Short-term high-intensity interval training exercise does not affect gut bacterial community diversity or composition of lean and overweight men

Elizabeth A Rettedal, Julia M E Cree, Shannon E Adams, Caitlin MacRae, Paula M L Skidmore, David Cameron-Smith, Nicholas Gant, Cherie Blenkiron, Troy L Merry, Elizabeth A Rettedal, Julia M E Cree, Shannon E Adams, Caitlin MacRae, Paula M L Skidmore, David Cameron-Smith, Nicholas Gant, Cherie Blenkiron, Troy L Merry

Abstract

New findings: What is the central question of this study? Does short-term high-intensity interval training alter the composition of the microbiome and is this associated with exercise-induced improvements in cardiorespiratory fitness and insulin sensitivity? What is the main finding and its importance? Although high-intensity interval training increased insulin sensitivity and cardiovascular fitness, it did not alter the composition of the microbiome. This suggests that changes in the composition of the microbiome that occur with prolonged exercise training might be in response to changes in metabolic health rather than driving exercise training-induced adaptations.

Abstract: Regular exercise reduces the risk of metabolic diseases, and the composition of the gut microbiome has been associated with metabolic function. We investigated whether short-term high-intensity interval training (HIIT) altered the diversity and composition of the bacterial community and whether there were associations with markers of insulin sensitivity or aerobic fitness. Cardiorespiratory fitness ( V̇O2peak ) and body composition (dual energy X-ray absorptiometry scan) were assessed and faecal and fasted blood samples collected from 14 lean (fat mass 21 ± 2%, aged 29 ± 2 years) and 15 overweight (fat mass 33 ± 2%, aged 31 ± 2 years) men before and after 3 weeks of HIIT training (8-12 × 60 s cycle ergometer bouts at V̇O2peak power output interspersed by 75 s rest, three times per week). Gut microbiome composition was analysed by 16S rRNA gene amplicon sequencing. The HIIT significantly increased the aerobic fitness of both groups (P < 0.001) and improved markers of insulin sensitivity (lowered fasted insulin and HOMA-IR; P < 0.001) in the overweight group. Despite differences in the abundance of several bacterial taxa being evident between the lean and overweight group, HIIT did not affect the overall bacterial diversity or community structure (α-diversity or β-diversity). No associations were found between the top 50 most abundant bacterial genera and cardiorespiratory fitness markers; however, significant associations (P < 0.05) were observed between the abundance of the bacterial species Coprococcus_3, Blautia, Lachnospiraceae_ge and Dorea and insulin sensitivity markers in the overweight group. Our results suggest that short-term HIIT does not greatly impact the overall composition of the gut microbiome, but that certain microbiome genera are associated with insulin sensitivity markers that were improved by HIIT in overweight participants.

Keywords: diabetes; exercise; gut; insulin resistance; microbiome; microbiota; obesity.

© 2020 The Authors. Experimental Physiology © 2020 The Physiological Society.

