Bacteroides coprocola protects dopaminergic neurons in rotenone-induced Parkinson’s disease mouse model by modulating gut microbiota dysbiosis and inhibiting the NLRP3 signaling pathway
Zixian Liu, Jiabei Nie, Yimei Li, Maoxin Huang, Ziluo Chen, Shushang Yu, Jiaqi Zheng, Yuyan Tan, Shengdi Chen
TL;DR
A gut bacterium called Bacteroides coprocola helps protect brain cells in a mouse model of Parkinson’s disease by improving gut health and reducing inflammation.
Contribution
This study demonstrates that B. coprocola alleviates Parkinson’s disease pathology by modulating gut microbiota and inhibiting the NLRP3 signaling pathway.
Findings
B. coprocola treatment improved motor deficits and reduced neuroinflammation in a mouse model of Parkinson’s disease.
The bacterium inhibited the NLRP3 inflammasome pathway and modulated macrophage polarization.
Acetate and butyrate from B. coprocola suppressed inflammation via FFAR2/3 receptors.
Abstract
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. Our previous clinical study showed that Bacteroides coprocola (B. coprocola), a gut bacterium producing short-chain fatty acids (SCFAs), was significantly reduced in PD patients. This study was aimed to investigate the potential of B. coprocola in ameliorating PD pathology and explore the underlying mechanisms in a rotenone-induced PD mouse model. The rotenone-induced PD mouse model was treated by orally administering B. coprocola for three weeks. Immunofluorescence, Western blotting, flow cytometry, 16S rRNA sequencing, and metabolomics were performed to assess midbrain and intestinal changes, NLRP3 inflammasome activation, macrophage…
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Taxonomy
TopicsGut microbiota and health · Parkinson's Disease Mechanisms and Treatments · Tryptophan and brain disorders
Introduction
Parkinson’s disease (PD) is the second most common neurodegenerative disorder, only next to Alzheimer’s disease [1]. The pathological hallmarks of PD primarily include selective loss of dopaminergic neurons in the substantia nigra of the midbrain and the formation of Lewy bodies mainly composed of α-synuclein (α-syn) [2]. In recent years, the gut-origin hypothesis of PD has gained attention, with evidence of abnormal α-syn aggregation 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 (SCFAs) and amino acids [11]. 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 functions, systemic chronic inflammation, and the integrity of blood-tissue barriers [12]. In our previous clinical study, metagenomic analysis of 63 healthy control subjects and 97 PD patients revealed a significantly reduced abundance of B. coprocola in PD patients compared to healthy controls [13]. However, 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 with gut microbiota dysbiosis, we aimed to evaluate whether B. coprocola treatment can modulate systemic chronic inflammation, thereby ameliorating PD pathological changes and behavioral symptoms related with the gut microbiota imbalance. Furthermore, we sought 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
Six-week-old male C57BL/6 J mice weighing 20–22 g, obtained from Shanghai Jihui Experimental Animal Breeding Co., Ltd, 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). The experimental mice were of the same batch, sex, and age, and were acclimated in SPF conditions with consistent feed and housing density. Mice were randomly assigned to groups and cages were rotated periodically. Routine management and procedures were standardized. The study employed a blinded approach with fixed testing times to minimize environmental and subjective influences.
Mice were randomly assigned to two groups: the control group and the model group. During the first week, the mice were acclimatized to the animal housing environment and subjected to handling procedures for familiarization to the experimenter’s operations. Over the following three weeks, the model group received daily intraperitoneal injections of rotenone, while the control group received vehicle (2% dimethyl sulfoxide in PBS). 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.
Rotenone model induction and administration
Rotenone (Sigma-Aldrich, Cas-83–79-4, St. Louis, MO) was dissolved in 2% dimethyl sulfoxide (Beyotime, ST038, Shanghai, China). The fresh rotenone solution was intraperitoneal injected at 2 mg/kg once a day for 3 weeks[14].
B. coprocola identification, culture and administration
B. coprocola (Mingzhoubio, Ningbo, China) were inoculated in a liquid medium (Table S1) with deoxygenation and cultivated in a 37 °C incubator for 2 days. An anaerobic environment was maintained throughout the cultivation process. For the B. coprocola group, B. coprocola was dissolved in PBS (10^8^ CFU/mouse per day), and the bacterial suspension was then delivered to each mouse via oral gavage within 15 min. The administration was made once a day, for 3 weeks.
Primers for the 16S rRNA of B. coprocola were designed, the bacterial DNA was amplified in vitro through PCR (10102ES03, Yeasen, Shanghai, China), and products were sequenced by Tsingke Biotech Company. 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′). Sequence identification of the species was performed using the BLAST function on National Center for Biotechnology Information (NCBI).
Behavioral tests
Rota-rod test
Each mouse was positioned on the rotarod apparatus, which rotated at an initial velocity of 4 revolutions per minute (rpm) and progressively accelerated to 30 rpm over a duration of 120 s. Thereafter, the latency of the animal to lose balance and fall from the rod was automatically captured by the rotarod system. Each mouse underwent three trials, with 30-min intervals.
Pole test
A 50-cm vertical wooden pole (diameter 3 cm) with a stationary wooden ball on the top, was positioned within the home cage. Initially, the mice were acclimated to the apparatus to ensure that they would adopt a head-bowing posture upon placement on the pole. Each mouse was positioned at the top of the pole with head oriented upward and subsequently descended to the platform along the length of the pole. The total time to descend to the floor, as well as the scores assigned to their crawling behavior, were recorded. The test was repeated for 3 times, with a 30 min interval between each trial.
Beam-walking test
The apparatus comprised a wooden beam (120 cm long and 1 cm wide) elevated 70 cm above the floor, 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. Each mouse was positioned at one end of the beam and permitted to walk across the beam to 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, with 30-min intervals.
The three different behavioral tests were conducted with an interval of 30 min.
