Abstract
Background
Coronary heart disease (CHD) and depression often coexist and complicate patient care. The gut microbiota plays a crucial role in overall health and is involved in both conditions. Dysbiosis, particularly, increased levels of lipopolysaccharides (LPSs), can activate the Toll-like receptor 4 (TLR4), triggering inflammatory pathways associated with CHD and depression. Although some associations have been observed, the direct mechanistic association among gut dysbiosis, LPSs, TLR4 activation, and comorbidity of CHD and depression remains unclear. Thus, in the present study, we aimed to explore this association and the potential of modulating gut microbiota as a therapeutic strategy.
Methods
A rat model of CHD and depression was established using a high-fat diet and chronic unpredictable mild stress and verified by electrocardiogram, behavioral assessments, and cardiac marker analysis. Fecal microbiota transplantation (FMT) was performed by transferring microbiota from diseased rats to healthy rats (FMT-Disease group); the fecal microbiota of the rats from the FMT-Disease and FMT-Normal groups were compared. The TLR4 inhibitor TAK-242 was administered, creating the Disease + TAK-242 and FMT-Disease-TAK-242 groups. Gut microbiota composition was analyzed using 16 S rRNA high-throughput sequencing; LPS levels were measured using enzyme-linked immunosorbent assay. Polymerase chain reaction and western blotting were used to detect the expression of genes and proteins related to the TLR4/MYD88/NF-κB pathway in the heart and hippocampus, respectively.
Results
We confirmed that in the FMT-Disease group, the gut microbiota of diseased rats altered the gut microbial composition of healthy rats in terms of β-diversity, α-diversity, and community structure. Notably, LPS levels in the serum of FMT-Disease rats were elevated, thereby activating the TLR4/MYD88/NF-κB inflammatory pathway and increasing susceptibility to CHD comorbid with depression. Additionally, after receiving fecal microbiota from healthy rats, the Disease group showed a restoration of gut microbiota balance, improvement in general condition, and normalization of pathological, biochemical, and inflammatory indicators, indicating a suppressive effect on the progression of CHD with depression.
Conclusion
Our findings further clarify the interrelationship between gut microbiota and CHD comorbid with depression, enhancing our understanding of its pathogenesis. Moreover, we propose a potential novel therapeutic strategy that focuses on modulating gut microbiota composition to block the TLR4/MYD88/NF-κB inflammatory pathway.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12866-025-04302-y.
Keywords: Coronary heart disease, Depression, Gut microbiota, Lipopolysaccharides, TLR4 receptors
Background
Coronary heart disease (CHD), a prevalent form of ischemic heart disease caused by atherosclerosis of the coronary arteries, is increasingly being recognized as a psychosomatic disorder intricately associated with psychological well-being. The co-occurrence of CHD with depression (CHDWD), a state characterized by persistently low mood and diminished interest, presents a formidable clinical challenge. This comorbidity, often referred to as “double-heart disease,” is associated with a high risk of cardiovascular events and significantly affects patients’ quality of life [1]. The prevalence of depression among patients with CHD is notably high, ranging from 18 to 60% [2], highlighting the urgent need for a deeper understanding of the interplay between these conditions.
The gut microbiota and its metabolites, such as lipopolysaccharides (LPSs), trimethylamine N-oxide (TMAO), and bile acids, have been associated with CHD comorbid with major depression (CHDMD). According to Yang et al., the gut microbial composition of patients with CHDMD differs significantly from that of healthy individuals [3]. These patients exhibit increased microbial richness and dysbiosis, which leads to enhanced gut permeability, elevated levels of microbial metabolites in the bloodstream, a heightened inflammatory state, and increased levels of inflammatory markers. However, the mechanisms by which microbial dysbiosis and the related inflammatory markers contribute to the development of CHDMD remain unclear and warrant further investigation through experimental studies.
