Abstract
The microorganisms in the gastrointestinal tract play a significant role in nutrient uptake, vitamin synthesis, energy harvest, inflammatory modulation, and host immune response, collectively contributing to human health. Important factors such as age, birth method, antibiotic use, and diet have been established as formative factors that shape the gut microbiota. Yet, less described is the role that exercise plays, particularly how associated factors and stressors, such as sport/exercise-specific diet, environment, and their interactions, may influence the gut microbiota. In particular, high-level athletes offer remarkable physiology and metabolism (including muscular strength/power, aerobic capacity, energy expenditure, and heat production) compared to sedentary individuals, and provide unique insight in gut microbiota research. In addition, the gut microbiota with its ability to harvest energy, modulate the immune system, and influence gastrointestinal health, likely plays an important role in athlete health, wellbeing, and sports performance. Therefore, understanding the mechanisms in which the gut microbiota could play in the role of influencing athletic performance is of considerable interest to athletes who work to improve their results in competition as well as reduce recovery time during training. Ultimately this research is expected to extend beyond athletics as understanding optimal fitness has applications for overall health and wellness in larger communities. Therefore, the purpose of this narrative review is to summarize current knowledge of the athletic gut microbiota and the factors that shape it. Exercise, associated dietary factors, and the athletic classification promote a more “health-associated” gut microbiota. Such features include a higher abundance of health-promoting bacterial species, increased microbial diversity, functional metabolic capacity, and microbial-associated metabolites, stimulation of bacterial abundance that can modulate mucosal immunity, and improved gastrointestinal barrier function.
Introduction
The human gut microbiota contains thousands of different bacterial taxa as well as various archaea, eukaryotic microbes and viruses, more than three million genes, and harbors an enormous metabolic capacity [Citation1, Citation2]. The microorganisms in the gastrointestinal (GI) tract play a role in nutrient uptake, vitamin synthesis, energy harvest, inflammatory modulation, and host immune response [Citation3, Citation4]. In turn, numerous intrinsic and extrinsic factors can affect the gut microbiota which results in a complex gut ecosystem that is highly dynamic and individual [Citation5, Citation6]. Important factors such as age, birth delivery route, antibiotic use, and diet can shape the gut microbiota [Citation7–Citation10]. The role that exercise plays, in particular the associated factors and stressors, such as sport/exercise-specific diet [Citation11], environment [Citation12], and their interactions, on the gut microbiota have been less well described. Athletes, although diverse as a population given the wide variety of different types of exercise/fitness/athletic training, competition, dietary practices and attributes, exemplify these factors on a generally consistent and long-term basis.
High-level athletes possess remarkable physiological and metabolic adaptations (including muscular strength/power, aerobic capacity, energy expenditure, and heat production) and provide unique insight in gut microbiome research. In addition, the gut microbiota with its ability to harvest energy, modulate the immune system, and influence mucosal and brain health, is likely to play a significant role in athlete health, wellbeing, and sports performance [Citation13–Citation15]. The microbiota has an indirect influence on various indices of exercise performance, recovery, and patterns of illness, such as signaling through myokines and other cytokines, modulating activation of the hypothalamic–pituitary–adrenal axis, and affecting performance-associated metabolic pathways [Citation13, Citation16–Citation18]. Understanding the various roles the gut microbiota plays in relation to athletic performance is of great interest to athletes seeking to improve competition outcomes as well as reduce recovery time from training. Such knowledge may be of general benefit to further understanding of microbial contributions to human health and disease. Current research reports a higher abundance of health-promoting bacterial species and increased microbial diversity in athletes [Citation13, Citation18, Citation19].
Given the increasing interest in exercise, associated dietary factors, and athletes as a population in relation to the gut microbiota, the purpose of this narrative review is to summarize current knowledge of the athletic gut microbiota and the factors that shape it. While differences likely exist among how the gut microbiota is affected by the different types of sport/athlete/fitness training regimens (e.g., resistance, interval, stretching/flexibility, endurance/aerobic, etc.), the primary aim is to provide a “state-of-the-art research” statement. Key topics covered include:
How the athletic/exercise-associated gut microbiota differs in comparison to other populations.
The effects of different types of exercise training on the gut microbiota.
The effects of an ‘athletic diet’ on the gut microbiota.
Influencing factors that shape the gut microbiota
Numerous factors such as age, genetics, drug use, stress, smoking, and diet can all affect the microbial composition of the gut, influencing a complex ecosystem that is highly dynamic and individual [Citation5–Citation7, Citation20]. For example, the manner in which we are born and raised can result in substantial differences in the composition of the gut microbiota. This outcome is related to the differences in exposure (or non-exposure) of bacteria in the birth canal during vaginal birth [Citation10], being bottle fed or breastfed [Citation21], living with a dog, cat, or close to farm animals [Citation22], the number of antibiotic treatments administered [Citation8], and environmental toxin exposure [Citation23]. From birth until the age of about 3 years, an individual assembles their core of resident microbiota primarily dominated by gram-positive Firmicutes and gram-negative Bacteroidetes phyla, and this subsequent make-up is as unique as a set of fingerprints [Citation24–Citation26]. The gut microbiota is also essential for processing dietary components and appears to have a major role in shaping the immune system [Citation27]. Not surprisingly, the role of the gut microbiota in determining host health and development of disease has been gaining clinical and community interest [Citation9]. Altered gut microbiota composition and/or function is linked to a growing number of conditions from metabolic disorders to some brain-related dysfunctions [Citation28, Citation29]. Individuals in a known disease state can have a significantly different gut microbiota composition compared with healthy individuals [Citation30]. A common observation is increased species diversity and/or richness in the gut microbiota of healthy individuals. Although new research suggests gene content/diversity in the gut may be a better predictor of physiological states [Citation31]. In addition, counterexamples exist as recent work links high gut microbial diversity with a longer colonic transit time and systemic circulation of potentially harmful protein degradation products [Citation32]. On a compositional level, it could be that low diversity indicates poorer health, while high diversity does not always guarantee improved health. Thus, information about compositional diversity alone is not sufficient to assess the health of the microbiota (and the host). Although, from an ecological perspective, functional diversity may be a key factor in allowing an ecosystem to continue operating properly [Citation33]. Resilience to both external and internal changes (with the ability to rapidly return to its baseline functional profile) is likely a key feature of a healthy gut microbiota’s ability to maintain itself [Citation34].
In individuals without disease, “health-associated” microbiota is preferred to the term “healthy microbiota”, since gut microbial composition alone cannot predict any state of health or disease according to currently available research [Citation30, Citation34]. It may turn out that many possible states of microbial composition are associated with health or indeed that a “health-associated” microbiota is more resilient and resistant to disruption [Citation35]. It is also important to keep in consideration that gut microbiome composition is quite stable over time [Citation36, Citation37]. For example, ~ 60% of microbiome composition was found to be stable up to a 5-year period in US adults [Citation38]. In addition, while species composition varies tremendously from person to person, there is substantial functional redundancy at the metabolic pathway level [Citation1, Citation2, Citation39]. Therefore, looking at metagenomic functions rather than taxonomy alone may provide for a better appreciation of the true gut microbiome metabolic activity and the impact of microbial functions on human physiology [Citation40, Citation41]. Physical activity has been an area of growing interest in gut microbiota research and appears to promote a health-associated microbial community and increased metabolic functional potential. This work includes identifying the impact that varying and diverse athletic and physical activity regimens exert on the gut microbiota.
Physical activity focused gut microbiota research is quite new and enabled by dramatic increases in scale and scope due to advances in DNA-sequencing technologies coupled with computational methods needed given the incredible information density of the microbiota [Citation42–Citation44]. Data are obtained predominantly from next-generation sequencing in three forms: A) ribosomal RNA (rRNA) gene sequence surveys that provide a view of microbiome membership, B) metagenomic data used to portray functional potential, and, C) metatranscriptomic data to describe active gene expression (for a review, readers are directed to [Citation42]). Currently, 16 rRNA gene surveys are the most commonly used as they are substantially more economical and therefore scale to larger projects [Citation44]. However, this technique is limited by short read lengths obtained, sequencing errors, and differences arising from the different regions chosen (e.g., hypervariable region V3 vs V4) [Citation45]. 16 rRNA sequencing also has limited resolution and lower sensitivity compared to whole-community shotgun metagenomic analysis, such as characterization down to the genus level with minimal capability of species-level detection [Citation46]. Therefore, shotgun metagenomics is displacing 16S rRNA amplicon analysis because of its expanded taxonomic range and strain-level resolution [Citation42].
Analyses used to interpret large data sets generated from these high-throughput sequencing techniques commonly include measures of biological diversity. Many of the studies included in this review measured alpha diversity which represents diversity within a sample. In calculating alpha diversity, various metrics (e.g., Shannon index, Chao1) consider the number of unique operational taxonomic units (OTUs), termed ‘richness’, and their relative abundance, termed ‘evenness’. Also often used is beta-diversity, a measurement of how different the communities are between samples. Beta-diversity metrics are quantitative (e.g., weighted UniFrac), when considering samples phylogeny, and qualitative (e.g., uniweighted UniFrac) when only evaluating the presence/absence of samples [Citation47]. In addition, other ‘omic’ techniques, such as metabolomics, are being integrated with these data to provide deeper insights into host metabolism and health. Metabolomics uses high throughput techniques to characterize and quantify small molecules in several biofluids (urine, serum, plasma, feces, saliva), revealing a unique metabolic signature [Citation48]. As a complement to sequencing-based approaches, the use of metabolomics (particularly from feces) is encouraged as it offers a ‘functional’ readout of the microbiome providing data on the metabolic interplay between the host, diet, exercise, and the gut microbiota [Citation49, Citation50].
While the aforementioned techniques have allowed for a rapid increase in gut microbiota research, the variation in microbial analysis across different studies can make comparing/contrasting study findings difficult. Indeed, variation in profiling techniques (e.g., sequencing strategy, platform, variable regions, sequencing depth, etc.) may act as a confounding variable resulting in divergent findings due entirely to laboratory techniques rather than treatment [Citation51]. Furthermore, many gut microbiota studies may be underpowered, and scientists may not be controlling for important confounding variables such as diet, gender, ethnicity, GI problems, antibiotics, etc. As the investigation of the athletic microbiota is a newer field of research, the intention of this review is to provide a broad overview of the current state of the literature. For future, more specific reviews, deeper discussions of methodological nuances are warranted.
The athlete/exercise-associated gut microbiota
Establishing consistent relationships across studies in physically active groups, such as athletes has been problematic. Beyond the obvious methodological differences such as sample preparation techniques, DNA sequencing, bioinformatics tools, and reference databases [Citation52–Citation55], there is also large variation across exercise/athletic regimens. Moreover, confounding factors including training history, level of physical fitness, training environment, and dietary intake all have the potential to affect study outcomes substantially, and make detecting differences due to exercise/athletic regimens on the gut microbiota difficult to ascertain. Therefore, when comparing these individuals within or across various exercise/athletic disciplines and classifications, these factors should be accounted for and reported by investigators. While the current body of this comparative-type research is mixed and more limited (see Table ), collectively it provides important insight and highlights key areas of future study.
Athletes/physically active individuals vs other populations
Several studies have investigated the difference in compositional gut microbiota between those physically active (including athletes) and a range of populations. While the above confounding factors are still relevant when interpreting these studies, such research provides an important comparator to the gut microbiota of these individuals. In an observational study, the gut microbiotas of sedentary and physically active premenopausal women were compared [Citation56]. Physical exercise was not related to differences in the microbiota diversity or richness (the total number of OTUs or species recorded); however, sedentary parameters (i.e., sedentary time and breaks) correlated negatively with microbiota richness. Further, quantitative polymerase chain reaction analysis revealed higher abundance of health-promoting bacterial species in active women, including Faecalibacterium prausnitzii, Roseburia hominis and Akkermansia muciniphila. In another cross-sectional study in females, Mörkl et al. [Citation57] compared the gut microbiota of anorexia nervosa inpatients to recreational athletes from a range of sports and overweight, obese, and normal weight controls. Microbiota diversity was markedly lower in anorexia nervosa patients and obese participants compared to other groups, while athletes showed the highest alpha diversity (species richness). Interestingly, total fat mass, serum lipids, C-reactive protein, depression scales, and smoking status were negatively associated (R 2 = − 0.012 to − 0.256, P < 0.05) with microbiota diversity. It is important to note that these associations are likely driven by lifestyle. While caution should be used in interpreting this data given the cross-sectional nature and inability to account for other potential influences, investigation of gut microbiota composition, diversity, and function should be useful in characterizing key elements of a healthy lifestyle.
Clarke et al. [Citation19] reported the gut microbiota of professional male rugby players was more diverse than healthy, non-athlete subjects matched for body mass index (BMI), age, and gender. Given the physical size of modern rugby players, two control groups were assessed; one matched for athlete size with a comparable (elevated) BMI (> 28 kg/m2) and a second reflecting the background age-matched and sex-matched population (lower BMI of < 25 kg/m2). Importantly, the alpha diversity of the elite athlete’s microbiota was higher than that of both control groups. Further, the athletes and those in the low BMI control group had higher proportions of the genus Akkermansia than the high BMI control group. Moreover, protein consumption was correlated positively (R = 0.24–0.43) with microbial diversity across all groups, indicating that greater protein intake was linked to higher levels of microbial diversity. There is a possibility that the increased diversity of the athlete’s gut microbiota was due, in part, to their higher protein intake. Barton et al. [Citation13] re-examined the microbiota in these participants using whole metagenome shotgun sequencing to provide deeper insight into taxonomic composition and metabolic potential. Differences in fecal microbiota between athletes and sedentary controls showed even greater separation at the metagenomic and metabolomic level than at the gut microbiota compositional level. Relative to controls athletes appear to have increases in metabolic pathways (e.g., amino acid and antibiotic biosynthesis and carbohydrate metabolism) and fecal metabolites (e.g., microbial produced short-chain fatty acids (SCFAs) including acetate, propionate, and butyrate) associated with enhanced fitness and overall health when compared to control groups [Citation13].
Athletes across different classifications and disciplines
To explore possible differences between levels of athletes, Petersen et al. [Citation18] investigated the gut microbiotas of 22 professional and 11 amateur competitive cyclists. Using metagenomic whole genome shotgun sequencing, no significant correlations were evident between the taxonomic clusters in professional or amateur cycling status. However, the amount of exercise (time reported exercising during the average week) was correlated positively with a greater abundance of the genus Prevotella (≥2.5%). Increased abundance of Prevotella, common in non-Western populations and associated with plant/fiber rich diets, was further positively correlated with several amino acid and carbohydrate metabolism pathways, including branched-chain amino acid (BCAA) metabolism. Using metatranscriptomic sequencing, there was increased abundance of Methanobrevibacter smithii transcripts in a number of the professional cyclists in comparison to amateur cyclists. Moreover, this archaeon had upregulation of genes involved in the production of methane and when methane metabolism was upregulated, there was similar upregulation of energy and carbohydrate metabolism pathways. Similar to Clarke et al. [Citation19], there was low abundance of Bacteroides in the athletes. In addition, Akkermansia was present in 30 out of 33 cyclists, with seven cyclists having relative abundances > 2% of this microbe in their metagenomic community. These outcomes may have been a reflection of higher fitness/metabolism of these athletes as increased proportions of Akkermansia are generally associated with a healthier metabolic profile [Citation59].
To examine the gut microbiota and metabolome across sport classification, O’Donovan and colleagues [Citation58] collected fecal and urine samples from 37 elite Irish athletes across 16 different sports (many of whom were participating in the 2016 Summer Olympics). To gain an understanding of the impact of dynamic (classified by estimated VO2max) versus static (classified by maximal voluntary contraction) components of exercise, each sport was classified into a broader sports classification group. Fecal samples were prepared for shotgun metagenomic sequencing and fecal and urine samples underwent metabolomic profiling. Athletes participating in sports with a high dynamic component were the most distinct compositionally (greater differences in proportions of species; see Table ), while athletes participating in sports with both a high dynamic and static component were the most functionally distinct (greater differences in functional potential). Fecal and urine derived metabolites also varied between classification including increased lactate (urine) in sports with a static component and creatinine (feces) in sports with a high dynamic and low static component. While increased lactate in the more static-based sports was not surprising, increased creatinine in more dynamic-based sports was. It may have been that the dynamic exercises in this athletic cohort involved substantial muscle turnover, potentially resulting in the increase in the production of creatinine. It is unclear what the causative factors of this finding and other reported differences in the gut microbiota and metabolome were due to the sampling variation, sample size and cross-sectional nature of this study. However, these differences were observed despite no significant variation in dietary intakes across athletes from different classifications; suggesting that variations in training loads and competition requirements contributed to these microbiome and metabolome-related patterns.
To investigate the long-term effects of a specific exercise type and athletes’ diets on gut microbiota, Jang et al. [Citation11] compared fecal microbiota characteristics, dietary intake, and body composition in 15 healthy sedentary men (as controls), 15 bodybuilders, and 15 distance runners. Exercise type was associated with athlete diet patterns (i.e., bodybuilders: high-protein, high-fat, and low-carbohydrate/dietary fiber diet; distance runners: low-carbohydrate and low-dietary fiber diet). While athlete type did not differ regarding gut microbiota alpha and beta diversity, it was significantly associated with the relative abundance of several bacteria. For instance, at the genus level, Faecalibacterium, Sutterella, Clostridium, Haemophilus, and Eisenbergiella were the highest, while Bifidobacterium and Parasutterella were the lowest in bodybuilders. At the species level, intestinal beneficial bacteria widely used as probiotics (Bifidobacterium adolescentis, Bifidobacterium longum, Lactobacillus sakei) and those producing short chain fatty acids (Blautia wexlerae, Eubacterium hallii) were the lowest in bodybuilders and the highest in controls. In distance runners, protein intake was negatively correlated with diversity (Shannon index R = − 0.63; P = 0.01) and in bodybuilders, fat intake was negatively correlated with Bifidobacteria (R = − 0.52; P = 0.05). These differences may relate to the nutrition status of athletes in the study (i.e. insufficient carbohydrate and dietary fiber; higher fat).
Summary of the athlete/exercise-associated gut microbiota
From the limited evidence, it appears that athletes harbor an increased abundance of functional pathways within the microbiome that are exploited by the host for potential health benefits, as well as carbohydrate degradation and secondary metabolite metabolism compared to control groups [Citation60]. While difficult to isolate, the influence of dietary intake on many of these differences is likely and needs to be considered in the context of this research. Furthermore, athletes have an enriched profile of SCFAs, previously associated with numerous health benefits and a lean phenotype [Citation61–Citation63]. This profile along with an increased number of detected SCFA pathways in athletes is conducive to an enhanced rate of SCFA production [Citation64]. While evidence is currently limited, results from Clarke et al. [Citation19] and Petersen et al. [Citation18] suggest A. muciniphilia may be more present in athletes than non-athletes. A. muciniphilia is a mucin-degrading bacterium that resides in the nutrient-rich mucus layer of the gut that appears to be associated with positive metabolic function [Citation59]. A. muciniphilia levels are decreased in obese and type 2 diabetic mice, and treatment with these bacteria reversed high-fat diet-induced metabolic disorders, including fat mass gain, metabolic endotoxemia, adipose tissue inflammation, and insulin resistance [Citation65]. A. muciniphilia can control mucus production by the host and restore mucus layer thickness in mice with high-fat diet-induced obesity, thereby reducing gut permeability. This outcome led to the hypothesis that A. muciniphilia engages in cross-talk with the intestinal epithelium to control inflammation and gut barrier function [Citation65]. A. muciniphilia has also been found to be enriched in mice fed a ketogenic diet, exhibiting gut-brain functions including conferring seizure protection in two preclinical models for refractory epilepsy [Citation66]. While the role of A. muciniphila is less certain in humans, it is depleted in individuals with several metabolic and inflammatory disorders. For example, of subjects undergoing dietary calorie restriction treatment for obesity, those with higher levels of these bacteria exhibited the best metabolic status and clinical outcomes [Citation59]. Future research in athletes should continue to investigate the role A. muciniphilia plays in the gut microbiota and its functional impact on metabolism.
