Exercise-Induced Modulation of the Gut Microbiota: Mechanisms, Evidence, and Implications for Athlete Health

Abstract

The gut microbiota plays a fundamental role in human physiology by influencing metabolism, immunity, and neuroendocrine communication. Growing evidence suggests that physical exercise modulates gut microbial composition; however, study findings remain inconsistent due to variations in design, training type, and population characteristics. This review summarizes current research on how different forms, intensities, and frequencies of exercise shape the gut microbiota and discusses their implications for athlete health and performance. Moderate and sustained physical activity generally promotes higher microbial diversity, increases short-chain fatty acid (SCFA)-producing bacteria, and enhances gut barrier integrity. Endurance training, particularly long-term, is most consistently associated with beneficial microbial shifts, including increases in Prevotella, Akkermansia, and Faecalibacterium. In contrast, excessive or high-intensity endurance exercise was shown to cause dysbiosis, inflammation, and greater intestinal permeability. Resistance training appears to induce milder changes but was shown to improve mucin synthesis and butyrate production, especially in older adults. Exercise frequency also plays a role, with regular daily training enriching metabolic pathways linked to gut and systemic health. Overall, the impact of exercise on the gut microbiota depends on the type, intensity, and duration of activity. Balanced, moderate exercise combined with a healthy diet emerges as the most effective strategy to enhance microbial diversity, reduce inflammation, and support overall performance and well-being in athletes.

1. Introduction

The gut microbiota, a diverse and dynamic microbial ecosystem within the human gastrointestinal tract, plays a central role in host physiology. It supports essential functions such as immune regulation, digestion, nutrient metabolism, and bidirectional signaling along the gut–brain axis [1,2]. Through the production of metabolites including short chain fatty acids, bile acid derivatives, and neurotransmitter precursors, the gut microbiota influences gastrointestinal function as well as systemic metabolic and neuroendocrine balance. Its composition and activity are strongly shaped by environmental and lifestyle factors, most notably diet, antibiotic exposure, stress, and physical activity [3].

Although diet has long been considered the primary determinant of microbial diversity and metabolic potential, recent evidence shows that physical activity also exerts a meaningful regulatory effect on the gut microbiota. Exercise produces systemic physiological changes that alter the gastrointestinal environment [4,5,6], including modifications in body temperature, splanchnic blood flow, immune and hormonal signaling, and intestinal motility. These shifts can influence the intestinal milieu and, consequently, the microbial communities that inhabit it. The concept of the exercise gut microbiota axis has emerged from these observations, highlighting the potential for exercise induced alterations in microbial composition and function to shape host metabolism, inflammation, and overall health [7,8,9].

Regular and moderate physical activity is associated with increased microbial diversity, greater abundance of short chain fatty acid producing taxa, and enhanced intestinal barrier integrity. These adaptations may contribute to improved metabolic efficiency, reduced inflammation, and greater neuroendocrine resilience. However, the relationship between exercise and the gut microbiota is complex and not always beneficial [10]. Excessive or very intense training can lead to increased intestinal permeability, microbial imbalance, and systemic inflammatory responses, effects frequently reported in endurance athletes, especially when combined with insufficient recovery or suboptimal nutrition [11,12,13].

Despite growing interest in this field, current findings remain inconsistent. Research varies widely in methodological design, microbial sequencing approaches, intervention duration and intensity, and participant characteristics such as diet and fitness level. Some studies report strong positive associations between physical activity and microbial diversity, while others observe minimal or short-lived changes, particularly in resistance based or brief interventions [14,15]. Many available studies rely on small or highly specific cohorts, which further limits generalizability [15,16]. The absence of standardized protocols for microbiota sampling and data interpretation also complicates comparison between studies and the development of firm conclusions [13,17].

These limitations highlight the need for an integrated and critical synthesis of existing evidence. Understanding how different exercise modalities influence the gut microbiota has important implications for both the general population and athletes, as physical activity represents a promising non pharmacological strategy to support gastrointestinal and systemic health. The intersection of exercise physiology and microbiome science also offers new opportunities for personalized approaches to nutrition, recovery, and the prevention of metabolic and inflammatory disorders.

This review summarizes current knowledge on how different types, intensities, and frequencies of physical activity influence gut microbiota composition and function. It outlines the physiological, metabolic, immune, and neuroendocrine mechanisms that may drive these changes, compares the effects of endurance and resistance training, and describes both the beneficial and potentially harmful impacts of exercise on the gut ecosystem. The aim is to clarify key concepts, address inconsistencies in the literature, and highlight priorities for future research on the relationship between exercise and the gut microbiota.

2. Basics of the Gut Microbiota

The microbiota refers to the microorganisms that inhabit a defined environment; in this context, the focus is on the human gut [18]. The gut microbiota is composed of bacteria, archaea, viruses, and eukaryotes. Among these groups, bacteria are the most abundant due to the favorable conditions for their growth. The dominant bacterial communities in the human gut are traditionally classified into seven major phyla: Firmicutes (Bacillota), Bacteroidetes (Bacteroidota), Fusobacteria (Fusobacteriota), Actinobacteria (Actinomycetota), Proteobacteria (Pseudomonadota), Verrucomicrobia (Verrucomicrobiota) and Cyanobacteria (Cyanobacteriota) [19]. Among these, Bacteroidetes (Bacteroidota) and Firmicutes (Bacillota) together comprise more than 90% of the total bacterial population in the human gut [20]. In addition to traditional taxonomic classification, the gut microbiota can also be described in terms of enterotypes. Enterotypes were proposed as a way to summarize the main characteristics of the human gut microbiota and to group individuals based on patterns in interindividual variation in microbial community composition [21,22,23]. Three enterotypes have been described.

