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The Nutrition-Microbiota-Physical Activity Triad: An Inspiring New Concept for Health and Sports Performance

Nathalie Boisseau
Nicolas Barnich
2 and
Christelle Koechlin-Ramonatxo
Laboratoire des Adaptations Métaboliques à l’Exercice en Conditions Physiologiques et Pathologiques (AME2P), Université Clermont Auvergne, CRNH Auvergne, 63000 Clermont-Ferrand, France
M2iSH, UMR 1071 Inserm, USC-INRAE 2018, Microbes, Intestin, Inflammation et Susceptibilité de l’Hôte (M2iSH), Université Clermont Auvergne, CRNH Auvergne, 63000 Clermont-Ferrand, France
DMEM, Université de Montpellier, INRAE, 34000 Montpellier, France
Author to whom correspondence should be addressed.
Nutrients 2022, 14(5), 924;
Submission received: 25 January 2022 / Revised: 10 February 2022 / Accepted: 16 February 2022 / Published: 22 February 2022
(This article belongs to the Special Issue Exercise, Microbiota, Health and Performance)


The human gut microbiota is currently the focus of converging interest in many diseases and sports performance. This review presents gut microbiota as a real “orchestra conductor” in the host’s physio(patho)logy due to its implications in many aspects of health and disease. Reciprocally, gut microbiota composition and activity are influenced by many different factors, such as diet and physical activity. Literature data have shown that macro- and micro-nutrients influence gut microbiota composition. Cumulative data indicate that gut bacteria are sensitive to modulation by physical activity, as shown by studies using training and hypoactivity models. Sports performance studies have also presented interesting and promising results. Therefore, gut microbiota could be considered a “pivotal” organ for health and sports performance, leading to a new concept: the nutrition-microbiota-physical activity triad. The next challenge for the scientific and medical communities is to test this concept in clinical studies. The long-term aim is to find the best combination of the three elements of this triad to optimize treatments, delay disease onset, or enhance sports performance. The many possibilities offered by biotic supplementation and training modalities open different avenues for future research.

1. Introduction

It has been suspected that gut microbiota may have a role in health and sports performance for a very long time. The massive sequencing of gut microbiota specimens in the 2010s, thanks to the technological advancements in high-throughput sequencing and bioinformatics analyses, and more recently, the development of methods to quantify different microbial metabolites, allowed population-level studies to be carried out on the human microbiota. Their findings help to better understand the microbiota’s role in physiology, its functional imbalance in various chronic pathologies [1], and its implications in athletic performance. In addition, mechanistic studies with gnotobiotic model organisms have brought novel insights into the underlying molecular mechanisms and can be used to test strategies to modulate the gut microbiota composition. In this review, we first summarize the knowledge on the mechanisms underlying the implications of gut microbiota in various chronic pathologies and sports performance. Then, we focus on the combination of physical activity and nutritional interventions to modulate gut microbiota composition in the context of health and performance. Our hypothesis is that the interaction of their underlying mechanisms might potentiate their effects. This new knowledge could be used to develop strategies (i.e., diet changes, supplementation, physical activity programs) to modulate the gut microbiota with the ultimate aim of preventing and/or treating various pathologies or improving performance in elite athletes.

2. Gut Microbiota: What Is It?

The term intestinal (or gut) microbiota describes the different microorganisms that live in the digestive tract. Natural microbiotas can also be found in other areas of the body, such as the skin, urogenital system and respiratory system; however, the gut microbiota is the densest and most studied. Since its first description by Antonie van Leeuwenhoek, who, in 1681, observed under the microscope more than 1000 “animalcules” in his feces, evidence about its essential role in human health has been accumulating [2].
The gut microbiota is mainly composed of bacteria (1013 bacteria), but eukaryotes (fungi and protozoa) and archaea are found occasionally. Similarly, viruses that infect bacteria (called “phages”) are frequently detected in the microbiota. They can modify the abundance, genetic profile and gene expression of bacterial populations. Thus, the “virome” is undoubtedly another piece in the puzzle of gut microbiota physiopathology. The characterization of the genome of all microorganisms found in the intestine (the intestinal metagenome) by high-throughput sequencing identified thousands of different species, mostly bacteria, and over 3 million genes, which correspond to 150 times the human genome [1,3,4,5]. The gut microbiota can reach up to 1.5 kg in a 70 kg individual [6]. Like the fingerprints, the intestinal microbiota is unique to each individual in terms of quality and quantity. Among the 160 species of bacteria that correspond to the average microbiota of a healthy individual, only half are commonly found in different individuals, and only 15 to 20 species are present in all human beings. These species are in charge of the essential functions of the microbiota. Indeed, although the microbiome composition varies among individuals, metabolic functions are incredibly stable and conserved [7].
The gut microbiota density varies along the gastrointestinal (GI) tract. It is fairly low in the stomach, duodenum and jejunum and increases in the ileum and colon. The stomach is characterized by the presence of oxygen and high acidity. It selectively hosts acid-tolerant and facultative anaerobic microorganisms, such as lactobacilli, streptococci and yeast species. In the small intestine, the microbiota is mainly composed of facultative anaerobic bacteria (e.g., Lactobacilli, Streptococci and Enterobacteria) and strict anaerobic bacteria (Bifidobacteria, Bacteroides and Clostridia). In the colon, the slower intestinal peristalsis and anaerobiosis favor the encroachment of a complex microbiota with the highest bacterial diversity (more than 1000 bacterial species) and density [8,9]. Two bacterial phyla account for 80–90% of the bacterial population in the colon: Firmicutes and Bacteroidetes [10,11,12,13]. Proteobacteria and Actinobacteria are minority phyla. Overall, in human adults, the dominant bacterial genera are Bacteroides, Eubacterium, Ruminococcus, Clostridium, and Bifidobacterium. The intestinal microbiota composition also varies according to the species and within the same GI segment between the near-mucosal compartment and the digesta/stool. For instance, in the colon, Firmicutes of the Lachnospiraceae and Ruminococcaceae families predominate in the near-mucosal compartment, whereas Bacteroidetes of the Bacteroidaceae, Prevotellaceae, and Rikenellaceae families are preponderant in the digesta/stool [14]. Murine models are widely used in basic/preclinical research, but the taxonomic differences between human and mouse microbiota do not always allow the transfer of the acquired data to the clinic [15].
The gut microbiota, often described as the “forgotten organ,” has many beneficial functions in the organism when it is in symbiosis with the host [6]. The microorganisms in the microbiota play a direct role in digestion, for instance, by ensuring the fermentation of substrates and non-digestible food residues, by facilitating the nutrient assimilation thanks to a set of enzymes that are not present in human cells, and by participating in the synthesis of some vitamins. They also influence the overall functioning of the GI tract and participate in the functioning of the intestinal immune system, which is essential for the intestinal wall barrier function. The host-microbiota symbiotic interactions reflect their co-evolution with reciprocal benefits. In conclusion, the human gut microbiota is a complex ecosystem that is different from that of other microbiota types in the human body [7]. It has adapted to local environmental constraints through mechanisms of co-evolution between microorganisms and hosts. Due to the complexity of this ecosystem and of its functions, host-microbiota interactions represent a fragile equilibrium that can be disrupted in many pathologies.

3. Gut Microbiota in Health and Disease

Locally, the gut microbiota is involved in the intestinal homeostasis by participating, for example, in the barrier function, extraction of nutrients from the diet, and conjugation of bile acids. However, its contribution is not limited to the intestine but also concerns, among others, the metabolism, immune system and immune responses [16,17]. The intestinal microbiota contribution to our health is becoming increasingly well known. Besides its homeostatic role, changes in the microbiota composition, called dysbiosis, are implicated in the establishment and chronicity of various pathologies, such as chronic inflammatory bowel disease (IBD), irritable bowel syndrome, colorectal cancer, metabolic diseases (type 2 diabetes, obesity), depression, and cardiovascular diseases [18] (Figure 1). Dysbiosis, i.e., the qualitative and/or functional alteration of the intestinal microbiota, can contribute to the etiology of some diseases, especially those in which autoimmune or inflammatory mechanisms are implicated.
The intestinal microbiota plays a role in the natural inflammation observed in the digestive tract. Inflammation is an important biological process closely related to immunity. A physiological low inflammation level is essential for immune activation and allows the microbiota to be controlled. Conversely, important inflammatory reactions are triggered by the presence of pathogenic species [19,20] through a mechanism based on the presence of inflammatory bacterial components, such as lipopolysaccharides (LPS) on the surface of Gram-negative bacteria. These antigens induce an immune response that leads to the production of pro-inflammatory mediators (cytokines) by macrophages in the intestine. Local inflammation is triggered, and the intestinal wall permeability increases. LPS can then pass through the intestinal wall, enter the bloodstream, and cause systemic inflammation in other target tissues [21].

3.1. A Clear Link with GI Diseases

Chronic IBDs, such as Crohn’s disease and ulcerative colitis, are the consequence of the inappropriate activation of the immune system in the intestine. The intestinal microbiota may be implicated because symptoms improve in patients undergoing antibiotic treatment and because inflammatory intestinal lesions disappear in people whose intestinal wall is no longer in contact with the feces (following the installation of fecal diversion) [22]. This is probably due to the role of intestinal bacteria and their metabolites in the local immune response balance [23]. In terms of microbiota composition, the abundance of bacteria belonging to the phylum Firmicutes is decreased, whereas that of bacteria belonging to the phylum Proteobacteria is increased [24]. Faecalibacterium prausnitzii, one of the dominant bacteria in the Firmicutes phylum and in the human intestinal microbiota, appears to be particularly decreased in patients with IBD, especially Crohn’s disease, and its level is predictive of the risk of relapse [25,26]. Furthermore, in patients with IBD, dysbiosis may favor the colonization by and growth of potentially pathogenic and pro-inflammatory microorganisms. Several microorganisms have been implicated in Crohn’s disease: Candida albicans, Listeria monocytogenes, Mycobacterium avium subspecies paratuberculosis, enterotoxin-producing Bacteroides fragilis, and adherent and invasive Escherichia coli [27,28,29].

3.2. Cancer

Normally, there is a balance between microbiota quality, immune system efficiency, and intestinal barrier integrity. Dysbiosis can promote cancer onset and/or progression through different mechanisms:
  • (i) The presence of specific microorganisms or of intestinal dysbiosis has been associated with some tumors. First, the pathogen can cause DNA lesions, for example, through the production of genotoxins, as reported for Helicobacter pylori, a bacterium that increases the risk of gastric cancer [30,31], and colibactin-producing E. coli, a bacterium that increases the risk of colorectal cancer [32,33,34]. Second, the microbiota imbalance favors some species (Fusobacterium) that can abnormally stimulate oncogenic pathways, such as the beta-catenin signaling pathway [35];
  • (ii) The close interaction between microbiota and local immunity [36,37]. Several pro-inflammatory or immunosuppressive signaling pathways are activated in the presence of dysbiosis. Moreover, dysbiosis increases intestinal permeability, allowing the passage of oncogenic compounds from the intestinal lumen into the body;
  • (iii) Microbiota anomalies might lead to the induction of genes linked to cancer cell survival [32], thus promoting tumor progression;
  • (iv) More recently, bacteria have been identified within tumors. Understanding their nature, origin, and influence on cancer development/progression may provide new therapeutic avenues [38]

3.3. Metabolic and Cardiovascular Diseases

Cardiovascular and cerebrovascular diseases (e.g., atherosclerosis, hypertension, stroke) and metabolic diseases (diabetes, obesity) have multifactorial (genetic, nutritional and environmental) origins. The role of each of these factors varies from one individual to another, and the implicated molecular mechanisms remain to be precisely described. However, it is becoming increasingly clear that the intestinal microbiota plays a role in their genesis [39]. For instance, upon fecal transplantation of microbiota from obese mice, axenic (i.e., germ-free) mice significantly and rapidly gain weight [40]. Several mechanisms could be at the origin of these relationships. In diabetes and obesity, chronic inflammation is favored by the higher percentage of fat in the diet that increases the proportion of Gram-negative bacteria in the intestine, thus increasing the local level of inflammatory LPS. LPS can pass in the bloodstream and reach other organs/tissues (e.g., liver, fat, muscle), where they favor the installation of low chronic inflammation that will promote the development of insulin resistance, a prerequisite for diabetes and obesity [41].
In addition, some bacterial metabolites might have a determining role in the development of cardiometabolic diseases, such as type 2 diabetes, atherosclerosis and arterial hypertension. The most convincing findings concern trimethylamine. This waste product produced by the microbiota can pass into the bloodstream. It is then oxidized by the liver to trimethylamine-N-oxide, a substance that promotes the formation of atherosclerotic plaques [42,43].

3.4. Brain

The nervous system that regulates the intestine (enteric nervous system, ENS) contains about 200 million neurons. Its primary function is to ensure intestinal motricity. Furthermore, the intestine is in close and bidirectional interaction with the central nervous system (CNS). This explains why the ENS is referred to as the second brain. A microbiota imbalance could modify the information transmitted to the CNS and ENS, thus altering the functioning of both organs [44]. Multiple mechanisms may be involved. Compounds from the microbiota (metabolites or structural elements) can diffuse through the intestinal wall and directly modulate the ENS. This affects the functioning of the intestine, the vagus nerve, and, indirectly, the brain. These compounds can also directly reach the CNS via the bloodstream. In the brain, they can negatively affect some functions directly or after metabolization. Finally, bacteria can indirectly modulate some endocrine functions that are controlled by the CNS by interacting with enteroendocrine cells located in the gut and linked to the brain, as described for the serotonin pathway [45,46]. These data support the hypothesis that the intestinal dysbiosis observed in neurodevelopmental disorders and neurodegenerative diseases, such as Parkinson’s and Alzheimer’s disease, may contribute not only to the digestive disorders described in these patients but also to their neurological symptoms.

3.5. Towards Individualized Treatments

Trials in patients with obesity, metabolic syndrome, or Crohn’s disease have shown that fecal transplantation improves some biological parameters, but the effect remains very modest [47,48]. Therefore, it has been proposed that research should focus on developing personalized interventions adapted to each patient’s condition and microbiota characteristics. For instance, as microbiota may synergize with some drugs, particularly anti-cancer compounds, these drugs could be combined with interventions to restore the proper microbiota functioning (e.g., probiotics, fecal transplantation, metabolites) [49,50]. In the near future, predictive tests of the patients’ response to a given treatment may be developed based on their microbiota analysis. In this context, it is essential to study the factors that influence the human gut microbiota composition, particularly diet and physical activity.
Take home messages, as well challenges and future directions dealing with the human microbiota in health and disease are summarized in the Box 1.
Box 1. The Human Microbiota in Health and Disease.
The gut microbiota is a real “orchestra conductor” in the host’s physio(patho)logy.
Dysbiosis is observed and is implicated in many chronic diseases.
Microbiota may synergize with some drugs and modulate their efficacy in chronic diseases.
Future microbiota-based tests to predict each patient’s response to a drug.
Studies on diet and physical activity, as gut microbiota composition regulators, are needed.