In relation to obesity, some athletes who may be defined as physically active may not necessarily be healthier based on BMI [Citation67]. For example, Rugby or American football players commonly have large amounts of lean mass, and many will have relatively healthy percent body fat levels, typically 12–20%, so BMI is considered to be a poor measure of obesity status in these athletic cohorts. While Clarke et al. [Citation19] and Barton et al. [Citation13] compared the gut microbiome of athletes to matched controls considered overweight by BMI, future work should also investigate this comparison at the obese classification. Findings from such research could provide important data in connection with the pathogenesis of obesity and the gut microbiota. One leading theory on the pathogenesis of obesity emphasizes a close link between the metabolic and immune systems via the gut microbiota [Citation68]. This body of work suggests that increased intestinal permeability from high-fat / high sugar diets allows bacterial lipopolysaccharide (LPS), an outer membrane component of gram-negative bacteria linked with induction of inflammation, from the gut microbiota to translocate into the systemic circulation, resulting in systemic endotoxemia. Activation of pro-inflammatory cytokines is observed, leading to the chronic low-grade inflammation often implicated in obesity [Citation69]. In contrast, athletes have been noted to have lower levels of circulating LPS compared to sedentary individuals [Citation70]. These findings support of the notion that other factors beyond BMI levels should be considered when assessing any relationship between metabolic health, obesity and the microbiome status of competitive athletes.
Barton et al. [Citation13] speculated that the athlete gut microbiome may possess a functional capacity primed for tissue repair and a greater ability to harness energy from the diet with increased capacity for carbohydrate metabolism, cell structure, and nucleotide biosynthesis. This assertion reflects the significant energy demands and tissue adaptation that occurs during intense exercise and elite sport. It appears that being physically active is another important factor in the relationship between the microbiota and host metabolism. Intervention-based studies to delineate this relationship will be important and provide further insights into optimal therapies to influence the gut microbiota, and its relationship with health and disease as well as athletic performance.
The effect of exercise on the gut microbiota
Animal research
Few studies have focused on the impact that voluntary exercise has on gut microbiota and, to date, all but seven of these experimental studies utilized murine models [Citation17, Citation71]. These preliminary studies indicate that exercise influences the composition of the gut microbiota community. Matsumoto et al. [Citation72] reported that regular running exercise in rats was related to an increase in butyrate-producing bacteria in the microbiota composition along with an increase of butyrate concentration. Other animal studies demonstrated that daily wheel running exercise may improve some aspects of unhealthy states, such as diet-induced obesity, diabetes, and toxicity, by impacting the gut microbial composition in mice [Citation73–Citation75]. These effects included altering the ratio between the dominant phyla Firmicutes and Bacteroidetes, which has been found to be correlated with obesity and other diseases [Citation76–Citation78]. Animal and human data have reported that the Firmicutes/Bacteroidetes ratio is higher (i.e., increased Firmicutes and/or decreased Bacteroidetes) in obese people compared to lean people [Citation79–Citation82]. However, this is not always the same between studies [Citation83, Citation84] and may be an oversimplification of phylum-level patterns in relation to host health. Further, mechanisms by which specific members of the microbiota, such as Firmicutes and Bacteroidetes, can affect human phenotypes remain to be fully elucidated [Citation85]. Therefore, changes in phyla ratios should be interpreted with caution.
Amongst the exercise studies in animals there was little agreement regarding what taxa are influenced by chronic exercise. Other than a positive correlation between exercise and Lactobacillus [Citation73, Citation86, Citation87], there are no other taxa that consistently increase in relative abundance in regularly exercised mice or rats. In particular, Choi et al. [Citation73] reported that, in comparison to a sedentary control, mice with running wheel exercise had higher phylum Firmicutes but fewer phyla Tenericutes and Bacteroidetes, which attenuated changes in gut microbiota induced by oral exposure to the environmental toxin, polychlorinated biphenyls. Lambert et al. [Citation75] described that exercised mice presented a greater abundance of Firmicutes species and lower Bacteroides/Prevotella genera compared with sedentary mice. In contrast, Evans et al. [Citation74] concluded that exercise increased Bacteroidetes, while it decreased Firmicutes in mice, implying that exercise plays an important role in prevention of diet-induced obesity producing a microbial composition similar to lean mice. The changes in the Firmicutes/Bacteroidetes ratio exerted by exercise were inversely proportional to the distance traveled by animals [Citation74]. Campbell et al. [Citation88] asserted that exercised mice have bacteria related to Faecalibacterium prausnitzii which may protect the digestive tract by producing butyrate and lowering the oxygen tension in the lumen by a flavin/thiol electron shuttle. Briefly, the health-related effects of butyrate are associated with anti-inflammatory properties, direct feeding of colonocytes, and an impact on satiety [Citation64]. Notably, butyrate, along with propionate and acetate, provides ~ 10% of the daily caloric requirements in humans who consume high (~ 60 g/day) amounts of dietary fiber [Citation64]. The bacterial abundance of Clostridiaceae and Bacteroidaceae families and Ruminoccocus genus were negatively associated with blood lactate levels in exercised animals, whereas a positive association was reported for Oscillospira genus [Citation86].
Moreover, it seems that the changes exerted by physical exercise depend on the physiological state of the individual. For example, regular forced exercise differentially affected microbiota richness whether they were obese-hypertensive or normal rats [Citation86]. Alterations to the microbiota exerted by exercise in rats following a high-fat diet were different to rats on a normal diet [Citation89], as well as the alterations produced in diabetic mice were different to their control counterparts [Citation75]. Collectively, these findings indicate that modulation of the microbiota by chronic exercise depends not only on the physiological state of the individual, but also on the diet. Moreover, another significant difference between forced vs. voluntary exercise in animals is exercise volume. This is recapitulated in human cyclist data [Citation18] and requires further investigation in animal models. Finally, it has been observed that exercise induces more effective changes in the microbiota in juvenile rats than in adult rats [Citation90]. A common finding in these murine studies examining the effects of exercise training on the gut microbiome, is an increase in alpha diversity [Citation17]. Several other studies using murine-based models also demonstrated increased alpha diversity in animals that exercised vs. those that were sedentary [Citation73, Citation74, Citation86, Citation87].
Cross-sectional research in humans
In healthy individuals, Estaki et al. [Citation14] reported higher cardiorespiratory fitness (as measured by peak or maximum oxygen uptake, VO2peak or VO2max) correlated with increases in both microbial diversity and fecal butyrate (see Table ). Also identified was a core set of gene related functions rather than a core set of bacterial taxa in individuals with high levels of fitness [Citation14]. Further, ~ 20% of the variation in gut bacterial alpha diversity could be explained by VO2peak alone; in fact, VO2peak stood as the only variable that contributed significantly to increased alpha diversity. The primary findings indicate that cardiorespiratory fitness is a good predictor of gut microbial diversity in healthy humans, outperforming several other variables including sex, age, BMI, and multiple dietary components. Additionally, enhanced bacterial diversity was correlated positively with certain microbial metabolic functions including chemotaxis, motility, and fatty acid biosynthesis. As VO2peak was not significantly associated with variation in community composition, this result suggests function may be a better predictor than species richness, as noted previously. This study also confirmed results by Matsumoto and colleagues [Citation72] who initially reported that exercising rats exhibited a positive correlation between high-cardiorespiratory fitness and an increase in the SCFA, butyrate. Increases in fecal butyrate were observed when relative abundances of Clostridiales, Roseburia, Lachnospiraceae, and Erysipelotrichaceae were increased [Citation14]. These SCFAs are derived from fermentation of undigested plant fiber by the microbiota in the large intestine.
Functional categories most strongly correlated with VO2peak were related to bacterial motility (bacterial motility proteins, flagella assembly, and bacterial chemotaxis), sporulation, and to a lesser extent the two-component system known to enable bacterial communities to sense and respond to environmental factors [Citation14]. One possible mechanism behind these associations may be derived from the observation that butyrate, which was more abundant among participants with higher cardiorespiratory fitness, can modulate neutrophil chemotaxis [Citation91]. VO2peak was inversely correlated with LPS biosynthesis and LPS biosynthesis proteins which were elevated among less fit participants. LPS is a major component of the cell wall of gram-negative bacteria and considered an endotoxin when present in the blood. By binding to extracellular toll-like receptor 4 located on many cell types, LPS elicits strong inflammatory responses that may be detrimental to the host. Continuous low-level translocation of LPS into circulation can induce chronic low-level inflammatory states associated with development of obesity and other metabolic syndromes [Citation92]. These inflammatory states are thought to be derived to some extent from inflammatory responses to blood LPS which is elevated in sedentary humans [Citation70]. Exercise training attenuates inflammation in part by reducing elevated blood LPS [Citation70]. The inverse relationship between VO2peak and LPS biosynthesis pathways implies a beneficial consequence of increased physical activity which may result in decreased LPS biosynthesis.
Durk et al. [Citation93] also explored the relationship between cardiorespiratory fitness and relative gut microbiota composition in healthy young adults showing that Firmicutes/Bacteroidetes ratio was significantly positively correlated to VO2max. While no other relationships between the gut microbiota and fitness, nutritional intake, or anthropometric variables were found, VO2max accounted for ~ 22% of the variance of an individual’s relative gut bacteria (as determined by the Firmicutes/Bacteroidetes ratio). In a cross-sectional study in premenopausal women, cardiorespiratory fitness was associated with gut microbiota composition, independent of age and carbohydrate or fat intake [Citation94]. Participants with low VO2max had lower Bacteroides, but higher Eubacterium rectale-Clostridium coccoides than the high VO2max group. Aerobic capacity was inversely associated with Eubacterium rectale-Clostridium coccoides but not with other bacteria. After adjusting for age and dietary intake, all significant associations remained.
In professional rugby players, who had a unique dietary pattern (higher energy intake and quantities of protein, fat, carbohydrates, sugar and saturated fat per day, with protein accounting for considerably more of the total energy) and a high level of physical activity, there was a higher diversity of gut microbiota compared with controls [Citation19]. However, it was unclear if this effect was due to exercise, a high-protein diet, a combination of these two factors, or other factors [Citation19].
Acute exercise effects on the human gut microbiota
To investigate the effect of an acute exercise bout in athletes, Zhao et al. [Citation20] examined the fecal metabolites and microbiota in 20 amateur runners before and after a half-marathon race using metabolomics and 16S rRNA sequencing analysis. According to the alpha diversity analysis, there were few differences in diversity, nevertheless, abundances of certain microbiota members showed differences before and after running. At the phylum level, Lentisphaerae and Acidobacteria, whose functions in the human gut are unknown, were detected after running. At the species level there was a marked increase in the families Coriobacteriaceae and Succinivibrionaceae. Coriobacteriaceae (phylum Actinobacteria) is involved in metabolism of bile salts and steroid hormones as well as activation of dietary polyphenols in the human gut [Citation95]. Coriobacteriaceae was correlated positively with 15 metabolites, indicating that metabolism of Coriobacteriaceae may be a potential mechanism underlying the role of exercise in preventing disease and improving health outcomes. These increased metabolites indicate a microbiota-derived metabolism was promoted by running. At the genus level, half-marathon running reduced the abundance of fecal Ezakiella, Romboutsia, and Actinobacillus, but increased the abundance of Coprococcus and Ruminococcus bicirculans. Actinobacillus species are purportedly responsible for several distinct animal diseases, such as actinomycosis in cattle, potent septicemia in the neonatal foal, and human periodontal disease [Citation96]. Thus, inhibition of this potential pathogen indicated an anti-inflammatory effect of exercise. Interestingly, the pentose phosphate pathway, a metabolic pathway parallel to glycolysis and involving the oxidation of glucose, was the most enriched pathway after a half-marathon run. These findings highlight a microbiota-derived mechanism for the health-promoting benefits of exercise.
In a unique study by Scheiman et al. [Citation16], athletes who were to run the Boston Marathon were recruited, along with a set of sedentary controls to identify gut bacteria associated with athletic performance and recovery states. 16S ribosomal DNA sequencing was conducted on daily fecal samples collected up to 1 week before and 1 week after the marathon event. The relative abundance of the bacterial genus Veillonella increased after the marathon and was the most differentially abundant microbial feature between the pre- and post-exercise states. Additionally, Veillonella was more prevalent among runners compared to non-runners. Veillonella species metabolize lactate into the SCFA acetate and propionate via the methylmalonyl-CoA pathway [Citation97]. To replicate these results in a second experiment and an additional cohort of human athletes, Scheiman and colleagues [Citation16] performed shotgun metagenomic sequencing on stool samples from ultramarathoners and Olympic trial rowers both before and after an exercise bout. Similar findings were reproduced as relative taxonomic abundances Veillonella were increased post-exercise. In addition, the Veillonella methylmalonyl-CoA pathway was overrepresented in the metagenomic samples post-exercise across the cohort. Given the limited prevalence of the methylmalonyl-CoA pathway across lactate-utilizing microbes, this enrichment post-exercise may implicate Veillonella in causing functional changes in the metabolic repertoire of the gut microbiota. It seems that the genus Veillonella is enriched in athletes after exercise and the metabolic pathway that Veillonella species utilize for lactate metabolism is also enriched. Gut colonization of Veillonella may augment the Cori cycle by providing an alternative lactate-processing method whereby systemic lactate is converted into SCFAs that re-enter the circulation. Higher levels of lactic acid in athletes’ GI tract favor the growth of this genus and these bacteria may in turn produce a compound that could aid performance.
In a third set of experiments, Scheiman et al. [Citation16] isolated a strain of Veillonella atypica from a stool sample of one of the aforementioned marathon runners and inoculated mice. In a pre-clinical crossover trial, Veillonella inoculated mice had a 13% improvement in time to exhaustion running tests as well as significant reductions in inflammatory cytokines post exercise compared to control. They also more effectively converted lactate to the SCFAs propionate. Importantly, Scheiman et al. [Citation16] found systemic lactate in these animals was able to cross the gut barrier into the lumen, making it available as a substrate for microbial SCFA conversion. Taken together, these experiments revealed that V. atypica improved run time via its metabolic conversion of exercise-induced lactate into propionate, thereby identifying a natural, microbiome-encoded enzymatic process that enhances athletic performance. While other studies reported butyrate as a prominent feature of the athletic microbiota [Citation13, Citation14, Citation72, Citation88, Citation98, Citation99], this research implicated propionate as another significant beneficial SCFA. Moreover, these preclinical, proof-of-concept experiments displayed for the first time that beneficial microbes from athletes can be effectively transferred to enhance performance. While performed in animal model, this research is notable as it took an important step from correlative to causal function, implicating athlete microbiomes for broader human health and performance applications.
Chronic exercise effects on the human gut microbiota
In a longitudinal research design, Allen et al. [Citation98] reported for the first time that exercise training can modulate the composition and metabolic capacity of the human gut microbiota in previously sedentary individuals. Lean and obese subjects underwent 6 weeks of endurance training with diet controlled, followed by a 6-week washout period [Citation98]. Exercise-induced modulations of the gut microbiota and SCFA were strongly associated with changes in body composition in lean participants and VO2max in obese participants, independent of diet. After the washout period, exercise-induced changes in the microbiota were largely reversed once exercise training ceased. This study supports the notion that gut microbiota composition is linked to exercise status and that exercised-induced changes may be temporary and require continual stimulus [Citation100]. Of note, the exercise induced shifts in SCFA-producing taxa (Faecalibacterium species [spp.] and Lachnospira spp.) and genetic machinery (butyrate-regulating gene, BCoAT) were more substantial in lean versus obese participants. This connection is also supported by the observed shifts in metabolic capacity of the gut microbiota which may be transient and likely dependent on repeated exercise stimuli.
Taniguchi et al. [Citation101] evaluated whether endurance exercise modulates the gut microbiota in elderly subjects, and whether these changes are associated with host cardiometabolic phenotypes. In a randomized crossover trial, 33 elderly Japanese men participated in a 5-week endurance exercise program. 16S rRNA gene-based metagenomic analyses revealed that the effect of endurance exercise on gut microbiota diversity was not greater than interindividual differences, whereas changes in alpha diversity indices during intervention were negatively correlated with changes in systolic and diastolic blood pressure, especially during exercise. Microbial composition analyses showed that the relative abundance of Clostridioides difficile decreased, whereas that of Oscillospira increased during exercise compared to the control period. The changes in these taxa were correlated with the changes in several cardiometabolic risk factors. These findings indicate that the changes in gut microbiota were associated with cardiometabolic risk factors, such as systolic and diastolic blood pressure. It appears microbial SCFAs influence blood pressure by interacting with host SCFA receptors [Citation102]. In another study with elderly subjects, Morita et al. [Citation103] examined the effect of a 12-week exercise intervention on the composition of intestinal microbiota in healthy women. The relative abundance of intestinal Bacteroides increased in subjects that completed aerobic exercise. In addition, the increases in Bacteroides following the exercise intervention were positively associated with increases in a 6-min walk test. It is widely accepted that lower levels of Bacteroides are associated with the higher prevalence of obesity and metabolic syndrome and that Bacteroides species may help in suppressing metabolic dysfunction [Citation79, Citation104]. However, Bacteroides sometimes correlate with higher BMI and a Westernized diet [Citation105]; therefore, the increased relative abundance observed after the 12-week exercise intervention may be due to its ability to shift substrates compared to other taxa that more reproducibly decline with a high-fat diet (i.e., Bifidobacteria).
More recently, Liu et al. [Citation106] conducted a well-controlled exercise intervention in 39 prediabetic, medication-naive overweight men with a comprehensive metagenomics and metabolomics analysis. Subjects maintained their normal dietary routine and were randomized into either a control group (no exercise; n = 19) or a supervised high-intensity exercise program (n = 20) consisting of 70 min combined aerobic and resistance interval training 3 times per week. Despite the overall metabolic benefits of the intervention, ~ 30% of subjects responded poorly to exercise in terms of improvement in glycemic control and insulin sensitivity. Those that did respond showed a remarkable decrease in fasting insulin and Homeostatic Model Assessment of Insulin Resistance index values (− 42.70% and − 49.60%, respectively). Upon investigating the gut microbiota there was a clear segregation in compositional and functional changes between exercise responders and non-responders, accompanied by distinct alterations in microbial metabolites. Specifically. responders displayed greater gene expression of functional pathways generating SCFAs and breaking down BCAAs. These may have been related to the positive findings in glucose metabolism as the rise of BCAA has been associated with insulin resistance [Citation107]. There was also a trend in changes of the metabolites of amino-acid catabolism (BCAAs and aromatic amino acids) and carbohydrate fermentation that was consistent with the altered patterns of genes encoding for associated metabolic enzymes. Conversely the microbial profiles of non-responders after the exercise intervention shared more similarity with those of the sedentary controls, suggesting a maladaptation of gut microbiota in these individuals. Similar to the findings from Barton et al. [Citation13] in professional rugby athletes, pathways involved in DNA replication and amino acid metabolism were preferentially enhanced in responders. Moreover, genes related to glycan biosynthesis and lipid metabolism were elevated in responders. Although there was no obvious difference in baseline microbial structures between responders and non-responders, Liu and colleagues were able to establish a model based on a machine-learning algorithm from baseline microbiome signatures which accurately predicted the exercise outcomes with respect to glycemic control and insulin sensitivity. This raised the possibility of screening for individuals with high likelihood of exercise resistance using gut microbiota, so that personalized adjustments can be implemented in time to maximize the efficacy of exercise intervention.
To examine the potential causal relationship between the differentially shaped microbiotas, Liu et al. [Citation106] then transplanted conventional antibiotic-treated mice with the microbiota from two responders and two non-responders from the above experiment. A substantial improvement in mice gavaged with microbiota from responders was mimicked in glycemic control and insulin sensitivity, in contrast to the lack of change in mice colonized with microbiota from non-responders. Together, the results from both the human and animal studies indicate that exercise may impose a differential impact on the composition and function of the gut microbiota across individuals. While future research is warranted, this study raised the possibility that the makeup of the gut microbiota may be a determiner for the efficacy of exercise (i.e., responders vs non-responders) and that targeting the gut microbiota could maximize the benefit of exercise. It may have been that exercise amplified subtle differences of the gut microbiota at baseline by remodeling the intestinal microenvironment (such as inflammatory and oxidative status and local immunity) critical for microbial growth and interaction, which ultimately lead to a divergent response of glycemic control to exercise intervention. Finally, these findings further reinforce the notion that the functional capacity of gut microbiota, as assessed by metagenomics and metabolomics, can be significantly altered without major shifts in its community structure, and that changes in host phenotype may be more dependent on the metabolic capacity and metabolites of the microbiota, instead of the composition per se.