Intestinal transit distance and colon length measurement
Thirty minutes prior to euthanasia, mice were orally administered with 0.3 mL of a 2.5% Evans blue solution (Sigma-Aldrich, Cas-314-13-6, Darmstadt, Germany), which was dissolved in a 1.5% carboxymethyl cellulose sodium vehicle (Sigma-Aldrich, Cas-9004-32-4, Darmstadt, Germany) to assess intestinal transit distance. Mice were subjected to anesthesia via intraperitoneal injection of tribromoethanol (100 mg/kg) and subsequently underwent transcardial perfusion with 1 × PBS followed by a 4% paraformaldehyde solution. Subsequently, intestinal transit distance, defined as the distance from the pylorus to the most distal point of dye migration, was measured. 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 h fasting period, each mouse was transferred from its home cage to a clean, transparent polycarbonate cage and stayed there for an additional 2 h. Fecal pellets were subsequently collected and enumerated. The fecal pellets were immediately weighed to obtain wet weight, and weighed after desiccation at 85 °C for 24 h to obtain dry weight. The fecal water content was calculated as a percentage based on the discrepancy between the wet and dry weights.
Flow cytometry (brain/blood/colon/BMDMs)
Antibodies used for flow cytometry were CD11b-APC (BioLegend, Cat-101212, San Diego, CA) and CD45-Percp/Cy5.5 (BioLegend, Cat-103132) obtained from BioLegend, CD86-BV421 (BD, Cat-564198, San Jose, CA), CD206-PE (BD, Cat-568273), F4/80-BV650 (BD, Cat-743282) and CD80-FICT (BD, Cat-561954) obtained from BD. For surface marker staining, cells were blocked with Fc Shield (anti-mouse CD16/CD32, BD, Cat-553141) and stained with the Zombie Aqua™ Fixable Viability Kit (BioLegend, Cat-423101) for 15 min to discriminate live from dead cells. Then the cells were washed and incubated with a cocktail of fluorochrome-conjugated antibodies against surface markers for 30 min at 4 °C in the dark. Next, the cells were permeabilized using the eBioscience™ Foxp3 kit for 30 min (Thermo Fisher Scientific, Cat-00-5523-00, Waltham, MA). Finally, the cells were stained for intracellular indexes CD206-PE. Between each step, the cells were extensively washed with FACS buffer (2% FBS and 2 mM ethylenediaminetetraacetic acid [EDTA] in PBS). The prepared samples were measured and analyzed using a Cyto FLEX flow cytometer (Beckman Coulter, Brea, CA).
Preparation of single-cell suspensions from mouse brain, blood and colon
Following mouse euthanasia, fresh brain, blood, and colonic tissues were collected for preparation of single-cell suspensions, which were subsequently subjected to single-cell analysis utilizing fluorochrome-conjugated antibodies.
The fresh peripheral whole blood was collected into EDTA anticoagulant tubes. The whole blood samples were subjected to lysis using a lysing solution (BD, Cat-555899) and subsequently washed with 1 × PBS.
The brain and colon tissues were harvested, washed, and minced into small pieces. Brain mononuclear cells were isolated using the Neural Tissue Dissociation Kit (Miltenyi Biotec, 130–107-677, Bergisch Gladbach, Germany) and pepsin (MedChemExpress, HY-P1635, Shanghai, China) according to the manufacturers’ protocol. Briefly, the 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 addition of preheated enzyme mix 2 (37 °C, 10 min) to the tissue sample for an additional 10 min. Subsequently, HBSS was added 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, 11875093), 5% fetal bovine serum (FBS; Capricorn, FBS-26A, Palo Alto, CA), 62.5 μg/mL Liberase (Sigma-Aldrich, Cat-5401020001, Darmstadt, Germany), and 50 μg/mL DNase I (Roche, Cat-11284932001, Mannheim, Germany) at 37 °C for 30 min. The cell pellets were then resuspended in 1 mL of 40% Percoll (40501ES60, Yeasen) solution and transferred to a 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 tube. Cells were collected from the interface [16].
Western blotting
Total proteins were extracted from brain or colon tissue or from bone marrow-derived macrophages (BMDMs) using RIPA lysis buffer containing a cocktail of protease and phosphatase inhibitors (Beyotime, P1046, Shanghai, China). Protein concentrations were determined using a BCA protein assay kit (Thermo Fisher Scientific, A55860). Proteins were separated by 7.5%–15% SDS–polyacrylamide gel electrophoresis, transferred to a PVDF membrane, and blocked with 5% non-fat milk powder or 5% bovine serum albumin (BSA) for 1 h. Then the membrane was incubated with primary antibody at 4 °C for 16 h, followed by secondary antibody HRP-conjugated anti-rabbit (1:5000, Abclonal, AS038, Wuhan, China) or anti-mouse (1:5000, Abclonal, AS003). The membrane was processed with an ECL kit (Epizyme, SQ201, Shanghai, China), and the gray values of protein bands were recorded and analyzed.
The primary antibodies included anti-NLRP3 (1:1000, Adipogen, AG-20B-0014-C100, Liestal, Switzerland), anti-interleukin-6 (IL-6) (1:1000, Abclonal, A0286), anti-ZO-1 (1: 5000, Proteintech, 21773-1-AP, Wuhan, China), anti-Occludin (1:5000, Proteintech, 27260-1-AP), anti-NF-κB (1:1000, Abclonal, A19653), anti-sirtuin type 1 (SIRT1) (1:1000, CST, 9475, Danvers, MA), anti-caspase-1 (1:1000, CST, 24232), anti-ionized calcium-binding adapter molecule 1 (Iba-1) (1:1000, CST, 17198), anti-phospho-IκBα (1:5000, HUABIO, HA722770, Hangzhou, China), anti-free fatty acid receptor (FFAR) 2 (1:1000, Proteintech, 84544-1-RR), anti-FFAR3 (1:1000, HUABIO, ER63606), anti-Toll-like receptor 4 (TLR4) (1:1000, Abclonal, A5258), anti-myeloid differentiation primary response protein 88 (MyD88) (1:1000, CST, 4283), and anti-interleukin-1β (IL-1β) (1:1000, Thermo, P420B, Waltham, MA). β-Actin (1:100000, Abclonal, AC026) was used as the internal control.
Immunohistochemistry and immunofluorescent staining
Mice were anesthesized by intraperitoneal injection of tribromoethanol (100 mg/kg) and subsequently underwent transcardial perfusion with 1 × PBS followed by 4% paraformaldehyde. Thereafter, the brain and colon tissues were collected, fixed in 4% paraformaldehyde for 48 h and subsequently dehydrated in a 30% sucrose solution for 72 h. The brain and colon tissues were then frozen and embedded in optimal cutting temperature (OCT) compound (Sakura Finetek, Torrance, CA, Cat-4583) prior to sectioning into uniform slices (brain: 40 μm; colon: 12 μm) using a Leica Microsystems microtome (Wetzlar, Germany). The frozen sections were thawed and mounted onto positively charged slides (ProbeOn Plus; Thermo Fisher Scientific) before being stored at –80 °C.