4. Diet Influences the Gut Microbiota Composition

The intestinal microbiota and the associated metabolic products interact with the host in many different ways, influencing gut homoeostasis and health outcomes. Studies in mice and humans suggest that the modern Western lifestyle, particularly the high-fat and/or high-sugar diets, can persistently alter commensal microbial communities, leading to microbial disturbances. This favors pathogen susceptibility [51], obesity [40,52], auto-inflammatory diseases [53], and other pathologies. Diet might explain more than 50% of the microbial structural changes in mice and 20% in humans, highlighting the potential of dietary strategies in the management of metabolic diseases through gut microbiota modulation [54,55]. Normally, the human microbiota remains stable for months and possibly for years [56]. In humans, short-term dietary interventions can rapidly modify microbiota diversity, but these changes are only transient [57].
The amount, type, and balance of the main dietary macronutrients (fat, proteins, and carbohydrates) greatly influence the intestinal microbiota.

4.1. Fats

Consumption of a high-fat diet (HFD) significantly reduces the fecal concentration of short-chain fatty acids (SCFA), including butyrate, and of Bifidobacteria, compared with a low-fat diet (Brinkworth et al., 2009). Moreover, several human studies demonstrated that HFDs increase the total anaerobic microflora and Bacteroides [58,59,60,61]. However, by definition, in HFDs, the carbohydrate amount in the total energy intake is decreased. Therefore, it is not clear whether microbiota composition and metabolism are mainly influenced by elevated fat or reduced carbohydrate content. In addition, more than their amount, the fat quality plays an important role in the gut microbiota composition. For example, HFDs are mainly composed of n-6 polyunsaturated fatty acids (PUFAs), often at the expense of n-3 PUFAs that have anti-inflammatory properties and modulate the intestinal microbiota in a beneficial way [62,63,64,65,66].

4.2. Proteins

Numerous studies have demonstrated that protein consumption positively correlates with overall microbial diversity [57,67]. For example, whey and glycated pea protein supplementation for a few days increases the commensal Bifidobacterium and Lactobacillus and decreases the pathogenic B. fragilis and Clostridium perfringens in the human gut [68,69]. Furthermore, pea protein consumption stimulates SCFA production in the intestine, leading to anti-inflammatory effects and mucosal barrier maintenance [70]. Conversely, a recent systematic review showed that short-term (1 to 4 weeks) beef intake has little or no effect on microbial profiles in humans [71]. However, when consumed at higher than recommended amounts, as part of a diet rich in sugar or fat, beef negatively affects the gut microbiota [71].

4.3. Carbohydrates

Modulation of the amount and/or type of carbohydrates in the diet for more than 4 weeks can alter the human gut microbiota and its metabolic products [72,73]. Carbohydrates can be subdivided into two categories: digestible and non-digestible. Digestible carbohydrates include starches and sugars (e.g., glucose, fructose, sucrose, and lactose) that are degraded in the small intestine by different enzymes. Upon digestion, they release glucose in the bloodstream and stimulate insulin production. Humans consume high amounts of glucose, fructose, and sucrose that increase the relative abundance of Bifidobacteria and reduce Bacteroides [74]. Non-digestible carbohydrates, such as fibers and resistant starch (RS), are not enzymatically degraded in the small intestine. Currently, four RS types (RS1-RS4) are recognized and may affect the bacterial composition differently [75]. Starch is a complex polysaccharide consisting of a mixture of amylose and amylopectin. The relative proportion of amylose and amylopectin affects the capacity of bacterial species to use different starch types for growth [76]. Dietary fibers, functionally known as microbiota-accessible carbohydrates, are present in inadequate amounts in Western diets [77]. As microbiota-accessible carbohydrates are the main source of energy for gut bacteria, their abundance and variety can influence gut microbiota composition and function [74]. Therefore, fibers should be considered prebiotics, which by definition are non-digestible dietary components that bring benefit to the host health via selective stimulation of the growth and/or activity of some microorganisms.

4.4. Prebiotics

In recent years, many researchers have tried to elucidate the relationship between prebiotics and human health [78]. Prebiotics can be metabolized by the intestinal microbiota. Moreover, their degradation products are SCFAs that are released in the blood, thus influencing not only the GI tract but also other distant organs [78]. Prebiotics include soybeans, inulins, unrefined wheat and barley, raw oats, and non-digestible oligosaccharides, such as fructans, polydextrose, fructo-oligosaccharides, galacto-oligosaccharides, xylo-oligosaccharides, and arabino-oligosaccharides. Fructo-oligosaccharides and galacto-oligosaccharides are two important groups of prebiotics with beneficial effects on human health [78]. A low fiber/prebiotic diet reduces the total bacterial abundance [79]. Moreover, prebiotics are routinely screened for their ability to selectively promote Bifidobacterial growth [74]. For more information on how prebiotics modulate the gut microbiota, the reader can refer to the recent review by Davani-Davari et al. [78].

4.5. Probiotics

Probiotics are live microorganisms that, when administered in adequate amounts, confer a health benefit to the host. Their effects on the gut and immune system are the most researched applications [80]. For example, fermented foods containing lactic acid bacteria, such as milk products and yogurt, represent a source of ingestible microorganisms that may beneficially regulate intestinal health and even treat or prevent IBDs [81]. Lactobacillus, Bifidobacterium and Saccharomyces strains have been safely and effectively used as probiotics for a long time. Roseburia spp., Akkermansia spp., Propionibacterium spp. And Faecalibacterium spp. are also promising probiotic microorganisms [82]. Research on the mechanisms of probiotic effects is mainly based on in vitro and animal models. However, the results cannot always be translated to humans, for instance, regarding probiotics for Crohn’s disease and mental health (see Jäger et al. and Sanders et al. for reviews) [80,82].

4.6. Bioactive Non-Nutrient Plant Compounds

Some bioactive non-nutrient compounds present in fruits, vegetables, grains, and other plants have been linked to a reduction in the risk of major chronic diseases [83]. These plant compounds include prebiotics and probiotics, as well as several chemical compounds, such as polyphenols (the largest group) and derivatives, carotenoids, and thiosulfates. Polyphenols can be subclassified into four main groups: flavonoids (including eight subgroups), phenolic acids (e.g., curcumin), stilbenoids (e.g., resveratrol), and lignans [84]. They promote health by limiting oxidative stress [85]. Common polyphenol-rich food types include fruits, seeds, vegetables, tea, cocoa products, and wine. The relative abundance of Bacteroides is increased in people consuming red wine polyphenols [86]. Moreover, it has been reported that the abundance of pathogenic Clostridium species (C. perfringens and C. histolyticum) is reduced after regular consumption of fruit, seed, wine, and tea polyphenols [74]. In a recent review, Rajha et al. showed that polyphenol metabolites interact with gut microbiota and mitochondria to fight many diseases, such as obesity, depression, inflammation and allergy [85].

4.7. Vitamins

Some vitamins are directly produced by the gut microbiota, and others play a role in modulating the presence of beneficial/detrimental bacterial species. Specifically, vitamin A can modulate health-beneficial microbes of the Bifidobacterium, Lactobacillus and Akkermansia genera [87,88]. Some B-complex vitamins are produced by gut commensals, and some of them contribute to increasing the virulence/colonization of potentially pathogenic microbes [88]. Vitamin C, D, and E supplementation may alter the microbiota composition by increasing the concentration of beneficial species, such as Bifidobacterium and Lactobacillus. Thus, vitamin intake could have a significant role in modulating gut microbiota. Moreover, this effect might depend on the host’s pre-supplementation vitamin level. However, clinical trials are still necessary to avoid adverse effects due to excess vitamin intake.

5. Potential Links between Gut Microbiome and Physical Fitness/Sports Performance

5.1. The Athletes’ Gut Microbiota, a Specialized Microbiota?

It is acknowledged that gut microbiota changes depend on individual factors, particularly in athletes, including energy expenditure, diet, drug intake (especially antibiotics) [89]. Many data on the gut microbiota composition in athletes are now available. As research in this field is rapidly expanding, the latest advances and major questions are summarized in several reviews [80,90,91,92,93,94,95] (Figure 2).
The analysis of literature data on this topic shows that the gut microbiota of athletes/exercised people is different from that of other populations and displays higher microbial diversity (Table 1). In 2014, Clarke et al. were the first to demonstrate that microbial diversity is increased in elite rugby players compared with matched controls. Specifically, the abundance of the phylum Bacteriodetes was decreased, whereas that of the genus Akkermensia was increased in athletes with low body mass index (BMI) (<25 kg/m2) compared with the high BMI (>28 kg/m2) group [96]. Moreover, Estaki et al. showed that peak oxygen uptake (VO2peak), the gold standard measure of cardiorespiratory fitness, can account for more than 20% of the variation in taxonomic richness in healthy men and women, after adjusting for all other factors, including diet [97]. Indeed, the abundance of key butyrate-producing taxa (Clostridiales, Roseburia, Lachnospiraceae, and Erysipelotrichaceae) was increased in individuals with high VO2peak values. The next step was to investigate whether the gut microbiota in athletes presents a specific composition in the function of the sports discipline. In 2019, Scheiman et al. generated much attention [98] by showing that the relative abundance of Veillonella was increased after a marathon and that the inoculation of a strain of Veillonella atypica from runner stool samples into mice significantly increased exhaustive treadmill run time in the inoculated animals. They also demonstrated a mechanistic link with lactate metabolism [98]. These results led to comparisons of the gut microbiota composition of athletes from different sports disciplines. The recent reviews by Mohr et al. in 2020 and by Aya et al. in 2021 concluded that in most cases, the gut microbiota α and β diversity are not different among sports disciplines, but some differences can be highlighted in the prevalence of some genera or taxa [90,95]. For example, O’Donovan et al., using shotgun metagenomic sequencing of fecal samples from elite athletes in 16 different sports, concluded that microbial diversity does not differ among sport disciplines [99]. However, they observed greater abundance of Bifidobacterium animalis, Lactobacillus acidophilus, Prevotella intermedia and F. prausnitzii in athletes with high dynamic components (high VO2max), and greater abundance of Bacteroides caccae in athletes with both high dynamic and static components (in relation with the maximal voluntary contraction component) [99].
Besides their chronic training regimes, the dietary intake patterns of athletes are often different from those of sedentary subjects [101], as is medication intake [102,103]. These factors also might influence their gut microbiota composition [94,104,105]. Finally, some data show that prolonged excessive exercise could have a detrimental effect on intestinal function [106]. Indeed, strenuous and prolonged exercise increases intestinal permeability and alters the gut barrier function. This promotes bacterial translocation from the colon [107,108], leak of bacterial LPS into the bloodstream, and activation of systemic inflammation. GI symptoms (e.g., abdominal pain, nausea, and diarrhea) are reported by 70% of athletes after strenuous exercise, and the frequency is higher in elite athletes than in recreational exercisers [109]. Besides the overall “diverse and rich” gut microbiota in athletes, many discrepancies can be observed in the microbiota profiles at lower taxonomic levels in relation to many confounding factors linked to the exercise type (e.g., intensity, mode, contraction type, duration, frequency), diet, drug intake, living environment, season, and many others.

5.2. Gut Bacteria Are Sensitive to Physical Activity Modulation: Lessons from Training and Hypoactivity Models

Intervention studies using different training modalities in healthy sedentary participants and in populations with specific conditions (e.g., age-related pathologies, GI diseases, metabolic or inflammatory diseases, such as obesity or osteoarthritis) indicate that exercise and physical activity have beneficial effects on the gut microbiota [94,110,111]. Similarly, the many available studies in animal models (e.g., controlled diet) show that physical activity can modify the intestinal microbiota composition, particularly the bacterial richness and diversity [112,113,114,115,116] (Table 2). At lower taxonomic levels, the available findings highlight some discrepancies because gut microbiota responds differently to different training modalities: forced or spontaneous exercise [114,117,118], high-intensity interval training (HIIT), and moderate-intensity continuous training (MICT) [116,119]. Moreover, it seems that the changes observed in the fecal microbiota are more important in younger animals [115].
Not many longitudinal studies are available in humans. In their review of longitudinal studies on changes in specific groups of bacteria after initiation of an exercise or training program, Aya et al. found that BMI is a determining factor in the human microbiota response to exercise [90]. For instance, Allen et al. reported that after six weeks of supervised aerobic training, discrete incremental changes of the relative abundance of the Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Verrucomicrobia phyla can be observed in the fecal microbiota of apparently healthy individuals with a BMI > 25 kg/m2. Conversely, gut microbiota from lean subjects responds to aerobic exercise by increasing the abundance of Faecalibacterium spp. and Lachnospira spp. and by reducing Bacteroides members [117]. To date, only one study reported findings related to HIIT. This non-randomized trial found that the abundance of the Subdoligranulumwa genus is increased in lean men after three weeks of cyclo-ergometer workout [131]. Thus, despite a growing literature, the effect of different training modalities on the human intestinal microbiota is still under investigation.
On the other hand, the effects of hypoactivity on the human gut microbiota have been rarely studied (Table 3). In their cross-sectional study, Bressa et al. compared healthy premenopausal active and sedentary women by correlating energy expenditure, physical activity intensity (measured with an accelerometer) and 16S gut microbiota sequencing data. They found that sedentary parameters were inversely correlated with the microbiota richness (i.e., number of species) and Shannon and Simpson indices [132].
Few studies have assessed the longitudinal impact of hypoactivity on the gut microbiota composition, and some concern space medicine. Data from microgravity studies suggest that gut bacteria are sensitive to drastic hypoactivity because spaceflight affects the microbial composition of the astronauts’ GI tract [134,135,136,137,139], mostly genera belonging to the Firmicutes phylum, the Clostridiales order, and the Lachnospiraceae family. Head-down bedrest and dry immersion are considered reliable ground-based models to study the physiological effects of hypoactivity in humans [140,141,142] and the response by gut microbiota to reduced/absence of physical activity. Nevertheless, very few studies have been published. Interestingly, Lachnospiraceae operational taxonomic units (OTUs) are increased in a mouse model of hypoactivity (hindlimb unloading) [133]. Similarly, Jollet et al. showed in healthy men that a short period of severe hypoactivity (five days of dry immersion that was enough to induce skeletal muscle atrophy) increases the OTUs associated with the Clostridiales order and the Lachnospiraceae family that belong to the Firmicutes phylum, without any effect on α and β diversity indices [138]. Moreover, propionate, an SCFA metabolized by skeletal muscle, was significantly reduced in the stool samples collected after the hypoactivity period. Overall, despite the limited number of available data, these first studies suggest that the Lachnospiraceae family is particularly sensitive to hypoactivity and might play a key role in the hypoactivity-gut microbiota axis.

