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Cited by 232Gut microbiota and healthProbiotics and Fermented FoodsGastrointestinal motility and disorders

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A Prospective Metagenomic and Metabolomic Analysis of the Impact of Exercise and/or Whey Protein Supplementation on the Gut Microbiome of Sedentary Adults

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Cronin, Owen, Barton, Wiley, Skuse, Peter, Penney, Nicholas C., Garcia-Perez, Isabel, Murphy, Eileen F., Woods, Trevor, Nugent, Helena, Fanning, Aine, Melgar, Silvia, Falvey, Eanna C., Holmes, Elaine, Cotter, Paul D., O’Sullivan, Orla, Molloy, Michael G., Shanahan, Fergus·2018·mSystems
DOI 10.1128/msystems.00044-18PMC PMC5915698
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Abstract

The gut microbiota of humans is a critical component of functional development and subsequent health. It is important to understand the lifestyle and dietary factors that affect the gut microbiome and what impact these factors may have. Animal studies suggest that exercise can directly affect the gut microbiota, and elite athletes demonstrate unique beneficial and diverse gut microbiome characteristics. These characteristics are associated with levels of protein consumption and levels of physical activity. The results of this study show that increasing the fitness levels of physically inactive humans leads to modest but detectable changes in gut microbiota characteristics. For the first time, we show that regular whey protein intake leads to significant alterations to the composition of the gut virome.

