Bacteroides coprocola Protects Dopaminergic Neurons in Rotenone-Induced Parkinson’s disease Mice Model by Modulating Gut Microbiota Dysbiosis and Inhibiting the NLRP3 Signaling Pathway

Bacteroides coprocola Protects Dopaminergic Neurons in Rotenone-Induced Parkinson’s disease Mice Model by Modulating Gut Microbiota Dysbiosis and Inhibiting the NLRP3 Signaling Pathway | 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 Bacteroides coprocola Protects Dopaminergic Neurons in Rotenone-Induced Parkinson’s disease Mice Model by Modulating Gut Microbiota Dysbiosis and Inhibiting the NLRP3 Signaling Pathway zixian liu, Jiabei Nie, Yimei Li, Maoxin Huang, Ziluo Chen, Shushang Yu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6875771/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2026 Read the published version in Translational Neurodegeneration → Version 1 posted 4 You are reading this latest preprint version Abstract Background: Parkinson’s disease (PD) is a prevalent neurodegenerative disease and its pathogenesis is still unclear. Emerging evidence supports the gut-origin hypothesis, highlighting gut microbiota dysbiosis as a contributing factor in PD pathogenesis. Alterations in gut microbial composition influence barrier integrity and systemic chronic inflammation via the microbiota-gut-brain axis. Bacteroides coprocola (B.coprocola) , a gut bacterium producing short-chain fatty acids (SCFAs), is significantly reduced in PD patients from our previous clinical study. This study investigates B.coprocola ’s potential in ameliorating PD pathology using a rotenone-induced PD mouse model. By evaluating its impact on gut microbiota balance, inflammation, and macrophage polarization, we aim to elucidate its therapeutic role and underlying mechanisms in PD progression. Methods: In this study, the rotenone-induced PD mouse model was established. After three weeks of rotenone administration, PD mice underwent continuous oral gavage with B.coprocola for an additional three weeks. Motor function was assessed using the Rota-Rod test, Pole test, and Beam walking test. Furthermore, 16S rRNA high-throughput sequencing and targeted SCFAs metabolomics were employed to analyze gut microbiota composition and SCFAs levels across groups. Additionally, flow cytometry, immunofluorescence, qPCR, and Western blot techniques were utilized to examine alterations in midbrain and intestinal structures, NLRP3 inflammasome pathway activation, and macrophage polarization. Results: B.coprocola treatment could alleviate PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and BBB and intestinal barrier permeability in the rotenone-induced PD mouse model. Additionally, B.coprocola inhibits the NLRP3 signaling pathway by modulating gut microbiota dysbiosis and macrophage polarization, ultimately alleviating systemic chronic inflammation and PD-like pathological symptoms in rotenone-induced mice. Conclusions: The current findings suggest that B.coprocola can regulate gut microbiota dysbiosis in rotenone-induced PD mice and influence macrophage polarization, which is associated with the inhibition of the NLRP3 inflammasome signaling pathway. Parkinson’s disease Gut microbiota NLRP3 signaling pathway Macrophage polarization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Parkinson’s disease (PD) is a prevalent neurodegenerative disorder, ranking second in prevalence after Alzheimer's disease[ 1 ]. The pathological hallmarks of PD primarily include the selective loss of dopaminergic neurons in the substantia nigra of the midbrain and the formation of Lewy bodies, which are mainly composed of α-synuclein (α-syn)[ 2 ]. In recent years, the gut-origin hypothesis of PD has gained attention, with evidence indicating that abnormal α-syn aggregation is significantly detected in the intestines of PD patients during the prodromal stage, even before it appears in the brain[ 3 , 4 ]. This suggests that the gut is likely a critical organ contributing to the development of PD. Current clinical studies indicate that PD patients exhibit significant alterations and dysbiosis in their gut microbiota and intestinal microenvironment. For example, an increased abundance of Akkermansia , Bifidobacterium , and Prevotella , as well as a reduction in Blautia and Anaerostipes , have been observed[ 5 – 7 ]. Dysbiosis of the gut microbiota can lead to chronic inflammatory responses in the intestinal epithelium, disrupting the intestinal barrier and increasing its permeability[ 8 ]. Consequently, pro-inflammatory products generated in the gut, such as lipopolysaccharides (LPS) and cytokines, can translocate into systemic circulation through the compromised barrier, triggering systemic chronic inflammation and accelerating the pathological progression of PD[ 9 , 10 ]. Bacteroides.coprocola ( B.coprocola ), a gut bacterium belonging to the Bacteroides genus, was first isolated from the feces of healthy individuals by Japanese biologists in 2005. It is a Gram-negative, strictly anaerobic bacterium that primarily metabolizes and produces a range of short-chain fatty acids and amino acids[ 11 ]. Short-chain fatty acids (SCFAs) are key gut microbial metabolites that mediate signaling from the gut microbiota to the host. Increasing evidence suggests that SCFAs play a crucial role in regulating brain function, systemic chronic inflammation, and the integrity of blood-tissue barriers[ 12 ]. In our previous clinical study, a metagenomic analysis of 63 healthy control and 97 PD patients revealed a significant statistical difference in the abundance of B.coprocola between the two groups (HC > PD)[ 13 ]. Given the current state of research on B.coprocola , no studies have explored its potential role in alleviating PD symptoms. Therefore, investigating the effects of B.coprocola in improving PD symptoms is a novel and pioneering endeavor in this field. In this study, by establishing a rotenone-induced PD mouse model that induces gut microbiota dysbiosis, we aim to evaluate whether B.coprocola treatment can modulate systemic chronic inflammation, thereby ameliorating gut microbiota imbalance PD pathological changes and behavioral symptoms. Furthermore, we seek to elucidate the potential mechanisms underlying B.coprocola intervention in PD and explore the role of the microbiota-gut-brain axis in the pathogenesis of PD. Materials and methods Animals and experimental design The experimental model consisted of 6-week-old male C57BL/6J mice weighing 20–22 g, obtained from Shanghai Jihui Experimental Animal Breeding Co., Ltd. The mice were housed in the Model Animal Facility of ShanghaiTech University. Ethical approval for animal care and use was granted by the Animal Research Ethics Committee of ShanghaiTech University (Approval Number: 20220802001). All procedures were conducted in compliance with the guidelines of ShanghaiTech University's Institutional Animal Care and Use Committee (IACUC). A total of mice was randomly assigned to two groups: the control group and the model group. During the first week, the mice were acclimatized to the animal house environment and subjected to handling procedures to familiarize them with the experimenter's operations. Over the following three weeks, the model group received daily intraperitoneal injections of rotenone, while the control group was administered the vehicle. After three weeks, the model group was further divided into two subgroups: the Rotenone group and the B.coprocola group. From weeks 4 to 6, mice in the B.coprocola group were treated with B.coprocola once daily, while the control and Rotenone groups received vehicle administration. All mice were weighed daily throughout the six-week study. At week 6, gastrointestinal function tests and behavioral assessments were conducted. Finally, all mice were sacrificed at week 6 for further analysis. Chronic rotenone model induction and administration Rotenone (Sigma-Aldrich,USA) was dissolved in 2% DMSO (Beyotime Biotechnology). The fresh rotenone solution was intraperitoneal injected to the mice (2 mg/kg body weight) once a day for 3 weeks[ 14 ]. B.coprocola identification, culture and administration B.coprocola (Mingzhoubio,China) were inoculated in a liquid medium (see in Table S1 ) with deoxygenation cultivated in 37℃ incubator for 2 days. An anaerobic environment was maintained throughout the cultivation process. For B.coprocola group, mice were administered with B.coprocola DSM 17136 dissolved in pbs (10 8 CFU/mice/d) for 3 weeks. The bacterial suspension was then delivered to each recipient mouse via oral gavage within 15 min. Design primers for 16s RNA bacterial species identification, amplify the bacterial DNA in vitro through PCR (10102ES03, Yeasen), and send it to Tsingke Biotech Company for sequencing. The V3-V4 regions of the microbial 16S RNA were amplified with the paired primers (forward primer: 5′-CCTACGGGRSGCAGCAG-3′; reverse primer: 5′-GGACTACVVGGGTATCTAATC-3′). Performed sequence identification of the species using the BLAST function on NCBI (National Center for Biotechnology Information). Behavioral tests To assess the motor function of each mouse, 3 behavioral tests were conducted with an interval of 30 min. Rota-Rod test Mice were positioned on the rotarod apparatus, which initiated rotation at an initial velocity of 4 revolutions per minute (rpm) and progressively accelerated to 30 rpm over a duration of 120 seconds. Thereafter, the time elapsed until each mouse lost balance and fell from the rod was automatically captured by the rotarod system. Each mouse underwent the experimental trial three times, separated by an inter-trial interval of 30 minutes. Pole test A 50-centimeter wooden rod, with a diameter of 3 centimeters and surmounted by a stationary wooden sphere, was positioned within the home cage. Initially, the mice were acclimated to the apparatus to ensure that they would assume a head-bowing posture upon placement on the rod. The mice were positioned atop the rod with their heads oriented upward and subsequently descended to the platform along the length of the rod. The descent time of the mice, as well as the scores assigned to their crawling behavior, were meticulously documented. Three trials were conducted, with each trial separated by a 30-minute intermission. Beam-Walking Test The apparatus comprised a wooden beam elevated 70 centimeters above the floor, with dimensions of 1 centimeter in width and 120 centimeters in length, terminating at one end with a dark enclosure. A mesh and foam substrate were positioned beneath the beam to mitigate the risk of injury to the mice. The mice were positioned at one extremity of the beam and permitted to traverse towards the terminal end equipped with the dark enclosure. Following each trial, the wooden beam and the dark enclosure were sanitized with ethanol and subsequently desiccated to eradicate any residual olfactory cues. Each mouse underwent three trials, interspersed with 30-minute Intestinal transit distance and colon length measurement Thirty minutes prior to euthanasia, mice were administered 0.3 mL of a 2.5% Evans blue solution (Sigma-Aldrich) orally, which was dissolved in a 1.5% carboxymethyl cellulose sodium (CMC-Na) vehicle (Sigma-Aldrich) to assess intestinal transit distance. Subsequently, the distance from the pylorus to the most distal point of dye migration was measured and defined as the intestinal transit distance. Furthermore, the length of the colon was determined by measuring the distance from the terminus of the cecum to the anus[ 15 ]. Fecal pellets output Following a 2-hour fasting period, individual mice were transferred from their home cages to clean, transparent polycarbonate cages for an additional 2 hours. Fecal pellets were subsequently collected and enumerated. The wet weight of the fecal pellets was determined by immediate weighing, while the dry weight was ascertained after desiccation at 85°C for 24 hours. The fecal water content was calculated as a percentage based on the discrepancy between the wet and dry weights. Flow Cytometry. (Brain/Blood/Colon/BMDM) FACS antibodies used for flow cytometry were CD11b-APC, CD45-Percp/Cy5.5, obtained from BioLegend. The CD86-BV421, CD206-PE, F4/80- BV650, CD80-FICT, obtained from BD. For surface marker staining, cells were blocked with Fc Shield (anti-mouse CD16/ CD32, BD) and used Zombie Aqua™ Fixable Viability Kit to incubate for 15 min. Then incubated with surface antibodies for 30 min. Next, cells were permeabilized using the eBioscience™ Foxp3 kit for 30 min (00-5523-00, thermo). Finally, the cells were stained for intracellular indexes CD206-PE. Between each step, the cells were extensively washed with FACS buffer (PBS, 2% FCS, and 2 mM EDTA). The prepared samples were measured and analyzed using a Cyto FLEX flow cytometer (Beckman Coulter, Brea, CA, USA). Preparation of single-cell suspensions from mouse brain, blood and colon Following euthanasia of the mice, fresh brain, blood, and colonic tissues were excised for the preparation of single-cell suspensions, which were subsequently subjected to single-cell analysis utilizing fluorochrome-conjugated antibodies. Fresh peripheral whole blood from mice was collected into ethylenediaminetetraacetic acid (EDTA) anticoagulant tubes. Whole blood samples were subjected to lysis using a lysing solution (BD Biosciences, CA, USA) and subsequently washed with 1× phosphate-buffered saline (PBS). The brain and colon were harvested, washed, and minced into small fragments. Brain mononuclear cells were isolated using Neural Tissue Dissociation Kits (Miltenyi Biotec, 130-107-677) in accordance with the manufacturer's protocol. Specifically, the ischemic hemisphere of the brain was excised and minced into small pieces. These pieces were transferred into an appropriately sized conical tube, rinsed with cold Hank's balanced salt solution (HBSS), and then centrifuged (300 g, 2 min) at room temperature. After carefully aspirating the supernatant, preheated enzyme mix 1 (37°C, 10 min) from the Neural Tissue Dissociation Kit was added to digest the tissue pieces for 15 min, followed by the addition of preheated enzyme mix 2 (37°C, 10 min) to the tissue sample for an additional 10 min. Subsequently, HBSS was used to resuspend the tissue, and single-cell pellets were isolated by passing through a 30-µm cell strainer. The colon tissues were incubated with 8 mL of digestion buffer composed of RPMI-1640 (Thermo Fisher Scientific, Waltham, MA, USA), 5% fetal bovine serum (FBS; Capricorn, Palo Alto, CA, USA), 62.5 µg/mL Liberase (Sigma), and 50 µg/mL DNase I (Roche) at 37°C for 30 min. The cell pellets were then resuspended in 1 mL of 40% Percoll solution and transferred to a prepared 15 mL conical tube containing 4 mL of 40% Percoll solution. Using glass Pasteur pipettes, 2.5 mL of 80% Percoll solution was carefully layered at the bottom of the tubes. Cells were collected from the interface[ 16 ]. Western Blot The mice were anesthetized to collect brain and colon tissue or collect successfully differentiated primary macrophages (BMDMs). The total proteins of the samples were extracted by lysis buffer containing RIPA lysis buffer, protease and phosphatase inhibitor cocktail (Beyotime Institute of Biotechnology, Shanghai, China). The protein concentration of the samples was determined using a BCA protein assay kit (Thermo Fisher Scientific, Waltham, MA, USA), and then adjusted to the same level. The protein samples were added to 7.5–15% SDS-polyacrylamide gel electrophoresis, and sealed using 5% non-fat milk powder or 5% BSA for 1 h before transferring onto a PVDF membrane; then the film was incubated with primary antibodies at 4℃ in 16h and secondary antibody marked by HRP-anti-rabbit (1:5000, Abclonal, AS038) or HRP-anti-mouse (1:5000, Abclonal, AS003) separately. The film was processed with an ECL kit, and the gray values of each protein were recorded and analyzed. The primary antibodies included anti-NLRP3 (1:1000, Adipogen,AG-20B-0014-C100), anti-IL-6 (1:1000, Abclonal, A0286), anti-ZO-1 (1: 5000, 21773-1-AP, Proteintech), anti-Occludin (1: 5000, 27260-1-AP, Proteintech), anti-NF-κB (1:5000, HUABIO, ET1603-12), anti- SIRT1 (1:1000, CST, 9475),anti-Caspase-1 (1:1000, CST, 24232), anti-IBA-1 (1:1000, CST, 17198), anti-Phospho-IκBα (1:5000, HUABIO, HA722770), anti-FFAR2 (1:1000, 84544-1-RR, Proteintech), anti-TLR4 (1:1000, Abclonal, A5258), anti-MyD88 (1:1000, CST, 4283), and anti-IL-1β(1:1000, Thermo, P420B). β-actin (1:100000, Abclonal, AC026) was used as the internal control. Immunohistochemistry (IHC) and Immunofluorescent (IF) staining Mice were subjected to anesthesia via intraperitoneal injection of tribromoethanol (100 mg/kg) and subsequently underwent transcardial perfusion with 1× phosphate-buffered saline (PBS) followed by a 4% paraformaldehyde solution. Thereafter, the brain and colon tissues were fixed in 4% paraformaldehyde for 48 hours and subsequently dehydrated in a 30% sucrose solution for 72 hours. The brain and colon tissues were then frozen and embedded in optimal cutting temperature (OCT) compound (Sakura Finetek, Torrance, CA, USA, Cat# 4583) prior to sectioning into uniform slices (brain: 40 µm; colon: 12 µm) using a microtome (Leica Microsystems, Wetzlar, Germany). The frozen sections were thawed and mounted onto positively charged slides (ProbeOn Plus; Thermo Fisher Scientific, Waltham, MA, USA) before being stored at − 80°C. For antigen retrieval from frozen brain sections, the sections were subjected to 20–30 minutes of microwave treatment (Midea, Foshan, Guangdong, China, Cat# M1-211A) in citrate buffer (pH 6.0) (Servicebio, Cat# G1202). Following this, a blocking solution composed of 10% bovine serum albumin (BSA) (Beyotime) and 0.3% Triton X-100 (Aladdin, Cat# T434386) in PBS was applied for 30 minutes. The sections were then incubated with 3% hydrogen peroxide (H₂O₂) for 15 minutes as part of the immunohistochemistry protocol. Subsequently, the sections were incubated overnight at 4°C with primary antibodies diluted in normal goat serum (2%) (Beyotime, Shanghai, China, Cat# C0265), followed by incubation with biotinylated secondary antibodies and horseradish peroxidase − streptavidin or the appropriate secondary antibodies to detect the corresponding primary antibodies. Nuclei were visualized using DAPI solution. Representative images were captured using a fluorescence microscope (Nikon CSU-W1 Sora 2 Camera (CSU-W1); Olympus Corporation, VS120-S6-W). The number of positive cells was quantified using Image Pro Plus 6.0 software, with each section analyzed based on five randomly selected fields. The primary antibodies utilized included anti-Tyrosine Hydroxylase antibody (1:1000, Thermo Fisher Scientific, P21962), anti-α-Synuclein (D37A6) antibody (1:1000, CST, 4179), anti-Iba1/AIF-1 (E4O4W) antibody (1:200, CST, 17198), anti-Occludin antibody (1:1000, Proteintech, 27260-1-AP), and anti-ZO-1 antibody (1:2000, Proteintech, 21773-1-AP). The secondary antibodies employed were Alexa 488-conjugated goat anti-rabbit IgG secondary antibodies (1:1000, Thermo Fisher Scientific, A32723), HRP-anti-rabbit (1:1000, Abclonal, AS038), and Alexa 594-conjugated goat anti-rabbit IgG secondary antibodies (1:1000, Thermo Fisher Scientific, A11005). Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) Total RNA was isolated utilizing TRIzol Reagent (Vazyme Biotech, R411-01) and subsequently subjected to reverse transcription via a PrimeScript RT-PCR kit (Abclonal, RK20433). Quantitative real-time PCR (qRT-PCR) was performed using SYBR Premix Ex Taq (Vazyme Biotech, R433) on the QuantStudio 7 platform (Life Technologies). The primers were custom-synthesized by GENEWIZ, China (refer to Table S2). The fluorescence signals corresponding to the target genes were analyzed by the 2−∆∆Ct method for relative quantification, with Actin or GAPDH serving as endogenous reference genes. Enzyme-linked immunosorbent assay The enzyme-linked immunosorbent assay (ELISA) kits utilized for the quantification of murine interleukin-1β (IL-1β), interleukin-6 (IL-6), lipopolysaccharide (LPS) endotoxin, and lipopolysaccharide-binding protein (LBP) were sourced from Jianglai Industrial Limited by Share Ltd, Shanghai, China (catalog numbers JL20691, JL29644, JL20268, JL18442). The experimental procedures were meticulously executed in strict compliance with the manufacturer’s instructions. The concentrations of the target analytes were determined via the generation and analysis of standard protein calibration curves. Fecal DNA extraction and 16S RNA sequencing At the six-week juncture, mice were randomly designated from each experimental cohort for microbiota sequencing analysis. Each mouse was individually housed in a distinct, sterile, autoclaved cage, and five fresh fecal pellets were collected from each mouse and promptly transferred into a sterile EP tube. All fecal samples were rapidly frozen and stored at − 80°C for subsequent analysis. Genomic DNA was isolated from 200 mg of each fecal sample using the QIAamp DNA Stool Mini Kit (QIAGEN, Hilden, Germany). The quality and integrity of the extracted DNA were subsequently validated through 1.2% agarose gel electrophoresis. For library construction, a two-step polymerase chain reaction (PCR) amplification targeting the V3-V4 hypervariable region of the 16S rRNA gene was employed. The PCR amplification utilized universal primers 357F (5′-ACTCCTACGGRAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The thermal cycling parameters were as follows: initial denaturation at 95°C for 3 min, followed by 30 cycles of denaturation at 98°C for 20 s, annealing at 58°C for 15 s, and extension at 72°C for 20 s, with a final extension at 72°C for 5 min. The quantified amplicons were then pooled at equimolar concentrations for Illumina MiSeq sequencing (Illumina, Inc., CA, USA). The entire experimental workflow, encompassing DNA extraction, quality assessment, library construction, and high-throughput sequencing, was executed by TinyGene Bio-Tech (Shanghai, China). Polarization of mouse bone marrow-derived macrophages and SCFAs treatment Bone marrow cells isolated from femurs of mice were cultured for 7 d in the presence of 20 ng/mL recombinant mouse macrophage colony-stimulating factor (M-CSF, PeproTech) in complete RPMI-1640 medium containing 10% fetal bovine serum (FBS), 10 mM glucose, 2 mM L-glutamine, 100 U/mL penicillin-streptomycin. During cell culture, the morphological changes and growth status of cells were observed with an inverted microscope (Nikon Ti-S) every day. In order to further explore the influence of acetate (NaA) and butyrate (NaB) on M1 and M2 polarization, on day 7, M0 macrophages were harvested and then were stimulated for 24 h with 1 µg/ml LPS (Shandong Sparkjade Biotechnology Co., Ltd.) and 1 mM ATP (Sigma) for the generation of M1 macrophages. And then acetate or butyrate was added for 24 h. Groups were as follows: Control group, LPS + ATP group, LPS + ATP + acetate group (5 mM acetate), LPS + ATP + butyrate group (0.5 mM butyrate). Small Interfering (si) RNA Transfection siRNA targeting FFAR2 or control siRNA were synthesized by GenePharma (see in Table S3). Four individual siRNA sequences were constructed to form the siRNA Smart Pool to reduce the off-target efficiency of siRNAs. Transfections were performed using the Lipofectamine™RNAiMAX reagent (Invitrogen). Cells were treated with 5mM NaA or 0.5mM NaB for 24h after 48h post-transfection and 24h Inflammation modeling. Western Blot confirmed the downregulation of the FFAR2 targeted by siRNA. Fecal sample collection and SCFA level measurement (Feces and B.coprocola bacterial solution supernatant) Each mouse was required to provide a fecal sample in the morning using designated fecal collection containers. The containers were immediately placed on ice and subsequently stored at − 80°C until further processing. The analysis of short-chain fatty acids (SCFAs) was conducted by TinyGene Bio-Tech (Shanghai) Co., Ltd., following standardized protocols. For each mouse, 400 mg of fresh fecal sample was subjected to SCFA analysis after undergoing grinding and sonication as pretreatment steps. The quantification of individual SCFAs in fecal samples was achieved using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). A calibration curve was constructed with the concentration of the standard as the x-axis and the peak area ratio of the standard to the internal standard as the y-axis. Utilizing these established metabolite calibration curves, quantitative determinations were performed for all samples to ascertain the SCFA concentrations in each fecal sample (R² >0.99). Statistical analysis Statistical analyses were conducted utilizing GraphPad Prism (version 8.01; GraphPad Software Inc., San Diego, CA, USA). One-way analysis of variance (ANOVA) was employed to assess differences among multiple groups. Comparisons of numerical data between two groups were performed using the Mann-Whitney U test or unpaired Student's t-test. For nonparametric analyses, the Kruskal-Wallis H test or Mann-Whitney U test was applied. Data are presented as mean ± standard deviation (SD) or as representative figures. The criterion for statistical significance was established at *p < 0.05. Results B.coprocola intervention ameliorates motor impairments and gastrointestinal disturbances in the rotenone-induced PD mouse model Weight reduction, motor disturbances, and GI impairments frequently manifest in animal models of PD. To assess the protective efficacy of B.coprocola administration in PD, we developed a chronic PD mouse model via intraperitoneal injection of rotenone over a 3-week period. Subsequently, during the following 3 weeks, mice induced with rotenone were treated with either B.coprocola or vehicle (Figure.1a). Regarding weight reduction, mice in the rotenone group exhibited significant weight loss during the initial 3-week period of PD model induction. From weeks 4 to 6, treatment with B.coprocola appeared to mitigate weight loss in rotenone-induced mice, and the rate of weight recovery in the B.coprocola -treated group was more rapid compared to that of the rotenone-induced PD group (Figure.1b-c). At the 6-week time point, three distinct behavioral assays were conducted to evaluate the motor functions of mice across different experimental groups. These tests included the Rota-Rod test for assessing motor coordination, the pole test, and the beam walking test for evaluating motor balance (Figure. 1a). Mice subjected to rotenone intoxication exhibited significant motor impairments compared to the control group, as evidenced by reduced latency on the Rota-Rod (P < 0.0001, Figure. 1d), prolonged climbing times in the pole test (P < 0.001, Figure. 1e), and increased time spent on the beam during the beam walking test (P < 0.01, Figure. 1f). Conversely, mice treated with B.coprocola demonstrated substantial improvements in performance on the Rota-Rod test (P < 0.01, Figure. 1d), the pole test (P < 0.05, Figure. 1e), and the beam walking test (P < 0.05, Figure. 1f) relative to the rotenone-induced PD group. Moreover, GI dysfunction was assessed in this study. Evans blue dye was utilized to evaluate intestinal transit function in mice, and the length of the colon was measured. Mice in the rotenone-induced PD group exhibited a significant reduction in intestinal transit distance (P < 0.001, Figure. 1g-h) and colon length (P < 0.001, Figure. 1i-j) compared to the control group. In contrast, treatment with B.coprocola significantly ameliorated these GI impairments induced by rotenone (P < 0.05, P < 0.01, Figure. 1g-j). Fecal pellets were collected to determine the fecal water content percentage. Mice subjected to rotenone exhibited a marked decrease in fecal water content percentage (P < 0.01, Figure. 1k), which was significantly increased following B.coprocola administration (P < 0.05, Figure. 1k). In summary, the data indicate that rotenone intoxication precipitates weight reduction, motor impairments, and GI dysfunction in the PD murine model, while administration of B.coprocola substantially mitigates these PD-related manifestations. B.coprocola administration mitigates PD-related histological features in the brain and the colon of the rotenone-induced mice model In order to elucidate the mechanisms underlying the protective effects of B.coprocola treatment against GI dysfunction and motor impairments, we examined the histological features in both the brain and the colon through a series of experimental approaches. It is widely recognized that the degeneration of dopaminergic neurons and the aggregation of α-syn are two key histological indicators of PD[ 17 ]. The cell bodies of dopaminergic neurons are situated in the substantia nigra pars compacta (SNc), whereas their axonal projections extend to the caudate-putamen (CPu) region[ 18 ]. In the present investigation, the number of TH + cells in the SNc and CPu of mice in the rotenone-induced PD group was significantly diminished compared to that of the control group (P < 0.01), whereas treatment with B.coprocola substantially mitigated this neuronal loss (P < 0.05) (Figure. 2a). As another critical histological marker of PD, immunofluorescence staining revealed a marked upregulation of α-syn expression in the SNc and CPu of mice in the rotenone-PD group (both P < 0.001) (Fig. 2 a-c). Conversely, B.coprocola treatment notably diminished the aggregation of α-syn in both regions (SNc: P < 0.001; CPu: P < 0.001) (Figure. 2d-f). The accumulation of synuclein protein in the gastrointestinal tract is also a significant pathological feature associated with the progression of PD[ 19 ]. Immunofluorescence analysis indicated that the expression of α-syn in the colon of rotenone-induced mice was significantly elevated compared to that of the control group and the B.coprocola -treated group (P < 0.001; P < 0.01, Figure. 2l-m). It has been reported that the activation of microglial cells may play a role in neuroinflammation and dopaminergic neuronal demise in the brain during the progression of PD[ 20 ]. The expression level of Iba-1 protein can serve as an early indicator of microglial reactivity[ 21 ]. In the current study, immunofluorescence staining of the SNc and CPu was performed to assess glial cell reactivity, with Iba-1 serving as a marker for microglia. A significant increase in Iba-1 + cells was observed in the SNc and CPu of mice in the rotenone-induced PD group (SNc: P < 0.01; CPu: P < 0.001, Figure. 2g-i). However, treatment with B.coprocola significantly reduced the elevation of Iba-1 + cells in the SNc and CPu of treated mice (SNc: P < 0.05; CPu: P < 0.01, Figure. 2g-i). Western blot analysis of Iba-1 levels in the midbrain also revealed a similar trend (P < 0.0001; P < 0.01, Figure. 2j-k). Collectively, these results demonstrate that B.coprocola intervention markedly ameliorates PD-associated histopathological features in both the brain and colon of rotenone-induced murine models. These observations also imply that B.coprocola treatment may be associated with the modulation of immune cell activity. B.coprocola intervention ameliorates gut microbiota dysbiosis in the rotenone-induced PD mouse model Currently, an increasing number of studies have identified gut microbiota dysbiosis in both PD patients and PD animal models, highlighting its crucial role in the pathogenesis of PD[ 22 ].To elucidate the mechanisms by which B.coprocola administration protects the rotenone-induced PD mouse model through modulation of the microbiome community structure, we performed 16S rRNA sequencing on fecal samples from mice in different experimental groups. Initially, α-diversity analysis was conducted to evaluate the richness and diversity of bacterial taxa. As depicted in Figure. 3a-f, mice in the rotenone-induced PD group demonstrated statistically significant reductions in the Observed species index (P = 0.021), Chao1 richness estimator (P = 0.0084), ACE richness index (P = 0.0102), Shannon diversity index (P = 0.0446), and Phylogenetic Diversity (PD) whole tree index (P = 0.0133), as well as an increase in the Simpson dominance index (P = 0.0504), relative to the control and B.coprocola -treated groups. These results suggest that B.coprocola treatment ameliorated the rotenone-induced alterations in microbial abundance and diversity. Moreover, β-diversity analysis unveiled analogous patterns. At week 6, the microbiome community structure of the rotenone-PD group exhibited a significant divergence from that of the control and B.coprocola groups, as demonstrated by OUT-JACCARD-ANOISM analysis (R = 0.1984, P = 0.013) and Unweighted-ANOISM analysis (R = 0.1086, P = 0.089). The microbiome community structures of the control and B.coprocola groups remained comparable, indicating that B.coprocola intervention markedly modified the diversity of the gut microbiota (Figure. 3g,h). Additionally, we performed taxonomic profiling at the genus level across all experimental groups (Figure. 3i). Differential abundance analysis using linear discriminant analysis effect size (LEfSe) identified key microbial taxa with statistically significant intergroup differences (Figure. 3k). Specifically, the relative abundances of Parabacteroides, Odoribacter, Alistipes , and Bacteroides were diminished in the rotenone-PD group compared to the control, whereas Akkermansia and Bifidobacterium were enriched. Notably, intervention with B.coprocola markedly restored the relative levels of these bacterial genera, including Parabacteroides, Odoribacter, Alistipes, Bacteroides, Akkermansia , and Bifidobacterium (Figure. 3j). B.coprocola treatment restores tight junction proteins expression and inhibit the leakage of microbial toxins in the rotenone-induced mouse model. Gut microbial disorders can trigger chronic inflammation of the body's intestinal and even systemic nature[ 23 ]. Existing evidence indicates that the rotenone-induced PD mouse model manifests compromised BBB and intestinal barrier integrity, concomitant with the generation of inflammatory cytokines and pathogenic lipopolysaccharide (LPS)[ 24 , 25 ]. We initially assessed the expression levels of two major tight junction proteins, namely ZO-1 and occludin, in the midbrain and colon. qRT-PCR and Western blot analyses demonstrated that the expression of ZO-1 and occludin was significantly diminished in the rotenone-induced group relative to the control group, whereas treatment with B.coprocola substantially restored these reductions (all P < 0.05) (Figure. S1 a-d; Figure. 4d-h). Additionally, immunofluorescence staining of the colon revealed that the fluorescence intensities of ZO-1 and occludin were markedly decreased in the rotenone-PD group (all P < 0.0001) but significantly increased in the B.coprocola group ( P < 0.01, P < 0.05) (Figure. 4a-c). Then, we quantified the levels of LPS, LBP in the midbrain, serum(blood) and colon. The ELISA analysis indicated that both LPS and LBP levels were elevated in the rotenone-PD group compared to the control group. In contrast, B.coprocola administration significantly attenuated these elevations (all P < 0.05, Figure. 4i-n). Collectively, these findings suggest that B.coprocola treatment restores barrier integrity in the rotenone-induced mouse model, protecting microbial toxins leakage. B.coprocola treatment affects the polarization response of M1/M2 type macrophages/microglia in the gut-blood-brain axis of the rotenone-induced Parkinson's disease mouse model. Systemic chronic inflammation activates various types of immune cells in the body to exert immune functions and thus modulate the inflammatory response. Previously, we have demonstrated that B.coprocola treatment may inhibit rotenone-induced inflammation in the brains of mice with PD by modulating the activation pattern of microglia. To investigate the potential impact of B.coprocola treatment on myeloid cells regulating systemic chronic inflammation, we measured the number and phenotypes of M1/M2 type macrophages/microglia in the gut-blood-brain axis. Macrophages were defined as CD11b + CD45 + F4/80 + cells in the colon and blood, and the populations of CD80 (M1 marker) and CD206 (M2 marker) macrophages were gated using FMO controls (Figure. 2S). In the colon, the percentage of CD80 + macrophages of the rotenone-PD group mice remarkably increased compared with the control group mice (P < 0.01), while B.coprocola treatment significantly decreased the CD80 + macrophages (P < 0.05) (Figure. 5a, e). In contrast, the percentage of CD206 + macrophages of the rotenone-PD group mice remarkably decreased compared with the control group mice (P < 0.001), but markedly elevated in the B.coprocola group (P < 0.05) (Figure. 5a, f). The preceding data suggest that intestinal barrier damage in the rotenone-induced PD mouse model leads to the leakage of LPS into peripheral tissues. In the blood, the results illustrated that the percentage of CD80 + macrophages increased significantly in the rotenone-induced group compared to the control group whereas B.coprocola treatment markedly decreased the CD80 + macrophages (P < 0.001, P < 0.01) (Figure. 5b, g). But it did not markedly affect the variation of cell counts of CD206 + macrophages (Figure. 5c, j). In the brain, we analyzed the accumulation of infiltrating macrophage and activated microglia, which defined as CD11b+, CD45 + high. Flow cytometry analysis revealed that B.coprocola treatment of rotenone-induced mice strikingly reduced the percentage of infiltrating macrophage and microglia defined as M1-type cells compared with the rotenone-PD group mice. However, B.coprocola administration did not significantly affect the percentage of M2-type microglia/macrophages in the brain (P < 0.0001, P < 0.001) (Figure. 5d, h, i). B.coprocola administration inhibits the NLRP3 signaling pathway to regulate macrophage/microglia polarization in the brain and colon of the rotenone-induced mouse model. NLRP3 signaling pathway is an inflammatory vesicle pathway. Specifically up-regulated LPS can act on the macrophage TLR4 receptor, bind to the key junction protein MyD88, further promote IκBα phosphorylation, and release NF-κB to activate NLRP3 inflammatory vesicles. The activated NLRP3 inflammasome can promote the maturation of Caspase-1, which in turn leads to the maturation and secretion of inflammatory factors, triggering an inflammatory response[ 26 ]. This pathway plays a dominant role in the mechanism of microbiota-gut-brain axis[ 27 ]. Therefore, we detected the activation status of NLRP3 pathway in the midbrain and the colon using western blot methods. Interestingly, the colon samples were consistent with the results in the midbrain tissues. The western blot results demonstrated a significantly enhanced expression of TLR4, MyD88, p-IκBα, NF-κB, NLRP3, and caspase-1 in the rotenone-PD group relative to the control group. Conversely, the B.coprocola group expression of TLR4, MyD88, p-IκB-α, NF-κB, NLRP3, and caspase-1 remarkably reduced (all P < 0.05) (Figure.6a-d). In addition, we examined the expression levels of NLRP3 downstream inflammatory factors in the midbrain, colon and blood by Western blotting, qRT-PCR and ELISA. Protein and mRNA expression of IL-1β and IL-6 was significantly increased in mice in the rotenone-PD group. However, B.coprocola treatment group mice significantly down-regulated the expression of these inflammatory factors (Figure. 6e-h, Figure. S2 a-f). This suggests that B.coprocola can alleviate PD-like pathology by modulating systemic inflammation in the rotenone-PD mouse model through the NLRP3 signaling pathway. The acetic acid and butyric acid produced by B.coprocola are potential active metabolites To investigate the relationship between B.coprocola and metabolite among the three groups of mice, and to identify potential bioactive metabolites, we first employed PCA analysis and PLS-DA model to perform a multivariate analysis (Figure. 