LPS, a component of the outer membrane of gram-negative bacteria, can trigger systemic inflammation. With the progression of CHD and depression, LPS levels in the bloodstream increase, suggesting its role as a key mediator in the development of these conditions. Recognition of LPSs by Toll-like receptor 4 (TLR4) on cell membranes initiates a cascade of intracellular signaling events [4, 5], activating the nuclear factor-kappa B (NF-κB) pathway and contributing to the pathogenesis of CHD and depression. The presence of elevated inflammatory cytokine levels in affected patients further underscores the nexus between inflammation and the progression of these comorbidities [6, 7].
Given the emerging evidence, investigating the causal association among the gut microbiota dysbiosis, LPS, and the TLR4/myeloid differentiation primary response protein 88 (MYD88)/NF-κB pathway in the context of CHD and depression is compelling. Therefore, this study aimed to unravel the intricate mechanisms by which the gut microbiota imbalance and its associated inflammatory markers contribute to the comorbidity of CHD and depression, thereby offering potential avenues for novel therapeutic interventions.
Materials and methods
The animal experiments in this study were conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals and were approved by the Animal Care and Use Committee of Guangxi University of Chinese Medicine (Ethical Approval No. DW20220609-69). All animal procedures complied with the European Parliament’s Directive on the Protection of Animals Used for Scientific Purposes. Rats in the first, second, and third stages were euthanized at the end of the experiment following anesthesia and blood collection, which was performed via abdominal aorta puncture, in order to obtain heart, hippocampal tissues, and blood samples. Anesthesia was induced by intraperitoneal injection of 0.3% sodium pentobarbital (50 mg/kg), and euthanasia was performed by tail vein injection of 3% sodium pentobarbital (150 mg/kg). After euthanasia, death was confirmed by the absence of cardiac activity. The entire euthanasia process was conducted under the supervision of the Animal Ethics Committee of the Guangxi University of Chinese Medicine.
Experimental animals
100 Six-week-old healthy male Sprague–Dawley rats, weighing 220 ± 30 g, were sourced from Hunan Slack Jingda Experimental Animal Co., Ltd (Building 1, Room 101, Hunan Science and Technology Achievement Transformation Center, Longping Hi-Tech Park, Changsha High-Tech Development Zone, Hunan Province, China). The rats were specific-pathogen-free grade and housed under a 12/12-h light/dark cycle with ad libitum access to water and food at the Experimental Animal Center of Guangxi University of Traditional Chinese Medicine (No. 13 Wuhe Avenue, Nanning, Guangxi, China).
Establishment of rats with CHDWD
The disease model was induced in rats through a high-fat diet and chronic unpredictable mild stress (CUMS) interventions to emulate the clinical characteristics of patients with CHDWD, which often included hyperlipidemia [8–10]. The diet consisted of 5% lard, 2% cholesterol, 0.2% bile salts, 20% sucrose, and 72.8% base feed. The CUMS regimen encompassed several stressors applied regularly over 6 weeks, including food deprivation, cold water swimming, white noise exposure, water deprivation, damp bedding, restraint, cage shaking, tail pain stimulation, cage tilt, and light/dark cycle reversal. Coronary artery ligation surgery was performed from the third week following the established methods [11, 12]. The control group received a base diet and underwent a sham operation. The control group initially consisted of 15 rats, with 12 remaining at the end of the experiment and 10 ultimately included in the statistical analysis after outlier exclusion. The disease group initially had 25 rats, of which 15 completed the experiment and 10 were included in the statistical analysis following the exclusion of outliers.
Model establishment success evaluation scheme
The success of the CHDMD rat model was evaluated based on three criteria: ECG readings, behavioral assessments, and myocardial enzyme levels. The model was considered successfully established if the following conditions were met: ECG showed ischemic changes, such as T wave inversion, ST-segment elevation, or pathological Q waves; behavioral tests indicated depressive-like behaviors or states; and the levels of all three myocardial enzymes—lactate dehydrogenase (LDH), creatine kinase (CK), and CK-MB—were elevated.
Electrocardiogram
After an intraperitoneal injection of sodium pentobarbital for anesthesia, the hair on the rats’ left and right forelimbs, left and right hindlimbs, and left precordial area was shaved. The rats were fixed on an operation board, with the LL lead connected to the left hind limb, RL lead to the right hindlimb, RA lead to the right forelimb, LA lead to the left forelimb, and V lead to the precordial area. Electrocardiogram (ECG) was recorded for 1 min.