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Figures

FIG 1 Study design. The figure presents details of study recruitment and allocation of participants to intervention groups as follows: exercise-only group (E), exercise and protein supplementation group (EP), and whey protein supplementation-only group (P). Reasons for volunteer dropout and completion numbers are also outlined. See also Table S1.
FIG 1 Study design. The figure presents details of study recruitment and allocation of participants to intervention groups as follows: exercise-only group (E), exercise and protein supplementation group (EP), and whey protein supplementation-only group (P). Reasons for volunteer dropout and completion numbers are also outlined. See also Table S1.CC BY · PubMed Central
FIG 2 Alterations in cardiorespiratory fitness and body composition following exercise interventions, protein interventions, and combined interventions. (A) Peak aerobic capacity (VO2max) per kilogram of body weight as predicted using the Rockport 1-mi walk test was higher in both the E and EP groups following the intervention period, indicating improved levels of cardiorespiratory fitness. Within-group comparisons were tested using the Wilcoxon signed-rank test (P < 0.001). (B) Changes in percentages of body fat following the intervention period as measured using DEXA. Percent body fat reduction was significantly greater in the exercise-only group and in the exercise plus protein supplementation group compared to the protein-only group. (C) Absolute changes in body fat mass (in kilograms) following the intervention period demonstrated a significantly greater reduction in both the exercise and exercise plus protein supplementation groups. (D) Absolute change in lean tissue mass (kg), measured using a three-compartment model, indicating significantly greater lean mass accretion in the E and EP groups than in the P group. Error bars represent 95% confidence intervals. See also Tables S3 to S5.
FIG 2 Alterations in cardiorespiratory fitness and body composition following exercise interventions, protein interventions, and combined interventions. (A) Peak aerobic capacity (VO2max) per kilogram of body weight as predicted using the Rockport 1-mi walk test was higher in both the E and EP groups following the intervention period, indicating improved levels of cardiorespiratory fitness. Within-group comparisons were tested using the Wilcoxon signed-rank test (P < 0.001). (B) Changes in percentages of body fat following the intervention period as measured using DEXA. Percent body fat reduction was significantly greater in the exercise-only group and in the exercise plus protein supplementation group compared to the protein-only group. (C) Absolute changes in body fat mass (in kilograms) following the intervention period demonstrated a significantly greater reduction in both the exercise and exercise plus protein supplementation groups. (D) Absolute change in lean tissue mass (kg), measured using a three-compartment model, indicating significantly greater lean mass accretion in the E and EP groups than in the P group. Error bars represent 95% confidence intervals. See also Tables S3 to S5.CC BY · PubMed Central
FIG 3 Intervention effects on taxonomic and functional pathway diversity of the intestinal microbiome. (A to D) Percent change (Δ) of Shannon α-diversity H-index values following intervention. No significant variations were presented for taxonomic measurements (A to C) or metabolic pathways (D). (E to G) Pairwise statistical assessment of taxonomy α-diversity demonstrates equal data with respect to the presence of taxonomy between groups at baseline. EP1, combined exercise and protein supplementation group, week 0; EP2, combined exercise and protein supplementation group, week 8; E1, exercise-only group, week 0; E2, exercise-only group, week 8; P1, protein-only group, week 0; P2, protein-only group, week 8. (E) The diversity of Archaea was significantly altered after intervention within the P group (P < 0.05) and, similarly, was greater in the P group (P2) than in the EP group (EP2) (P < 0.01). (F) Postintervention bacterial diversity was greater in the EP group (EP2) in testing against the P group (P2) (P < 0.05). (G) Similar levels of virus diversity were presented in the protein supplementation groups (EP and P) following the intervention, with significantly lower diversity in the EP group than in the E group (P < 0.05). (H to O) Principal-coordinate analysis (PCoA) of relative abundance profiles for taxonomic and metabolic pathway constructions of the three groups demonstrates the influence of the interventions on the diversity of microbial populations. (H to K) Prior to intervention, group profiles of taxonomic and metabolic pathway diversity were not significantly differentiated. (L to O) Following intervention, a significant separation was identified between the groups for measures of (L) metabolic pathways (P = 0.054), (M) all detected species unsegregated by phylogeny (P < 0.001), (N) bacteria (P < 0.05), and (O) virus species (P < 0.001). Specific separations in diversity per intervention group are outlined further in Fig. 4 for virus species and Fig. S3 for all other comparisons. Statistical assessment of PCoA dissimilarity matrices was performed with the Adonis2 permutational multivariate analysis of variance (PERMANOVA) test. (H to O) Density plots were derived from kernel density estimates and scaled to a maximum estimated value of 1 and display concentrations of plotted data along the corresponding plot axis. P values were calculated for α-diversity comparisons using the Wilcoxon signed-rank test.
FIG 3 Intervention effects on taxonomic and functional pathway diversity of the intestinal microbiome. (A to D) Percent change (Δ) of Shannon α-diversity H-index values following intervention. No significant variations were presented for taxonomic measurements (A to C) or metabolic pathways (D). (E to G) Pairwise statistical assessment of taxonomy α-diversity demonstrates equal data with respect to the presence of taxonomy between groups at baseline. EP1, combined exercise and protein supplementation group, week 0; EP2, combined exercise and protein supplementation group, week 8; E1, exercise-only group, week 0; E2, exercise-only group, week 8; P1, protein-only group, week 0; P2, protein-only group, week 8. (E) The diversity of Archaea was significantly altered after intervention within the P group (P < 0.05) and, similarly, was greater in the P group (P2) than in the EP group (EP2) (P < 0.01). (F) Postintervention bacterial diversity was greater in the EP group (EP2) in testing against the P group (P2) (P < 0.05). (G) Similar levels of virus diversity were presented in the protein supplementation groups (EP and P) following the intervention, with significantly lower diversity in the EP group than in the E group (P < 0.05). (H to O) Principal-coordinate analysis (PCoA) of relative abundance profiles for taxonomic and metabolic pathway constructions of the three groups demonstrates the influence of the interventions on the diversity of microbial populations. (H to K) Prior to intervention, group profiles of taxonomic and metabolic pathway diversity were not significantly differentiated. (L to O) Following intervention, a significant separation was identified between the groups for measures of (L) metabolic pathways (P = 0.054), (M) all detected species unsegregated by phylogeny (P < 0.001), (N) bacteria (P < 0.05), and (O) virus species (P < 0.001). Specific separations in diversity per intervention group are outlined further in Fig. 4 for virus species and Fig. S3 for all other comparisons. Statistical assessment of PCoA dissimilarity matrices was performed with the Adonis2 permutational multivariate analysis of variance (PERMANOVA) test. (H to O) Density plots were derived from kernel density estimates and scaled to a maximum estimated value of 1 and display concentrations of plotted data along the corresponding plot axis. P values were calculated for α-diversity comparisons using the Wilcoxon signed-rank test.CC BY · PubMed Central
FIG 4 Pairwise analysis of detected virus taxonomy prior to and following intervention. (A to C) PCoA of virus species for each group, comparing virus profiles before and after the intervention period (time point 1 [TP1] [week 0] and time point 2 [TP2] [week 8], respectively). (A) The exercise-only group had virus diversity that was not significantly altered by intervention. (B and C) Diversity of viruses was significantly affected during the intervention period for both groups receiving protein supplementation (P < 0.001). The exercise plus protein supplementation group (B) and the protein-only group (C) demonstrated reduced variability of diversity following intervention. Results of pairwise analysis of additional taxonomic and metabolic pathway profiles are presented in Fig. S3. Statistical assessment of PCoA dissimilarity matrices was performed with the Adonis2 PERMANOVA test. (A to C) Density plots were derived from kernel density estimates and scaled to a maximum estimated value of 1 and display concentrations of plotted data along the corresponding plot axis.
FIG 4 Pairwise analysis of detected virus taxonomy prior to and following intervention. (A to C) PCoA of virus species for each group, comparing virus profiles before and after the intervention period (time point 1 [TP1] [week 0] and time point 2 [TP2] [week 8], respectively). (A) The exercise-only group had virus diversity that was not significantly altered by intervention. (B and C) Diversity of viruses was significantly affected during the intervention period for both groups receiving protein supplementation (P < 0.001). The exercise plus protein supplementation group (B) and the protein-only group (C) demonstrated reduced variability of diversity following intervention. Results of pairwise analysis of additional taxonomic and metabolic pathway profiles are presented in Fig. S3. Statistical assessment of PCoA dissimilarity matrices was performed with the Adonis2 PERMANOVA test. (A to C) Density plots were derived from kernel density estimates and scaled to a maximum estimated value of 1 and display concentrations of plotted data along the corresponding plot axis.CC BY · PubMed Central