5.3. The Gut-Muscle-Adipose Tissue Axis

Using bacteria-free (germ-free condition) or microbiota-depleted (dysbiosis) models, researchers revealed the existence of a “cross-talk” between gut microbiota and adipose tissue [143], and more recently, skeletal muscle [144], two key tissues for athletic performance.
The most spectacular finding is that after the transfer of the microbiota of obese mice in germ-free mice (without gut microbiota), inoculated mice develop a fat phenotype in the absence of any change in their diet [145]. Moreover, people with obesity are characterized by dysbiosis compared with lean subjects [75]. According to the energy harvest theory, the gut microbiota of obese mice (the composition of which is influenced by a high-calorie diet) can extract more calories than the microbiota of lean mice [40]. In addition, obesity-induced dysbiosis decreases the expression of fasting inducing adipose factor (FIAF), thus increasing the activity of lipoprotein lipase (LPL) that facilitates the transport and thus the storage of fatty acids by peripheral tissues [146]. Several studies have confirmed the link between a high-fat diet, fat mass, and intestinal microbiota dysbiosis [147,148,149,150]. The Firmicutes/Bacteroidetes ratio is positively correlated with BMI and has been considered a sign of dysbiosis in people with obesity [151]; however, it is now questioned [152]. Bacterial metagenome sequencing in some individuals with obesity revealed that the number of bacterial genes is decreased, and consequently, the α diversity and β diversity are reduced compared with healthy subjects [153]. As said previously, the response of gut bacteria to exercise training is different in individuals with normal weight and with obesity. Moreover, the gut microbiota pattern in individuals with obesity is associated with various taxonomic signatures. This is probably due to many different lifestyle-associated factors (e.g., diet, physical activity, food additives and drugs) that affect the microbiota composition and/or diversity.
The influence of the intestinal microbiota on skeletal muscle, which is a metabolic organ, has been fully established only some years ago. The first data came from studies on the gut microbiota influence in obesity and cancer. Backhed et al. were the first to show that axenic mice fed a high-lipid diet are protected from obesity by two distinct mechanisms [145]. The first is an increase in the AMPK protein kinase (a metabolic sensor) associated with the over-activity of CPT1 (a mitochondrial membrane transporter of fatty acids, particularly in muscles). The second mechanism concerns the overexpression of FIAF that inhibits circulating LPL and stimulates PGC-1α, a transcription factor involved in oxidative metabolism and mitochondriogenesis in the gastrocnemius muscles [145]. Then, Delzenne and Cani’s group strongly suggested the existence of a possible axis between intestinal microbiota and skeletal muscle by investigating the composition of the intestinal microbiota of a mouse model of severe leukemia with cachexia [144]. Cachexia is a wasting syndrome observed in many chronic pathologies and is characterized by significant weight loss, particularly in muscles. Bindels et al. [130] found that the genus Lactobacillus spp., which has anti-inflammatory properties, is drastically decreased in cachectic mice. Oral targeted probiotic supplementation (Lactobacillus reuteri 100-23e and Lactobacillus gasseri 311476e) prevented muscle atrophy in cachectic mice by decreasing the expression of E3 ligases (responsible for the ubiquitination of proteins and then their degradation by proteasomes) as well as of atrogin-1, muscle ring finger-1 (MuRF1) and cathepsin-L (atrophy markers) in the tibialis anterior and gastrocnemius muscles. Supplementation also reduced lysosomal autophagy, involved in muscle breakdown, via protein 1A/1B-light chain 3 (LC3) downregulation [144]. These results were subsequently confirmed [154,155] and suggest that the gut microbiota could play an essential role in maintaining muscle mass in severe/chronic pathologies. The first review on a possible link between intestinal microbiota and muscle atrophy was published by Bindels and Delzenne and is currently considered the reference on this topic [156].
Besides the impact on muscle mass regulation, some studies have evaluated the functional link between gut microbiota and skeletal muscles. For instance, Yan and colleagues, inspired by the results obtained by transferring the flora of obese mice to axenic mice, investigated the impact on the muscle phenotype of a microbiota transfer from fat pigs to axenic mice [157]. Recipient axenic mice tended to mimic the donor phenotype. Muscle lipogenesis was significantly increased (higher concentration of intramuscular triglycerides, higher expression of LPL and of the membrane transporter of the fatty acid translocase (FAT/CD36), and slightly increased expression of the insulin mediator SREBP-1c (sterol regulatory element-binding protein 1). Moreover, the muscle structure and function of recipient axenic mice were closer to the donor muscle phenotype: slightly reduced cross-sectional area of muscle fibers with a shift towards the slow fiber type [157]. Nay et al. showed using ex vivo contractile tests that gut microbiota depletion (induced by antibiotic treatment) affects the intrinsic contractile muscle endurance associated with glucose homeostasis dysfunction [158]. These deleterious effects were normalized by natural microbiota reseeding.
On the basis of the available data, it is now evident that gut bacteria are essential for skeletal muscle and for the adaptation to exercise and training through numerous and various functions: control of the inflammatory and redox pathways, regulation of nutrient availability and metabolite-derived bacterial production, interaction with anabolic and catabolic processes, and also mitochondrial biogenesis, redox and immune system regulation [92,106,119,159,160,161].
Collectively, the latest studies on the athletes’ gut microbiota and the relationships between intestinal microbiota, physical activity and the gut-muscle-adipose tissue axis open innovative and original perspectives for rehabilitation and sports training in the context of individual performance optimization. The scientific community is now much interested in understanding the effects on the gut microbiota of supplementation with probiotics or, more generally, of “biotic diets” coupled or not with physical activity or training.
The take home messages, as well challenges and future directions dealing with independent impacts of diet or physical activity on the regulation of the gut microbiota are summarized in the Box 2.
Box 2. Diet OR Physical Activity as Major Regulators of Gut Microbiota Composition.
The amount, type, and balance of the main dietary macronutrients, including n-3 PUFAs and non‐digestible carbohydrates, greatly influence the gut microbiota.
Many dietary compounds are available to modify the gut microbiota composition. The intake of prebiotics and probiotics should be adapted to each patient’s characteristics.
The diverse and rich gut microbiota in athletes must be better described at lower taxonomic levels to detect differences among sports disciplines.
Gut bacteria are sensitive to sedentary behaviors (e.g., hypogravity), but very few data are available, and this issue needs to be thoroughly investigated. Some interventional studies using different training modalities to optimize gut microbiota composition in healthy sedentary people or in disabled populations show interesting results. Studies on the underlying mechanisms highlighted a cross‐talk between organs (i.e., gut-muscle-adipose tissue axis).

6. Gut Microbiota Modulation by Exercise and Nutrition for Health and/or Performance

As previously shown, gut microbiota diversity and function are affected by diet modulation and physical activity, and these changes influence the host’s physiology. Therefore, gut microbiota modulation appears as an appropriate target for nutritional and/or physical activity interventions to improve health and/or performance. Paradoxically, although both interventions are classically accepted and implemented, no human study has associated diet modulation with a physical activity program, with the exception of those combining probiotic consumption and high-level sports practice [80]. In their review, Donnati Zeppa et al. [162] mention the potential interest of different nutritional supplements for modulating gut microbiota composition in the hope of improving athletic performance; however, no human study has actually compared the combination of controlled physical training and nutritional intake on gut microbiota composition changes. Additional and synergistic effects could be expected, as suggested by recent studies in animals [113,116].

6.1. Diet and Microbiota Modulation, Health and Performance

Currently, many studies have tested specific diets (e.g., ketogenic diet, high-carbohydrate diet, high-protein diet, gluten-free diet) to improve sports performance; however, none has really investigated their potential influence on gut microbiota modulation in athletes, but only in active, non-sport populations or in populations with specific diseases, particularly chronic inflammatory diseases. For example, the very low carbohydrate ketogenic diet (VLCKD) is currently becoming very popular as a potential therapy for obesity and related metabolic disorders [163,164], and its effect on the gut microbiome is well documented [165,166,167,168]. In a sports context, VLCKD is used to favor fat oxidation during exercise, with the aim of delaying fatigue onset by sparing glycogen stores [169]; however, no data is available on its potential impact on the intestinal microbiota of athletes. Similarly, a high carbohydrate diet, which is often consumed by athletes 3–4 days before an endurance event and can sometimes represent more than 70% of the total energy intake, has not been studied as a potential gut microbiota modulator.

6.2. Probiotics, Athletes, and Performance

GI complaints are very common among endurance athletes and include nausea, vomiting, abdominal angina, and bloody diarrhea. Immune depression in athletes has also been described after excessive training load and has been associated with psychological stress, disturbed sleep, and extreme environmental conditions, all of which increase the risk of respiratory tract infections. In recent years, the use of probiotics in sports has been growing, mainly to attenuate GI symptoms and respiratory tract infections [80,170]. Overall, a positive effect has been demonstrated [170]. However, results are heterogeneous in the function of the probiotic strain, dose, intake duration, and even dosage form (capsules, sachets, or fermented milk). It seems that multi-strain probiotics in sachets or as fermented food consumed for a long period give better results (reduction of GI symptoms and respiratory tract infections) [170]. The probiotic effectiveness is probably explained by the increased barrier function, higher immune cell activity (from the pro-/anti-inflammatory pathways and immunoglobulin production), enhanced SCFA production, lower intestinal pH, and greater mucus production [171,172]. In athletes, probiotics may improve immune function by increasing interferon gamma production by T lymphocytes and possibly by increasing immunoglobulines A production by B lymphocytes [170]. Moreover, Lamprecht et al. suggested that probiotics favor Toll-like receptor 2 (TLR2) activation, which stimulates tight junction protein production, especially zonulin [173], thus decreasing gut permeability and consequently endotoxemia and GI symptoms.
Probiotics also influence gut microbiota composition. For example, West et al. found a 7-fold increase of the Lactobacillus genus after 11 weeks of L. fermentum supplementation in competitive cyclists (both sexes) [174]. Similarly, Martarelli et al. showed that in athletes, supplementation with Lactobacillus species during 4 weeks of intense physical activity significantly increased the fecal Lactobacillus count [175]. Unfortunately, these results were not associated with an increase in physical capacities. Currently, some data show that probiotics may have, directly or indirectly, positive effects on human sports performance (reviewed by the International Society of Sports Nutrition in 2019) [80]. For example, Huang et al. showed in a double-blind placebo-controlled trial that 6-week supplementation with Lactobacillus plantarum TWK10 at low (3 × 1010 CFU) and high doses (9 × 1010 CFU) prolongs the time to exhaustion during an 85% VO2 max exercise in a dose-dependent manner and decreases serum lactate levels during exercise and recovery [176]. Recently, 4-week supplementation using another Lactobacillus plantarum strain (PS128) has been associated with a decrease in the concentration of muscle damage and oxidative stress systemic markers after a half-marathon in recreational runners without changes in their exercise capacity [177]. Thus, ergogenic results are not always clear; however, probiotics might help to improve recovery by promoting muscle repair via increased protein synthesis [178,179].

6.3. Combining Supplements and Physical Activity Programs for Better Health by Modulating Gut Microbiota

Lifestyle interventions, including diet and/or physical activity programs, help to improve the metabolic profile of patients with obesity, type 2 diabetes, IBD, and other metabolic diseases. The American College of Sports Medicine recommends regular (150 min/week) low- to moderate-intensity continuous training for patients with obesity, (pre)diabetes, and other metabolic problems [180]. Currently, HIIT, defined as short bursts of intense activity interspersed by periods of low-intensity exercise or rest [181], is considered a time-efficient and safe exercise mode to reduce total fat mass, especially intra-abdominal fat mass [182,183]. It may also improve glucose metabolism [184,185,186]. Furthermore, HIIT modulates gut microbiota composition in humans and rodents [112,113,114,115,187]. A growing body of evidence suggests that in humans, dietary interventions, including supplementation of creatine monohydrate, caffeine, nitrate, sodium bicarbonate, beta-alanine, proteins, and essential amino acids, as well as manipulating carbohydrate availability, lead to more favorable outcomes after HITT programs by enhancing energy metabolism or by increasing the adaptive response during recovery [167]. However, none of them investigated the potential influence of the intervention on gut microbiota modulation. In this context, our group tested the impact on gut microbiota modulation of a 12-week HIIT program combined with a polyphenol-rich extract from five plants (olive leaves, bilberry, artichoke, chrysanthellum, and black pepper). This extract is called Totum-63 and was designed to reduce type 2 diabetes risk factors by modulating body composition and whole-body glucose homeostasis [113]. We found that HIIT, combined with Totum-63 supplementation, alters the body composition and glycemic profile in a rat model of pre-obesity, specifically by modulating the intestinal mucosa-associated microbiota. In our experimental conditions, the HIIT + Totum-63 combination significantly limited body weight gain, without any energy intake modulation, and improved glycemic control. Body weight variation was correlated with the α diversity of the colon mucosa microbiota, and this correlation was higher in the HIIT + Totum-63 group. Moreover, the relative abundance of Anaeroplasmaceae, Christensenellaceae and Oscillospira was higher in the HIIT + Totum-63 group. Thus, the combination of HIIT and Totum-63 supplementation could be proposed for the management of obesity and prediabetes and also of other chronic pathologies that involve gut microbiota dysbiosis.
More recently, we evaluated the effects of a 12-week intervention program combining physical activity (HIIT) and n-3 PUFA supplementation (i.e., the addition of linseed oil (LO) in the diet) on body composition and metabolic profile changes in a rodent model of obesity. We hypothesized that each intervention could specifically affect the mucosa-associated gut microbiota composition (α and β diversity) with more favorable adaptations in the HIIT + LO group [116]. It is known that n-3 PUFAs from natural sources or dietary supplements exert a beneficial effect on body composition and inflammation status [188,189], improve the intestinal barrier function [63] and integrity, and increase healthy bacterial communities [62,190]. By combining HIIT and LO, we hoped to induce an additive or even synergistic effect on the intestinal mucosa-associated microbiota that would promote body composition and metabolic profile changes. Our results show that HIIT significantly reduced total body fat mass and that the HIIT + LO combination improved alpha-linolenic acid to docosahexaenoic acid conversion and increased the relative abundance of Oscillospira bacteria in the colon microbiota [116]. Oscillospira abundance was negatively correlated with weight and fat mass gain. Prevotella also increased in the HIIT and HIIT + LO groups (compared with controls), and its abundance was negatively correlated with weight and fat mass gain. Thus, the combination of HIIT and LO could be proposed for the management of metabolic diseases, such as obesity.
The take home messages, as well challenges and future directions dealing with the Nutrition-Microbiota-Physical Activity triad is summarized in the Box 3.
Box 3. The Nutrition‐Microbiota‐Physical Activity Triad.
Animal studies suggest additional and synergistic effects of physical activity and nutritional modulations on the gut microbiota composition that need to be confirmed in human studies. No study has investigated the effect of the high‐carbohydrate and very low ketogenic diets on the athletes’ microbiota.
Multi-strain probiotics in the form of sachets or fermented food and consumed for a long period show beneficial effects in athletes.
Lactobacillus plantarum species are the only probiotics with ergogenic effects in a double-blind-controlled human study. High-intensity interval training associated with n-3 PUFA or polyphenol-rich extract supplementation is the only tested training + diet intervention.
The many possibilities offered by “biotic diets” and training modalities need to be investigated to show the clinical and/or ergogenic value of the triad.
Triad-targeted interventions must take into account the microbiome profile of the patient or athlete to be efficient.