For antigen retrieval from frozen brain sections, the sections were subjected to 20–30 min of microwave treatment (Midea, Foshan, Guangdong, China, Cat-M1-211A) in citrate buffer (pH 6.0) (Servicebio, Cat-G1202). Then the sections were blocked in a blocking solution composed of 10% BSA and 0.3% Triton X-100 (Sigma, X100-5, Darmstadt, Germany) in PBS for 30 min. The sections were then incubated with 3% hydrogen peroxide for 15 min. Subsequently, the sections were incubated overnight at 4 °C with primary antibodies diluted in normal goat serum (2%) (Beyotime, Cat-C0265, Shanghai, China), followed by incubation with biotinylated secondary antibodies and horseradish peroxidase (HRP)− streptavidin or the appropriate secondary antibodies. Nuclei were visualized using DAPI solution. Representative images were captured using a fluorescence microscope (Nikon CSU-W1 Sora 2 Camera; Olympus Corporation, VS120-S6-W). The number of positive cells was quantified using Image Pro Plus 6.0 software. Each section was analyzed based on five randomly selected fields.
The primary antibodies included anti-tyrosine hydroxylase (TH) (1:1000, Thermo Fisher Scientific, P21962), anti-α-synuclein (D37A6) antibody (1:1000, CST, 4179), anti-Iba-1/AIF-1 (E4O4W) (1:200, CST, 17198), anti-Occludin (1:1000, Proteintech, 27260-1-AP), and anti-ZO-1 (1:2000, Proteintech, 21773–1-AP). The secondary antibodies employed were Alexa 488-conjugated goat anti-rabbit IgG (1:1000, Thermo Fisher Scientific, A32723), HRP-conjugated donkey anti-rabbit (1:1000, Abclonal, AS038), and Alexa 594-conjugated goat anti-rabbit IgG (1:1000, Thermo Fisher Scientific, A11005).
Quantitative real-time polymerase chain reaction (qRT-PCR)
Total RNA was extracted using TRIzol Reagent (Vazyme Biotech, R411-01, Nanjing, China) and reverse transcribed into cDNA via a PrimeScript RT-PCR kit (Abclonal, RK20433). qRT-PCR was performed using SYBR Premix Ex Taq (Vazyme Biotech, R433) on the QuantStudio 7 platform (Life Technologies, Waltham, MA). The primers (Table S2) were custom-synthesized by GENEWIZ (Shanghai, China). The fluorescence signals corresponding to the target genes were analyzed using the 2^−∆∆Ct^ method for relative quantification. β-Actin and GAPDH served as endogenous controls.
Enzyme-linked immunosorbent assay (ELISA)
Quantification of murine IL-1β, IL-6, LPS, and lipopolysaccharide-binding protein (LBP) levels was performed using ELISA kits purchased from Jianglai Industrial Limited by Share Ltd. (Shanghai, China, Cat-JL20691, JL29644, JL20268, JL18442).
Fecal DNA extraction and 16S RNA sequencing
At the end of the six-week experiment, 6 mice from each experimental group were used for microbiota sequencing analysis. Mice were individually housed in a sterile, autoclaved cage, and five fresh fecal pellets were collected for 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, 51604, Hilden, Germany). The quality and integrity of the extracted DNA were subsequently validated by 1.2% agarose gel electrophoresis. For library construction, a two-step PCR amplification targeting the V3-V4 hypervariable region of the 16S rRNA gene was performed. The PCR amplification utilized universal primers 357F (5′-ACTCCTACGGRAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The thermal cycling was 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, San Diego, CA). 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 BMDMs and SCFA treatment
Bone marrow cells isolated from femurs of mice were cultured for 7 days in the presence of 20 ng/mL recombinant mouse macrophage colony-stimulating factor (M-CSF, 315-02-10UG, PeproTech, Cranbury, NJ) in complete RPMI-1640 medium containing 10% FBS, 10 mM glucose, 2 mM L-glutamine, and 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.
To further explore the effects of sodium acetate (NaA) (Absin, abs42027403, Shanghai, China) and sodium butyrate (NaB) (MedChemExpress, HY-B0350A) on M1 and M2 polarization, on day 7 of culture, M0 macrophages were harvested and then were stimulated for 24 h with 1 μg/ml LPS (SJ-MB0005, Shandong Sparkjade Biotechnology, China) and 1 mM ATP (SJ-MN0102A, Shandong Sparkjade Biotechnology) for the generation of M1 macrophages. Then acetate or butyrate was added for 24 h. Groups were as follows: Control group, LPS + ATP group, LPS + ATP + NaA group (5 mM NaA), LPS + ATP + NaB group (0.5 mM NaB).
Small interfering RNA (siRNA) transfection
siRNA targeting FFAR2/3 and control siRNA were synthesized by GenePharma (Table S3). Four individual siRNA sequences were constructed to form the siRNA Smart Pool to reduce the off-target effects of siRNAs. Transfections were performed using the Lipofectamine™ RNAiMAX reagent (Invitrogen, 13778030, Waltham, MA). At 48 h post-transfection and at 24 h of inflammation modeling, cells were treated with 5 mM NaA or 0.5 mM NaB for 24 h. Western blotting was performed to confirm the downregulation of FFAR2/3 targeted by siRNA.
Fecal sample collection and SCFA level measurement
Fecal sample from each mouse was collected in the morning using designated fecal collection containers. For each mouse, 400 mg of fresh fecal sample was used for SCFA analysis after grinding and sonication as pretreatment steps. Additionally, fresh B. coprocola bacterial culture solution was collected and centrifuged to obtain the supernatant for SCFA analysis. Individual SCFAs in fecal samples and B. coprocola bacterial supernatant were quantified by gas chromatography-mass spectrometry (GC–MS) and liquid chromatography tandem mass spectrometry (LC–MS/MS), conducted by TinyGene Bio-Tech (Shanghai, China) Co., Ltd., following standardized protocols.