Enterotype 1 is dominated by Bacteroides and is commonly associated with a Western type diet rich in saturated fats and animal proteins. Enterotype 2 is dominated by Prevotella and is linked to a plant-based diet high in fiber and complex carbohydrates. Prevotella species are capable of producing vitamin B1 (thiamine) and participate in the degradation of mucin glycoproteins. Enterotype 3 is dominated by Ruminococcus, one of the most frequently observed enterotypes in the human gut. This community type is associated with heme metabolism and the ability to degrade mucins [21,22,23] (Figure 1). However, several studies argue that this three enterotype model oversimplifies the human gut ecosystem. Rather than belonging to discrete and fixed groups, most individuals appear to fall along a continuum between these community types [24].

From a metabolic perspective, the gut microbiota participates in carbohydrate, lipid, protein and amino acid metabolism, as well as vitamin synthesis. Carbohydrates that escape digestion in the small intestine are fermented by gut microbes. Fermentation is a major energy source for the microbiota and produces short chain fatty acids [25]. Short chain fatty acids supply up to 10% of human caloric needs and contribute to gut barrier maintenance, immune modulation and neuroprotective functions. They also influence epigenetic regulation, immune pathways and central nervous system plasticity [26,27].

In lipid metabolism, the microbiota supports digestion by upregulating colipase, a protein required for fat breakdown, and participates in the regulation of fat storage by modulating lipoprotein lipase activity [28]. In protein and amino acid metabolism, microbial proteinases and peptidases assist in digestion [29]. In addition to digesting carbohydrates, lipids and proteins, the microbiota contributes to the synthesis of vitamin K and several B vitamins, conversion of primary to secondary bile acids, and oxalate degradation [30,31].

The immunologic functions of the microbiota include several key roles. Microbial colonization after birth contributes to the development of gut associated lymphoid tissue. Microbes can induce pro-inflammatory or anti inflammatory responses. Activation of TLR MyD88 signaling increases the production of Th17 cells, which promote inflammation [32,33,34]. Conversely, some organisms, such as Clostridium clusters and Bacteroides fragilis, stimulate regulatory T cells that suppress inflammation. The gut microbiota also promotes IgA production by B cells and supports neutrophil priming, enhancing immune readiness [35,36,37].

The microbiota also contributes to structural integrity of the gut. Butyrate, a major microbial metabolite, increases the production of tight junction proteins and strengthens the intestinal barrier. It also stimulates goblet cells to produce mucin [38,39]. Certain bacteria then degrade mucin for nutrients, which in turn stimulates its regeneration [40]. Butyrate further promotes intestinal stem cell division and the renewal of epithelial cells. Microbiota also protect against pathogens by competing for nutrients and space, and some bacteria produce natural antimicrobial compounds [41,42].

The neurological functions of the microbiota include the production or modulation of neurotransmitters such as serotonin and dopamine. Microbes help maintain the integrity of the blood–brain barrier through regulation of tight junctions. Microbial metabolites can influence afferent nerve activity by binding to receptors on nerve endings and altering signal transmission [19,43,44,45].

Numerous factors influence gut microbiota composition. Lifestyle factors, especially diet, play a major role. Diets high in fat reduce microbial diversity and promote metabolic dysfunction, whereas fiber rich diets support beneficial microbial communities and reduce inflammation [46]. Enterotypes are strongly associated with dietary habits [47], and rapid microbiota shifts can occur following dietary changes [48]. Other lifestyle factors, such as stress, smoking, sleep patterns and physical activity, also influence microbiota composition. Physical activity, the focus of this review, alters the microbiota depending on exercise type and intensity, and this will be discussed in later sections [49,50,51,52].

Beyond lifestyle, host related factors strongly influence gut microbiota development. Mode of delivery is important; infants born vaginally are exposed to maternal microbiota that support immune development, while infants delivered by cesarean section acquire different microbial communities. Some studies associate cesarean birth with increased risk of obesity and diabetes, although findings remain inconsistent [53]. Breastfeeding exposes infants to bacteria present in maternal milk, which support early microbial development. Some evidence suggests that mothers who deliver by cesarean section have reduced microbial diversity in breast milk [54,55]. Chronic conditions such as inflammatory bowel disease and irritable bowel syndrome are associated with reduced microbial diversity [56], and medications, especially antibiotics, further diminish microbial richness [57,58]. Genetics also shapes the microbiota; monozygotic twins share more similar microbiota than dizygotic twins [59,60]. Sociodemographic factors, including geographic location, socioeconomic status and household environment, also contribute to microbial variation [61].

3. Potential Mechanisms

Exercise can influence the gut microbiota through multiple mechanisms, which can be broadly categorized into physiological changes, metabolic effects, and the actions of myokines. Physiological mechanisms include alterations in gut motility and blood flow, which can impact microbial composition. Metabolic effects involve shifts in nutrient availability and energy metabolism that create a favorable environment for certain microbial species. Myokines (bioactive molecules released by muscles during exercise) can further modulate gut microbiota composition and function, linking skeletal muscle activity directly to microbial health. Moreover, long-term exercise can positively influence several host factors that in turn affect gut microbiota. Regular physical activity has been shown to enhance immune function, improve sleep quality, regulate appetite and dietary habits, and reduce the risk of infections and medication use. These exercise-associated improvements may create a more favorable gut environment, supporting microbial diversity and metabolic health [62,63,64,65,66,67,68].

3.1. Physiological Mechanisms Linking Exercise to Gut Microbiota

Exercise can influence gut microbiota through several physiological mechanisms. One major factor is gut motility (transit time). Multiple studies indicate that exercise tends to increase gut motility, leading to more rapid passage of food through the colon. This can stimulate the release of gastrointestinal hormones, which may alter colonic pH and, in turn, affect microbial composition [62,63].

