CRC is the third most common cancer and second leading cause of cancer death globally 1 . Extensive research 23456 confirms that aerobic exercise intervention prevents disease onset, inhibits disease progression, and improves patient prognosis, underscoring its key role in disease prevention and treatment.An imbalance in the gut microbiota is closely linked to the development of CRC 7 . The gut microbiota colonizes 8 the colorectal epithelium, participates in dietary metabolism, and plays a crucial role in maintaining bodily balance. Dysbiosis is characterized by the proliferation of pathogens 9 , a reduction in commensals 10 , and a decrease in diversity 11 . Fusobacterium nucleatum and other bacteria can promote CRC progression through different signaling pathways 1213 . Pathogenic microorganisms 1415 can also produce genotoxins or cause deoxyribonucleic acid (DNA) damage via indirect mechanisms, thereby promoting tumor formation. Therefore, elucidating the molecular mechanisms underlying the imbalance between pathogenic bacteria and antitumor probiotics during gut dysbiosis could open new avenues for the prevention and treatment of CRC.The structure of the gut microbiota 16 is complex and dynamic. It can alter host metabolism through various pathways, thereby affecting the development of colorectal cancer. Short-chain fatty acids (SCFAs) are a type of metabolite that is influenced by the gut microbiota and is closely associated with CRC 17 . The levels of SCFAs in the feces of CRC patients are significantly decreased, and the root cause lies in the reduction in the number of microorganisms, such as the Lachnospira, that produce SCFAs. Specifically, butyrate, an SCFA, is deeply involved in key cellular activities, such as DNA methylation and cell cycle regulation, and SCFAs as a whole are also associated with programmed death-ligand 1 (PD-L1) therapy 18 . Another metabolomics study 19 also provided new evidence that, in the colon of mice exposed to smoke, the bile acid metabolite taurodeoxycholic acid (TDCA) increases significantly. This phenomenon is closely related to Eggerthella lenta, and the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling pathway is also involved, as it is associated with changes in TDCA levels and damage to the intestinal barrier. In addition, a high-fat diet 20 can also change the structure of the gut microbiota in mice, leading to an increase in pathogenic bacteria, a decrease in probiotics, and an increase in the related metabolite glycerophospholipids, ultimately resulting in damage to intestinal barrier function.In this study, we used aerobic exercise interventions at different intensities and stages. Our goals were to determine whether CRC alters the intestinal microbiota composition, understand the role of these changes in CRC, and uncover the molecular mechanisms of CRC progression. We aimed to identify better CRC prevention and treatment strategies. The experimental roadmap of this study is shown in Figure 1. Thirty-six 8-week-old male Sprague-Dawley (SD) rats were purchased from the Laboratory Animal Center of the Second Affiliated Hospital of Harbin Medical University. All breeding conditions were carried out in accordance with standard specifications. After a one-week adaptation period, the rats were randomly divided into 6 groups: the control group and the DMH group. Adv-Ex-HIIT group (high-intensity intermittent exercise intervention was performed in advance before the DMH was injected), Adv-Ex-MIIT group (mid-intensity intermittent exercise intervention was performed in advance before the DMH was injected), HIIT group (high-intensity intermittent exercise intervention was performed in progress while the DMH was injected), and MIIT group (mid-intensity intermittent exercise intervention was performed in progress while the DMH was injected). The weights were recorded every week, and after 24 consecutive weeks of feeding, the blood, colon, and fecal tissues were removed, and the samples were stored in a -80°refrigerator for later experiments.A simplified schematic diagram of the exercise protocol is provided in Supplementary Figure S1.Aerobic exercise programme: After one week of adaptation, the exercise group was forced to run on the treadmill. The running exercise training included a 2-week adaptive training phase, followed by a sports training phase (with two days off per week).For the Adv-Ex-HIIT group, the first day starts at 8 m/minute, lasts for 15 minutes, at 10 m/minute on the second day, lasts for 30 minutes, at 10 m/minute on the third day, lasts for 30 minutes, at 15 m/minute on the fourth day, lasts for 45 minutes, at 15 meters/minute