References

REFERENCES

    1. Allen, J. M., Mailing, L. J., Niemiro, G. M., Moore, R., Cook, M. D., White, B. A., … Woods, J. A. (2018). Exercise alters gut microbiota composition and function in lean and obese humans. Medicine and Science in Sports and Exercise, 50, 747-757.
    1. Andrews, S. (2010). FastQC: A quality control tool for high throughput sequence data. Available at:
    1. Barton, W., Penney, N. C., Cronin, O., Garcia-Perez, I., Molloy, M. G., Holmes, E., … O'Sullivan, O. (2018). The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic level. Gut, 67, 625-633.
    1. Battaglia, T. (2019). btools: A suite of R function for all types of microbial diversity analyses. R package version 0.0.1. Available at:
    1. Bohm, A., Weigert, C., Staiger, H., & Haring, H. U. (2016). Exercise and diabetes: Relevance and causes for response variability. Endocrine, 51, 390-401.
    1. Borghouts, L. B., & Keizer, H. A. (2000). Exercise and insulin sensitivity: A review. International Journal of Sports Medicine, 21, 1-12.
    1. Bressa, C., Bailén-Andrino, M., Pérez-Santiago, J., González-Soltero, R., Pérez, M., Montalvo-Lominchar, M. G., … Larrosa, M. (2017). Differences in gut microbiota profile between women with active lifestyle and sedentary women. PLoS One, 12, e0171352.
    1. Burgomaster, K. A., Heigenhauser, G. J., & Gibala, M. J. (2006). Effect of short-term sprint interval training on human skeletal muscle carbohydrate metabolism during exercise and time-trial performance. Journal of Applied Physiology, 100, 2041-2047.
    1. Choi, J. J., Eum, S. Y., Rampersaud, E., Daunert, S., Abreu, M. T., & Toborek, M. (2013). Exercise attenuates PCB-induced changes in the mouse gut microbiome. Environmental Health Perspectives, 121, 725-730.
    1. Clarke, S. F., Murphy, E. F., O'Sullivan, O., Lucey, A. J., Humphreys, M., Hogan, A., … Cotter, P. D. (2014). Exercise and associated dietary extremes impact on gut microbial diversity. Gut, 63, 1913-1920.
    1. Costa, R. J. S., Snipe, R. M. J., Kitic, C. M., & Gibson, P. R. (2017). Systematic review: Exercise-induced gastrointestinal syndrome-implications for health and intestinal disease. Alimentary Pharmacology & Therapeutics, 46, 246-265.
    1. Cronin, O., Barton, W., Skuse, P., Penney, N. C., Garcia-Perez, I., Murphy, E. F., … Shanahan, F. (2018). A prospective metagenomic and metabolomic analysis of the impact of exercise and/or whey protein supplementation on the gut microbiome of sedentary adults. mSystems, 3, e00044-18.
    1. Estaki, M., Pither, J., Baumeister, P., Little, J. P., Gill, S. K., Ghosh, S., … Gibson, D. L. (2016). Cardiorespiratory fitness as a predictor of intestinal microbial diversity and distinct metagenomic functions. Microbiome, 4, 42.
    1. Evans, C. C., LePard, K. J., Kwak, J. W., Stancukas, M. C., Laskowski, S., Dougherty, J., … Ciancio, M. J. (2014). Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity. PLoS One, 9, e92193.
    1. Faith, J. J., Guruge, J. L., Charbonneau, M., Subramanian, S., Seedorf, H., Goodman, A. L., … Gordon, J. I. (2013). The long-term stability of the human gut microbiota. Science, 341, 1237439.
    1. Falony, G., Joossens, M., Vieira-Silva, S., Wang, J., Darzi, Y., Faust, K., … Raes, J. (2016). Population-level analysis of gut microbiome variation. Science, 352, 560-564.
    1. Fernandes, J., Su, W., Rahat-Rozenbloom, S., Wolever, T. M., & Comelli, E. M. (2014). Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutrition & Diabetes, 4, e121.
    1. Forslund, K., Hildebrand, F., Nielsen, T., Falony, G., Le Chatelier, E., Sunagawa, S., … Pedersen, O. (2015). Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature, 528, 262-266.
    1. Gibala, M. J., Little, J. P., Van Essen, M., Wilkin, G. P., Burgomaster, K. A., Safdar, A., … Tarnopolsky, M. A. (2006). Short-term sprint interval versus traditional endurance training: Similar initial adaptations in human skeletal muscle and exercise performance. The Journal of Physiology, 575, 901-911.
    1. Gondim, O. S., de Camargo, V. T. N., Gutierrez, F. A., Martins, P. F., Passos, M. E. P., Momesso, C. M., … Cury-Boaventura, M. F. (2015). Benefits of regular exercise on inflammatory and cardiovascular risk markers in normal weight, overweight and obese adults. PLoS One, 10, e0140596.
    1. Harrison, S. A., & Day, C. P. (2007). Benefits of lifestyle modification in NAFLD. Gut, 56, 1760-1769.
    1. Hartstra, A. V., Bouter, K. E., Backhed, F., & Nieuwdorp, M. (2015). Insights into the role of the microbiome in obesity and type 2 diabetes. Diabetes Care, 38, 159-165.
    1. Hedges, C. P., Woodhead, J. S. T., Wang, H. W., Mitchell, C. J., Cameron-Smith, D., Hickey, A. J. R., & Merry, T. L. (2019). Peripheral blood mononuclear cells do not reflect skeletal muscle mitochondrial function or adaptation to high-intensity interval training in healthy young men. Journal of Applied Physiology, 126, 454-461.
    1. Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., & Glöckner, F. O. (2013). Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Research, 41, e1.
    1. Koh, A., De Vadder, F., Kovatcheva-Datchary, P., & Backhed, F. (2016). From dietary fiber to host physiology: Short-chain fatty acids as key bacterial metabolites. Cell, 165, 1332-1345.
    1. Lahti, L., & Shetty, S., et al. (2017). Tools for microbiome analysis in R. Version 2.1.24. Retrieved from