Visceral blood flow is another critical factor. During exercise, blood is preferentially redirected to active muscles, reducing perfusion to visceral organs. This transient hypoperfusion can induce epithelial hypoxia and increase intestinal permeability. Upon restoration of blood flow, reactive oxygen species (ROS) may be generated, potentially damaging intestinal epithelial cells and further increasing permeability. Epithelial hypoxia can also trigger autophagy and reduce Toll-like receptor 4 (TLR4) expression, which may alter the gut microbiota composition and affect microbial functions related to lipid, nucleotide, and amino acid metabolism [64,65,66].

Finally, hyperthermia and dehydration associated with exercise can impact gut microbiota. Exercise-induced increases in gut temperature may disrupt tight junction protein expression, leading to higher intestinal permeability. This, combined with fluid loss, contributes to dehydration. Elevated permeability and dehydration have both been linked to dysbiosis, impaired pathogen clearance, and reduced Th17 cell function and differentiation [65,67,68]. From a physiological perspective, exercise can modulate gut microbiota by increasing gut motility, altering visceral blood flow, and inducing hyperthermia and dehydration, all of which create a dynamic environment that influences microbial composition and function.

3.2. Metabolism-Related Mechanisms Linking Exercise to Gut Microbiota

Exercise can influence the gut microbiota through metabolic mechanisms, with several metabolites acting as key mediators. One well-studied example is the interaction between lactate and Veillonella species. During exercise, skeletal muscles produce lactate, which enters the bloodstream and can reach the gut lumen. Veillonella species utilize lactate and convert it into short-chain fatty acids (SCFAs), mainly acetate and propionate [69,70]. These SCFAs serve as an energy source for colonocytes, regulate immune responses, and support gut barrier function, showing how exercise-induced metabolites directly shape microbial activity.

In addition to lactate, exercise can influence other metabolite pathways, including bile acid metabolism. Physical activity can alter the abundance of bile-acid-metabolizing bacteria, such as Clostridium and Bacteroides, many of which produce bile salt hydrolase (BSH), an enzyme that deconjugates bile acids and shapes the intestinal bile acid pool. Changes in BSH activity modulate FXR and TGR5 signaling, affecting lipid metabolism and energy homeostasis. For example, recent work has shown that inhibiting microbial BSH increases conjugated bile acids, suppresses intestinal FXR signaling, and improves lipid metabolism in high-fat diet–induced obesity [68,69]. Exercise may also modulate tryptophan metabolism, supporting the production of microbial-derived indoles that regulate gut immune homeostasis and epithelial integrity [68,69,70].

Overall, these examples illustrate that exercise provides substrates and environmental signals that selectively enhance the growth and metabolic activity of certain gut microbes. Through these metabolic interactions, exercise contributes to shaping microbial composition, functional output, and ultimately host physiology.

3.3. Myokine-Mediated Mechanisms Linking Exercise to Gut Microbiota

In addition to physiological and metabolic effects, exercise can modulate the gut microbiota through myokines, which are bioactive molecules released by contracting muscles. There are hundreds of myokines with diverse functions, and some have been shown to influence the gut microbiota directly or indirectly [71].

Interleukin-6 (IL-6), which increases during exercise, can affect gut microbiota by stimulating glucagon-like peptide 1 (GLP-1) secretion and elevating levels of anti-inflammatory cytokines such as IL-10 and IL-1 receptor antagonist (IL-1ra). GLP-1 enhances glucose tolerance and may contribute to intestinal mucosal repair in conditions such as inflammatory bowel disease. Increases in IL-10 and IL-1ra are associated with reduced intestinal inflammation, which can favor a healthier microbial environment [72].

Irisin is another exercise-induced myokine that typically peaks up to 60 min after physical activity. Several studies have suggested that irisin may ameliorate dysbiosis-related conditions and exert anti-inflammatory effects in ulcerative colitis. It has also been reported to directly influence gut microbial composition by selectively increasing or decreasing the abundance of specific bacterial taxa. Moreover, mice lacking irisin display alterations in gut microbiota and exhibit anxiety- and depression-like behaviors, supporting the possibility of a gut–brain–muscle axis. However, irisin remains a highly controversial molecule. Questions persist regarding the specificity of commonly used antibodies, the reliability of circulating irisin measurements, and whether it is produced at physiologically meaningful levels in humans. Consequently, although emerging data suggest potential roles for irisin in gut homeostasis and host–microbe interactions, these findings should be interpreted cautiously until more rigorous and standardized measurement methods are established. [73,74].

Interleukin-15 (IL-15), which can be elevated for several hours following exercise, has anti-diabetic and immunomodulatory effects that may indirectly shape gut microbial composition by reducing inflammation and supporting host metabolic homeostasis [75].

Therefore, myokines produced by skeletal muscles can influence the gut microbiota through multiple pathways: directly, by modifying microbial composition or promoting intestinal mucosal repair, and indirectly, by enhancing immune function and reducing inflammation.

4. Observed Patterns for Aerobic and Anaerobic Exercise

Exercise influences gut microbiota in distinct ways depending on the type of activity. Aerobic exercise, such as running or cycling, generally promotes microbial diversity and beneficial metabolite production, while anaerobic (resistance) exercise induces subtler changes but may enhance pathways like mucin and butyrate synthesis. In this section, we summarize the observed patterns for aerobic and anaerobic exercise.