Animal behavior
Open field test: The open field test was conducted using a rat open field test box, and the ANY-maze behavioral analysis system was used to measure the total distance traveled, number of rearing events, and grooming episodes within specific areas over a set period. The specific method was performed as previously described [13]. These measures reflect the degree of depression in rats; deeper depression correlates with shorter total distance moved and fewer rearing and grooming behaviors.
Elevated plus maze test: The rats were assessed using an elevated plus maze and the ANY-maze system to measure the number of entries into the open arms and the time spent in the open arms, following the method described by Bertoglio and Carobrez [14]. Higher levels of depression were correlated with fewer open arm entries and shorter time spent in the open arms.
Forced swim test: The rats were assessed in a forced swim cylinder using the ANY-maze system to measure the total immobility time and number of dives, following the method described by Shoji and Miyakawa [15]. Higher levels of depression were correlated with longer immobility times and fewer dives.
Myocardial enzymes
LDH, CK, and CK-MB levels were measured using kits from Nanjing Jiancheng Bioengineering Institute, China. The absorbance of each well was measured using a microplate reader to determine LDH level. CK level was determined using absorbance measurements from an ultraviolet-visible spectrophotometer and a standard curve provided with the kit. CK-MB level was determined based on absorbance measurements before and after a 3-min 37 °C incubation.
Serum lipid analysis
Serum levels of total cholesterol (TC), triglycerides (TGs), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were quantified using kits from the same institute, and absorbance was measured to calculate the respective levels.
Hematoxylin and eosin (H&E) staining
Heart tissues were fixed, sectioned, and stained with H&E to evaluate myocardial cell structure.
Fecal sample collection
Feces from eight CHDWD model rats and eight healthy rats were collected, mixed, and placed in sterile tubes. The feces were diluted with sterile saline (feces: saline = 1:10), homogenized for 5 min, vortexed for 1 min, and centrifuged at 800–1200 revolutions per minute at 4 °C for 3 min. The supernatant was collected, and the bacterial content (expressed as AVS abundance) was 56,282. The supernatant was stored at − 20 °C.
Microbiota transplantation
Fecal microbiota transplantation (FMT) was performed according to the methods described by García-Lezana et al. [16] and Zhang et al. [17]. To facilitate the successful recolonization of the transplanted gut microbiota, the rats were administered omeprazole (50 mg/kg/day) by gavage for 3 d prior to transplantation to clear the gut. Then, 24 and 12 h before FMT, the rats were administered 1 mL and 2 mL of CitraFleet and 1 mL of pure water, respectively, to empty the intestines (specific composition according to Zhang et al.) [17]. As it has been reported that a single microbiota transplantation could last for at least 1–3 months, with evident effects after 1 month [18], we gavaged for 6 weeks to ensure repeated recolonization (10 mL/kg/day). Rats receiving autologous fecal gavage were used as controls (FMT-Normal group), A total of 10 rats were used, and 7 were included in the statistical analysis after excluding outliers). Rats receiving CHDWD rat feces (AVS abundance of 57361) were used as the experimental animals (FMT-Disease group). A total of 10 rats were used, of which 7 were included in the statistical analysis after excluding outliers. To investigate the association between the TLR4/MYD88/NF-κB pathway and CHDWD, CHDWD rats that had received fecal gavage and TAK-242 injection (3 mg/kg/day for 4 weeks) were included (FMT-Disease-TAK-242 group). A total of 10 rats were used, of which 7 were included in the statistical analysis after excluding outliers. In another group, diseased rats that received TAK-242 injection only (3 mg/kg/day for 4 weeks) were include (designated as the Disease + TAK-242 group). A total of 10 rats were used, of which 7 were included in the statistical analysis after excluding outliers; animals in the FMT-Disease and Disease groups served as controls. To study the therapeutic effects of long-term FMT in healthy rats, feces were collected from eight healthy rats and recolonization was repeated by gavage for 6 weeks. Animals in the Disease + Disease FMT group (control group; a total of 10 rats were used, of which 7 were included in the statistical analysis after excluding outliers) received autologous fecal microbiota (AVS abundance, 55686) transplantation, whereas animals in the Disease + Normal FMT group (a total of 10 rats were used, of which 7 were included in the statistical analysis after excluding outliers) received fecal microbiota from healthy rats (AVS abundance, 57361).
