Chronic diseases are the most costly and preventable cause of death and disability in the United States (1). The gut microbiome (2), a broad term that refers to colonization of trillions of bacteria, fungi, archaea, protozoa, and viruses within the gastrointestinal tract (2) is increasingly recognized as having a pivotal role in health and disease (3). These microorganisms inhabit the human gut to form a complex community that interact with each other and the host (4–6). The gut microbiome is shaped by host genetics and numerous environmental factors, the latter plays a dominant role.
Dietary patterns, specific foods, and food constituents have a distinct influence on the gut microbiota (7). Western diets, which are low in fiber and high in fat and refined carbohydrates, have been associated with a permanent loss of bacteria (8), a reduction in community diversity (9,10), and “dysbiosis” of the gut microbiota (8). The composition of the microbiome can change rapidly (i.e., within 24 h) in response to short-term change in macronutrition content of the diet (11). In turn, long-term dietary changes, particularly in protein and animal fat intake, can lead to alterations in the structure and activity of gut bacterial communities (12).
Regular aerobic exercise has been reported to alter the gut microbiota in a variety of species including humans (13,14). However, whether exercise impacts the gut microbiota independent of habitual diet composition has been difficult to discern. Although there have been several reviews (14–17), to our knowledge there have been no systematic reviews evaluating the independent effects regular aerobic exercise on the gut microbiota across mammal models. Therefore, the objectives of this systematic review were to evaluate the available evidence on the effects of regular aerobic exercise on the gut microbiota and to summarize findings across species to inform future research.
Study inclusion and exclusion criteria
The population, intervention, comparison, outcome, and study (PICOS) model was used to develop eligibility criteria for studies returned via search terms entered into online research databases, and criteria are presented in Table 1. The review protocol described herein has been registered with PROSPERO (registration number: CRD42018075833). Briefly, this review included experimental studies, randomized controlled trials (RCT) and quasi-experimental designs, including observational and cohort studies. Systematic reviews, nonsystematic reviews, meta-analyses, narrative reviews, and textbook publications were not included. However, reviews and meta-analyses were retained, and reference lists were reviewed as an added measure to ensure search comprehensiveness. Studies whose primary objectives focused on changes to gut microbial composition (see Document, Supplemental Digital Content 1, Summary of terminology and operational definitions, http://links.lww.com/MSS/B387) associated with exercise or habitual physical activity (PA) were included.
We included all animal studies in mammals of all ages with the exception of those which focused on congenital conditions and those involving nutritional supplementation to enhance exercise performance. There were no further inclusion/exclusion criteria.
Database search strategies
Search strategies were conducted based upon the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (18). Databases used for this systematic review were: PubMed; PubMed Central; Medline via ProQuest; Web of Science; Cumulative Index of Nursing and Allied Health Literature (CINAHL) via EbscoHost; Science Direct via Elsevier; CAB Direct via CABI; and Health Source: Nursing/Academic Edition via EbscoHost. Search terms were also entered into ClinicalTrials.gov, Cochrane Library, and PROSPERO to ensure that trials with recently published data were included, and that no systematic reviews on this topic were previously published or registered. Databases were selected based upon both their coverage in biological and health sciences, and their coverage of national and international research. The search included articles published on or before January 5, 2018. In total, there were 36 search combinations, and Boolean search operators were used for each database. Search terms combinations are listed in Table 2, and refinement criteria across databases are presented in Table 3. An example of a complete search strategy for one database is presented in Table 4. After each search term combination was refined by title and abstract within a database, that search was downloaded and imported to EndNote X8.0.1 (19). The title and abstract of each imported article were appraised by a single reviewer against the eligibility criteria outlined above. All articles that had a title or abstract, which appeared to meet eligibility criteria, were retained for full text review.
Data extraction, data synthesis, and risk of bias
Data from articles retained for full-text review were independently extracted by a single reviewer (CM). Data extraction guidelines and recommendations published by The Centre for Reviews and Dissemination were used to prevent selection bias and to provide objective framework for inclusion/exclusion decisions (20). The information collected from retained articles included: author, year, aims, sample size, participant or subject characteristics, methods, reported gut microbiome composition measures, significant taxonomy findings, and declared funding source. Study results were classified primarily by species, and secondarily by health status. Risk of bias was evaluated independently by two reviewers (C.M. and B.D.) using the Cochrane Risk of Bias AUB Kq1 Tool for each article included (21). Bias levels are reported based upon the number of articles categorized into each level: high, low, or unclear, and are presented in Table 5.