4.1. Endurance Training

Several studies have examined how different exercise regimens influence gut microbiota composition and diversity. In one case study, a participant underwent six months of endurance training to assess longitudinal changes in their gut microbiota. During the peak of training, α-diversity—a measure of microbial richness within the individual—was highest. Throughout the study, Prevotella copri was consistently the most abundant species. Notable shifts occurred during the highest intensity period: Ruminococcus, Dorea, and Eubacterium species decreased, while Bifidobacterium longum showed a pronounced increase. Over the full training period, Methanobrevibacter smithii increased 5.8-fold, Bifidobacterium animalis decreased 7.4-fold, and Akkermansia muciniphila increased 2.6-fold. Additionally, SCFA-associated bacteria increased, suggesting potential benefits for recovery and performance. The study concluded that long-term training can enrich and diversify the gut microbiota, shifting it toward a profile resembling that of elite athletes, whereas shorter training periods may not produce the same effect [76].

Another study examined competitive swimmers undergoing a seven-week intense training program. Post-training, both α-diversity and SCFA-producing bacteria increased. The proportion of Firmicutes decreased, while Bacteroidota increased, indicating improved microbial richness and gut health [77]. Overall, sustained physical activity, especially exceeding 12 weeks, enhances gut microbiota health and reduces inflammation. Specific microbial shifts include increases in Prevotella, Methanobrevibacter smithii (more pronounced in professional cyclists than amateurs), and Faecalibacterium (observed in professional female runners).

However, long-term endurance training is not without potential negative effects. Markers of gut damage and permeability, such as intestinal fatty acid-binding protein (I-FABP) and zonulin, can increase during prolonged exercise (e.g., 12-h runs). High-sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation, is also elevated. Despite this, protective factors are upregulated: MUC2, a mucosal protective protein, and tight junction proteins occludin and ZO-1 increase, indicating enhanced intestinal barrier function. Beneficial bacteria such as Lactobacillaceae and Desulfovibrio also increase. In summary, long-term training tends to enhance α- and β-diversity, SCFA-producing bacteria, and gut-protective factors, though some markers indicate stress and inflammation [78,79].

In contrast, acute or short-term exercise induces more modest microbiota changes. In a study assessing gut microbiota before and after a half-marathon, no significant changes in α-diversity were observed, though specific taxa shifted: 26 unique Operational Taxonomic Units (OTUs) appeared post-race, compared with 15 pre-race, and 20 bacterial groups were more abundant, many associated with SCFA production [80].

A study on an ultramarathon found minimal changes in α- or β-diversity, but shifts in key taxa were observed. Faecalibacterium prausnitzii and Eubacterium rectale, both butyrate-producing and anti-inflammatory species, decreased, while Collinsella aerofaciens, associated with pro-inflammatory states, increased. Interestingly, Veillonella atypica, a lactate-metabolizing species, did not increase post-ultramarathon, in contrast to other marathon studies. These findings suggest that the impact of acute exercise on gut microbiota is highly dependent on exercise intensity and duration, with short-term moderate events favoring SCFA-producing taxa and extreme endurance events potentially reducing them [81].

Table 1. Positive and negative effects of a long- and short-term endurance training.

Endurance Training	Positive Effects	Negative Effects
Long-term training	Increase in α and β diversity [76,78] Increase in SCFA-producers (Bifidobacterium longum, Akkermansia muciniphila, Prevotella) [76] Increase in gut barrier proteins (MUC2, Occludin, ZO-1) [79] Increase in Lactobacillaceae and Desulfovibrio [79] Microbiota composition becomes more like elite athletes [76] Decrease inflammation in some studies [78]	Increase in I-FABP, zonulin (gut permeability) and hs-CRP (systemic inflammation) [78] Increase in pro-inflammatory cytokines [78] Increase in pro-inflammatory bacteria in some cases [78]
Short-term training	Half-marathon: Increase in SCFA-associated taxa, unique OTUs, and microbial abundance [80] Modest short-term improvements [80]	Ultramarathon: No α/β-diversity change [81] Decrease in Faecalibacterium and Eubacterium (butyrate-producers) [81] Increase in Collinsella (pro-inflammatory) [81] Veillonella atypica not increased (contradicting other studies) [81]

compares positive and negative effects of a long- and short-term endurance training

Exercise-induced changes in gut microbiota can also vary depending on the type of endurance training and the athlete’s gender. A study comparing cyclists and runners revealed distinct microbial profiles between the two groups [82].

Runners exhibited higher α-diversity, lower levels of Enterobacteriaceae (a family often associated with pathogenicity), and higher abundance of Methanosphaera, an archaeal genus involved in methane production. Male runners also had elevated levels of Catenibacterium compared to male cyclists.

Cyclists, in general, showed reduced levels of Enterobacteriaceae. Male cyclists specifically displayed increased abundance of Bifidobacterium, Pseudomonas, and Coriobacteriaceae, alongside decreased levels of Leuconostocaceae and Catenibacterium. Female cyclists demonstrated increases in Clostridiaceae, Lachnospiraceae, Mitsuokella, Phascolarctobacterium, Ruminococcaceae, Dialister, Ruminococcus, and Prevotella, while Coriobacteriaceae and Gemellaceae decreased.

These findings suggest that both the type of endurance training and the athlete’s gender can shape gut microbiota composition, likely through differences in physiology, training intensity, diet, and hormonal profiles. Overall, most of these changes are considered beneficial, reflecting enhanced microbial diversity and increased abundance of potentially health-promoting taxa (

Table 2. Gut Microbiota Profiles Across Athlete Gender and Endurance Training Modalities.