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Authors
Cronin, O., Barton, W., Skuse, P., Penney, N. C., Garcia-Perez, I., Murphy, E. F., Woods, T., Nugent, H., Fanning, A., Melgar, S., Falvey, E. C., Holmes, E., Cotter, P. D., O’Sullivan, O., Molloy, M. G., & Shanahan, F.
Affiliations
  • National University of Ireland (IE)
  • Teagasc - The Irish Agriculture and Food Development Authority (IE)
  • Imperial College London (GB)
  • Section of Biomolecular Medicine, Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
  • Alimentary Health (Ireland) (IE)
  • Department of Medicine, National University of Ireland, Cork, Ireland
  • APC Microbiome Ireland, National University of Ireland, Cork, Ireland
Corresponding author
Cronin, Owen
ORCID
Venue
mSystems
Publisher
American Society for Microbiology
Published
2018-06-26
Volume
3
Issue
3
ISSN
2379-5077 (ISSN-L)
DOI
10.1128/msystems.00044-18
PMC
PMC5915698
OpenAlex
W2802946611
Cited by
232
References
75
Citations by year
2026: 24 · 2025: 24 · 2024: 36 · 2023: 33 · 2022: 35 · 2021: 31 · 2020: 23 · 2019: 22 · 2018: 4
FWCI
7.12
Type
journal article
Language
en
Open access
Licence
Locations
  • mSystems (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Cork Open Research Archive (University College Cork, Ireland) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Spiral (Imperial College London) (submittedVersion, other-oa)
  • T-Stór (Teagasc) (submittedVersion, cc-by-nc-sa)
Funders
  • Irish Centre for Arthritis Research and Education (N/A)
  • Science Foundation Ireland (SFI/12/RC/2273, SFI/11/PI/1137, SFI/13/SIRG/2160)
  • Diabetes Research & Wellness Foundation (Sutherland-Earl Clinical Research Fellowship 2015)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
  • Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
Keywords
gut microbiota, physical activity, whey protein supplementation, gut virome, sedentary adults, physical inactivity, microbiota composition, metabolomics

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