Whole genome analysis of B. coprocola
High-quality genomic DNA was extracted and subjected to a hybrid sequencing strategy utilizing both Illumina (short-read) and PacBio/Nanopore (long-read) platforms. Following quality control and adapter trimming, the sequencing data were assembled into a complete circular genome using Unicycler (v0.4.8). The final assembly was annotated to identify protein-coding genes, non-coding RNAs, genomic islands, and mobile genetic elements. Functional annotation of the predicted genes was carried out by comparing their sequences against major public databases. This sequencing was executed by TinyGene Bio-Tech (Shanghai, China).
Statistical analysis
Statistical analyses were conducted using GraphPad Prism (version 8.01; GraphPad Software Inc., San Diego, CA). One-way analysis of variance (ANOVA) was used to assess differences among multiple groups. When ANOVA indicated a significant difference, post-hoc comparisons were performed using Tukey’s test (for data meeting assumptions of normality and homogeneity of variances) or Games-Howell test (for nonparametric data analyzed by Kruskal–Wallis test). 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). P < 0.05 was considered as statistically significant.
Results
B. coprocola intervention ameliorates motor impairments and gastrointestinal disturbances in the rotenone-induced PD mouse model
To evaluate the effects of B. coprocola in PD, mice received intraperitoneal rotenone for 3 weeks, followed by 3 weeks of treatment with B. coprocola or vehicle (Fig. 1a). Weight reduction, motor disturbances, and gastrointestinal (GI) impairments frequently manifest in animal models of PD [17]. Rotenone administration caused significant weight loss during the induction period. From weeks 4 to 6, treatment with B. coprocola mitigated the weight loss in rotenone-induced mice, accompanied by faster weight recovery than controls (Fig. 1b). However, there was no significant difference in the area under the curve between rotenone and B. coprocola groups (Fig. 1c).Fig. 1B. coprocola treatment alleviated motor symptoms and gastrointestinal dysfunctions of the rotenone-induced PD mouse model. a Flow chart of animal treatments. b, c Average body weights of 3 groups of mice from week 0 to week 6 and area-under-curve area analysis. d–f Behavioral results of Rota-Rod test, pole test, and beam walking test. g, h Intestinal transit distances. i, j Colon lengths. k Water content percentages in 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 < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test
At 6 weeks, behavioral assays were conducted to evaluate the motor functions of mice (Fig. 1a). Mice subjected to rotenone intoxication exhibited significant motor impairments compared to the control group, as evidenced by reduced latency to fall from the Rota-Rod (P < 0.0001, Fig. 1d), prolonged climbing times in the pole test (P < 0.001, Fig. 1e), and increased time spent on the beam in the beam walking test (P < 0.01, Fig. 1f). Conversely, mice treated with B. coprocola demonstrated significant improvements in these behavioral parameters compared to the rotenone-induced PD group.
Moreover, mice in the rotenone-induced PD group exhibited a significant reduction in intestinal transit distance (P < 0.001, Fig. 1g, h) and colon length (P < 0.001, Fig. 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, Fig. 1g-j). In addition, mice subjected to rotenone exhibited a marked decrease in fecal water content percentage (P < 0.01, Fig. 1k), which was significantly increased following B. coprocola administration (P < 0.05, Fig. 1k).
In summary, rotenone intoxication induced weight reduction, motor impairments, and GI dysfunction in the mice, while administration of B. coprocola substantially mitigated these PD-related manifestations.
B. coprocola administration mitigates PD-related histological features in the brain and the colon in the rotenone-induced mouse model
Degeneration of dopaminergic neurons and accumulation and phosphorylation of α-syn are two key histological characteristics of PD [18]. The cell bodies of dopaminergic neurons are situated in the substantia nigra pars compacta (SNc), with their axons projecting to the caudate-putamen (CPu) region [19].
In the rotenone-induced PD mouse model, the numbers of TH^+^ cells in the SNc and CPu were significantly diminished compared to the control group (P < 0.01), whereas treatment with B. coprocola substantially mitigated this neuronal loss (P < 0.05) (Fig. 2a–c). Immunofluorescence staining revealed a marked increase of α-syn and pS129-α-syn levels in the SNc of mice in the rotenone-induced PD group. Conversely, B. coprocola treatment notably reduced the levels of α-syn and pS129-α-syn in this region (Fig. 2d–f, m, o). The increased levels of α-syn and pS129-α-syn protein in the gastrointestinal tract were also a significant pathological feature associated with the progression of PD [20]. Immunofluorescence analysis indicated that the levels of α-syn and α-syn-ser-129 in the colon of rotenone-induced mice were significantly elevated compared to that of the control group and the B. coprocola-treated group (Fig. 2l–o).Fig. 2B. coprocola treatment attenuated PD-associated histological features in the midbrain and the colon of the rotenone-induced mouse model. a-c Representative immunohistochemistry images of TH staining in the SNc and CPu, and statistical analysis of TH^+^ cells. d-f Representative immunofluorescence images of nuclei (DAPI, blue) and α-syn (green) staining in the SNc and CPu, as well as statistical analysis of α-syn density in the SNc and CPu. g-i Representative immunofluorescence images of nuclei (DAPI, blue) and Iba-1 (red) staining in the SNc and CPu. Statistical analysis about numbers of Iba-1^+^ cells in the SNc and CPu. j, k Representative Western blotting bands of Iba-1 in the midbrain, and density analysis. l, n Representative immunofluorescence images of nuclei (DAPI, blue) and α-syn (green) staining in the colon, and statistical analysis. m, o Representative immunofluorescence images of nuclei (DAPI, blue) and pS129-α-syn (red) staining in the SNc and colon, as well as statistical analysis. For a-o, n = 5 for each group. Data are presented as mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test
Activation of microglia plays a role in neuroinflammation and dopaminergic neuronal loss in the brain during the progression of PD [21]. In the current study, immunofluorescence staining of Iba-1, a marker for microglia [22], in the SNc and CPu, was performed to assess glial cell reactivity. 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, Fig. 2g–i). However, treatment with B. coprocola significantly reduced Iba-1^+^ cells in the SNc and CPu (SNc: P < 0.05; CPu: P < 0.01, Fig. 2g–i). Western blotting analysis of Iba-1 in the midbrain also revealed a similar trend (P < 0.0001; P < 0.01, Fig. 2j, k).
Collectively, these results demonstrated that B. coprocola intervention markedly ameliorated PD-related histopathology in both the brain and the colon of rotenone-induced murine model, and that B. coprocola treatment is associated with modulation of immune cell activity.