7a, b). The PCA score chart and the PLS-DA model showed that the samples in the three groups was clearly separated, and the clustering effect was relatively obvious. The clustering of the control group and B.coprocola tends to be more consistent. This further suggests that distinct metabolic principal components may play a key role in influencing the PD progression of rotenone-induced. In order to identify potential bioactive metabolites, we performed metabolomic analyses targeting SCFAs on feces from three groups of experimental mice, as well as on B.coprocola bacterial liquid supernatants and found that acetic acid (P = 0.022) and butyric acid (P = 0.008) exhibited statistically significant differences among the three groups of mice (Figure. 7c-e; Figure.S4). Therefore, it suggested that acetic acid and butyric acid were likely the key metabolites involved in the regulation of the PD pathological progression by the B.coprocola (Figure. 7c-e). Finally, we also performed a correlation analysis between the differentially abundant bacterial genera and short-chain fatty acids (SCFAs) at the genus level. Alistipes and Odoribacter showed a positive correlation with butyric acid, at the same time, Anaeroplasma and Candidatus_Soleaferrea exhibited a significant positive correlation with acetic acid. These findings suggest that bacterial genera such as Alistipes , Odoribacter and Anaeroplasma may be closely associated with the metabolism of SCFAs (e.g., butyric acid and acetic acid) and could potentially play a beneficial role in maintaining host gut health. And this similarly suggests that B.coprocola may regulate the level of SCFAs in the gut by affecting the abundance of other SCFAs-producing genera. Acetic acid and butyric acid produced by B.coprocola induce the M1/M2 polarization of primary macrophages to inhibit the NLRP3 signaling pathway and the production of pro-inflammatory factors in the LPS BMDM model. In vivo, we have demonstrated that B.coprocola gavage can influence the polarization of macrophages/microglia in the gut-blood-brain axis while alleviating the systemic chronic inflammatory response in rotenone-induced mice. Based on these findings, we further investigated whether the potential functional metabolites of B.coprocola can affect the polarization of macrophages, thereby regulating the inflammatory response. To better reflect in vivo conditions, we selected mouse bone marrow-derived BMDM as the experimental model and induced their differentiation into primary macrophages in vitro. LPS + ATP (LPS: 1 µg/ml, ATP: 1 mm) were used to induce the activation of NLRP3 inflammasome in primary macrophages. M1 macrophages were defined as CD11b/F4/80+/CD80 cells and M2 macrophages were defined as CD11b/F4/80+/CD206 cells, which were gated using FMO controls (Figure.S5). As expected, both acetic acid and butyric acid significantly dowmregulated the percentage of CD86 + M1 macrophages. However, only butyric acid was able to upregulate the proportion of CD206 + M2 macrophages, and acetic acid did not significantly affect the percentage of M2-type macrophages (Figure. 8a-d). FFAR2 is the key receptor through which acetic acid and butyric acid exert their effects on immune cells. As shown in Figure. S3, after using FFAR2-siRNA 4mix smartpool to interfere with primary macrophages, FFAR2 protein levels were significantly decreased, with the knockdown efficiency reached 75%. Then, we examined the expression of FFAR2 receptor and its downstream deacetylase SIRT1 in primary macrophages in 8 group [LPS + ATP group, LPS + ATP + FFAR2-siRNA 4mix group, LPS + ATP + FFAR2-siRNA 4mix + acetate/butyrate group (5 mM acetate, 0.5 mM butyrate), LPS + ATP + acetate/butyrate group]. The western blot results showed that the expression of FFAR2 and SIRT1 were significantly upregulated in the LPS + ATP + acetate/butyrate group (Figure.9a, c, e, i, l). The upregulated SIRT1 can further act on the downstream p-IκBα factor, inhibiting its phosphorylation. Consistent with in vivo results, the protein expression levels of p-IκBα, caspase-1, NLRP3 and NF-κB (Figure. 9a-m), which are dowmstream and upstream priming signal molecule of NLRP3 inflammasome, were significantly decreased after acetic acid and butyric acid treatment (all P < 0.05). We also proceeded to measure the downstream inflammatory cytokines including IL-1β, IL-6, and the ELISA results demonstrated that the level of IL-1β, IL-6 LPS reduced in the acetic acid group and the butyric acid group compared to the LPS group (all P < 0.001) (Figure.8e-h). Discussion Given the growing body of research suggesting that gut microbiota dysbiosis, triggered by gastrointestinal disturbances, may be a key factor in the pathogenesis of PD[ 22 , 28 ]. In our previous large-scale clinical study, we identified a statistically significant difference in the abundance of B.coprocola between healthy individuals and PD patients (HC > PD)[ 13 ]. To further explore the role of B.coprocola in PD, we established a rotenone-induced PD mouse model associated with gut microbiota dysbiosis. This model was used to evaluate the protective effects of B.coprocola treatment in PD and to further investigate the potential mechanisms. Recent studies have revealed that microbial toxins, such as LPS, can specifically target and regulate immune cells, thereby contributing to systemic chronic inflammation and gut microbiota dysbiosis—both of which are associated with PD pathology[ 29 ]. Additionally, these microbial toxins can directly target neurons in the CNS, inducing neuronal dysfunction, which is closely linked to the pathological progression of PD[ 30 ]. It is currently known that the rotenone-induced PD mouse model can activate the gut-brain toxicity pathway in PD[ 24 ]. Therefore, we hypothesize that B.coprocola supplementation may alleviate systemic chronic inflammation in rotenone-induced PD mice, thereby modulating motor dysfunction and pathological features in PD. In this study, we established a PD mouse model by intraperitoneal injection of rotenone, followed by oral gavage treatment with B.coprocola . The rotenone-induced PD mice exhibited significant phenotypes, including weight loss, gastrointestinal dysfunction, and motor impairments. Three classical behavioral tests used in PD research—Rota-Rod test, Pole test, and Beam walking test—were conducted to assess motor function, while GI dysfunction was evaluated by measuring intestinal transit distance and colonic length. Further histological analyses of intestinal and brain tissues revealed that rotenone administration led to a reduction in tyrosine hydroxylase positive cells (dopaminergic neurons) and cytoplasmic accumulation of α-synuclein in the brain, which is consistent with findings from other studies[ 31 ]. Collectively, these results indicate that the chronic rotenone-induced mouse model effectively recapitulates PD progression, exhibiting both GI dysfunction and motor deficits. Notably, B.coprocola treatment significantly ameliorated PD-related behavioral impairments and pathological changes in rotenone-induced PD mice. Firstly, it is generally accepted that the balance of gut microbiota maintains well the individual health[ 32 ]. We provided evidence that rotenone-induced mouse model significantly affects gut microbial composition resulting in disturbed gut ecology. To investigate whether B.coprocola treatment could ameliorate gut microbiota dysbiosis in PD mice, we performed 16S rRNA sequencing. The results indicated that rotenone-induced significantly disrupted microbial diversity, leading to alterations in α-diversity indices and β-diversity. Notably, B.coprocola treatment restored microbial diversity and increased the abundance of beneficial genera such as Parabacteroides , Odoribacter , and Bacteroides , while reducing the overgrowth of Akkermansia and Bifidobacterium , both of which have been reported to be elevated in PD patients[ 33 – 36 ]. Bacteroides , Odoribacter and Parabacteroides are major genera of SCFAs producing bacteria in the gut with potent anti-inflammatory and immunomodulatory effects[ 37 , 38 ]. Moreover, it has been shown that an increase in the abundance of Bifidobacterium species correlates with a decrease in the abundance of SCFA species[ 6 ]. Elevated levels of Bifidobacterium and a loss of SCFA-producing bacteria have also been observed in other inflammatory disorders of the gut[ 39 ]. A positive correlation between elevated Akkermansia abundance and the development of PD has been noted in several previous studies[ 40 , 41 ], and the same trend was observed in our study. However, other studies have also pointed out that Akkermansia spp. have a tendency to decrease in abundance in some senescent mice and ALS model mice, and that gavage of Akkermansia Muciniphila has a protective effect on ALS model mice[ 42 ]. Thus, the exact role of Akkermansia in pathogenesis of neurodegenerative diseases needs further exploration. Our findings suggests that B.coprocola may influence the pathologic development of PD by modulating the composition of the gut microbiota. Systemic chronic inflammation is a key factor in the pathogenesis of PD[ 43 ]. Both PD patients and animal models exhibit increased intestinal permeability, which allows microbial toxins to enter systemic circulation, thereby exacerbating neuroinflammation[ 44 , 45 ]. We examined the levels of LPS and LBP in the gut-blood-brain axis, and found that the levels of LPS and LBP in the gut, blood, and brain were significantly reduced in PD mice after B.coprocola treatment. Therefore, we hypothesize that B.coprocola may maintain the intestinal barrier by up-regulating the expression of tight junction proteins, improve the structure of the intestinal microbiota, increase the number of beneficial bacteria in the intestinal tract, and improve the balance of the intestinal flora, which in turn reduces the production of LPS in the intestinal tract. There are many studies pointing out that probiotic therapy can play an anti-inflammatory role by regulating the intestinal flora. For example, Lactobacillus reuteri can restore the gut microbial composition of the Cis rat model and ameliorate intestinal inflammation through remodeling of the gut microbiota[ 46 ]. P.distasonis reduces insulin resistance by repairing the intestinal barrier and improving the anti-inflammatory effects of gut microbiota dysbiosis[ 47 ]. Lactiplantibacillus pentosus prevents the inflammatory response in DSS-induced colitis mice by modulating the gut microbiota and serum metabolite levels[ 48 ]. Taken together, the studies have responded to the ability of probiotic therapy to influence the composition of gut microbes and build a healthier gut microbial ecology. In this study, B.coprocola treatment restored the expression of tight junction proteins (ZO-1 and occludin) in the colon and midbrain, indicating enhanced integrity of the intestinal barrier and BBB. This suggests that B.coprocola is able to maintain the intestinal barrier function, reduce the permeability of the intestinal barrier, and prevent the leakage of biotin toxins, such as LPS, from the intestines to the periphery triggering further immune responses. LPS in the intestine induces macrophages to polarize towards the M1 pro-inflammatory type, and polarized M1 macrophages trigger an inflammatory response and release inflammatory factors [ 49 ].The release of inflammatory factors is closely linked to the activation state of macrophages. M1 macrophages/microglia exhibit pro-inflammatory properties, whereas M2 macrophages/microglia promote tissue repair and anti-inflammatory responses[ 50 ]. We then further explored the proportion of M1 and M2 types of macrophages in the gut-blood-brain axis. Our flow cytometry results showed that B.coprocola treatment reduced the proportion of CD80⁺ M1 macrophages in the colon, blood, and brain. However, an increased proportion of CD206⁺ M2 macrophages was only observed in the colon. Studies of other gut microbes affecting macrophage polarization have also reported that Lactobacilli can alleviate the inflammatory response in a mouse model of IBD by modulating macrophage polarization [ 51 ]. C.butyricum -derived EVs modulate disordered intestinal flora and polarize macrophages toward the M2 type in UC mice[ 52 ]. So intestinal flora and macrophage polarization responses are closely linked. Then, we conclude that B.coprocola treatment mainly affects the polarization of M1-type macrophages to M2-type macrophages by reducing the amount of LPS in the intestine, thus controlling the inflammatory response in the intestine and preventing inflammatory factors from leaking or transmitting signals to the periphery. To further elucidate the molecular mechanisms underlying the therapeutic effects of B.coprocola , we focused on the systemic chronic inflammation induced by rotenone. Rotenone-induced PD mice models elicit systemic chronic inflammation and induce the formation of the NLRP3 inflammasome[ 53 ]. Additionally, research has indicated that neuronal NLRP3 is a parkin substrate that drives neurodegeneration in PD[ 54 ]. So the NLRP3 signaling pathway is closely related to the development of PD. Our study investigated the expression of this signaling pathway. First, we examined the expression of NLRP3 protein and mRNA in the colon and midbrain of three groups of experimental mice and found that NLRP3 expression was downregulated in B.coprocola treatment PD mice. LPS can act on the TLR4 receptor, recruit the key junction protein MyD88, and transmit signals downstream to prompt the phosphorylation of IκB, and the isolated NF-κB enters the nucleus, further up-regulates the expression of NLRP3, and activates the cleavage of inflammatory factors by caspase-1, which is converted into mature inflammatory factors to further promote the development of inflammation[ 55 , 56 ]. Our results demonstrated that B.coprocola treatment downregulated the expression of key components in the NLRP3 pathway, including TLR4, MyD88, p-IκBα, caspase-1, and NF-κB. This, in turn, downregulated the expression of pro-inflammatory factors IL-1β and IL-6. SCFAs are the main metabolites produced by intestinal flora fermenting dietary fiber, among which acetic acid, propionic acid and butyric acid are the three most abundant[ 57 ]. On the one hand, they can serve as energy substrates for cells and regulate energy homeostasis, and on the other hand, they can regulate the differentiation of immune cells to inhibit the occurrence of neuroinflammation and thus maintain the intestinal barrier function[ 58 ]. Butyrate is critical for the maintenance of intestinal homeostasis and capable of promoting iTreg generation by up-regulating histone acetylation for gene expression as an HDAC inhibitor[ 59 ]. Microbiota-derived acetate exerts antihypertensive effects by modulating microglia and astrocytes and inhibiting neuroinflammation and sympathetic output[ 60 ]. In our study, SCFAs metabolomic analysis revealed that acetic acid and butyric acid are the key metabolites produced by B.coprocola . We similarly performed metabolic analysis of targeted SCFAs in three groups of mice and found that acetic acid and butyric acid were statistically different between the three groups. We then further explored the effects of acetic acid and butyric acid on primary macrophage polarization in vitro, and established a primary macrophage LPS model to investigate whether acetic acid and butyric acid could ameliorate inflammation through the NLRP3 signaling pathway. In vitro experiments demonstrated that acetic acid and butyric acid significantly influenced macrophage polarization by reducing the proportion of M1-like CD86⁺ macrophages, while butyric acid not acetic acid specifically promoted the proportion of M2-like CD206⁺ macrophages. In addition, binding of acetic acid and butyric acid to the FFAR2 receptor similarly affected NF-κB inhibition of the NLRP3 signaling pathway and downregulated the release of inflammatory cytokines. These results further support the conclusion that B.coprocola -derived acetic acid and butyric acid may regulate macrophage polarization and suppress the NLRP3 signaling pathway, thereby alleviating systemic chronic inflammation in PD mice and improving PD-like symptoms. Our study for the first time reveals the protective effects of B.coprocola treatment in a chronic rotenone-induced PD mouse model. B.coprocola treatment alleviates PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and barrier dysfunction. Among these, regulating macrophage polarization and inhibiting the NLRP3 signaling pathway to alleviate systemic chronic inflammation may be key molecular mechanisms underlying the B.coprocola intervention in PD. Finally, our study highlights the importance of the gut-brain axis in the pathogenesis of PD and suggests that B.coprocola could be a promising microbial intervention strategy for PD treatment. Although the findings of this study are encouraging, several limitations warrant further investigation. First, while this study demonstrated the protective effects of B.coprocola in the rotenone-induced PD model, future research should explore its efficacy in other PD models. Additionally, we have shown that B.coprocola modulates PD pathology by regulating anti-inflammatory pathways in macrophages and shaping gut microbiota composition. However, the role of other immune cells has not been extensively investigated. Future studies will aim to elucidate the direct effects of B.coprocola on various immune cell populations. Finally, clinical translation remains a significant challenge. Further validation through additional animal models, such as primate PD models, is necessary to confirm the therapeutic potential of B.coprocola in PD. Conclusion Our study for the first time reveals the protective effects of B.coprocola treatment in a chronic rotenone-induced PD mouse model. B.coprocola treatment alleviates PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and barrier dysfunction. Among these, inhibiting the NLRP3 signaling pathway to alleviate systemic chronic inflammation may be key molecular mechanisms underlying the B.coprocola intervention in PD. Finally, our study highlights the importance of the gut-brain axis in the pathogenesis of PD and suggests that B.coprocola could be a promising microbial intervention strategy for PD treatment (Figure. 