Enzyme-linked immunosorbent assay detection
Enzyme-linked immunosorbent assay kits (Wuhan Boster Biological Technology, China) were used for detecting the molecules. The standards were diluted to six concentrations and added to the plates, with each concentration in duplicates. The serum samples were added to duplicate wells. The corresponding reagents were added to each well, gently mixed, incubated, washed, and developed. Following this, the stop solution was added to wells, and absorbance was measured using a multifunctional microplate reader (UV-1100 from the Manufacturer Shanghai Meipuda Co., Ltd.)to estimate the concentration.
Quantitative reverse transcription polymerase chain reaction (PCR)
Heart and hippocampal tissues were minced and lysed to extract the RNA. Then, RNA concentration and purity were evaluated, and the RNA was reverse-transcribed into cDNA. Real-time quantitative PCR was performed using glyceraldehyde 3-phosphate dehydrogenase as the reference gene. Primers for TLR4, MYD88, NF-κBp65, inhibitory kappa B kinase (IKK)-β, tumor necrosis factor (TNF)-α, and nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (IκB-α) were designed and synthesized by Tianyi Huayu Gene Technology Co., Ltd. (Wuhan, China). Each sample was tested in triplicate, and the average value was used for relative quantification analysis using the 2−△△Ct method.
Western blotting
Heart and hippocampal tissues were minced and lysed to extract proteins. The proteins were quantified using a microplate reader (Batch No.: PC0020, Manufacturer: Solarbio). The proteins were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred onto polyvinylidene fluoride membranes (Batch No.: IPVH00010, Manufacturer: millipore). The membranes were blocked with non-fat milk and probed overnight with primary antibodies (TLR4, MYD88, NF-κBp65, IKKβ, TNF-α, and IκB-α) at 4 °C. The membranes were then incubated with secondary antibodies for 2 h at 22 °C (± 2 °C). Protein bands were visualized using ECL chemiluminescence reagents (Biosharp, Hefei, Anhui Province, China) and imaged. Band intensity was analyzed using the TANONGIS software (Tanon Life Science, Shanghai, China) to assess target gene expression.
16 S ribosomal ribonucleic acid high-throughput sequencing
Genomic DNA was extracted from rat feces using a MagPure Soil DNA KF Kit (Magen, China). The extracted DNA was analyzed using agarose gel electrophoresis. The V3–V4 region of the 16 S ribosomal ribonucleic acid (rRNA) gene was amplified using specific primers (343 F, 798R) and barcoding tags. The first round of PCR was performed using the Tks Gflex DNA polymerase (Takara, Japan). The amplicons were purified using magnetic beads, and the purified products were used as templates for the second round of PCR. The second PCR product was identified by electrophoresis and purified using magnetic beads. The purified products were quantified using Qubit. Sequencing was performed using an Illumina NovaSeq 6000 platform (OE Biotech Co., Ltd., Shanghai, China). Sequencing data were stored in the FASTQ format.
Bioinformatic analysis
Cutadapt was used to import FASTQ files; denoise, merge, and remove chimeric sequences; and perform quality control analysis to generate the ASV abundance tables. R was used with the QIIME 2 package for microbiota composition analysis at the phylum and genus levels and identification of dominant bacterial groups. The Silva database (version 138) was used for taxonomic classification using the q2-feature-classifier software. Alpha diversity differences between samples were compared using QIIME 2, and beta diversity was assessed using principal coordinates analysis (PCoA) based on unweighted UniFrac distance matrices calculated using R 4.0.4 (R Foundation for Statistical Computing, Vienna, Austria). Differential analysis was performed using analysis of variance (ANOVA), Kruskal–Wallis test, t-test, and Wilcoxon test based on R packages.