    1. Lambert, J. E., Parnell, J. A., Eksteen, B., Raman, M., Bomhof, M. R., Rioux, K. P., … Reimer, R. A. (2015). Gut microbiota manipulation with prebiotics in patients with non-alcoholic fatty liver disease: A randomized controlled trial protocol. BMC Gastroenterology, 15, 169.
    1. Larsen, N., Vogensen, F. K., van den Berg, F. W., Nielsen, D. S., Andreasen, A. S., Pedersen, B. K., … Jakobsen, M. (2010). Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One, 5, e9085.
    1. Ley, R. E., Backhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005). Obesity alters gut microbial ecology. Proceedings of the National Academy of Sciences of the United States of America, 102, 11070-11075.
    1. Ley, R. E., Turnbaugh, P. J., Klein, S., & Gordon, J. I. (2006). Microbial ecology: Human gut microbes associated with obesity. Nature, 444, 1022-1023.
    1. Liu, Y., Wang, Y., Ni, Y., Cheung, C. K. Y., Lam, K. S. L., Wang, Y., … Xu, A. (2020). Gut microbiome fermentation determines the efficacy of exercise for diabetes prevention. Cell Metabolism, 31, 77-91.e75.
    1. Macfarlane, S., & Macfarlane, G. T. (2003). Regulation of short-chain fatty acid production. The Proceedings of the Nutrition Society, 62, 67-72.
    1. McMurdie, P. J., & Holmes, S. (2013). phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One, 8, e61217.
    1. Montero, D., & Lundby, C. (2017). Refuting the myth of non-response to exercise training: ‘non-responders’ do respond to higher dose of training. The Journal of Physiology, 595, 3377-3387.
    1. Munukka, E., Ahtiainen, J. P., Puigbó, P., Jalkanen, S., Pahkala, K., Keskitalo, A., … Pekkala, S. (2018). Six-week endurance exercise alters gut metagenome that is not reflected in systemic metabolism in over-weight women. Frontiers in Microbiology, 9, 2323.
    1. Onyszkiewicz, M., Jaworska, K., & Ufnal, M. (2020). Short chain fatty acids and methylamines produced by gut microbiota as mediators and markers in the circulatory system. Experimental Biology and Medicine (Maywood, N.J.), 245, 166-175.
    1. Petersen, L. M., Bautista, E. J., Nguyen, H., Hanson, B. M., Chen, L., Lek, S. H., … Weinstock, G. M. (2017). Community characteristics of the gut microbiomes of competitive cyclists. Microbiome, 5, 98.
    1. Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., … Glockner, F. O. (2013). The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research, 41, D590-596.
    1. Rognes, T., Flouri, T., Nichols, B., Quince, C., & Mahé, F. (2016). VSEARCH: A versatile open source tool for metagenomics. PeerJ, 4, e2584.
    1. Sam, C. H., Skeaff, S., & Skidmore, P. M. (2014). A comprehensive FFQ developed for use in New Zealand adults: Reliability and validity for nutrient intakes. Public Health Nutrition, 17, 287-296.
    1. Scheiman, J., Luber, J. M., Chavkin, T. A., MacDonald, T., Tung, A., Pham, L. D., … Kostic, A. D. (2019). Meta-omics analysis of elite athletes identifies a performance-enhancing microbe that functions via lactate metabolism. Nature Medicine, 25, 1104-1109.
    1. Schloss, P. D., Gevers, D., & Westcott, S. L. (2011). Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies. PLoS One, 6, e27310.
    1. Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., … Weber, C. F. (2009). Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75, 7537-7541.
    1. Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W. S., & Huttenhower, C. (2011). Metagenomic biomarker discovery and explanation. Genome Biology, 12, R60.
    1. Sekirov, I., Tam, N. M., Jogova, M., Robertson, M. L., Li, Y., Lupp, C., & Finlay, B. B. (2008). Antibiotic-induced perturbations of the intestinal microbiota alter host susceptibility to enteric infection. Infection and Immunity, 76, 4726-4736.
    1. Shin, N. R., Lee, J. C., Lee, H. Y., Kim, M. S., Whon, T. W., Lee, M. S., & Bae, J. W. (2014). An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice. Gut, 63, 727-735.
    1. Singh, R. K., Chang, H. W., Yan, D., Lee, K. M., Ucmak, D., Wong, K., … Liao, W. (2017). Influence of diet on the gut microbiome and implications for human health. Journal of Translational Medicine, 15, 73.
    1. R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Retrieved from
    1. Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006). An obesity-associated gut microbiome with increased capacity for energy harvest. Nature, 444, 1027-1031.
    1. Utzschneider, K. M., Kratz, M., Damman, C. J., & Hullar, M. (2016). Mechanisms linking the gut microbiome and glucose metabolism. Journal of Clinical Endocrinology and Metabolism, 101, 1445-1454.
    1. Warburton, D. E., Nicol, C. W., & Bredin, S. S. (2006). Health benefits of physical activity: The evidence. CMAJ: Canadian Medical Association Journal, 174, 801-809.
    1. Wei, T., & Simko, V. (2017). R package “corrplot”: Visualization of a correlation matrix (version 0.84). Retrieved from
    1. Welly, R. J., Liu, T. W., Zidon, T. M., Rowles, J. L., 3rd, Park, Y.-M., Smith, T. N., … Vieira-Potter, V. J. (2016). Comparison of diet versus exercise on metabolic function and gut microbiota in obese rats. Medicine and Science in Sports and Exercise, 48, 1688-1698.
    1. Wu, H., Esteve, E., Tremaroli, V., Khan, M. T., Caesar, R., Mannerås-Holm, L., … Bäckhed, F. (2017). Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nature Medicine, 23, 850-858.
    1. Zakrzewski, M., Proietti, C., Ellis, J. J., Hasan, S., Brion, M. J., Berger, B., & Krause, L. (2017). Calypso: A user-friendly web-server for mining and visualizing microbiome-environment interactions. Bioinformatics, 33, 782-783.

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