Regulation of Gut Microecology in Ischemic Stroke Fecal Microbiota Transplantation Mice by Buyang Huanwu Decoction and Soy Isoflavones

This study established a mouse model of stroke based on fecal microbiota transplantation (FMT) from ischemic stroke patients to investigate stroke-associated gut microbiota characteristics and their impact on host microecology. Mice were pretreated with antibiotics followed by transplantation of fecal samples from stroke patients, successfully mimicking the dysbiotic state observed in patients. Comparative analysis with published data from middle cerebral artery occlusion (MCAO) mouse models revealed that Akkermansia was significantly reduced, while Escherichia-Shigella was increased in the FMT mice, demonstrating a microbial profile highly consistent with stroke models and confirming the clinical relevance of the established model. Functional predictions indicated that antibiotic treatment enhanced pathways related to carbohydrate, amino acid, and energy metabolism, while membrane transport and signal transduction pathways were suppressed. HE staining showed that Buyang Huanwu decoction (BHD) and soy Isoflavones (SI) alleviated colonic inflammation induced by stroke patient-derived FMT. Microecological interventions with BHD, SI, and their combination all contributed to varying degrees of gut microbiota restoration, with Ileibacterium significantly upregulated across all intervention groups, suggesting it may be a key responsive genus. BHD exerted the most prominent effect, characterized by the enrichment of Alloprevotella and marked enhancement of pathways related to nucleotide metabolism, replication, and repair. SI intervention notably increased the abundance of Lachnospiraceae_NK4A136_group, indicating a potential role in modulating short-chain fatty acid metabolism. These findings provide both theoretical and experimental evidence for targeting the gut microbiota as a therapeutic strategy in post-stroke microecological interventions. 1. Introduction Stroke, also known as cerebrovascular accident, is a common brain vascular disease, with various subtypes including ischemic stroke, hemorrhagic stroke, subarachnoid hemorrhage, cerebral venous thrombosis, and spinal cord stroke (Ma et al., 2024). Among all types of stroke, approximately 87% are ischemic strokes (Saini et al., 2021). The clinical manifestations of stroke typically include unilateral weakness, numbness, speech difficulties, and ataxia. The pathophysiological process of stroke involves excitotoxicity, oxidative stress, cell death, and neuroinflammation, which are regulated by multiple signaling pathways (Zheng et al., 2025). Currently, treatment for ischemic stroke mainly focuses on thrombolysis or surgical intervention to rapidly restore blood flow (Zhang et al., 2025). In recent years, the discovery of the microbiome-gut-brain axis (MGB axis) has provided new insights into stroke treatment (Abdel-Haq et al., 2019). The gut, as the largest microbial reservoir in the human body, plays a key role in maintaining the gut-immune homeostasis. The gut microbiota affects host physiological and pathological processes through metabolites (such as short-chain fatty acids) and immune regulation (such as Treg cell differentiation). Disruption of homeostasis leads to dysbiosis (e.g., reduced α-diversity, overgrowth of opportunistic pathogens), which can damage the intestinal barrier and cause distant organ injury, such as blood-brain barrier dysfunction. Studies have shown that dysbiosis in ischemic stroke patients is closely related to the host’s metabolism and inflammation (Yamashiro et al., 2017). Stroke can cause intestinal barrier damage and microbiota dysbiosis, promoting the translocation of specific bacterial strains from the host gut microbiota to peripheral tissues, such as the lungs, leading to infections (Wen and Wong, 2017). Traditional Chinese medicine (TCM) has unique advantages in stroke treatment, with many classical formulations showing good therapeutic effects. Research has shown that TCM can modulate the gut microbiota to influence the MGB axis. For example, the Zhi Long Huoxue Tongyu Capsule (ZHTC) can improve the pathological state after stroke by modulating gut microbiota and metabolic disorders (Wang et al., 2022). Buyang Huanwu decoction (BHD), a classical TCM formula used for the prevention and treatment of stroke for centuries, has shown significant effects in improving neurological function scores and reducing the incidence of cerebral infarction in MCAO rats, improving cerebral blood flow, and promoting the expression of angiogenic factors (Li et al., 2024;Zhou et al., 2023).In addition to TCM, natural products such as soy isoflavones also regulate gut microbiota. The mechanism includes inhibiting harmful bacteria, regulating obesity-associated microbiota, and promoting the proliferation of probiotics and enhancing their antimicrobial activity (Chen et al., 2022)). Fecal microbiota transplantation (FMT) has shown potential in the treatment of ischemic stroke (IS). Studies indicate that FMT can alleviate cerebral ischemic injury and improve neurological function in obese rats, likely related to reduced oxidative stress and cell apoptosis in the brain. In animal models, FMT has also shown protective effects against transient cerebral ischemia-induced damage (Benakis et al., 2016). Although traditional stroke animal models, such as MCAO, effectively simulate cerebral ischemic injury, they do not fully represent the gut microbiota phenotype of clinical patients, limiting the in-depth study of stroke-gut interactions. A humanized modeling method has been developed that does not rely on germ-free facilities. In this method, the baseline microbiota of non-sterile mice is cleared by broad-spectrum antibiotics, and human fecal samples are transplanted to rebuild a human-like gut microbiota. This strategy can stably reconstruct microbiota compositions similar to the donor, with 16S rRNA sequence similarity reaching 68-75%, and showing donor-specific differences at the metabolomic level, reflecting the functional characteristics of the donor’s gut microbiota (Hintze et al., 2014). In this study, we applied fecal microbiota transplantation by transplanting feces from ischemic stroke patients into antibiotic-treated mice to construct a mouse model simulating the gut microbiota characteristics of stroke patients. To evaluate the effects of this model on gut microbiota composition and its differences compared with the traditional MCAO model, we integrated and analyzed 16S rRNA sequencing data from publicly available MCAO model mice and compared them with the microbiota characteristics of our fecal transplantation model.Furthermore, this study investigated the intervention effects of Buyang Huanwu decoction and soy isoflavones on the mouse stroke model and analyzed their regulatory mechanisms on gut microbiota using 16S rRNA sequencing. By constructing a model that more closely mimics the actual gut status of stroke patients and evaluating the effects of different intervention strategies on gut microbiota, this study provides experimental evidence and novel perspectives for research into the microbiota-related mechanisms of stroke and targeted therapeutic strategies. 