10). Abbreviations PD Parkinson’s disease NF-κB Nuclear factor-κB NLRP3 NOD-, LRR- and pyrin domain-containing 3 B.coprocola Bacteroides coprocola WT Wild type IL-1β Interleukin 1β Iba1 Ionized calcium-binding adapter molecule 1 CNS Central nervous system TH Tyrosine hydroxylase LPS Lipopolysaccharides LBP Lipopolysaccharide-binding protein IL-6 Interleukin 6 SCFA Short‑chain fatty acid BMDM Bone marrow-derived macrophages α-syn α-synuclein HC Healthy Control DMSO Dimethyl sulfoxide CMC-Na Carboxymethyl cellulose sodium EDTA Ethylenediaminetetraacetic acid HBSS Hank's balanced salt solution FBS Fetal bovine serum NaA Acetate NaB Butyrate ATP Adenosine 5'-triphosphate SNc Substantia nigra pars compacta CPu Caudate-putamen LEfSe Linear discriminant analysis effect size TLR4 Toll-like receptors 4 MyD88 Myeloid differentiation primary response protein 88 p-IκBα NF-kappa-B inhibitor alpha Phosphorylation PCA Principal components analysis PLS-DA Partial Least Squares Discriminant Analysis FFAR2 Free fatty acid receptor 2 SIRT1 Sirtuin type 1 Declarations Supplementary Information The online version contains supplementary material available at XXX Acknowledgments We acknowledge the contributions of all members of Professor Chen Shengdi’s laboratory at ShanghaiTech University. We are grateful for the support with flow cytometry provided by the Discovery Technology Platform at the Institute for Immunology and Chemical Biology. We also thank the Molecular and Cellular Platform and the Clinical Research Center at ShanghaiTech University for their support with microscopy and other instrumentation. Additionally, we appreciate the generous assistance with the anaerobic glove box provided by Professor Zhu Huanhu’s group at ShanghaiTech University. Authors’ contributions LZX, NJB, LYM and ZJQ performed experiments. LZX, HMX, CZL and YSS analyzed data. LZX, CSD and TYY designed the studies. LZX, CSD and TYY performed the research and analyzed the animal data. LZX wrote the manuscript and CSD and TYY revised the manuscript. All authors read and checked this manuscript. Funding This work was supported by the National Natural Science Foundation of China, (82171401), Shanghai Municipal Science and Technology Major Project, No. 2018SHZDZX05 and Peak Disciplines (Type IV) of Institutions of Higher Learning in Shanghai. Availability of data and material The 16S rRNA sequencing data have been deposited in the NCBI BioProject database https://www.ncbi.nlm.nih.gov/sra/PRJNA1267990. Other data relevant to the study are included in the article or uploaded as supplementary files. The data are available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate The animal experiment was approved by the Institutional Animal Care and Use Committee (IACUC) of ShanghaiTech University (IACUC No: 20220503001). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Disclosure statement No potential conflict of interest was reported by the author(s). 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Commensal bacteria-derived extracellular vesicles suppress ulcerative colitis through regulating the macrophages polarization and remodeling the gut microbiota. Microb Cell Fact. 2022;21:88. Zheng D, Lai Y, Huang K, Guan D, Xie Z, Fu C, et al. Pyroptosis mediated by Parkin-NLRP3 negative feedback loop contributed to Parkinson’s disease induced by rotenone. Int Immunopharmacol. 2024;143:113608. Panicker N, Kam T-I, Wang H, Neifert S, Chou S-C, Kumar M, et al. Neuronal NLRP3 is a parkin substrate that drives neurodegeneration in Parkinson’s disease. Neuron. 2022;110:2422–e24379. Maluleke TT, Manilall A, Shezi N, Baijnath S, Millen AME. Acute exposure to LPS induces cardiac dysfunction via the activation of the NLRP3 inflammasome. Sci Rep. 2024;14:24378. Wang L, Hauenstein AV. The NLRP3 inflammasome: Mechanism of action, role in disease and therapies. Mol Aspects Med. 2020;76:100889. Kim CH. Microbiota or short-chain fatty acids: which regulates diabetes? Cell Mol Immunol. 2018;15:88–91. Dalile B, Van Oudenhove L, Vervliet B, Verbeke K. The role of short-chain fatty acids in microbiota–gut–brain communication. Nat Rev Gastroenterol Hepatol. 2019;16:461–78. Hao F, Tian M, Zhang X, Jin X, Jiang Y, Sun X, et al. Butyrate enhances CPT1A activity to promote fatty acid oxidation and iTreg differentiation. Proc Natl Acad Sci USA. 2021;118:e2014681118. Yin X, Duan C, Zhang L, Zhu Y, Qiu Y, Shi K, et al. Microbiota-derived acetate attenuates neuroinflammation in rostral ventrolateral medulla of spontaneously hypertensive rats. J Neuroinflammation. 2024;21:101. Supplementary Files westernblotsupplementaryfile.docx Additionalfile1.docx Additional file 1: Methods. Table S1. The culture medium formula for B.coprocola . Table S2. Paired primers for qPCR. Table S3. Primers for FFAR2 siRNA Smart Pool. Additionalfile2.docx Additional file 2: Figure S1-S2. Effects of B.coprocola treatment on rotenone-induced PD mice. mRNA expression levels of occludin, ZO-1, NLRP3, IL-1β, IL-6 in the midbrain and colon were detected via qRT-PCR. Figure S3. Representative western blot brands and density analysis of FFAR2-siRNA knockdown efficiency. Figure S4. The metabolomics analysis of short-chain fatty acids targeted by the supernatant of B. coprocola . Figure S5. The gating strategy of flow cytometry. Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2026 Read the published version in Translational Neurodegeneration → Version 1 posted Reviewers agreed at journal 13 Jul, 2025 Reviewers invited by journal 08 Jul, 2025 Editor assigned by journal 30 Jun, 2025 First submitted to journal 27 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-6875771","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482664104,"identity":"f977fcb7-0a10-484e-8144-64378317a599","order_by":0,"name":"zixian liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACPmYQaWDDYACkgGwJIMUDxGy4tbCBtRSkwbVIENYCJj8chmlhIEILO4/xZx6D8/bm7GcPvy6osajjZz97gOFD2WEG/tkNOBzGY2A4w+B24s6evDTrGcckJCR78hIYZ5w7zCBx5wBOLQkfDG4nGBzIMTPmYZOQMLjBY8DM2wZ0qkQCTi0HEgzO2RucfwPU8k9Cwh6k5S9+LYYNHwwOMG64kWP8mLcNaIsEUAsjXi1sxYwzDJITN9x4Y8bM2ychOeNMjsHBnnPpPBI3sGvh5z+8+TPPHzugw3KAQfetjp+//Yzhgx9l1nL8M7BrQbFRAsY6wACJHYKA+QMxqkbBKBgFo2DkAQCDoFIpxU6GqAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-1998-1093","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":true,"prefix":"","firstName":"zixian","middleName":"","lastName":"liu","suffix":""},{"id":482664105,"identity":"103788bc-a5c7-47de-902b-70737e15f82e","order_by":1,"name":"Jiabei Nie","email":"","orcid":"","institution":"Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiabei","middleName":"","lastName":"Nie","suffix":""},{"id":482664106,"identity":"681fdf7c-073f-46b5-ab57-563e134c7bb1","order_by":2,"name":"Yimei Li","email":"","orcid":"","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Yimei","middleName":"","lastName":"Li","suffix":""},{"id":482664107,"identity":"1edddb0f-1b86-423f-8d19-85cd5f8c61d4","order_by":3,"name":"Maoxin Huang","email":"","orcid":"","institution":"Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital","correspondingAuthor":false,"prefix":"","firstName":"Maoxin","middleName":"","lastName":"Huang","suffix":""},{"id":482664108,"identity":"ab685261-6647-4bf0-8bc0-491906dc01dc","order_by":4,"name":"Ziluo Chen","email":"","orcid":"","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Ziluo","middleName":"","lastName":"Chen","suffix":""},{"id":482664109,"identity":"9d9dac3d-dd12-4144-ad00-abb05b66f916","order_by":5,"name":"Shushang Yu","email":"","orcid":"","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Shushang","middleName":"","lastName":"Yu","suffix":""},{"id":482664110,"identity":"fea4c5df-827a-4fe9-ba8c-9b82a337d329","order_by":6,"name":"Jiaqi Zheng","email":"","orcid":"","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Zheng","suffix":""},{"id":482664111,"identity":"91427e23-bc59-49a3-9abe-c99984e16dc1","order_by":7,"name":"Yuyan Tan","email":"","orcid":"","institution":"Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuyan","middleName":"","lastName":"Tan","suffix":""},{"id":482664112,"identity":"1f834edc-b3ff-4079-9411-c47bd427f0ad","order_by":8,"name":"Shengdi Chen","email":"","orcid":"","institution":"ShanghaiTech University - Zhangjiang Campus: ShanghaiTech University","correspondingAuthor":false,"prefix":"","firstName":"Shengdi","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-06-12 02:35:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6875771/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6875771/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40035-026-00542-8","type":"published","date":"2026-02-28T15:58:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86663270,"identity":"ed2585fe-2efa-4679-aa46-052cd02b87b4","added_by":"auto","created_at":"2025-07-14 10:48:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1682948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e treatment alleviates motor symptoms and gastrointestinal dysfunctions of the rotenone-induced PD mouse model.\u003c/p\u003e\n\u003cp\u003e(a) The flow chart of animal treatments. (b-c) The body weights of mice from week 0 to week 6. (d) Rota-Rod test. ePole test. f Beam walking. (g-h)Intestinal transit distances. (i-j)Colon lengths. (k) Water percentages of fecal pellets. For (b–f), n=15 for each group. For (g-k), n=5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/54772c4259aa9f612f54c13e.png"},{"id":86659813,"identity":"d13187c1-c6fb-4654-8904-7c17ffd8be00","added_by":"auto","created_at":"2025-07-14 10:32:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2165010,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e treatment attenuates PD-associated histological features in the midbrain and the colon of the rotenone-induced mouse model.\u003c/p\u003e\n\u003cp\u003e(a-c) Representative captures of immunohistochemistry in the SNc and CPu ; Statistical analysis about numbers of TH+ cells in the SNc and CPu. (d-f)Representative captures of immunofluorescence in the SNc and CPu of nuclei (DAPI, blue), α-syn (green). Statistical analysis of α-syn density in the SNc and CPu. (g-i) Representative captures of immunofluorescence in the SNc and CPu of nuclei (DAPI, blue), Iba-1 (red). Statistical analysis about numbers of Iba-1+ cells (activated microglial cells) in the SNc and CPu. (j) Representative western blot brands of Iba-1 in the midbrain. (k) The density analysis result of Iba-1 western blot in the midbrain. (l-m) Representative captures of immunofluorescence in the colon of nuclei (DAPI, blue), α-syn (green). Statistical analysis of α-syn density in the colon. For (a)to (k), n=5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/0146990bf06bbb1c1d5b9511.png"},{"id":86659816,"identity":"ed57ca8d-27af-443b-922d-292a06f0d0a1","added_by":"auto","created_at":"2025-07-14 10:32:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":808338,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e intervention mitigates the fecal microbiota dysbiosis in rotenone-induced PD mice.\u003c/p\u003e\n\u003cp\u003e(a)Analysis of alpha diversity of gut microbiota by Observed index. (b)Analysis of alpha diversity of gut microbiota by chao index. (c)Analysis of alpha diversity of gut microbiota by ace index. (d)Analysis of alpha diversity of gut microbiota by Shannon index. (e)Analysis of alpha diversity of gut microbiota by Simpson index. (f)Analysis of alpha diversity of gut microbiota by PD whole tree index. (g) Beta diversity based on OUT-JACCARD-ANOISM analysis in different groups. (h)Beta diversity based on unweighted ANOSIM analysis in different groups. (i)Relative abundances of gut microbiota at the genus level in the 3 groups. (j)Relative abundances of 6 significantly altered bacterial genera: \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eOdoribacter\u003c/em\u003e, \u003cem\u003eAlistipes\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e. (k) LEfSe difference analysis. In this Figure, n=6 for each group. Each boxplot represents the median, interquartile range, minimum and maximum values. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/e48a168f91785422c638fa2c.png"},{"id":86659859,"identity":"450ece7b-293a-44af-afe3-3d42c7381d36","added_by":"auto","created_at":"2025-07-14 10:32:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":954647,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e treatment restores tight junction proteins and protects LPS leakage in the rotenone-induced mouse model.\u003c/p\u003e\n\u003cp\u003e(a) Representative captures of immunofluorescence in the colon of ZO-1 and occludin. (b-c)ZO-1 and occludin relative integrity in the colon. (d)Representative western blot brands of ZO-1 and occludin in the colon and midbrain. (e–h)The density analysis result of ZO-1 and occludin western blot in the midbrain and colon. (i) Colon levels of LPS endotoxin. (j)Blood levels of LPS endotoxin. (k) Midbrain levels of LPS endotoxin. (l)Colon levels of LBP. (m) Blood levels of LBP. (n)Midbrain levels of LBP. For (a) to (n), n=5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/90b7fd2b21a88a9d44ebd158.png"},{"id":86659827,"identity":"0cb8fd51-3826-430f-b4b5-fe118d0f70ba","added_by":"auto","created_at":"2025-07-14 10:32:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":585966,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of \u003cem\u003eB.coprocola\u003c/em\u003e treatment on macrophage polarization in the rotenone-induced mouse model.\u003c/p\u003e\n\u003cp\u003e(a-d) Representative contour map of flow cytometry show the M1-type（CD80+）and M2-type macrophage (CD206+) in the gut-blood-brain axis of 3 group. All gates were set using FMO control samples. (e-f) Bar graph summarizing the percentage of M1/M2-type macrophage in the colon. (g,J)Bar graph summarizing the percentage of M1/M2-type macrophage in the blood. (h-i)Bar graph summarizing the percentage of M1/M2-type macrophage in the brain. For (a) to (j), n=4 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/4eba28254f383e608b4b1d1a.png"},{"id":86659821,"identity":"f896abbf-e410-4d66-8e70-efd25b568fca","added_by":"auto","created_at":"2025-07-14 10:32:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":881028,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e treatment inhibits the NLRP3 signaling pathway in the rotenone-induced mouse model.\u003c/p\u003e\n\u003cp\u003e(a) Representative western blot brands of TLR4, MyD88, p-IκBα, NF-κB, NLRP3, and caspase-1 in the midbrain. (b) The density analysis result of TLR4, MyD88, p-IκBα, NF-κB, NLRP3, and caspase-1 western blot in the midbrain. (c) Representative western blot brands of TLR4, MyD88, p-IκBα, NF-κB, NLRP3, and caspase-1 in the colon. (d) The density analysis result of TLR4, MyD88, p-IκBα, NF-κB, NLRP3, and caspase-1 western blot in the colon. (e) Representative western blot brands of IL-1β, IL-6 in the midbrain and colon. (f) The density analysis result of IL-1β, IL-6 western blot in the midbrain and colon. (g) Blood levels of IL-1β. (h) Blood levels of IL-6. For (a) to (h), n=5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/cd962cd4642bc1ed064c8fc9.png"},{"id":86661940,"identity":"e64f4cc3-e837-4340-89e7-745438c22e70","added_by":"auto","created_at":"2025-07-14 10:40:29","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":408744,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolomic analysis of Short-Chain Fatty Acids targeted by \u003cem\u003eBacteroides coprocola\u003c/em\u003e and their correlation with gut microbiota profiling\u003c/p\u003e\n\u003cp\u003e(a) PCA score plot analysis of microbiome profiling in 3 groups. (b) PLS−DA analysis of Metabolomic analysis in 3 groups. (c) Short-chain fatty acid levels in the three experimental groups' feces. (d-e)Short chain fatty acids in the three experimental groups' feces using the Kruskal-Wallis test (Acetic acid; Butyric acid). (f)Correlation heatmap of microbiome profiling and targeted short-chain fatty acid metabolomics. In this Figure, n=6 for each group. Each boxplot represents the median, interquartile range, minimum and maximum values. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 3 groups.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/0dd6da26ccc86748f3943e54.png"},{"id":86659814,"identity":"e4c6c34b-570f-48d5-a6f3-a26a6b6665bc","added_by":"auto","created_at":"2025-07-14 10:32:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":913077,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of acetic acid and butyric acid on BMDM polarization and inflammatory factors release in the LPS model.\u003c/p\u003e\n\u003cp\u003e(a-b) Representative density plot of flow cytometry show the M1-type（CD86+）and M2-type macrophage (CD206+) in the 4 groups. All gates were set using FMO control samples. (c-d)Bar graph summarizing the percentage of M1/M2-type macrophage in the 4 groups. (e-h)IL-1β and IL-6 levels in the cell supernatant by elisa. For (a)to (d), n = 8 for each group. For (e)to (h), n = 5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 4 groups (LPS model=LPS+ATP).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/76770172c5249f0a01d8fb55.png"},{"id":86664936,"identity":"9265a0d6-572d-4125-8bf9-1fef1551561c","added_by":"auto","created_at":"2025-07-14 10:56:29","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1075707,"visible":true,"origin":"","legend":"\u003cp\u003eAcetic acid and butyric acid treatment inhibits the NLRP3 signaling pathway in the LPS model.\u003c/p\u003e\n\u003cp\u003e(a) Representative western blot brands of FFAR2, SIRT1, p-IκBα, NF-κB, NLRP3 and caspase-1 in the 4 groups. (b–m) The density analysis result of FFAR2, SIRT1, p-IκBα, NF-κB, NLRP3 and caspase-1 western blot in the 4 groups. For (a) to (m), n=5 for each group. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 in the 4groups (LPS model=LPS+ATP).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/cd4a2c53aab7b51d3fcbaf4f.png"},{"id":86659819,"identity":"61597011-e5d2-4d3d-be62-a97714bb3428","added_by":"auto","created_at":"2025-07-14 10:32:29","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":2464299,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of the hypothesis model in this study.\u003c/p\u003e\n\u003cp\u003eBriefly, \u003cem\u003eB.coprocola\u003c/em\u003e treatment effectively restored the rotenone-induced dysbiosis of the intestinal flora, reduced the production of pathogenic LPS in the gut, and upregulated the expression of tight junction proteins, thereby preventing the penetration of microbial toxins from the periphery to the brain. In addition, \u003cem\u003eB.coprocola\u003c/em\u003einduces macrophage polarization from pro-inflammatory M1-type to anti-inflammatory M2-type by regulating the gut microbial ecology, and ultimately reduces the amount of inflammatory factors spilled into the peripheral circulation by inhibiting the LPS/TLR4/NLRP3 signaling pathway, which in turn reduces the release of pro-inflammatory factors (e.g., IL-1β and IL-6) and repairs the compromised intestinal barrier. Meanwhile, short-chain fatty acids (e.g., acetic acid and butyric acid) produced by \u003cem\u003eB.coprocola\u003c/em\u003e can act on the FFAR2 receptor on the surface of macrophages, which in turn inhibits the NLRP3 signaling pathway, alleviates the development of chronic inflammation in the gut-brain axis, and ultimately reduces the symptoms of rotenone-induced PD-like pathology.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/9454c82df601b992e94b247c.png"},{"id":103765557,"identity":"64ed1170-de65-429a-9d50-7e4ec6aa597a","added_by":"auto","created_at":"2026-03-02 16:04:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13391253,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/511258d1-d7ff-4421-8c9a-21c25daabce1.pdf"},{"id":86663271,"identity":"c0cb80c5-606d-4b89-b7f1-1afe37d17455","added_by":"auto","created_at":"2025-07-14 10:48:29","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6753532,"visible":true,"origin":"","legend":"","description":"","filename":"westernblotsupplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/8e5788834113bfeb30610f1f.docx"},{"id":86659838,"identity":"c046fee4-7d62-432c-b212-cd22292abfe2","added_by":"auto","created_at":"2025-07-14 10:32:29","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":356767,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1: Methods. Table S1. The culture medium formula for \u003cem\u003eB.coprocola\u003c/em\u003e. Table S2. Paired primers for qPCR. Table S3. Primers for FFAR2 siRNA Smart Pool.\u003c/p\u003e","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/32f0b3a924f3673a87c73eff.docx"},{"id":86661945,"identity":"de592778-1817-49a6-ab94-5b07bd006787","added_by":"auto","created_at":"2025-07-14 10:40:29","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1640714,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2: Figure S1-S2. Effects of \u003cem\u003eB.coprocola\u003c/em\u003etreatment on rotenone-induced PD mice. mRNA expression levels of occludin, ZO-1, NLRP3, IL-1β, IL-6 in the midbrain and colon were detected via qRT-PCR. Figure S3. Representative western blot brands and density analysis of FFAR2-siRNA knockdown efficiency. Figure S4. The metabolomics analysis of short-chain fatty acids targeted by the supernatant of \u003cem\u003eB. coprocola\u003c/em\u003e. Figure S5. The gating strategy of flow cytometry.