7. Conclusions and Perspectives

Today, there is no doubt that the discovery of the gut microbiota community opened a promising and rapidly growing research field on the potential beneficial health effects of manipulating the gut microbiota. Indeed, the gut microbiota influences the function of the intestine and also brain and metabolic tissues, such as adipose tissue and skeletal muscle. Through its bacteria-derived metabolites, the gut plays the role of an orchestra conductor in the host. Cumulative data in murine models allowed “failed/dysbiotic” and “healthy/competitive” microbiota profiles to be identified. Conversely, human studies are still limited. In many countries, National Gut Human Projects (e.g., the American Human Microbiome Project and the European Human Microbiome Action that started in 2021) have been set up to collect human fecal samples and to correlate the obtained microbiota results with the host’s characteristics. Human fecal samples and metagenomic data are currently collected for future biostatistics analyses. For instance, the Million Microbiome of Humans Project (MMHP) is a major international project, the aims of which are to create the largest human microbiota database in the world, to analyze 1 million samples, and to explore the full microbiome potential. One major milestone will be to launch interventional studies to modulate the gut microbiota composition because, as we demonstrated in this review, the gut can adapt its bacterial community in response to external factors, such as nutrition and physical activity. The scientific and medical communities must now find the best way(s) to optimize the nutrition-gut microbiota-physical activity triad for each patient or athlete. Currently, HIIT with n-3 PUFA or polyphenol-rich extract supplementation appears to be a promising combination. However, the possibilities offered by biotic nutrition and training modalities represent a veritable “playground” for scientists. The challenge is to develop innovative, original and promising microbiota-based strategies coupled with physical activity programs to optimize sports performance and medical treatments or to delay disease onset (Figure 3). Finally, it is essential to increase the population’s awareness of the need for a healthy diet and some physical activity for a healthy microbiota, although the triad mechanisms have not been fully elucidated yet. Some scientific organizations and large food companies are already campaigning about the importance of a healthy diet as a key factor in microbiota formation. However, they did not include the physical activity component. Indeed, the goal should be to make clear that both a healthy/well-balanced diet and regular (high-level) physical activity practice are needed to improve gut microbiota composition/function for better health and/or performance. We think that outreach programs should also include the triad concept to develop individualized microbiota-based strategies for health and sports performance management.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Qin, J.; Li, R.; Raes, J.; Arumugam, M.; Burgdorf, K.S.; Manichanh, C.; Nielsen, T.; Pons, N.; Levenez, F.; Yamada, T.; et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010, 464, 59–65. [Google Scholar] [CrossRef] [Green Version]
  2. Farré-Maduell, E.; Casals-Pascual, C. The origins of gut microbiome research in Europe: From Escherich to Nissle. Hum. Microbiome J. 2019, 14, 100065. [Google Scholar] [CrossRef]
  3. Fujimura, K.E.; Slusher, N.A.; Cabana, M.D.; Lynch, S.V. Role of the gut microbiota in defining human health. Expert Rev. Anti-Infect. Ther. 2010, 8, 435–454. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Le Chatelier, E.; Nielsen, T.; Qin, J.; Prifti, E.; Hildebrand, F.; Falony, G.; Almeida, M.; Arumugam, M.; Batto, J.M.; Kennedy, S.; et al. Richness of human gut microbiome correlates with metabolic markers. Nature 2013, 500, 541–546. [Google Scholar] [CrossRef] [PubMed]
  5. Li, J.; Jia, H.; Cai, X.; Zhong, H.; Feng, Q.; Sunagawa, S.; Arumugam, M.; Kultima, J.R.; Prifti, E.; Nielsen, T.; et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 2014, 32, 834–841. [Google Scholar] [CrossRef] [PubMed]
  6. O’Hara, A.M.; Shanahan, F. The gut flora as a forgotten organ. EMBO Rep. 2006, 7, 688–693. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 2012, 486, 207–214. [Google Scholar] [CrossRef] [Green Version]
  8. Cho, I.; Blaser, M.J. The human microbiome: At the interface of health and disease. Nat. Rev. Genet. 2012, 13, 260–270. [Google Scholar] [CrossRef] [Green Version]
  9. Walter, J.; Ley, R. The human gut microbiome: Ecology and recent evolutionary changes. Annu. Rev. Microbiol. 2011, 65, 411–429. [Google Scholar] [CrossRef] [Green Version]
  10. Arumugam, M.; Raes, J.; Pelletier, E.; Le Paslier, D.; Yamada, T.; Mende, D.R.; Fernandes, G.R.; Tap, J.; Bruls, T.; Batto, J.M.; et al. Enterotypes of the human gut microbiome. Nature 2011, 473, 174–180. [Google Scholar] [CrossRef]
  11. Eckburg, P.B.; Bik, E.M.; Bernstein, C.N.; Purdom, E.; Dethlefsen, L.; Sargent, M.; Gill, S.R.; Nelson, K.E.; Relman, D.A. Diversity of the human intestinal microbial flora. Science 2005, 308, 1635–1638. [Google Scholar] [CrossRef] [Green Version]
  12. Jandhyala, S.M.; Talukdar, R.; Subramanyam, C.; Vuyyuru, H.; Sasikala, M.; Nageshwar Reddy, D. Role of the normal gut microbiota. World J. Gastroenterol. 2015, 21, 8787–8803. [Google Scholar] [CrossRef]
  13. Ley, R.E.; Hamady, M.; Lozupone, C.; Turnbaugh, P.J.; Ramey, R.R.; Bircher, J.S.; Schlegel, M.L.; Tucker, T.A.; Schrenzel, M.D.; Knight, R.; et al. Evolution of mammals and their gut microbes. Science 2008, 320, 1647–1651. [Google Scholar] [CrossRef] [Green Version]
  14. Lavelle, A.; Lennon, G.; O’Sullivan, O.; Docherty, N.; Balfe, A.; Maguire, A.; Mulcahy, H.E.; Doherty, G.; O’Donoghue, D.; Hyland, J.; et al. Spatial variation of the colonic microbiota in patients with ulcerative colitis and control volunteers. Gut 2015, 64, 1553–1561. [Google Scholar] [CrossRef] [Green Version]
  15. Hugenholtz, F.; de Vos, W.M. Mouse models for human intestinal microbiota research: A critical evaluation. Cell Mol. Life Sci. 2018, 75, 149–160. [Google Scholar] [CrossRef] [Green Version]
  16. Fassarella, M.; Blaak, E.E.; Penders, J.; Nauta, A.; Smidt, H.; Zoetendal, E.G. Gut microbiome stability and resilience: Elucidating the response to perturbations in order to modulate gut health. Gut 2021, 70, 595–605. [Google Scholar] [CrossRef]
  17. Ratsika, A.; Codagnone, M.C.; O’Mahony, S.; Stanton, C.; Cryan, J.F. Priming for Life: Early Life Nutrition and the Microbiota-Gut-Brain Axis. Nutrients 2021, 13, 423. [Google Scholar] [CrossRef]
  18. Laudes, M.; Geisler, C.; Rohmann, N.; Bouwman, J.; Pischon, T.; Schlicht, K. Microbiota in Health and Disease-Potential Clinical Applications. Nutrients 2021, 13, 3866. [Google Scholar] [CrossRef]
  19. Shah, T.; Baloch, Z.; Shah, Z.; Cui, X.; Xia, X. The Intestinal Microbiota: Impacts of Antibiotics Therapy, Colonization Resistance, and Diseases. Int. J. Mol. Sci. 2021, 22, 6597. [Google Scholar] [CrossRef]
  20. Zeissig, S.; Blumberg, R.S. Commensal microbial regulation of natural killer T cells at the frontiers of the mucosal immune system. FEBS Lett. 2014, 588, 4188–4194. [Google Scholar] [CrossRef]
  21. Potrykus, M.; Czaja-Stolc, S.; Stankiewicz, M.; Kaska, L.; Malgorzewicz, S. Intestinal Microbiota as a Contributor to Chronic Inflammation and Its Potential Modifications. Nutrients 2021, 13, 3839. [Google Scholar] [CrossRef]
  22. Rutgeerts, P.; Goboes, K.; Peeters, M.; Hiele, M.; Penninckx, F.; Aerts, R.; Kerremans, R.; Vantrappen, G. Effect of faecal stream diversion on recurrence of Crohn’s disease in the neoterminal ileum. Lancet 1991, 338, 771–774. [Google Scholar] [CrossRef]
  23. Caparros, E.; Wiest, R.; Scharl, M.; Rogler, G.; Gutierrez Casbas, A.; Yilmaz, B.; Wawrzyniak, M.; Frances, R. Dysbiotic microbiota interactions in Crohn’s disease. Gut Microbes 2021, 13, 1949096. [Google Scholar] [CrossRef]
  24. Wright, E.K.; Kamm, M.A.; Teo, S.M.; Inouye, M.; Wagner, J.; Kirkwood, C.D. Recent advances in characterizing the gastrointestinal microbiome in Crohn’s disease: A systematic review. Inflamm. Bowel Dis. 2015, 21, 1219–1228. [Google Scholar] [CrossRef] [Green Version]
  25. Quevrain, E.; Maubert, M.A.; Michon, C.; Chain, F.; Marquant, R.; Tailhades, J.; Miquel, S.; Carlier, L.; Bermudez-Humaran, L.G.; Pigneur, B.; et al. Identification of an anti-inflammatory protein from Faecalibacterium prausnitzii, a commensal bacterium deficient in Crohn’s disease. Gut 2016, 65, 415–425. [Google Scholar] [CrossRef] [Green Version]
  26. Sokol, H.; Pigneur, B.; Watterlot, L.; Lakhdari, O.; Bermudez-Humaran, L.G.; Gratadoux, J.J.; Blugeon, S.; Bridonneau, C.; Furet, J.P.; Corthier, G.; et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc. Natl. Acad. Sci. USA 2008, 105, 16731–16736. [Google Scholar] [CrossRef] [Green Version]
  27. Alhagamhmad, M.H.; Day, A.S.; Lemberg, D.A.; Leach, S.T. An overview of the bacterial contribution to Crohn disease pathogenesis. J. Med. Microbiol. 2016, 65, 1049–1059. [Google Scholar] [CrossRef] [PubMed]
  28. Nadalian, B.; Yadegar, A.; Houri, H.; Olfatifar, M.; Shahrokh, S.; Asadzadeh Aghdaei, H.; Suzuki, H.; Zali, M.R. Prevalence of the pathobiont adherent-invasive Escherichia coli and inflammatory bowel disease: A systematic review and meta-analysis. J. Gastroenterol. Hepatol. 2021, 36, 852–863. [Google Scholar] [CrossRef] [PubMed]
  29. Palmela, C.; Chevarin, C.; Xu, Z.; Torres, J.; Sevrin, G.; Hirten, R.; Barnich, N.; Ng, S.C.; Colombel, J.F. Adherent-invasive Escherichia coli in inflammatory bowel disease. Gut 2018, 67, 574–587. [Google Scholar] [CrossRef] [PubMed]
  30. Ferreira, R.M.; Pereira-Marques, J.; Pinto-Ribeiro, I.; Costa, J.L.; Carneiro, F.; Machado, J.C.; Figueiredo, C. Gastric microbial community profiling reveals a dysbiotic cancer-associated microbiota. Gut 2018, 67, 226–236. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Touati, E.; Michel, V.; Thiberge, J.M.; Wuscher, N.; Huerre, M.; Labigne, A. Chronic Helicobacter pylori infections induce gastric mutations in mice. Gastroenterology 2003, 124, 1408–1419. [Google Scholar] [CrossRef]
  32. Cougnoux, A.; Dalmasso, G.; Martinez, R.; Buc, E.; Delmas, J.; Gibold, L.; Sauvanet, P.; Darcha, C.; Dechelotte, P.; Bonnet, M.; et al. Bacterial genotoxin colibactin promotes colon tumour growth by inducing a senescence-associated secretory phenotype. Gut 2014, 63, 1932–1942. [Google Scholar] [CrossRef]
  33. Nougayrede, J.P.; Homburg, S.; Taieb, F.; Boury, M.; Brzuszkiewicz, E.; Gottschalk, G.; Buchrieser, C.; Hacker, J.; Dobrindt, U.; Oswald, E. Escherichia coli induces DNA double-strand breaks in eukaryotic cells. Science 2006, 313, 848–851. [Google Scholar] [CrossRef]
  34. Veziant, J.; Villeger, R.; Barnich, N.; Bonnet, M. Gut Microbiota as Potential Biomarker and/or Therapeutic Target to Improve the Management of Cancer: Focus on Colibactin-Producing Escherichia coli in Colorectal Cancer. Cancers 2021, 13, 2215. [Google Scholar] [CrossRef]
  35. Ranjbar, M.; Salehi, R.; Haghjooy Javanmard, S.; Rafiee, L.; Faraji, H.; Jafarpor, S.; Ferns, G.A.; Ghayour-Mobarhan, M.; Manian, M.; Nedaeinia, R. The dysbiosis signature of Fusobacterium nucleatum in colorectal cancer-cause or consequences? A systematic review. Cancer Cell Int. 2021, 21, 194. [Google Scholar] [CrossRef]
  36. Chen, Y.; Liu, B.; Wei, Y.; Kuang, D.M. Influence of gut and intratumoral microbiota on the immune microenvironment and anti-cancer therapy. Pharmacol. Res. 2021, 174, 105966. [Google Scholar] [CrossRef]
  37. Lopes, A.; Billard, E.; Casse, A.H.; Villeger, R.; Veziant, J.; Roche, G.; Carrier, G.; Sauvanet, P.; Briat, A.; Pages, F.; et al. Colibactin-positive Escherichia coli induce a procarcinogenic immune environment leading to immunotherapy resistance in colorectal cancer. Int. J. Cancer 2020, 146, 3147–3159. [Google Scholar] [CrossRef] [Green Version]
  38. Silva, M.; Brunner, V.; Tschurtschenthaler, M. Microbiota and Colorectal Cancer: From Gut to Bedside. Front. Pharmacol. 2021, 12, 760280. [Google Scholar] [CrossRef]
  39. Aron-Wisnewsky, J.; Warmbrunn, M.V.; Nieuwdorp, M.; Clement, K. Metabolism and Metabolic Disorders and the Microbiome: The Intestinal Microbiota Associated With Obesity, Lipid Metabolism, and Metabolic Health-Pathophysiology and Therapeutic Strategies. Gastroenterology 2021, 160, 573–599. [Google Scholar] [CrossRef]