B. coprocola intervention ameliorates gut microbiota dysbiosis in the rotenone-induced PD mouse model
An increasing number of studies has identified gut microbiota dysbiosis in both PD patients and PD animal models, highlighting its crucial role in the pathogenesis of PD [23]. To elucidate if B. coprocola administration protects against the rotenone-induced PD through modulation of the microbiome community structure, 16S rRNA sequencing was performed on fecal samples from mice in the three experimental groups.
Initially, α-diversity analysis was conducted to evaluate the richness and diversity of bacterial taxa. The mice in the rotenone-induced PD group demonstrated 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 (Fig. 3a–f). These results suggest that B. coprocola treatment ameliorated the rotenone-induced alterations in microbial abundance and diversity.Fig. 3B. coprocola intervention mitigated the fecal microbiota dysbiosis in rotenone-induced PD mice. 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 OTU-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: Akkermansia, Bifidobacterium, Parabacteroides, Odoribacter, Alistipes, and Bacteroides. k LEfSe difference analysis. n = 6 for each group. Each boxplot represents the median, interquartile range, minimum and maximum values. Data are presented as mean ± SD. Statistical analysis was performed using the Kruskal–Wallis nonparametric test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
Moreover, β-diversity analysis revealed consistent results. At week 6, the microbiome community structure of the rotenone-induced PD group exhibited a significant divergence from that of the control and B. coprocola groups, as demonstrated by OTU-Jaccard-Anosim analysis (R = 0.1984, P = 0.013) and Unweighted-Anosim 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 gut microbiota (Fig. 3g, h).
Additionally, we performed taxonomic profiling at the genus level (Fig. 3i). Differential abundance analysis using LEfSe (linear discriminant analysis effect size) identified key microbial taxa with significant intergroup differences (Fig. 3k). Specifically, the relative abundances of Parabacteroides, Odoribacter, Alistipes and Bacteroides were diminished in the rotenone-induced PD group compared to the control, whereas Akkermansia and Bifidobacterium were enriched. Notably, B. coprocola administration markedly restored the relative levels of these bacterial genera, including Parabacteroides, Odoribacter, Alistipes, Bacteroides, Akkermansia, and Bifidobacterium (Fig. 3j, k).
B. coprocola treatment restores expression of tight junction proteins and inhibits the leakage of microbial toxins in the rotenone model
Gut microbial disorders can trigger chronic inflammation of the body’s intestinal and even systemic inflammation [24]. The rotenone-induced PD mouse model manifests compromised blood–brain barrier (BBB) and intestinal barrier integrity, with concomitant generation of inflammatory cytokines and pathogenic LPS [17, 25]. We assessed the expression levels of two major tight junction proteins, ZO-1 and occludin, in the midbrain and colon. qRT-PCR and Western blotting analyses demonstrated that the expression of ZO-1 and occludin was significantly diminished in the rotenone-induced group compared to the control group, whereas treatment with B. coprocola substantially restored their expression (all P < 0.05) (Fig. S1a,b; Fig. 4c–e). Immunofluorescence staining of the colon further revealed that the fluorescence intensities of ZO-1 and occludin were markedly decreased in the rotenone-PD group but significantly increased in the B. coprocola group (P < 0.01, P < 0.05) (Fig. 4a, b).Fig. 4B. coprocola treatment restored tight junction proteins and protected LPS leakage in the rotenone-induced mouse model. a,b Representative immunofluorescence images of ZO-1 and occludin staining in the colon, as well as quantification of relative intensity. c–e Representative Western blotting bands of ZO-1 and occludin in the colon and midbrain, as well as density analysis. f–h LPS endotoxin levels in the colon (f), blood (g) and the midbrain (h). i–k LBP levels in the colon (i), blood (j) and the midbrain (k). For a-k, n = 5 for each group. Data are presented as mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test
Then, we quantified the levels of LPS and LBP in the midbrain, serum and colon. ELISA analysis indicated that both LPS and LBP levels were elevated in the rotenone-induced PD group compared to the control group. In contrast, B. coprocola administration significantly attenuated these elevations (all P < 0.05, Fig. 4f–k).
Collectively, these findings suggest that B. coprocola treatment restores barrier integrity in the rotenone-induced mouse model, protecting against microbial toxin leakage.
B. coprocola treatment affects the M1/M2 polarization of macrophages/microglia in the gut-blood-brain axis of the rotenone-induced PD mouse model
Systemic chronic inflammation activates various types of immune cells in the body to exert immune function and thus modulate the inflammatory response. We next investigated the potential impact of B. coprocola treatment on myeloid cells regulating systemic chronic inflammation, by measuring 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 Fluorescence Minus One (FMO) control [26] (Fig. S5). In the colon, the percentage of CD80^+^ macrophages was remarkably increased in the rotenone-induced PD group mice compared with the control group mice (P < 0.01), while B. coprocola treatment significantly decreased the CD80^+^ macrophages (P < 0.05) (Fig. 5a, e). In contrast, the percentage of CD206^+^ macrophages was remarkably decreased in the rotenone-PD group mice compared with the control group mice (P < 0.001), but markedly elevated in the B. coprocola group (P < 0.05) (Fig. 5a, f).Fig. 5. Effects of B. coprocola treatment on macrophage polarization in the rotenone-induced mouse model. a-d Representative contour maps of flow cytometry showing the M1-type (CD80^+^) and M2-type (CD206^+^) macrophages in the gut–blood–brain axis of the 3 groups. All gates were set using FMO control samples. e-j Percentages of M1/M2-type macrophages in the colon (e, f), blood (g, j) and the brain (h, i). For a–j, n = 4 for each group. Data are presented as mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test
The preceding data suggested that intestinal barrier damage in the rotenone-induced PD mouse model led 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^+^ macrophage levels (P < 0.001, P < 0.01) (Fig. 5b, g). However, it did not markedly affect the variation in cell counts of CD206^+^ macrophages (Fig. 5c, j).
