How are diet and exercise in bodybuilders related to gut microbiota and metabolites?

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A recent study published in Metabolites explored the dynamics of the diet-exercise-gut microbiome in male bodybuilders.

Study: Intersection of diet and exercise with gut microbiome and circulating metabolites in male bodybuilders: a pilot study. Image Credit: Goami/Shutterstock

Background

Optimal exercise and diet regimens are elusive because exercise/diet interventions have achieved variable results between individuals. This is seen in sports where diets have been designed to complement athletic performance and optimize energy availability. However, individual factors determine sports results. Lately, there has been growing interest in the role of the gut microbiota in individual athletic outcomes.

About the study

In the current study, researchers tested whether defined changes in diet and exercise in bodybuilders are associated with changes in gut microbiota and metabolites. Male participants aged 18 or older, preparing for a bodybuilding competition, were eligible for inclusion.

Five bodybuilders with longitudinal blood and stool samples matching an exercise and diet history were selected. They were on average 28 years old, 177cm tall, weighed 77.7kg and had 4.2 years of bodybuilding experience. The samples were obtained eight weeks (PRE8), one week (PRE1) before and four weeks (POST4) after the competition.

Participants abstained from alcohol, caffeine, and exercise 12 hours before blood collection. Hydrophilic metabolites were measured in a targeted metabolomic analysis using a liquid chromatography-mass spectrometry (LC-MS) system. Participants completed food and training diaries for a week prior to each assessment point.

Food, fluid, and supplement intake were documented in food diaries, while resistance and aerobic training were documented in training diaries. Body composition was estimated using a dual-energy X-ray absorptiometry (DXA) scanner. Stool samples were self-collected by participants in the week prior to each assessment time point. Total DNA was isolated from stool samples. The V4 region of 16S ribosomal RNA (rRNA) was used for microbiome profiling.

Changes in exercise and body composition at PRE1 and POST4 time points were compared to PRE8 as baseline. Differences in metabolite concentrations between time points were analyzed using the Kruskal-Wallis test. A sample from time point PRE1 was excluded from analysis due to an LC-MS quality control failure.

Results

All participants achieved the predicted changes in body composition during the preparation period (PRE8 – PRE1). There was a greater decrease in fat mass than lean mass. Two participants were more successful in preserving lean body mass than the others. One participant had the least (6.4%) reduction in fat mass. There was an increase in fat and lean mass after competition in all participants.

Physical training was reduced at PRE8 and POST4 time points compared to baseline, but training regimens varied among individuals. The increase in aerobic and resistance training from PRE8 to PRE1 in a single participant reflected better lean mass retention but did not correlate with the reduction in fat mass. Next, participants were assessed for dietary intake at food, macronutrient, and energy levels.

Energy intake was similar between participants and highest after competition in four participants. Larger declines in pre-competition energy intake (PRE8 to PRE1) corresponded to better reductions in fat mass but not to changes in lean mass. The pre-competition protein contribution to energy was above the upper limit of the acceptable macronutrient distribution range (AMDR), while the carbohydrate contribution was below the lower limit. Energy intake from fat was within AMDR limits.

The minimum recommended daily intake (MRDI) of protein exceeded in participants at all times. In addition, there was interindividual variability in the consumption of protein/amino acid supplements. Each participant exhibited a unique and dynamic gut microbiota. There was no significant association between samples from the same time point from different participants.

After the competition, a time lag was observed in the inter- and intra-sample microbial diversities. The microbial communities at time points PRE8 and PRE1 of each individual were more similar than the community of the POST4 sample. Additionally, four individuals exhibited low intra-sample diversity at the POST4 time point.

Among all participants, most microbes (55% to 85%) were Firmicutes. Serum metabolic profiles of participants were assessed under fasting and without exertion. Of the 127 metabolites, nine were found to be significant at some point. Participants had unique metabolite profiles throughout the assessment.

POST4 metabolite profiles were different from PRE8 or PRE1 profiles. Prior to competition, metabolite profiles were characterized by higher levels of malonate, guanidinoacetic acid, acetylcarnitine, α-ketobutyrate, and β-hydroxybutyrate. In contrast, post-competition profiles were characterized by increased saccharopine, choline, and NAD+ levels.

conclusion

Overall, all participants were successful in reducing fat mass and maintaining lean mass during the pre-competition period. Participants with the greatest decrease in dietary energy intake before competition showed greater reductions in fat mass. The microbial composition differed significantly between individuals. Despite interindividual differences in the composition of the gut microbiome, microbial diversity within and between samples could be predictably modulated by diet.

The results suggest that predicting the dynamics between gut microbiome, metabolites, diet, and exercise would be successful at the individual level rather than between individuals. Thus, physical training and personalized diets would be more beneficial than diet/exercise regimens based on generalized population patterns.

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