Statistical analyses
IBM SPSS Statistics for Windows version 20.0 (IBM Corp., Armonk, NY, USA) was used for the analysis, and the Origin 2021 software was used for plotting graphs. Data are presented as mean ± standard deviation for normally distributed data with homogeneity of variance, and comparisons between two groups were made using t-tests. A one-way ANOVA was used for multiple group comparisons. Data that were not normally distributed or had heterogeneity of variance are presented as medians (interquartile ranges) and analyzed using the Wilcoxon signed-rank test for two-group comparisons and the Kruskal–Wallis test for multiple group comparisons. Statistical significance was set at p < 0.05, with p < 0.01 indicating significant statistical differences.
Results
Successful establishment of the CHDWD rat model with a 60% success rate
In our study, the establishment of the CHDWD rat model was achieved with a 60% success rate (25 rats operated, 15 successfully modeled and survived), utilizing a combination of high-fat diet, CUMS intervention, and coronary artery ligation surgery. The model exhibited clinical similarities to patients with CHDWD, including lethargy, reduced responsiveness, loose stools, weight loss (Fig. 1a; **p < 0.01), decreased appetite (Fig. 1b; **p < 0.01), and ECG abnormalities, such as inverted T waves, ST-segment elevation, and pathological Q waves. Additionally, elevated levels of myocardial enzymes (LDH, CK, and CK-MB) and myocardial cell damage, as indicated by H&E staining, were observed, alongside dyslipidemia characterized by increased TC, TG, and LDL levels and decreased HDL levels (Fig. 1c–h; **p < 0.01). Therefore, this CHDWD rat model can be used in future CHDWD studies.
Fig. 1.
Assessment of a rat model of coronary heart disease and depression. a Comparison of changes in weight between the disease and control groups over 6 weeks. b Comparison of changes in dietary intake between the disease and control groups over 6 weeks. c, d Comparison of myocardial enzyme index between the disease and control groups after 6 weeks. e Comparison of electrocardiogram findings between the disease and control groups after 6 weeks. f Comparison of blood lipid indexes between the disease and control groups after 6 weeks. g Comparative map of depression test results between the disease and control groups after 6 weeks. h Comparison of cardiomyocytes between the disease and control groups after 6 weeks. Data are expressed as the means ± standard error of the mean. *p < 0.05, **p < 0.01
CHDWD altered gut microbiota composition
The fecal microbiota of the control and diseased rats was analyzed using high-throughput 16 S rRNA sequencing. Weighted PCoA Bray–Curtis distance analysis (Fig. 2a) indicated distinct microbial community structures between the diseased and control rats, with significant separation along the first principal coordinate (PC1) due to CHDWD. At the phylum level, there were increases in the abundances of Desulfobacterota and Campylobacterota in the diseased rats (Fig. 2b; **p < 0.01). At the family level, diseased rats showed a higher abundance of Helicobacteraceae, whereas the control rats had a higher abundance of Prevotellaceae. Additionally, we observed a decrease in the abundance of Bacteroidetes in rats with CHDWD, resulting in an increased Firmicutes/Bacteroidetes (F/B) ratio (Fig. 2c). These differences were also traceable to the genus level (Fig. 2d–f; *p < 0.05). Although the α-diversity at the ASV level showed no significant differences in species diversity (Fig. 2g), the microbial community structures of the diseased and control rats differed significantly at the phylum, family, and genus levels (detailed differential microbiota listed in Table 1). PICRUSt functional prediction revealed that compared with the gut microbiota of the control rats, that of the diseased rats displayed significantly different bacterial gene functions. These genes were primarily related to signal transduction, cell motility, immune system, environmental adaptation, and cardiovascular diseases, indicating that the gut microbiota of diseased rats was more active and aggressive (Fig. 2h, i; *p < 0.05), suggesting substantial changes in the gut microbiota during CHDWD development.
Fig. 2.
16 S ribosomal ribonucleic acid high-throughput sequencing analysis results. a Graph of weighted principal coordinate analysis based on Bray–Curtis distance. b, c Comparative diagram of microflora composition at the phyla level. d–f Comparative diagram of microflora composition at the family and genus levels. g A comparative map of α-phenotypic diversity at the AVS level of microflora. h, i Heatmap and bar plot depicting the Kyoto Encyclopedia of Genes and Genomes functional prediction of the gut microbiota in rats from the control and disease groups
Table 1.
