong Myong University, Busan, 48520, South Korea.

Jin-Hee Kim (JH)

Department of Biomedical Laboratory Science, College of Health Science, Cheongju University, Cheongju, 28503, South Korea. jinheekim@cju.ac.kr.

Chounghun Kang (C)

Molecular Metabolism in Health and Disease, Exercise Physiology Laboratory, Sport Science Research Institute, Inha University, Incheon, 22212, South Korea. ck@inha.ac.kr.
Department of Physical Education, College of Education, Inha University, Incheon, 22212, South Korea. ck@inha.ac.kr.

Classifications MeSH