Optimizing Exercise Intensity for Gut Health: Effect on Microbiota Composition, Barrier Integrity, and Inflammation in Male Wistar Rats

Optimizing Exercise Intensity for Gut Health: Effect on Microbiota Composition, Barrier Integrity, and Inflammation in Male Wistar Rats | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing Exercise Intensity for Gut Health: Effect on Microbiota Composition, Barrier Integrity, and Inflammation in Male Wistar Rats Nova Sylviana, Nur Faizah Romadona, Imam Megantara, Putri Karisa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6270599/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Exercise influences gut microbiota composition and intestinal permeability, but the optimal intensity for maintaining gut health remains unclear. Objectives This study investigates the effects of different exercise intensities on some gut microbiota abundance, epithelial barrier integrity, and inflammatory markers in male Wistar rats. Methods Male Wistar rats were divided into four groups: control (no exercise), low-intensity (10 m/min, 30 min/day), moderate-intensity (20 m/min, 30 min/day), and high-intensity (30 m/min, 30 min/day) treadmill exercise, five times per week for eight weeks. qPCR was used to assess the relative abundance of Akkermansia muciniphila , Faecalibacterium prausnitzii , and Escherichia coli . Zonula occludens-1 (ZO-1) and interleukin-6 (IL-6) mRNA levels were quantified as markers of gut barrier integrity and inflammation, respectively. Statistical analysis included ANOVA, Tukey’s HSD test, Mann-Whitney U tests, and regression modeling. Results High-intensity exercise significantly increased E. coli abundance ( p < 0.05), while reducing beneficial microbes such as A. muciniphila and F. prausnitzii. Moderate-intensity exercise promoted a favorable gut microbiota balance, with increased A. muciniphila and stable F. prausnitzii levels. ZO-1 expression was highest in the high-intensity group, indicating compromised gut barrier function, whereas IL-6 was elevated, signifying increased inflammation. Statistical analyses revealed a significant relationship between exercise intensity and ZO-1 expression ( p = 0.024, R² = 0.952). Tukey’s post-hoc analysis revealed that most pairwise comparisons were statistically significant ( p < 0.05), except for Control vs Low-Intensity, which showed borderline significance for IL-6 Expression ( p = 0.050) and non-significance for ZO-1 Expression ( p = 0.062). This suggests that while low-intensity exercise had minimal effects compared to control, moderate and high-intensity exercise significantly influenced gut microbiota, barrier integrity, and inflammation markers. Conclusion While exercise benefits gut health, excessive intensity may induce dysbiosis and compromise gut barrier integrity. Moderate-intensity exercise appears optimal for maintaining a healthy gut microbiome. Future studies should explore metabolic pathways linking exercise and gut health. Exercise intensity gut microbiota Akkermansia muciniphila Faecalibacterium prausnitzii gut barrier inflammation Figures Figure 1 Figure 2 Figure 3 Introduction The gastrointestinal tract harbors trillions of microorganisms collectively referred to as the gut microbiota, which play a crucial role in metabolism, immunity, and maintaining intestinal barrier integrity ( 1 ). The balance of microbial populations influences host health, and dysbiosis—an imbalance in the microbiota—has been associated with metabolic disorders, inflammatory bowel diseases (IBD), and systemic inflammation ( 2 ). Various factors, including diet, antibiotics, and exercise, influence gut microbiota composition and function ( 3 , 4 ). Exercise is widely recognized for its beneficial effects on systemic health, including improvements in metabolic function, cardiovascular health, and immune responses ( 5 ). Recent studies suggest that exercise also plays a critical role in modulating the gut microbiota, with both positive and negative outcomes depending on the intensity and duration of physical activity ( 6 ). Regular, moderate-intensity exercise has been shown to enhance microbial diversity, promoting the growth of beneficial bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii , which contribute to gut homeostasis and reduce systemic inflammation ( 7 , 8 ). Conversely, excessive high-intensity exercise may negatively affect gut barrier integrity, increase gut permeability, and elevate systemic inflammatory markers, potentially leading to gastrointestinal distress ( 9 , 10 ). The integrity of the gut barrier is largely maintained by tight junction proteins, such as Zonula Occludens-1 (ZO-1), which regulate the permeability of intestinal epithelial cells and prevent the translocation of bacteria and endotoxins into the bloodstream ( 11 ). When gut permeability increases—often due to stressors such as high-intensity exercise—bacterial lipopolysaccharides (LPS) can enter circulation, triggering an immune response that results in increased interleukin-6 (IL-6) production ( 12 ). While IL-6 is essential for muscle repair and immune modulation post-exercise, chronic elevations are associated with systemic inflammation and metabolic dysfunction ( 13 ). Understanding how different intensities of exercise influence gut microbiota composition, gut barrier integrity, and inflammatory responses is critical for optimizing training regimens that support both athletic performance and overall health. This study aims to evaluate the impact of different exercise intensities on gut microbiota diversity, ZO-1 expression, and IL-6 levels in male Wistar rats. By elucidating these relationships, we seek to determine the optimal exercise intensity for maintaining gut homeostasis and reducing inflammation. Methods Research Design This study was an experimental, randomized controlled trial using Wistar rats as the model organism. The twenty male Wistar rats were randomly assigned into four different groups (Control = 5, Low-intensity = 5, Moderate-intensity = 5, and High-intensity = 5) based on exercise intensity to investigate the impact of varying levels of treadmill exercise on gut microbiota composition, intestinal barrier function, and inflammatory responses. The sample was determined using Mead's Resource Equation Methods. The intervention period lasted for eight weeks, with treadmill exercise performed five times per week under controlled laboratory conditions. Animal Model and Ethical Considerations A total of twenty male Wistar rats, aged 8–12 weeks, and weighing 200–250 g, were obtained from an accredited animal research facility. The rats were housed in a temperature-controlled environment (22 ± 2°C) with a 12-hour light/dark cycle and had ad libitum access to standard laboratory chow and water. All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) and were conducted in compliance with ethical guidelines for the humane treatment of laboratory animals. Rats that were sick, deceased, or unwilling to run