An overview of search results and study flow throughout the initial identification, screening, eligibility, and inclusion process of the initial search is depicted in Figure 1. In total, 17,342 citations were identified from 11 electronic databases (Table 3) and 36 search term combinations (Table 2). The search totals were further refined by title and abstract and totaled 2,784 articles. Duplicates were then removed and a total of 1,057 articles remained for screening. After screening and full text review, 25 articles were eligible for inclusion. A summary of findings table was generated and included author, year, aim, sample size, participant or subject characteristics, methods, study design, gut microbiome composition measures, significant taxonomy findings, and funding source for included articles. These were categorized in descending order primarily by species and alphabetized secondarily publication year. Table data are provided in Supplemental Digital Content 2 (see Document, Supplemental Digital Content 2, study design information and alterations in gut microbial composition, http://links.lww.com/MSS/B388).
The risk of bias was unclear for all 25 articles. The primary reasons for unclear ratings for risk of bias included lack of sufficient details for random sequence generation, allocation concealment, blinding measures, and incomplete outcome data. Experimental design quality and reporting are issues that have been previously identified as problematic in animal research (22). Appropriate tool selection for appraisal of translational research is challenging because there are no validated tools available to critically appraise clinical trials across all models used (e.g., cell vs animal vs human) (23).
Nine studies included in this review focused on mouse models (24–32) and eight studies used rat models (33–40). The rodent lines studied are detailed in the supplemental content (see Document, Supplemental Digital Content 2, study design information and alterations in gut microbial composition, http://links.lww.com/MSS/B388). Collectively, nine studies implemented dietary comparison groups that included high-fat diets (25–27,29,33,35,40), casein-sucrose blends (36), and caloric restriction (39). Seven investigations used a standardized control diet (e.g., standard chow) (24,28,30–32,34,37) and one did not report dietary composition (38). The percentage of dietary fat (in seven studies) ranged from 25% to 60% fat, but the composition of dietary fat (e.g., % saturated fat) was not reported in any of the studies (25–27,29,33,35,40). The type of exercise was evaluated in two broad categories: voluntary and forced. Voluntary exercise (defined as unlimited access to a running wheel) was used in nine studies (24,25,27,31,35–37,39,40). Forced exercise (endurance or interval) was used in 10 studies (24,26,28–34,38), and only one of these 10 studies used interval training (38). All studies used treadmills and walking or running as the mode of exercise.
Two studies compared voluntary to forced exercise (24,31); the remaining studies compared their respective exercise intervention group with sedentary controls. Eleven investigations focused on the effect of exercise in exclusively healthy rodent models (24–27,29,31,33,35–37,39). Nine studies investigated the effect of exercise in models for disease (dysfunction or genetically predisposed) including metabolic syndrome (34), obesity (38,40), diet-induced obesity (25,26), type 2 diabetes (30), mitochondrial dysfunction (28), myocardial infarction (32), and hypertension (38), with and without healthy controls for comparison.
Significant shifts in relative abundance of a variety of taxa after exercise have been reported in multiple investigations [(24,26–30,32–35,37–40); see Document, Supplemental Digital Content 2, study design information and alterations in gut microbial composition, http://links.lww.com/MSS/B388]. The association between exercise and community evenness was reported in only three studies (24,33,37); no consistent impact of exercise was observed. There was no consistent impact of any form of exercise on community richness (24,31,33,37–40). However, in one study, the impact of exercise on community richness depended on the measure used and whether cecal or fecal contents were being evaluated (24). In addition, developmental stage (37) and/or aging (28) may impact whether exercise alters the gut microbiota.