Endurance Training	Man	Woman
Cyclist	Lower Enterobacteriaceae (compared to non-athletes) [82] Increase in Bifidobacterium, Pseudomonas, Coriobacteriaceae [82] Decrease in Leuconostocaceae, Catenibacterium [82]	Increase in Clostridiaceae, Lachnospiraceae, Mitsuokella, Phascolarctobacterium, Ruminococcaceae, Dialister, Ruminococcus, Prevotella [82] Decrease in Coriobacteriaceae, Gemellaceae [82]
Runners	Higher α-diversity [76,82] Lower Enterobacteriaceae (compared to non-athletes) [82] Higher Methanosphaera [82,83] Higher Catenibacterium compared to male cyclists [82]	Higher α-diversity [76,82] Lower Enterobacteriaceae (compared to non-athletes) [82] -Higher Methanosphaera [82,83]

).

To summarize, in longer-term study programs we see increases in alpha and beta diversity with addition to some other positive factors, but we also see an increase in some negative markers. For short-term training, we don’t see alpha and beta diversity changes, but we do see changes in SCFA-producing bacteria, although the results are mixed, if it is positive or negative. Lastly, we can see that the difference in type of endurance training is affecting the microbiota differently, but also the gender of the trainer.

4.2. Resistance Training

Most studies indicate that resistance training does not induce significant changes in either alpha or beta diversity of the gut microbiota. One study did report an increase in beta diversity, but this effect was limited to participants who exhibited the greatest gains in muscular strength over the intervention, suggesting that microbiota shifts may depend on the magnitude of physiological adaptation rather than the training stimulus alone.

Several investigations also report an upregulation of mucin biosynthesis, which may enhance mucosal barrier integrity. In addition, reductions in LRG1 (Leucine-Rich Alpha-2-Glycoprotein 1) and zonulin have been observed; lower levels of these biomarkers are generally associated with decreased systemic inflammation and reduced intestinal permeability, respectively. Conversely, some studies document increases in fecal pH and FABP2 (Fatty Acid-Binding Protein 2), the latter being a marker of enterocyte damage and gut injury. The functional significance of these changes remains uncertain, and overall effect sizes are small. Taken together, current evidence does not support a consistent or robust impact of resistance training on global microbiota composition [15,84,85,86].

At the taxonomic level, two studies reported an increase in Faecalibacterium, a butyrate-producing genus commonly associated with gut health. Only one study noted increases in Roseburia hominis, Sutterella, Haemophilus, Eisenbergiella, and Clostridium, along with decreases in Bifidobacterium and Parasutterella. These findings were not replicated in other datasets, highlighting the variability across studies and the absence of a reproducible microbial signature associated with resistance training [15,84,85,86].

4.3. Intensity and Volume

Exercise intensity and modality can differentially influence gut microbiota composition and diversity. One study compared moderate- to high-intensity interval training with high-intensity functional training. The results showed that α-diversity improved more with high-intensity training, particularly functional training, while β-diversity exhibited only minor changes. Across all groups, the Firmicutes/Bacteroidetes ratio decreased, with the greatest reductions observed in high-intensity functional training [87].

High-intensity training, especially functional modalities, enriched SCFA-producing taxa and promoted microbial pathways associated with muscle metabolism, highlighting a potential mechanistic link between exercise and host energy homeostasis. Overall, this study concluded that while exercise generally benefits gut microbiota, higher intensity, particularly functional training, produced the most pronounced improvements [88].

However, two systematic reviews report somewhat different findings. They indicate that moderate or moderate-to-high intensity training may confer greater benefits to the gut microbiota, including increases in α- and β-diversity, improved intestinal barrier function, anti-inflammatory effects, and enrichment of SCFA-producing species and Veillonella, which is associated with endurance performance [89,90,91]. In contrast, high-intensity exercise showed more mixed outcomes: some studies reported increases in inflammatory bacteria, and results for microbial diversity were inconsistent, with both increases and decreases reported. Nonetheless, high-intensity training was linked to beneficial shifts in Bacteroidetes, improved mitochondrial function, lactate metabolism, and enhanced protein and carbohydrate utilization.

Specific training modalities exhibited distinct effects: high-intensity interval training (HIIT) increased β-diversity but not α-diversity, with modest changes in microbial taxa. Maximal effort sprints showed no reliable changes in either α- or β-diversity, while low-intensity training produced limited microbiota alterations.

In conclusion, although high-intensity functional training can induce beneficial microbial shifts, moderate-intensity training appears to offer the most consistent and overall positive effects on gut microbiota composition, diversity, and function, emphasizing that the relationship between exercise intensity and microbiota is complex and context-dependent [78,92].

Table 3. Positive and negative effects of different intensity levels of training.

Training Type	Positive	Negative
General high-intensity training	Lower Firmicutes/Bacteroidetes ratio [87] Higher Bacteroidetes, mitochondrial function, lactate metabolism, better protein/carbohydrate metabolism [78,92]	Mixed microbial diversity results (some positive, some negative) [78,87,92] Increase inflammatory bacteria [78,92]
High-Intensity Functional Training (HIFT)	Greatest increase in α-diversity [87] Strong decrease in Firmicutes/Bacteroidetes ratio (linked to better metabolic health) [87] Increase in SCFA-producing taxa [88] Increase in muscle-associated metabolic pathways [88]	None reported
High-Intensity Interval Training (HIIT)	Increase in β-diversity [78,92] Some beneficial taxa changes (SCFA-related, metabolism-linked) [88] Better mitochondrial function and lactate metabolism (in general, high-intensity) [78,92]	No consistent α-diversity increase [78,92] Reports of an increase in inflammatory bacteria [78,92] Results are inconsistent across studies
Maximal Effort	None reported	Non-noticeable effect on α-diversity or β-diversity [78,92]
Moderate/Moderate-to-High Intensity Training	Most consistently beneficial across reviews [89,90,91] Increase in α- and β-diversity [89,90,91] Increase in SCFA-producing species [89,90,91] Increase in Veillonella (lactate-metabolizing, linked to endurance [89,90,91] Improved intestinal barrier function (increased tight junctions, increased permeability) [89,90,91] Anti-inflammatory effects [89,90,91]	None reported
Low Intensity Training	Minimal but possibly slightly beneficial changes [78,92]	Limited microbiota changes overall (weak effect) [78,92]

summarizes positive and negative effects of different intensity levels of training.