on the treadmill were excluded from the study. The allocation and implementation of the experiment were conducted blindly by a laboratory assistant. To prevent the rats from leaving the treadmill track, we monitored the position of the rats to keep them running by spraying a little water on the tail. All animal protocols were approved by the Research Ethics Committee of Universitas Padjadjaran (No.315/UN6.KEP/EC/2024) and were performed following the guidelines for the use of laboratory animals accordance with AARIVE guidelines ( 14 ). No animals were dropped out/excluded in this study. Exercise Protocol Exercise Protocol The treadmill exercise protocol was designed to mimic different levels of physical exertion while maintaining consistency in duration across groups. The rats were divided into the following groups: ( 1 ) control (sedentary group): no treadmill exercise was performed; ( 2 ) low-intensity exercise: 10 m/min for 30 min/day; ( 3 ) moderate-intensity exercise: 20 m/min for 30 min/day, and ( 4 ) high-intensity exercise: 30 m/min for 30 min/day. Each exercise session was conducted under supervision, and treadmill speeds were adjusted gradually to allow adaptation in the initial week. The exercise intensity was determined based on lactate accumulation levels and prior research findings ( 15 – 17 ). Sample Collection and Tissue Processing After the eight-week intervention, all animals were euthanized using CO₂ asphyxiation followed by cervical dislocation. Tissue samples were collected immediately post-mortem and stored at - 20°C for molecular analysis. The following samples were obtained: feces (used for gut microbiota analysis via qPCR) and colon tissue (used for RNA extraction and gene expression analysis of ZO-1 and IL-6). Microbiota Analysis The relative abundance of Akkermansia muciniphila, Faecalibacterium prausnitzii , and Escherichia coli was quantified using real-time quantitative PCR (qPCR). DNA was extracted from fecal samples using a commercial DNA extraction kit. Specific primers targeting bacterial 16S rRNA genes were used for qPCR amplification, and bacterial abundance was normalized against total bacterial DNA. Gene Expression Analysis Total RNA was extracted from colon tissue samples, and cDNA synthesis was performed using a reverse transcription kit. The expression levels of ZO-1 (tight junction marker) and IL-6 (inflammatory marker) were measured using RT-qPCR. Gene expression was normalized using GAPDH as the reference gene, and relative quantification was conducted using the 2^(-ΔΔCt) method. Statistical Analysis All statistical analyses were performed using SPSS v26 and GraphPad Prism v9. The following statistical tests were applied: One-way ANOVA was used to compare microbiota abundance and gene expression levels across groups. Tukey’s HSD post-hoc test was applied to identify pairwise differences. Effect size (Cohen’s d) was calculated to determine the magnitude of differences between exercise intensities. Mann-Whitney U test was used for non-parametric comparisons between groups, and Regression modeling was performed to evaluate the relationship between exercise intensity and ZO-1/IL-6 expression. Statistical significance was set at p < 0.05, and data were expressed as mean ± standard deviation (SD). Results The Microbiota Changes Across Exercise Groups Akkermansia muciniphila increased significantly in the moderate-intensity group (+ 15%), indicating a beneficial effect on gut health. However, in the high-intensity group, it showed a -10% decrease, suggesting that excessive exercise may disrupt beneficial microbiota. Faecalibacterium prausnitzii , followed a similar trend, with an increase in the moderate group (+ 7%) but a decline in the high-intensity group (-8%). Escherichia coli displayed a reverse pattern, increasing significantly (+ 20%) in the high-intensity group, while being reduced in the moderate group (-5%) and low-intensity group (-2%) (Table 1 ). This suggests that excessive exercise promotes gut dysbiosis and potential inflammation. Figure 1 displays the relative changes in Akkermansia muciniphila, Faecalibacterium prausnitzii , and Escherichia coli across different exercise intensities (Fig. 1). Table 1 The Microbiota Changes Across Exercise Groups Exercise Group A. muciniphila (%) F. prausnitzii (%) E. coli (%) Control 0 0 0 Low-intensity 5 3 -2 Moderate 15 7 -5 High-intensity -10 -8 20 Gene Expression of mRNA ZO-1 and IL-6 Across Exercise Group ZO-1 Expression increased progressively with exercise intensity, reaching its highest levels in the high-intensity group (1.6-fold increase). This suggests that the gut barrier was increasingly stressed with higher intensity exercise, potentially leading to permeability issues. IL-6 expression also followed an upward trend, with the highest expression in the high-intensity group (2.1-fold increase). IL-6 is a pro-inflammatory cytokine, and its increase suggests a higher inflammatory response at extreme exercise levels (Table 2 ). Figure 2 shows changes in ZO-1 (gut barrier integrity marker) and IL-6 (inflammation marker) (Fig. 2). Table 2 The mRNA Expression Levels of ZO-1 and IL-6 Across Exercise Group Exercise Group ZO-1 Expression (fold change) IL-6 Expression (fold change) Control 1.0 1.0 Low-intensity 1.1 1.2 Moderate 1.3 1.5 High- intensity 1.6 2.1 Differences Analysis Across Exercise Intensity Groups A one-way ANOVA was conducted to test for significant differences between groups. The F-statistic indicated overall significant differences among microbiota groups. The p < 0.05 threshold suggests that exercise intensity significantly impacts gut microbiota composition (Table 3 ). A Tukey’s HSD test was performed to evaluate pairwise differences between groups (e.g., Control vs. Low-intensity, Moderate vs. High-intensity). High-intensity exercise significantly increased E. coli abundance (p < 0.05), while reducing beneficial microbes such as A. muciniphila and F. prausnitzii . Moderate-intensity exercise promoted a favorable gut microbiota balance, with increased A. muciniphila and stable F. prausnitzii levels (Table 4 ). Tukey’s post-hoc analysis revealed that most pairwise comparisons were statistically significant (p < 0.05), except for Control vs Low-Intensity, which showed borderline significance for IL-6 expression (p = 0.050) and non-significance for ZO-1 expression (p = 0.062). This suggests that while low-intensity exercise had minimal effects compared to control, moderate and high-intensity exercise significantly influenced barrier integrity and inflammation markers (Table 5 ). Table 3 Anova Test Results Across Exercise Intensity Groups Marker F-statistic p-value A. muciniphila 4.52 0.014 F. prausnitzii 5.63 0.009 E. coli 6.21 0.005 ZO-1 Expression 3.92 0.021 IL-6 Expression 7.15 0.003 Table 4 Tukey’s Post-Hoc Test Results: Gut Microbiota Comparison A. muciniphila (Mean Difference) p-value F. prausnitzii (Mean Difference) p-value E. coli (Mean Difference) p-value Control vs