2.Materials and Methods 2.1 Experimental Animals and Grouping Six- to eight-week-old SPF-grade male C57BL/6J mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. The animal study protocol was approved by the Institu-tional Review Board of Chongqing Hospital of Traditional Chinese Medicine (protocol code: 2022-DWSY-sJZ, Date:2022.04.25). After one week of acclimatization, mice were randomly allocated into six experimental groups (n = 6 per group) as schematically illustrated in Figure 1 : a control group (mus.fmt.con), an antibiotic-only group (mus.fmt.Abx), a stroke fecal microbiota transplantation (FMT) group (mus.fmt.nc), a BHD-treated group (mus.fmt.bhd), a soy isoflavone-treated group (mus.fmt.SI), and a combination group (mus.fmt.SIbhd). The control group received no treatment; the ABX group received an antibiotic cocktail alone. The FMT and drug-treated groups were pretreated with antibiotics and then orally gavaged with fecal suspensions from ischemic stroke patients, followed by interventions with BHD, soy isoflavones, or both. At the end of the experiment, fecal samples were collected and preserved in liquid nitrogen at -80 °C for microbial 16S rRNA sequencing. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Figure 1.Mouse experimental grouping and flow chart 2.2 Reagents and Compounds The antibiotic cocktail included vancomycin hydrochloride (0.5 g/L), ampicillin sodium (1 g/L), neomycin sulfate (1 g/L), and metronidazole (1 g/L), purchased from Zhaoren Biotech and North China Pharmaceutical. BHD was prepared using raw herbs ( Astragalus membranaceus 120 g, Angelica sinensis 6 g, Paeoniae rubra 4.5 g, Ligusticum chuanxiong 3 g, Carthamus tinctorius 3 g, Persicae semen 3 g, and Pheretima 3 g), sourced from the Chongqing Academy of Traditional Chinese Medicine. Soy isoflavones (≥98% purity) were provided by Shaanxi Ronglin Biotech. 2.3 Antibiotic and FMT Procedure Antibiotics were administered in drinking water for 7 consecutive days. Fecal samples from untreated ischemic stroke patients (60–80 years old) were homogenized in sterile PBS (20 mg/mL), filtered through 100 and 40 μm strainers, and centrifuged. The pellet was resuspended in PBS with 10% glycerol at a final ratio of 1 g feces to 4.5 mL PBS and 0.5 mL glycerol. Mice received 200 μL of this suspension via oral gavage every other day at 10:00 a.m. 2.4 Herbal and Isoflavone Administration Buyang Huanwu decoction was decocted twice in distilled water, and the combined extract was concentrated using rotary evaporation to a final concentration of 2 g/mL. Based on previously published dose conversion methods (Reagan-Shaw et al., 2008;Wei et al., 2013), the equivalent mouse dosage was calculated from the adult daily dose of 142.5 g, resulting in 20.54 g/kg. Accordingly, each mouse received 410.8 mg/day by oral gavage, corresponding to a volume of approximately 200 μL. Soy isoflavones were dissolved in 0.5% sodium carboxymethylcellulose to a final concentration of 11.572 mg/mL. Using body surface area normalization, each mouse was administered 400 μL/day by gavage, equivalent to 231.44 mg/kg. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 2.5 Data Collection and Integration To compare gut microbial profiles across different ischemic stroke mouse models, public 16S rRNA datasets were retrieved from the NCBI database using the keywords ‘ischemic stroke’ and ‘gut microbiota’. After manual screening based on group definition and data completeness, eight datasets were included (PRJNA808830, PRJNA565336, PRJNA862280, PRJNA769802, PRJNA875206, PRJNA906348, PRJEB48735, PRJNA855110). In addition to three sample groups collected in this study, all other data were obtained from the NCBI Sequence Read Archive (SRA). Sample metadata were standardized and grouped by experimental condition for downstream analysis (Table 1). | Table 1. Data Grouping Information | ||||| | Group | Data Source | Sample Size | Data Type | Sequencing Platform | Category | | mus_fmt_con | Collected sequencing data | 6 | Amplicon | Illumina | Mouse Normal Control Group | | mus_fmt_Abx | Collected sequencing data | 6 | Amplicon | Illumina | Antibiotic-treated Mouse Group | | mus_fmt_human | Collected sequencing data | 6 | Amplicon | Illumina | Fecal Microbiota Transplantation Group from Ischemic Stroke Patients | | rat_sham | PRJNA808830, PRJNA565336, PRJNA862280, PRJNA769802, PRJNA875206 | 34 | Amplicon | Illumina | Rat Sham Surgery Group | | rat_mcao | PRJNA808830, PRJNA565336, PRJNA862280, PRJNA769802, PRJNA875206 | 40 | Amplicon | Illumina | Rat Stroke Model Group | | mus_sham | PRJNA906348, PRJEB48735, PRJNA855110 | 25 | Amplicon | Illumina | Mouse Sham Surgery Group | | mus_mcao | PRJNA906348, PRJEB48735, PRJNA855110 | 27 | Amplicon | Illumina | Mouse Stroke Model Group | 2.6 16S rRNA Sequencing and Bioinformatics Fecal samples were submitted to a commercial sequencing provider for DNA extraction. The V3–V4 region of the bacterial 16S rRNA gene was amplified using the primer pair 341F (CCTACGGGNGGCWGCAG) and 806R (GGACTACHVGGGTATCTAAT), followed by Illumina sequencing and library construction. Raw sequencing data were processed using the QIIME2 pipeline for quality control and operational taxonomic unit (OTU) clustering, while denoising, chimera removal, and error correction were performed using the DADA2 algorithm to generate amplicon sequence variants (ASVs). All OTU and ASV representative sequences were taxonomically annotated against the SILVA database (version 138.1).Alpha and beta diversity analyses were conducted to assess within-sample microbial diversity and between-group community differences, respectively. Differential abundance analysis was performed using the LEfSe tool, with the Kruskal-Wallis test applied to identify significantly different taxa across groups, followed by pairwise Wilcoxon rank-sum tests and linear discriminant analysis (LDA) for ranking and phylogenetic visualization. Functional prediction of microbial communities was conducted using Tax4Fun, which inferred KEGG orthologs and pathway-level functional profiles based on SILVA -annotated OTU/ASV abundance tables. 