Differences in microbiota between the control and disease groups
| Name | Degree of difference (p-value) | Relative abundance compared to control | Taxonomy level |
|---|---|---|---|
| Thermodesulfobacteriota | 3.16E-03 | Decreased | Phylum |
| Clostridia_UCG_014 | 2.06E-01 | Decreased | Genus |
| Parabacteroides | 8.27E-03 | Increased | Genus |
| Escherichia_Shigella | 9.29E-13 | Decreased | Genus |
| [Eubacterium]_coprostanoligenes_group | 2.72E-03 | Decreased | Genus |
| Lactobacillus | 4.46E-01 | Decreased | Genus |
| Ruminococcus | 2.48E-05 | Decreased | Genus |
| Turicibacter | 7.85E-01 | Increased | Genus |
| Odoribacter | 4.13E-04 | Increased | Genus |
| Bacteroidales_RF16_group | 4.16E-04 | Decreased | Genus |
| UCG_010 | 9.84E-05 | Decreased | Genus |
| GCA_900066575 | 1.76E-03 | Increased | Genus |
| Prevotellaceae_Ga6A1_group | 0.00E + 00 | Decreased | Genus |
| Dorea | 3.07E-03 | Increased | Genus |
| UCG_007 | 6.81E-02 | Increased | Genus |
| Candidatus_Stoquefichus | 2.63E-08 | Increased | Genus |
| Staphylococcus | 2.19E-03 | Increased | Genus |
| Streptococcus | 4.56E-06 | Decreased | Genus |
| Erysipelatoclostridium | 9.16E-08 | Increased | Genus |
| [Ruminococcus]_gauvreauii_group | 0.00E + 00 | Increased | Genus |
| Clade_Ia | 2.51E-01 | Decreased | Genus |
| Lachnospiraceae_UCG_006 | 0.00E + 00 | Increased | Genus |
| Candidatus_Soleaferrea | 4.80E-04 | Increased | Genus |
| Family_XIII_UCG_001 | 8.23E-10 | Increased | Genus |
| Fournierella | 0.00E + 00 | Decreased | Genus |
| Oribacterium | 0.00E + 00 | Decreased | Genus |
Transplantation of microbiota from rats with CHDWD increased susceptibility to CHDWD in healthy rats
To investigate the role of the gut microbiota in CHDWD, we conducted a 6-week FMT in two groups of healthy rats using autologous feces (FMT-Normal) and CHDWD feces (FMT-Disease). After 6 weeks, we analyzed the 16 S rRNA gene sequences of the fecal microbiota in both groups. Weighted Bray–Curtis distance analysis based on ASV showed that the microbial community structures of the FMT-Normal and FMT-Disease groups were completely separated (Fig. 3a). The top 15 differential microbial communities at the family level confirmed successful transplantation, with the donor microbiota successfully colonizing the recipient rat intestines (Fig. 3b). This change was also observed at the phylum level with a significant reduction in the F/B ratio (Fig. 3c). The detailed differential microbiota compositions are shown in Table 2. PICRUSt functional prediction revealed that compared with the gut microbiota of FMT-Normal rats, that of the FMT-Diseased rats exhibited significantly different bacterial gene functions. Notably, the expression of genes related to the circulatory system was markedly reduced, indicating that the gut microbiota of FMT-Diseased rats were less active (Fig. 3d, e; *p < 0.05). These results validated that the CHDWD fecal microbiota successfully altered the gut microbiota ecosystem in healthy rats.
Fig. 3.
Results of 16 S ribosomal ribonucleic acid high-throughput sequencing of fecal microorganism transplantation group. a Graph of weighted principal coordinate analysis based on Bray–Curtis distance. b Comparative diagram of microflora composition at the family level. c Comparative diagram of microflora composition at the phyla level. d, e Heatmap and bar plot depicting the Kyoto Encyclopedia of Genes and Genomes functional prediction of the gut microbiota in fecal microbiota transplantation (FMT)-Normal and FMT-Diseased Rats
Table 2.