Shifts in the ratio of Bacteroidetes:Firmicutes were variably reported across studies with reports of increases (26–28,37–39), decreases (29,34), and no change (24,34,35,40) after exercise. In the remaining studies changes in the ratio of Bacteroidetes:Firmicutes were not reported (25,30,32,33,36,39). The results of many (24,26,28,32,34,35,37–39), but not all (31,33,40) studies reported significant shifts in α-diversity; the remaining did not report α-diversity (25,27,29,30,36). β-diversity, or methods commonly used to assess β-diversity (e.g., weighted or unweighted UniFrac), were reported in 14 studies (24,26–29,31–35,37–40). However, there was no clear associations between exercise and β-diversity due, at least in part, to unclear and/or inconsistent reporting.
Exercise was associated with increases in the abundance of Firmicutes as well as diversification of sub-species within this phylum in eight studies involving healthy rodent models and models of disease (24–27,29,33,36–38). Conversely, exercise was associated with decreased abundance of Firmicutes in models of aging (28) and food restriction (39). The results of one study indicated that rodents selectively bred for high aerobic capacity had greater diversification when compared with their low aerobic capacity counterparts [see Document, Supplemental Digital Content 2, study design information and alterations in gut microbial composition, http://links.lww.com/MSS/B388; (35)]. In contrast, exercise was not consistently associated with diversification within Bacteroidetes, Actinobacteria, and Proteobacteria phyla in models of disease and dysfunction compared with healthy controls (25,26,28,30,32,33,40). Only two investigations compared the influences of forced versus voluntary exercise on gut microbial composition (24,31). Although one study found differential effects between voluntary and forced exercise (24), the other did not (31). In addition, exercise was associated with a shift in various bacterial groups independent of diet (25–27,29,33) and also appeared to lessened the impact of aging (28). Importantly many studies (25,26,40) but not all (33), found that exercise mitigated the effect of a high-fat diet on gut microbial composition and function. Lastly, four investigations reported only analyses of cecal contents (30,35,36,40), and one investigation reported analyses for both fecal and cecal contents (24). The remaining rodent studies all reported analyses for fecal contents. There were no apparent differences in abundance, diversity, evenness, and richness in studies that reported fecal contents compared with those that reported cecal contents.
Large animal studies
One investigation evaluated the influence of exercise on the gut microbiota during a weight loss protocol in canines (41). Two companion studies assessed the acute and long-term effects of forced exercise in equines (42,43). One study used dietary controls (41), and two studies did not (42,43). All studies used forced treadmill exercise (41–43). In canines, exercise was associated with a transient increase in several bacterial genera (41). However, evenness, richness, and the ratio of Bacteroidetes:Firmicutes were not reported in the canine study (41). There were no significant influence of exercise on α-diversity in canines; β-diversity was not reported (41). There was no change in relative abundance of any bacterial taxa, α-diversity, or β-diversity shifts in response to an acute bout of exercise in equines (43). However, exercise was associated with significant increases in Bacteriodetes, Proteobacteria, and Spirochaetes (42). The increases in Proteobacteria were transient (42). Evenness and richness were not reported in either of the equine studies (42,43). Numerous phyla-level changes associated with exercise were observed for Bacteroidetes, Firmicutes, Proteobacteria, and Spirochaetes (42).
Five studies in humans that assessed the association of exercise or PA and gut microbial composition were included for review (13,44–47). Four studies included healthy adults (13,44–46). One study included adults with obesity (13), another included breast cancer survivors (46), and a third study compared physically active well-managed type-1 diabetics with normoglycemic adults (47). Only one study in lean and obese adults implemented dietary controls for a 3-d period leading up to stool sample collection (13). The remaining investigations used 24-h recalls (47), food frequency questionnaires (44,45), or 3-d food intake records to account for dietary intake (46). Methods for exercise or PA quantification included: PA questionnaires (45), self-reported PA levels (46), or accelerometry (44), one did not specify how engagement in regular exercise or PA was determined (47), and only one trial used an exercise intervention and measured changes maximal oxygen consumption after a 6-wk intervention (13).