2.7 Haematoxylin and eosin staining Colon tissue was collected from euthanised mice and placed in sterile centrifuge tubes, then fixed overnight in 10% neutral formaldehyde solution. Following fixation, the samples were dehydrated with a series of ethanol solutions, cleared with xylene, and embedded in paraffin. Tissue sections 4 μm thick were prepared and stained with haematoxylin and eosin (HE). Histopathological changes in the colon were assessed under a light microscope. Blind histological scoring was performed according to a previously established semi-quantitative method(McCafferty et al., 2000). 2.8 Statistical analysis Statistical analysis was performed using R software (version 4.0.3). Alpha diversity between two groups was compared using Welch’s t-test, and between multiple groups using the Kruskal-Wallis H test. All data are presented as mean ± SEM, with a significance threshold set at p < 0.05. 3.1 Alpha diversity analysis of murine intestinal flora For alpha diversity analysis, we selected six indices ( Chao1, Goods-coverage, observed_species, PD_whole_tree, Shannon, and Simpson ) to evaluate the species richness and evenness, while also reflecting sequencing depth and data volume. Kruskal-Wallis tests revealed significant differences ( p < 0.01) among the six alpha diversity indices, indicating that the treatments significantly altered gut microbiota diversity.As shown in Figure 2, the Chao1 index, representing species richness, demonstrated that antibiotic-treated mice exhibited significantly reduced gut microbial richness. The observed_species index, reflecting the number of detected species, revealed lower richness in stroke model mice compared to sham-operated controls, with antibiotic-treated mice showing further reduced species counts. The PD_whole_tree index, incorporating phylogenetic distances, indicated that stroke modeling led to decreased phylogenetic diversity.The Simpson and Shannon indices, integrating species richness and evenness, showed comparable diversity across groups, though antibiotic-treated mice displayed slightly lower diversity than others. Figure 2.Box Plots of Six Alpha Diversity Indices. It plots displaying six alpha diversity metrics: (A) Chao1 ( p = 0.0039), (B) observed species ( p = 0.018), (C) Good’s coverage ( p = 0.0015), (D) PD whole tree ( p = 0.0085), (E) Simpson ( p = 6.4×10⁻⁵), and (F) Shannon ( p = 0.0078). Statistical differences were assessed using the Kruskal-Wallis test . Boxes represent the interquartile range (IQR), horizontal lines denote the median, and whiskers extend to 1.5 × IQR. These indices were used to evaluate within-sample microbial diversity. 3.2 Beta Diversity Analysis of Murine Gut Microbiota Beta diversity analysis was performed to compare the gut microbial community structures across different treatment groups. Principal coordinates analysis (PCoA) was used to visualize the differences in beta diversity ( Figure 3 ). Based on Bray-Curtis and Jaccard distance metrics, which assess species abundance and community composition, respectively, the microbiota profiles of the sham-operated mice and stroke models were similar, but differences were observed between mouse and rat groups. PCoA based on weighted UniFrac distance showed that principal component 1 (PC1) accounted for 43.3% of the total variation, while PC2 explained 13.23%. Antibiotic-treated mice exhibited significant changes in microbial structure and diversity compared to untreated controls. However, after fecal microbiota transplantation (FMT) from ischemic stroke patients, the microbiota of recipient mice became more similar to both the normal and antibiotic-treated groups, suggesting that FMT partially restored the diversity lost due to antibiotic treatment.Further analysis using different distance metrics provided additional insights. PCoA based on weighted and unweighted UniFrac distances indicated that the microbiota of FMT-treated mice was phylogenetically closer to that of stroke model mice, with overlapping dominant taxa. However, Bray-Curtis and Jaccard distances revealed differences in community composition, particularly in the abundance of certain taxa and rare species. These results suggest that while the core microbiota was conserved across groups, treatment interventions influenced the relative abundance of specific microbial taxa. Figure 3. Beta diversity PCoA analysis based on different distance metrics. PCoA plots showing the beta diversity of microbial communities across different groups using (A) Binary Jaccard, (B) Bray-Curtis, (C) Weighted UniFrac, and (D) Unweighted UniFrac metrics. Groups are differentiated by color and shape: red squares (mus_fmt_Abx), blue circles (mus_fmt_con), green triangles (mus_fmt_human), purple diamonds (mus_mcao), yellow circles (mus_sham), orange circles (rat_mcao), and open circles (rat_sham). jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 3.3 Changes in the Composition of the Murine Gut Microbiota Microbial taxonomy typically follows a hierarchical classification system, from kingdom to species. In this study, we used OTU sequence annotation to link the results with the biological significance of species changes within the microbial communities. The relative abundance of species at the phylum and genus levels was visualized through stacked bar plots (Figure 4 ) to display differences across the experimental groups. At the genus level, the top 15 genera were selected for detailed analysis, while other known genera were combined into the ”others” category, and unidentified species were labeled as ”unknown.”At the phylum level, the abundance of p_ Firmicutes, p_ Bacteroidota, p_ Verrucomicrobiota, and p_ Proteobacteria was relatively high. Antibiotic treatment increased the relative abundance of p_ Verrucomicrobiota and p_ Actinobacteriota compared to normal mice. In the stroke model, the relative abundance of p_ Proteobacteria was significantly increased. Compared to the sham-operated group, the relative abundance of p_ Firmicutes was significantly decreased in the mouse stroke model, while the relative abundance of p_ Bacteroidota was higher, although in the rat stroke model, p_ Bacteroidota abundance slightly decreased compared to the sham group.At the genus level, g_ Muribaculaceae, g_ Lactobacillus, g_ Akkermansia, g_ Bifidobacterium, and