\u003c/p\u003e","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6875771/v1/aecaed269ac868f5929c3298.docx"}],"financialInterests":"","formattedTitle":"Bacteroides coprocola Protects Dopaminergic Neurons in Rotenone-Induced Parkinson’s disease Mice Model by Modulating Gut Microbiota Dysbiosis and Inhibiting the NLRP3 Signaling Pathway","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson\u0026rsquo;s disease (PD) is a prevalent neurodegenerative disorder, ranking second in prevalence after Alzheimer's disease[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The pathological hallmarks of PD primarily include the selective loss of dopaminergic neurons in the substantia nigra of the midbrain and the formation of Lewy bodies, which are mainly composed of α-synuclein (α-syn)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In recent years, the gut-origin hypothesis of PD has gained attention, with evidence indicating that abnormal α-syn aggregation is significantly detected in the intestines of PD patients during the prodromal stage, even before it appears in the brain[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This suggests that the gut is likely a critical organ contributing to the development of PD.\u003c/p\u003e\u003cp\u003eCurrent clinical studies indicate that PD patients exhibit significant alterations and dysbiosis in their gut microbiota and intestinal microenvironment. For example, an increased abundance of \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, and \u003cem\u003ePrevotella\u003c/em\u003e, as well as a reduction in \u003cem\u003eBlautia\u003c/em\u003e and \u003cem\u003eAnaerostipes\u003c/em\u003e, have been observed[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Dysbiosis of the gut microbiota can lead to chronic inflammatory responses in the intestinal epithelium, disrupting the intestinal barrier and increasing its permeability[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consequently, pro-inflammatory products generated in the gut, such as lipopolysaccharides (LPS) and cytokines, can translocate into systemic circulation through the compromised barrier, triggering systemic chronic inflammation and accelerating the pathological progression of PD[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eBacteroides.coprocola\u003c/em\u003e (\u003cem\u003eB.coprocola\u003c/em\u003e), a gut bacterium belonging to the \u003cem\u003eBacteroides\u003c/em\u003e genus, was first isolated from the feces of healthy individuals by Japanese biologists in 2005. It is a Gram-negative, strictly anaerobic bacterium that primarily metabolizes and produces a range of short-chain fatty acids and amino acids[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Short-chain fatty acids (SCFAs) are key gut microbial metabolites that mediate signaling from the gut microbiota to the host. Increasing evidence suggests that SCFAs play a crucial role in regulating brain function, systemic chronic inflammation, and the integrity of blood-tissue barriers[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In our previous clinical study, a metagenomic analysis of 63 healthy control and 97 PD patients revealed a significant statistical difference in the abundance of \u003cem\u003eB.coprocola\u003c/em\u003e between the two groups (HC\u0026thinsp;\u0026gt;\u0026thinsp;PD)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given the current state of research on \u003cem\u003eB.coprocola\u003c/em\u003e, no studies have explored its potential role in alleviating PD symptoms. Therefore, investigating the effects of \u003cem\u003eB.coprocola\u003c/em\u003e in improving PD symptoms is a novel and pioneering endeavor in this field.\u003c/p\u003e\u003cp\u003eIn this study, by establishing a rotenone-induced PD mouse model that induces gut microbiota dysbiosis, we aim to evaluate whether \u003cem\u003eB.coprocola\u003c/em\u003e treatment can modulate systemic chronic inflammation, thereby ameliorating gut microbiota imbalance PD pathological changes and behavioral symptoms. Furthermore, we seek to elucidate the potential mechanisms underlying \u003cem\u003eB.coprocola\u003c/em\u003e intervention in PD and explore the role of the microbiota-gut-brain axis in the pathogenesis of PD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eAnimals and experimental design\u003c/h2\u003e\u003cp\u003eThe experimental model consisted of 6-week-old male C57BL/6J mice weighing 20\u0026ndash;22 g, obtained from Shanghai Jihui Experimental Animal Breeding Co., Ltd. The mice were housed in the Model Animal Facility of ShanghaiTech University. Ethical approval for animal care and use was granted by the Animal Research Ethics Committee of ShanghaiTech University (Approval Number: 20220802001). All procedures were conducted in compliance with the guidelines of ShanghaiTech University's Institutional Animal Care and Use Committee (IACUC).\u003c/p\u003e\u003cp\u003eA total of mice was randomly assigned to two groups: the control group and the model group. During the first week, the mice were acclimatized to the animal house environment and subjected to handling procedures to familiarize them with the experimenter's operations. Over the following three weeks, the model group received daily intraperitoneal injections of rotenone, while the control group was administered the vehicle. After three weeks, the model group was further divided into two subgroups: the Rotenone group and the \u003cem\u003eB.coprocola\u003c/em\u003e group. From weeks 4 to 6, mice in the \u003cem\u003eB.coprocola\u003c/em\u003e group were treated with \u003cem\u003eB.coprocola\u003c/em\u003e once daily, while the control and Rotenone groups received vehicle administration. All mice were weighed daily throughout the six-week study. At week 6, gastrointestinal function tests and behavioral assessments were conducted. Finally, all mice were sacrificed at week 6 for further analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eChronic rotenone model induction and administration\u003c/h3\u003e\n\u003cp\u003eRotenone (Sigma-Aldrich,USA) was dissolved in 2% DMSO (Beyotime Biotechnology). The fresh rotenone solution was intraperitoneal injected to the mice (2 mg/kg body weight) once a day for 3 weeks[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eB.coprocola\u003c/b\u003e \u003cb\u003eidentification, culture and administration\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e (Mingzhoubio,China) were inoculated in a liquid medium (see in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) with deoxygenation cultivated in 37℃ incubator for 2 days. An anaerobic environment was maintained throughout the cultivation process. For \u003cem\u003eB.coprocola\u003c/em\u003e group, mice were administered with \u003cem\u003eB.coprocola\u003c/em\u003e DSM 17136 dissolved in pbs (10\u003csup\u003e8\u003c/sup\u003e CFU/mice/d) for 3 weeks. The bacterial suspension was then delivered to each recipient mouse via oral gavage within 15 min.\u003c/p\u003e\u003cp\u003eDesign primers for 16s RNA bacterial species identification, amplify the bacterial DNA in vitro through PCR (10102ES03, Yeasen), and send it to Tsingke Biotech Company for sequencing. The V3-V4 regions of the microbial 16S RNA were amplified with the paired primers (forward primer: 5\u0026prime;-CCTACGGGRSGCAGCAG-3\u0026prime;; reverse primer: 5\u0026prime;-GGACTACVVGGGTATCTAATC-3\u0026prime;). Performed sequence identification of the species using the BLAST function on NCBI (National Center for Biotechnology Information).\u003c/p\u003e\n\u003ch3\u003eBehavioral tests\u003c/h3\u003e\n\u003cp\u003eTo assess the motor function of each mouse, 3 behavioral tests were conducted with an interval of 30 min.\u003c/p\u003e\n\u003ch3\u003eRota-Rod test\u003c/h3\u003e\n\u003cp\u003eMice were positioned on the rotarod apparatus, which initiated rotation at an initial velocity of 4 revolutions per minute (rpm) and progressively accelerated to 30 rpm over a duration of 120 seconds. Thereafter, the time elapsed until each mouse lost balance and fell from the rod was automatically captured by the rotarod system. Each mouse underwent the experimental trial three times, separated by an inter-trial interval of 30 minutes.\u003c/p\u003e\n\u003ch3\u003ePole test\u003c/h3\u003e\n\u003cp\u003eA 50-centimeter wooden rod, with a diameter of 3 centimeters and surmounted by a stationary wooden sphere, was positioned within the home cage. Initially, the mice were acclimated to the apparatus to ensure that they would assume a head-bowing posture upon placement on the rod. The mice were positioned atop the rod with their heads oriented upward and subsequently descended to the platform along the length of the rod. The descent time of the mice, as well as the scores assigned to their crawling behavior, were meticulously documented. Three trials were conducted, with each trial separated by a 30-minute intermission.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eBeam-Walking Test\u003c/h2\u003e\u003cp\u003eThe apparatus comprised a wooden beam elevated 70 centimeters above the floor, with dimensions of 1 centimeter in width and 120 centimeters in length, terminating at one end with a dark enclosure. A mesh and foam substrate were positioned beneath the beam to mitigate the risk of injury to the mice. The mice were positioned at one extremity of the beam and permitted to traverse towards the terminal end equipped with the dark enclosure. Following each trial, the wooden beam and the dark enclosure were sanitized with ethanol and subsequently desiccated to eradicate any residual olfactory cues. Each mouse underwent three trials, interspersed with 30-minute\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eIntestinal transit distance and colon length measurement\u003c/h3\u003e\n\u003cp\u003eThirty minutes prior to euthanasia, mice were administered 0.3 mL of a 2.5% Evans blue solution (Sigma-Aldrich) orally, which was dissolved in a 1.5% carboxymethyl cellulose sodium (CMC-Na) vehicle (Sigma-Aldrich) to assess intestinal transit distance. Subsequently, the distance from the pylorus to the most distal point of dye migration was measured and defined as the intestinal transit distance. Furthermore, the length of the colon was determined by measuring the distance from the terminus of the cecum to the anus[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eFecal pellets output\u003c/h3\u003e\n\u003cp\u003eFollowing a 2-hour fasting period, individual mice were transferred from their home cages to clean, transparent polycarbonate cages for an additional 2 hours. Fecal pellets were subsequently collected and enumerated. The wet weight of the fecal pellets was determined by immediate weighing, while the dry weight was ascertained after desiccation at 85\u0026deg;C for 24 hours. The fecal water content was calculated as a percentage based on the discrepancy between the wet and dry weights.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eFlow Cytometry. (Brain/Blood/Colon/BMDM)\u003c/h2\u003e\u003cp\u003eFACS antibodies used for flow cytometry were CD11b-APC, CD45-Percp/Cy5.5, obtained from BioLegend. The CD86-BV421, CD206-PE, F4/80- BV650, CD80-FICT, obtained from BD. For surface marker staining, cells were blocked with Fc Shield (anti-mouse CD16/ CD32, BD) and used Zombie Aqua\u0026trade; Fixable Viability Kit to incubate for 15 min. Then incubated with surface antibodies for 30 min. Next, cells were permeabilized using the eBioscience\u0026trade; Foxp3 kit for 30 min (00-5523-00, thermo). Finally, the cells were stained for intracellular indexes CD206-PE. Between each step, the cells were extensively washed with FACS buffer (PBS, 2% FCS, and 2 mM EDTA). The prepared samples were measured and analyzed using a Cyto FLEX flow cytometer (Beckman Coulter, Brea, CA, USA).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePreparation of single-cell suspensions from mouse brain, blood and colon\u003c/h2\u003e\u003cp\u003eFollowing euthanasia of the mice, fresh brain, blood, and colonic tissues were excised for the preparation of single-cell suspensions, which were subsequently subjected to single-cell analysis utilizing fluorochrome-conjugated antibodies.\u003c/p\u003e\u003cp\u003eFresh peripheral whole blood from mice was collected into ethylenediaminetetraacetic acid (EDTA) anticoagulant tubes. Whole blood samples were subjected to lysis using a lysing solution (BD Biosciences, CA, USA) and subsequently washed with 1\u0026times; phosphate-buffered saline (PBS).\u003c/p\u003e\u003cp\u003eThe brain and colon were harvested, washed, and minced into small fragments. Brain mononuclear cells were isolated using Neural Tissue Dissociation Kits (Miltenyi Biotec, 130-107-677) in accordance with the manufacturer's protocol. Specifically, the ischemic hemisphere of the brain was excised and minced into small pieces. These pieces were transferred into an appropriately sized conical tube, rinsed with cold Hank's balanced salt solution (HBSS), and then centrifuged (300 g, 2 min) at room temperature. After carefully aspirating the supernatant, preheated enzyme mix 1 (37\u0026deg;C, 10 min) from the Neural Tissue Dissociation Kit was added to digest the tissue pieces for 15 min, followed by the addition of preheated enzyme mix 2 (37\u0026deg;C, 10 min) to the tissue sample for an additional 10 min. Subsequently, HBSS was used to resuspend the tissue, and single-cell pellets were isolated by passing through a 30-\u0026micro;m cell strainer.\u003c/p\u003e\u003cp\u003eThe colon tissues were incubated with 8 mL of digestion buffer composed of RPMI-1640 (Thermo Fisher Scientific, Waltham, MA, USA), 5% fetal bovine serum (FBS; Capricorn, Palo Alto, CA, USA), 62.5 \u0026micro;g/mL Liberase (Sigma), and 50 \u0026micro;g/mL DNase I (Roche) at 37\u0026deg;C for 30 min. The cell pellets were then resuspended in 1 mL of 40% Percoll solution and transferred to a prepared 15 mL conical tube containing 4 mL of 40% Percoll solution. Using glass Pasteur pipettes, 2.5 mL of 80% Percoll solution was carefully layered at the bottom of the tubes. Cells were collected from the interface[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eWestern Blot\u003c/h2\u003e\u003cp\u003eThe mice were anesthetized to collect brain and colon tissue or collect successfully differentiated primary macrophages (BMDMs). The total proteins of the samples were extracted by lysis buffer containing RIPA lysis buffer, protease and phosphatase inhibitor cocktail (Beyotime Institute of Biotechnology, Shanghai, China). The protein concentration of the samples was determined using a BCA protein assay kit (Thermo Fisher Scientific, Waltham, MA, USA), and then adjusted to the same level. The protein samples were added to 7.5\u0026ndash;15% SDS-polyacrylamide gel electrophoresis, and sealed using 5% non-fat milk powder or 5% BSA for 1 h before transferring onto a PVDF membrane; then the film was incubated with primary antibodies at 4℃ in 16h and secondary antibody marked by HRP-anti-rabbit (1:5000, Abclonal, AS038) or HRP-anti-mouse (1:5000, Abclonal, AS003) separately. The film was processed with an ECL kit, and the gray values of each protein were recorded and analyzed.\u003c/p\u003e\u003cp\u003eThe primary antibodies included anti-NLRP3 (1:1000, Adipogen,AG-20B-0014-C100), anti-IL-6 (1:1000, Abclonal, A0286), anti-ZO-1 (1: 5000, 21773-1-AP, Proteintech), anti-Occludin (1: 5000, 27260-1-AP, Proteintech), anti-NF-κB (1:5000, HUABIO, ET1603-12), anti- SIRT1 (1:1000, CST, 9475),anti-Caspase-1 (1:1000, CST, 24232), anti-IBA-1 (1:1000, CST, 17198), anti-Phospho-IκBα (1:5000, HUABIO, HA722770), anti-FFAR2 (1:1000, 84544-1-RR, Proteintech), anti-TLR4 (1:1000, Abclonal, A5258), anti-MyD88 (1:1000, CST, 4283), and anti-IL-1β(1:1000, Thermo, P420B). β-actin (1:100000, Abclonal, AC026) was used as the internal control.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eImmunohistochemistry (IHC) and Immunofluorescent (IF) staining\u003c/h2\u003e\u003cp\u003eMice were subjected to anesthesia via intraperitoneal injection of tribromoethanol (100 mg/kg) and subsequently underwent transcardial perfusion with 1\u0026times; phosphate-buffered saline (PBS) followed by a 4% paraformaldehyde solution. Thereafter, the brain and colon tissues were fixed in 4% paraformaldehyde for 48 hours and subsequently dehydrated in a 30% sucrose solution for 72 hours. The brain and colon tissues were then frozen and embedded in optimal cutting temperature (OCT) compound (Sakura Finetek, Torrance, CA, USA, Cat# 4583) prior to sectioning into uniform slices (brain: 40 \u0026micro;m; colon: 12 \u0026micro;m) using a microtome (Leica Microsystems, Wetzlar, Germany). The frozen sections were thawed and mounted onto positively charged slides (ProbeOn Plus; Thermo Fisher Scientific, Waltham, MA, USA) before being stored at \u0026minus;\u0026thinsp;80\u0026deg;C.\u003c/p\u003e\u003cp\u003eFor antigen retrieval from frozen brain sections, the sections were subjected to 20\u0026ndash;30 minutes of microwave treatment (Midea, Foshan, Guangdong, China, Cat# M1-211A) in citrate buffer (pH 6.0) (Servicebio, Cat# G1202). Following this, a blocking solution composed of 10% bovine serum albumin (BSA) (Beyotime) and 0.3% Triton X-100 (Aladdin, Cat# T434386) in PBS was applied for 30 minutes. The sections were then incubated with 3% hydrogen peroxide (H₂O₂) for 15 minutes as part of the immunohistochemistry protocol. Subsequently, the sections were incubated overnight at 4\u0026deg;C with primary antibodies diluted in normal goat serum (2%) (Beyotime, Shanghai, China, Cat# C0265), followed by incubation with biotinylated secondary antibodies and horseradish peroxidase\u0026thinsp;\u0026minus;\u0026thinsp;streptavidin or the appropriate secondary antibodies to detect the corresponding primary antibodies. Nuclei were visualized using DAPI solution. Representative images were captured using a fluorescence microscope (Nikon CSU-W1 Sora 2 Camera (CSU-W1); Olympus Corporation, VS120-S6-W). The number of positive cells was quantified using Image Pro Plus 6.0 software, with each section analyzed based on five randomly selected fields.\u003c/p\u003e\u003cp\u003eThe primary antibodies utilized included anti-Tyrosine Hydroxylase antibody (1:1000, Thermo Fisher Scientific, P21962), anti-α-Synuclein (D37A6) antibody (1:1000, CST, 4179), anti-Iba1/AIF-1 (E4O4W) antibody (1:200, CST, 17198), anti-Occludin antibody (1:1000, Proteintech, 27260-1-AP), and anti-ZO-1 antibody (1:2000, Proteintech, 21773-1-AP). The secondary antibodies employed were Alexa 488-conjugated goat anti-rabbit IgG secondary antibodies (1:1000, Thermo Fisher Scientific, A32723), HRP-anti-rabbit (1:1000, Abclonal, AS038), and Alexa 594-conjugated goat anti-rabbit IgG secondary antibodies (1:1000, Thermo Fisher Scientific, A11005).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eQuantitative Real-time Polymerase Chain Reaction (qRT-PCR)\u003c/h2\u003e\u003cp\u003eTotal RNA was isolated utilizing TRIzol Reagent (Vazyme Biotech, R411-01) and subsequently subjected to reverse transcription via a PrimeScript RT-PCR kit (Abclonal, RK20433). Quantitative real-time PCR (qRT-PCR) was performed using SYBR Premix Ex Taq (Vazyme Biotech, R433) on the QuantStudio 7 platform (Life Technologies). The primers were custom-synthesized by GENEWIZ, China (refer to Table S2). The fluorescence signals corresponding to the target genes were analyzed by the 2\u0026minus;∆∆Ct method for relative quantification, with Actin or GAPDH serving as endogenous reference genes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eEnzyme-linked immunosorbent assay\u003c/h2\u003e\u003cp\u003eThe enzyme-linked immunosorbent assay (ELISA) kits utilized for the quantification of murine interleukin-1β (IL-1β), interleukin-6 (IL-6), lipopolysaccharide (LPS) endotoxin, and lipopolysaccharide-binding protein (LBP) were sourced from Jianglai Industrial Limited by Share Ltd, Shanghai, China (catalog numbers JL20691, JL29644, JL20268, JL18442). The experimental procedures were meticulously executed in strict compliance with the manufacturer\u0026rsquo;s instructions. The concentrations of the target analytes were determined via the generation and analysis of standard protein calibration curves.