Relative abundance for a variety of taxa were reported (see Document, Supplemental Digital Content 2, study design information and alterations in gut microbial composition, http://links.lww.com/MSS/B388), and most reported taxa were higher in exercise-trained and physically active adults when compared with sedentary adults (13,44,45,47). Evenness was not reported in any investigations in humans. Only one study reported that richness was not associated with PA level (44). There were no significant shifts in the ratio of Bacteroidetes:Firmicutes in adults who habitually exercised when compared with sedentary individuals (44). The remaining studies in humans did not report this ratio (13,45–47). α-Diversity was greater in athletes when compared with controls (45), but no differences between exercise and control groups were observed in other studies (13,44,46,47). Cardiorespiratory fitness was associated with higher β-diversity in breast cancer survivors (46), but was not significantly different in physically active adults compared with their sedentary counterparts in another study (44). However, the observable changes in β-diversity associated with exercise training appeared to be dependent on obesity status and became more similar in obese compared with lean after the intervention (13). One study compared gut microbial composition in physically active normoglycemic adults with type 1 diabetics but no sedentary control groups were included (47) and did not report on β-diversity. Overall, generalizability of the studies were limited, given the wide variety of study methods, populations studied, and outcomes reported.
To our knowledge, this is the first systematic review of the translational evidence addressing whether exercise is associated with altered gut microbial community structure. Our review was limited to studies of human subjects, healthy mammals, and models of chronic disease. In rodents, there was no consistent association between exercise and the direction of change in specific phyla comprising the gut microbiome. However, exercise was associated with an increase in butyrate producing bacteria in multiple studies. There was no consistent impact of exercise on shaping the gut microbiota in the very small number of studies in large animals. The evidence supporting an association between exercise and altered gut microbial communities in humans was inconsistent and low quality. The inconsistency in indices used and outcome reporting precluded an objective risk of bias categorization.
In general, there was a lack of consistent evidence supporting a role for exercise in modifying specific taxonomic groups or indices of evenness, richness, or diversity among studies in rodents. Differences in study design, mode, intensity, and duration of exercise, dietary factors, health status of vivariums, index used for diversity assessment (i.e., Shannon vs Chao1 vs QIIME calculated, etc.) and inconsistency in reporting may have contributed to the discrepant findings among studies. Importantly, all of the studies in mice were performed on a C57B/6 background strain. In addition, none of the studies reported cage (animal housing conditions) or parents-of-origin (inheritance of genetic variation from the mother or father) effects. As such, these findings should be interpreted with these limitations considered. Nevertheless, there was a tendency for exercise to be associated with an increase butyrate producing bacteria which may be important given the role of these taxa in contributing to intestinal barrier function and colon health (48–50).
There were only three studies in large animals that were identified for inclusion in our review (41–43). In dogs, the addition of exercise to diet-induced weight loss had no discernible impact on gut microbial community structure (41). In contrast, exercise training in horses was associated with phyla level changes in Bacteriodetes, Proteobacteria, and Spirochaetes (42). Perhaps not surprisingly, an acute bout of exercise did not appear to exert an obvious influence on gut microbial community composition in horses (43).
The evidence linking exercise with alterations in gut microbial community structure in humans was, in general, low quality and inconsistent. Furthermore, it was difficult to disentangle the relative influence of exercise and diet on gut microbial communities in most studies (13,44–47). For example, Clarke et al. (45) reported that α-diversity and the proportion of numerous taxa were higher in professional rugby athletes compared with weight-matched sedentary control participants. However, the differences in gut microbial community structure in between groups could not be attributed solely to differences in exercise, (i.e., habitual dietary intake was also different between the groups). Importantly, only one RCT in humans was identified and included in our review. Allen et al. (13) reported that 6 wk of endurance exercise training was associated with an increase in β-diversity that was dependent on obesity status. β-diversity was lower in obese individuals at baseline but not different from lean individuals after exercise training (13). Several bacterial taxa and fecal short chain fatty acid concentrations were also increased after exercise training and returned toward baseline with return to a sedentary state (13). Collectively, this is a strong indication that gut microbial community changes are exerting a significant influence on gut metabolism and function. Importantly, dietary intake was controlled for 3 d before stool collection at baseline and follow-up in attempt to minimize the potential confound of differences in habitual dietary intake on gut microbial composition (13). Whether dietary intake should be controlled for a longer period of time of time preceding and during the exercise training period is unclear. This would seem to be an important goal of future studies in this area.