  40. Turnbaugh, P.J.; Ley, R.E.; Mahowald, M.A.; Magrini, V.; Mardis, E.R.; Gordon, J.I. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444, 1027–1031. [Google Scholar] [CrossRef]
  41. Cani, P.D.; Osto, M.; Geurts, L.; Everard, A. Involvement of gut microbiota in the development of low-grade inflammation and type 2 diabetes associated with obesity. Gut Microbes 2012, 3, 279–288. [Google Scholar] [CrossRef] [Green Version]
  42. Krueger, E.S.; Lloyd, T.S.; Tessem, J.S. The Accumulation and Molecular Effects of Trimethylamine N-Oxide on Metabolic Tissues: It’s Not All Bad. Nutrients 2021, 13, 2873. [Google Scholar] [CrossRef]
  43. Wang, B.; Qiu, J.; Lian, J.; Yang, X.; Zhou, J. Gut Metabolite Trimethylamine-N-Oxide in Atherosclerosis: From Mechanism to Therapy. Front. Cardiovasc. Med. 2021, 8, 723886. [Google Scholar] [CrossRef]
  44. Maiuolo, J.; Gliozzi, M.; Musolino, V.; Carresi, C.; Scarano, F.; Nucera, S.; Scicchitano, M.; Oppedisano, F.; Bosco, F.; Ruga, S.; et al. The Contribution of Gut Microbiota-Brain Axis in the Development of Brain Disorders. Front. Neurosci. 2021, 15, 616883. [Google Scholar] [CrossRef]
  45. Bremner, J.D.; Moazzami, K.; Wittbrodt, M.T.; Nye, J.A.; Lima, B.B.; Gillespie, C.F.; Rapaport, M.H.; Pearce, B.D.; Shah, A.J.; Vaccarino, V. Diet, Stress and Mental Health. Nutrients 2020, 12, 2428. [Google Scholar] [CrossRef]
  46. Gershon, M.D.; Margolis, K.G. The gut, its microbiome, and the brain: Connections and communications. J. Clin. Investig. 2021, 131. [Google Scholar] [CrossRef]
  47. Aron-Wisnewsky, J.; Clement, K.; Nieuwdorp, M. Fecal Microbiota Transplantation: A Future Therapeutic Option for Obesity/Diabetes? Curr. Diabetes Rep. 2019, 19, 51. [Google Scholar] [CrossRef]
  48. Sokol, H.; Landman, C.; Seksik, P.; Berard, L.; Montil, M.; Nion-Larmurier, I.; Bourrier, A.; Le Gall, G.; Lalande, V.; De Rougemont, A.; et al. Fecal microbiota transplantation to maintain remission in Crohn’s disease: A pilot randomized controlled study. Microbiome 2020, 8, 12. [Google Scholar] [CrossRef]
  49. Daillere, R.; Derosa, L.; Bonvalet, M.; Segata, N.; Routy, B.; Gariboldi, M.; Budinska, E.; De Vries, I.J.M.; Naccarati, A.G.; Zitvogel, V.; et al. Trial watch: The gut microbiota as a tool to boost the clinical efficacy of anticancer immunotherapy. Oncoimmunology 2020, 9, 1774298. [Google Scholar] [CrossRef]
  50. Zhou, H.; Yuan, Y.; Wang, H.; Xiang, W.; Li, S.; Zheng, H.; Wen, Y.; Ming, Y.; Chen, L.; Zhou, J. Gut Microbiota: A Potential Target for Cancer Interventions. Cancer Manag. Res. 2021, 13, 8281–8296. [Google Scholar] [CrossRef]
  51. Buffie, C.G.; Jarchum, I.; Equinda, M.; Lipuma, L.; Gobourne, A.; Viale, A.; Ubeda, C.; Xavier, J.; Pamer, E.G. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect. Immun. 2012, 80, 62–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Ley, R.E.; Turnbaugh, P.J.; Klein, S.; Gordon, J.I. Microbial ecology: Human gut microbes associated with obesity. Nature 2006, 444, 1022–1023. [Google Scholar] [CrossRef] [PubMed]
  53. Devkota, S.; Wang, Y.; Musch, M.W.; Leone, V.; Fehlner-Peach, H.; Nadimpalli, A.; Antonopoulos, D.A.; Jabri, B.; Chang, E.B. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10-/- mice. Nature 2012, 487, 104–108. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Rothschild, D.; Weissbrod, O.; Barkan, E.; Kurilshikov, A.; Korem, T.; Zeevi, D.; Costea, P.I.; Godneva, A.; Kalka, I.N.; Bar, N.; et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 2018, 555, 210–215. [Google Scholar] [CrossRef] [PubMed]
  55. Zhang, C.; Zhang, M.; Wang, S.; Han, R.; Cao, Y.; Hua, W.; Mao, Y.; Zhang, X.; Pang, X.; Wei, C.; et al. Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice. ISME J. 2010, 4, 232–241. [Google Scholar] [CrossRef] [Green Version]
  56. Faith, J.J.; Guruge, J.L.; Charbonneau, M.; Subramanian, S.; Seedorf, H.; Goodman, A.L.; Clemente, J.C.; Knight, R.; Heath, A.C.; Leibel, R.L.; et al. The long-term stability of the human gut microbiota. Science 2013, 341, 1237439. [Google Scholar] [CrossRef] [Green Version]
  57. David, L.A.; Maurice, C.F.; Carmody, R.N.; Gootenberg, D.B.; Button, J.E.; Wolfe, B.E.; Ling, A.V.; Devlin, A.S.; Varma, Y.; Fischbach, M.A.; et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 2014, 505, 559–563. [Google Scholar] [CrossRef] [Green Version]
  58. Drasar, B.S.; Crowther, J.S.; Goddard, P.; Hawksworth, G.; Hill, M.J.; Peach, S.; Williams, R.E.; Renwick, A. The relation between diet and the gut microflora in man. Proc. Nutr. Soc. 1973, 32, 49–52. [Google Scholar] [CrossRef] [Green Version]
  59. Fava, F.; Gitau, R.; Griffin, B.A.; Gibson, G.R.; Tuohy, K.M.; Lovegrove, J.A. The type and quantity of dietary fat and carbohydrate alter faecal microbiome and short-chain fatty acid excretion in a metabolic syndrome ‘at-risk’ population. Int. J. Obes. 2013, 37, 216–223. [Google Scholar] [CrossRef] [Green Version]
  60. Reddy, B.S.; Weisburger, J.H.; Wynder, E.L. Effects of high risk and low risk diets for colon carcinogenesis on fecal microflora and steroids in man. J. Nutr. 1975, 105, 878–884. [Google Scholar] [CrossRef]
  61. Wu, G.D.; Chen, J.; Hoffmann, C.; Bittinger, K.; Chen, Y.Y.; Keilbaugh, S.A.; Bewtra, M.; Knights, D.; Walters, W.A.; Knight, R.; et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 2011, 334, 105–108. [Google Scholar] [CrossRef] [Green Version]
  62. Caesar, R.; Tremaroli, V.; Kovatcheva-Datchary, P.; Cani, P.D.; Bäckhed, F. Crosstalk between Gut Microbiota and Dietary Lipids Aggravates WAT Inflammation through TLR Signaling. Cell Metab. 2015, 22, 658–668. [Google Scholar] [CrossRef] [Green Version]
  63. Lam, Y.Y.; Ha, C.W.; Hoffmann, J.M.; Oscarsson, J.; Dinudom, A.; Mather, T.J.; Cook, D.I.; Hunt, N.H.; Caterson, I.D.; Holmes, A.J.; et al. Effects of dietary fat profile on gut permeability and microbiota and their relationships with metabolic changes in mice. Obesity 2015, 23, 1429–1439. [Google Scholar] [CrossRef]
  64. Määttänen, P.; Lurz, E.; Botts, S.R.; Wu, R.Y.; Yeung, C.W.; Li, B.; Abiff, S.; Johnson-Henry, K.C.; Lepp, D.; Power, K.A.; et al. Ground flaxseed reverses protection of a reduced-fat diet against Citrobacter rodentium-induced colitis. Am. J. Physiol.-Gastrointest. Liver Physiol. 2018, 315, G788–G798. [Google Scholar] [CrossRef] [Green Version]
  65. Zhuang, P.; Shou, Q.; Wang, W.; He, L.; Wang, J.; Chen, J.; Zhang, Y.; Jiao, J. Essential Fatty Acids Linoleic Acid and α-Linolenic Acid Sex-Dependently Regulate Glucose Homeostasis in Obesity. Mol. Nutr. Food Res. 2018, 62, e1800448. [Google Scholar] [CrossRef]
  66. Zhuang, P.; Zhang, Y.; Shou, Q.; Li, H.; Zhu, Y.; He, L.; Chen, J.; Jiao, J. Eicosapentaenoic and Docosahexaenoic Acids Differentially Alter Gut Microbiome and Reverse High-Fat Diet-Induced Insulin Resistance. Mol. Nutr. Food Res. 2020, 64, e1900946. [Google Scholar] [CrossRef]
  67. Cotillard, A.; Kennedy, S.P.; Kong, L.C.; Prifti, E.; Pons, N.; Le Chatelier, E.; Almeida, M.; Quinquis, B.; Levenez, F.; Galleron, N.; et al. Dietary intervention impact on gut microbial gene richness. Nature 2013, 500, 585–588. [Google Scholar] [CrossRef]
  68. Meddah, A.T.; Yazourh, A.; Desmet, I.; Risbourg, B.; Verstraete, W.; Romond, M.B. The regulatory effects of whey retentate from bifidobacteria fermented milk on the microbiota of the Simulator of the Human Intestinal Microbial Ecosystem (SHIME). J. Appl. Microbiol. 2001, 91, 1110–1117. [Google Scholar] [CrossRef] [Green Version]
  69. Świątecka, D.; Narbad, A.; Ridgway, K.P.; Kostyra, H. The study on the impact of glycated pea proteins on human intestinal bacteria. Int. J. Food Microbiol. 2011, 145, 267–272. [Google Scholar] [CrossRef]
  70. Kim, C.H.; Park, J.; Kim, M. Gut microbiota-derived short-chain Fatty acids, T cells, and inflammation. Immune Netw. 2014, 14, 277–288. [Google Scholar] [CrossRef] [Green Version]
  71. Albracht-Schulte, K.; Islam, T.; Johnson, P.; Moustaid-Moussa, N. Systematic Review of Beef Protein Effects on Gut Microbiota: Implications for Health. Adv. Nutr. 2021, 12, 102–114. [Google Scholar] [CrossRef] [PubMed]
  72. Brinkworth, G.D.; Noakes, M.; Clifton, P.M.; Bird, A.R. Comparative 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 populations. Br. J. Nutr. 2009, 101, 1493–1502. [Google Scholar] [CrossRef] [Green Version]
  73. Duncan, S.H.; Belenguer, A.; Holtrop, G.; Johnstone, A.M.; Flint, H.J.; Lobley, G.E. Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces. Appl. Environ. Microbiol. 2007, 73, 1073–1078. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Singh, R.K.; Chang, H.W.; Yan, D.; Lee, K.M.; Ucmak, D.; Wong, K.; Abrouk, M.; Farahnik, B.; Nakamura, M.; Zhu, T.H.; et al. Influence of diet on the gut microbiome and implications for human health. J. Transl. Med. 2017, 15, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Martinez, K.B.; Leone, V.; Chang, E.B. Western diets, gut dysbiosis, and metabolic diseases: Are they linked? Gut Microbes 2017, 8, 130–142. [Google Scholar] [CrossRef] [Green Version]
  76. Scott, K.P.; Gratz, S.W.; Sheridan, P.O.; Flint, H.J.; Duncan, S.H. The influence of diet on the gut microbiota. Pharmacol. Res. 2013, 69, 52–60. [Google Scholar] [CrossRef]
  77. Daien, C.I.; Pinget, G.V.; Tan, J.K.; Macia, L. Detrimental Impact of Microbiota-Accessible Carbohydrate-Deprived Diet on Gut and Immune Homeostasis: An Overview. Front. Immunol. 2017, 8, 548. [Google Scholar] [CrossRef] [Green Version]
  78. Davani-Davari, D.; Negahdaripour, M.; Karimzadeh, I.; Seifan, M.; Mohkam, M.; Masoumi, S.J.; Berenjian, A.; Ghasemi, Y. Prebiotics: Definition, Types, Sources, Mechanisms, and Clinical Applications. Foods 2019, 8, 92. [Google Scholar] [CrossRef] [Green Version]
  79. Pandey, K.R.; Naik, S.R.; Vakil, B.V. Probiotics, prebiotics and synbiotics—A review. J. Food Sci. Technol. 2015, 52, 7577–7587. [Google Scholar] [CrossRef]
  80. Jäger, R.; Mohr, A.E.; Carpenter, K.C.; Kerksick, C.M.; Purpura, M.; Moussa, A.; Townsend, J.R.; Lamprecht, M.; West, N.P.; Black, K.; et al. International Society of Sports Nutrition Position Stand: Probiotics. J. Int. Soc. Sports Nutr. 2019, 16, 62. [Google Scholar] [CrossRef] [Green Version]
  81. Shen, J.; Zuo, Z.X.; Mao, A.P. Effect of probiotics on inducing remission and maintaining therapy in ulcerative colitis, Crohn’s disease, and pouchitis: Meta-analysis of randomized controlled trials. Inflamm. Bowel Dis. 2014, 20, 21–35. [Google Scholar] [CrossRef] [Green Version]
  82. Sanders, M.E.; Merenstein, D.J.; Reid, G.; Gibson, G.R.; Rastall, R.A. Probiotics and prebiotics in intestinal health and disease: From biology to the clinic. Nat. Rev. Gastroenterol. Hepatol. 2019, 16, 605–616. [Google Scholar] [CrossRef]
  83. Liu, R.H. Potential synergy of phytochemicals in cancer prevention: Mechanism of action. J. Nutr. 2004, 134, 3479S–3485S. [Google Scholar] [CrossRef] [Green Version]
  84. Carrera-Quintanar, L.; López Roa, R.I.; Quintero-Fabián, S.; Sánchez-Sánchez, M.A.; Vizmanos, B.; Ortuño-Sahagún, D. Phytochemicals That Influence Gut Microbiota as Prophylactics and for the Treatment of Obesity and Inflammatory Diseases. Mediat. Inflamm. 2018, 2018, 9734845. [Google Scholar] [CrossRef]
  85. Rajha, H.N.; Paule, A.; Aragones, G.; Barbosa, M.; Caddeo, C.; Debs, E.; Dinkova, R.; Eckert, G.P.; Fontana, A.; Gebrayel, P.; et al. Recent Advances in Research on Polyphenols: Effects on Microbiota, Metabolism, and Health. Mol. Nutr. Food Res. 2022, 66, e2100670. [Google Scholar] [CrossRef]
  86. Queipo-Ortuño, M.I.; Boto-Ordóñez, M.; Murri, M.; Gomez-Zumaquero, J.M.; Clemente-Postigo, M.; Estruch, R.; Cardona Diaz, F.; Andrés-Lacueva, C.; Tinahones, F.J. Influence of red wine polyphenols and ethanol on the gut microbiota ecology and biochemical biomarkers. Am. J. Clin. Nutr. 2012, 95, 1323–1334. [Google Scholar] [CrossRef]
  87. Huda, M.N.; Ahmad, S.M.; Kalanetra, K.M.; Taft, D.H.; Alam, M.J.; Khanam, A.; Raqib, R.; Underwood, M.A.; Mills, D.A.; Stephensen, C.B. Neonatal Vitamin A Supplementation and Vitamin A Status Are Associated with Gut Microbiome Composition in Bangladeshi Infants in Early Infancy and at 2 Years of Age. J. Nutr. 2019, 149, 1075–1088. [Google Scholar] [CrossRef] [Green Version]
  88. Yang, Q.; Liang, Q.; Balakrishnan, B.; Belobrajdic, D.P.; Feng, Q.J.; Zhang, W. Role of Dietary Nutrients in the Modulation of Gut Microbiota: A Narrative Review. Nutrients 2020, 12, 381. [Google Scholar] [CrossRef] [Green Version]
  89. Clemente, J.C.; Ursell, L.K.; Parfrey, L.W.; Knight, R. The impact of the gut microbiota on human health: An integrative view. Cell 2012, 148, 1258–1270. [Google Scholar] [CrossRef] [Green Version]