In the brain, we analyzed the accumulation of infiltrating macrophages and activated microglia, which were defined as CD11b^+^, CD45^+^ high [26, 27]. Flow cytometry analysis revealed that B. coprocola treatment of rotenone-induced mice strikingly reduced the percentage of infiltrating macrophages and microglia defined as M1-type cells compared with the rotenone-induced PD group mice. However, B. coprocola administration did not significantly affect the percentage of M2-type microglia/macrophages in the brain (Fig. 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
The NLRP3 signaling pathway represents a highly intricate and well-regulated inflammasome-associated pathway that plays a pivotal role in orchestrating immune and inflammatory responses, particularly in the context of the microbiota-gut-brain axis. LPS, a major component of the outer membrane of Gram-negative bacteria, is a potent pro-inflammatory molecule. It directly binds to TLR4 with high affinity, initiating a cascade of intracellular signaling events. 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 inflammasome. 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 [28]. This pathway plays a dominant role in the microbiota-gut-brain axis [29].
Therefore, we detected the activation status of NLRP3 pathway in the midbrain and the colon by Western blotting. Interestingly, we observed a striking consistency in the activation patterns of the NLRP3 pathway components between the colon and the midbrain tissues. This finding suggests a coordinated regulation of this inflammatory pathway across different regions, potentially highlighting a systemic response in our experimental model. The protein levels of TLR4, MyD88, p-IκB-α, NF-κB, NLRP3, and caspase-1 in the rotenone-induced PD group were significantly increased compared to those in the control group. Conversely, the levels of these proteins were remarkably reduced by B. coprocola administration (all P < 0.05) (Fig. 6a–d).Fig. 6B. coprocola treatment inhibited the NLRP3 signaling pathway in the rotenone-induced mouse model. a, b Representative Western blotting bands of TLR4, MyD88, p-IκB-α, NF-κB, NLRP3, and caspase-1 in the midbrain, as well as density analysis. c, d Representative Western blotting bands of TLR4, MyD88, p-IκB-α, NF-κB, NLRP3, and caspase-1 in the colon, as well as density analysis. e, f Representative Western blotting bands of IL-1β and IL-6 in the midbrain and colon, as well as density analysis. g Blood levels of IL-1β and IL-6. For a–g, n = 5 for each group. Data are presented as mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test
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. The protein level and mRNA expression of IL-1β and IL-6 were significantly increased in the rotenone-induced PD group. However, B. coprocola treatment significantly down-regulated the expression of these inflammatory factors (Fig. 6e–g, Fig. S2a, b). This suggests that B. coprocola can alleviate PD-like pathology by modulating systemic inflammation in the rotenone-induced PD mouse model through the NLRP3 signaling pathway.
Acetic acid and butyric acid are potential active metabolites of B. coprocola
To investigate the relationship between B. coprocola and metabolites among the three groups of mice, and to identify potential bioactive metabolites of B. coprocola, we first performed principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) for multivariate analysis (Fig. 7a, b). The PCA score chart and the PLS-DA model showed that the fecal samples in the three groups were clearly separated, and the clustering effect was relatively obvious. The clustering of the control group and B. coprocola tended to be more consistent. This further suggested that distinct metabolic principal components play a key role in influencing the progression of rotenone-induced PD-like symptoms.Fig. 7. Metabolomic analysis of short-chain fatty acids in B. coprocola liquid supernatants and their correlation with gut microbiota profiling a PCA score plot analysis of microbiome profiling in feces from 3 groups. b PLS–DA analysis of metabolomic analysis in feces from 3 groups. c Short-chain fatty acid levels in the feces of the three experimental groups. d, e Short-chain fatty acids in the feces of the three experimental groups (Acetic acid; Butyric acid). f Correlation heatmap of microbiome profiling and targeted short-chain fatty acid metabolomics. n = 6 for each group. Each boxplot represents the median, interquartile range, minimum and maximum values. Data are presented as mean ± SD. Statistical analysis was performed using the Kruskal–Wallis nonparametric test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
To identify potential bioactive metabolites, we performed metabolomic analyses targeting SCFAs in feces from the three groups, as well as in B. coprocola bacterial liquid supernatants. We found that acetic acid (P = 0.022) and butyric acid (P = 0.008) exhibited statistically significant differences among the three groups (Fig. 7c–e; Fig. S4). Therefore, acetic acid and butyric acid are likely the key metabolites involved in the regulation of the PD pathological progression by B. coprocola (Fig. 7c–e).
Finally, we performed a correlation analysis between the differentially abundant bacterial genera and SCFAs. Alistipes and Odoribacter showed a positive correlation with butyric acid, while Anaeroplasma and Candidatus_Soleaferrea exhibited a significant positive correlation with acetic acid. These findings suggest that bacterial genera such as Alistipes, Odoribacter and Anaeroplasma are closely associated with the metabolism of SCFAs (e.g., butyric acid and acetic acid) and play a beneficial role in maintaining the host gut health. In addition, B. coprocola may regulate the level of SCFAs in the gut by affecting the abundance of other SCFA-producing genera.
Genomic insights into B. coprocola: metabolism and functional genes
To further explore the functional genes of B. coprocola, we performed whole-genome sequencing. This enabled us to understand the composition, structure, and function of B. coprocola genes, uncover new genetic resources, and provide foundational data for in-depth research on B. coprocola.
Based on the COG database enrichment gene pathways (Fig. 8a), B. coprocola was identified as a free-living bacterium with strong independent living ability and active metabolism, particularly excelling in carbohydrate utilization. It exhibited a robust ability in genetic information processing, diverse metabolic potential, capacity to sense and respond to environmental changes, and low motility and pathogenic potential.Fig. 8. Whole metagenomic sequencing of B. coprocola. a Gene pathway enrichment summarized based on the COG database. b Gene pathway enrichment summarized based on the KEGG database. c Circular diagram showing the genome structure of B. coprocola. d B. coprocola genes related to fatty acid biosynthesis based on KEGG database enrichment
The KEGG pathway enrichment (Fig. 8b) further elucidated its metabolic characteristics. The top-ranked pathways, including Global and overview maps, Carbohydrate metabolism, and Amino acid metabolism, highlighted its complex metabolic network. We further refined our analysis of genes enriched in fatty acid biosynthesis in B. coprocola and identified a total of nine genes related to fatty acid synthesis, including ACP (acyl carrier protein), a key gene involved in butyrate synthesis [30]. Simultaneously, among the genes associated with butyrate synthesis, genes related to butyrate kinase were enriched (e.g. buk, KO ID: K00929). The presence of buk serves as one of the most important markers indicating that microorganisms possess classical butyrate synthesis capability [31] (Fig. 8d, Tables S5 and S6). This indicated that B. coprocola possesses the capacity to produce both acetate and butyrate.