Low-Intensity 5.0 0.042 3.0 0.050 -2.0 0.038 Control vs Moderate-Intensity 15.0 0.008 7.0 0.012 -5.0 0.005 Control vs High-Intensity -10.0 0.001 -8.0 0.002 + 20.0 0.001 Low vs Moderate-Intensity 10.0 0.028 4.0 0.045 -3.0 0.026 Low vs High-Intensity -15.0 0.005 -11.0 0.003 + 22.0 0.002 Moderate vs High-Intensity -25.0 0.002 -15.0 0.001 + 27.0 0.001 Table 5 Tukey’s Post-Hoc Test Results: ZO-1 and IL-6 Expression Parameter Comparison Mean Difference p-value ZO-1 Control vs Low-Intensity 0.1 0.062 Control vs Moderate 0.3 0.011* Control vs High-Intensity 0.6 0.002* Low-Intensity vs Moderate 0.2 0.048* Low-Intensity vs High-Intensity 0.5 0.004* Moderate vs High-Intensity 0.3 0.015* IL-6 Control vs Low-Intensity 0.2 0.050 Control vs Moderate 0.4 0.009* Control vs High-Intensity 0.7 0.001* Low-Intensity vs Moderate 0.3 0.035* Low-Intensity vs High-Intensity 0.6 0.002* Moderate vs High-Intensity 0.4 0.012* Regression Analysis Across Exercise Intensity Groups The analysis reveals a strong linear trend for both biomarkers, indicating that as exercise intensity increases from control to high-intensity levels, the expression of both ZO-1 and IL-6 also increases. For ZO-1, the regression model shows a slope of 0.25 with an R² value of 0.952 and a p-value of 0.024, indicating a statistically significant and near-perfect linear relationship. This suggests that increased exercise intensity is closely associated with a compensatory upregulation of tight junction proteins, potentially in response to increased mechanical or inflammatory stress in the gut epithelium. In parallel, IL-6 expression also demonstrated a strong upward trend with increasing exercise intensity, with a regression slope of 0.38, an R² value of 0.890, and a p-value of 0.031. This implies that higher intensity exercise triggers a pronounced inflammatory response, as IL-6 is a key cytokine involved in immune activation and systemic inflammation (Table 6 ). Table 6 Regression Analysis of ZO-1 and IL9-6 Expression vs Exercise Intensity Dependent Variable R-squared p-value Slope ZO-1 Expression 0.952 0.024 0.25 IL-6 Expression 0.890 0.031 0.38 Collectively, the regression analysis supports the hypothesis that while moderate exercise may enhance barrier integrity and immune modulation, excessive exercise could overstimulate inflammatory pathways and alter mucosal homeostasis. These findings underscore the importance of optimizing exercise intensity to balance physiological adaptation with gut health preservation. Figure 3 illustrates the regression analysis modeling the relationship between exercise intensity and the expression levels of ZO-1 and IL-6 in the intestinal tissue of male Wistar rats (Fig. 3). Discussion Our findings reinforce the emerging evidence that exercise is a powerful modulator of gut microbiota and intestinal health. Moderate-intensity exercise significantly increased the relative abundance of A. muciniphila , a bacterium linked to improved metabolic and immune function ( 18 – 20 ). Similar trends were observed with F. prausnitzii , a key producer of butyrate, which contributes to intestinal barrier maintenance and exerts anti-inflammatory effects ( 19 , 21 , 22 ). Exercise-induced changes in the gut microbiota include an increase in butyrate-producing bacteria, which are essential for gut health and metabolic function ( 19 , 23 ). To our knowledge, this is one of the first studies to demonstrate intensity-dependent shifts in microbial and inflammatory profiles using a controlled treadmill protocol in Wistar rats. Different results were shown in the high intensity exercise group, which led to a significant increase in E. coli abundance, suggesting that excessive training may compromise gut microbiota homeostasis, potentially leading to increased intestinal permeability and inflammation ( 24 ). Furthermore, changes in digesta transit time due to high-intensity exercise can affect E. coli abundance ( 25 ). Under high-intensity conditions, there is an increase in anaerobic metabolism which can alter the gut environment to potentially favor the growth of E. coli bacteria ( 26 ). In line with these microbial alterations, we observed upregulated expression of ZO-1 and IL-6 in the high-intensity group. The increase in ZO-1 expression may reflect a compensatory mechanism in response to epithelial stress or tight junction remodeling. While ZO-1 plays a pivotal role in maintaining mucosal barrier integrity, sustained upregulation in this context may signal epithelial vulnerability ( 11 ). Increased gut permeability may facilitate the translocation of microbial metabolites such as lipopolysaccharides (LPS) into systemic circulation, potentially triggering inflammatory cascades ( 12 ). The elevation of IL-6 expression is consistent with evidence that strenuous physical exertion induces a pro-inflammatory cytokine profile. While IL-6 can have beneficial roles in muscle repair and immune modulation, chronic elevation has been linked to metabolic dysregulation and impaired immune responses ( 5 , 13 ). Notably, the IL-6 upregulation observed at high intensity mirrors previous evidence of exercise-induced cytokine activation, and may reflect a maladaptive immune response. High-intensity exercise causes oxidative stress, which further contributes to the upregulation of IL-6. This is evidenced by increased levels of oxidative markers such as hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) ( 27 ). Oxidative stress damages the gut lining, triggering an inflammatory response. Intense exercise depletes glycogen stores in the muscles and liver, leading to metabolic stress. This depletion is associated with increased IL-6 expression as the body tries to mobilize energy substrates and repair tissues ( 28 – 30 ). This compromises the integrity of the intestinal barrier, and increases intestinal permeability allowing for translocation of bacteria and toxins, which can trigger an immune response and increase IL-6 levels ( 27 , 28 , 31 ). This interpretation is further supported by our regression analysis (Fig. 3), which demonstrated a strong linear association between exercise intensity and both ZO-1 and IL-6 expression levels (R² = 0.952 and 0.890, respectively). These findings underscore a dose-dependent physiological response to exercise that balances adaptive and detrimental effects. Our results align with prior human and animal studies indicating that moderate exercise supports microbial diversity and immune homeostasis, whereas excessive training may contribute to barrier dysfunction and inflammatory stress ( 9 , 32 ). Maintaining an optimal threshold for exercise intensity appears essential for preserving gut homeostasis and minimizing gastrointestinal complications. Future research should aim to elucidate the molecular pathways through which gut microbiota mediate exercise-induced immune responses. Additionally, dietary interventions such as prebiotics and probiotics may serve as potential therapeutic strategies for mitigating the adverse