  90. Aya, V.; Flórez, A.; Perez, L.; Ramírez, J.D. Association between physical activity and changes in intestinal microbiota composition: A systematic review. PLoS ONE 2021, 16, e0247039. [Google Scholar] [CrossRef]
  91. Cerdá, B.; Pérez, M.; Pérez-Santiago, J.D.; Tornero-Aguilera, J.F.; González-Soltero, R.; Larrosa, M. Gut Microbiota Modification: Another Piece in the Puzzle of the Benefits of Physical Exercise in Health? Front. Physiol. 2016, 7, 51. [Google Scholar] [CrossRef] [Green Version]
  92. Clark, A.; Mach, N. The Crosstalk between the Gut Microbiota and Mitochondria during Exercise. Front. Physiol. 2017, 8, 319. [Google Scholar] [CrossRef]
  93. Mach, N.; Fuster-Botella, D. Endurance exercise and gut microbiota: A review. J. Sport Health Sci. 2017, 6, 179–197. [Google Scholar] [CrossRef]
  94. Marttinen, M.; Ala-Jaakkola, R.; Laitila, A.; Lehtinen, M.J. Gut Microbiota, Probiotics and Physical Performance in Athletes and Physically Active Individuals. Nutrients 2020, 12, 2936. [Google Scholar] [CrossRef] [PubMed]
  95. Mohr, A.E.; Jäger, R.; Carpenter, K.C.; Kerksick, C.M.; Purpura, M.; Townsend, J.R.; West, N.P.; Black, K.; Gleeson, M.; Pyne, D.B.; et al. The athletic gut microbiota. J. Int. Soc. Sports Nutr. 2020, 17, 24. [Google Scholar] [CrossRef] [PubMed]
  96. Clarke, S.F.; Murphy, E.F.; O’Sullivan, O.; Lucey, A.J.; Humphreys, M.; Hogan, A.; Hayes, P.; O’Reilly, M.; Jeffery, I.B.; Wood-Martin, R.; et al. Exercise and associated dietary extremes impact on gut microbial diversity. Gut 2014, 63, 1913–1920. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Estaki, M.; Pither, J.; Baumeister, P.; Little, J.P.; Gill, S.K.; Ghosh, S.; Ahmadi-Vand, Z.; Marsden, K.R.; Gibson, D.L. Cardiorespiratory fitness as a predictor of intestinal microbial diversity and distinct metagenomic functions. Microbiome 2016, 4, 42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Scheiman, J.; Luber, J.M.; Chavkin, T.A.; MacDonald, T.; Tung, A.; Pham, L.-D.; Wibowo, M.C.; Wurth, R.C.; Punthambaker, S.; Tierney, B.T.; et al. Meta-omics analysis of elite athletes identifies a performance-enhancing microbe that functions via lactate metabolism. Nat. Med. 2019, 25, 1104–1109. [Google Scholar] [CrossRef]
  99. O’Donovan, C.M.; Madigan, S.M.; Garcia-Perez, I.; Rankin, A.; O’Sullivan, O.; Cotter, P.D. Distinct microbiome composition and metabolome exists across subgroups of elite Irish athletes. J. Sci. Med. Sport 2020, 23, 63–68. [Google Scholar] [CrossRef] [Green Version]
  100. Jang, L.-G.; Choi, G.; Kim, S.-W.; Kim, B.-Y.; Lee, S.; Park, H. The combination of sport and sport-specific diet is associated with characteristics of gut microbiota: An observational study. J. Int. Soc. Sports Nutr. 2019, 16, 21. [Google Scholar] [CrossRef] [Green Version]
  101. Charreire, H.; Kesse-Guyot, E.; Bertrais, S.; Simon, C.; Chaix, B.; Weber, C.; Touvier, M.; Galan, P.; Hercberg, S.; Oppert, J.-M. Associations between dietary patterns, physical activity (leisure-time and occupational) and television viewing in middle-aged French adults. Br. J. Nutr. 2011, 105, 902–910. [Google Scholar] [CrossRef]
  102. Alaranta, A.; Alaranta, H.; Heliövaara, M.; Airaksinen, M.; Helenius, I. Ample use of physician-prescribed medications in Finnish elite athletes. Int. J. Sports Med. 2006, 27, 919–925. [Google Scholar] [CrossRef]
  103. Ferry, B.; DeCastro, A.; Bragg, S. Common Prescription Medications Used in Athletes. Prim. Care 2020, 47, 49–64. [Google Scholar] [CrossRef]
  104. Dorelli, B.; Gallè, F.; De Vito, C.; Duranti, G.; Iachini, M.; Zaccarin, M.; Preziosi Standoli, J.; Ceci, R.; Romano, F.; Liguori, G.; et al. Can Physical Activity Influence Human Gut Microbiota Composition Independently of Diet? A Systematic Review. Nutrients 2021, 13, 1890. [Google Scholar] [CrossRef]
  105. Sheflin, A.M.; Melby, C.L.; Carbonero, F.; Weir, T.L. Linking dietary patterns with gut microbial composition and function. Gut Microbes 2017, 8, 113–129. [Google Scholar] [CrossRef]
  106. Przewłócka, K.; Folwarski, M.; Kaźmierczak-Siedlecka, K.; Skonieczna-Żydecka, K.; Kaczor, J.J. Gut-Muscle AxisExists and May Affect Skeletal Muscle Adaptation to Training. Nutrients 2020, 12, 1451. [Google Scholar] [CrossRef]
  107. Gisolfi, C.V. Is the GI System Built For Exercise? Physiology 2000, 15, 114–119. [Google Scholar] [CrossRef]
  108. Peters, H.P.; De Vries, W.R.; Vanberge-Henegouwen, G.P.; Akkermans, L.M. Potential benefits and hazards of physical activity and exercise on the gastrointestinal tract. Gut 2001, 48, 435–439. [Google Scholar] [CrossRef] [Green Version]
  109. de Oliveira, E.P.; Burini, R.C. The impact of physical exercise on the gastrointestinal tract. Curr. Opin. Clin. Nutr. Metab. Care 2009, 12, 533–538. [Google Scholar] [CrossRef]
  110. de Sire, A.; de Sire, R.; Petito, V.; Masi, L.; Cisari, C.; Gasbarrini, A.; Scaldaferri, F.; Invernizzi, M. Gut-Joint Axis: The Role of Physical Exercise on Gut Microbiota Modulation in Older People with Osteoarthritis. Nutrients 2020, 12, 574. [Google Scholar] [CrossRef] [Green Version]
  111. Monda, V.; Villano, I.; Messina, A.; Valenzano, A.; Esposito, T.; Moscatelli, F.; Viggiano, A.; Cibelli, G.; Chieffi, S.; Monda, M.; et al. Exercise Modifies the Gut Microbiota with Positive Health Effects. Oxidative Med. Cell. Longev. 2017, 2017, 3831972. [Google Scholar] [CrossRef]
  112. Batacan, R.B.; Fenning, A.S.; Dalbo, V.J.; Scanlan, A.T.; Duncan, M.J.; Moore, R.J.; Stanley, D. A gut reaction: The combined influence of exercise and diet on gastrointestinal microbiota in rats. J. Appl. Microbiol. 2017, 122, 1627–1638. [Google Scholar] [CrossRef]
  113. Dupuit, M.; Chavanelle, V.; Chassaing, B.; Perriere, F.; Etienne, M.; Plissonneau, C.; Boscaro, A.; Barnich, N.; Pialoux, V.; Maugard, T.; et al. The TOTUM-63 Supplement and High-Intensity Interval Training Combination Limits Weight Gain, Improves Glycemic Control, and Influences the Composition of Gut Mucosa-Associated Bacteria in Rats on a High Fat Diet. Nutrients 2021, 13, 1569. [Google Scholar] [CrossRef]
  114. Evans, C.C.; LePard, K.J.; Kwak, J.W.; Stancukas, M.C.; Laskowski, S.; Dougherty, J.; Moulton, L.; Glawe, A.; Wang, Y.; Leone, V.; et al. Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity. PLoS ONE 2014, 9, e92193. [Google Scholar] [CrossRef]
  115. Mika, A.; Van Treuren, W.; González, A.; Herrera, J.J.; Knight, R.; Fleshner, M. Exercise is More Effective at Altering Gut Microbial Composition and Producing Stable Changes in Lean Mass in Juvenile versus Adult Male F344 Rats. PLoS ONE 2015, 10, e0125889. [Google Scholar] [CrossRef]
  116. Plissonneau, C.; Capel, F.; Chassaing, B.; Dupuit, M.; Maillard, F.; Wawrzyniak, I.; Combaret, L.; Dutheil, F.; Etienne, M.; Mairesse, G.; et al. High-Intensity Interval Training and α-Linolenic Acid Supplementation Improve DHA Conversion and Increase the Abundance of Gut Mucosa-Associated Oscillospira Bacteria. Nutrients 2021, 13, 788. [Google Scholar] [CrossRef]
  117. Allen, J.M.; Mailing, L.J.; Niemiro, G.M.; Moore, R.; Cook, M.D.; White, B.A.; Holscher, H.D.; Woods, J.A. Exercise Alters Gut Microbiota Composition and Function in Lean and Obese Humans. Med. Sci. Sports Exerc. 2018, 50, 747–757. [Google Scholar] [CrossRef]
  118. Matsumoto, M.; Inoue, R.; Tsukahara, T.; Ushida, K.; Chiji, H.; Matsubara, N.; Hara, H. Voluntary running exercise alters microbiota composition and increases n-butyrate concentration in the rat cecum. Biosci. Biotechnol. Biochem. 2008, 72, 572–576. [Google Scholar] [CrossRef]
  119. Ticinesi, A.; Lauretani, F.; Tana, C.; Nouvenne, A.; Ridolo, E.; Meschi, T. Exercise and immune system as modulators of intestinal microbiome: Implications for the gut-muscle axis hypothesis. Exerc. Immunol. Rev. 2019, 25, 84–95. [Google Scholar]
  120. Choi, J.J.; Eum, S.Y.; Rampersaud, E.; Daunert, S.; Abreu, M.T.; Toborek, M. Exercise attenuates PCB-induced changes in the mouse gut microbiome. Environ. Health Perspect. 2013, 121, 725–730. [Google Scholar] [CrossRef]
  121. Queipo-Ortuno, M.I.; Seoane, L.M.; Murri, M.; Pardo, M.; Gomez-Zumaquero, J.M.; Cardona, F.; Casanueva, F.; Tinahones, F.J. Gut microbiota composition in male rat models under different nutritional status and physical activity and its association with serum leptin and ghrelin levels. PLoS ONE 2013, 8, e65465. [Google Scholar] [CrossRef] [PubMed]
  122. Kang, S.S.; Jeraldo, P.R.; Kurti, A.; Miller, M.E.; Cook, M.D.; Whitlock, K.; Goldenfeld, N.; Woods, J.A.; White, B.A.; Chia, N.; et al. Diet and exercise orthogonally alter the gut microbiome and reveal independent associations with anxiety and cognition. Mol. Neurodegener. 2014, 9, 36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Allen, J.M.; Berg Miller, M.E.; Pence, B.D.; Whitlock, K.; Nehra, V.; Gaskins, H.R.; White, B.A.; Fryer, J.D.; Woods, J.A. Voluntary and forced exercise differentially alters the gut microbiome in C57BL/6J mice. J. Appl. Physiol. 2015, 118, 1059–1066. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Denou, E.; Marcinko, K.; Surette, M.G.; Steinberg, G.R.; Schertzer, J.D. High-intensity exercise training increases the diversity and metabolic capacity of the mouse distal gut microbiota during diet-induced obesity. Am. J. Physiol. Endocrinol. Metab. 2016, 310, E982–E993. [Google Scholar] [CrossRef]
  125. Allen, J.M.; Mailing, L.J.; Cohrs, J.; Salmonson, C.; Fryer, J.D.; Nehra, V.; Hale, V.L.; Kashyap, P.; White, B.A.; Woods, J.A. Exercise training-induced modification of the gut microbiota persists after microbiota colonization and attenuates the response to chemically-induced colitis in gnotobiotic mice. Gut Microbes 2018, 9, 115–130. [Google Scholar] [CrossRef] [Green Version]
  126. McCabe, L.R.; Irwin, R.; Tekalur, A.; Evans, C.; Schepper, J.D.; Parameswaran, N.; Ciancio, M. Exercise prevents high fat diet-induced bone loss, marrow adiposity and dysbiosis in male mice. Bone 2019, 118, 20–31. [Google Scholar] [CrossRef]
  127. Maillard, F.; Vazeille, E.; Sauvanet, P.; Sirvent, P.; Bonnet, R.; Combaret, L.; Chausse, P.; Chevarin, C.; Otero, Y.F.; Delcros, G.; et al. Preventive Effect of Spontaneous Physical Activity on the Gut-Adipose Tissue in a Mouse Model That Mimics Crohn’s Disease Susceptibility. Cells 2019, 8, 33. [Google Scholar] [CrossRef] [Green Version]
  128. Ribeiro, F.M.; Ribeiro, C.F.A.; Garcia, A.; Castro, A.P.; Almeida, J.A.; Franco, O.L.; Petriz, B.A. Limited Effects of Low-to-Moderate Aerobic Exercise on the Gut Microbiota of Mice Subjected to a High-Fat Diet. Nutrients 2019, 11, 149. [Google Scholar] [CrossRef] [Green Version]
  129. Aoki, T.; Oyanagi, E.; Watanabe, C.; Kobiki, N.; Miura, S.; Yokogawa, Y.; Kitamura, H.; Teramoto, F.; Kremenik, M.J.; Yano, H. The Effect of Voluntary Exercise on Gut Microbiota in Partially Hydrolyzed Guar Gum Intake Mice under High-Fat Diet Feeding. Nutrients 2020, 12, 2508. [Google Scholar] [CrossRef]
  130. Wang, G.; Zhou, H.; Zhang, L.; Li, R.; Luo, L.; Yu, Z.; Wan, Z. Effects of high-intensity interval training on gut microbiota profiles in 12 months’ old ICR mice. J. Physiol. Biochem. 2020, 76, 539–548. [Google Scholar] [CrossRef]
  131. Rettedal, E.A.; Cree, J.M.E.; Adams, S.E.; MacRae, C.; Skidmore, P.M.L.; Cameron-Smith, D.; Gant, N.; Blenkiron, C.; Merry, T.L. Short-term high-intensity interval training exercise does not affect gut bacterial community diversity or composition of lean and overweight men. Exp. Physiol. 2020, 105, 1268–1279. [Google Scholar] [CrossRef]
  132. Bressa, C.; Bailén-Andrino, M.; Pérez-Santiago, J.; González-Soltero, R.; Pérez, M.; Montalvo-Lominchar, M.G.; Maté-Muñoz, J.L.; Domínguez, R.; Moreno, D.; Larrosa, M. Differences in gut microbiota profile between women with active lifestyle and sedentary women. PLoS ONE 2017, 12, e0171352. [Google Scholar] [CrossRef] [Green Version]
  133. Shi, J.; Wang, Y.; He, J.; Li, P.; Jin, R.; Wang, K.; Xu, X.; Hao, J.; Zhang, Y.; Liu, H.; et al. Intestinal microbiota contributes to colonic epithelial changes in simulated microgravity mouse model. FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. 2017, 31, 3695–3709. [Google Scholar] [CrossRef] [Green Version]
  134. Crucian, B.E.; Choukèr, A.; Simpson, R.J.; Mehta, S.; Marshall, G.; Smith, S.M.; Zwart, S.R.; Heer, M.; Ponomarev, S.; Whitmire, A.; et al. Immune System Dysregulation During Spaceflight: Potential Countermeasures for Deep Space Exploration Missions. Front. Immunol. 2018, 9, 1437. [Google Scholar] [CrossRef]