In the longest exercise intervention to date, Kern et al. [Citation108] investigated the effects of regular aerobic training of different intensities and modalities with similar exercise energy expenditure on gut microbiota over a 6-month period. A total of 88 sedentary overweight/obese subjects were randomized into four arms, including habitual living (control), active commuting by non-motorized bicycle, leisure-time exercise of moderate intensity, or vigorous intensity exercise. Beta diversity changed in all exercise groups compared to control, with participants in the vigorous intensity group showing decreased heterogeneity. Further, the vigorous exercise group experienced a greater increase in alpha diversity at 3 months compared to control. More intense exercise may be needed to induce change in the gut microbiota in sedentary, overweight/obese subjects. In a study of acute exercise, both high intensity interval and moderate continuous training affected the gut microbiota in insulin resistant, sedentary individuals following a 2-week exercise intervention [Citation109]. Specifically, Bacteroidetes increased and the Firmicutes/Bacteroidetes ratio decreased. This outcome has relevance to athletes as the increase in Bacteroidetes plays an essential role in the metabolic conversions of complex sugar polymers and degradation of proteins [Citation110]. There was also a decrease in Clostridium and Blautia genera. Clostridium plays an important role in whole-body immune responses, while Blautia purportedly increases the release of proinflammatory cytokines [Citation111]. Interestingly, colonic glucose concentrations associated positively with Bacteroidetes and inversely with Firmicutes phylum, the Firmicutes/Bacteroidetes ratio, and Blautia genus. In addition, lower abundance of Blautia genus was associated with better whole-body insulin sensitivity. These results highlight the importance of intestinal substrate uptake on the whole-body and changes, especially in glucose uptake, might have a positive effect on the gut microbiota.
Finally, in an observational study, Keohane et al. [Citation99] explored the gut microbiota response of four well-trained ultra-endurance male athletes to prolonged, high intensity trans-oceanic rowing, describing changes in microbial diversity, abundance, and metabolic capacity. Serial stool samples were obtained from the athletes for metagenomic whole-genome shotgun sequencing to record microbial community structure and relevant functional gene profiles pre-race, mid-race, race-finish, and 3 months post-race after a continuous, unsupported 33-day, 5000-km transoceanic rowing event. Alpha diversity increased throughout the ultra-endurance event and was evident as early as day 17 in the race. This increase occurred independent of any change in cardiorespiratory fitness, with VO2max similar pre- and post-race. Variations in taxonomic composition included increased abundance of butyrate producing species and species associated with improved metabolic health and improved insulin sensitivity.
The functional potential of bacterial species involved in specific amino and fatty acid biosynthesis also increased. Specifically, the gene expression of functional metabolic pathways involved in L-isoleucine and L-lysine production increased, which play an important role in reducing muscular fatigue and damage during strenuous exercise [Citation112]. Microbial-derived lysine may also contribute to the body protein pool in humans [Citation113]. Changes in essential amino acid availability influence hematopoiesis, which in turn may increase oxygen carrying capacity and cardiorespiratory fitness [Citation112]. Many of the adaptations in microbial community structure and metaproteomics persisted at 3 months follow up.
Summary of the effect of exercise on the gut microbiota
Overall, the mechanisms by which physical activity may promote a rich bacterial community and increased functional pathways have not been fully elucidated but likely involve a combination of intrinsic and extrinsic factors. For example, physically active individuals are more likely to be exposed to their environmental biosphere (e.g., time spent outdoors) and follow an overall healthy lifestyle and, consequently, harbor a richer microbiota. Simultaneously, intrinsic adaptations to endurance training, such as decreased blood flow, tissue hypoxia, and increased transit and absorptive capacity can lead to changes in the GI tract [Citation114, Citation115]. Changes in GI transit time have been reported to affect the pH within the colonic lumen which could lead to alterations in the composition of the gut microbiota. For instance, longer colonic transit time is associated with decreased gut microbiota diversity, which is paralleled by an increase in pH during transit from the proximal to the distal colon [Citation116, Citation117]. Repeated bouts of aerobic exercise can increase GI transit time in healthy individuals and middle-aged patients with chronic constipation [Citation118–Citation120]. However, at higher intensities (e.g., above 70% VO2max), gastric emptying appears to be delayed [Citation121–Citation124]. Aerobic exercise also increases fecal SCFA concentration which can decrease pH in the colonic lumen [Citation125]. Furthermore, metabolites that are a by-product of exercise and circulate throughout the body (e.g., lactate) may filter through the gut and serve as an energy source for certain bacterial taxa (e.g., Veillonella). There is expected competition for nutrients and resources in every ecosystem, including the gut microbiota. Therefore, many of these microbial characteristics may be a result of ‘form fits function’, as communities in the gut are shaped by available resources, as determined by the physiology of their host. These and other potential adaptive mechanisms, such as a change in gut pH, may create an environmental setting that allows for richer community diversity and metabolic functions. Anaerobic capacity and resistance exercise training may also influence community composition, though to date, no work has examined these parameters in relation to gut microbiota.
A single acute bout of prolonged excessive exercise can have a deleterious influence on intestinal function. Intense exercise redistributes blood from the splanchnic circulation to actively respiring tissues [Citation126]. Prolonged intestinal hypo-perfusion impairs mucosal homeostasis and causes enterocyte injury. Intestinal ischemia may result, particularly in the setting of dehydration, manifesting as abdominal cramps, diarrhea, or occasionally bloody diarrhea [Citation127]. This adverse effect is particularly the case in endurance sports [Citation128]. As a result, increased intestinal permeability ensues, thought to be driven by the phosphorylation of several tight junction proteins [Citation129]. These events render the gut mucosa susceptible to endotoxin translocation [Citation130]. Moderate endurance exercise in mice has been associated with a lesser degree of intestinal permeability, preservation of mucous thickness, and lower rates of bacterial translocation along with up-regulated anti-microbial protein production and gene expression in small intestinal tissue (α-defensin, β-defensin, Reg IIIb and Reg IIIc) [Citation131]. Together these changes might help mitigate the effects of stress-induced intestinal barrier dysfunction. In humans, physical activity can improve gastrointestinal symptoms in subjects with irritable bowel syndrome [Citation132]. Collectively, these outcomes are evidence of a differential and dose-response effect of exercise on gut health, with the underlying mechanisms yet to be fully explored in healthy humans.
The current body of research supports the role of exercise as an important behavioral factor that can affect qualitative and quantitative changes in the gut microbial composition and function with benefits to the host. Although these changes may not occur in a similar fashion across individuals and may also depend on baseline characteristics of both the microbiota and host. However, based on the current body of research, exercise appears to enrich microbiota diversity, stimulate the proliferation of bacteria which can modulate mucosal immunity, improve barrier functions, and stimulate bacteria and functional pathways capable of producing substances that protect against gastrointestinal disorders and improve performance (i.e., SCFAs). Indeed, exercise may be an important intervention to alter gut microbiota composition and restore gut symbiosis [Citation100]. However, excessive and/or prolonged high-intensity exercise may not impart these effects. Notably, certain taxa may be enriched in athletes such as the lean phenotype-associated A. muciniphila, and propionate producing Veillonella (via metabolism of lactate). In addition, higher diversity of microbiota composition was associated with lean phenotypes compared to that of obese individuals. It is likely that the diverse, metabolically favorable intestinal microbiota evident in the elite athlete is the cumulative manifestation of many years of high nutrient intake and high degrees of physical activity and training throughout youth, adolescence, and during adult participation in high-level sports [Citation133]. Future areas of gut microbiota research in relation to athletes and exercise is presented in Table .
The effect of athletic diet on the gut microbiota
In researching the human gut microbiota, it is difficult to examine exercise and diet separately. This relationship is compounded by changes in dietary intakes often associated with physical activity (e.g., increased protein intake in resistance trained athletes or carbohydrate intake in endurance athletes and increased total energy and nutrient intake in general). Athletes often consume a diet that differs from the general population with implications on the composition of the gut microbiome.
Diet is an established modulator of gut microbiota composition, with significant alterations reported within 24 h of a dietary change [Citation134]. This ability to rapidly change has implications in research design for the timing of measurements in exercise studies, as does dietary composition. Indeed, various food components, dietary patterns, and nutrients all have the potential to substantially alter the growth of different gut microbial populations. Medication and diet are principal environmental factors that influence gut microbiota composition according to large-cohort studies [Citation135, Citation136]. The gut microbiota is an important factor that shapes both energy harvest and storage through metabolism of proteins and production of several metabolites including SCFAs, ammonia, sulfur-containing metabolites such as hydrogen sulfide and methanethiol, and neuroactive compounds such as tryptamine, serotonin, phenethylamine, tryptophan, and histamine [Citation137, Citation138]. Moreover, the gut microbiota can also synthesize de novo amino acids and is involved in the utilization and catabolism of several amino acids originating from both alimentary and endogenous proteins. These amino acids can serve as precursors for the synthesis of other metabolites produced by the microbiota including SCFAs [Citation139]. Animal studies have revealed communication between the gut microbiota and muscle, in which gut microbiota can affect muscle energy homeostasis by interfering with fat deposition, and lipid and glucose metabolism through various metabolites including SCFAs and secondary bile salts [Citation17]. Broadly, athletes consume higher energy diets compared to sedentary individuals and are often encouraged to consume a diet high in carbohydrate and protein and lower in fat [Citation140]. During training and competition, fiber intake may be reduced to avoid potential GI issues including gas and distension [Citation141]. Importantly athletes’ dietary plans often account for macro- and micronutrient needs, hydration, the timing of nutrients, and dietary supplements, but rarely is the health of the gut microbiota considered [Citation140]. Here we describe the influence of total energy intake and the principal macronutrient classes (protein, carbohydrate, and fat) on the gut microbiota.
Energy intake
The GI tract represents the interface between ingested nutrients and the host where energy is effectively extracted. In healthy adults, ~ 85% of carbohydrates, 65–95% of proteins, and nearly all fats are absorbed before entering the large intestine [Citation142]. Consequently, indigestible carbohydrates and proteins that enter the colon represent between 10 and 30% of total ingested energy [Citation143, Citation144]. If not for the colonic microbiota, these nutrients would generally be eliminated via the stool without further absorption due to the limited digestive capability of the human large intestine [Citation142]. Therefore, the gut microbiota plays an important role in energy extraction and, in turn, can be influenced by the composition of the diet and the amount of energy entering this environment [Citation145]. In relation, the gut microbiota produces and releases an enormous array of compounds which may act upon host tissues modulating appetite, gut motility, energy uptake and storage, and energy expenditure [Citation146, Citation147]. Riedl et al. [Citation148] estimated that for an average 90 kg male, the biomass of bacteria in the gut could be expected to contribute anywhere from 7 to 22% of daily adult human caloric turnover (based on 2000 kcal [kcal] per day). Clearly, the gut microbiota-host interaction can affect energy balance which has implications for weight gain or loss and body composition [Citation149, Citation150].
Strong evidence exists to support the role for the gut microbiota in energy balance by contributing to host digestive efficiency [Citation151]. Studies of lean and obese mice indicate that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet and how this harvested energy is used and stored. For example, studies of germ-free mice (so called ‘gnotobiotic mice’) have provided important insights into the role the gut microbiota plays in energy homeostasis. Gnotobiotic mice are inefficient at processing food, yet when colonized with conventional mouse gut biota they gain weight by increasing their energy stores [Citation152]. This weight gain occurs even when decreasing energy intake by 30% and increasing energy expenditure by 30%, compared to mice who remained germ-free [Citation153]. These results implicate the gut microbiota as an energy harvester, significantly affecting nutrient absorption by extracting energy from dietary substances.
To examine the impact of energy consumption on the gut microbiota, rats fed a high-energy dense diet rapidly altered their gut microbiota with increases in Firmicutes/Bacteroidetes ratio and in pro-inflammatory Proteobacteria proliferation compared to those consuming a low-energy diet [Citation154]. Moreover, the high-energy diet increased circulating pro-inflammatory LPS. However, the impact of energy consumption on, and the ultimate extraction by, the gut microbiota is deeply intertwined with composition of the ingested diet. For example, obese mice fed a low saturated fat, high fruit and vegetable diet can take on microbiota characteristics of lean mice [Citation63]. Moreover, mice consuming this diet regardless of lean or obese state gained less fat mass compared to lean and obese mice fed a high-saturated fat, low fruit and vegetable diet, typical of a Westernized diet.
In terms of human research there are few studies that have examined the effect of energy intake and energy expenditure on the gut microbiota. The majority of this research has been conducted in relation to the study of obesity, weight loss, and malnourishment in children. Generally, when comparing obese and lean individuals, both the diversity of the gut microbiota and the ratio of Bacteroidetes to Firmicutes is decreased in obese individuals [Citation145]. Similar findings have been reported in relation to gene richness and altered metabolic pathways [Citation155]. However, the composition of the gut microbiota does appear to be sensitive to caloric balance as noted in subjects studied before, during, and after weight loss [Citation38]. Furthermore, improved gene richness has been reported during weight-loss and weight-stabilization interventions in obese and overweight individuals [Citation156]. What remains unclear is the influence of energy stores (obese or lean state) versus the impact of energy intake (positive or negative energy balance) on ability to alter the gut microbiota. In a carefully monitored inpatient crossover feeding trial, Jumpetz and colleagues [Citation157] examined how gut bacterial community structure is affected by two distinct caloric loads (2400 vs 3400 kcal/day) with a similar nutrient profile (24% protein, 16% fat, and 60% carbohydrates) and dietary energy harvest in 12 lean and 9 obese individuals. The higher caloric load was positively correlated with the relative abundance of Firmicutes species and negatively correlated with the relative abundance of Bacteroidetes species in both lean and obese humans. In lean individuals, these changes were associated with an increased energy harvest of approximately 150 kcal. This finding suggests that the microbiota is responsive to energy balance (degree of overfeeding) as well as actual adiposity. It may be that the gut “senses” alterations in nutrient availability and subsequently modulated the nutrient absorption. Regardless, these results show that the nutrient load is a key variable that can influence the gut community structure. In rugby athletes with high energy consumption (median intake of 4449 kcals per day), gut microbial diversity was significantly greater compared to age and BMI matched sedentary controls (median intake of 2801 kcal per day) [Citation19]. Moreover, in cyclists consuming high-energy, high-carbohydrate diets, abundances of health associated bacteria were high (including Prevotella and Akkermansia) and less characteristic of Western-associated microbiota [Citation18]. However, it is difficult to remove physical activity influence from this, and gut microbiota research in athletes with high energy consumption requires further investigation.
In contrast to high-energy intake and obesity, even less is known about the gut microbiota in undernutrition [Citation142]. Athletes can have a tremendous energy expenditure often requiring a corresponding increase in dietary intake to maintain energy balance. However, Relative Energy Deficiency in Sports (RED-S) syndrome is present in many athletic disciplines as a result of insufficient energy availability due to insufficient caloric intake and/or excessive energy expenditure [Citation158]. Occurring in both males and females, RED-S possesses a significant health risk. To date, no study in athletes has addressed RED-S in relation to the gut microbiota. Moreover, little is known on the effects of energy reduced diets in athletes looking to healthfully reduce bodyweight and/or improve body composition. Calorie restriction, primarily in animals, can improve the composition and associated metabolism of the gut microbiota, including increasing the relative abundances of probiotic and butyrate-producing microbes [Citation159] and increasing SCFA biosynthesis [Citation160].
In humans, severe calorie restriction as a result of bariatric surgery offers an interesting research model to explore the effect on the gut microbiota [Citation161]. Changes such as reduced abundance of Firmicutes post-surgery have been reported [Citation162]. Although it is unclear if these modifications were caused by dietary change or weight loss. Furet and colleagues [Citation163] reported that the Bacteroides/Prevotella ratio increased within 3 months after surgery and remained stable thereafter. While this ratio was negatively correlated with body weight, BMI, and body fat mass, the correlation was highly dependent on total calorie intake. Other alterations, such as the reduction of lactic acid forming bacteria, indicate a complex effect of severe calorie restriction.
Undernourished children have been observed to exhibit impaired gut microbiota development, with reduced relative abundance of several Bifidobacterium and Lactobacillus spp. as well as obligate anaerobic SCFA-producing taxa [Citation164]. For instance, a sample of children living in an urban slum in Bangladesh with either moderate acute malnutrition or severe acute malnutrition had a gut microbiota that was ‘immature’; meaning discriminatory taxa in their gut communities were more similar to younger rather than age-matched healthy individuals from the same location [Citation165]. This ‘immaturity’ was greater in those more severely malnourished with probable physiologic, metabolic, and immunologic consequences [Citation165]. This has led to the proposal that disrupted microbiota development impairs healthy bone and muscle growth during infancy [Citation166]. To explore the association between nutrition and the gut microbiota during infancy, Charbonneau et al. [Citation166] colonized young germ-free mice with the fecal microbiota of a growth-stunted Malawian infant. These animals were fed a representative Malawian diet with or without a bioactive substance in breast milk (purified sialylated bovine milk oligosaccharides). Treatment with the milk oligosaccharides produced microbiota-dependent growth promotion, including lean body mass gain, changed bone morphology, and altered liver, muscle and brain metabolism. These effects were also documented in gnotobiotic piglets using a similar design showing a greater ability to utilize nutrients from the diet [Citation166]. These preclinical models indicate a causal, microbiota-dependent relationship between nutrition and growth promotion which may have implications for younger athletes.
Various studies have explored the gut microbiota of anorexia nervosa patients with the majority of them being characterized by heterogeneity in the methodology and small sample sizes (for review see: [Citation167]). Several studies of anorexia nervosa patients have reported decreased abundances of the butyrate producing Roseburia in combination with reduced butyrate levels and lower microbial diversity and taxa abundance compared to healthy controls [Citation168–Citation170]. During an in-patient, medically supervised weight gain study in anorexic individuals, microbial richness increased, however perturbations in intestinal microbiota and SCFA profiles, in addition to several gastrointestinal symptoms, did not recover during the subject’s in-patient stay [Citation169]. Future studies will be needed to dissect the impact of restricted energy consumption and/or increased energy expenditure on the gut microbiota in athletes.
Overall, energy balance is an overlooked factor in relation to the athletic gut microbiota. Not only is this relevant to improving performance, but also addressing the health status of those affected by RED-S. Different dietary patterns affecting macronutrient consumption can alter the composition of what enters the large intestine where there is the greatest density of gut microbes. This has a tremendous impact on the human body’s ability to extract and utilize energy from the diet. Moreover, it is difficult (if not impossible) to solely investigate the impact of total energy consumption on the composition of the gut microbiota without considering dietary variability such as the major dietary macronutrient classes.
Protein
Despite the difficulties of studying macronutrient effects in isolation, there is evidence to support the assertion that dietary protein (and fat) consumption elicit both compositional and functional changes to the gut microbiota [Citation171]. David et al. [Citation134] showed a rapid shift in gut microbial community composition and increased populations of Alistipes, Bilophila, and Bacteroides after consuming a high-fat/protein diet for 5 days and these changes were thought to be a result of increased bile secretion. Changes to the gut microbiota have also been documented when dietary protein is increased: Bacteroides spp. are highly associated with animal proteins, whereas Prevotella spp. are highly associated with increased intakes of plant proteins [Citation172]. Intervention studies have demonstrated that high-protein diets (animal protein) reduced fecal butyrate concentrations and butyrate-producing bacteria such as Bifidobacteria spp., Roseburia spp., and E. rectale [Citation173–Citation175]. Fecal concentrations of potentially damaging N-nitroso compounds increase markedly in volunteers who consumed a high-protein, low-carbohydrate diet [Citation175]. Furthermore, a study of five male volunteers consuming high intakes of animal protein showed that fecal sulfide production is related to meat intake [Citation176]; notably, hydrogen sulfide is a compound associated with ulcerative colitis [Citation177]. Ma et al. [Citation178] suggested that excessive protein intake or an unsuitable ratio of protein to protein-fermenting bacteria, could potentially produce adverse effects on health.
The partitioning of individuals into so-called ‘enterotypes’ (stratifying global microbiome variation into a few categories, reviewed in [Citation179]) has been suggested to be driven by whether their primary dietary patterns include high complex carbohydrate (Prevotella) or high-fat/protein (Bacteroides) consumption [Citation172]. This categorization has been criticized as an oversimplification, obscuring potentially important microbial variation, and may not be appropriate for the athletic population [Citation180, Citation181]. For example, the Bacteroides enterotype has been suggested to most strongly be correlated with frequent consumption of animal protein and saturated fat. However, the effects of high-protein consumption (without concurrent high-fat) on gut bacteria are not well studied but of increasing importance given the current popularity of high-protein diets, especially in athletes. In professional rugby players, distinct compositional and functional microbial characteristics, including increased alpha diversity, enhanced microbial production of SCFAs, and greater metabolic capacity are evident in the gut [Citation13, Citation19]. These microbial features not only positively correlate with the athletes’ levels of physical activity, but also the quantity of dietary protein consumed. In many athletic disciplines, as well as recreational exercise, protein supplementation (e.g., whey protein) provides a sizeable proportion of athletes’ daily protein intake [Citation19]. Clarke et al. [Citation19] reported microbiota diversity indices correlated positively with protein intake and serum creatine kinase indicating that diet and exercise are both drivers of biodiversity in the gut. The protein and microbiota diversity relationship is further supported by a positive correlation between blood urea levels (a by-product of diets rich in protein) and microbiota diversity [Citation19]. In contrast, Jang et al. [Citation11] reported that daily protein intake was negatively correlated with alpha diversity in distance runners. The inconsistency of these results compared to Clarke et al. [Citation19] may relate to the nutritional status of the athletes. In addition, the study by Clarke and colleagues [Citation19] met all of the recommended dietary intake requirements, while the athletes in the investigation by Jang et al. [Citation11] had insufficient carbohydrate and dietary fiber intake (compared to standard macronutrient distribution ranges). It seems that high-protein diets may have a negative impact on gut microbiota diversity for athletes in endurance sports who consume lower amounts of energy, carbohydrates, and dietary fiber, while athletes in resistance sports that follow a high-protein, low-carbohydrate, and high-fat diet demonstrate a decrease in SCFA-producing commensal bacteria. Long-term diets have been linked to certain compositional clusters in the gut microbiota: protein and animal fat are associated with Bacteroides enrichment and simple carbohydrates with Prevotella enrichment [Citation172]. Excessive fermentation of dietary protein in the GI tract is generally considered detrimental given the production of toxic by-products such as amines, phenols, indoles, thiols, and ammonia [Citation182, Citation183]. In contrast, feeding of whey protein to mice attenuated some negative effects on the composition of the gut microbiota composition including increasing Lactobacillaceae/Lactobacillus and decreasing Clostridiaceae/Clostridium [Citation184, Citation185]. Further, whey protein has been associated with reductions in body weight and increased insulin sensitivity in the past, and is frequently a major component of the athlete diet, particularly in strength and power sports [Citation186, Citation187].