While exercise generally benefits gut microbiota, prolonged high-intensity endurance exercise can also produce negative effects. A study comparing elite endurance runners to a control group revealed that runners exhibited higher microbial richness and β-diversity. However, taxonomic analyses indicated an increase in pro-inflammatory bacteria. Faecalibacterium, typically considered anti-inflammatory, was also elevated; under certain conditions, such as dysbiosis, it can act opportunistically and contribute to gut imbalance.

Metabolically, endurance runners had higher succinate levels, potentially linked to increased Faecalibacterium abundance. Normally, succinate is converted into propionate, but this conversion may be impaired in cases of excess carbohydrate intake or vitamin B12 deficiency, potentially leading to diarrhea and gut inflammation. Additionally, indole levels were decreased, suggesting that the gut environment favored organic acid production over putrefactive metabolites [78,92].

In summary, prolonged high-intensity exercise can induce gut dysbiosis, oxidative stress, elevated pro-inflammatory cytokines, and impaired nutrient metabolism, highlighting that extreme endurance activities may pose risks to gut health despite overall exercise benefits [93].

4.4. Impact of Exercise Frequency on Gut Microbiota Across Age and Weight Groups

Exercise frequency is an important factor influencing gut microbial composition and function. A systematic review examining different training frequencies found that exercising 2–3 times per week rarely increased α-diversity (only 1 out of 13 studies), whereas β-diversity showed more consistent increases (observed in 58% of studies). At the genus level, beneficial changes included increases in Lachnospira (50% of studies, SCFA producer) [94], Bifidobacterium (60% of studies, marker of gut health) [95], Roseburia (67% of studies, butyrate producer) [96], and Oscillospira (100% of studies, associated with lower body mass index) [97].

With 4–5 sessions per week, α-diversity increased in 33% of studies and β-diversity in 67%, while genus-level changes were inconsistent. In participants training 5+ times per week, α-diversity increased in 67% of studies, but no significant changes were observed in β-diversity. Notably, Prevotella copri, involved in carbohydrate and fiber metabolism, increased in 50% of studies [98]. These findings suggest that β-diversity responds more to moderate training frequencies, while α-diversity changes are more pronounced with daily training, and genus-level shifts are most evident at lower frequencies.

A study on elderly individuals further explored the effects of training frequency. Participants were grouped as: never/rarely exercising, 1–2 times/week, 3–5 times/week, and daily. α-diversity showed minimal differences across groups. However, higher training frequency resulted in gut microbiota composition more closely resembling that of younger adults, with the greatest similarity observed in daily exercisers, both at phylum and family levels [99,100]. Functional analyses revealed that 24 metabolic pathways differed between groups engaging in daily/regular exercise versus rare/never exercising, with 18 pathways enriched in the daily/regular group, indicating that regular activity enhances gut metabolic function.

The study also examined obese elderly individuals. Compared to normal-weight elderly, obese participants had higher α-diversity and an increased Firmicutes/Bacteroidetes ratio, elevated Verrucomicrobia (linked to gut barrier function), and higher abundance of SCFA-producing taxa such as Lachnospiraceae and Prevotellaceae. Oxalobacteraceae, involved in oxalate metabolism, was also increased [101]. Decreases were observed in Enterobacteriaceae (pro-inflammatory), Christensenellaceae (healthy metabolism), Bacteroidaceae, and Porphyromonadaceae, suggesting dysbiosis [102,103,104].

When comparing obese elderly who exercise regularly to those who do not, beneficial changes included increases in Turicibacteraceae (SCFA producers) and decreases in Pseudomonadaceae, Odoribacteraceae, and Barnesiellaceae, reflecting a healthier microbial profile [105,106,107]. Functional pathway analysis revealed 25 pathways significantly altered by exercise, with 12 shifting the obese profile toward that of normal-weight elderly, demonstrating that regular exercise improves microbial diversity, composition, and metabolic function in obese older adults [92,108].

Exercise frequency has differential effects on gut microbiota. Moderate frequency (2–3 sessions/week) mainly influences β-diversity and some SCFA-producing genera, while daily exercise enhances microbial composition and functional metabolic pathways. In elderly populations, including obese individuals, regular exercise can partially restore a younger, healthier microbiota profile and improve gut metabolic activity.

5. Exercise–Gut Microbiota Interactions in Athletes

In athletes, the interplay between exercise and the gut microbiota is most consistently associated with gastrointestinal tolerance, illness risk, and recovery processes, rather than large, universal gains in performance [109,110]. Emerging evidence suggests bidirectional effects: training status and load can shape microbial composition and metabolite production, while microbially derived products, such as short-chain fatty acids (SCFAs), may influence mucosal integrity, immune signaling, and muscle bioenergetics [13,111,112,113].

Mechanistically, SCFAs—including acetate, propionate, and butyrate—are central microbial metabolites implicated in regulating skeletal muscle insulin sensitivity, mitochondrial function, inflammation, and protein metabolism, providing a plausible pathway by which microbiota shifts could influence training adaptations and recovery. However, direct evidence in athletes remains limited [114,115,116].