  135. Garrett-Bakelman, F.E.; Darshi, M.; Green, S.J.; Gur, R.C.; Lin, L.; Macias, B.R.; McKenna, M.J.; Meydan, C.; Mishra, T.; Nasrini, J.; et al. The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Science 2019, 364, eaau8650. [Google Scholar] [CrossRef]
  136. Voorhies, A.A.; Mark Ott, C.; Mehta, S.; Pierson, D.L.; Crucian, B.E.; Feiveson, A.; Oubre, C.M.; Torralba, M.; Moncera, K.; Zhang, Y.; et al. Study of the impact of long-duration space missions at the International Space Station on the astronaut microbiome. Sci. Rep. 2019, 9, 9911. [Google Scholar] [CrossRef]
  137. Jiang, P.; Green, S.J.; Chlipala, G.E.; Turek, F.W.; Vitaterna, M.H. Reproducible changes in the gut microbiome suggest a shift in microbial and host metabolism during spaceflight. Microbiome 2019, 7, 113. [Google Scholar] [CrossRef]
  138. Jollet, M.; Nay, K.; Chopard, A.; Bareille, M.-P.; Beck, A.; Ollendorff, V.; Vernus, B.; Bonnieu, A.; Mariadassou, M.; Rué, O.; et al. Does Physical Inactivity Induce Significant Changes in Human Gut Microbiota? New Answers Using the Dry Immersion Hypoactivity Model. Nutrients 2021, 13, 3865. [Google Scholar] [CrossRef]
  139. Ritchie, L.E.; Taddeo, S.S.; Weeks, B.R.; Lima, F.; Bloomfield, S.A.; Azcarate-Peril, M.A.; Zwart, S.R.; Smith, S.M.; Turner, N.D. Space Environmental Factor Impacts upon Murine Colon Microbiota and Mucosal Homeostasis. PLoS ONE 2015, 10, e0125792. [Google Scholar] [CrossRef]
  140. Demangel, R.; Treffel, L.; Py, G.; Brioche, T.; Pagano, A.F.; Bareille, M.-P.; Beck, A.; Pessemesse, L.; Candau, R.; Gharib, C.; et al. Early structural and functional signature of 3-day human skeletal muscle disuse using the dry immersion model. J. Physiol. 2017, 595, 4301–4315. [Google Scholar] [CrossRef]
  141. Navasiolava, N.M.; Custaud, M.-A.; Tomilovskaya, E.S.; Larina, I.M.; Mano, T.; Gauquelin-Koch, G.; Gharib, C.; Kozlovskaya, I.B. Long-term dry immersion: Review and prospects. Eur. J. Appl. Physiol. 2011, 111, 1235–1260. [Google Scholar] [CrossRef] [Green Version]
  142. Treffel, L.; Mkhitaryan, K.; Gellee, S.; Gauquelin-Koch, G.; Gharib, C.; Blanc, S.; Millet, C. Intervertebral Disc Swelling Demonstrated by 3D and Water Content Magnetic Resonance Analyses after a 3-Day Dry Immersion Simulating Microgravity. Front. Physiol. 2016, 7, 605. [Google Scholar] [CrossRef] [Green Version]
  143. Cani, P.D.; Delzenne, N.M. The role of the gut microbiota in energy metabolism and metabolic disease. Curr. Pharm. Des. 2009, 15, 1546–1558. [Google Scholar] [CrossRef] [Green Version]
  144. Bindels, L.B.; Beck, R.; Schakman, O.; Martin, J.C.; De Backer, F.; Sohet, F.M.; Dewulf, E.M.; Pachikian, B.D.; Neyrinck, A.M.; Thissen, J.-P.; et al. Restoring specific lactobacilli levels decreases inflammation and muscle atrophy markers in an acute leukemia mouse model. PLoS ONE 2012, 7, e37971. [Google Scholar] [CrossRef] [Green Version]
  145. Bäckhed, F.; Manchester, J.K.; Semenkovich, C.F.; Gordon, J.I. Mechanisms underlying the resistance to diet-induced obesity in germ-free mice. Proc. Natl. Acad. Sci. USA 2007, 104, 979–984. [Google Scholar] [CrossRef] [Green Version]
  146. Delzenne, N.M.; Cani, P.D. Gut microflora is a key player in host energy homeostasis. Med. Sci. M/S 2008, 24, 505–510. [Google Scholar] [CrossRef] [Green Version]
  147. Anhê, F.F.; Varin, T.V.; Le Barz, M.; Desjardins, Y.; Levy, E.; Roy, D.; Marette, A. Gut Microbiota Dysbiosis in Obesity-Linked Metabolic Diseases and Prebiotic Potential of Polyphenol-Rich Extracts. Curr. Obes. Rep. 2015, 4, 389–400. [Google Scholar] [CrossRef]
  148. Gomes, A.C.; Hoffmann, C.; Mota, J.F. The human gut microbiota: Metabolism and perspective in obesity. Gut Microbes 2018, 9, 308–325. [Google Scholar] [CrossRef] [Green Version]
  149. Isolauri, E. Microbiota and Obesity. Nestle Nutr. Inst. Workshop Ser. 2017, 88, 95–105. [Google Scholar] [CrossRef] [Green Version]
  150. Lippert, K.; Kedenko, L.; Antonielli, L.; Kedenko, I.; Gemeier, C.; Leitner, M.; Kautzky-Willer, A.; Paulweber, B.; Hackl, E. Gut microbiota dysbiosis associated with glucose metabolism disorders and the metabolic syndrome in older adults. Benef. Microbes 2017, 8, 545–556. [Google Scholar] [CrossRef]
  151. Goffredo, M.; Mass, K.; Parks, E.J.; Wagner, D.A.; McClure, E.A.; Graf, J.; Savoye, M.; Pierpont, B.; Cline, G.; Santoro, N. Role of Gut Microbiota and Short Chain Fatty Acids in Modulating Energy Harvest and Fat Partitioning in Youth. J. Clin. Endocrinol. Metab. 2016, 101, 4367–4376. [Google Scholar] [CrossRef] [PubMed]
  152. Magne, F.; Gotteland, M.; Gauthier, L.; Zazueta, A.; Pesoa, S.; Navarrete, P.; Balamurugan, R. The Firmicutes/Bacteroidetes Ratio: A Relevant Marker of Gut Dysbiosis in Obese Patients? Nutrients 2020, 12, 1474. [Google Scholar] [CrossRef] [PubMed]
  153. Claesson, M.J.; Jeffery, I.B.; Conde, S.; Power, S.E.; O’Connor, E.M.; Cusack, S.; Harris, H.M.B.; Coakley, M.; Lakshminarayanan, B.; O’Sullivan, O.; et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 2012, 488, 178–184. [Google Scholar] [CrossRef] [PubMed]
  154. Schieber, A.M.P.; Lee, Y.M.; Chang, M.W.; Leblanc, M.; Collins, B.; Downes, M.; Evans, R.M.; Ayres, J.S. Disease tolerance mediated by microbiome E. coli involves inflammasome and IGF-1 signaling. Science 2015, 350, 558–563. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  155. Varian, B.J.; Gourishetti, S.; Poutahidis, T.; Lakritz, J.R.; Levkovich, T.; Kwok, C.; Teliousis, K.; Ibrahim, Y.M.; Mirabal, S.; Erdman, S.E. Beneficial bacteria inhibit cachexia. Oncotarget 2016, 7, 11803–11816. [Google Scholar] [CrossRef] [Green Version]
  156. Bindels, L.B.; Delzenne, N.M. Muscle wasting: The gut microbiota as a new therapeutic target? Int. J. Biochem. Cell Biol. 2013, 45, 2186–2190. [Google Scholar] [CrossRef]
  157. Yan, H.; Diao, H.; Xiao, Y.; Li, W.; Yu, B.; He, J.; Yu, J.; Zheng, P.; Mao, X.; Luo, Y.; et al. Gut microbiota can transfer fiber characteristics and lipid metabolic profiles of skeletal muscle from pigs to germ-free mice. Sci. Rep. 2016, 6, 31786. [Google Scholar] [CrossRef] [Green Version]
  158. Nay, K.; Jollet, M.; Goustard, B.; Baati, N.; Vernus, B.; Pontones, M.; Lefeuvre-Orfila, L.; Bendavid, C.; Rué, O.; Mariadassou, M.; et al. Gut bacteria are critical for optimal muscle function: A potential link with glucose homeostasis. Am. J. Physiology. Endocrinol. Metab. 2019, 317, E158–E171. [Google Scholar] [CrossRef]
  159. Gizard, F.; Fernandez, A.; De Vadder, F. Interactions between gut microbiota and skeletal muscle. Nutr. Metab. Insights 2020, 13, 1178638820980490. [Google Scholar] [CrossRef]
  160. Grosicki, G.J.; Fielding, R.A.; Lustgarten, M.S. Gut Microbiota Contribute to Age-Related Changes in Skeletal Muscle Size, Composition, and Function: Biological Basis for a Gut-Muscle Axis. Calcif. Tissue Int. 2018, 102, 433–442. [Google Scholar] [CrossRef] [Green Version]
  161. Lahiri, S.; Kim, H.; Garcia-Perez, I.; Reza, M.M.; Martin, K.A.; Kundu, P.; Cox, L.M.; Selkrig, J.; Posma, J.M.; Zhang, H.; et al. The gut microbiota influences skeletal muscle mass and function in mice. Sci. Transl. Med. 2019, 11, eaan5662. [Google Scholar] [CrossRef] [Green Version]
  162. Donati Zeppa, S.; Agostini, D.; Gervasi, M.; Annibalini, G.; Amatori, S.; Ferrini, F.; Sisti, D.; Piccoli, G.; Barbieri, E.; Sestili, P.; et al. Mutual Interactions among Exercise, Sport Supplements and Microbiota. Nutrients 2019, 12, 17. [Google Scholar] [CrossRef] [Green Version]
  163. Perez-Guisado, J. Ketogenic diets: Additional benefits to the weight loss and unfounded secondary effects. Arch. Latinoam. Nutr. 2008, 58, 323–329. [Google Scholar]
  164. Paoli, A.; Mancin, L.; Bianco, A.; Thomas, E.; Mota, J.F.; Piccini, F. Ketogenic Diet and Microbiota: Friends or Enemies? Genes 2019, 10, 534. [Google Scholar] [CrossRef] [Green Version]
  165. Ma, D.; Wang, A.C.; Parikh, I.; Green, S.J.; Hoffman, J.D.; Chlipala, G.; Murphy, M.P.; Sokola, B.S.; Bauer, B.; Hartz, A.M.S.; et al. Ketogenic diet enhances neurovascular function with altered gut microbiome in young healthy mice. Sci. Rep. 2018, 8, 6670. [Google Scholar] [CrossRef] [Green Version]
  166. Olson, C.A.; Vuong, H.E.; Yano, J.M.; Liang, Q.Y.; Nusbaum, D.J.; Hsiao, E.Y. The Gut Microbiota Mediates the Anti-Seizure Effects of the Ketogenic Diet. Cell 2018, 173, 1728–1741.e1713. [Google Scholar] [CrossRef] [Green Version]
  167. Swidsinski, A.; Dorffel, Y.; Loening-Baucke, V.; Gille, C.; Goktas, O.; Reisshauer, A.; Neuhaus, J.; Weylandt, K.H.; Guschin, A.; Bock, M. Reduced Mass and Diversity of the Colonic Microbiome in Patients with Multiple Sclerosis and Their Improvement with Ketogenic Diet. Front. Microbiol. 2017, 8, 1141. [Google Scholar] [CrossRef]
  168. Tagliabue, A.; Ferraris, C.; Uggeri, F.; Trentani, C.; Bertoli, S.; de Giorgis, V.; Veggiotti, P.; Elli, M. Short-term impact of a classical ketogenic diet on gut microbiota in GLUT1 Deficiency Syndrome: A 3-month prospective observational study. Clin. Nutr. ESPEN 2017, 17, 33–37. [Google Scholar] [CrossRef]
  169. Burke, L.M. Ketogenic low-CHO, high-fat diet: The future of elite endurance sport? J. Physiol. 2021, 599, 819–843. [Google Scholar] [CrossRef]
  170. Leite, G.S.F.; Resende Master Student, A.S.; West, N.P.; Lancha, A.H., Jr. Probiotics and sports: A new magic bullet? Nutrition 2019, 60, 152–160. [Google Scholar] [CrossRef] [Green Version]
  171. Bermon, S.; Petriz, B.; Kajeniene, A.; Prestes, J.; Castell, L.; Franco, O.L. The microbiota: An exercise immunology perspective. Exerc. Immunol. Rev. 2015, 21, 70–79. [Google Scholar] [PubMed]
  172. Pyne, D.B.; West, N.P.; Cox, A.J.; Cripps, A.W. Probiotics supplementation for athletes—clinical and physiological effects. Eur. J. Sport Sci. 2015, 15, 63–72. [Google Scholar] [CrossRef] [PubMed]
  173. Lamprecht, M.; Frauwallner, A. Exercise, intestinal barrier dysfunction and probiotic supplementation. Med. Sport Sci. 2012, 59, 47–56. [Google Scholar] [CrossRef] [PubMed]
  174. West, N.P.; Pyne, D.B.; Cripps, A.W.; Hopkins, W.G.; Eskesen, D.C.; Jairath, A.; Christophersen, C.T.; Conlon, M.A.; Fricker, P.A. Lactobacillus fermentum (PCC(R)) supplementation and gastrointestinal and respiratory-tract illness symptoms: A randomised control trial in athletes. Nutr. J. 2011, 10, 30. [Google Scholar] [CrossRef] [Green Version]
  175. Martarelli, D.; Verdenelli, M.C.; Scuri, S.; Cocchioni, M.; Silvi, S.; Cecchini, C.; Pompei, P. Effect of a probiotic intake on oxidant and antioxidant parameters in plasma of athletes during intense exercise training. Curr. Microbiol. 2011, 62, 1689–1696. [Google Scholar] [CrossRef]
  176. Huang, W.C.; Lee, M.C.; Lee, C.C.; Ng, K.S.; Hsu, Y.J.; Tsai, T.Y.; Young, S.L.; Lin, J.S.; Huang, C.C. Effect of Lactobacillus plantarum TWK10 on Exercise Physiological Adaptation, Performance, and Body Composition in Healthy Humans. Nutrients 2019, 11, 2836. [Google Scholar] [CrossRef] [Green Version]
  177. Fu, S.K.; Tseng, W.C.; Tseng, K.W.; Lai, C.C.; Tsai, Y.C.; Tai, H.L.; Hsu, C.C. Effect of Daily Oral Lactobacillus plantarum PS128 on Exercise Capacity Recovery after a Half-Marathon. Nutrients 2021, 13, 4023. [Google Scholar] [CrossRef]
  178. Gepner, Y.; Hoffman, J.R.; Shemesh, E.; Stout, J.R.; Church, D.D.; Varanoske, A.N.; Zelicha, H.; Shelef, I.; Chen, Y.; Frankel, H.; et al. Combined effect of Bacillus coagulans GBI-30, 6086 and HMB supplementation on muscle integrity and cytokine response during intense military training. J. Appl. Physiol. 2017, 123, 11–18. [Google Scholar] [CrossRef] [Green Version]
  179. Jager, R.; Shields, K.A.; Lowery, R.P.; De Souza, E.O.; Partl, J.M.; Hollmer, C.; Purpura, M.; Wilson, J.M. Probiotic Bacillus coagulans GBI-30, 6086 reduces exercise-induced muscle damage and increases recovery. PeerJ 2016, 4, e2276. [Google Scholar] [CrossRef] [Green Version]
  180. Donnelly, J.E.; Blair, S.N.; Jakicic, J.M.; Manore, M.M.; Rankin, J.W.; Smith, B.K.; American College of Sports Medicine. American College of Sports Medicine Position Stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med. Sci. Sports Exerc. 2009, 41, 459–471. [Google Scholar] [CrossRef]
  181. Weston, K.S.; Wisloff, U.; Coombes, J.S. High-intensity interval training in patients with lifestyle-induced cardiometabolic disease: A systematic review and meta-analysis. Br. J. Sports Med. 2014, 48, 1227–1234. [Google Scholar] [CrossRef]
  182. Dupuit, M.; Maillard, F.; Pereira, B.; Marquezi, M.L.; Lancha, A.H., Jr.; Boisseau, N. Effect of high intensity interval training on body composition in women before and after menopause: A meta-analysis. Exp. Physiol. 2020, 105, 1470–1490. [Google Scholar] [CrossRef]