g_ Lachnospiraceae_NK4A136_group showed relatively high abundances. Notably, g_ Akkermansia had higher relative abundance in both the sham-operated and antibiotic-treated mouse groups, suggesting that this genus might play a key role in the gut microbiota of mice. Compared to the sham-operated group, g_ Bacteroides and g_ Escherichia-Shigella showed increased relative abundance in the stroke model group. After fecal microbiota transplantation (FMT) from ischemic stroke patients, the relative abundances of g_ Akkermansia, g_ Bifidobacterium, and g_ Dubosiella in the recipient mice were significantly reduced compared to the antibiotic-treated group. Figure 4. Relative abundance of microbial communities at the phylum and genus levels. Stacked bar charts display the relative abundance of microbial communities at phylum (A) and genus (B) levels across different experimental groups. Each color represents a specific genus.The samples include: rat_sham (rat sham surgery), rat_mcao (rat MCAO model), mus _sham (mouse sham surgery), mus _mcao (mouse MCAO model), mus _fmt_con (mouse control group), mus _fmt_Abx (mouse antibiotic treatment group), and mus _fmt_human (mouse fecal microbiota transplantation from ischemic stroke patients). 3.4 Alpha Diversity Analysis of Mouse Gut Microbiota After Drug Treatment As shown in Figure 5, different letters are used to indicate significant differences between groups. Alpha diversity analysis revealed that antibiotic-treated mice ( mus .fmt.Abx) exhibited significant differences in Chao1 and Observed OTUs indices compared to the drug-treated groups ( mus .fmt.SI, mus .fmt.bhd, mus .fmt.SIbhd), with antibiotic treatment significantly reducing species richness in the gut microbiota. Furthermore, the Shannon and Simpson indices suggested that although total species richness did not fully recover, treatment may have promoted the proliferation of specific functional microbes, leading to a stabilization of community functionality. Figure 5. Alpha diversity indices across different experimental groups. Box plots showing the alpha diversity indices for different groups based on (A) Chao1, (B) Observed OTUs, (C) Shannon, and (D) Simpson indices. Different groups are denoted by color and shape: mus .fmt.Abx (green), mus .fmt.SI (orange), mus .fmt.Slbh (blue), mus .fmt.bhd (purple), mus .fmt.con (pink), and mus .fmt.nc (yellow). Boxes represent interquartile ranges with medians as horizontal lines. Different lowercase letters above indicate statistically significant differences between groups. 3.5 Beta Diversity Analysis of Mouse Gut Microbiota After Drug Treatment As shown in Figure 6, the PCoA results based on four distance metrics: Bray-Curtis, Jaccard, weighted UniFrac, and unweighted UniFrac are presented. The microbiota of antibiotic-treated mice ( mus .fmt.Abx) differed significantly from that of the control mice ( mus .fmt.con) in terms of species abundance and community structure. The PCoA plot based on the weighted UniFrac distance showed a clear separation of the antibiotic-treated group from the other groups, indicating that antibiotic treatment disrupted both microbial abundance and phylogenetic structure.Mice treated with Buyang Huanwu decoction ( mus .fmt.bhd) exhibited a microbiota composition similar to that of the control group, suggesting that Buyang Huanwu decoction may help restore gut microbiota. In contrast, soy isoflavone-treated mice ( mus .fmt.SI) showed differences from the control group, indicating that the effect of soy isoflavones on restoring microbiota abundance may be limited. The combined treatment group ( mus .fmt.SIbhd) showed microbiota profiles and species abundance similar to those of both the soy isoflavone and Buyang Huanwu decoction groups, suggesting that the combination therapy may help stabilize microbiota in stroke treatment. Figure 6. Beta diversity analysis of microbial communities after drug treatment. Principal Coordinate Analysis (PCA) plots based on different beta diversity metrics: (A) Bray-Curtis, (B) Jaccard, (C) Unweighted UniFrac, and (D) Weighted UniFrac distances. Each point represents a sample from different treatment groups: mus .fmt.con (red squares), mus .fmt.Abx (blue circles), mus .fmt.bhd (orange diamonds), mus .fmt.SI (green circles), mus .fmt.SIbhd (purple triangles), and mus .fmt.nc (yellow squares). The percentage values on the axes indicate the proportion of variance explained by the corresponding principal components (PC1 and PC2). 3.6Changes in the Composition of the Gut Microbiota in Mice After Drug Treatment Figure 7 shows the relative abundance stacked bar plots of the microbiota at the phylum and genus levels for each drug treatment group. At the phylum level, p_ Firmicutes, p_ Bacteroidota, p_ Actinobacteriota, and p_ Verrucomicrobiota exhibited relatively high abundance. Compared to the control group, antibiotic treatment significantly increased the relative abundance of p_ Actinobacteriota and p_ Verrucomicrobiota . After drug treatment, the relative abundance of p_ Actinobacteriota increased compared to the stroke patient fecal transplantation group ( mus .fmt.nc), although differences remained compared to the control group ( mus .fmt.con). The relative abundance of p_ Verrucomicrobiota and p_ Proteobacteria decreased, with p_ Verrucomicrobiota levels approaching those of the normal control group.At the genus level, antibiotic treatment led to a significant increase in the relative abundance of g_ Bifidobacterium, g_ Dubosiella, g_ Akkermansia, g_ Lactobacillus, and g_ Prevotellaceae_NK3B31_group compared to the normal control group. After treatment with Buyang Huanwu decoction ( mus .fmt.bhd), the relative abundance of g_ Bifidobacterium, g_ Akkermansia, g_ Lactobacillus, and g_ Alloprevotella became closer to that of normal mice. The combined treatment group ( mus .fmt.SIbhd) showed relative abundance of g_ Prevotellaceae_NK3B31_group that was more similar to the normal control group, suggesting that the combined treatment more effectively restored this genus.Compared to other groups, the relative abundance of g_ Ileibacterium was significantly higher in the drug treatment groups, with the combined treatment group ( mus .fmt.SIbhd) showing the most prominent increase. These results suggest that g_ Ileibacterium may play a key ecological role in the drug treatment process or may be highly sensitive to the combined treatment of Buyang Huanwu decoction and soy isoflavones. It is further speculated that Buyang Huanwu decoction, soy isoflavones, and their metabolites may provide