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eFecal DNA extraction and 16S RNA sequencing\u003c/h2\u003e\u003cp\u003eAt the six-week juncture, mice were randomly designated from each experimental cohort for microbiota sequencing analysis. Each mouse was individually housed in a distinct, sterile, autoclaved cage, and five fresh fecal pellets were collected from each mouse and promptly transferred into a sterile EP tube. All fecal samples were rapidly frozen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent analysis. Genomic DNA was isolated from 200 mg of each fecal sample using the QIAamp DNA Stool Mini Kit (QIAGEN, Hilden, Germany). The quality and integrity of the extracted DNA were subsequently validated through 1.2% agarose gel electrophoresis. For library construction, a two-step polymerase chain reaction (PCR) amplification targeting the V3-V4 hypervariable region of the 16S rRNA gene was employed. The PCR amplification utilized universal primers 357F (5\u0026prime;-ACTCCTACGGRAGGCAGCAG-3\u0026prime;) and 806R (5\u0026prime;-GGACTACHVGGGTWTCTAAT-3\u0026prime;). The thermal cycling parameters were as follows: initial denaturation at 95\u0026deg;C for 3 min, followed by 30 cycles of denaturation at 98\u0026deg;C for 20 s, annealing at 58\u0026deg;C for 15 s, and extension at 72\u0026deg;C for 20 s, with a final extension at 72\u0026deg;C for 5 min. The quantified amplicons were then pooled at equimolar concentrations for Illumina MiSeq sequencing (Illumina, Inc., CA, USA). The entire experimental workflow, encompassing DNA extraction, quality assessment, library construction, and high-throughput sequencing, was executed by TinyGene Bio-Tech (Shanghai, China).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003ePolarization of mouse bone marrow-derived macrophages and SCFAs treatment\u003c/h2\u003e\u003cp\u003eBone marrow cells isolated from femurs of mice were cultured for 7 d in the presence of 20 ng/mL recombinant mouse macrophage colony-stimulating factor (M-CSF, PeproTech) in complete RPMI-1640 medium containing 10% fetal bovine serum (FBS), 10 mM glucose, 2 mM L-glutamine, 100 U/mL penicillin-streptomycin. During cell culture, the morphological changes and growth status of cells were observed with an inverted microscope (Nikon Ti-S) every day.\u003c/p\u003e\u003cp\u003eIn order to further explore the influence of acetate (NaA) and butyrate (NaB) on M1 and M2 polarization, on day 7, M0 macrophages were harvested and then were stimulated for 24 h with 1 \u0026micro;g/ml LPS (Shandong Sparkjade Biotechnology Co., Ltd.) and 1 mM ATP (Sigma) for the generation of M1 macrophages. And then acetate or butyrate was added for 24 h. Groups were as follows: Control group, LPS\u0026thinsp;+\u0026thinsp;ATP group, LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;acetate group (5 mM acetate), LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;butyrate group (0.5 mM butyrate).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eSmall Interfering (si) RNA Transfection\u003c/h2\u003e\u003cp\u003esiRNA targeting FFAR2 or control siRNA were synthesized by GenePharma (see in Table S3). Four individual siRNA sequences were constructed to form the siRNA Smart Pool to reduce the off-target efficiency of siRNAs. Transfections were performed using the Lipofectamine\u0026trade;RNAiMAX reagent (Invitrogen). Cells were treated with 5mM NaA or 0.5mM NaB for 24h after 48h post-transfection and 24h Inflammation modeling. Western Blot confirmed the downregulation of the FFAR2 targeted by siRNA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFecal sample collection and SCFA level measurement (Feces and\u003c/b\u003e \u003cb\u003eB.coprocola\u003c/b\u003e \u003cb\u003ebacterial solution supernatant)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEach mouse was required to provide a fecal sample in the morning using designated fecal collection containers. The containers were immediately placed on ice and subsequently stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further processing. The analysis of short-chain fatty acids (SCFAs) was conducted by TinyGene Bio-Tech (Shanghai) Co., Ltd., following standardized protocols. For each mouse, 400 mg of fresh fecal sample was subjected to SCFA analysis after undergoing grinding and sonication as pretreatment steps. The quantification of individual SCFAs in fecal samples was achieved using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). A calibration curve was constructed with the concentration of the standard as the x-axis and the peak area ratio of the standard to the internal standard as the y-axis. Utilizing these established metabolite calibration curves, quantitative determinations were performed for all samples to ascertain the SCFA concentrations in each fecal sample (R\u0026sup2; \u0026gt;0.99).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted utilizing GraphPad Prism (version 8.01; GraphPad Software Inc., San Diego, CA, USA). One-way analysis of variance (ANOVA) was employed to assess differences among multiple groups. Comparisons of numerical data between two groups were performed using the Mann-Whitney U test or unpaired Student's t-test. For nonparametric analyses, the Kruskal-Wallis H test or Mann-Whitney U test was applied. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or as representative figures. The criterion for statistical significance was established at *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003eintervention ameliorates motor impairments and gastrointestinal disturbances in the rotenone-induced PD mouse model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeight reduction, motor disturbances, and GI impairments frequently manifest in animal models of PD. To assess the protective efficacy of \u003cem\u003eB.coprocola\u003c/em\u003e administration in PD, we developed a chronic PD mouse model via intraperitoneal injection of rotenone over a 3-week period. Subsequently, during the following 3 weeks, mice induced with rotenone were treated with either \u003cem\u003eB.coprocola\u003c/em\u003e or vehicle (Figure.1a). Regarding weight reduction, mice in the rotenone group exhibited significant weight loss during the initial 3-week period of PD model induction. From weeks 4 to 6, treatment with \u003cem\u003eB.coprocola\u003c/em\u003e appeared to mitigate weight loss in rotenone-induced mice, and the rate of weight recovery in the \u003cem\u003eB.coprocola\u003c/em\u003e-treated group was more rapid compared to that of the rotenone-induced PD group (Figure.1b-c).\u003c/p\u003e\n\u003cp\u003eAt the 6-week time point, three distinct behavioral assays were conducted to evaluate the motor functions of mice across different experimental groups. These tests included the Rota-Rod test for assessing motor coordination, the pole test, and the beam walking test for evaluating motor balance (Figure. 1a). Mice subjected to rotenone intoxication exhibited significant motor impairments compared to the control group, as evidenced by reduced latency on the Rota-Rod (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Figure. 1d), prolonged climbing times in the pole test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Figure. 1e), and increased time spent on the beam during the beam walking test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 1f). Conversely, mice treated with \u003cem\u003eB.coprocola\u003c/em\u003e demonstrated substantial improvements in performance on the Rota-Rod test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 1d), the pole test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Figure. 1e), and the beam walking test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Figure. 1f) relative to the rotenone-induced PD group.\u003c/p\u003e\n\u003cp\u003eMoreover, GI dysfunction was assessed in this study. Evans blue dye was utilized to evaluate intestinal transit function in mice, and the length of the colon was measured. Mice in the rotenone-induced PD group exhibited a significant reduction in intestinal transit distance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Figure. 1g-h) and colon length (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Figure. 1i-j) compared to the control group. In contrast, treatment with \u003cem\u003eB.coprocola\u003c/em\u003e significantly ameliorated these GI impairments induced by rotenone (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 1g-j). Fecal pellets were collected to determine the fecal water content percentage. Mice subjected to rotenone exhibited a marked decrease in fecal water content percentage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 1k), which was significantly increased following \u003cem\u003eB.coprocola\u003c/em\u003e administration (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Figure. 1k).\u003c/p\u003e\n\u003cp\u003eIn summary, the data indicate that rotenone intoxication precipitates weight reduction, motor impairments, and GI dysfunction in the PD murine model, while administration of \u003cem\u003eB.coprocola\u003c/em\u003e substantially mitigates these PD-related manifestations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003eadministration mitigates PD-related histological features in the brain and the colon of the rotenone-induced mice model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to elucidate the mechanisms underlying the protective effects of \u003cem\u003eB.coprocola\u003c/em\u003e treatment against GI dysfunction and motor impairments, we examined the histological features in both the brain and the colon through a series of experimental approaches. It is widely recognized that the degeneration of dopaminergic neurons and the aggregation of \u0026alpha;-syn are two key histological indicators of PD[\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. The cell bodies of dopaminergic neurons are situated in the substantia nigra pars compacta (SNc), whereas their axonal projections extend to the caudate-putamen (CPu) region[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eIn the present investigation, the number of TH\u0026thinsp;+\u0026thinsp;cells in the SNc and CPu of mice in the rotenone-induced PD group was significantly diminished compared to that of the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas treatment with \u003cem\u003eB.coprocola\u003c/em\u003e substantially mitigated this neuronal loss (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure. 2a). As another critical histological marker of PD, immunofluorescence staining revealed a marked upregulation of \u0026alpha;-syn expression in the SNc and CPu of mice in the rotenone-PD group (both P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea-c). Conversely, \u003cem\u003eB.coprocola\u003c/em\u003e treatment notably diminished the aggregation of \u0026alpha;-syn in both regions (SNc: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CPu: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure. 2d-f). The accumulation of synuclein protein in the gastrointestinal tract is also a significant pathological feature associated with the progression of PD[\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. Immunofluorescence analysis indicated that the expression of \u0026alpha;-syn in the colon of rotenone-induced mice was significantly elevated compared to that of the control group and the \u003cem\u003eB.coprocola\u003c/em\u003e-treated group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 2l-m).\u003c/p\u003e\n\u003cp\u003eIt has been reported that the activation of microglial cells may play a role in neuroinflammation and dopaminergic neuronal demise in the brain during the progression of PD[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. The expression level of Iba-1 protein can serve as an early indicator of microglial reactivity[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the current study, immunofluorescence staining of the SNc and CPu was performed to assess glial cell reactivity, with Iba-1 serving as a marker for microglia. A significant increase in Iba-1\u0026thinsp;+\u0026thinsp;cells was observed in the SNc and CPu of mice in the rotenone-induced PD group (SNc: P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; CPu: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Figure. 2g-i). However, treatment with \u003cem\u003eB.coprocola\u003c/em\u003e significantly reduced the elevation of Iba-1\u0026thinsp;+\u0026thinsp;cells in the SNc and CPu of treated mice (SNc: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; CPu: P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 2g-i). Western blot analysis of Iba-1 levels in the midbrain also revealed a similar trend (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Figure. 2j-k).\u003c/p\u003e\n\u003cp\u003eCollectively, these results demonstrate that \u003cem\u003eB.coprocola\u003c/em\u003e intervention markedly ameliorates PD-associated histopathological features in both the brain and colon of rotenone-induced murine models. These observations also imply that \u003cem\u003eB.coprocola\u003c/em\u003e treatment may be associated with the modulation of immune cell activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003eintervention ameliorates gut microbiota dysbiosis in the rotenone-induced PD mouse model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrently, an increasing number of studies have identified gut microbiota dysbiosis in both PD patients and PD animal models, highlighting its crucial role in the pathogenesis of PD[\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].To elucidate the mechanisms by which \u003cem\u003eB.coprocola\u003c/em\u003e administration protects the rotenone-induced PD mouse model through modulation of the microbiome community structure, we performed 16S rRNA sequencing on fecal samples from mice in different experimental groups.\u003c/p\u003e\n\u003cp\u003eInitially, \u0026alpha;-diversity analysis was conducted to evaluate the richness and diversity of bacterial taxa. As depicted in Figure. 3a-f, mice in the rotenone-induced PD group demonstrated statistically significant reductions in the Observed species index (P\u0026thinsp;=\u0026thinsp;0.021), Chao1 richness estimator (P\u0026thinsp;=\u0026thinsp;0.0084), ACE richness index (P\u0026thinsp;=\u0026thinsp;0.0102), Shannon diversity index (P\u0026thinsp;=\u0026thinsp;0.0446), and Phylogenetic Diversity (PD) whole tree index (P\u0026thinsp;=\u0026thinsp;0.0133), as well as an increase in the Simpson dominance index (P\u0026thinsp;=\u0026thinsp;0.0504), relative to the control and \u003cem\u003eB.coprocola\u003c/em\u003e-treated groups. These results suggest that \u003cem\u003eB.coprocola\u003c/em\u003e treatment ameliorated the rotenone-induced alterations in microbial abundance and diversity.\u003c/p\u003e\n\u003cp\u003eMoreover, \u0026beta;-diversity analysis unveiled analogous patterns. At week 6, the microbiome community structure of the rotenone-PD group exhibited a significant divergence from that of the control and \u003cem\u003eB.coprocola\u003c/em\u003e groups, as demonstrated by OUT-JACCARD-ANOISM analysis (R\u0026thinsp;=\u0026thinsp;0.1984, P\u0026thinsp;=\u0026thinsp;0.013) and Unweighted-ANOISM analysis (R\u0026thinsp;=\u0026thinsp;0.1086, P\u0026thinsp;=\u0026thinsp;0.089). The microbiome community structures of the control and \u003cem\u003eB.coprocola\u003c/em\u003e groups remained comparable, indicating that \u003cem\u003eB.coprocola\u003c/em\u003e intervention markedly modified the diversity of the gut microbiota (Figure. 3g,h).\u003c/p\u003e\n\u003cp\u003eAdditionally, we performed taxonomic profiling at the genus level across all experimental groups (Figure. 3i). Differential abundance analysis using linear discriminant analysis effect size (LEfSe) identified key microbial taxa with statistically significant intergroup differences (Figure. 3k). Specifically, the relative abundances of \u003cem\u003eParabacteroides, Odoribacter, Alistipes\u003c/em\u003e, and \u003cem\u003eBacteroides\u003c/em\u003e were diminished in the rotenone-PD group compared to the control, whereas \u003cem\u003eAkkermansia\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e were enriched. Notably, intervention with \u003cem\u003eB.coprocola\u003c/em\u003e markedly restored the relative levels of these bacterial genera, including \u003cem\u003eParabacteroides, Odoribacter, Alistipes, Bacteroides, Akkermansia\u003c/em\u003e, and \u003cem\u003eBifidobacterium\u003c/em\u003e (Figure. 3j).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003etreatment restores tight junction proteins expression and inhibit the leakage of microbial toxins in the rotenone-induced mouse model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGut microbial disorders can trigger chronic inflammation of the body\u0026apos;s intestinal and even systemic nature[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Existing evidence indicates that the rotenone-induced PD mouse model manifests compromised BBB and intestinal barrier integrity, concomitant with the generation of inflammatory cytokines and pathogenic lipopolysaccharide (LPS)[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. We initially assessed the expression levels of two major tight junction proteins, namely ZO-1 and occludin, in the midbrain and colon. qRT-PCR and Western blot analyses demonstrated that the expression of ZO-1 and occludin was significantly diminished in the rotenone-induced group relative to the control group, whereas treatment with \u003cem\u003eB.coprocola\u003c/em\u003e substantially restored these reductions (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure. S1 a-d; Figure. 4d-h). Additionally, immunofluorescence staining of the colon revealed that the fluorescence intensities of ZO-1 and occludin were markedly decreased in the rotenone-PD group (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) but significantly increased in the \u003cem\u003eB.coprocola\u003c/em\u003e group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure. 4a-c).\u003c/p\u003e\n\u003cp\u003eThen, we quantified the levels of LPS, LBP in the midbrain, serum(blood) and colon. The ELISA analysis indicated that both LPS and LBP levels were elevated in the rotenone-PD group compared to the control group. In contrast, \u003cem\u003eB.coprocola\u003c/em\u003e administration significantly attenuated these elevations (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Figure. 4i-n).\u003c/p\u003e\n\u003cp\u003eCollectively, these findings suggest that \u003cem\u003eB.coprocola\u003c/em\u003e treatment restores barrier integrity in the rotenone-induced mouse model, protecting microbial toxins leakage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003etreatment affects the polarization response of M1/M2 type macrophages/microglia in the gut-blood-brain axis of the rotenone-induced Parkinson\u0026apos;s disease mouse model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSystemic chronic inflammation activates various types of immune cells in the body to exert immune functions and thus modulate the inflammatory response. Previously, we have demonstrated that \u003cem\u003eB.coprocola\u003c/em\u003e treatment may inhibit rotenone-induced inflammation in the brains of mice with PD by modulating the activation pattern of microglia. To investigate the potential impact of \u003cem\u003eB.coprocola\u003c/em\u003e treatment on myeloid cells regulating systemic chronic inflammation, we measured the number and phenotypes of M1/M2 type macrophages/microglia in the gut-blood-brain axis.