Estaki et al. [Citation14], reported total protein intake was a major contributor to increased beta diversity (the ratio between regional and local species diversity) at each taxonomic rank tested in 39 healthy adults with varying cardiorespiratory fitness levels. A strong association was evident between protein intake and Bacteroides and, in particular, Ruminococcaceae and Lachnospiraceae, two of the most abundant families in human gut environments [Citation188], in explaining community diversity. These saccharolytic organisms persist in fibrolytic gut communities and are considered an important component of a healthy gut microbiota, while their depletion has been observed in inflammatory bowel disease patients [Citation189, Citation190].
In comparing athletes to both high and low BMI non-athlete controls, Barton et al. [Citation13] reported a greater number of pathways correlating to specific macronutrients within the control participants suggesting a shift in the dynamics of varied metabolic functions. The impact of the athletes’ increased protein intake compared to both control groups was evident in the metabolomic phenotyping results. Metabolites derived from dietary protein (trimethylamine N-oxide, carnitines, trimethylamine, 3-Carboxy-4-methyl-5-propyl-2-furanpropionic acid, and 3-hydroxy-isovaleric acid), muscle turnover (creatine, 3-methylhistidine, and L-valine), vitamins and recovery supplements (glutamine, lysine, 4-pyridoxic acid, and nicotinamide), as well as phenylacetylglutamine (a microbial conversion product of phenylalanine) were increased in athletes [Citation191].
Investigating the gut microbiota of cyclists, Petersen et al. [Citation18] reported an increased abundance of Prevotella which positively correlated with a number of amino acid and carbohydrate metabolism pathways, including BCAA metabolism. High levels of BCAAs (leucine, isoleucine, and valine) can attenuate exercise-induced muscle fatigue and promote muscle-protein synthesis [Citation192]. While there is strong evidence showing that BCAAs do not enhance exercise performance [Citation192, Citation193], they may reduce central fatigue [Citation194] and attenuate muscle damage during prolonged exercise [Citation195]. Since BCAAs are not produced by the human body and need to come from the diet, having a gut microbial community that contains Prevotella spp. to either synthesize BCAAs or alternatively influence other microbes to produce these amino acids would be highly beneficial to athletes who require a rapid recovery from intense exercise.
In cross-country runners, the effect of 10 weeks of protein supplementation (10 g whey isolate and 10 g beef hydrolysate per day) consumed daily decreased SCFA-producing bacteria while increasing bacteria with proteolytic activity in the microbiota without affecting SCFAs, ammonia, or fecal pH of endurance athletes [Citation196]. The amount of additional dietary protein was small but yielded a significant 17% increase in dietary protein for these athletes. Specifically, protein supplementation increased the abundance of the Bacteroidetes phylum and decreased the presence of health-related taxa including Roseburia, Blautia, and B. longum. In contrast to Clarke et al. [Citation19], no changes in compositional microbiota diversity were detected after the ten-week intervention, which may relate to the low percentage of protein intake. Increases in dietary protein can increase the amounts reaching the colon, where they are metabolized by colonic microbiota, leading to changes in microbiota populations and in microbial metabolites [Citation178]. The difference between these two studies may also be due to differences in analyses, as Clarke et al. [Citation19] only assessed the V4 region of the gene, while the present study used the V3 and V4 region (see Table ). Balancing the protein/carbohydrate ratio with prebiotics when protein intake is elevated [Citation197], or accompanying the intake of protein supplements with probiotics, could be future strategies to mitigate the observed or anticipated gut microbiota shift [Citation198].
Cronin et al. [Citation199] noted participants consuming whey protein daily experienced a marked alteration in the diversity of their gut virome (a collection of viruses that inhabits the gut environment and affect host cells as well as other commensal organisms [Citation200]) following 8 weeks of oral supplementation. Sedentary subjects (predominantly overweight > 30% body fat) were divided into three groups of 30 subjects: an exercise-only group, a daily whey protein supplementation (30 g per day) group, and an exercise plus daily whey protein supplementation (30 g per day) group. Individuals in the whey protein supplementation-only group experienced a significant increase in the beta diversity of the gut virome. Furthermore, this change was mirrored in the combined exercise and protein supplementation group, suggesting a robust positive effect of whey protein on the taxonomic richness of the gut virome. Specifically, all bacteriophages (bacteria-targeting viruses) increased in the groups receiving whey protein were present in high relative abundance within the whey protein supplement. Therefore, it may be virus particles from whey protein transmit to the gut from consumption. The effect of the gut virome on the gut microbiota and host requires further investigation, particularly in relation to food and supplement consumption.
The source of protein, including its quality and digestibility, may influence the site of fermentation within the gut. Highly digestible proteins, such as whey, can be digested by host enzymes in the proximal intestine, reducing microbial fermentation. Similarly, plant-originated proteins are available for microbial fermentation in a more distal site given incomplete digestion by host enzymes, particularly at a higher protein level. Evidence indicates proteins from vegetable origin have a more marked effect on microbial diversity than animal proteins [Citation201], however investigation in athletes is needed. By selecting dietary ingredients containing protein of rather high digestibility and quality, the amount of dietary protein reaching the large intestine may be diminished, thus limiting the quantity of residual protein available for protein fermenting bacteria. As a consequence, the growth and activity of potential pathogens could be suppressed. These seemingly opposing effects of high-protein diets imply that protein-diet interactions are modulated by factors such as host body composition and exercise intensity. The types and amounts of fats consumed in each of these studies are also likely important for the overall effects on the gut microbiota. For example, a ketogenic diet alters gut microbiota composition leading to an increase in Akkermansia abundance. Moreover, Akkermansia fed to mice has a positive impact on reducing seizures, providing a potential mechanism for the observed neuroprotective effects of a ketogenic diet [Citation66, Citation202].
Carbohydrates
As a macronutrient class, carbohydrates (including dietary fiber) have a profound effect on the gut microbiota. In comparison to bacteria, humans have much fewer enzymes to break down carbohydrates [Citation203] and what can be digested by these enzymes is absorbed in the small intestine. Dietary fiber passes undigested from the small intestine into the colonic environment [Citation171] and the gut microbiota relies on these fibers for energy, which they target for disassembly with a combined ‘toolkit’ of thousands of enzymes [Citation204]. Therefore, carbohydrates in the form of dietary fiber represent enormous potential for modulation of gut microbiota based upon the chemistry and accessibility of specific dietary fibers to microbial groups.
Increased intake of dietary fiber does not have an overall Bifidobacterium increasing effect, however, specific dietary fibers have been shown to selectively increase Bifidobacteria abundance [Citation205]. Furthermore, increased intake of dietary fiber has been associated with an increase in gut microbial richness and/or diversity, especially in individuals with reduced diversity [Citation206]. Long-term patterns of dietary fiber consumption can also shape the overall bacterial community type. As previously discussed, enterotype assignment to the Prevotella group has been suggested to be associated with high-fiber diets. O’Keefe et al. [Citation207] studied the effects on gut microbiota when fat and fiber content of native African and African American diets were swapped for 2 weeks, such that African Americans consumed high-fiber, low-fat rural African diets and vice versa. While changes in abundances of Bacteroides or Prevotella genera were not observed in either group, the high-fiber, low-fat diets enriched bacterial genes for butyrate production and decreased genes for secondary bile acid synthesis, emphasizing the importance of identifying functional rather than compositional shifts.
Endurance athletes are well known to follow diets that result in the consumption of high amounts of both simple and complex carbohydrates [Citation208, Citation209]. This dietary pattern, in combination with the substantial number of hours spent exercising on a weekly basis, led to the hypothesis that endurance athletes are likely to have increased abundance of the bacterial genus Prevotella [Citation208]. Prevotella is normally found in only a small percentage of healthy individuals in European and American cohorts [Citation1, Citation2, Citation20, Citation210]. Previous microbiome studies have repeatedly identified significant correlations of both diet and geographic location to abundances of Prevotella or Bacteroides. Prevotella is more often found in individuals from certain areas of Asia [Citation211, Citation212] and rural Africa [Citation213], and this enrichment for Prevotella is often reflective of diets high in complex carbohydrates (including high dietary fiber from various sources including fruits and vegetables), egg food items, and high levels of vitamins and minerals [Citation172, Citation211]. However, Prevotella has been noted to be associated with several disease states. For instance, Prevotella has been shown to be higher in patients with depression [Citation214], insulin resistance [Citation215], non-alcoholic fatty liver disease [Citation216, Citation217], hypertension [Citation217], and colon cancer [Citation218]. One potential explanation for this phenomenon is that there are several strains within the Prevotella genus that exert pathogenic actions, which could help explain the bi-directional and almost opposing effects that Prevotella has shown to have in human health [Citation219]. More studies in humans are needed to better understand Prevotella’s role in athletes, as well as its role in disease. For this, more in-depth metagenomic studies will be required to reveal the health- or disease-modulating properties of Prevotella, particularly at species and functional level [Citation219].
Nutritional strategies (i.e., avoiding fat and fiber) have been recommended to reduce the risk of GI distress before and during training and competition [Citation220]. These recommendations aim to support rapid gastric emptying, water and nutrient absorption and adequate perfusion of the splanchnic vasculature [Citation221]. However, the lack of complex carbohydrates in elite athletes’ diets may negatively affect the gut microbiota composition and function over time. Many athletes may not be consuming enough fiber that feed commensal bacteria that produce beneficial byproducts for host metabolism and homeostasis [Citation15]. Furthermore, adding fiber, including resistant starch, to high protein diets may help reduce potential negative effects of high protein consumption [Citation222] and may increase fat oxidation [Citation202], further illustrating the importance of consuming adequate dietary fiber for gut and overall health.
Petersen et al. [Citation18] reported increased abundance of M. smithii transcripts in professional cyclists using RNA sequencing. M. smithii increases the fermentation efficiency of many bacterial taxa in the gut, including those that ferment complex polysaccharides [Citation223]. This effect could benefit athletes because an increase in bacterial fermentation products (such as SCFAs) could be absorbed and utilized by the host. Theoretically, this effect could enhance recovery from intense exercise and possibly race performance. SCFAs can improve skeletal muscle insulin sensitivity [Citation224], reduce inflammation [Citation225], and regulate satiety [Citation226], all of which may contribute to the improvements in body composition observed in this study. Additionally, SCFAs are also energy substrates for numerous tissue types, including the colon [Citation227], adipose [Citation228] and muscle tissues [Citation224], indicating that SCFAs can contribute to enhanced energy harvest from the diet, ultimately providing support to healthy tissue growth and turnover.
Within the SCFAs, distinct clusters (acetic acid, propionic acid, and butyric acid) were observed by Barton et al. [Citation13] to positively correlate with dietary contributors (fiber and protein), while isobutyric acid, isovaleric acid, and valeric acid positively correlated with microbial diversity. The same clusters were observed when positively correlating with individual taxa, in support of purported links between SCFAs and numerous metabolic benefits and a lean phenotype [Citation61–Citation63].
Fat
Like protein and carbohydrate, the specific effects of fat on the gut microbiota are difficult to isolate; however, the types of fats consumed appear to be important. In a rodent study, animals fed lard showed increases in Bacteroides and displayed signs of metabolic dysfunction. In contrast, animals fed fish oil showed increased levels of lactic acid bacteria and were protected from metabolic dysfunction [Citation229]. In humans, ingestion of an animal-based diet for 5 days, high in fat (69% of total energy) and protein (30% of total energy) and almost entirely void of carbohydrates (including dietary fiber), induced rapid and significant changes in microbial community structure and overwhelmed inter-individual differences in microbial gene expression. Specific alterations included gut bacterial taxonomic shifts and transcriptional responses characteristic of carnivorous mammals, with higher concentrations of bile-tolerant bacteria (presumably due to the extremely high-fat intake known to increase bile acid secretion) [Citation134]. Diets high in fat could interact in various ways with the gut microbiota to facilitate the translocation of bacterial LPS generating chronic inflammation [Citation171]. LPS can be incorporated into lipid micelles formed during fat digestion, and certain gut microbes may be important in regulating this process.
In a short-term feeding study Wu et al. [Citation172] randomized ten subjects into a 10-day high-fat/low-fiber diet (38% fat, 35% carbohydrate, 27% protein) while others were given a high-fiber/low-fat diet (13% fat, 69% carbohydrate, 18% protein). Although specific taxa changes varied between individuals, the high-fat diet slowed intestinal transit time by as much as 3 days. Metagenomic analysis indicated that functional shifts, including greater protein export and lipoic acid metabolism, were also associated with the high-fat diet. Finally, the Bacteroides enterotype was most strongly correlated with reports of frequent consumption of animal protein and saturated fat. Similarly, Murtaza and colleagues [Citation230] completed a three-week diet intervention in elite race walkers undertaking intensified training combined with a ketogenic, low-carbohydrate, high-fat diet (LCHF; < 50 g day carbohydrate; 78% energy as fat; 2.1 g/kg/day protein) and reported increased relative abundance of Bacteroides and Dorea and reduced Faecalibacterium. In comparison to high or periodized carbohydrate diet groups, the LCHF diet resulted in a more pronounced effect on the gut microbiota increasing the relative abundance of bacterial taxa with recognized capabilities for lipid metabolism. The relative abundance of Bacteroides spp. was negatively correlated with fat oxidation and the relative abundance of Dorea was negatively correlated with an exercise economy test. It appears that individual responsiveness to a high-fat diet may affect the amount of dietary fat that actually reaches the distal gut, where it could have associative effects on the gut microbiota. Furthermore, relative abundance of Faecalibacterium spp. was decreased in athletes after consumption of the LCHF diet. Interestingly, Faecalibacterium spp. is one of the most abundant bacterial taxa present in the gut microbiota of healthy individuals and has been linked to a host of metabolic products with anti-inflammatory effects [Citation231]. Diets high in fat likely increase the pool of bile acids that elude epithelial absorption in the GI tract and interact with the gut microbiota [Citation232]. This interaction can impact the composition of the gut microbiota including reductions in the relative abundance of Faecalibacterium spp. [Citation233]. Faecalibacterium is widely recognized for its production of a suite of metabolites and peptides with anti-inflammatory effects [Citation231].
Summary of the effect of athletic diet on the gut microbiota
Overall, there is a need for longer-term studies in different athletic cohorts examining the impact of diet on the structure and function of the gut microbiota. This approach is of particular importance as many athletes follow special dietary practices, such as during periods of intensified training prior to competition and offseason periods. Research studies should investigate exercise-nutrient interactions that underpin adaptation and performance [Citation234]. Finally, further research is needed to determine the synthesis kinetics and clinical consequence of microbial by-products during increased nutritional status and metabolic demands during exercise. Ultimately modulation of the microbiota and its fermentation capacity may be considered in dietary prescription for athletes. This may include specific nutrient recommendations aimed at improving performance by enhancing certain metabolites during exercise and recovery, and limiting those that produce toxic metabolites that may made worsen the consequences of exercise stress [Citation15].
Conclusion
The current body of literature, although limited, indicates that the cluster of athletic components such as exercise, associated dietary factors, and body composition promotes a more “health-associated” gut microbiota. Typical features include a higher abundance of health-promoting bacterial species, increased microbial diversity, functional pathways, and microbial-associated metabolites, stimulation of bacterial abundance that can modulate mucosal immunity, and improved barrier functions. In comparison to sedentary controls, athletes have increased fecal metabolites and improved overall health (unless over-trained or in RED-S). However, in sedentary individuals, exercise appears to positively modulate the composition and metabolic capacity of the human gut microbiota. Given that athletes generally have a distinct diet, research on the gut microbiome in athletes must incorporate dietary and supplemental intake otherwise it might be a confounding factor in determining exercise-specific effects on the composition of the microbiome. While individuals’ microbiotas appear to be driven by their primary dietary patterns, future research is needed to better describe the impact of high-protein consumption and (in conjunction) the types and amount of fiber and fats consumed. Investigators should examine how different types of sport, athlete, and physical training regimens influence the gut microbiota. The present review focuses on the discussion of the results from microbiota-related studies, however, a deep discussion of the methodological approaches of each manuscript was not possible due to the already extended content. Future, more specific reviews in this research area should aim for discussing the results in the frame of their methodological approaches. Finally, much of the current research is cross-sectional and has relied on 16S rRNA sequencing. Therefore, future research should employ longitudinal designs as well as more advanced high-throughput sequencing and bioinformatic analyses to provide deeper understanding and functional causation of the gut microbial influence on athlete health and performance. This information can then be used to develop novel therapeutic and nutritional strategies to modulate the microbiota and enhance the athlete’s overall performance and health. Ultimately this body of work will define how metabolic capabilities of gut microbiota are shaped by exercise and elucidate their functional roles influencing health and disease.
Authors’ contributions
AEM and RJ conceptualized and designed this review. AEM, RJ, KCC, and CMK prepared and compiled the first draft for review and editing. All other co-authors critically evaluated and revised the first draft and articles for inclusion. AEM completed the final draft of the manuscript which was reviewed, edited, and approved by all co-authors. The author(s) read and approved the final manuscript.
Ethics approval
Not applicable.
Consent for publication
Not applicable.
Competing interests
KB, LB, and SDW declare no competing interests. RJ has received grants to evaluate the efficacy and safety of probiotics, serves on scientific advisory boards, and has served as an expert witness, legal and scientific consultant. AEM and KCC are employed by Isagenix, a company selling branded probiotics products. CMK has previously received external funding to conduct research studies involving nutritional supplements and is currently conducting studies involving prebiotics and probiotics. MP has received grants to evaluate the efficacy and safety of probiotics and has served as a scientific consultant. JRT reports no conflicts of interest regarding the material or paper presented. JRT has previously received grants to evaluate the efficacy of various nutritional supplements including probiotics. NPW reports no conflicts of interested regarding the paper presented and has been the recipient of external funding to conduct research on nutritional supplements on the microbiome in athletes. MG reports no conflicts of interest regarding the material or paper presented. MG has previously received external funding to conduct research studies involving nutritional supplements including probiotics. DBP reports no conflicts of interest regarding the material or paper presented, and has received grants to evaluate the effectiveness of probiotic supplementation in athletes. BIC has conducted industry sponsored studies at his university and occasionally serves as a scientific and legal consultant related to exercise and nutrition intervention studies. He also serves on the scientific advisory board of Dymatize (Post Holdings). RBK reports no conflicts of interest related to the material presented in this paper. He has conducted industry sponsored studies at the universities he has been affiliated with and occasionally serves as a scientific and legal consultant related to exercise and nutrition intervention studies. CJW is employed by Jamieson Labs, a company selling branded probiotics products. MPA is employed by Biolab research Srl, performing research & development activities for Probiotical SpA, a leading probiotic supplier. DSK reports he works for a contract research organization that has received funding from the probiotic industry for clinical trials and serves on the Scientific Advisory Board for Dymatize (Post Holdings). JS is a co-founder of Fitbiomics, a company identifying, researching and commercializing new probiotic strains. JAT is employed by the International Probiotic Association and further consults within the probiotic and microbiome industries. PJA reports no conflicts of interest related to the material presented in this paper. He serves on the Scientific Advisory Board for Dymatize (Post Holdings), and Isagenix International LLC and has conducted industry sponsored studies involving nutritional supplements. SMA reports no conflicts of interest related to the material presented in this paper. He serves on the Scientific Advisory Board for Dymatize (Post Holdings) and has conducted industry sponsored studies involving nutritional supplements. JA is the CEO of the International Society of Sports Nutrition and reports no conflicts of interest with the material presented.