critical factors promoting the growth of g_ Ileibacterium, thus contributing to gut microbiota regulation and potential therapeutic effects in disease intervention. Figure 7.Species composition of gut microbiota at phylum and genus levels after drug treatment (A) Stacked bar chart depicting the relative abundance of microbial communities at the phylum level in different treatment groups. Each bar represents a sample, with colors corresponding to different phyla. The groups include mus .fmt.con, mus .fmt.Abx, mus .fmt.bhd, mus .fmt.SI, mus .fmt.SIbhd, and mus .fmt.nc. (B) Stacked bar chart illustrating the relative abundance of microbial communities at the genus level in the same groups. Each color represents a specific genus, and the bars correspond to the same treatment groups as in panel A. 3.7 LEfSe Analysis of Mouse Gut Microbiota After Drug Treatment To further investigate the changes in microbial biomarkers following drug intervention, LEfSe analysis was performed on gut microbiota samples from each group of mice, with the LDA threshold set at 4.0 ( Figure 8 ). The results showed that the Buyang Huanwu decoction group ( mus .fmt.bhd) was significantly enriched in g_ Alloprevotella . The soy isoflavone-treated group ( mus .fmt.SI) was mainly enriched in p_ Desulfobacterota and its subordinate taxa, including c_ Desulfovibrionia, o_ Desulfovibrionales, and f_ Desulfovibrionaceae . The combined treatment group ( mus .fmt.SIbhd) exhibited enrichment of g_ Alloprevotella, g_ Ileibacterium, and the species s_ Ileibacterium _valens. In the antibiotic-treated group ( mus .fmt.Abx), enrichment was observed in p_ Verrucomicrobiota, p_ Actinobacteriota, g_ Akkermansia, g_ Lactobacillus, and g_ Prevotellaceae_NK3B31_group . Mice that received fecal microbiota transplantation from ischemic stroke patients ( mus .fmt.nc) were enriched in p_ Proteobacteria, g_ Odoribacter, g_unidentified_ Oscillospiraceae, and g_ Rikenella . In contrast, the normal control group ( mus .fmt.con) showed significant enrichment of p_Bacteroidota and its associated taxa. Figure 8.LEfSe analysis of microbial communities in mice after drug treatment. (A) Cladogram displays taxonomic differences among treatment groups, with colored branches highlighting significant taxa: mus .fmt.Abx (red), mus .fmt.SIbhd (yellow), mus .fmt.bhd (orange), mus .fmt.con (purple), mus .fmt.SI (green), and mus .fmt.nc (light green). (B) LDA scores (log10) identify taxa most enriched in each group, with higher scores indicating stronger group-specific enrichment. 3.8 Functional Prediction of Mouse Gut Microbiota After Drug Treatment Using Tax4Fun Functional annotation of the gut microbiota was performed using Tax4Fun, and the top 10 most abundant functional pathways were selected to create heatmaps for each treatment group ( Figure 9 ). Compared to normal mice, antibiotic-treated mice showed significant enrichment in pathways related to carbohydrate metabolism, translation, amino acid metabolism, energy metabolism, and glycan biosynthesis and metabolism, while the pathways for signal transduction and membrane transport were significantly reduced.In the fecal microbiota transplantation group ( mus .fmt.nc), the relative abundance of pathways related to energy metabolism and cofactor and vitamin metabolism was higher than that in both the antibiotic and normal control groups. However, the relative abundance of nucleotide metabolism, replication and repair, and translation pathways was the lowest, indicating that the microbiota derived from stroke patients affected the overall growth activity in the recipient mice, with the microbiota responding by increasing stress-related metabolic activity to adapt to the host environment.The functional abundance distribution of Buyang Huanwu decoction-treated mice ( mus .fmt.bhd) was more similar to that of normal mice, especially in cofactor and vitamin metabolism, amino acid metabolism, and translation, suggesting that Buyang Huanwu decoction effectively restored the gut microbiota functionality in antibiotic-treated and fecal transplantation mice.Soy isoflavone-treated mice ( mus .fmt.SI) showed significant upregulation in multiple functional pathways, particularly in energy metabolism, transport and catabolism, and carbohydrate metabolism. The combined treatment group ( mus .fmt.SIbhd) exhibited functional abundances in cofactor and vitamin metabolism and carbohydrate metabolism similar to those of the Buyang Huanwu decoction group, while the remaining functional pathways resembled those of the soy isoflavone-treated group, indicating that the combined treatment is largely influenced by soy isoflavones. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Figure 9.Functional profile of gut microbiota in mice after drug treatment. Heatmap shows predicted functional abundances by Tax4Fun for the top 10 categories across treatment groups: mus .fmt.con, mus .fmt.bhd, mus .fmt.Abx, mus .fmt.nc, mus .fmt.SI, and mus .fmt.SIbhd. Rows are functions; columns are groups. Color intensity indicates relative abundance, with red for high and blue for low. This reveals gut microbiota functional changes after treatments. 3.9 Pathological evaluation of colon tissue in mice after drug treatment As shown in the HE staining of the mouse colonic sections, in the control group ( Figure 10B ), the colonic tissue exhibited an intact architecture with densely arranged glands. The crypt structure was well-preserved, goblet cells were evenly distributed, and no significant mucosal detachment was observed. Following antibiotic treatment ( Figure 10A ), structural alterations in the colonic mucosa were evident, including epithelial cell shedding, a reduction in goblet cells, and mild edema in the lamina propria. These findings suggest that antibiotics compromise the integrity of the mucosal barrier, though no severe tissue damage was observed. After fecal microbiota transplantation (FMT) from stroke patients ( Figure 10C ), the submucosal layer became thinner, goblet cells were markedly reduced, and increased spacing between some crypt structures was noted. After normal feeding for three weeks, inflammatory cell infiltration was observed in the lamina propria ( Figure 10D ). In the group receiving stroke patient FMT combined with soy isoflavone treatment ( Figure 10E ), inflammation was alleviated, though the effect was modest. Treatment with Buyang Huanwu decoction (BHD) ( Figure 10F ) led to an increase in goblet cell numbers and a reduction in inflammatory cell infiltration. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Figure 10. Histological analysis of colonic tissues from mice in different treatment groups. HE -stained mouse colon tissue images from seven groups: (A) antibiotic-treated ( mus .fmt.Abx), (B) control ( mus .fmt.con), (C) stroke patient fecal transplant, (D) transplant + 3 weeks normal feeding ( mus .fmt.nc), (E) transplant + soy isoflavone ( mus .fmt.SI), (F) transplant + Buyang Huanwu decoction ( mus .fmt.bhd), and (G) combined treatment ( mus .fmt.SIbhd).[Note] 1: ×40 magnification; 2: ×100 magnification. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 4.Discussion The gut microbiota is a key microbial ecosystem that closely interacts with the host and plays a pivotal role in ischemic stroke. It regulates inflammatory cytokines, supports glial cell development, mediates immune cell trafficking, and produces metabolites that affect brain function (Xie et al., 2024). For instance, lipopolysaccharides (LPS) can cross the blood-brain barrier and trigger neuroinflammation (Yang et al., 2020), while short-chain fatty acids (SCFAs) enhance gut barrier integrity, suppress inflammation, and modulate neuronal apoptosis and microglial activity (Dang and Marsland, 2019). In this study, we combined publicly available murine stroke microbiota datasets with our own experimental samples for 16S rRNA sequencing analysis. The results revealed that stroke modeling significantly altered the composition and diversity of gut microbiota in mice. Compared to sham controls, stroke mice exhibited reduced species richness but similar overall diversity. At the phylum level, relative abundance of Proteobacteria increased, while Firmicutes and Verrucomicrobiota decreased, consistent with clinical observations of dysbiosis in stroke patients ((Wu et al., 2021). At the genus level, Akkermansia was markedly depleted in stroke mice, which may be associated with low-grade inflammation and disrupted gut homeostasis (Fung et al., 2017). Akkermansia muciniphila is known to exert anti-inflammatory effects and maintain intestinal barrier integrity (van der Lugt et al., 2019). Its reduction likely weakens mucosal protection, thereby exacerbating inflammation. Similarly, mice receiving fecal transplants from stroke patients also showed reduced Akkermansia, suggesting that dysbiotic donor microbiota may persistently affect the recipient gut environment and inhibit colonization of beneficial taxa. Moreover, Escherichia-Shigella was enriched in both the stroke and FMT groups, indicating its potential as a microbial marker of stroke-related dysbiosis. This genus has been linked to inflammatory conditions such as IgA nephropathy (Zhao et al., 2022), and may expand in response to ischemia-induced gut injury and oxidative stress (Xu et al., 2021). HE staining results showed that faecal transplantation in stroke patients induced significant inflammatory responses in mouse colon tissue. These findings support the hypothesis that stroke influences microbial structure and function via the gut–brain axis (Arya and Hu, 2018). Previous studies by Singh et al. demonstrated that transplantation of nutrient-deprived post-stroke microbiota exacerbated ischemic brain damage and promoted pro-inflammatory T cell polarization in recipient germ-free mice (Singh et al., 2016). Similarly, Xia et al. proposed a Stroke Dysbiosis Index (SDI) based on patient gut microbiota profiles, which correlated with clinical prognosis. High-SDI fecal transplants led to increased brain damage and elevated IL-17+ γδT cell levels in mice (Xia et al., 2019). Collectively, these results suggest that using FMT from stroke patients may offer a more clinically relevant model than traditional MCAO surgery for studying microbiota-stroke interactions. Interestingly, Dubosiella was significantly enriched after antibiotic treatment but declined following FMT with stroke-derived feces. Dubosiella newyorkensis has been shown to promote mucosal barrier repair and immune balance via production of propionate and L-lysine (Zhang et al., 2024). The observed suppression of this genus suggests that stroke-associated microbiota may impair gut–immune signaling by limiting the colonization of beneficial commensals, thereby contributing to post-stroke inflammatory pathology. Prior to treatment with BHD (Buyang Huanwu decoction), soy isoflavones, or their combination, mice were pretreated with broad-spectrum antibiotics. This approach has been shown to effectively deplete resident microbiota, enabling robust colonization of human-derived gut microbes comparable to that achieved in germ-free models (Staley et al., 2017). Moreover, antibiotic pretreatment facilitates allogeneic microbial engraftment in the gut mucosa, enhancing the efficiency of fecal microbiota transplantation (FMT) (Sarrabayrouse et al., 2020). In our study, antibiotic administration markedly reduced gut microbial richness and diversity in mice, disrupting phylogenetic structures and microbial stability (Shao et al., 2020). Furthermore, colon tissue section results from mice showed that antibiotic treatment affected the mucosal structure of colon tissue. This dysbiotic state conferred ecological advantages to certain antibiotic-tolerant taxa, such as Akkermansia, which expanded significantly post-treatment (Cozzolino et al., 2020). Consistent with this, we observed elevated relative abundances of Akkermansia and Bifidobacterium in the antibiotic group. Akkermansia has been reported to thrive under low-grade inflammatory conditions (Borton et al., 2017), suggesting adaptive growth potential in disrupted environments. Regarding Bifidobacterium, previous studies have shown strain-specific variations in sensitivity to metronidazole and vancomycin (Charteris et al., 1998;Delgado et al., 2005), while Wang et al. demonstrated its ability to inhibit pathogenic bacteria and promote beneficial colonization (Wang et al., 2022), supporting its post-antibiotic reestablishment capability. Functional predictions using Tax4Fun revealed that antibiotic-treated mice exhibited significantly increased capacities for carbohydrate metabolism, energy metabolism, amino acid metabolism, translation, and glycan biosynthesis and metabolism, whereas signal transduction and membrane transport pathways were markedly reduced. The upregulation of energy and biosynthetic functions reflects a heightened metabolic demand to support rapid adaptation and survival, while the suppression of signaling and transport functions implies impaired microbial cooperation and reduced ecological complexity. Collectively, these findings indicate