Experimental studies have highlighted a potential lactate–propionate shuttle, suggesting a gut–muscle loop. Exercise-derived lactate can reach the gut lumen, where Veillonella spp. metabolize it to generate propionate. In mouse models, administration of Veillonella increased submaximal treadmill run time. Additionally, metagenomic analyses in elite athletes revealed enrichment of the lactate–propionate pathway after exercise [69,117]. While these findings are promising, subsequent commentary has emphasized that caution is warranted when extrapolating to human performance, and that standardized, sport-specific trials are needed to confirm functional relevance [118]. Figure 2 summarizes how exercise modulates microbiota-derived SCFAs and related physiological responses.

When translated to applied outcomes, recent systematic reviews in athletes and physically active populations report heterogeneous effects of probiotic or symbiotic supplementation on direct performance metrics, while evidence is clearer on illness/GI outcomes. Some trials indicate improvements while others show no change, underscoring strain-, dose-, and protocol-specificity. At the same time, these reviews point to some benefits for reducing upper-respiratory tract infection (URTI) symptoms and exercise-related GI complaints, outcomes that plausibly preserve training continuity and readiness even when time-trial or time-to-exhaustion results are neutral [119,120].

In line with this, athlete-focused summaries recommend that any microbiota-targeted approach be tailored to a clearly defined goal (e.g., mitigating URTI or GI symptoms during heavy training) rather than assumed to enhance performance universally [121,122].

Non-supplement interventions that target GI tolerance are also supported: structured “gut training” (progressive practice ingesting fluids and carbohydrate during exercise) and nutrition strategies optimized for event demands are associated with fewer GI symptoms and better carbohydrate handling during endurance efforts [123,124]. Practical guidance from recent reviews recommends aligning carbohydrate type and intake with exercise intensity and duration, practicing race fueling in training, and prioritizing hydration strategies to reduce Ex-GIS (exercise-induced GI symptoms), all of which can indirectly support performance by allowing athletes to maintain planned fueling without gastrointestinal distress [125,126,127]. Because diet co-drives the microbiota–exercise relationship, athlete-oriented reviews highlight habitual fiber and polyphenol intake and adequate carbohydrate availability as levers that shape microbial composition and SCFA output alongside training, implying that diet can modulate the effectiveness of any microbiome-targeted strategy [128,129].

More broadly, observational human data in older adults with insomnia indicate that increased physical activity is associated with shifts in gut microbial composition, supporting the concept that training load and lifestyle factors together influence microbiome profiles relevant to health and performance [130]. Taken together, the practical, evidence-based stance is to implement foundational behaviors first. Appropriate carbohydrate intake, hydration, and progressive gut training, while considering strain-specific probiotic or symbiotic use in athletes with recurrent GI or URTI issues, started several weeks before key competitions and were monitored for symptomatic benefits rather than performance gains [131,132]. This framing is consistent with mechanistic plausibility (SCFAs; lactate→propionate) yet remains cautious about generalizing to large performance effects without sport-specific, standardized randomized trials [118,133,134].

Overall, available data show significant variation in results between probiotic strains, dosages, training environments, and dietary control levels. Any suggested effects on performance should be viewed as conditional and extremely context-dependent in light of these discrepancies. In order to improve tolerance to target carbohydrate intakes, practitioners are advised to first make sure that the diet is of the highest quality, then match hydration and carbohydrate strategies to the particular requirements of the event, and finally, integrate progressive gut-training protocols. Consider microbiota-targeted supplements when aiming to reduce illness or GI symptoms, recognizing that direct performance effects are mixed and likely strain-specific; and interpret promising mechanisms (SCFAs, lactate→propionate) as a rationale for targeted experimentation rather than as guarantees of improvement [132,135,136,137].

6. Limitations in Current Evidence

The interpretability, reproducibility, and clinical translation of current findings are limited by a number of enduring limitations, despite the growing body of research linking physical activity and the gut microbiota.

First of all, we should mention heterogeneous study designs and small sample sizes. Small sample sizes and cross-sectional designs have been used in many studies to date, which can make it challenging to identify causal relationships or account for interindividual variability. Fewer studies have been done on older adults, sedentary people, or people with comorbidities; the majority have been done on young, healthy, or athletic populations. While this current focus on demographics offers insightful information about particular cohorts, it also identifies areas where future research can be expanded to include more diverse populations. Secondly, the influence of diet and lifestyle factors. It is a significantly limiting factor because stress, medication use, sleep patterns, and diet all have a significant impact on the makeup of gut microbes. Therefore, it can be difficult to distinguish between the separate effects of exercise. The variability in reported outcomes may be partially explained by the fact that not all studies have been able to fully standardize or monitor these confounders. To more precisely evaluate the effects of exercise, it would be beneficial to incorporate comprehensive dietary records or controlled nutrition protocols. We also need to take into account the characterization of exercise exposure.

Definitions and quantification of exercise intensity, duration, and frequency differ across studies, which can influence the comparability of results. Some trials rely on self-reported data, while others use objective physiological measurements. Developing harmonized descriptors and reporting standards for exercise interventions could enhance reproducibility and support meta-analyses [138,139,140].

The identification and measurement of microbial taxa may be impacted by variations in the procedures used for stool collection, preservation, and sequencing. All of these can result in limitations due to sampling and analytical variability. Heterogeneity in reported findings is further exacerbated by differences in databases, statistical analyses, and bioinformatic pipelines. standardized approaches and open reporting procedures, like those suggested by the STORMS (Strengthening The Organisation and Reporting of Microbiome Studies) framework, could lessen methodological variability and enhance the comparability of data from different studies [141,142,143]. The absence of functional and mechanistic data is an additional significant research limitation. Relatively few studies have included functional evaluations like inflammatory biomarkers or metabolomics; the majority have concentrated on microbial taxonomy. The way that exercise-induced microbial changes translate into immunological and metabolic effects could be clarified by placing more emphasis on integrative, multi-omics approaches [90,144].