Abbreviations
BCAA | = | Branched-chain amino acid |
BMI | = | Body mass index |
GI | = | Gastrointestinal |
Kcal | = | Kilocalories |
LCHF | = | Low-carbohydrate, high-fat |
LPS | = | Lipopolysaccharide |
OTUs | = | Operational taxonomic units |
RED-S | = | Relative Energy Deficiency in Sports |
rRNA | = | Ribosomal RNA |
SFCA | = | Short chain fatty acid |
Spp. | = | Species |
VO2 | = | Volume of oxygen utilization |
Acknowledgments
The authors would like to thank the participants and researchers who contributed works cited in this paper.
Funding
The publication fee was sponsored by Increnovo LLC. The authors received no remuneration for writing and/or reviewing this review.
Availability of data and materials
Not applicable.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- Human Microbiome Project C Structure, function and diversity of the healthy human microbiomeNature.2012486 7402 207 214 https://doi.org/10.1038/nature11234 1:CAS:528:DC%2BC38Xos1ejurs%3D https://doi.org/10.1038/nature11234
- QinJLiRRaesJArumugamMBurgdorfKSManichanhC et al A human gut microbial gene catalogue established by metagenomic sequencingNature.2010464 7285 59 65 1:CAS:528:DC%2BC3cXislahsLc%3D 3779803 https://doi.org/10.1038/nature08821 3779803 https://doi.org/10.1038/nature08821
- CroninOMolloyMGShanahanFExercise, fitness, and the gutCurr Opin Gastroenterol201632 2 67 73 https://doi.org/10.1097/MOG.0000000000000240 https://doi.org/10.1097/MOG.0000000000000240
- UrsellLKMetcalfJLParfreyLWKnightRDefining the human microbiomeNutr Rev201270 Suppl 1 S38 S44 3426293 https://doi.org/10.1111/j.1753-4887.2012.00493.x 3426293 https://doi.org/10.1111/j.1753-4887.2012.00493.x
- DuffyLCRaitenDJHubbardVSStarke-ReedPProgress and challenges in developing metabolic footprints from diet in human gut microbial cometabolismJ Nutr2015145 5 1123S 1130S 1:CAS:528:DC%2BC2MXptlGns70%3D 4410496 https://doi.org/10.3945/jn.114.194936 4410496 https://doi.org/10.3945/jn.114.194936
- CostelloEKLauberCLHamadyMFiererNGordonJIKnightRBacterial community variation in human body habitats across space and timeScience.2009326 5960 1694 1697 1:CAS:528:DC%2BD1MXhsFGmsL7K 3602444 https://doi.org/10.1126/science.1177486 3602444 https://doi.org/10.1126/science.1177486
- YatsunenkoTReyFEManaryMJTrehanIDominguez-BelloMGContrerasM et al Human gut microbiome viewed across age and geographyNature.2012486 7402 222 227 1:CAS:528:DC%2BC38Xos1emtLc%3D 3376388 https://doi.org/10.1038/nature11053 3376388 https://doi.org/10.1038/nature11053
- Dudek-WicherRKJunkaABartoszewiczMThe influence of antibiotics and dietary components on gut microbiotaPrz Gastroenterol201813 2 85 92 1:CAS:528:DC%2BC1MXhs1KhtL3M 6040098 6040098 https://doi.org/10.5114/pg.2018.76005
- FlintHJDuncanSHScottKPLouisPLinks between diet, gut microbiota composition and gut metabolismProc Nutr Soc201574 1 13 22 1:CAS:528:DC%2BC2MXhsVCnu74%3D https://doi.org/10.1017/S0029665114001463 https://doi.org/10.1017/S0029665114001463
- WampachLHeintz-BuschartAFritzJVRamiro-GarciaJHabierJHeroldM et al Birth mode is associated with earliest strain-conferred gut microbiome functions and immunostimulatory potentialNat Commun20189 1 5091 6269548 https://doi.org/10.1038/s41467-018-07631-x 1:CAS:528:DC%2BC1cXisVakt7vM 30504906 https://doi.org/10.1038/s41467-018-07631-x
- JangLGChoiGKimSWKimBYLeeSParkHThe combination of sport and sport-specific diet is associated with characteristics of gut microbiota: an observational studyJ Int Soc Sports Nutr201916 1 21 6500072 https://doi.org/10.1186/s12970-019-0290-y 31053143 https://doi.org/10.1186/s12970-019-0290-y
- BermonSPetrizBKajenieneAPrestesJCastellLFrancoOLThe microbiota: an exercise immunology perspectiveExerc Immunol Rev201521 70 79 25825908 25825908
- BartonWPenneyNCCroninOGarcia-PerezIMolloyMGHolmesE et al The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic levelGut.201867 4 625 633 1:CAS:528:DC%2BC1cXit1Wgur7O https://doi.org/10.1136/gutjnl-2016-313627 28360096 28360096
- EstakiMPitherJBaumeisterPLittleJPGillSKGhoshS et al Cardiorespiratory fitness as a predictor of intestinal microbial diversity and distinct metagenomic functionsMicrobiome.20164 1 42 4976518 https://doi.org/10.1186/s40168-016-0189-7 27502158 https://doi.org/10.1186/s40168-016-0189-7
- ClarkAMachNExercise-induced stress behavior, gut-microbiota-brain axis and diet: a systematic review for athletesJ Int Soc Sports Nutr201613 43 5121944 https://doi.org/10.1186/s12970-016-0155-6 1:CAS:528:DC%2BC1cXhsVyltro%3D 27924137 https://doi.org/10.1186/s12970-016-0155-6
- ScheimanJLuberJMChavkinTAMacDonaldTTungAPhamLD et al Meta-omics analysis of elite athletes identifies a performance-enhancing microbe that functions via lactate metabolismNat Med201925 7 1104 1109 1:CAS:528:DC%2BC1MXht1eku7jM https://doi.org/10.1038/s41591-019-0485-4 31235964 31235964 https://doi.org/10.1038/s41591-019-0485-4
- CerdaBPerezMPerez-SantiagoJDTornero-AguileraJFGonzalez-SolteroRLarrosaMGut microbiota modification: another piece in the puzzle of the benefits of physical exercise in health?Front Physiol20167 51 4757670 https://doi.org/10.3389/fphys.2016.00051 26924990 https://doi.org/10.3389/fphys.2016.00051
- PetersenLMBautistaEJNguyenHHansonBMChenLLekSH et al Community characteristics of the gut microbiomes of competitive cyclistsMicrobiome.20175 1 98 5553673 https://doi.org/10.1186/s40168-017-0320-4 28797298 https://doi.org/10.1186/s40168-017-0320-4
- ClarkeSFMurphyEFO'SullivanOLuceyAJHumphreysMHoganA et al Exercise and associated dietary extremes impact on gut microbial diversityGut.201463 12 1913 1920 1:CAS:528:DC%2BC2MXhs1ejsA%3D%3D https://doi.org/10.1136/gutjnl-2013-306541 25021423 25021423
- ZhouYMihindukulasuriyaKAGaoHLa RosaPSWylieKMMartinJC et al Exploration of bacterial community classes in major human habitatsGenome Biol201415 5 R66 4073010 https://doi.org/10.1186/gb-2014-15-5-r66 24887286 https://doi.org/10.1186/gb-2014-15-5-r66
- O'SullivanAFarverMSmilowitzJTThe influence of early infant-feeding practices on the intestinal microbiome and body composition in infantsNutr Metab Insights20158 Suppl 1 1 9 1:CAS:528:DC%2BC1cXmsVClsbc%3D 4686345 26715853 https://doi.org/10.4137/NMI.S29530
- SteinMMHruschCLGozdzJIgartuaCPivnioukVMurraySE et al Innate immunity and asthma risk in Amish and Hutterite farm childrenN Engl J Med2016375 5 411 421 1:CAS:528:DC%2BC28XhvF2ks77J 5137793 https://doi.org/10.1056/NEJMoa1508749 5137793 https://doi.org/10.1056/NEJMoa1508749
- ZhangLNicholsRGCorrellJMurrayIATanakaNSmithPB et al Persistent organic pollutants modify gut microbiota-host metabolic homeostasis in mice through aryl hydrocarbon receptor activationEnviron Health Perspect2015123 7 679 688 1:CAS:528:DC%2BC1cXls1Smsbc%3D 4492271 https://doi.org/10.1289/ehp.1409055 4492271 https://doi.org/10.1289/ehp.1409055
- FouhyFWatkinsCHillCJO'SheaCANagleBDempseyEM et al Perinatal factors affect the gut microbiota up to four years after birthNat Commun201910 1 1517 6447568 https://doi.org/10.1038/s41467-019-09252-4 1:CAS:528:DC%2BC1MXoslGku7k%3D 6447568 https://doi.org/10.1038/s41467-019-09252-4
- HollisterEBRiehleKLunaRAWeidlerEMRubio-GonzalesMMistrettaTA et al Structure and function of the healthy pre-adolescent pediatric gut microbiomeMicrobiome.20153 36 4550057 https://doi.org/10.1186/s40168-015-0101-x 4550057 https://doi.org/10.1186/s40168-015-0101-x
- EckburgPBBikEMBernsteinCNPurdomEDethlefsenLSargentM et al Diversity of the human intestinal microbial floraScience.2005308 5728 1635 1638 1395357 https://doi.org/10.1126/science.1110591 1395357 https://doi.org/10.1126/science.1110591
- WuHJWuEThe role of gut microbiota in immune homeostasis and autoimmunityGut Microbes20123 1 4 14 3337124 https://doi.org/10.4161/gmic.19320 3337124 https://doi.org/10.4161/gmic.19320
- Harsch IA, Konturek PC. The Role of Gut Microbiota in Obesity and Type 2 and Type 1 Diabetes Mellitus: New Insights into "Old" Diseases. Med Sci (Basel). 2018;6(2) https://doi.org/https://doi.org/10.3390/medsci6020032.
- MayerEATillischKGuptaAGut/brain axis and the microbiotaJ Clin Invest2015125 3 926 938 4362231 https://doi.org/10.1172/JCI76304 25689247 https://doi.org/10.1172/JCI76304
- IshiguroEHaskeyNCampbellK Gut microbiota: interactive effects of nutrition and health: Elsevier2018
- TierneyBTYangZLuberJMBeaudinMWibowoMCBaekC et al The landscape of genetic content in the gut and Oral human microbiomeCell Host Microbe201926 2 283 95. e8 1:CAS:528:DC%2BC1MXhs1Sit7zL https://doi.org/10.1016/j.chom.2019.07.008 31415755 31415755 https://doi.org/10.1016/j.chom.2019.07.008
- RoagerHMHansenLBBahlMIFrandsenHLCarvalhoVGobelRJ et al Colonic transit time is related to bacterial metabolism and mucosal turnover in the gutNat Microbiol20161 9 16093 1:CAS:528:DC%2BC2sXkvFyrs7g%3D https://doi.org/10.1038/nmicrobiol.2016.93 27562254 27562254 https://doi.org/10.1038/nmicrobiol.2016.93
- LauretoLCianciarusoMSamiaDFunctional diversity: an overview of its history and applicabilityNatureza & Conservacao201513 2 112 116 https://doi.org/10.1016/j.ncon.2015.11.001 https://doi.org/10.1016/j.ncon.2015.11.001
- BackhedFFraserCMRingelYSandersMESartorRBShermanPM et al Defining a healthy human gut microbiome: current concepts, future directions, and clinical applicationsCell Host Microbe201212 5 611 622 https://doi.org/10.1016/j.chom.2012.10.012 1:CAS:528:DC%2BC38Xhs1Oksr7O 23159051 23159051 https://doi.org/10.1016/j.chom.2012.10.012
- Lloyd-PriceJAbu-AliGHuttenhowerCThe healthy human microbiomeGenome Med20168 1 51 4848870 https://doi.org/10.1186/s13073-016-0307-y 27122046 https://doi.org/10.1186/s13073-016-0307-y
- LozuponeCAStombaughJIGordonJIJanssonJKKnightRDiversity, stability and resilience of the human gut microbiotaNature.2012489 7415 220 230 1:CAS:528:DC%2BC38Xhtleru7jO 3577372 https://doi.org/10.1038/nature11550 22972295 https://doi.org/10.1038/nature11550
- RodriguezJMMurphyKStantonCRossRPKoberOIJugeN et al The composition of the gut microbiota throughout life, with an emphasis on early lifeMicrob Ecol Health Dis201526 26050 25651996 25651996 https://doi.org/10.3402/mehd.v26.26050
- FaithJJGurugeJLCharbonneauMSubramanianSSeedorfHGoodmanAL et al The long-term stability of the human gut microbiotaScience.2013341 6141 1237439 3791589 https://doi.org/10.1126/science.1237439 1:CAS:528:DC%2BC3sXhtVCgs7rJ 23828941 https://doi.org/10.1126/science.1237439
- ViscontiALe RoyCIRosaFRossiNMartinTCMohneyRP et al Interplay between the human gut microbiome and host metabolismNat Commun201910 1 4505 6776654 https://doi.org/10.1038/s41467-019-12476-z 1:CAS:528:DC%2BC1MXhvFaksrzE 31582752 https://doi.org/10.1038/s41467-019-12476-z
- Heintz-BuschartAWilmesPHuman gut microbiome: function mattersTrends Microbiol201826 7 563 574 1:CAS:528:DC%2BC2sXhvValtbbI https://doi.org/10.1016/j.tim.2017.11.002 29173869 29173869 https://doi.org/10.1016/j.tim.2017.11.002
- TurnbaughPJGordonJIAn invitation to the marriage of metagenomics and metabolomicsCell.2008134 5 708 713 1:CAS:528:DC%2BD1cXhtFCqs7jL https://doi.org/10.1016/j.cell.2008.08.025 18775300 18775300 https://doi.org/10.1016/j.cell.2008.08.025
- AllabandCMcDonaldDVazquez-BaezaYMinichJJTripathiABrennerDA et al Microbiome 101: studying, analyzing, and interpreting gut microbiome data for cliniciansClin Gastroenterol Hepatol201917 2 218 230 https://doi.org/10.1016/j.cgh.2018.09.017 30240894 30240894 https://doi.org/10.1016/j.cgh.2018.09.017
- KnightRCallewaertCMarotzCHydeERDebeliusJWMcDonaldD et al The microbiome and human biologyAnnu Rev Genomics Hum Genet201718 65 86 1:CAS:528:DC%2BC2sXlsFShtrw%3D https://doi.org/10.1146/annurev-genom-083115-022438 28375652 28375652 https://doi.org/10.1146/annurev-genom-083115-022438
- GoodrichJKDi RienziSCPooleACKorenOWaltersWACaporasoJG et al Conducting a microbiome studyCell.2014158 2 250 262 1:CAS:528:DC%2BC2cXhtFyjtLfO 5074386 https://doi.org/10.1016/j.cell.2014.06.037 25036628 https://doi.org/10.1016/j.cell.2014.06.037
- PoretskyRRodriguezRLLuoCTsementziDKonstantinidisKTStrengths and limitations of 16S rRNA gene amplicon sequencing in revealing temporal microbial community dynamicsPLoS One20149 4 3979728 https://doi.org/10.1371/journal.pone.0093827 1:CAS:528:DC%2BC2cXhs1artbzL 24714158 https://doi.org/10.1371/journal.pone.0093827
- JandaJMAbbottSL16S rRNA gene sequencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfallsJ Clin Microbiol200745 9 2761 2764 1:CAS:528:DC%2BD2sXhtFemt7bI 2045242 https://doi.org/10.1128/JCM.01228-07 17626177 https://doi.org/10.1128/JCM.01228-07
- LozuponeCAHamadyMKelleySTKnightRQuantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communitiesAppl Environ Microbiol200773 5 1576 1585 1:CAS:528:DC%2BD2sXjsVSktr0%3D 1828774 https://doi.org/10.1128/AEM.01996-06 17220268 https://doi.org/10.1128/AEM.01996-06
- VernocchiPDel ChiericoFPutignaniLGut microbiota profiling: metabolomics based approach to unravel compounds affecting human healthFront Microbiol20167 1144 4960240 https://doi.org/10.3389/fmicb.2016.01144 27507964 https://doi.org/10.3389/fmicb.2016.01144
- MarcobalAKashyapPCNelsonTAAronovPADoniaMSSpormannA et al A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic miceISME J20137 10 1933 1943 1:CAS:528:DC%2BC3sXhsFens7jM 3965317 https://doi.org/10.1038/ismej.2013.89 23739052 https://doi.org/10.1038/ismej.2013.89
- ZiererJJacksonMAKastenmullerGManginoMLongTTelentiA et al The fecal metabolome as a functional readout of the gut microbiomeNat Genet201850 6 790 795 1:CAS:528:DC%2BC1cXhtVelsbvN 6104805 https://doi.org/10.1038/s41588-018-0135-7 29808030 https://doi.org/10.1038/s41588-018-0135-7
- BisanzJEUpadhyayVTurnbaughJALyKTurnbaughPJMeta-analysis reveals reproducible gut microbiome alterations in response to a high-fat dietCell Host Microbe201926 2 265 72.e4 1:CAS:528:DC%2BC1MXhtl2is77F https://doi.org/10.1016/j.chom.2019.06.013 31324413 31324413 https://doi.org/10.1016/j.chom.2019.06.013
- BarbJJOlerAJKimHSChalmersNWallenGRCashionA et al Development of an analysis pipeline characterizing multiple hypervariable regions of 16S rRNA using mock samplesPLoS One201611 2 4734828 https://doi.org/10.1371/journal.pone.0148047 1:CAS:528:DC%2BC28XntlWqsr8%3D 26829716 https://doi.org/10.1371/journal.pone.0148047
- KemppainenKMArdissoneANDavis-RichardsonAGFagenJRGanoKALeon-NoveloLG et al Early childhood gut microbiomes show strong geographic differences among subjects at high risk for type 1 diabetesDiabetes Care201538 2 329 332 https://doi.org/10.2337/dc14-0850 25519450 25519450 https://doi.org/10.2337/dc14-0850
- LeeSSungJLeeJKoGComparison of the gut microbiotas of healthy adult twins living in South Korea and the United StatesAppl Environ Microbiol201177 20 7433 7437 1:CAS:528:DC%2BC3MXhsVKnu73P 3194848 https://doi.org/10.1128/AEM.05490-11 21873488 https://doi.org/10.1128/AEM.05490-11
- LiuZDeSantisTZAndersenGLKnightRAccurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencersNucleic Acids Res200836 18 2566877 https://doi.org/10.1093/nar/gkn491 1:CAS:528:DC%2BD1cXht1Kgu7fP 18723574 https://doi.org/10.1093/nar/gkn491
- BressaCBailen-AndrinoMPerez-SantiagoJGonzalez-SolteroRPerezMMontalvo-LomincharMG et al Differences in gut microbiota profile between women with active lifestyle and sedentary womenPLoS One201712 2 5302835 https://doi.org/10.1371/journal.pone.0171352 1:CAS:528:DC%2BC2sXhvF2rs7bP 28187199 https://doi.org/10.1371/journal.pone.0171352
- MorklSLacknerSMullerWGorkiewiczGKashoferKOberascherA et al Gut microbiota and body composition in anorexia nervosa inpatients in comparison to athletes, overweight, obese, and normal weight controlsInt J Eat Disord201750 12 1421 1431 https://doi.org/10.1002/eat.22801 29131365 29131365 https://doi.org/10.1002/eat.22801
- O'DonovanCMMadiganSMGarcia-PerezIRankinAO OS, Cotter PD. distinct microbiome composition and metabolome exists across subgroups of elite Irish athletesJ Sci Med Sport202023 1 63 68 https://doi.org/10.1016/j.jsams.2019.08.290 31558359 31558359 https://doi.org/10.1016/j.jsams.2019.08.290
- DaoMCEverardAAron-WisnewskyJSokolovskaNPriftiEVergerEO et al Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecologyGut.201665 3 426 436 1:CAS:528:DC%2BC2sXivV2mt7Y%3D https://doi.org/10.1136/gutjnl-2014-308778 26100928 26100928
- FlintHJScottKPDuncanSHLouisPForanoEMicrobial degradation of complex carbohydrates in the gutGut Microbes20123 4 289 306 3463488 https://doi.org/10.4161/gmic.19897 3463488 https://doi.org/10.4161/gmic.19897
- HamerHMJonkersDMBastAVanhoutvinSAFischerMAKoddeA et al Butyrate modulates oxidative stress in the colonic mucosa of healthy humansClin Nutr200928 1 88 93 1:CAS:528:DC%2BD1MXhs1arsb0%3D https://doi.org/10.1016/j.clnu.2008.11.002 https://doi.org/10.1016/j.clnu.2008.11.002
- KohADe VadderFKovatcheva-DatcharyPBackhedFFrom dietary Fiber to host physiology: short-chain fatty acids as key bacterial metabolitesCell.2016165 6 1332 1345 1:CAS:528:DC%2BC28Xpslaltro%3D https://doi.org/10.1016/j.cell.2016.05.041 https://doi.org/10.1016/j.cell.2016.05.041
- RidauraVKFaithJJReyFEChengJDuncanAEKauAL et al Gut microbiota from twins discordant for obesity modulate metabolism in miceScience.2013341 6150 1241214 https://doi.org/10.1126/science.1241214 1:CAS:528:DC%2BC3sXhtlyjs77L https://doi.org/10.1126/science.1241214
- den BestenGvan EunenKGroenAKVenemaKReijngoudDJBakkerBMThe role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolismJ Lipid Res201354 9 2325 2340 https://doi.org/10.1194/jlr.R036012 1:CAS:528:DC%2BC3sXht1aqsbrO https://doi.org/10.1194/jlr. R036012
- EverardABelzerCGeurtsLOuwerkerkJPDruartCBindelsLB et al Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesityProc Natl Acad Sci U S A2013110 22 9066 9071 1:CAS:528:DC%2BC3sXhtFait7rM 3670398 https://doi.org/10.1073/pnas.1219451110 23671105 https://doi.org/10.1073/pnas.1219451110
- OlsonCAVuongHEYanoJMLiangQYNusbaumDJHsiaoEYThe gut microbiota mediates the anti-seizure effects of the ketogenic dietCell.2018174 2 497 1:CAS:528:DC%2BC1cXhtlenur%2FF 6062008 https://doi.org/10.1016/j.cell.2018.06.051 30007420 https://doi.org/10.1016/j.cell.2018.04.027