  183. Maillard, F.; Pereira, B.; Boisseau, N. Effect of High-Intensity Interval Training on Total, Abdominal and Visceral Fat Mass: A Meta-Analysis. Sports Med. 2018, 48, 269–288. [Google Scholar] [CrossRef]
  184. Colberg, S.R.; Sigal, R.J.; Yardley, J.E.; Riddell, M.C.; Dunstan, D.W.; Dempsey, P.C.; Horton, E.S.; Castorino, K.; Tate, D.F. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care 2016, 39, 2065–2079. [Google Scholar] [CrossRef] [Green Version]
  185. Francois, M.E.; Little, J.P. Effectiveness and safety of high-intensity interval training in patients with type 2 diabetes. Diabetes Spectr. 2015, 28, 39–44. [Google Scholar] [CrossRef] [Green Version]
  186. Wormgoor, S.G.; Dalleck, L.C.; Zinn, C.; Borotkanics, R.; Harris, N.K. High-Intensity Interval Training Is Equivalent to Moderate-Intensity Continuous Training for Short- and Medium-Term Outcomes of Glucose Control, Cardiometabolic Risk, and Microvascular Complication Markers in Men With Type 2 Diabetes. Front. Endocrinol. 2018, 9, 475. [Google Scholar] [CrossRef]
  187. Dupuit, M.; Rance, M.; Morel, C.; Bouillon, P.; Boscaro, A.; Martin, V.; Vazeille, E.; Barnich, N.; Chassaing, B.; Boisseau, N. Impact of Concurrent Training on Body Composition and Gut Microbiota in Postmenopausal Women with Overweight or Obesity. Med. Sci. Sports Exerc. 2021. [Google Scholar] [CrossRef]
  188. Albracht-Schulte, K.; Kalupahana, N.S.; Ramalingam, L.; Wang, S.; Rahman, S.M.; Robert-McComb, J.; Moustaid-Moussa, N. Omega-3 fatty acids in obesity and metabolic syndrome: A mechanistic update. J. Nutr. Biochem. 2018, 58, 1–16. [Google Scholar] [CrossRef]
  189. Calder, P.C. Omega-3 fatty acids and inflammatory processes: From molecules to man. Biochem. Soc. Trans. 2017, 45, 1105–1115. [Google Scholar] [CrossRef] [Green Version]
  190. Patterson, E.; O’Doherty, R.M.; Murphy, E.F.; Wall, R.; O’Sullivan, O.; Nilaweera, K.; Fitzgerald, G.F.; Cotter, P.D.; Ross, R.P.; Stanton, C. Impact of dietary fatty acids on metabolic activity and host intestinal microbiota composition in C57BL/6J mice. Br. J. Nutr. 2014, 111, 1905–1917. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Disease-related gut microbiota dysbiosis.
Figure 1. Disease-related gut microbiota dysbiosis.
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Figure 2. Athletic gut microbiota: main reviews [80,90,91,92,94,95].
Figure 2. Athletic gut microbiota: main reviews [80,90,91,92,94,95].
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Figure 3. The “Nutrition-Physical activity-Microbiota” triad for health and sports performance: what is known and what remains to be discovered.
Figure 3. The “Nutrition-Physical activity-Microbiota” triad for health and sports performance: what is known and what remains to be discovered.
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Table 1. Gut microbiota in athletes—original articles.
Table 1. Gut microbiota in athletes—original articles.
Sports Type/Activity LevelMain ResultsAuthors-Year
Professional rugby players
High level
Gut microbiota with higher richness, decrease of the phylum Bacteroidetes and increase of the genus Akkermansia prevalence.Clarke et al., 2014 [96]
39 healthy participants
Various cardiorespiratory fitness levels with similar age, body mass index, and diets
VO2 peak explained 20% of the variation in taxonomic richness. Increased abundances of key butyrate-producing taxa (Clostridiales, Roseburia, Lachnospiraceae, and Erysipelotrichaceae) in physically fit participants and increase in butyrate levels.Estaki et al., 2016 [97]
Boston Marathon participants
Treadmill-exercised C57BL/6 mice with acute supplementation of Veillonella atypica
Higher prevalence of Veillonella atypica in the athletes’ fecal samples after the marathon.
Inoculation of this strain in mice significantly increased exhaustive treadmill run time via its metabolic conversion of exercise-induced lactate into propionate.
Scheiman et al., 2019 [98]
Bodybuilders and distance runners compared to healthy sedentary menGut microbiota α and β diversity similar in the two athlete groups. At the genus and species level, differences between sport disciplines, but associated with diet variations.Jang et al., 2019 [100]
37 elite athletes who competed in 16 different sports/Olympic levelThe gut microbiome and metabolome differ among sports, classified in groups. Diet is not the driver of these differences.O’Donovan et al., 2020 [99]
Table 2. Effect of training on gut microbiota—animal studies.
Table 2. Effect of training on gut microbiota—animal studies.
Training ModalitiesMain Results on Gut Microbiota CompositionAuthors-Year
Wistar male rats
Standard diet ad libitum
Spontaneous exercise: wheel, 5 weeks
↑ SM7/11 and T287 (Firmicutes)Matsumoto et al., 2008 [118]
C57BL/6J male mice
Standard diet ad libitum
Spontaneous exercise: wheel, 5 weeks
↑ Lactobacillales and Bacillales (Firmicutes)
↓ Clostridiales (Firmicutes), Bacteroidales (Bacteroidetes), and Erysipelotrichales (Tenericutes)
Choi et al., 2013 [120]
Sprague-Dawley male rats
Standard diet ad libitum
Spontaneous exercise: wheel, 6 days
Lactobacillus, Bifidobacterium and Blautia coccoides-Eubacterium rectale groupQueipo-Ortuño et al., 2013 [121]
8-weel-old C57BL/6J male mice
Standard diet or high-fat diet
Wheel 7 m.min−1
60 min, 5 sessions/week for 14 weeks
↑ Firmicutes, Lachnospiraceae, Peptostreptococcaceae, Pseudomonadaceae, Cryomorphaceae, Phyllobacteriaceae, Alcaligenaceae, Rhizobiaceae,
Incertae_Sedis_IV, Microbacteriaceae, Nocardiaceae, Coriobacteriaceae, Flavobacteriaceae, Sphingobacteriaceae, Bradyrhizobiaceae, Burkholderiaceae, Comamonadaceae
↓ Bacteroidetes, Streptococcus (HFD), Tenericutes (standard diet), Porphyromonadaceae, Peptococcaceae, Streptococcaceae
Kang et al., 2014 [122]
C57BL/6J male mice
Low- or high-fat diet
Spontaneous exercise: wheel, 12 weeks
↑ Bacteroidetes/Firmicutes ratio, Clostridiaceae, Lachnospiraceae, Ruminococcaceae, S24-7
↓ Actinobacteria, Lactobacillaceae, Turicibacteraceae, Erysipelotrichaceae, Bifidobacteriaceae
Evans et al., 2014 [114]
24- or 70-day-old Fischer F344 male rats
Standard diet ad libitum
Spontaneous exercise: wheel, 6 weeks
Juvenile rats: ↑ Bacteroidetes, Blautia spp., Anaerostipes spp., Methanosphaera spp.
↓ Firmicutes, Desulfovibrio spp. and Rikenellaceae
Adult rats: ↑ Turicibacter spp. and Rikenellaceae
Mika et al., 2015 [115]
6-week-old C57BL/6J male mice
Standard diet
Spontaneous exercise: Wheel, 30 days
Controlled treadmill exercise: 8–12 m.min−1, 5% slope, 40 min, 5 sessions/week for 6 weeks
Spontaneous exercise: ↑ Anaerotruncus
and ↓ Prevotella
Controlled exercise: ↑ Tenericutes, Proteobacteria, Nautilia, Oscillospira and Dorea
Allen et al., 2015 [123]
C57BL/6J male mice
Treadmill HIIT, 3 sessions/week for 6 weeks
after 6 weeks of high-fat diet
↑ Bacteroidetes/Firmicutes ratio, Bacteroidales, Dorea and ↓ Clostridiaceae in cecal samples
↑ Actinobacteria in duodenum and jejunum samples
Lactobacillus in ileum samples
↑ Bacteroidetes, Bacteroidales, Dorea and ↓ Clostridium and Lachnospiraceae in colon samples
↑ Bacteroidetes/Firmicutes ratio in fecal samples
Denou et al., 2016 [124]
Wistar Male Rats
Standard diet
Treadmill MICT, 5 times/week for 12 weeks
Treadmill HIIT, 5 times/week for 12 weeks
MICT training: ↑ Parasutterella excrementihominis, Lactobacillus johnsonii, Bifidobacteriaceae, Erysipelotrichaceae, Clostridium geopurificans
HIIT training: ↑ Clostridium saccharolyticum, C. geopurificans
Batacan et al., 2017 [112]
C57BL/6J male mice
Standard diet ad libitum
Spontaneous exercise: wheel, 6 weeks
Anaerostipes, Akkermansia spp., Lachnospiraceae,
Ruminococcus spp., Parabacteroides spp.
Allen et al., 2018 [125]
C57BL/6J male mice
Standard diet ad libitum
Controlled training: treadmill, 4 weeks
More bacterial diversity in the exercise group
↑ Butyricimonas, Akkermansia
Liu et al., 2017 [83]
C57BL/6J male mice
Standard diet or high-fat diet
Spontaneous exercise: wheel, 14 weeks
↓ Firmicutes/Bacteroidetes ratioMcCabe et al., 2018 [126]
CEABAC10 male mice
High-fat diet
Spontaneous exercise: wheel, 12 weeks
Anaerotruncus, Parabacteroides, Unclassified Desulfovibrionaceae, Oscillospira, RuminococcusMaillard et al., 2019 [127]
C57BL/6J male mice
Standard diet or high-fat diet
Controlled training: treadmill, 2 months
Vagococcus in training group with standard diet
Vagococcus and ↓ Proteus in training group with high-fat diet
Ribeiro et al., 2019 [128]
C57BL/6J male mice
Standard diet or high-fat diet
Spontaneous exercise: wheel, 10 weeks
↑ Bacteroidetes and ↓ Lactobacillus in training group with standard diet; ↑ α diversity and ↓ Lactobacillus in training group with high-fat dietAoki et al., 2020 [129]
ICR male mice
Standard diet
HIIT running, 7 weeks
↑ TM7, Dorea, Dehalobacterium
↓ Proteobacteria, Candidatus arthromitus
Wang et al., 2020 [130]
Wistar male rats
Standard diet or high-fat diet ± Totum-63
HIIT running, 12 weeks
Anaeroplasma, Christensenellaceae in HIIT group
Anaeroplasma, Christensenellaceae, Oscillospira in HIIT+Totum-63 group
Dupuit et al., 2021 [113]
Wistar male rats
Standart diet or high-fat diet ± linseed oil
HIIT running, 12 weeks
Prevotella, YS2, Anaeroplasma and ↓ Clostridiales
in HIIT group
Prevotella, YS2, Anaeroplasma, Oscillospira
and ↓ Clostridiales in HIIT + linseed oil group
Plissonneau et al., 2021 [116]
↑: increase; ↓: decrease; HIIT: High-Intensity Interval Training; MICT: Moderate-Intensity Continuous Training.
Table 3. Effect of hypoactivity on gut microbiota.
Table 3. Effect of hypoactivity on gut microbiota.
Population/Hypoactivity ModelMain ResultsAuthors-Year
Premenopausal women (n = 40):
19 active and 21 sedentary
Inverse association between sedentary parameters and microbiota richness
↓ Bifidobacterium spp., Paraprevotella, Roseburia hominis, Akkermansia muciniphila, and Faecalibacterium prausnitzii in sedentary women
Bressa et al., 2017 [132]
Hindlimb unloading for 28 days
Increased microbial evenness, but not richness in hindlimb unloading vs. control group? ↓ Bacteriodetes, ↑ Firmicutes
At the class/order level, ↑ Clostridia/Clostridiales and ↓ Bacteroidia/Bacteroidales
At the family level, ↑ abundance of Lachnospiraceae and ↓ abundance of S247
Shi et al., 2017 [133]
Microbial content of human samples collected pre- and post-flight evaluated on culturable bacteria (not the genomic profile)Lactobacilli and Bifidobacteria post-flight
Enterobacteria and Clostridia post-flight
Crucian et al., 2018 [134]
The NASA Twins Study:
twins (one on ground and the other in the International Space Station, for 25 months)
No impact on microbiome diversity
Significant and spaceflight-specific increase in the Firmicutes/Bacteriodetes ratio
Garrett-Bakelman et al., 2019 [135]
6 to 12 months in the International Space Station
↑ Shannon α diversity and richness. Changes in 17 gastrointestinal genus abundance during spaceflight
13/17 genera belonged to the phylum Firmicutes, mostly to the order Clostridiales ↓ Akkermansia, Ruminococcus, Pseudobutyrivibrio and Fusicatenibacter
Voorhies et al., 2019 [136]
C57BL/6 female mice
37 days in the International Space Station
Unchanged richness of microbial community
Higher Firmicutes/Bacteriodetes ratio with ↓ phylum Bacteriodetes), ↑ genera of the Lachnospiraceae family and Ruminococcaceae UCG-010 genus ↓ Hydrogenoanaerobacterium genus and Tyzzerella genus
Jiang et al., 2019 [137]
Healthy men (n = 14)
Dry immersion for 5 days
Unchanged α and β diversity indices
↑ Clostridiales order and Lachnospiraceae family
↓ Propionate levels in post-dry immersion stool samples
Jollet et al., 2021 [138]
↑: increase; ↓: decrease.
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Boisseau, N.; Barnich, N.; Koechlin-Ramonatxo, C. The Nutrition-Microbiota-Physical Activity Triad: An Inspiring New Concept for Health and Sports Performance. Nutrients 2022, 14, 924.

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Boisseau N, Barnich N, Koechlin-Ramonatxo C. The Nutrition-Microbiota-Physical Activity Triad: An Inspiring New Concept for Health and Sports Performance. Nutrients. 2022; 14(5):924.

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Boisseau, Nathalie, Nicolas Barnich, and Christelle Koechlin-Ramonatxo. 2022. "The Nutrition-Microbiota-Physical Activity Triad: An Inspiring New Concept for Health and Sports Performance" Nutrients 14, no. 5: 924.

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