on the fifth day, lasts for 45 minutes, at 20 meters/minute on the sixth day, lasts for 45 minutes, at 20 meters/minute on the seventh day, lasts 50 minutes, at 22 meters/minute on the eighth day, lasts 60 minutes, at 22 meters/minute on the ninth day, lasts 60 minutes, and lasts 60 minutes, at 25 meters/minute on the last tenth day, lasting 66 minutes. The Adv-Ex-MIIT group, similar to the Adv-Ex-HIIT group, lasts for the first seven days, lasts 20 meters/minute on the eighth day, lasts 60 minutes, and lasts 20 meters/minute on the ninth day, lasting 66 minutes, and lasts 66 minutes, and lasts 66 minutes. After the speed and duration of exercise were determined, one month of exercise training was performed in advance for both the HIIT group and the MIIT group, and exercise training was continued until the end of modeling. After that, the HIIT group and the MIIT group also conducted two weeks of adaptive training, with the acceleration cycle and time being the same as those of the Adv-Ex-HIIT group and the Adv-Ex-MIIT group. After two weeks, the exercise training phase began until the modeling ended.In the following exercise training stage, the rats in the Adv-Ex-HIIT group and Adv-Ex-MIIT group were subjected to two intensities of advanced exercise intervention and were running on a 0-degree inclined treadmill. The two groups were trained for 66 minutes at speeds of 25 m/min and 20 m/min each day, 5 days a week, for 24 weeks. The HIIT group and the MIIT group were in the same mode as the Adv-Ex-HIIT group and the Adv-Ex-MIIT group for 20 weeks.Intermittent exercise training mode: Adv-Ex-HIIT group and HIIT group (5-minute warm-up speed: 8 meters/minute; 8 interval training modes: 25 meters/minute speed lasting for 5 minutes, 2-minute rest mode; 5-minute cooling speed: 8 meters/minute). The Adv-Ex-MIIT group and MIIT group (5-minute warm-up speed: 8 meters/minute; 8 interval training modes: 20 meters/minute speed lasting for 5 minutes, 2-minute rest mode; 5-minute cooling speed: 8 meters/minute) 21-25 .Paraffin sections were incubated at 60°C for 20-30 minutes, dewaxed in xylene, rehydrated in graded ethanol, and rinsed with phosphate-buffered saline (PBS). Antigen retrieval was performed with sodium citrate in a microwave oven, followed by blocking peroxidase activity with 3% hydrogen peroxide and serum. The samples were incubated with primary antibody at 4°C overnight, rewarmed at 37°C the next day, washed, and incubated with secondary antibody for 1 hour, followed by another wash. After 3,3'-diaminobenzidine (DAB) staining and counterstaining with hematoxylin, the samples were washed, dehydrated, cleared, mounted, and then imaged under an upright microscope. The antibodies used in this experiment are shown in Supplementary Table 1.The primers used in the experiment were designed via Primer 3 online software and synthesized by Sangon Bioengineering Co., Ltd. The specific sequences of the primers used are provided in Supplementary Table 2.We extracted total ribonucleic acid (RNA) from rat tissue via a standard protocol and performed reverse transcription and qRT-PCR. The specific components and procedures are listed in Supplementary Tables S3--S5.Paraffin sections were heated at 60℃ for 20-30 minutes, dewaxed in xylene (I and II, 15 minutes each), rehydrated in graded ethanol (100%, 90%, 80%, 70%) for 5 minutes each, and rinsed with PBS 3 times for 3 minutes each. Nuclei were stained with hematoxylin for 3-5 minutes (adjusted under a microscope), rinsed with tap water for 10 minutes to turn blue, and the cytoplasm was stained with eosin for 1-3 minutes. The samples were dehydrated in graded ethanol (75%, 95%, 100%) for 1 min each, cleared in xylene (I and II, 5 min each), mounted with neutral balsam, air-dried, and then examined and photographed under a microscope.The ELISA was meticulously carried out in strict accordance with the detailed protocols furnished within the specific kit. For comprehensive information regarding the kit, including its brand and manufacturer details, please refer to Supplementary Table S6.Total RNA from diverse microbial groups was extracted via the cetyltrimethylammonium bromide (CTAB) method, with extraction efficiency assessed via agar gel electrophoresis and RNA content determined via ultraviolet spectroscopy. The PCR products were purified via AMPureXT beads, quantified via a Qubit, identified via 2% agarose gel electrophoresis, and recovered with the same beads. The purified products were evaluated via an Agilent 2100 Bioanalyzer and an Illumina Kapa kit, with libraries ≥2 nM selected. Qualified libraries (with unique indices) were pooled proportionally, denatured