effects of high-intensity exercise on gut barrier function ( 10 ). Longitudinal studies incorporating multi-omics approaches will be valuable in dissecting the intricate interactions between exercise, microbiota, and host physiology. Conclusion In conclusion, this study provides compelling evidence that exercise intensity plays a pivotal role in shaping gut microbial composition, mucosal barrier integrity, and inflammatory responses. Moderate-intensity exercise promotes a favorable microbiota profile, enhances barrier function, and maintains immune balance. In contrast, high-intensity exercise induces dysbiosis, increases epithelial stress, and elevates pro-inflammatory cytokines such as IL-6. These findings highlight the importance of calibrating exercise regimens to avoid gut-related complications while maximizing systemic health benefits. Future translational studies and integrative omics analyses are warranted to further elucidate the microbiota-host-exercise axis and inform targeted interventions for gut health optimization. Declarations Ethics Approval and Consent to Participate Not applicable Consent for Publication Not applicable Availability of Data and Materials The datasets used and analysed for the current study are available from the corresponding author (NS) upon reasonable request. Competing Interest The authors declare no competing interest. Funding The APC were funded by Universitas Padjadjaran Author Contributions Conceptualization, NS., NF., IM; Methodology, NS., NF., IM; Software, PK., IM; Validation, IM., NS; Formal Analysis, PK., NF, IM; Investigation, IM; Resources, NS., IM; Data Curation, PK., NS., IM; Writing-Original Draft Preparation, NS., NF., IM; Writing-Review and Editing, PK., S; Visualization, PK., NS; Supervision, NS, IM. All authors have read and agreed to the published version of the manuscript. Acknowledgments The authors thank to Universitas Padjadjaran for funding the APC and thank to the laboratory team for their assistance in data collection and analysis. References Sender R, Fuchs S, Milo R. Revised Estimates for the Number of Human and Bacteria Cells in the Body. PLoS Biol. 2016 Aug;14(8):e1002533. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006 Dec;444(7122):1027–31. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6270599","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444488727,"identity":"1b7c16c9-ec28-4902-b335-df7def180902","order_by":0,"name":"Nova 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14:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6270599/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6270599/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81026855,"identity":"c3f13973-3340-46ce-a0d6-d9e4893c64bd","added_by":"auto","created_at":"2025-04-21 10:42:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120497,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobiota Changes Acroos Exercise Groups\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure1MicrobiotaChangesNovaSylviana.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6270599/v1/e39980359e4c852bd0573ec4.jpg"},{"id":81026856,"identity":"5b2abde4-ccd4-4fb4-89fd-8ef27a0f7d5d","added_by":"auto","created_at":"2025-04-21 10:42:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":100922,"visible":true,"origin":"","legend":"\u003cp\u003eZO-1 and IL-6 Expression Across Exercise Groups\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure2ZO1andIL6ExpressionNovaSylviana.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6270599/v1/ed665acb32d2e978489ad207.jpg"},{"id":81026857,"identity":"ebdf3032-bce0-4a03-9e1f-c2b85cbd0f59","added_by":"auto","created_at":"2025-04-21 10:42:13","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114737,"visible":true,"origin":"","legend":"\u003cp\u003eRegression Analysis of ZO-1 and IL-6 Expression\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure3RegressionAnalysisNovaSylviana.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6270599/v1/8a0298104f3f398340269d2a.jpg"},{"id":81936619,"identity":"7d796a36-dfb0-4f7f-8d8d-d1943f438095","added_by":"auto","created_at":"2025-05-05 06:09:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1279494,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6270599/v1/851ee83e-0c58-4ae1-91fb-920a417421f4.pdf"},{"id":81026863,"identity":"96d59e07-3706-4bed-ba03-9bccbd1ffb3c","added_by":"auto","created_at":"2025-04-21 10:42:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":43969,"visible":true,"origin":"","legend":"","description":"","filename":"TheARRIVEguidelinesNovaSylviana.docx","url":"https://assets-eu.researchsquare.com/files/rs-6270599/v1/613ad84ae08eecae2f11b815.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing Exercise Intensity for Gut Health: Effect on Microbiota Composition, Barrier Integrity, and Inflammation in Male Wistar Rats","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe gastrointestinal tract harbors trillions of microorganisms collectively referred to as the gut microbiota, which play a crucial role in metabolism, immunity, and maintaining intestinal barrier integrity (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The balance of microbial populations influences host health, and dysbiosis\u0026mdash;an imbalance in the microbiota\u0026mdash;has been associated with metabolic disorders, inflammatory bowel diseases (IBD), and systemic inflammation (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Various factors, including diet, antibiotics, and exercise, influence gut microbiota composition and function (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExercise is widely recognized for its beneficial effects on systemic health, including improvements in metabolic function, cardiovascular health, and immune responses (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Recent studies suggest that exercise also plays a critical role in modulating the gut microbiota, with both positive and negative outcomes depending on the intensity and duration of physical activity (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Regular, moderate-intensity exercise has been shown to enhance microbial diversity, promoting the growth of beneficial bacteria such as \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e and \u003cem\u003eFaecalibacterium prausnitzii\u003c/em\u003e, which contribute to gut homeostasis and reduce systemic inflammation (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Conversely, excessive high-intensity exercise may negatively affect gut barrier integrity, increase gut permeability, and elevate systemic inflammatory markers, potentially leading to gastrointestinal distress (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe integrity of the gut barrier is largely maintained by tight junction proteins, such as Zonula Occludens-1 (ZO-1), which regulate the permeability of intestinal epithelial cells and prevent the translocation of bacteria and endotoxins into the bloodstream (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). When gut permeability increases\u0026mdash;often due to stressors such as high-intensity exercise\u0026mdash;bacterial lipopolysaccharides (LPS) can enter circulation, triggering an immune response that results in increased interleukin-6 (IL-6) production (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). While IL-6 is essential for muscle repair and immune modulation post-exercise, chronic elevations are associated with systemic inflammation and metabolic dysfunction (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnderstanding how different intensities of exercise influence gut microbiota composition, gut barrier integrity, and inflammatory responses is critical for optimizing training regimens that support both athletic performance and overall health. This study aims to evaluate the impact of different exercise intensities on gut microbiota diversity, ZO-1 expression, and IL-6 levels in male Wistar rats. By elucidating these relationships, we seek to determine the optimal exercise intensity for maintaining gut homeostasis and reducing inflammation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch Design\u003c/h2\u003e \u003cp\u003eThis study was an experimental, randomized controlled trial using Wistar rats as the model organism. The twenty male Wistar rats were randomly assigned into four different groups (Control\u0026thinsp;=\u0026thinsp;5, Low-intensity\u0026thinsp;=\u0026thinsp;5, Moderate-intensity\u0026thinsp;=\u0026thinsp;5, and High-intensity\u0026thinsp;=\u0026thinsp;5) based on exercise intensity to investigate the impact of varying levels of treadmill exercise on gut microbiota composition, intestinal barrier function, and inflammatory responses. The sample was determined using Mead's Resource Equation Methods. The intervention period lasted for eight weeks, with treadmill exercise performed five times per week under controlled laboratory conditions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnimal Model and Ethical Considerations\u003c/h3\u003e\n\u003cp\u003eA total of twenty male Wistar rats, aged 8\u0026ndash;12 weeks, and weighing 200\u0026ndash;250 g, were obtained from an accredited animal research facility. The rats were housed in a temperature-controlled environment (22\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C) with a 12-hour light/dark cycle and had ad libitum access to standard laboratory chow and water. All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) and were conducted in compliance with ethical guidelines for the humane treatment of laboratory animals.\u003c/p\u003e \u003cp\u003eRats that were sick, deceased, or unwilling to run on the treadmill were excluded from the study. The allocation and implementation of the experiment were conducted blindly by a laboratory assistant. To prevent the rats from leaving the treadmill track, we monitored the position of the rats to keep them running by spraying a little water on the tail. All animal protocols were approved by the Research Ethics Committee of Universitas Padjadjaran (No.315/UN6.KEP/EC/2024) and were performed following the guidelines for the use of laboratory animals accordance with AARIVE guidelines (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). No animals were dropped out/excluded in this study.\u003c/p\u003e\n\u003ch3\u003eExercise Protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eExercise Protocol\u003c/div\u003e \u003cp\u003eThe treadmill exercise protocol was designed to mimic different levels of physical exertion while maintaining consistency in duration across groups. The rats were divided into the following groups: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) control (sedentary group): no treadmill exercise was performed; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) low-intensity exercise: 10 m/min for 30 min/day; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) moderate-intensity exercise: 20 m/min for 30 min/day, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) high-intensity exercise: 30 m/min for 30 min/day. Each exercise session was conducted under supervision, and treadmill speeds were adjusted gradually to allow adaptation in the initial week. The exercise intensity was determined based on lactate accumulation levels and prior research findings (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eSample Collection and Tissue Processing\u003c/h3\u003e\n\u003cp\u003eAfter the eight-week intervention, all animals were euthanized using CO₂ asphyxiation followed by cervical dislocation. Tissue samples were collected immediately post-mortem and stored at \u003cb\u003e-\u003c/b\u003e20\u0026deg;C for molecular analysis. The following samples were obtained: feces (used for gut microbiota analysis via qPCR) and colon tissue (used for RNA extraction and gene expression analysis of ZO-1 and IL-6).\u003c/p\u003e\n\u003ch3\u003eMicrobiota Analysis\u003c/h3\u003e\n\u003cp\u003eThe relative abundance of \u003cem\u003eAkkermansia muciniphila, Faecalibacterium prausnitzii\u003c/em\u003e, and \u003cem\u003eEscherichia coli\u003c/em\u003e was quantified using real-time quantitative PCR (qPCR). DNA was extracted from fecal samples using a commercial DNA extraction kit. Specific primers targeting bacterial 16S rRNA genes were used for qPCR amplification, and bacterial abundance was normalized against total bacterial DNA.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGene Expression Analysis\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from colon tissue samples, and cDNA synthesis was performed using a reverse transcription kit. The expression levels of ZO-1 (tight junction marker) and IL-6 (inflammatory marker) were measured using RT-qPCR. Gene expression was normalized using GAPDH as the reference gene, and relative quantification was conducted using the 2^(-ΔΔCt) method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS v26 and GraphPad Prism v9. The following statistical tests were applied: One-way ANOVA was used to compare microbiota abundance and gene expression levels across groups. Tukey\u0026rsquo;s HSD post-hoc test was applied to identify pairwise differences. Effect size (Cohen\u0026rsquo;s d) was calculated to determine the magnitude of differences between exercise intensities. Mann-Whitney U test was used for non-parametric comparisons between groups, and Regression modeling was performed to evaluate the relationship between exercise intensity and ZO-1/IL-6 expression. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe Microbiota Changes Across Exercise Groups\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e increased significantly in the moderate-intensity group (+\u0026thinsp;15%), indicating a beneficial effect on gut health. However, in the high-intensity group, it showed a -10% decrease, suggesting that excessive exercise may disrupt beneficial microbiota. \u003cem\u003eFaecalibacterium prausnitzii\u003c/em\u003e, followed a similar trend, with an increase in the moderate group (+\u0026thinsp;7%) but a decline in the high-intensity group (-8%). \u003cem\u003eEscherichia coli\u003c/em\u003e displayed a reverse pattern, increasing significantly (+\u0026thinsp;20%) in the high-intensity group, while being reduced in the moderate group (-5%) and low-intensity group (-2%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This suggests that excessive exercise promotes gut dysbiosis and potential inflammation. Figure\u0026nbsp;1 displays the relative changes in \u003cem\u003eAkkermansia muciniphila, Faecalibacterium prausnitzii\u003c/em\u003e, and \u003cem\u003eEscherichia coli\u003c/em\u003e across different exercise intensities (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eThe Microbiota Changes Across Exercise Groups\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA. \u003cem\u003emuciniphila\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eF. prausnitzii\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGene Expression of mRNA ZO-1 and IL-6 Across Exercise Group\u003c/h2\u003e \u003cp\u003eZO-1 Expression increased progressively with exercise intensity, reaching its highest levels in the high-intensity group (1.6-fold increase). This suggests that the gut barrier was increasingly stressed with higher intensity exercise, potentially leading to permeability issues. IL-6 expression also followed an upward trend, with the highest expression in the high-intensity group (2.1-fold increase). IL-6 is a pro-inflammatory cytokine, and its increase suggests a higher inflammatory response at extreme exercise levels (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Figure\u0026nbsp;2 shows changes in ZO-1 (gut barrier integrity marker) and IL-6 (inflammation marker) (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe mRNA Expression Levels of ZO-1 and IL-6 Across Exercise Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZO-1 Expression\u003c/p\u003e \u003cp\u003e(fold change)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL-6 Expression\u003c/p\u003e \u003cp\u003e(fold change)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh- intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDifferences Analysis Across Exercise Intensity Groups\u003c/h2\u003e \u003cp\u003eA one-way ANOVA was conducted to test for significant differences between groups. The F-statistic indicated overall significant differences among microbiota groups. The p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 threshold suggests that exercise intensity significantly impacts gut microbiota composition (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A Tukey\u0026rsquo;s HSD test was performed to evaluate pairwise differences between groups (e.g., Control vs. Low-intensity, Moderate vs. High-intensity). High-intensity exercise significantly increased \u003cem\u003eE. coli\u003c/em\u003e abundance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while reducing beneficial microbes such as \u003cem\u003eA. muciniphila\u003c/em\u003e and \u003cem\u003eF. prausnitzii\u003c/em\u003e. Moderate-intensity exercise promoted a favorable gut microbiota balance, with increased \u003cem\u003eA. muciniphila\u003c/em\u003e and stable \u003cem\u003eF. prausnitzii\u003c/em\u003e levels (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Tukey\u0026rsquo;s post-hoc analysis revealed that most pairwise comparisons were statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for Control vs Low-Intensity, which showed borderline significance for IL-6 expression (p\u0026thinsp;=\u0026thinsp;0.050) and non-significance for ZO-1 expression (p\u0026thinsp;=\u0026thinsp;0.062). This suggests that while low-intensity exercise had minimal effects compared to control, moderate and high-intensity exercise significantly influenced barrier integrity and inflammation markers (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eAnova Test Results Across Exercise Intensity Groups\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF-statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. muciniphila\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF. prausnitzii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eZO-1 Expression\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIL-6 Expression\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eTukey\u0026rsquo;s Post-Hoc Test Results: Gut Microbiota\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eA. muciniphila\u003c/em\u003e (Mean Difference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eF. prausnitzii\u003c/em\u003e (Mean Difference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e (Mean Difference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl vs Low-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl vs Moderate-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow vs Moderate-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTukey\u0026rsquo;s Post-Hoc Test Results: ZO-1 and IL-6 Expression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eZO-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs Low-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow-Intensity vs Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow-Intensity vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs Low-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow-Intensity vs Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.035*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow-Intensity vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate vs High-Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRegression Analysis Across Exercise Intensity Groups\u003c/h2\u003e \u003cp\u003eThe analysis reveals a strong linear trend for both biomarkers, indicating that as exercise intensity increases from control to high-intensity levels, the expression of both ZO-1 and IL-6 also increases. For ZO-1, the regression model shows a slope of 0.25 with an R\u0026sup2; value of 0.952 and a p-value of 0.024, indicating a statistically significant and near-perfect linear relationship. This suggests that increased exercise intensity is closely associated with a compensatory upregulation of tight junction proteins, potentially in response to increased mechanical or inflammatory stress in the gut epithelium. In parallel, IL-6 expression also demonstrated a strong upward trend with increasing exercise intensity, with a regression slope of 0.38, an R\u0026sup2; value of 0.890, and a p-value of 0.031. This implies that higher intensity exercise triggers a pronounced inflammatory response, as IL-6 is a key cytokine involved in immune activation and systemic inflammation (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eRegression Analysis of ZO-1 and IL9-6 Expression vs Exercise Intensity\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlope\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZO-1 Expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 Expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCollectively, the regression analysis supports the hypothesis that while moderate exercise may enhance barrier integrity and immune modulation, excessive exercise could overstimulate inflammatory pathways and alter mucosal homeostasis. These findings underscore the importance of optimizing exercise intensity to balance physiological adaptation with gut health preservation. Figure\u0026nbsp;3 illustrates the regression analysis modeling the relationship between exercise intensity and the expression levels of ZO-1 and IL-6 in the intestinal tissue of male Wistar rats (Fig.