that antibiotic pretreatment shifts the gut microbiota from a diverse and stable ecosystem to a metabolically active but ecologically simplified stress-responsive state. Compared to antibiotic-treated mice, drug-treated mice exhibited restored species richness and diversity in their gut microbiota. Specifically, after treatment with Buyang Huanwu decoction (BHD), the microbiota composition and phylogenetic structure of the mice were highly similar to those of the normal control group. HE staining results also showed that Buyang Huanwu decoction (BHD) treatment effectively alleviated intestinal inflammation caused by faeces in transplant stroke patients. After drug intervention, we observed a significant increase in the relative abundance of g_ Ileibacterium in all treatment groups, with the highest abundance in the combination treatment group ( mus .fmt.SIbhd). LEfSe analysis further identified g_ Ileibacterium and s_ Ileibacterium _valens as characteristic taxa in the combination treatment group. Previous studies have shown that Ileibacterium valens is a core functional bacterium involved in modulating gut microbial diversity in mice with non-alcoholic fatty liver disease (NAFLD). By upregulating its abundance, Ileibacterium valens activates the gut purine metabolism pathway, promotes the production of hepatoprotective metabolites such as inosine, and significantly reduces serum ALT, AST, and liver lipid accumulation, thereby improving NAFLD (Qiu et al., 2023). These findings suggest that g_ Ileibacterium plays a critical ecological role in drug therapy and may exhibit a high sensitivity to combined interventions with BHD and soy isoflavones. The main active ingredients of BHD include quercetin, ligustrum extract, astragaloside IV, astragalus glycosides, paeoniflorin, and ferulic acid (Xiong et al., 2025). Studies have shown that quercetin promotes the polarization of microglia/macrophages M2 cells through the PI3K/Akt/NF-κB signaling pathway, thereby improving neurological deficits (Li et al., 2023). Soy isoflavones, a naturally occurring compound, are widely recognized as plant estrogens used in managing menopausal symptoms (Chen and Chen, 2021;Laddha et al., 2022). Considering that both BHD and soy isoflavones are rich in bioactive components, such as flavonoids and glycosides, we hypothesize that these compounds or their metabolites may provide nutritional substrates or growth stimulants for g_ Ileibacterium, thus promoting its proliferation. Therefore, the significant changes in g_ Ileibacterium abundance may not only reflect its response to drug components but also suggest that combined treatment may regulate gut microbiota, promote beneficial metabolic product generation, and contribute to disease intervention. In the future, we aim to further clarify its role in the drug-microbe-host interaction mechanism through metabolomics and functional validation. LEfSe analysis revealed a significant enrichment of g_ Alloprevotella in the Buyang Huanwu decoction (BHD) group, with functional profiles resembling those of healthy controls. Compared to the stroke-FMT group, pathways related to replication and repair and nucleotide metabolism were significantly upregulated, suggesting enhanced epithelial repair ( Supplementary material Fig.1 ). Previous studies showed that activating the PI3K/AKT pathway alleviates oxidative and ER stress, reduces inflammation, and protects the BBB (Han et al., 2025). BHD similarly targets the S1P/S1PR1/PI3K/AKT axis (Liu et al., 2023). Pan et al. identified bioactive components in BHD (e.g., ferulic acid, amygdalin) that reach brain tissue and inhibit NF-κB and NLRP3 activation, promoting M2 microglial polarization and mitigating hemorrhagic transformation post-thrombolysis (Pan et al., 2025). Additional mechanisms include ferroptosis inhibition via Nrf2/GPX4 (Huang et al., 2025) and improved synaptic plasticity through cAMP/PKA/CREB signaling (Mo et al., 2024). These findings imply that Buyang Huanwu decoction may exert its therapeutic effects in mice transplanted with stroke patient-derived microbiota via comparable mechanistic pathways. In the soy isoflavone treatment group, p_ Desulfobacterota and its subordinate taxa were identified as key bacterial communities. Compared to the stroke-FMT group, the relative abundance of Lachnospiraceae_NK4A136_group was significantly increased, even surpassing that of the healthy control group. This genus is recognized as an important butyrate producer in the gut microbiota, contributing to the maintenance of gut barrier integrity, immune regulation, and anti-inflammatory effects (Louis and Flint, 2017). Butyrate, a major short-chain fatty acid, is known to modulate intestinal immune responses and enhance barrier function (Tan et al., 2014). We speculate that soy isoflavones may promote the proliferation of Lachnospiraceae_NK4A136_group, thereby increasing butyrate production, improving the intestinal immune microenvironment, and facilitating gut health restoration. In addition, several studies have demonstrated that isoflavones activate estrogen receptor (ER) signaling pathways in the gut, downregulate pro-inflammatory cytokine expression, and reinforce epithelial barrier function (Moussa et al., 2012). Diets rich in isoflavones have also been found to modulate lipopolysaccharide (LPS) biosynthesis pathways in gut microbiota, thereby suppressing inflammatory responses and reducing disease severity (Ghimire et al., 2022). Soy isoflavones have also been shown to activate the Nrf2/Keap1 pathway, enhancing antioxidant defense, reducing oxidative stress, inhibiting neuronal apoptosis, and promoting cell migration, thereby exhibiting strong neuroprotective effects (Xue et al., 2025). Furthermore, pathway prediction analysis based on Tax4Fun combined with t-test results showed significant upregulation of multiple functional pathways ( Supplementary material Fig.2 ), including nucleotide metabolism, replication and repair, and translation, in the soy isoflavone group. These pathways are associated with nucleic acid synthesis, DNA repair, and protein biosynthesis, reflecting potential enhancement of host epithelial cell function and barrier restoration. These results are consistent with the proposed mechanisms of isoflavone-mediated modulation of both microbial ecology and host signaling, highlighting its potential to promote post-stroke gut homeostasis through coordinated neuroprotective and microbiome-regulatory effects. Clinically, ischemic stroke often coexists with comorbidities such as hypertension, diabetes, hyperlipidemia, and