Looking into the genomic structure of B. coprocola (Fig. 8c, Table S4), the high proportion (88.5%) of coding sequences in the approximately 4.59 Mb genome was a typical feature of bacterial genomes. The significant difference in GC content between gene regions (42.7%) and intergenic regions (34.2%) indicated a preference for GC bases in coding areas.
Overall, these findings enhanced our understanding of B. coprocola’s ecological adaptation and functional potential, and further confirmed the role of B. coprocola in fatty acid synthesis.
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 PD mice. Based on these findings, we further investigated whether the potential functional metabolites of B. coprocola can affect the polarization of macrophages, thereby regulating inflammatory responses.
To better reflect in vivo conditions, we induced differentiation of mouse bone marrow cells into primary macrophages. The primary macrophages were treated with LPS + ATP (LPS: 1 μg/ml, ATP: 1 mM) to induce NLRP3 inflammasome activation. M1 macrophages defined as [CD11b/F4/80/CD86]^+^ and M2 macrophages defined as [CD11b/F4/80/CD206]^+^, which were gated using FMO control [26] (Fig. S5). As expected, both NaA and NaB significantly downregulated the percentage of CD86^+^ M1 macrophages. However, only NaB upregulated the proportion of CD206^+^ M2 macrophages (Fig. 9a, b).Fig. 9. Effects of NaA and NaB on BMDM polarization in the LPS model. a, b Representative density plots of flow cytometry and bar graphs summarizing the percentages of the M1-type (CD86^+^) and M2-type macrophages (CD206^+^) in the 4 groups. c, d Representative density plots and bar graphs showing the percentages of the M1-type(CD86^+^) and M2-type macrophage(CD206^+^) in the siRNA-FFAR2/3-NaA treatment groups. e, f Representative density plots and bar graphs showing the percentages of the M1-type (CD86^+^) and M2-type macrophages (CD206^+^) in the siRNA-FFAR2/3-NaB treatment groups. For a-f, n = 5 for each group. Data are presented as mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, one-way ANOVA followed by Tukey’s test. LPS model = LPS + ATP
FFAR2/3 are the key receptors through which acetic acid and butyric acid exert effects on immune cells [32]. FFAR2/3 protein levels were significantly decreased by treatment with FFAR2/3-siRNA 4mix smartpool (Fig. S3). Separate silencing of FFAR2 or FFAR3 partially blocked the effects of NaA/NaB on M1/M2 macrophages, and simultaneous silencing of both receptors further diminished these effects. The results indicated that FFAR2 and FFAR3 are key receptors through which NaA and NaB influence macrophage polarization (Fig. 9c-f).
Then, we examined the expression of FFAR2/3 receptor and its downstream deacetylase SIRT1 in the primary macrophages. SIRT1 deacetylates specific lysine residues on p-IκB-α, thereby inhibiting the phosphorylation of the NF-κB complex. SIRT1 upregulation leads to the binding of unphosphorylated IκBα to NF-κB, blocking NF-κB translocation into the cell nucleus. Western blotting results showed that the protein levels of FFAR2/3 and SIRT1 were significantly upregulated in the LPS + ATP + NaA/NaB group compared with the LPS + ATP group. The upregulated SIRT1 further inhibited phosphorylation of the downstream p-IκB-α. Nonphosphorylated IκBα could not further release mature NF-κB transcription factor, thereby further inhibiting NLRP3 synthesis and ultimately reducing the release of inflammatory cytokines. Consistent with the in vivo experimental results, treatment with NaA and NaB significantly reduced the protein levels of NLRP3 inflammasome, its upstream signaling molecules p-IκB-α and NF-κB, and the downstream factor caspase-1 (Fig. 10a–c; Figs. S7–S9) (all P < 0.05). Following the specific silencing of FFAR2/3, the capacity of NaA and NaB to mitigate the NLRP3 signaling pathway was markedly attenuated. The co-silencing of both FFAR2 and FFAR3 resulted in an even more pronounced reduction in the influence exerted by NaA and NaB on the NLRP3 signaling. These findings further substantiated that FFAR2 and FFAR3 function as pivotal receptors through which NaA and NaB modulated the NLRP3 signaling pathway. ELISA results further demonstrated that the levels of downstream inflammatory cytokines IL-1β and IL-6 were reduced in the NaA group and the NaB group compared to the LPS group (all P < 0.05) (Fig. S6).Fig. 10. NaA and NaB treatment inhibits the NLRP3 signaling pathway in the LPS model. a Representative Western blotting bands of FFAR2, SIRT1, p-IκB-α, NF-κB, NLRP3 and caspase-1 in the siRNA-FFAR2 groups. b Representative Western blotting bands of FFAR3, SIRT1, p-IκB-α, NF-κB, NLRP3 andcaspase-1 in the siRNA-FFAR3 groups.** c** Representative Western blotting bands of FFAR2/3, SIRT1, p-IκB-α, NF-κB, NLRP3 and caspase-1 in the siRNA-FFAR2/3 groups. n = 5 for each group. LPS model = LPS + ATP
In summary, the in vitro experiments using BMDMs revealed that the potential functional metabolites of B. coprocola—NaA and NaB—can modulate macrophage polarization and NLRP3 signaling pathways, with NaB exhibiting a more comprehensive effect. In addition, FFAR2 and FFAR3 were confirmed as key receptors through which NaA and NaB influence macrophage polarization.
Discussion
A growing body of research suggests that gut microbiota dysbiosis, triggered by gastrointestinal disturbances, may be a key factor in the pathogenesis of PD [23, 33]. In our previous large-scale clinical study, we identified a significantly reduced abundance of B. coprocola in PD patients compared to healthy individuals [13]. In this study, we established a PD mouse model by intraperitoneal injection of rotenone, followed by oral gavage treatment with B. coprocola to evaluate its protective effects in PD and to 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 [34]. Additionally, these microbial toxins can directly target neurons in the CNS, inducing neuronal dysfunction, which is closely linked to the pathological progression of PD [35]. It is currently known that the rotenone-induced PD mouse model can activate the gut-brain toxicity pathway in PD [17]. 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, 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 TH^+^ cells and increased levels of α-syn and pS129-α-syn in the brain, which is consistent with findings from other studies [36]. Collectively, these results indicate that the 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 the rotenone-induced PD mice.