There are several aspects of our systematic review that should be emphasized. Our review is the first to be registered with PROSPERO to address this body of literature and using a comprehensive search strategy with a broad selection of national and international databases. The implementation of PRISMA standards assured that relevant articles were not missed and review methods were standardized and reproducible. The reporting in animal studies was variable and precluded objective categorization and interpretation for risk of bias (22). There were five studies in humans that were included in our review and only one was a RCT. In general, the risk of bias was unclear using the Cochrane AUB Kq1 Risk of Bias Assessment tool (21); insufficient detail was provided regarding random sequence generation, allocation concealment, and blinding related to performance and detection bias. Taken together, the quality of evidence for this body of literature was considered low.
Recent advances in DNA sequencing and computational technology has resulted in rapid growth in the number of studies exploring the role of exercise in shaping gut microbial community structure. Methods to improve taxonomic resolution have rapidly evolved and as a consequence the volume and detail of data generated in a single study has increased. Although these biotechnology advances are necessary for this field to move forward, comparisons across a decade of microbiome research is challenging given the inherently limited taxonomy data reported in earlier studies. The mouse microbiome has only been extensively characterized recently (48). The limited information available from earlier mouse studies reporting only cecal contents may be a source of discrepancy among studies (30,35,36,40). In addition, there was little overlap between the first reference database for the mouse gut microbiota with human gut microbial diversity (48).
There are several caveats that should be considered when attempting to translate and compare exercise and gut microbiota studies in mice and humans. First, there are significant difference in the anatomy and physiology of the mouse and human gastrointestinal tract (50). Second, a large fraction of bacterial taxa found in the mouse gut are not present in humans (50). Third, inconsistency in sample site in the mouse studies include our review further limit the translatability to humans. Finally, there has been a general failure in the ability to translate findings in mice, particularly in the C57B/6 mouse strain, to humans (51,52). As such, caution is warranted in extrapolating studies in this model to humans. Future studies in a broad spectrum of strains are needed.
There are several opportunities that could be considered to advance our understanding of the role of exercise in shaping the gut microbiota. First, future research should use standardized reporting methods to improve the quality of evidence and reduce risk of bias, particularly in animal studies (53,54). Second, energy intake and macronutrient composition (e.g., carbohydrate and fat composition) should be controlled and reported to minimize the potential confounding of habitual dietary intake on the gut microbial community composition. Third, the characteristics of exercise training (e.g., mode, frequency, intensity, and dose) need to be considered with translation in mind. All studies included focused exclusively on aerobic exercise/PA. Therefore, the impact of resistance training on the gut microbial composition is unknown. Finally, future research is needed on the influence of exercise on the function of specific taxa while taking advantage of functional genomic, metabolomics, and transcriptomic approaches (55,56).
The investigation of the gut microbiota in health and disease is a rapidly growing area of investigation. However, the impact of exercise on the gut microbiota structure and function is poorly understood due, at least in part, to the limited number and low quality of studies in this area. Although the available evidence would suggest that exercise appears to alter gut microbial composition, the metrics (e.g., abundance, evenness, richness, and diversity) were not consistently reported across studies (25,36,44,45,47). Exercise does appear to be associated with changes in gut microbial composition, an increase in butyrate-producing bacteria (e.g., Roseburia hominis, Faecalibacterium pausnitzii, and Ruminococcaceae) and increases in fecal butyrate concentrations in rodent models (24,25,27,35,37,39) and in humans (13) independent of diet. The overall quality of evidence in the studies in humans was low and the risk of bias was unclear. Importantly, the increase in butyrate-producing bacteria may be an important mechanism for improving intestinal and cardiometabolic health with exercise. Future studies with controlled dietary intake are needed to determine the influence of exercise on structure, function, and diversity of the human gut microbiome.
This project was internally supported by the department of Human Nutrition, Foods, and Exercise at Virginia Tech. CMM was supported in part by the Translational Obesity Research Interdisciplinary Graduate Education Program at Virginia Tech.
The authors have no conflicts of interest to declare. The results of this study do not constitute an endorsement by ACSM. All results are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
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