Future studies should focus on comprehending the longitudinal and temporal dynamics of exercise-induced alterations in the gut microbiota. The persistence of microbial adaptations over longer training cycles and recovery periods has not yet been thoroughly characterized, and many interventions have been rather brief. Multiple sampling time point longitudinal studies may offer important information about whether these changes are temporary or long-lasting [76]. Similarly, synthesis across studies would be facilitated by transparent and consistent reporting, which includes standardized statistical and bioinformatic workflows, clear descriptions of data normalization, and comprehensive metadata. Adopting frameworks like the STORMS checklist can help future meta-analytic efforts, transparency, and reproducibility [145,146].

7. Future Directions

Future research in the exercise–microbiome field should prioritize enhancements to core study designs. To isolate the causal effects of exercise interventions, for instance, randomized controlled trials (RCTs) with well-matched control groups are still necessary. Many current studies are small, non-randomized, or lack sufficient control arms, which restricts interpretability, according to a number of recent systematic reviews [147,148]. Additionally, in order to ensure that the studies are sufficiently powered to detect microbiome, metabolome, and host-physiology outcomes, sample sizes should be scaled upward. Simultaneously, there should be a shift in the field away from cross-sectional snapshots and towards longitudinal designs that include multiple time points (pre-intervention baseline, during training, post-intervention, and follow-up/recovery). By evaluating changes over time within individuals, longitudinal designs can support causality inference and help determine whether exercise-induced microbial adaptations are temporary or long-lasting. Two previously untrained individuals were the subject of a six-month repeated-measures study that demonstrated dynamic changes in microbiome diversity and metabolites in response to training, injury, and illness [76].

Standardization of exposure and analytical techniques is another crucial path. To allow for cross-study comparability, exercise interventions should have well-defined parameters for intensity, duration, frequency, and modality (e.g., aerobic vs. resistance vs. high-intensity interval). For instance, a meta-analysis found that the interpretation of the Firmicutes/Bacteroidota ratio in athlete versus non-athlete studies is hampered by variations in the definition of exercise intensity [91]. Likewise, the need for methodological harmonization in microbiome research is becoming more widely acknowledged. In sport and exercise contexts, a new viewpoint suggests best-practice frameworks for sample collection, sequencing, data management, and reporting [149]. Beyond the intervention definition, more open data practices would help with reproducibility and meta-analyses. Examples of these practices include using common bioinformatics pipelines and storing sequencing and metabolomics data in public repositories.

The field should strive for greater representativeness in terms of study populations by including participants from a wider range of ages, genders, and ethnic and racial backgrounds, as well as those with varying baseline levels of fitness. Additionally, it should avoid extreme heterogeneity without stratification or excessive homogeneity. This broadens the scope of generalizability and permits the examination of subgroup reactions (e.g., does sex moderate the gut-microbiome response to exercise?). In fact, a multi-cohort athlete study found that the gut microbiota was influenced by sport type and exercise intensity in a sex-dependent manner [150].

Beyond exercise, it’s critical to carefully account for confounding variables. Gut microbiota can be greatly impacted by factors like stress levels, medication use, sleep patterns, food consumption, and other lifestyle choices. Research should minimize dependence on unsupervised self-reporting and monitor and control these as covariates or through standardized protocols. To minimize measurement error, objective measurements (such as actigraphy for sleep, dietary biomarkers, and accelerometry for activity) should be used whenever possible [151,152].

In order to capture microbial activity and host responses, future research should incorporate mucosal samples, blood biomarkers, and metabolomics (serum, urine, fecal) in addition to standardizing and expanding the scope of biospecimen collection protocols. For instance, a recent multi-omics exercise intervention in overweight women linked exercise to microbial and metabolic changes using metagenomic pathways and serum and fecal metabolomics [151,153,154]. These integrative methods aid in the transition from taxonomy to a mechanistic understanding of how microbial changes brought on by exercise result in immunological and metabolic effects.

It will take meticulously planned, multi-omics, longitudinal studies with a variety of populations and standardized methodologies to further our understanding of how exercise affects the gut microbiota. More accurate understanding of the mechanisms relating to physical activity, microbial adaptations, and host health will be possible through the integration of thorough biospecimen collection, open reporting, and standardized analytical techniques.

8. Conclusions

The gut microbiota is essential for maintaining gastrointestinal integrity, metabolic balance, and immune–neuroendocrine communication. Evidence from current studies indicates that exercise can beneficially modulate the gut microbiota, yet the outcomes depend strongly on training type, intensity, and duration. Moderate and sustained physical activity appears to be the most effective in enhancing microbial diversity, promoting the growth of short-chain fatty acid-producing bacteria, and strengthening the intestinal barrier. In contrast, excessive or high-intensity endurance exercise may induce transient dysbiosis, gut permeability, and low-grade inflammation, underscoring that more is not always better. Resistance training generally produces milder effects but may improve mucin synthesis and butyrate production, particularly in older adults.

These findings highlight the gut as a dynamic mediator between physical activity and systemic health. Regular, balanced exercise—combined with appropriate nutrition and hydration—may serve as a non-pharmacological strategy to support microbial resilience, gastrointestinal function, and overall athletic performance. However, substantial heterogeneity in study design, participant profiles, and analytical methods limits the comparability of current results. Future longitudinal and multi-omics studies are needed to establish causality, identify microbial biomarkers of exercise adaptation, and translate these insights into personalized training or therapeutic interventions.