to single strands with sodium hydroxide, and sequenced on a NovaSeq 6000 (2×250 bp paired-end) using a 500-cycle SP reaction box as a control. The data were subjected to demultiplexing, splicing, filtering, diversity analysis, species annotation, differential analysis, and advanced analyses. The specific experimental procedures are provided in Supplementary Tables S7-S9.A Thermo UltiMate 3000 high-performance liquid chromatography system was coupled with an ACQUITY UPLC BEH C18 column (100 mm×2.1 mm, 1.8 μm), with a column temperature of 35°C and a flow rate of 0.4 mL/min. The mobile phases were 0.1% formic acid (A) and 0.1% formic acid in acetonitrile (B). Metabolites were analyzed via a Thermo high-resolution tandem mass spectrometer in simultaneous positive/negative ion modes: parent ion scanning (70-1050 m/z, resolution 70,000, AGC 3e6, maximum injection time 100 ms); fragment spectra were acquired in Data-Dependent Acquisition mode (resolution 17,500, AGC 1e5, maximum time 80 ms).Liquid chromatography-mass spectrometry stability was monitored via 10 quality control injections. The raw data were converted to mzXML format (via MSConvert) and processed with XCMS (peak separation/QC) and collection of algorithms for metabolite profile annotation (adduct annotation). Preliminary identification (via primary mass spectrometry and standard library matching) was performed via MetaX software, with metabolites annotated against the Human Metabolome Database (HMDB)/Kyoto Encyclopedia of Genes and Genomes (KEGG). MetaX also quantified and screened differentially abundant metabolites.All the experiments were repeated 3 times or more, and the results are expressed as the means ± SDs. Statistical comparisons were performed for different groups via one-way analysis of variance, and the results between groups were compared via t tests. GraphPad Prism 9.0 software was used for data analysis and statistical charting. The difference was statistically significant at P < 0.05 (*P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001).To explore the role of aerobic exercise in CRC progression, we investigated its effect on the development of CRC by establishing a DMH-induced colorectal tumorigenesis model and performing exercise interventions of varying intensities (Fig. 2A). Colon length reflects colorectal cancer severity: the colon length in the Model group was significantly shorter than that in the Control group, whereas Adv-Ex-MIIT and HIIT significantly alleviated this shortening (Fig. 2B). During the 24-week intervention, the weekly weight data revealed that the exercise groups had significantly greater weights than did the Model group (lower than the Control group), with no significant difference between the Model and MIIT groups; varying-intensity exercise improved cancer-induced slow weight gain in the SD rats (Fig. 2C-D). H&E staining revealed severe intestinal damage in the Model group (reduced goblet cells, inflammatory infiltration, etc.), with more adenocarcinoma and dysplasia, which were significantly alleviated by exercise (Fig. 2E).The Model group had more PCNA-positive cells, which were significantly reduced after exercise (Fig. 2E-F). In summary, exercise of varying intensities can inhibit colorectal cancer progression. Alpha diversity characterizes species diversity, richness. There were differences in the Chao1, observed ASVs, and Shannon index of the intestinal microbiota among the different groups of rats, indicating that exercise interventions of different intensities can alter their richness and diversity. Among them, there were significant differences between the Model group and the Adv-Ex-MIIT group, suggesting that this intervention can significantly increase the richness and diversity of the intestinal microbiota in rats (Fig. 3A-C).β diversity refers to the degree of dissimilarity in species composition between different microbial communities. Compared with the control group, the model group was separated along the PCoA1 and PCoA2, indicating significant differences in intestinal microbial species between the two groups (Fig. 3D). After exercise interventions of different intensities, the model group and each intervention group presented significant differences in the gut microbiota (Fig. 3E-H). Exercise of different intensities can alter the colonization ability of the gut microbiota, affecting the progression of colorectal cancer to a certain extent.Total amplicon sequence variants (ASVs) in the control, model, Adv-Ex-HIIT, Adv-Ex-MIIT, HIIT, and MIIT groups were 3606, 3268, 3150, 3761, 3488, and 3242, respectively. 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