atherosclerosis (Martin et al., 2024), which can significantly modulate the gut microbial ecosystem. Compared with traditional middle cerebral artery occlusion (MCAO) surgical models (Fluri et al., 2015), fecal microbiota transplantation (FMT) using samples from ischemic stroke patients may better replicate the clinical gut environment, offering higher translational relevance. Nevertheless, this study lacked an MCAO control group and did not perform microbial sequencing of the stroke donor samples, limiting our ability to associate donor-specific microbiota with observed post-transplantation effects.Future research should include microbial profiling of donor fecal samples to elucidate the link between donor community composition and recipient microbiota dynamics. Additionally, incorporating MCAO-operated mice as controls during the FMT phase would provide a more robust comparative framework to assess model-specific microbial perturbations. We also plan to integrate microbiota data from groups treated with Buyang Huanwu decoction and soy isoflavones to further explore the underlying mechanisms by which these agents modulate the gut microbiome. This will facilitate the identification of microbial targets and pathways involved in stroke progression, supporting the development of microbiota-oriented therapeutic strategies for ischemic stroke. 5.Conclusion This study demonstrated that stroke modeling significantly alters the composition and diversity of gut microbiota in rodents, with noticeable differences in relative microbial abundance between mouse and rat models. Fecal microbiota transplantation (FMT) from stroke patients into antibiotic-treated mice resulted in microbial communities partially resembling those of both healthy and antibiotic-treated mice, suggesting successful colonization of human-derived microbiota in the host.Antibiotic treatment substantially reshaped the gut microbiota, significantly increasing the relative abundance of g_ Dubosiella, g_ Akkermansia, and g_ Bifidobacterium, likely due to ecological advantages conferred by reduced competition. Functional predictions revealed upregulation of pathways related to carbohydrate metabolism, translation, amino acid metabolism, energy metabolism, and glycan biosynthesis, whereas pathways related to signal transduction and membrane transport were markedly downregulated, reflecting a metabolically active but ecologically simplified microbial state.After FMT from stroke patients, the abundance patterns of g_ Akkermansia and g_ Escherichia-Shigella mirrored those observed in the stroke model, implying that stroke-associated microbial characteristics can exert lasting effects on host immunity and inflammation following transplantation. Drug intervention, particularly with Buyang Huanwu decoction (BHD), led to a significant restoration of microbial richness and structure. The relative abundance of g_ Ileibacterium increased across all treatment groups and was highest in the combined treatment group, identifying it as a potential keystone genus. BHD-treated mice displayed microbial compositions and functional profiles closely resembling those of healthy controls, with significant upregulation of replication and repair and nucleotide metabolism pathways. g_ Alloprevotella was enriched in the BHD group, serving as a biomarker genus. In contrast, soy isoflavones intervention markedly elevated the relative abundance of Lachnospiraceae_NK4A136_group (a butyrate-producing genus), exceeding levels observed in the normal group. However, its overall therapeutic efficacy was less pronounced than BHD. HE staining results showed that transplanting faeces from stroke patients caused inflammation in the colon tissue of mice, while administration of BHD and soy isoflavone effectively alleviated the inflammation. BHD had a significant effect on improving stroke-related dysbiosis, and its ability to regulate the microbiota may be an important biological basis for its therapeutic effect on stroke. Declarations Ethics approval and consent to participate The animal study protocol was approved by the Institu-tional Review Board of Chongqing Hospital of Traditional Chinese Medicine (protocol code: 2022-DWSY-sJZ, Date: 2022.04.25). Availability of data and materials The datasets generated and/or analyzed during the current study are available in the Mendeley Data repository at https://data.mendeley.com/datasets/x6cvkg8dwt/1. Competing interests The authors declare no competing interests. Funding This work was supported by the Natural Science Foundation Project of Chongqing (Grant No. cstc2015jcyjA0752 and cstc2021jcyj-msxmX0848), the Bishan Science Research Project of Chongqing (Grant No. BSKJ2022006), and the Chongqing Student Innovation and Entrepreneurship Project (Grant No. S202410617021 and 202510617007). Authors’ contributions Xiaohong He and Yuting Deng carried out experiments, analyzed data, and wrote the manuscript. Yueyue Guan, Xiaorong Huang, and Xiaoyu Zhang performed experiments and analyzed results. Jiaying Hu, Fengying Liu, Yuhan Huang, Feibo Xu, Xuetong Yong and Keman Wu participated in experimental work, data analysis, and discussion. Yongfang Xie and Jianzhong Shu designed the study, supervised the research, and acquired funding. All authors read and approved the final manuscript.

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Colored branches in the cladogram (left) indicate significant differences. LDA scores (right) highlight taxa strongly enriched per group. (B) Similar cladogram and LDA results for mus.fmt.nc, mus.fmt.SI, mus.fmt.SIbhd, and mus.fmt.bhd, showing taxonomic differences and group-specific enriched taxa. Supplementary Figure 2. Tax4Fun functional prediction analysis of gut microbiota in mice after drug treatment. Left panels show mean functional abundance differences between groups with bars. Right panels display 95% confidence intervals for these differences, where circle centers indicate mean differences and horizontal lines show interval bounds. Circle colors represent p-values for significance of intergroup differences. Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 246views 130downloads Citations Download citation Xiaohong He, Yuting Deng, Yueyue Guan, et al. Regulation of Gut Microecology in Ischemic Stroke Fecal Microbiota Transplantation Mice by Buyang Huanwu Decoction and Soy Isoflavones. Authorea. 26 July 2025. DOI: https://doi.org/10.22541/au.175353678.81726846/v1 DOI: https://doi.org/10.22541/au.175353678.81726846/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.