Firstly, it is generally accepted that the gut microbiota balance maintains the individual health [37]. We provided evidence that rotenone significantly affected 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 significant disruption of 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, Alistipes and Bacteroides, while reducing the overgrowth of Akkermansia and Bifidobacterium, both of which have been reported to be elevated in PD patients [38–41]. Bacteroides, Odoribacter and Parabacteroides are the primary bacterial genera in the gut that exert immunomodulatory effects, with Bacteroides and Odoribacter exhibiting a negative correlation with cognitive aging [42, 43]. A positive correlation between elevated Akkermansia abundance and the development of PD has been noted in several previous studies [44, 45], 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 in ALS model mice [46]. Thus, the exact roles of Akkermansia in the pathogenesis of neurodegenerative diseases need further exploration. Our findings suggest 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 [47]. Both PD patients and animal models exhibit increased intestinal permeability, which allows microbial toxins to enter systemic circulation, thereby exacerbating neuroinflammation [48, 49]. 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, improving the structure of the intestinal microbiota, increasing the number of beneficial bacteria in the intestinal tract, and improving the balance of intestinal flora, which in turn reduces the production of LPS in the intestinal tract. Many studies have pointed 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 cisplatin rat model (kidney injury model) and ameliorate intestinal inflammation through remodeling of the gut microbiota [50]. Parabacteroides distasonis reduces insulin resistance by repairing the intestinal barrier and improving the anti-inflammatory effects of gut microbiota dysbiosis [51]. Lactiplantibacillus pentosus prevents the inflammatory response in dextran sulfate sodium salt-induced colitis mice by modulating the gut microbiota and serum metabolite levels [52]. Taken together, these studies have demonstrated that probiotic therapy could modulate gut microbiota composition and promote a healthier 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 the polarized M1 macrophages trigger an inflammatory response and release inflammatory factors [53]. 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 [54]. We then further explored the proportions of M1 and M2 types of macrophages in the gut–blood–brain axis. Our flow cytometry results showed that B. coprocola treatment reduced the proportions 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 inflammatory responses in a mouse model of inflammatory bowel disease by modulating macrophage polarization [55]. Clostridium butyricum-derived EVs modulate the disordered intestinal flora and polarize macrophages toward the M2 type in ulcerative colitis mice [56]. So intestinal flora and macrophage polarization responses are closely linked. B. coprocola treatment might affect the polarization of M1-type macrophages to the M2-type, thus reducing the inflammatory response in the intestine and preventing inflammatory factors from leaking or transmitting signals to the periphery.
Rotenone-induced PD mouse model elicits systemic chronic inflammation with induction of NLRP3 inflammasome activation [57]. Additionally, some studies indicate that NLRP3 can drive the onset of neurodegeneration and neuroinflammation [58, 59]. Our study investigated the expression of NLRP3 signaling pathway. We found that NLRP3 expression was downregulated in B. coprocola-treated 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. 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 the mature inflammatory factors to further promote the development of inflammation [60, 61]. Our results demonstrated that B. coprocola treatment downregulated the expression of key components in the NLRP3 pathway, including TLR4, MyD88, p-IκB-α, caspase-1, NLRP3 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 most abundant [62]. On the one hand, they can serve as energy substrates for cells and regulate energy homeostasis. 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 [63]. Butyrate is critical for the maintenance of intestinal homeostasis and capable of promoting generation of inducible regulatory T cells as an HDAC inhibitor, by up-regulating histone acetylation [64]. Microbiota-derived acetate exerts antihypertensive effects by modulating microglia and astrocytes and inhibiting neuroinflammation and sympathetic output [65]. In our study, SCFAs metabolomic analysis revealed that acetic acid and butyric acid are the key metabolites produced by B. coprocola. Our metabolic analysis of targeted SCFAs in three groups of mice revealed that acetic acid and butyric acid were statistically different among the three groups. We then further explored the effects of NaA and NaB on primary macrophage polarization in the LPS model. In vitro experiments demonstrated that NaA and NaB significantly influenced macrophage polarization by reducing the proportion of M1-like CD86⁺ macrophages. In addition, NaB but not NaA specifically promoted the proportion of M2-like CD206⁺ macrophages. Furthermore, NaA and NaB inhibited NF-κB activation in the NLRP3 signaling pathway and reduced the release of inflammatory cytokines. Notably, when FFAR2/3 receptor expression was suppressed via gene silencing, the regulatory effects of NaA and NaB on the NLRP3 signaling pathway were significantly diminished. This suggests that NaA and NaB primarily act through FFAR2/3 receptors to regulate NLRP3 signaling pathway. 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 and improving PD-like symptoms in rotenone-induced PD mice.
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 reshaping the gut microbiota composition; however, the roles of other immune cells remain poorly understood. And the temporal dynamics of B. coprocola regulation of macrophage polarization require more intensive and long-term characterization. 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 in additional animal models, such as primate PD models, is necessary to confirm the therapeutic potential of B. coprocola in PD.
Conclusion
Our study revealed for the first time the protective effects of B. coprocola treatment in the rotenone-induced PD mouse model. B. coprocola treatment alleviates PD-related motor deficits, neuroinflammation, gut microbiota dysbiosis, and barrier dysfunction through inhibiting the NLRP3 signaling pathway to alleviate systemic chronic inflammation. 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.
Supplementary Information
Additional file 1. Table S1. Culture medium formula for B. coprocola. Table S2. Paired primers for qPCR. Table S3. Primers for FFAR2/3 siRNA. Table S4. B.coprocola Whole Genome Feature Values. Table S5. B.coprocola fatty acid synthesis enrichment gene. Table S6. B. coprocola butyric acid biosynthesis enrichment gene. Fig S1. Effects of B. coprocola treatment on mRNA expression of occludin and ZO-1 in midbrain and colon, detected by qRT-PCR. Fig S2. Effects of B. coprocola treatment on mRNA expression of NLRP3, IL-1β and IL-6 in the midbrain and colon, detected by qRT-PCR. Fig S3. Representative Western blot bands and density analysis of FFAR2 and FFAR3 siRNA knockdown efficiency. Fig S4. Metabolomics analysis of short-chain fatty acids in the liquid supernatant of B. coprocola.** Fig S5.** Gating strategy of flow cytometry.** Fig S6. **ELISA results of IL-1β and IL-6 levels in the cell supernatant. Fig S7-S9. Western blotting statistical analysis.Additional file 2. Original Western blots.
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