- MaffetonePBLaursenPBAthletes: fit but unhealthy?Sports Med Open20152 24 https://doi.org/10.1186/s40798-016-0048-x 27340616 27340616 https://doi.org/10.1186/s40798-016-0048-x
- CoxAJWestNPCrippsAWObesity, inflammation, and the gut microbiotaLancet Diabetes Endocrinol20153 3 207 215 1:CAS:528:DC%2BC2MXpsFeksLo%3D https://doi.org/10.1016/S2213-8587(14)70134-2 25066177 25066177 https://doi.org/10.1016/S2213-8587(14)70134-2
- KhanMJGerasimidisKEdwardsCAShaikhMGRole of gut microbiota in the Aetiology of obesity: proposed mechanisms and review of the literatureJ Obes20162016 7353642 https://doi.org/10.1155/2016/7353642 5040794 27703805
- LiraFSRosaJCPimentelGDSouzaHACaperutoECCarnevaliLCJr et al Endotoxin levels correlate positively with a sedentary lifestyle and negatively with highly trained subjectsLipids Health Dis20109 82 2922209 https://doi.org/10.1186/1476-511X-9-82 1:CAS:528:DC%2BC3cXpvFCnu7c%3D 2922209 https://doi.org/10.1186/1476-511X-9-82
- CookMDAllenJMPenceBDWalligMAGaskinsHRWhiteBA et al Exercise and gut immune function: evidence of alterations in colon immune cell homeostasis and microbiome characteristics with exercise trainingImmunol Cell Biol201694 2 158 163 1:CAS:528:DC%2BC2MXitVymtbzL https://doi.org/10.1038/icb.2015.108 https://doi.org/10.1038/icb.2015.108
- MatsumotoMInoueRTsukaharaTUshidaKChijiHMatsubaraN et al Voluntary running exercise alters microbiota composition and increases n-butyrate concentration in the rat cecumBiosci Biotechnol Biochem200872 2 572 576 1:CAS:528:DC%2BD1cXjsVWrs7w%3D https://doi.org/10.1271/bbb.70474 https://doi.org/10.1271/bbb.70474
- ChoiJJEumSYRampersaudEDaunertSAbreuMTToborekMExercise attenuates PCB-induced changes in the mouse gut microbiomeEnviron Health Perspect2013121 6 725 730 3672930 https://doi.org/10.1289/ehp.1306534 3672930 https://doi.org/10.1289/ehp.1306534
- EvansCCLePardKJKwakJWStancukasMCLaskowskiSDoughertyJ et al Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesityPLoS One20149 3 3966766 https://doi.org/10.1371/journal.pone.0092193 1:CAS:528:DC%2BC2cXhsVKitrzM 3966766 https://doi.org/10.1371/journal.pone.0092193
- LambertJEMyslickiJPBomhofMRBelkeDDShearerJReimerRAExercise training modifies gut microbiota in normal and diabetic miceAppl Physiol Nutr Metab201540 7 749 752 https://doi.org/10.1139/apnm-2014-0452 https://doi.org/10.1139/apnm-2014-0452
- MathurRBarlowGMObesity and the microbiomeExpert Rev Gastroenterol Hepatol20159 8 1087 1099 1:CAS:528:DC%2BC2MXhtFyjtLbO https://doi.org/10.1586/17474124.2015.1051029 https://doi.org/10.1586/17474124.2015.1051029
- SalonenAde VosWMPalvaAGastrointestinal microbiota in irritable bowel syndrome: present state and perspectivesMicrobiology.2010156 Pt 11 3205 3215 1:CAS:528:DC%2BC3cXhsFCiur3E https://doi.org/10.1099/mic.0.043257-0 https://doi.org/10.1099/mic.0.043257-0
- LarsenNVogensenFKvan den BergFWNielsenDSAndreasenASPedersenBK et al Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adultsPLoS One20105 2 2816710 https://doi.org/10.1371/journal.pone.0009085 1:CAS:528:DC%2BC3cXhsl2rsbk%3D 2816710 https://doi.org/10.1371/journal.pone.0009085
- LeyRETurnbaughPJKleinSGordonJIMicrobial ecology: human gut microbes associated with obesityNature.2006444 7122 1022 1023 1:CAS:528:DC%2BD28XhtlemtLvM https://doi.org/10.1038/4441022a https://doi.org/10.1038/4441022a
- LeyREBackhedFTurnbaughPLozuponeCAKnightRDGordonJIObesity alters gut microbial ecologyProc Natl Acad Sci U S A2005102 31 11070 11075 1:CAS:528:DC%2BD2MXnvVWju7g%3D 1176910 https://doi.org/10.1073/pnas.0504978102 1176910 https://doi.org/10.1073/pnas.0504978102
- KasaiCSugimotoKMoritaniITanakaJOyaYInoueH et al Comparison of the gut microbiota composition between obese and non-obese individuals in a Japanese population, as analyzed by terminal restriction fragment length polymorphism and next-generation sequencingBMC Gastroenterol201515 100 4531509 https://doi.org/10.1186/s12876-015-0330-2 4531509 https://doi.org/10.1186/s12876-015-0330-2
- KoliadaASyzenkoGMoseikoVBudovskaLPuchkovKPerederiyV et al Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian populationBMC Microbiol201717 1 120 5440985 https://doi.org/10.1186/s12866-017-1027-1 1:CAS:528:DC%2BC1cXhvFKqt7fM 5440985 https://doi.org/10.1186/s12866-017-1027-1
- WaltersWAXuZKnightRMeta-analyses of human gut microbes associated with obesity and IBDFEBS Lett2014588 22 4223 4233 1:CAS:528:DC%2BC2cXhslCisbjO 5050012 https://doi.org/10.1016/j.febslet.2014.09.039 5050012 https://doi.org/10.1016/j.febslet.2014.09.039
- FinucaneMMSharptonTJLaurentTJPollardKSA taxonomic signature of obesity in the microbiome? Getting to the guts of the matterPLoS One20149 1 3885756 https://doi.org/10.1371/journal.pone.0084689 1:CAS:528:DC%2BC2cXhvFOgsbk%3D 3885756 https://doi.org/10.1371/journal.pone.0084689
- JohnsonELHeaverSLWaltersWALeyREMicrobiome and metabolic disease: revisiting the bacterial phylum BacteroidetesJ Mol Med (Berl)201795 1 1 8 1:CAS:528:DC%2BC28XhvF2gs73M https://doi.org/10.1007/s00109-016-1492-2 https://doi.org/10.1007/s00109-016-1492-2
- PetrizBACastroAPAlmeidaJAGomesCPFernandesGRKrugerRH et al Exercise induction of gut microbiota modifications in obese, non-obese and hypertensive ratsBMC Genomics201415 511 4082611 https://doi.org/10.1186/1471-2164-15-511 24952588 https://doi.org/10.1186/1471-2164-15-511
- Queipo-OrtunoMISeoaneLMMurriMPardoMGomez-ZumaqueroJMCardonaF et al Gut microbiota composition in male rat models under different nutritional status and physical activity and its association with serum leptin and ghrelin levelsPLoS One20138 5 1:CAS:528:DC%2BC3sXptlyhtbc%3D 3665787 https://doi.org/10.1371/journal.pone.0065465 3665787 https://doi.org/10.1371/journal.pone.0065465
- CampbellSCWisniewskiPJNojiMMcGuinnessLRHaggblomMMLightfootSA et al The effect of diet and exercise on intestinal integrity and microbial diversity in micePLoS One201611 3 4783017 https://doi.org/10.1371/journal.pone.0150502 1:CAS:528:DC%2BC28XhsFGjtL%2FE 4783017 https://doi.org/10.1371/journal.pone.0150502
- KangSSJeraldoPRKurtiAMillerMECookMDWhitlockK et al Diet and exercise orthogonally alter the gut microbiome and reveal independent associations with anxiety and cognitionMol Neurodegener20149 36 4168696 https://doi.org/10.1186/1750-1326-9-36 1:CAS:528:DC%2BC2MXlvV2ksQ%3D%3D 4168696 https://doi.org/10.1186/1750-1326-9-36
- MikaAVan TreurenWGonzalezAHerreraJJKnightRFleshnerMExercise is more effective at altering gut microbial composition and producing stable changes in lean mass in juvenile versus adult male F344 ratsPLoS One201510 5 4446322 https://doi.org/10.1371/journal.pone.0125889 1:CAS:528:DC%2BC2MXhs12itbfN 4446322 https://doi.org/10.1371/journal.pone.0125889
- BockerUNebeTHerweckFHoltLPanjaAJobinC et al Butyrate modulates intestinal epithelial cell-mediated neutrophil migrationClin Exp Immunol2003131 1 53 60 1:STN:280:DC%2BD3s7gs1CjsA%3D%3D 1808611 https://doi.org/10.1046/j.1365-2249.2003.02056.x 1808611 https://doi.org/10.1046/j.1365-2249.2003.02056.x
- Monteiro R, Azevedo I. Chronic inflammation in obesity and the metabolic syndrome. Mediat Inflamm. 2010;2010. https://doi.org/https://doi.org/10.1155/2010/289645.
- DurkRPCastilloEMarquez-MaganaLGrosickiGJBolterNDLeeCM et al Gut microbiota composition is related to cardiorespiratory fitness in healthy Young adultsInt J Sport Nutr Exerc Metab201929 3 249 253 1:CAS:528:DC%2BB3cXmt1artb4%3D https://doi.org/10.1123/ijsnem.2018-0024 https://doi.org/10.1123/ijsnem.2018-0024
- YangYShiYWiklundPTanXWuNZhangX et al The association between cardiorespiratory fitness and gut microbiota composition in premenopausal womenNutrients.20179 8 792 5579588 https://doi.org/10.3390/nu9080792 1:CAS:528:DC%2BC1cXitVWntLrF 5579588 https://doi.org/10.3390/nu9080792
- ClavelTLepagePCharrierC RosenbergEDeLongEFLorySStackebrandtEThompsonFThe family CoriobacteriaceaeThe prokaryotes2014 Berlin Springer
- RycroftANGarsideLHActinobacillus species and their role in animal diseaseVet J2000159 1 18 36 1:STN:280:DC%2BD3c7gvFWqtQ%3D%3D https://doi.org/10.1053/tvjl.1999.0403 https://doi.org/10.1053/tvjl.1999.0403
- NgSKHamiltonIRCarbon dioxide fixation by Veillonella parvula M 4 and its relation to propionic acid formationCan J Microbiol197319 6 715 723 1:CAS:528:DyaE3sXltVamsLc%3D https://doi.org/10.1139/m73-116 https://doi.org/10.1139/m73-116
- AllenJMMailingLJNiemiroGMMooreRCookMDWhiteBA et al Exercise alters gut microbiota composition and function in lean and obese humansMed Sci Sports Exerc201850 4 747 757 https://doi.org/10.1249/MSS.0000000000001495 https://doi.org/10.1249/MSS.0000000000001495
- KeohaneDMWoodsTO'ConnorPUnderwoodSCroninOWhistonR et al Four men in a boat: ultra-endurance exercise alters the gut microbiomeJ Sci Med Sport201922 9 1059 1064 https://doi.org/10.1016/j.jsams.2019.04.004 https://doi.org/10.1016/j.jsams.2019.04.004
- HawleyJAMicrobiota and muscle highway - two way trafficNat Rev Endocrinol201916 2 71 72 https://doi.org/10.1038/s41574-019-0291-6 https://doi.org/10.1038/s41574-019-0291-6
- TaniguchiHTanisawaKSunXKuboTHoshinoYHosokawaM et al Effects of short-term endurance exercise on gut microbiota in elderly menPhys Rep20186 23 https://doi.org/10.14814/phy2.13935
- PluznickJLMicrobial short-chain fatty acids and blood pressure regulationCurr Hypertens Rep201719 4 25 5584783 https://doi.org/10.1007/s11906-017-0722-5 1:CAS:528:DC%2BC2sXkslKksrw%3D 28315048 https://doi.org/10.1007/s11906-017-0722-5
- MoritaEYokoyamaHImaiDTakedaROtaAKawaiE et al Aerobic exercise training with brisk walking increases intestinal Bacteroides in healthy elderly womenNutrients.201911 4 868 1:CAS:528:DC%2BC1MXhslOrtbvF 6520866 https://doi.org/10.3390/nu11040868 https://doi.org/10.3390/nu11040868
- SantacruzAColladoMCGarcia-ValdesLSeguraMTMartin-LagosJAAnjosT et al Gut microbiota composition is associated with body weight, weight gain and biochemical parameters in pregnant womenBr J Nutr2010104 1 83 92 1:CAS:528:DC%2BC3cXnvVeksbg%3D https://doi.org/10.1017/S0007114510000176 https://doi.org/10.1017/S0007114510000176
- AbenavoliLScarpelliniEColicaCBoccutoLSalehiBSharifi-RadJ et al Gut microbiota and obesity: a role for probioticsNutrients.201911 11 2690 6893459 https://doi.org/10.3390/nu11112690 https://doi.org/10.3390/nu11112690
- LiuYWangYNiYCheungCKYLamKSLWangY et al Gut Microbiome Fermentation Determines the Efficacy of Exercise for Diabetes PreventionCell Metab201931 1 P77 91.E5 https://doi.org/10.1016/j.cmet.2019.11.001 1:CAS:528:DC%2BC1MXit1KqsrjI https://doi.org/10.1016/j.cmet.2019.11.001
- NewgardCBAnJBainJRMuehlbauerMJStevensRDLienLF et al A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistanceCell Metab20099 4 311 326 1:CAS:528:DC%2BD1MXlsFyru78%3D 3640280 https://doi.org/10.1016/j.cmet.2009.02.002 19356713 https://doi.org/10.1016/j.cmet.2009.02.002
- KernTBlondMBHansenTHRosenkildeMQuistJSGramAS et al Structured exercise alters the gut microbiota in humans with overweight and obesity-a randomized controlled trialInt J Obes201944 125 135 https://doi.org/10.1038/s41366-019-0440-y https://doi.org/10.1038/s41366-019-0440-y
- MotianiKKColladoMCEskelinenJJVirtanenKALoyttyniemiESalminenS et al Exercise training modulates gut microbiota profile and improves EndotoxemiaMed Sci Sports Exerc201952 1 94 104 7028471 https://doi.org/10.1249/MSS.0000000000002112 https://doi.org/10.1249/MSS.0000000000002112
- Rajilic-StojanovicMde VosWMThe first 1000 cultured species of the human gastrointestinal microbiotaFEMS Microbiol Rev201438 5 996 1047 1:CAS:528:DC%2BC2cXhsFOgu7rK 4262072 https://doi.org/10.1111/1574-6976.12075 24861948 https://doi.org/10.1111/1574-6976.12075
- TuovinenEKetoJNikkilaJMattoJLahteenmakiKCytokine response of human mononuclear cells induced by intestinal Clostridium speciesAnaerobe.201319 70 76 1:CAS:528:DC%2BC38XhslynurvP https://doi.org/10.1016/j.anaerobe.2012.11.002 23168133 23168133 https://doi.org/10.1016/j.anaerobe.2012.11.002
- OhtaniMSugitaMMaruyamaKAmino acid mixture improves training efficiency in athletesJ Nutr2006136 2 538S 543S 1:CAS:528:DC%2BD28XhtFGhu7w%3D https://doi.org/10.1093/jn/136.2.538S 16424143 16424143 https://doi.org/10.1093/jn/136.2.538S
- MetgesCCContribution of microbial amino acids to amino acid homeostasis of the hostJ Nutr2000130 7 1857S 1864S 1:CAS:528:DC%2BD3cXks12iur8%3D https://doi.org/10.1093/jn/130.7.1857S 10867063 10867063 https://doi.org/10.1093/jn/130.7.1857S
- GisolfiCVIs the GI system built for exercise?News Physiol Sci200015 114 119 11390892 11390892 https://doi.org/10.1152/physiologyonline.2000.15.3.114
- RosaEFSilvaACIharaSSMoraOAAboulafiaJNouailhetasVLHabitual exercise program protects murine intestinal, skeletal, and cardiac muscles against agingJ Appl Physiol200599 4 1569 1575 https://doi.org/10.1152/japplphysiol.00417.2005 15961611 15961611 https://doi.org/10.1152/japplphysiol.00417.2005
- TotteyWFeria-GervasioDGaciNLailletBPujosEMartinJF et al Colonic transit time is a driven force of the gut microbiota composition and metabolism: in vitro evidenceJ Neurogastroenterol Motil201723 1 124 134 5216643 https://doi.org/10.5056/jnm16042 27530163 https://doi.org/10.5056/jnm16042
- AbbasAWildingGSitrinMDoes colonic transit time affect colonic pH?J Gastroenterol Hepatol Res20143 6 1103 1107 https://doi.org/10.6051/j.issn.2224-3992.2014.03.399
- StridHSimrenMStorsrudSStotzerPOSadikREffect of heavy exercise on gastrointestinal transit in endurance athletesScand J Gastroenterol201146 6 673 677 https://doi.org/10.3109/00365521.2011.558110 21366388 21366388 https://doi.org/10.3109/00365521.2011.558110
- De SchryverAMKeulemansYCPetersHPAkkermansLMSmoutAJDe VriesWR et al Effects of regular physical activity on defecation pattern in middle-aged patients complaining of chronic constipationScand J Gastroenterol200540 4 422 429 https://doi.org/10.1080/00365520510011641 16028436 16028436 https://doi.org/10.1080/00365520510011641
- OettleGJEffect of moderate exercise on bowel habitGut.199132 8 941 944 1:STN:280:DyaK3MzlslGrsg%3D%3D 1378967 https://doi.org/10.1136/gut.32.8.941 1885077 https://doi.org/10.1136/gut.32.8.941
- HornerKMSchubertMMDesbrowBByrneNMKingNAAcute exercise and gastric emptying: a meta-analysis and implications for appetite controlSports Med201545 5 659 678 https://doi.org/10.1007/s40279-014-0285-4 25398225 25398225 https://doi.org/10.1007/s40279-014-0285-4
- RehrerNJBeckersEBrounsFHoor tenFSarisWHExercise and training effects on gastric emptying of carbohydrate beveragesMed Sci Sports Exerc198921 5 540 549 1:STN:280:DyaK3c7htlygsQ%3D%3D https://doi.org/10.1249/00005768-198910000-00008 2691815 2691815 https://doi.org/10.1249/00005768-198910000-00008
- NeuferPDYoungAJSawkaMNGastric emptying during walking and running: effects of varied exercise intensityEur J Appl Physiol Occup Physiol198958 4 440 445 1:STN:280:DyaL1M7ltlSrsQ%3D%3D https://doi.org/10.1007/BF00643522 2920722 2920722 https://doi.org/10.1007/bf00643522
- FeldmanMNixonJVEffect of exercise on postprandial gastric secretion and emptying in humansJ Appl Physiol Respir Environ Exerc Physiol198253 4 851 854 1:STN:280:DyaL3s7gvVCmtg%3D%3D 7153120 7153120 https://doi.org/10.1152/jappl.1982.53.4.851
- WalkerAWDuncanSHMcWilliam LeitchECChildMWFlintHJpH and peptide supply can radically alter bacterial populations and short-chain fatty acid ratios within microbial communities from the human colonAppl Environ Microbiol200571 7 3692 3700 1:CAS:528:DC%2BD2MXmt1ylt7o%3D 1169066 https://doi.org/10.1128/AEM.71.7.3692-3700.2005 16000778 https://doi.org/10.1128/AEM.71.7.3692-3700.2005
- QamarMIReadAEEffects of exercise on mesenteric blood flow in manGut.198728 5 583 587 1:STN:280:DyaL2s3kvVagsg%3D%3D 1432887 https://doi.org/10.1136/gut.28.5.583 3596339 https://doi.org/10.1136/gut.28.5.583
- de OliveiraEPBuriniRCThe impact of physical exercise on the gastrointestinal tractCurr Opin Clin Nutr Metab Care200912 5 533 538 https://doi.org/10.1097/MCO.0b013e32832e6776 19535976 19535976 https://doi.org/10.1097/MCO.0b013e32832e6776
- OktedalenOLundeOCOpstadPKAabakkenLKverneboKChanges in the gastrointestinal mucosa after long-distance runningScand J Gastroenterol199227 4 270 274 1:STN:280:DyaK383ntFSltQ%3D%3D https://doi.org/10.3109/00365529209000073 1589703 1589703 https://doi.org/10.3109/00365529209000073
- ZuhlMSchneiderSLanphereKConnCDokladnyKMoseleyPExercise regulation of intestinal tight junction proteinsBr J Sports Med201448 12 980 986 https://doi.org/10.1136/bjsports-2012-091585 23134759 23134759
- Brock-UtneJGGaffinSLWellsMTGathiramPSoharEJamesMF et al Endotoxaemia in exhausted runners after a long-distance raceS Afr Med J198873 9 533 536 1:STN:280:DyaL1c3js1WhsA%3D%3D 3375945 3375945
- LuoBXiangDNiemanDCChenPThe effects of moderate exercise on chronic stress-induced intestinal barrier dysfunction and antimicrobial defenseBrain Behav Immun201439 99 106 1:CAS:528:DC%2BC3sXitVShtrnF https://doi.org/10.1016/j.bbi.2013.11.013 24291325 24291325 https://doi.org/10.1016/j.bbi.2013.11.013
- JohannessonESimrenMStridHBajorASadikRPhysical activity improves symptoms in irritable bowel syndrome: a randomized controlled trialAm J Gastroenterol2011106 5 915 922 https://doi.org/10.1038/ajg.2010.480 21206488 21206488 https://doi.org/10.1038/ajg.2010.480
- CroninOO'SullivanOBartonWCotterPDMolloyMGShanahanFGut microbiota: implications for sports and exercise medicineBr J Sports Med201751 9 700 701 https://doi.org/10.1136/bjsports-2016-097225 28077354 28077354
- DavidLAMauriceCFCarmodyRNGootenbergDBButtonJEWolfeBE et al Diet rapidly and reproducibly alters the human gut microbiomeNature.2014505 7484 559 563 1:CAS:528:DC%2BC2cXhtFOls78%3D https://doi.org/10.1038/nature12820 24336217 24336217 https://doi.org/10.1038/nature12820
- FalonyGJoossensMVieira-SilvaSWangJDarziYFaustK et al Population-level analysis of gut microbiome variationScience.2016352 6285 560 564 1:CAS:528:DC%2BC28Xms1Kisbo%3D https://doi.org/10.1126/science.aad3503 27126039 27126039 https://doi.org/10.1126/science.aad3503