\u003c/p\u003e\n\u003cp\u003eMacrophages were defined as CD11b\u0026thinsp;+\u0026thinsp;CD45\u0026thinsp;+\u0026thinsp;F4/80\u0026thinsp;+\u0026thinsp;cells in the colon and blood, and the populations of CD80 (M1 marker) and CD206 (M2 marker) macrophages were gated using FMO controls (Figure. 2S). In the colon, the percentage of CD80\u0026thinsp;+\u0026thinsp;macrophages of the rotenone-PD group mice remarkably increased compared with the control group mice (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while \u003cem\u003eB.coprocola\u003c/em\u003e treatment significantly decreased the CD80\u0026thinsp;+\u0026thinsp;macrophages (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure. 5a, e). In contrast, the percentage of CD206\u0026thinsp;+\u0026thinsp;macrophages of the rotenone-PD group mice remarkably decreased compared with the control group mice (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but markedly elevated in the \u003cem\u003eB.coprocola\u003c/em\u003e group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure. 5a, f).\u003c/p\u003e\n\u003cp\u003eThe preceding data suggest that intestinal barrier damage in the rotenone-induced PD mouse model leads to the leakage of LPS into peripheral tissues. In the blood, the results illustrated that the percentage of CD80\u0026thinsp;+\u0026thinsp;macrophages increased significantly in the rotenone-induced group compared to the control group whereas \u003cem\u003eB.coprocola\u003c/em\u003e treatment markedly decreased the CD80\u0026thinsp;+\u0026thinsp;macrophages (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Figure. 5b, g). But it did not markedly affect the variation of cell counts of CD206\u0026thinsp;+\u0026thinsp;macrophages (Figure. 5c, j).\u003c/p\u003e\n\u003cp\u003eIn the brain, we analyzed the accumulation of infiltrating macrophage and activated microglia, which defined as CD11b+, CD45\u0026thinsp;+\u0026thinsp;high. Flow cytometry analysis revealed that \u003cem\u003eB.coprocola\u003c/em\u003e treatment of rotenone-induced mice strikingly reduced the percentage of infiltrating macrophage and microglia defined as M1-type cells compared with the rotenone-PD group mice. However, \u003cem\u003eB.coprocola\u003c/em\u003e administration did not significantly affect the percentage of M2-type microglia/macrophages in the brain (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure. 5d, h, i).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003eadministration inhibits the NLRP3 signaling pathway to regulate macrophage/microglia polarization in the brain and colon of the rotenone-induced mouse model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNLRP3 signaling pathway is an inflammatory vesicle pathway. Specifically up-regulated LPS can act on the macrophage TLR4 receptor, bind to the key junction protein MyD88, further promote I\u0026kappa;B\u0026alpha; phosphorylation, and release NF-\u0026kappa;B to activate NLRP3 inflammatory vesicles. The activated NLRP3 inflammasome can promote the maturation of Caspase-1, which in turn leads to the maturation and secretion of inflammatory factors, triggering an inflammatory response[\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. This pathway plays a dominant role in the mechanism of microbiota-gut-brain axis[\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eTherefore, we detected the activation status of NLRP3 pathway in the midbrain and the colon using western blot methods. Interestingly, the colon samples were consistent with the results in the midbrain tissues. The western blot results demonstrated a significantly enhanced expression of TLR4, MyD88, p-I\u0026kappa;B\u0026alpha;, NF-\u0026kappa;B, NLRP3, and caspase-1 in the rotenone-PD group relative to the control group. Conversely, the \u003cem\u003eB.coprocola\u003c/em\u003e group expression of TLR4, MyD88, p-I\u0026kappa;B-\u0026alpha;, NF-\u0026kappa;B, NLRP3, and caspase-1 remarkably reduced (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure.6a-d).\u003c/p\u003e\n\u003cp\u003eIn addition, we examined the expression levels of NLRP3 downstream inflammatory factors in the midbrain, colon and blood by Western blotting, qRT-PCR and ELISA. Protein and mRNA expression of IL-1\u0026beta; and IL-6 was significantly increased in mice in the rotenone-PD group. However, \u003cem\u003eB.coprocola\u003c/em\u003e treatment group mice significantly down-regulated the expression of these inflammatory factors (Figure. 6e-h, Figure. S2 a-f). This suggests that \u003cem\u003eB.coprocola\u003c/em\u003e can alleviate PD-like pathology by modulating systemic inflammation in the rotenone-PD mouse model through the NLRP3 signaling pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe acetic acid and butyric acid produced by\u003c/strong\u003e \u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003eare potential active metabolites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the relationship between \u003cem\u003eB.coprocola\u003c/em\u003e and metabolite among the three groups of mice, and to identify potential bioactive metabolites, we first employed PCA analysis and PLS-DA model to perform a multivariate analysis (Figure. 7a, b). The PCA score chart and the PLS-DA model showed that the samples in the three groups was clearly separated, and the clustering effect was relatively obvious. The clustering of the control group and \u003cem\u003eB.coprocola\u003c/em\u003e tends to be more consistent. This further suggests that distinct metabolic principal components may play a key role in influencing the PD progression of rotenone-induced.\u003c/p\u003e\n\u003cp\u003eIn order to identify potential bioactive metabolites, we performed metabolomic analyses targeting SCFAs on feces from three groups of experimental mice, as well as on \u003cem\u003eB.coprocola\u003c/em\u003e bacterial liquid supernatants and found that acetic acid (P\u0026thinsp;=\u0026thinsp;0.022) and butyric acid (P\u0026thinsp;=\u0026thinsp;0.008) exhibited statistically significant differences among the three groups of mice (Figure. 7c-e; Figure.S4). Therefore, it suggested that acetic acid and butyric acid were likely the key metabolites involved in the regulation of the PD pathological progression by the \u003cem\u003eB.coprocola\u003c/em\u003e (Figure. 7c-e).\u003c/p\u003e\n\u003cp\u003eFinally, we also performed a correlation analysis between the differentially abundant bacterial genera and short-chain fatty acids (SCFAs) at the genus level. \u003cem\u003eAlistipes\u003c/em\u003e and \u003cem\u003eOdoribacter\u003c/em\u003e showed a positive correlation with butyric acid, at the same time, \u003cem\u003eAnaeroplasma\u003c/em\u003e and \u003cem\u003eCandidatus_Soleaferrea\u003c/em\u003e exhibited a significant positive correlation with acetic acid. These findings suggest that bacterial genera such as \u003cem\u003eAlistipes\u003c/em\u003e, \u003cem\u003eOdoribacter\u003c/em\u003e and \u003cem\u003eAnaeroplasma\u003c/em\u003e may be closely associated with the metabolism of SCFAs (e.g., butyric acid and acetic acid) and could potentially play a beneficial role in maintaining host gut health. And this similarly suggests that \u003cem\u003eB.coprocola\u003c/em\u003e may regulate the level of SCFAs in the gut by affecting the abundance of other SCFAs-producing genera.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcetic acid and butyric acid produced by\u003c/strong\u003e \u003cstrong\u003eB.coprocola\u003c/strong\u003e \u003cstrong\u003einduce the M1/M2 polarization of primary macrophages to inhibit the NLRP3 signaling pathway and the production of pro-inflammatory factors in the LPS BMDM model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn vivo, we have demonstrated that \u003cem\u003eB.coprocola\u003c/em\u003e gavage can influence the polarization of macrophages/microglia in the gut-blood-brain axis while alleviating the systemic chronic inflammatory response in rotenone-induced mice. Based on these findings, we further investigated whether the potential functional metabolites of \u003cem\u003eB.coprocola\u003c/em\u003e can affect the polarization of macrophages, thereby regulating the inflammatory response. To better reflect in vivo conditions, we selected mouse bone marrow-derived BMDM as the experimental model and induced their differentiation into primary macrophages in vitro.\u003c/p\u003e\n\u003cp\u003eLPS\u0026thinsp;+\u0026thinsp;ATP (LPS: 1 \u0026micro;g/ml, ATP: 1 mm) were used to induce the activation of NLRP3 inflammasome in primary macrophages. M1 macrophages were defined as CD11b/F4/80+/CD80 cells and M2 macrophages were defined as CD11b/F4/80+/CD206 cells, which were gated using FMO controls (Figure.S5). As expected, both acetic acid and butyric acid significantly dowmregulated the percentage of CD86\u0026thinsp;+\u0026thinsp;M1 macrophages. However, only butyric acid was able to upregulate the proportion of CD206\u0026thinsp;+\u0026thinsp;M2 macrophages, and acetic acid did not significantly affect the percentage of M2-type macrophages (Figure. 8a-d).\u003c/p\u003e\n\u003cp\u003eFFAR2 is the key receptor through which acetic acid and butyric acid exert their effects on immune cells. As shown in Figure. S3, after using FFAR2-siRNA 4mix smartpool to interfere with primary macrophages, FFAR2 protein levels were significantly decreased, with the knockdown efficiency reached 75%. Then, we examined the expression of FFAR2 receptor and its downstream deacetylase SIRT1 in primary macrophages in 8 group [LPS\u0026thinsp;+\u0026thinsp;ATP group, LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;FFAR2-siRNA 4mix group, LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;FFAR2-siRNA 4mix\u0026thinsp;+\u0026thinsp;acetate/butyrate group (5 mM acetate, 0.5 mM butyrate), LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;acetate/butyrate group]. The western blot results showed that the expression of FFAR2 and SIRT1 were significantly upregulated in the LPS\u0026thinsp;+\u0026thinsp;ATP\u0026thinsp;+\u0026thinsp;acetate/butyrate group (Figure.9a, c, e, i, l). The upregulated SIRT1 can further act on the downstream p-I\u0026kappa;B\u0026alpha; factor, inhibiting its phosphorylation. Consistent with in vivo results, the protein expression levels of p-I\u0026kappa;B\u0026alpha;, caspase-1, NLRP3 and NF-\u0026kappa;B (Figure. 9a-m), which are dowmstream and upstream priming signal molecule of NLRP3 inflammasome, were significantly decreased after acetic acid and butyric acid treatment (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We also proceeded to measure the downstream inflammatory cytokines including IL-1\u0026beta;, IL-6, and the ELISA results demonstrated that the level of IL-1\u0026beta;, IL-6 LPS reduced in the acetic acid group and the butyric acid group compared to the LPS group (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure.8e-h).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGiven the growing body of research suggesting that gut microbiota dysbiosis, triggered by gastrointestinal disturbances, may be a key factor in the pathogenesis of PD[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In our previous large-scale clinical study, we identified a statistically significant difference in the abundance of \u003cem\u003eB.coprocola\u003c/em\u003e between healthy individuals and PD patients (HC\u0026thinsp;\u0026gt;\u0026thinsp;PD)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To further explore the role of \u003cem\u003eB.coprocola\u003c/em\u003e in PD, we established a rotenone-induced PD mouse model associated with gut microbiota dysbiosis. This model was used to evaluate the protective effects of \u003cem\u003eB.coprocola\u003c/em\u003e treatment in PD and to further investigate the potential mechanisms.\u003c/p\u003e\u003cp\u003eRecent studies have revealed that microbial toxins, such as LPS, can specifically target and regulate immune cells, thereby contributing to systemic chronic inflammation and gut microbiota dysbiosis\u0026mdash;both of which are associated with PD pathology[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, these microbial toxins can directly target neurons in the CNS, inducing neuronal dysfunction, which is closely linked to the pathological progression of PD[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It is currently known that the rotenone-induced PD mouse model can activate the gut-brain toxicity pathway in PD[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, we hypothesize that \u003cem\u003eB.coprocola\u003c/em\u003e supplementation may alleviate systemic chronic inflammation in rotenone-induced PD mice, thereby modulating motor dysfunction and pathological features in PD.\u003c/p\u003e\u003cp\u003eIn this study, we established a PD mouse model by intraperitoneal injection of rotenone, followed by oral gavage treatment with \u003cem\u003eB.coprocola\u003c/em\u003e. The rotenone-induced PD mice exhibited significant phenotypes, including weight loss, gastrointestinal dysfunction, and motor impairments. Three classical behavioral tests used in PD research\u0026mdash;Rota-Rod test, Pole test, and Beam walking test\u0026mdash;were conducted to assess motor function, while GI dysfunction was evaluated by measuring intestinal transit distance and colonic length. Further histological analyses of intestinal and brain tissues revealed that rotenone administration led to a reduction in tyrosine hydroxylase positive cells (dopaminergic neurons) and cytoplasmic accumulation of α-synuclein in the brain, which is consistent with findings from other studies[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Collectively, these results indicate that the chronic rotenone-induced mouse model effectively recapitulates PD progression, exhibiting both GI dysfunction and motor deficits. Notably, \u003cem\u003eB.coprocola\u003c/em\u003e treatment significantly ameliorated PD-related behavioral impairments and pathological changes in rotenone-induced PD mice.\u003c/p\u003e\u003cp\u003eFirstly, it is generally accepted that the balance of gut microbiota maintains well the individual health[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. We provided evidence that rotenone-induced mouse model significantly affects gut microbial composition resulting in disturbed gut ecology. To investigate whether \u003cem\u003eB.coprocola\u003c/em\u003e treatment could ameliorate gut microbiota dysbiosis in PD mice, we performed 16S rRNA sequencing. The results indicated that rotenone-induced significantly disrupted microbial diversity, leading to alterations in α-diversity indices and β-diversity. Notably, \u003cem\u003eB.coprocola\u003c/em\u003e treatment restored microbial diversity and increased the abundance of beneficial genera such as \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eOdoribacter\u003c/em\u003e, and \u003cem\u003eBacteroides\u003c/em\u003e, while reducing the overgrowth of \u003cem\u003eAkkermansia\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e, both of which have been reported to be elevated in PD patients[\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eOdoribacter\u003c/em\u003e and \u003cem\u003eParabacteroides\u003c/em\u003e are major genera of SCFAs producing bacteria in the gut with potent anti-inflammatory and immunomodulatory effects[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moreover, it has been shown that an increase in the abundance of Bifidobacterium species correlates with a decrease in the abundance of SCFA species[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Elevated levels of \u003cem\u003eBifidobacterium\u003c/em\u003e and a loss of SCFA-producing bacteria have also been observed in other inflammatory disorders of the gut[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A positive correlation between elevated \u003cem\u003eAkkermansia\u003c/em\u003e abundance and the development of PD has been noted in several previous studies[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and the same trend was observed in our study. However, other studies have also pointed out that Akkermansia spp. have a tendency to decrease in abundance in some senescent mice and ALS model mice, and that gavage of \u003cem\u003eAkkermansia Muciniphila\u003c/em\u003e has a protective effect on ALS model mice[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Thus, the exact role of \u003cem\u003eAkkermansia\u003c/em\u003e in pathogenesis of neurodegenerative diseases needs further exploration. Our findings suggests that \u003cem\u003eB.coprocola\u003c/em\u003e may influence the pathologic development of PD by modulating the composition of the gut microbiota.\u003c/p\u003e\u003cp\u003eSystemic chronic inflammation is a key factor in the pathogenesis of PD[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Both PD patients and animal models exhibit increased intestinal permeability, which allows microbial toxins to enter systemic circulation, thereby exacerbating neuroinflammation[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. We examined the levels of LPS and LBP in the gut-blood-brain axis, and found that the levels of LPS and LBP in the gut, blood, and brain were significantly reduced in PD mice after \u003cem\u003eB.coprocola\u003c/em\u003e treatment. Therefore, we hypothesize that \u003cem\u003eB.coprocola\u003c/em\u003e may maintain the intestinal barrier by up-regulating the expression of tight junction proteins, improve the structure of the intestinal microbiota, increase the number of beneficial bacteria in the intestinal tract, and improve the balance of the intestinal flora, which in turn reduces the production of LPS in the intestinal tract. There are many studies pointing out that probiotic therapy can play an anti-inflammatory role by regulating the intestinal flora. For example, \u003cem\u003eLactobacillus reuteri\u003c/em\u003e can restore the gut microbial composition of the Cis rat model and ameliorate intestinal inflammation through remodeling of the gut microbiota[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. \u003cem\u003eP.distasonis\u003c/em\u003e reduces insulin resistance by repairing the intestinal barrier and improving the anti-inflammatory effects of gut microbiota dysbiosis[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. \u003cem\u003eLactiplantibacillus pentosus\u003c/em\u003e prevents the inflammatory response in DSS-induced colitis mice by modulating the gut microbiota and serum metabolite levels[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Taken together, the studies have responded to the ability of probiotic therapy to influence the composition of gut microbes and build a healthier gut microbial ecology. In this study, \u003cem\u003eB.coprocola\u003c/em\u003e treatment restored the expression of tight junction proteins (ZO-1 and occludin) in the colon and midbrain, indicating enhanced integrity of the intestinal barrier and BBB. This suggests that \u003cem\u003eB.coprocola\u003c/em\u003e is able to maintain the intestinal barrier function, reduce the permeability of the intestinal barrier, and prevent the leakage of biotin toxins, such as LPS, from the intestines to the periphery triggering further immune responses.