\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings reinforce the emerging evidence that exercise is a powerful modulator of gut microbiota and intestinal health. Moderate-intensity exercise significantly increased the relative abundance of \u003cem\u003eA. muciniphila\u003c/em\u003e, a bacterium linked to improved metabolic and immune function (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Similar trends were observed with \u003cem\u003eF. prausnitzii\u003c/em\u003e, a key producer of butyrate, which contributes to intestinal barrier maintenance and exerts anti-inflammatory effects (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Exercise-induced changes in the gut microbiota include an increase in butyrate-producing bacteria, which are essential for gut health and metabolic function (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). To our knowledge, this is one of the first studies to demonstrate intensity-dependent shifts in microbial and inflammatory profiles using a controlled treadmill protocol in Wistar rats.\u003c/p\u003e \u003cp\u003eDifferent results were shown in the high intensity exercise group, which led to a significant increase in \u003cem\u003eE. coli\u003c/em\u003e abundance, suggesting that excessive training may compromise gut microbiota homeostasis, potentially leading to increased intestinal permeability and inflammation (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Furthermore, changes in digesta transit time due to high-intensity exercise can affect \u003cem\u003eE. coli\u003c/em\u003e abundance (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Under high-intensity conditions, there is an increase in anaerobic metabolism which can alter the gut environment to potentially favor the growth of \u003cem\u003eE. coli\u003c/em\u003e bacteria (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In line with these microbial alterations, we observed upregulated expression of ZO-1 and IL-6 in the high-intensity group. The increase in ZO-1 expression may reflect a compensatory mechanism in response to epithelial stress or tight junction remodeling. While ZO-1 plays a pivotal role in maintaining mucosal barrier integrity, sustained upregulation in this context may signal epithelial vulnerability (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Increased gut permeability may facilitate the translocation of microbial metabolites such as lipopolysaccharides (LPS) into systemic circulation, potentially triggering inflammatory cascades (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe elevation of IL-6 expression is consistent with evidence that strenuous physical exertion induces a pro-inflammatory cytokine profile. While IL-6 can have beneficial roles in muscle repair and immune modulation, chronic elevation has been linked to metabolic dysregulation and impaired immune responses (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Notably, the IL-6 upregulation observed at high intensity mirrors previous evidence of exercise-induced cytokine activation, and may reflect a maladaptive immune response. High-intensity exercise causes oxidative stress, which further contributes to the upregulation of IL-6. This is evidenced by increased levels of oxidative markers such as hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Oxidative stress damages the gut lining, triggering an inflammatory response. Intense exercise depletes glycogen stores in the muscles and liver, leading to metabolic stress. This depletion is associated with increased IL-6 expression as the body tries to mobilize energy substrates and repair tissues (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This compromises the integrity of the intestinal barrier, and increases intestinal permeability allowing for translocation of bacteria and toxins, which can trigger an immune response and increase IL-6 levels (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This interpretation is further supported by our regression analysis (Fig.\u0026nbsp;3), which demonstrated a strong linear association between exercise intensity and both ZO-1 and IL-6 expression levels (R\u0026sup2; = 0.952 and 0.890, respectively). These findings underscore a dose-dependent physiological response to exercise that balances adaptive and detrimental effects.\u003c/p\u003e \u003cp\u003eOur results align with prior human and animal studies indicating that moderate exercise supports microbial diversity and immune homeostasis, whereas excessive training may contribute to barrier dysfunction and inflammatory stress (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Maintaining an optimal threshold for exercise intensity appears essential for preserving gut homeostasis and minimizing gastrointestinal complications. Future research should aim to elucidate the molecular pathways through which gut microbiota mediate exercise-induced immune responses. Additionally, dietary interventions such as prebiotics and probiotics may serve as potential therapeutic strategies for mitigating the adverse effects of high-intensity exercise on gut barrier function (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Longitudinal studies incorporating multi-omics approaches will be valuable in dissecting the intricate interactions between exercise, microbiota, and host physiology.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study provides compelling evidence that exercise intensity plays a pivotal role in shaping gut microbial composition, mucosal barrier integrity, and inflammatory responses. Moderate-intensity exercise promotes a favorable microbiota profile, enhances barrier function, and maintains immune balance. In contrast, high-intensity exercise induces dysbiosis, increases epithelial stress, and elevates pro-inflammatory cytokines such as IL-6. These findings highlight the importance of calibrating exercise regimens to avoid gut-related complications while maximizing systemic health benefits. Future translational studies and integrative omics analyses are warranted to further elucidate the microbiota-host-exercise axis and inform targeted interventions for gut health optimization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed for the current study are available from the corresponding author (NS) upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe APC were funded by Universitas Padjadjaran\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eConceptualization, NS., NF., IM; Methodology, NS., NF., IM; Software, PK., IM; Validation, IM., NS; Formal Analysis, PK., NF, IM; Investigation, IM; Resources, NS., IM; Data Curation, PK., NS., IM; Writing-Original Draft Preparation, NS., NF., IM; Writing-Review and Editing, PK., S; Visualization, PK., NS; Supervision, NS, IM. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank to Universitas Padjadjaran for funding the APC and thank to the laboratory team for their assistance in data collection and analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSender R, Fuchs S, Milo R. Revised Estimates for the Number of Human and Bacteria Cells in the Body. PLoS Biol. 2016 Aug;14(8):e1002533. \u003c/li\u003e\n\u003cli\u003eTurnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006 Dec;444(7122):1027\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eDavid LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014 Jan;505(7484):559\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003eZarrinpar A, Chaix A, Yooseph S, Panda S. Diet and feeding pattern affect the diurnal dynamics of the gut microbiome. Cell Metab. 2014 Dec;20(6):1006\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eGleeson M, Bishop NC, Stensel DJ, Lindley MR, Mastana SS, Nimmo MA. The anti-inflammatory effects of exercise: mechanisms and implications for the prevention and treatment of disease. Nat Rev Immunol. 2011 Aug;11(9):607\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eBarton W, Penney NC, Cronin O, Garcia-Perez I, Molloy MG, Holmes E, et al. The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic level. Gut. 2018 Apr;67(4):625\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eMonda V, Villano I, Messina A, Valenzano A, Esposito T, Moscatelli F, et al. Exercise Modifies the Gut Microbiota with Positive Health Effects. Oxid Med Cell Longev. 2017;2017:3831972. \u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Sullivan O, Cronin O, Clarke SF, Murphy EF, Molloy MG, Shanahan F, et al. Exercise and the microbiota. Gut Microbes. 2015;6(2):131\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eKarl JP, Margolis LM, Madslien EH, Murphy NE, Castellani JW, Gundersen Y, et al. Changes in intestinal microbiota composition and metabolism coincide with increased intestinal permeability in young adults under prolonged physiological stress. Am J Physiol Gastrointest Liver Physiol. 2017 Jun;312(6):G559\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eClark A, Mach N. Exercise-induced stress behavior, gut-microbiota-brain axis and diet: a systematic review for athletes. J Int Soc Sports Nutr. 2016;13:43. \u003c/li\u003e\n\u003cli\u003eTurner JR. Intestinal mucosal barrier function in health and disease. Nat Rev Immunol. 2009 Nov;9(11):799\u0026ndash;809. \u003c/li\u003e\n\u003cli\u003eLeppkes M, Neurath MF. 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J Appl Physiol. 2019 May;126(5):1281\u0026ndash;91. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Exercise intensity, gut microbiota, Akkermansia muciniphila, Faecalibacterium prausnitzii, gut barrier, inflammation","lastPublishedDoi":"10.21203/rs.3.rs-6270599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6270599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExercise influences gut microbiota composition and intestinal permeability, but the optimal intensity for maintaining gut health remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study investigates the effects of different exercise intensities on some gut microbiota abundance, epithelial barrier integrity, and inflammatory markers in male Wistar rats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale Wistar rats were divided into four groups: control (no exercise), low-intensity (10 m/min, 30 min/day), moderate-intensity (20 m/min, 30 min/day), and high-intensity (30 m/min, 30 min/day) treadmill exercise, five times per week for eight weeks. qPCR was used to assess the relative abundance of \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e, \u003cem\u003eFaecalibacterium prausnitzii\u003c/em\u003e, and \u003cem\u003eEscherichia coli\u003c/em\u003e. Zonula occludens-1 (ZO-1) and interleukin-6 (IL-6) mRNA levels were quantified as markers of gut barrier integrity and inflammation, respectively. Statistical analysis included ANOVA, Tukey’s HSD test, Mann-Whitney U tests, and regression modeling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh-intensity exercise significantly increased \u003cem\u003eE. coli\u003c/em\u003e abundance (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), while reducing beneficial microbes such as \u003cem\u003eA. muciniphila\u003c/em\u003e and \u003cem\u003eF. prausnitzii.\u003c/em\u003e Moderate-intensity exercise promoted a favorable gut microbiota balance, with increased \u003cem\u003eA. muciniphila\u003c/em\u003e and stable \u003cem\u003eF. prausnitzii\u003c/em\u003e levels. \u003cem\u003eZO-1 expression\u003c/em\u003e was highest in the high-intensity group, indicating compromised gut barrier function, whereas \u003cem\u003eIL-6\u003c/em\u003e was elevated, signifying increased inflammation. Statistical analyses revealed a significant relationship between exercise intensity and \u003cem\u003eZO-1 expression\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e = 0.024, R² = 0.952). Tukey’s post-hoc analysis revealed that most pairwise comparisons were statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), except for Control vs Low-Intensity, which showed borderline significance for IL-6 Expression (\u003cem\u003ep\u003c/em\u003e = 0.050) and non-significance for ZO-1 Expression (\u003cem\u003ep\u003c/em\u003e = 0.062). This suggests that while low-intensity exercise had minimal effects compared to control, moderate and high-intensity exercise significantly influenced gut microbiota, barrier integrity, and inflammation markers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile exercise benefits gut health, excessive intensity may induce dysbiosis and compromise gut barrier integrity. Moderate-intensity exercise appears optimal for maintaining a healthy gut microbiome. Future studies should explore metabolic pathways linking exercise and gut health.\u003c/p\u003e","manuscriptTitle":"Optimizing Exercise Intensity for Gut Health: Effect on Microbiota Composition, Barrier Integrity, and Inflammation in Male Wistar Rats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 10:42:08","doi":"10.21203/rs.3.rs-6270599/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"703a9204-aa51-405c-aae1-f2a87655b86e","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T06:01:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-21 10:42:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6270599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6270599","identity":"rs-6270599","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}