- ZhernakovaAKurilshikovABonderMJTigchelaarEFSchirmerMVatanenT et al Population-based metagenomics analysis reveals markers for gut microbiome composition and diversityScience.2016352 6285 565 569 1:CAS:528:DC%2BC28Xms1KisL8%3D 5240844 https://doi.org/10.1126/science.aad3369 27126040 https://doi.org/10.1126/science.aad3369
- PortuneKBeaumontMDavilaATomeDBlachierFSanzYGut microbiota role in dietary protein metabolism and health-related outcomes: the two sides of the coinTrends Food Sci Technol201657 213 232 1:CAS:528:DC%2BC28XhsVakt73N https://doi.org/10.1016/j.tifs.2016.08.011 https://doi.org/10.1016/j.tifs.2016.08.011
- RowlandIGibsonGHeinkenAScottKSwannJThieleI et al Gut microbiota functions: metabolism of nutrients and other food componentsEur J Nutr201857 1 1 24 1:CAS:528:DC%2BC2sXlvVSktb8%3D https://doi.org/10.1007/s00394-017-1445-8 28393285 28393285 https://doi.org/10.1007/s00394-017-1445-8
- NeisEPDejongCHRensenSSThe role of microbial amino acid metabolism in host metabolismNutrients.20157 4 2930 2946 1:CAS:528:DC%2BC2MXotVaksb4%3D 4425181 https://doi.org/10.3390/nu7042930 25894657 https://doi.org/10.3390/nu7042930
- KerksickCMWilbornCDRobertsMDSmith-RyanAKleinerSMJagerR et al ISSN exercise & sports nutrition review update: research & recommendationsJ Int Soc Sports Nutr201815 1 38 6090881 https://doi.org/10.1186/s12970-018-0242-y 1:CAS:528:DC%2BC1MXjtVyrsLc%3D 30068354 https://doi.org/10.1186/s12970-018-0242-y
- TillerNBRobertsJDBeasleyLChapmanSPintoJMSmithL et al International Society of Sports Nutrition Position Stand: nutritional considerations for single-stage ultra-marathon training and racingJ Int Soc Sports Nutr201916 1 50 6839090 https://doi.org/10.1186/s12970-019-0312-9 31699159 https://doi.org/10.1186/s12970-019-0312-9
- Krajmalnik-BrownRIlhanZEKangDWDiBaiseJKEffects of gut microbes on nutrient absorption and energy regulationNutr Clin Pract201227 2 201 214 3601187 https://doi.org/10.1177/0884533611436116 22367888 https://doi.org/10.1177/0884533611436116
- BergmanENEnergy contributions of volatile fatty acids from the gastrointestinal tract in various speciesPhysiol Rev199070 2 567 590 1:CAS:528:DyaK3cXlvVymtb0%3D https://doi.org/10.1152/physrev.1990.70.2.567 2181501 2181501 https://doi.org/10.1152/physrev.1990.70.2.567
- ParkerDSThe measurement of production rates of volatile fatty acids in the caecum of the conscious rabbitBr J Nutr197636 1 61 70 1:CAS:528:DyaE28XkvFSqt7g%3D https://doi.org/10.1079/BJN19760058 949469 949469 https://doi.org/10.1079/bjn19760058
- RosenbaumMKnightRLeibelRLThe gut microbiota in human energy homeostasis and obesityTrends Endocrinol Metab201526 9 493 501 1:CAS:528:DC%2BC2MXht1amsLzO 4862197 https://doi.org/10.1016/j.tem.2015.07.002 26257300 https://doi.org/10.1016/j.tem.2015.07.002
- HeissCNOlofssonLEGut microbiota-dependent modulation of energy metabolismJ Innate Immun201810 3 163 171 1:CAS:528:DC%2BC1cXht1alurfL https://doi.org/10.1159/000481519 29131106 29131106 https://doi.org/10.1159/000481519
- DoniaMSFischbachMASmall molecules from the human microbiotaScience.2015349 6246 1254766 4641445 https://doi.org/10.1126/science.1254766 1:CAS:528:DC%2BC2MXhtF2mtrzN 26206939 https://doi.org/10.1126/science.1254766
- RiedlRAAtkinsonSNBurnettCMLGrobeJLKirbyJRThe gut microbiome, energy homeostasis, and implications for hypertensionCurr Hypertens Rep201719 4 27 5773096 https://doi.org/10.1007/s11906-017-0721-6 1:CAS:528:DC%2BC2sXkslKktrg%3D 28316052 https://doi.org/10.1007/s11906-017-0721-6
- AvolioEGualtieriPRomanoLPecorellaCFerraroSDi RenzoL et al Obesity and body composition in man and woman: associated diseases and new role of gut microbiotaCurr Med Chem201927 2 216 229 https://doi.org/10.2174/0929867326666190326113607 1:CAS:528:DC%2BB3cXkt1Oru78%3D https://doi.org/10.2174/0929867326666190326113607
- TagliabueAElliMThe role of gut microbiota in human obesity: recent findings and future perspectivesNutr Metab Cardiovasc Dis201323 3 160 168 1:STN:280:DC%2BC3s7jtFWhug%3D%3D https://doi.org/10.1016/j.numecd.2012.09.002 23149072 23149072 https://doi.org/10.1016/j.numecd.2012.09.002
- ScheithauerTPDallinga-ThieGMde VosWMNieuwdorpMvan RaalteDHCausality of small and large intestinal microbiota in weight regulation and insulin resistanceMol Metab20165 9 759 770 1:CAS:528:DC%2BC28XpvFejtL0%3D 5004227 https://doi.org/10.1016/j.molmet.2016.06.002 27617199 https://doi.org/10.1016/j.molmet.2016.06.002
- TurnbaughPJLeyREMahowaldMAMagriniVMardisERGordonJIAn obesity-associated gut microbiome with increased capacity for energy harvestNature.2006444 7122 1027 1031 https://doi.org/10.1038/nature05414 17183312 17183312 https://doi.org/10.1038/nature05414
- BackhedFDingHWangTHooperLVKohGYNagyA et al The gut microbiota as an environmental factor that regulates fat storageProc Natl Acad Sci U S A2004101 44 15718 15723 524219 https://doi.org/10.1073/pnas.0407076101 1:CAS:528:DC%2BD2cXhtVWisLjE 15505215 https://doi.org/10.1073/pnas.0407076101
- VaughnACCooperEMDiLorenzoPMO'LoughlinLJKonkelMEPetersJH et al Energy-dense diet triggers changes in gut microbiota, reorganization of gutbrain vagal communication and increases body fat accumulationActa Neurobiol Exp201777 1 18 30 https://doi.org/10.21307/ane-2017-033
- TurnbaughPJHamadyMYatsunenkoTCantarelBLDuncanALeyRE et al A core gut microbiome in obese and lean twinsNature.2009457 7228 480 484 1:CAS:528:DC%2BD1MXotlOlsw%3D%3D https://doi.org/10.1038/nature07540 19043404 19043404 https://doi.org/10.1038/nature07540
- CotillardAKennedySPKongLCPriftiEPonsNLe ChatelierE et al Dietary intervention impact on gut microbial gene richnessNature.2013500 7464 585 588 1:CAS:528:DC%2BC3sXhtlCntrnM https://doi.org/10.1038/nature12480 23985875 23985875 https://doi.org/10.1038/nature12480
- JumpertzRLeDSTurnbaughPJTrinidadCBogardusCGordonJI et al Energy-balance studies reveal associations between gut microbes, caloric load, and nutrient absorption in humansAm J Clin Nutr201194 1 58 65 1:CAS:528:DC%2BC3MXot1Khtrc%3D 3127503 https://doi.org/10.3945/ajcn.110.010132 21543530 https://doi.org/10.3945/ajcn.110.010132
- MountjoyMSundgot-BorgenJBurkeLCarterSConstantiniNLebrunC et al The IOC consensus statement: beyond the female athlete triad--relative energy deficiency in sport (RED-S)Br J Sports Med201448 7 491 497 https://doi.org/10.1136/bjsports-2014-093502 https://doi.org/10.1136/bjsports-2014-093502
- ZhengXWangSJiaWCalorie restriction and its impact on gut microbial composition and global metabolismFront Med201812 6 634 644 https://doi.org/10.1007/s11684-018-0670-8 30446879 30446879 https://doi.org/10.1007/s11684-018-0670-8
- TancaAAbbondioMPalombaAFraumeneCMarongiuFSerraM et al Caloric restriction promotes functional changes involving short-chain fatty acid biosynthesis in the rat gut microbiotaSci Rep20188 1 14778 6170429 https://doi.org/10.1038/s41598-018-33100-y 1:CAS:528:DC%2BC1MXhtVeqs7Y%3D 30283130 https://doi.org/10.1038/s41598-018-33100-y
- Aron-WisnewskyJDoreJClementKThe importance of the gut microbiota after bariatric surgeryNat Rev Gastroenterol Hepatol20129 10 590 598 https://doi.org/10.1038/nrgastro.2012.161 22926153 22926153 https://doi.org/10.1038/nrgastro.2012.161
- RejehNAhmadiFMohammadiEAnooshehMKazemnejadABarriers to, and facilitators of post-operative pain management in Iranian nursing: a qualitative research studyInt Nurs Rev200855 4 468 475 1:STN:280:DC%2BD1M%2FnsVOmsQ%3D%3D https://doi.org/10.1111/j.1466-7657.2008.00659.x 19146560 19146560 https://doi.org/10.1111/j.1466-7657.2008.00659.x
- FuretJPKongLCTapJPoitouCBasdevantABouillotJL et al Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markersDiabetes.201059 12 3049 3057 1:CAS:528:DC%2BC3MXlsVamtg%3D%3D 2992765 https://doi.org/10.2337/db10-0253 20876719 https://doi.org/10.2337/db10-0253
- Blanton LV, Charbonneau MR, Salih T, Barratt MJ, Venkatesh S, Ilkaveya O, et al. Gut bacteria that prevent growth impairments transmitted by microbiota from malnourished children. Science. 2016;351(6275) https://doi.org/https://doi.org/10.1126/science.aad3311.
- SubramanianSHuqSYatsunenkoTHaqueRMahfuzMAlamMA et al Persistent gut microbiota immaturity in malnourished Bangladeshi childrenNature.2014510 7505 417 421 1:CAS:528:DC%2BC2cXpslGhsL0%3D 4189846 https://doi.org/10.1038/nature13421 24896187 https://doi.org/10.1038/nature13421
- CharbonneauMRO'DonnellDBlantonLVTottenSMDavisJCBarrattMJ et al Sialylated Milk oligosaccharides promote microbiota-dependent growth in models of infant undernutritionCell.2016164 5 859 871 1:CAS:528:DC%2BC28XivVGkurg%3D 4793393 https://doi.org/10.1016/j.cell.2016.01.024 26898329 https://doi.org/10.1016/j.cell.2016.01.024
- MackIPendersJCookJDugmoreJMazurakNEnckPIs the impact of starvation on the gut microbiota specific or unspecific to anorexia nervosa? A narrative review based on a systematic literature searchCurr Neuropharmacol201816 8 1131 1149 1:CAS:528:DC%2BC1cXhs1OmsbrN 6187755 https://doi.org/10.2174/1570159X16666180118101354 29345582 https://doi.org/10.2174/1570159X16666180118101354
- BorgoFRivaABenettiACasiraghiMCBertelliSGarbossaS et al Microbiota in anorexia nervosa: the triangle between bacterial species, metabolites and psychological testsPLoS One201712 6 e0179739 5479564 https://doi.org/10.1371/journal.pone.0179739 1:CAS:528:DC%2BC1cXis1Cisbg%3D 28636668 https://doi.org/10.1371/journal.pone.0179739
- MackICuntzUGramerCNiedermaierSPohlCSchwiertzA et al Weight gain in anorexia nervosa does not ameliorate the faecal microbiota, branched chain fatty acid profiles, and gastrointestinal complaintsSci Rep20166 26752 1:CAS:528:DC%2BC28XptVSktL4%3D 4882621 https://doi.org/10.1038/srep26752 27229737 https://doi.org/10.1038/srep26752
- KleimanSCWatsonHJBulik-SullivanECHuhEYTarantinoLMBulikCM et al The intestinal microbiota in acute anorexia nervosa and during Renourishment: relationship to depression, anxiety, and eating disorder psychopathologyPsychosom Med201577 9 969 981 4643361 https://doi.org/10.1097/PSY.0000000000000247 26428446 https://doi.org/10.1097/PSY.0000000000000247
- SheflinAMMelbyCLCarboneroFWeirTLLinking dietary patterns with gut microbial composition and functionGut Microbes20178 2 113 129 1:CAS:528:DC%2BC2sXlsFSitQ%3D%3D https://doi.org/10.1080/19490976.2016.1270809 27960648 27960648 https://doi.org/10.1080/19490976.2016.1270809
- WuGDChenJHoffmannCBittingerKChenYYKeilbaughSA et al Linking long-term dietary patterns with gut microbial enterotypesScience.2011334 6052 105 108 1:CAS:528:DC%2BC3MXht1Gms77K 3368382 https://doi.org/10.1126/science.1208344 21885731 https://doi.org/10.1126/science.1208344
- BrinkworthGDNoakesMCliftonPMBirdARComparative effects of very low-carbohydrate, high-fat and high-carbohydrate, low-fat weight-loss diets on bowel habit and faecal short-chain fatty acids and bacterial populationsBr J Nutr2009101 10 1493 1502 1:CAS:528:DC%2BD1MXnslSlsLs%3D https://doi.org/10.1017/S0007114508094658 19224658 19224658 https://doi.org/10.1017/S0007114508094658
- DuncanSHBelenguerAHoltropGJohnstoneAMFlintHJLobleyGEReduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in fecesAppl Environ Microbiol200773 4 1073 1078 1:CAS:528:DC%2BD2sXitlyqs7o%3D https://doi.org/10.1128/AEM.02340-06 17189447 17189447 https://doi.org/10.1128/AEM.02340-06
- RussellWRGratzSWDuncanSHHoltropGInceJScobbieL et al High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic healthAm J Clin Nutr201193 5 1062 1072 1:CAS:528:DC%2BC3MXltlCqsbc%3D https://doi.org/10.3945/ajcn.110.002188 https://doi.org/10.3945/ajcn.110.002188
- MageeEARichardsonCJHughesRCummingsJHContribution of dietary protein to sulfide production in the large intestine: an in vitro and a controlled feeding study in humansAm J Clin Nutr200072 6 1488 1494 1:CAS:528:DC%2BD3cXosl2mtrk%3D https://doi.org/10.1093/ajcn/72.6.1488 https://doi.org/10.1093/ajcn/72.6.1488
- RowanFEDochertyNGCoffeyJCO'ConnellPRSulphate-reducing bacteria and hydrogen sulphide in the aetiology of ulcerative colitisBr J Surg200996 2 151 158 1:CAS:528:DC%2BD1MXjsVeqtbg%3D https://doi.org/10.1002/bjs.6454 https://doi.org/10.1002/bjs.6454
- MaNTianYWuYMaXContributions of the interaction between dietary protein and gut microbiota to intestinal healthCurr Protein Pept Sci201718 8 795 808 1:CAS:528:DC%2BC2sXhtVShtL7J https://doi.org/10.2174/1389203718666170216153505 https://doi.org/10.2174/1389203718666170216153505
- ArumugamMRaesJPelletierELe PaslierDYamadaTMendeDR et al Enterotypes of the human gut microbiomeNature.2011473 7346 174 180 1:CAS:528:DC%2BC3MXkvFeisLo%3D 3728647 https://doi.org/10.1038/nature09944 3728647 https://doi.org/10.1038/nature09944
- CosteaPIHildebrandFArumugamMBackhedFBlaserMJBushmanFD et al Enterotypes in the landscape of gut microbial community compositionNat Microbiol20183 1 8 16 1:CAS:528:DC%2BC2sXitVSmtLvK https://doi.org/10.1038/s41564-017-0072-8 https://doi.org/10.1038/s41564-017-0072-8
- KnightsDWardTLMcKinlayCEMillerHGonzalezAMcDonaldD et al Rethinking "enterotypes"Cell Host Microbe201416 4 433 437 1:CAS:528:DC%2BC2cXhs1KltL3N 5558460 https://doi.org/10.1016/j.chom.2014.09.013 5558460 https://doi.org/10.1016/j.chom.2014.09.013
- MacfarlaneGTMacfarlaneSBacteria, colonic fermentation, and gastrointestinal healthJ AOAC Int201295 1 50 60 1:CAS:528:DC%2BC38XjsFSisr8%3D https://doi.org/10.5740/jaoacint.SGE_Macfarlane https://doi.org/10.5740/jaoacint.sge_macfarlane
- RistVTWeissEEklundMMosenthinRImpact of dietary protein on microbiota composition and activity in the gastrointestinal tract of piglets in relation to gut health: a reviewAnimal.20137 7 1067 1078 1:CAS:528:DC%2BC3sXotlelsbc%3D https://doi.org/10.1017/S1751731113000062 https://doi.org/10.1017/S1751731113000062
- McAllanLSkusePCotterPDO'ConnorPCryanJFRossRP et al Protein quality and the protein to carbohydrate ratio within a high fat diet influences energy balance and the gut microbiota in C57BL/6J micePLoS One20149 2 3919831 https://doi.org/10.1371/journal.pone.0088904 1:CAS:528:DC%2BC2cXhsVGqtbzE 3919831 https://doi.org/10.1371/journal.pone.0088904
- TranbergBHellgrenLILykkesfeldtJSejrsenKJeametARuneI et al Whey protein reduces early life weight gain in mice fed a high-fat dietPLoS One20138 8 1:CAS:528:DC%2BC3sXhtlSmtrzL 3735523 https://doi.org/10.1371/journal.pone.0071439 3735523 https://doi.org/10.1371/journal.pone.0071439
- BelobrajdicDPMcIntoshGHOwensJAA high-whey-protein diet reduces body weight gain and alters insulin sensitivity relative to red meat in wistar ratsJ Nutr2004134 6 1454 1458 1:CAS:528:DC%2BD2cXkslyks74%3D https://doi.org/10.1093/jn/134.6.1454 https://doi.org/10.1093/jn/134.6.1454
- TiptonKDWolfeRRProtein and amino acids for athletesJ Sports Sci200422 1 65 79 https://doi.org/10.1080/0264041031000140554 https://doi.org/10.1080/0264041031000140554
- Jalanka-TuovinenJSalonenANikkilaJImmonenOKekkonenRLahtiL et al Intestinal microbiota in healthy adults: temporal analysis reveals individual and common core and relation to intestinal symptomsPLoS One20116 7 1:CAS:528:DC%2BC3MXhtVOrt73P 3145776 https://doi.org/10.1371/journal.pone.0023035 3145776 https://doi.org/10.1371/journal.pone.0023035
- FrankDNSt AmandALFeldmanRABoedekerECHarpazNPaceNRMolecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseasesProc Natl Acad Sci U S A2007104 34 13780 13785 1:CAS:528:DC%2BD2sXpvVGjsbg%3D 1959459 https://doi.org/10.1073/pnas.0706625104 1959459 https://doi.org/10.1073/pnas.0706625104
- FujimotoTImaedaHTakahashiKKasumiEBambaSFujiyamaY et al Decreased abundance of Faecalibacterium prausnitzii in the gut microbiota of Crohn's diseaseJ Gastroenterol Hepatol201328 4 613 619 1:CAS:528:DC%2BC3sXkvFOgt70%3D https://doi.org/10.1111/jgh.12073 https://doi.org/10.1111/jgh.12073
- HolmesELiJVAthanasiouTAshrafianHNicholsonJKUnderstanding the role of gut microbiome-host metabolic signal disruption in health and diseaseTrends Microbiol201119 7 349 359 1:CAS:528:DC%2BC3MXosFagsLo%3D https://doi.org/10.1016/j.tim.2011.05.006 https://doi.org/10.1016/j.tim.2011.05.006
- NegroMGiardinaSMarzaniBMarzaticoFBranched-chain amino acid supplementation does not enhance athletic performance but affects muscle recovery and the immune systemJ Sports Med Phys Fitness200848 3 347 351 1:CAS:528:DC%2BD1cXhsVaitbjF
- van HallGRaaymakersJSSarisWHWagenmakersAJIngestion of branched-chain amino acids and tryptophan during sustained exercise in man: failure to affect performanceJ Physiol1995486 Pt 3 789 794 1156566 https://doi.org/10.1113/jphysiol.1995.sp020854 1156566 https://doi.org/10.1113/jphysiol.1995.sp020854
- NewsholmeEABlomstrandEBranched-chain amino acids and central fatigueJ Nutr2006136 1 Suppl 274S 276S 1:CAS:528:DC%2BD28XivFSitw%3D%3D https://doi.org/10.1093/jn/136.1.274S https://doi.org/10.1093/jn/136.1.274S
- GreerBKWoodardJLWhiteJPArguelloEMHaymesEMBranched-chain amino acid supplementation and indicators of muscle damage after endurance exerciseInt J Sport Nutr Exerc Metab200717 6 595 607 1:CAS:528:DC%2BD1cXitVektA%3D%3D https://doi.org/10.1123/ijsnem.17.6.595 https://doi.org/10.1123/ijsnem.17.6.595
- Moreno-PerezDBressaCBailenMHamed-BousdarSNaclerioFCarmonaM et al Effect of a protein supplement on the gut microbiota of endurance athletes: a randomized, controlledDouble-Blind Pilot Study Nutrients201810 3 337 https://doi.org/10.3390/nu10030337
- WilliamsBAZhangDLisleATMikkelsenDMcSweeneyCSKangS et al Soluble arabinoxylan enhances large intestinal microbial health biomarkers in pigs fed a red meat-containing dietNutrition.201632 4 491 497 1:CAS:528:DC%2BC2MXitV2rs7rE https://doi.org/10.1016/j.nut.2015.10.008 https://doi.org/10.1016/j.nut.2015.10.008
- JagerRShieldsKALoweryRPDe SouzaEOPartlJMHollmerC et al Probiotic Bacillus coagulans GBI-30, 6086 reduces exercise-induced muscle damage and increases recoveryPeerJ.20164 4963221 https://doi.org/10.7717/peerj.2276 1:CAS:528:DC%2BC1cXotl2gtbw%3D 4963221 https://doi.org/10.7717/peerj.2276
- Cronin O, Barton W, Skuse P, Penney NC, Garcia-Perez I, Murphy EF, et al. A Prospective Metagenomic and Metabolomic Analysis of the Impact of Exercise and/or Whey Protein Supplementation on the Gut Microbiome of Sedentary Adults. mSystems. 2018;3(3) https://doi.org/https://doi.org/10.1128/mSystems.00044-18.