\u003c/p\u003e\u003cp\u003eLPS in the intestine induces macrophages to polarize towards the M1 pro-inflammatory type, and polarized M1 macrophages trigger an inflammatory response and release inflammatory factors [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].The release of inflammatory factors is closely linked to the activation state of macrophages. M1 macrophages/microglia exhibit pro-inflammatory properties, whereas M2 macrophages/microglia promote tissue repair and anti-inflammatory responses[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. We then further explored the proportion of M1 and M2 types of macrophages in the gut-blood-brain axis. Our flow cytometry results showed that \u003cem\u003eB.coprocola\u003c/em\u003e treatment reduced the proportion of CD80⁺ M1 macrophages in the colon, blood, and brain. However, an increased proportion of CD206⁺ M2 macrophages was only observed in the colon. Studies of other gut microbes affecting macrophage polarization have also reported that \u003cem\u003eLactobacilli\u003c/em\u003e can alleviate the inflammatory response in a mouse model of IBD by modulating macrophage polarization [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. \u003cem\u003eC.butyricum\u003c/em\u003e-derived EVs modulate disordered intestinal flora and polarize macrophages toward the M2 type in UC mice[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. So intestinal flora and macrophage polarization responses are closely linked. Then, we conclude that \u003cem\u003eB.coprocola\u003c/em\u003e treatment mainly affects the polarization of M1-type macrophages to M2-type macrophages by reducing the amount of LPS in the intestine, thus controlling the inflammatory response in the intestine and preventing inflammatory factors from leaking or transmitting signals to the periphery.\u003c/p\u003e\u003cp\u003eTo further elucidate the molecular mechanisms underlying the therapeutic effects of \u003cem\u003eB.coprocola\u003c/em\u003e, we focused on the systemic chronic inflammation induced by rotenone. Rotenone-induced PD mice models elicit systemic chronic inflammation and induce the formation of the NLRP3 inflammasome[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Additionally, research has indicated that neuronal NLRP3 is a parkin substrate that drives neurodegeneration in PD[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. So the NLRP3 signaling pathway is closely related to the development of PD. Our study investigated the expression of this signaling pathway. First, we examined the expression of NLRP3 protein and mRNA in the colon and midbrain of three groups of experimental mice and found that NLRP3 expression was downregulated in \u003cem\u003eB.coprocola\u003c/em\u003e treatment PD mice. LPS can act on the TLR4 receptor, recruit the key junction protein MyD88, and transmit signals downstream to prompt the phosphorylation of IκB, and the isolated NF-κB enters the nucleus, further up-regulates the expression of NLRP3, and activates the cleavage of inflammatory factors by caspase-1, which is converted into mature inflammatory factors to further promote the development of inflammation[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Our results demonstrated that \u003cem\u003eB.coprocola\u003c/em\u003e treatment downregulated the expression of key components in the NLRP3 pathway, including TLR4, MyD88, p-IκBα, caspase-1, and NF-κB. This, in turn, downregulated the expression of pro-inflammatory factors IL-1β and IL-6.\u003c/p\u003e\u003cp\u003eSCFAs are the main metabolites produced by intestinal flora fermenting dietary fiber, among which acetic acid, propionic acid and butyric acid are the three most abundant[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. On the one hand, they can serve as energy substrates for cells and regulate energy homeostasis, and on the other hand, they can regulate the differentiation of immune cells to inhibit the occurrence of neuroinflammation and thus maintain the intestinal barrier function[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Butyrate is critical for the maintenance of intestinal homeostasis and capable of promoting iTreg generation by up-regulating histone acetylation for gene expression as an HDAC inhibitor[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Microbiota-derived acetate exerts antihypertensive effects by modulating microglia and astrocytes and inhibiting neuroinflammation and sympathetic output[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In our study, SCFAs metabolomic analysis revealed that acetic acid and butyric acid are the key metabolites produced by \u003cem\u003eB.coprocola\u003c/em\u003e. We similarly performed metabolic analysis of targeted SCFAs in three groups of mice and found that acetic acid and butyric acid were statistically different between the three groups. We then further explored the effects of acetic acid and butyric acid on primary macrophage polarization in vitro, and established a primary macrophage LPS model to investigate whether acetic acid and butyric acid could ameliorate inflammation through the NLRP3 signaling pathway. In vitro experiments demonstrated that acetic acid and butyric acid significantly influenced macrophage polarization by reducing the proportion of M1-like CD86⁺ macrophages, while butyric acid not acetic acid specifically promoted the proportion of M2-like CD206⁺ macrophages. In addition, binding of acetic acid and butyric acid to the FFAR2 receptor similarly affected NF-κB inhibition of the NLRP3 signaling pathway and downregulated the release of inflammatory cytokines. These results further support the conclusion that \u003cem\u003eB.coprocola\u003c/em\u003e-derived acetic acid and butyric acid may regulate macrophage polarization and suppress the NLRP3 signaling pathway, thereby alleviating systemic chronic inflammation in PD mice and improving PD-like symptoms.\u003c/p\u003e\u003cp\u003eOur study for the first time reveals the protective effects of \u003cem\u003eB.coprocola\u003c/em\u003e treatment in a chronic rotenone-induced PD mouse model. \u003cem\u003eB.coprocola\u003c/em\u003e treatment alleviates PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and barrier dysfunction. Among these, regulating macrophage polarization and inhibiting the NLRP3 signaling pathway to alleviate systemic chronic inflammation may be key molecular mechanisms underlying the \u003cem\u003eB.coprocola\u003c/em\u003e intervention in PD. Finally, our study highlights the importance of the gut-brain axis in the pathogenesis of PD and suggests that \u003cem\u003eB.coprocola\u003c/em\u003e could be a promising microbial intervention strategy for PD treatment.\u003c/p\u003e\u003cp\u003eAlthough the findings of this study are encouraging, several limitations warrant further investigation. First, while this study demonstrated the protective effects of \u003cem\u003eB.coprocola\u003c/em\u003e in the rotenone-induced PD model, future research should explore its efficacy in other PD models.\u003c/p\u003e\u003cp\u003eAdditionally, we have shown that \u003cem\u003eB.coprocola\u003c/em\u003e modulates PD pathology by regulating anti-inflammatory pathways in macrophages and shaping gut microbiota composition. However, the role of other immune cells has not been extensively investigated. Future studies will aim to elucidate the direct effects of \u003cem\u003eB.coprocola\u003c/em\u003e on various immune cell populations. Finally, clinical translation remains a significant challenge. Further validation through additional animal models, such as primate PD models, is necessary to confirm the therapeutic potential of \u003cem\u003eB.coprocola\u003c/em\u003e in PD.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study for the first time reveals the protective effects of \u003cem\u003eB.coprocola\u003c/em\u003e treatment in a chronic rotenone-induced PD mouse model. \u003cem\u003eB.coprocola\u003c/em\u003e treatment alleviates PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and barrier dysfunction. Among these, inhibiting the NLRP3 signaling pathway to alleviate systemic chronic inflammation may be key molecular mechanisms underlying the \u003cem\u003eB.coprocola\u003c/em\u003e intervention in PD. Finally, our study highlights the importance of the gut-brain axis in the pathogenesis of PD and suggests that \u003cem\u003eB.coprocola\u003c/em\u003e could be a promising microbial intervention strategy for PD treatment (Figure. 10).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Parkinson\u0026rsquo;s disease\u003c/p\u003e\n\u003cp\u003eNF-\u0026kappa;B \u0026nbsp; \u0026nbsp; \u0026nbsp; Nuclear factor-\u0026kappa;B\u003c/p\u003e\n\u003cp\u003eNLRP3 \u0026nbsp; \u0026nbsp; \u0026nbsp; NOD-, LRR- and pyrin domain-containing 3\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e\u003cem\u003e\u0026nbsp;Bacteroides coprocola\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Wild type\u003c/p\u003e\n\u003cp\u003eIL-1\u0026beta; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Interleukin 1\u0026beta;\u003c/p\u003e\n\u003cp\u003eIba1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ionized calcium-binding adapter molecule 1\u003c/p\u003e\n\u003cp\u003eCNS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Central nervous system\u003c/p\u003e\n\u003cp\u003eTH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Tyrosine hydroxylase\u003c/p\u003e\n\u003cp\u003eLPS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lipopolysaccharides\u003c/p\u003e\n\u003cp\u003eLBP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lipopolysaccharide-binding protein\u003c/p\u003e\n\u003cp\u003eIL-6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Interleukin 6\u003c/p\u003e\n\u003cp\u003eSCFA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Short‑chain fatty acid\u003c/p\u003e\n\u003cp\u003eBMDM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Bone marrow-derived macrophages\u003c/p\u003e\n\u003cp\u003e\u0026alpha;-syn\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026alpha;-synuclein\u003c/p\u003e\n\u003cp\u003eHC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Healthy Control\u003c/p\u003e\n\u003cp\u003eDMSO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Dimethyl sulfoxide\u003c/p\u003e\n\u003cp\u003eCMC-Na\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Carboxymethyl cellulose sodium\u003c/p\u003e\n\u003cp\u003eEDTA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ethylenediaminetetraacetic acid\u003c/p\u003e\n\u003cp\u003eHBSS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Hank\u0026apos;s balanced salt solution\u003c/p\u003e\n\u003cp\u003eFBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Fetal bovine serum\u003c/p\u003e\n\u003cp\u003eNaA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Acetate\u003c/p\u003e\n\u003cp\u003eNaB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Butyrate\u003c/p\u003e\n\u003cp\u003eATP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Adenosine 5\u0026apos;-triphosphate\u003c/p\u003e\n\u003cp\u003eSNc\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Substantia nigra pars compacta\u003c/p\u003e\n\u003cp\u003eCPu\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Caudate-putamen\u003c/p\u003e\n\u003cp\u003eLEfSe\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Linear discriminant analysis effect size\u003c/p\u003e\n\u003cp\u003eTLR4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Toll-like receptors 4\u003c/p\u003e\n\u003cp\u003eMyD88\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Myeloid differentiation primary response protein 88\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ep-I\u0026kappa;B\u0026alpha;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;NF-kappa-B inhibitor alpha Phosphorylation\u003c/p\u003e\n\u003cp\u003ePCA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Principal components analysis\u003c/p\u003e\n\u003cp\u003ePLS-DA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Partial Least Squares Discriminant Analysis\u003c/p\u003e\n\u003cp\u003eFFAR2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Free fatty acid receptor 2\u003c/p\u003e\n\u003cp\u003eSIRT1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sirtuin type 1\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eSupplementary Information\u003c/p\u003e\n\u003cp\u003eThe online version contains supplementary material available at XXX\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe acknowledge the contributions of all members of Professor Chen Shengdi\u0026rsquo;s laboratory at ShanghaiTech University. We are grateful for the support with flow cytometry provided by the Discovery Technology Platform at the Institute for Immunology and Chemical Biology. We also thank the Molecular and Cellular Platform and the Clinical Research Center at ShanghaiTech University for their support with microscopy and other instrumentation. Additionally, we appreciate the generous assistance with the anaerobic glove box provided by Professor Zhu Huanhu\u0026rsquo;s group at ShanghaiTech University.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLZX, NJB, LYM and ZJQ performed experiments. LZX, HMX, CZL and YSS analyzed data. LZX, CSD and TYY designed the studies. LZX, CSD and TYY performed the research and analyzed the animal data. LZX wrote the manuscript and CSD and TYY revised the manuscript. All authors read and checked this manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China, (82171401), Shanghai Municipal Science and Technology Major Project, No. 2018SHZDZX05 and Peak Disciplines (Type IV) of Institutions of Higher Learning in Shanghai.\u003c/p\u003e\n\u003cp\u003eAvailability of data and material\u003c/p\u003e\n\u003cp\u003eThe 16S rRNA sequencing data have been deposited in the NCBI BioProject database\u0026nbsp;https://www.ncbi.nlm.nih.gov/sra/PRJNA1267990. Other data relevant to the study are included in the article or uploaded as supplementary files.\u0026nbsp;The data are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eDeclarations\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe animal experiment was approved by the Institutional Animal Care and Use Committee (IACUC) of ShanghaiTech University (IACUC No: 20220503001).\u003c/p\u003e\n\u003cp\u003eConsent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eDisclosure statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the author(s).\u003c/p\u003e\n\u003cp\u003eAuthor details\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eLab for Translational Research of Neurodegenerative Diseases, Shanghai Institute for Advanced Immunochemical Studies (SIAIS), Shanghai Tech University, Shanghai, 201210 China. \u003csup\u003e2\u003c/sup\u003eDepartment and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025 China. \u003csup\u003e3\u003c/sup\u003eShanghai Institute of Stem Cell Research and Clinical Translation, Shanghai 200120, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhu J, Cui Y, Zhang J, Yan R, Su D, Zhao D, et al. 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J Neuroinflammation. 2024;21:101.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-neurodegeneration","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tneu","sideBox":"Learn more about [Translational Neurodegeneration](http://translationalneurodegeneration.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/tneu/default.aspx","title":"Translational Neurodegeneration","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, Gut microbiota, NLRP3 signaling pathway, Macrophage polarization","lastPublishedDoi":"10.21203/rs.3.rs-6875771/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6875771/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground:\u003c/p\u003e\n\u003cp\u003eParkinson’s disease (PD) is a prevalent neurodegenerative disease and its pathogenesis is still unclear. Emerging evidence supports the gut-origin hypothesis, highlighting gut microbiota dysbiosis as a contributing factor in PD pathogenesis. Alterations in gut microbial composition influence barrier integrity and systemic chronic inflammation via the microbiota-gut-brain axis. \u003cem\u003eBacteroides coprocola (B.coprocola)\u003c/em\u003e, a gut bacterium producing short-chain fatty acids (SCFAs), is significantly reduced in PD patients from our previous clinical study. This study investigates \u003cem\u003eB.coprocola\u003c/em\u003e’s potential in ameliorating PD pathology using a rotenone-induced PD mouse model. By evaluating its impact on gut microbiota balance, inflammation, and macrophage polarization, we aim to elucidate its therapeutic role and underlying mechanisms in PD progression.\u003c/p\u003e\n\u003cp\u003eMethods:\u003c/p\u003e\n\u003cp\u003eIn this study, the rotenone-induced PD mouse model was established. After three weeks of rotenone administration, PD mice underwent continuous oral gavage with \u003cem\u003eB.coprocola\u003c/em\u003e for an additional three weeks. Motor function was assessed using the Rota-Rod test, Pole test, and Beam walking test. Furthermore, 16S rRNA high-throughput sequencing and targeted SCFAs metabolomics were employed to analyze gut microbiota composition and SCFAs levels across groups. Additionally, flow cytometry, immunofluorescence, qPCR, and Western blot techniques were utilized to examine alterations in midbrain and intestinal structures, NLRP3 inflammasome pathway activation, and macrophage polarization.\u003c/p\u003e\n\u003cp\u003eResults:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eB.coprocola\u003c/em\u003e treatment could alleviate PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and BBB and intestinal barrier permeability in the rotenone-induced PD mouse model. Additionally, \u003cem\u003eB.coprocola\u003c/em\u003e inhibits the NLRP3 signaling pathway by modulating gut microbiota dysbiosis and macrophage polarization, ultimately alleviating systemic chronic inflammation and PD-like pathological symptoms in rotenone-induced mice.\u003c/p\u003e\n\u003cp\u003eConclusions:\u003c/p\u003e\n\u003cp\u003eThe current findings suggest that \u003cem\u003eB.coprocola\u003c/em\u003e can regulate gut microbiota dysbiosis in rotenone-induced PD mice and influence macrophage polarization, which is associated with the inhibition of the NLRP3 inflammasome signaling pathway.\u003c/p\u003e","manuscriptTitle":"Bacteroides coprocola Protects Dopaminergic Neurons in Rotenone-Induced Parkinson’s disease Mice Model by Modulating Gut Microbiota Dysbiosis and Inhibiting the NLRP3 Signaling Pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 10:32:23","doi":"10.21203/rs.3.rs-6875771/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-07-14T02:47:20+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-09T02:53:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-30T11:29:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Neurodegeneration","date":"2025-06-28T03:06:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-neurodegeneration","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tneu","sideBox":"Learn more about [Translational Neurodegeneration](http://translationalneurodegeneration.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/tneu/default.aspx","title":"Translational Neurodegeneration","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d5b2ae87-9fa3-4698-8141-2f94991762d8","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:01:37+00:00","versionOfRecord":{"articleIdentity":"rs-6875771","link":"https://doi.org/10.1186/s40035-026-00542-8","journal":{"identity":"translational-neurodegeneration","isVorOnly":false,"title":"Translational Neurodegeneration"},"publishedOn":"2026-02-28 15:58:29","publishedOnDateReadable":"February 28th, 2026"},"versionCreatedAt":"2025-07-14 10:32:23","video":"","vorDoi":"10.1186/s40035-026-00542-8","vorDoiUrl":"https://doi.org/10.1186/s40035-026-00542-8","workflowStages":[]},"version":"v1","identity":"rs-6875771","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6875771","identity":"rs-6875771","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}