- MukhopadhyaISegalJPCardingSRHartALHoldGLThe gut virome: the 'missing link' between gut bacteria and host immunity?Ther Adv Gastroenterol201912 1756284819836620 1:CAS:528:DC%2BB3cXjt1KlsA%3D%3D https://doi.org/10.1177/1756284819836620 https://doi.org/10.1177/1756284819836620
- ButteigerDNHibberdAAMcGrawNJNapawanNHall-PorterJMKrulESSoy protein compared with Milk protein in a Western diet increases gut microbial diversity and reduces serum lipids in Golden Syrian hamstersJ Nutr2016146 4 697 705 1:CAS:528:DC%2BC28Xhs1OntLnO https://doi.org/10.3945/jn.115.224196 26936141 26936141 https://doi.org/10.3945/jn.115.224196
- GentileCLWardEHolstJJAstrupAOrmsbeeMJConnellyS et al Resistant starch and protein intake enhances fat oxidation and feelings of fullness in lean and overweight/obese womenNutr J201514 113 4627411 https://doi.org/10.1186/s12937-015-0104-2 1:CAS:528:DC%2BC28XntVSqtrw%3D 26514213 https://doi.org/10.1186/s12937-015-0104-2
- MartensECMicrobiome: fibre for the futureNature.2016529 7585 158 159 1:CAS:528:DC%2BC28Xns1GqsA%3D%3D https://doi.org/10.1038/529158a 26762451 26762451 https://doi.org/10.1038/529158a
- El KaoutariAArmougomFGordonJIRaoultDHenrissatBThe abundance and variety of carbohydrate-active enzymes in the human gut microbiotaNat Rev Microbiol201311 7 497 504 https://doi.org/10.1038/nrmicro3050 1:CAS:528:DC%2BC3sXptValurc%3D 23748339 23748339 https://doi.org/10.1038/nrmicro3050
- SimpsonHLCampbellBJReview article: dietary fibre-microbiota interactionsAliment Pharmacol Ther201542 2 158 179 1:CAS:528:DC%2BC2MXhtVKntbvK 4949558 https://doi.org/10.1111/apt.13248 26011307 https://doi.org/10.1111/apt.13248
- TapJFuretJPBensaadaMPhilippeCRothHRabotS et al Gut microbiota richness promotes its stability upon increased dietary fibre intake in healthy adultsEnviron Microbiol201517 12 4954 4964 1:CAS:528:DC%2BC28XjtVOntA%3D%3D https://doi.org/10.1111/1462-2920.13006 26235304 26235304 https://doi.org/10.1111/1462-2920.13006
- O'KeefeSJLiJVLahtiLOuJCarboneroFMohammedK et al Fat, fibre and cancer risk in African Americans and rural AfricansNat Commun20156 6342 1:CAS:528:DC%2BC2MXhtF2ksrbL 4415091 https://doi.org/10.1038/ncomms7342 25919227 https://doi.org/10.1038/ncomms7342
- CrampTBroadEMartinDMeyerBJEffects of preexercise carbohydrate ingestion on mountain bike performanceMed Sci Sports Exerc200436 9 1602 1609 1:CAS:528:DC%2BD2cXnt12itrw%3D https://doi.org/10.1249/01.MSS.0000139805.91675.5B 15354044 15354044 https://doi.org/10.1249/01.mss.0000139805.91675.5b
- JacobsKAShermanWMThe efficacy of carbohydrate supplementation and chronic high- carbohydrate diets for improving endurance performanceInt J Sport Nutr19999 1 92 115 1:CAS:528:DyaK1MXitVShsbc%3D https://doi.org/10.1123/ijsn.9.1.92 10200063 10200063 https://doi.org/10.1123/ijsn.9.1.92
- GorvitovskaiaAHolmesSPHuseSMInterpreting Prevotella and Bacteroides as biomarkers of diet and lifestyleMicrobiome.20164 15 4828855 https://doi.org/10.1186/s40168-016-0160-7 27068581 https://doi.org/10.1186/s40168-016-0160-7
- LimMYRhoMSongYMLeeKSungJKoGStability of gut enterotypes in Korean monozygotic twins and their association with biomarkers and dietSci Rep20144 7348 1:CAS:528:DC%2BC2MXktlOju7s%3D 4258686 https://doi.org/10.1038/srep07348 25482875 https://doi.org/10.1038/srep07348
- NakayamaJWatanabeKJiangJMatsudaKChaoSHHaryonoP et al Diversity in gut bacterial community of school-age children in AsiaSci Rep20155 8397 1:CAS:528:DC%2BC2MXhtFKhurnK 4336934 https://doi.org/10.1038/srep08397 25703686 https://doi.org/10.1038/srep08397
- De FilippoCCavalieriDDi PaolaMRamazzottiMPoulletJBMassartS et al Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural AfricaProc Natl Acad Sci U S A2010107 33 14691 14696 2930426 https://doi.org/10.1073/pnas.1005963107 20679230 https://doi.org/10.1073/pnas.1005963107
- LiuYZhangLWangXWangZZhangJJiangR et al Similar fecal microbiota signatures in patients with diarrhea-predominant irritable bowel syndrome and patients with depressionClin Gastroenterol Hepatol201614 11 1602 11.e5 https://doi.org/10.1016/j.cgh.2016.05.033 27266978 27266978 https://doi.org/10.1016/j.cgh.2016.05.033
- Moreno-IndiasISanchez-AlcoholadoLGarcia-FuentesECardonaFQueipo-OrtunoMITinahonesFJInsulin resistance is associated with specific gut microbiota in appendix samples from morbidly obese patientsAm J Transl Res20168 12 5672 5684 1:CAS:528:DC%2BC1cXhtF2ntrnP 5209518 28078038
- MichailSLinMFreyMRFanterRPaliyOHilbushB et al Altered gut microbial energy and metabolism in children with non-alcoholic fatty liver diseaseFEMS Microbiol Ecol201591 2 1 9 https://doi.org/10.1093/femsec/fiu002 1:CAS:528:DC%2BC2sXht1CrurzL 25764541 25764541 https://doi.org/10.1093/femsec/fiu002
- LiJZhaoFWangYChenJTaoJTianG et al Gut microbiota dysbiosis contributes to the development of hypertensionMicrobiome.20175 1 14 5286796 https://doi.org/10.1186/s40168-016-0222-x 28143587 https://doi.org/10.1186/s40168-016-0222-x
- ChenWLiuFLingZTongXXiangCHuman intestinal lumen and mucosa-associated microbiota in patients with colorectal cancerPLoS One20127 6 1:CAS:528:DC%2BC38XpvVWrtr4%3D 3386193 https://doi.org/10.1371/journal.pone.0039743 22761885 https://doi.org/10.1371/journal.pone.0039743
- PrecupGVodnarDCGut Prevotella as a possible biomarker of diet and its eubiotic versus dysbiotic roles: a comprehensive literature reviewBr J Nutr2019122 2 131 140 1:CAS:528:DC%2BC1MXhs1ajtL%2FF https://doi.org/10.1017/S0007114519000680 30924428 30924428 https://doi.org/10.1017/S0007114519000680
- ThomasDTErdmanKABurkeLMAmerican College of Sports Medicine joint position statement. Nutrition and athletic performanceMed Sci Sports Exerc201648 3 543 568 1:CAS:528:DC%2BC28XjtFKgtLk%3D https://doi.org/10.1249/MSS.0000000000000852 26891166 26891166 https://doi.org/10.1249/MSS.0000000000000852
- JeukendrupAETraining the gut for athletesSports Med201747 Suppl 1 101 110 5371619 https://doi.org/10.1007/s40279-017-0690-6 28332114 https://doi.org/10.1007/s40279-017-0690-6
- TodenSBirdARToppingDLConlonMAResistant starch prevents colonic DNA damage induced by high dietary cooked red meat or casein in ratsCancer Biol Ther20065 3 267 272 1:CAS:528:DC%2BD28XntlWkurY%3D https://doi.org/10.4161/cbt.5.3.2382 16410726 16410726 https://doi.org/10.4161/cbt.5.3.2382
- SamuelBSHansenEEManchesterJKCoutinhoPMHenrissatBFultonR et al Genomic and metabolic adaptations of Methanobrevibacter smithii to the human gutProc Natl Acad Sci U S A2007104 25 10643 10648 1:CAS:528:DC%2BD2sXnt1OmtL0%3D 1890564 https://doi.org/10.1073/pnas.0704189104 17563350 https://doi.org/10.1073/pnas.0704189104
- CanforaEEJockenJWBlaakEEShort-chain fatty acids in control of body weight and insulin sensitivityNat Rev Endocrinol201511 10 577 591 1:CAS:528:DC%2BC2MXhtlGgtL3E https://doi.org/10.1038/nrendo.2015.128 26260141 26260141 https://doi.org/10.1038/nrendo.2015.128
- RoelofsenHPriebeMGVonkRJThe interaction of short-chain fatty acids with adipose tissue: relevance for prevention of type 2 diabetesBenefic Microbes20101 4 433 437 1:CAS:528:DC%2BC3MXhsFGru7nF https://doi.org/10.3920/BM2010.0028 https://doi.org/10.3920/BM2010.0028
- KajiIKarakiSKuwaharaAShort-chain fatty acid receptor and its contribution to glucagon-like peptide-1 releaseDigestion.201489 1 31 36 1:CAS:528:DC%2BC2cXhs1Chu7s%3D https://doi.org/10.1159/000356211 24458110 24458110 https://doi.org/10.1159/000356211
- AstburySMCorfeBMUptake and metabolism of the short-chain fatty acid butyrate, a critical review of the literatureCurr Drug Metab201213 6 815 821 1:CAS:528:DC%2BC38XhtVOhur3O https://doi.org/10.2174/138920012800840428 22571479 22571479 https://doi.org/10.2174/138920012800840428
- den BestenGBleekerAGerdingAvan EunenKHavingaRvan DijkTH et al Short-chain fatty acids protect against high-fat diet-induced obesity via a PPARgamma-dependent switch from lipogenesis to fat oxidationDiabetes.201564 7 2398 2408 https://doi.org/10.2337/db14-1213 1:CAS:528:DC%2BC2MXhtFynsrrM https://doi.org/10.2337/db14-1213
- CaesarRTremaroliVKovatcheva-DatcharyPCaniPDBackhedFCrosstalk between gut microbiota and dietary lipids aggravates WAT inflammation through TLR signalingCell Metab201522 4 658 668 1:CAS:528:DC%2BC2MXhsVajs73I 4598654 https://doi.org/10.1016/j.cmet.2015.07.026 26321659 https://doi.org/10.1016/j.cmet.2015.07.026
- Murtaza N, Burke LM, Vlahovich N, Charlesson B, H ON, Ross ML, et al. The Effects of Dietary Pattern during Intensified Training on Stool Microbiota of Elite Race Walkers. Nutrients. 2019;11(2) https://doi.org/https://doi.org/10.3390/nu11020261.
- SokolHPigneurBWatterlotLLakhdariOBermudez-HumaranLGGratadouxJJ et al Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patientsProc Natl Acad Sci U S A2008105 43 16731 16736 1:CAS:528:DC%2BD1cXhtleks7%2FI 2575488 https://doi.org/10.1073/pnas.0804812105 18936492 https://doi.org/10.1073/pnas.0804812105
- FiorucciSDistruttiEBile acid-activated receptors, intestinal microbiota, and the treatment of metabolic disordersTrends Mol Med201521 11 702 714 1:CAS:528:DC%2BC2MXhs1Sht7nP https://doi.org/10.1016/j.molmed.2015.09.001 26481828 26481828 https://doi.org/10.1016/j.molmed.2015.09.001
- Lopez-SilesMKhanTMDuncanSHHarmsenHJGarcia-GilLJFlintHJCultured representatives of two major phylogroups of human colonic Faecalibacterium prausnitzii can utilize pectin, uronic acids, and host-derived substrates for growthAppl Environ Microbiol201278 2 420 428 1:CAS:528:DC%2BC38XnvFOrsA%3D%3D 3255724 https://doi.org/10.1128/AEM.06858-11 22101049 https://doi.org/10.1128/AEM.06858-11
- BurkeLMHawleyJAJeukendrupAMortonJPStellingwerffTMaughanRJToward a common understanding of diet-exercise strategies to manipulate fuel availability for training and competition preparation in endurance sportInt J Sport Nutr Exerc Metab201828 5 451 463 https://doi.org/10.1123/ijsnem.2018-0289 30249148 30249148 https://doi.org/10.1123/ijsnem.2018-0289
- KozichJJWestcottSLBaxterNTHighlanderSKSchlossPDDevelopment of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platformAppl Environ Microbiol201379 17 5112 5120 1:CAS:528:DC%2BC3sXhtlSgu73L 3753973 https://doi.org/10.1128/AEM.01043-13 23793624 https://doi.org/10.1128/AEM.01043-13
- RevickiDAWoodMWiklundICrawleyJReliability and validity of the gastrointestinal symptom rating scale in patients with gastroesophageal reflux diseaseQual Life Res19987 1 75 83 1:STN:280:DyaK1c7kt1WmsA%3D%3D https://doi.org/10.1023/A:1008841022998 9481153 9481153 https://doi.org/10.1023/a:1008841022998
- BlakeMRRakerJMWhelanKValidity and reliability of the Bristol stool form scale in healthy adults and patients with diarrhoea-predominant irritable bowel syndromeAliment Pharmacol Ther201644 7 693 703 1:STN:280:DC%2BC2s3nvFegsQ%3D%3D https://doi.org/10.1111/apt.13746 27492648 27492648 https://doi.org/10.1111/apt.13746
- CardonaSEckACassellasMGallartMAlastrueCDoreJ et al Storage conditions of intestinal microbiota matter in metagenomic analysisBMC Microbiol201212 158 1:CAS:528:DC%2BC3sXjsFWhsw%3D%3D 3489833 https://doi.org/10.1186/1471-2180-12-158 22846661 https://doi.org/10.1186/1471-2180-12-158
- RoeschLFCasellaGSimellOKrischerJWasserfallCHSchatzD et al Influence of fecal sample storage on bacterial community diversityOpen Microbiol J20093 40 46 2681173 https://doi.org/10.2174/1874285800903010040 19440250 https://doi.org/10.2174/1874285800903010040
- LiFHullarMALampeJWOptimization of terminal restriction fragment polymorphism (TRFLP) analysis of human gut microbiotaJ Microbiol Methods200768 2 303 311 1:CAS:528:DC%2BD2sXhtVCgsrw%3D https://doi.org/10.1016/j.mimet.2006.09.006 17069911 17069911 https://doi.org/10.1016/j.mimet.2006.09.006
- DebeliusJSongSJVazquez-BaezaYXuZZGonzalezAKnightRTiny microbes, enormous impacts: what matters in gut microbiome studies?Genome Biol201617 1 217 5072314 https://doi.org/10.1186/s13059-016-1086-x 27760558 https://doi.org/10.1186/s13059-016-1086-x
- Liang Y, Dong T, Chen M, He L, Wang T, Liu X, et al. Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles. mSphere. 2020;5(1) https://doi.org/https://doi.org/10.1128/mSphere.00763-19.