Differences in microbiota between the FMT-Normal and FMT-Disease groups
| Microbiota | Degree of difference (p-value) | Relative abundance compared to control | Taxonomy level |
|---|---|---|---|
| Campilobacterota | 8.72E-02 | Decreased | Phylum |
| Deferribacterota | 5.25E-02 | Decreased | Phylum |
| Alloprevotella | 2.04E-01 | Decreased | Genus |
| Bacteroides | 5.45E-01 | Increased | Genus |
| Helicobacter | 8.72E-02 | Decreased | Genus |
| Parasutterella | 6.64E-03 | Increased | Genus |
| Turicibacter | 5.76E-03 | Increased | Genus |
| Anaerovibrio | 1.04E-05 | Decreased | Genus |
| Clostridium_sensu_stricto_1 | 1.47E-01 | Increased | Genus |
| Allobaculum | 9.93E-06 | Increased | Genus |
| Bifidobacterium | 0.00E + 00 | Increased | Genus |
| Acinetobacter | 5.53E-05 | Increased | Genus |
| Odoribacter | 3.20E-07 | Decreased | Genus |
| Bilophila | 6.21E-08 | Increased | Genus |
| UCG_004 | 0.00E + 00 | Decreased | Genus |
| [Eubacterium]_nodatum_group | 3.31E-05 | Increased | Genus |
| Anaerovorax | 5.25E-02 | Decreased | Genus |
| Pygmaiobacter | 0.00E + 00 | Increased | Genus |
| Rs_E47_termite_group | 2.19E-01 | Decreased | Genus |
| Lachnospiraceae_FCS020_group | 0.00E + 00 | Increased | Genus |
| Coriobacteriaceae_UCG_002 | 0.00E + 00 | Decreased | Genus |
| Oligella | 0.00E + 00 | Increased | Genus |
| Enterorhabdus | 0.00E + 00 | Increased | Genus |
| Paludicola | 0.00E + 00 | Decreased | Genus |
| Tyzzerella | 0.00E + 00 | Decreased | Genus |
| [Eubacterium]_ventriosum_group | 0.00E + 00 | Decreased | Genus |
As hypothesized, clinical manifestations of CHDWD were induced in FMT-Diseased rats, but not in FMT-Normal rats. The CHDWD fecal microbiota demonstrated a higher CHDWD-induction capacity than the fecal microbiota of the FMT-Normal group, causing recipients to exhibit sluggish responses, loose stools, weight loss (Fig. 4a; **p < 0.01), decreased appetite (Fig. 4b; **p < 0.01), and depressive behaviors (Fig. 4c; **p < 0.01). Additionally, Masson staining revealed disorganized cardiac cell arrangement, myocardial fiber breakage, edema, congestion, and rupture in FMT-Diseased rats (Fig. 4f), along with ST-segment elevation on ECG (Fig. 4e). Changes the serum lipid concentrations in the FMT-Diseased rats mirrored those observed in rats with CHDWD, with increased TC, TG, and LDL levels and decreased HDL levels (Fig. 4d; **p < 0.01). These findings indicate that the fecal microbiota from rats with CHDWD increases the susceptibility to double-heart disease in healthy rats.
Fig. 4.
Results of the disease susceptibility test after fecal microorganism transplantation. a Comparison of body weight changes within 6 weeks. b Comparative map of food intake changes in 6 weeks. c Comparative map of depression after 6 weeks. d Comparison of blood lipid indexes after 6 weeks. e Comparative electrocardiogram findings after 6 weeks. f Comparative map of cardiomyocytes after 6 weeks. Data are expressed as the means ± standard error of the mean. *p < 0.05, **p < 0.01
Microbial metabolite lipopolysaccharide promotes CHDWD development by activating the TLR4/MYD88/NF-κB inflammatory pathway
To determine the role of LPSs in CHDWD, serum samples were collected from the rats in the control, Diseased, FMT-Normal, and FMT-Diseased groups for LPS and inflammatory marker detection. Our results showed that the serum LPS levels were negatively correlated with the abundance of Clostridia_UCG-014, Escherichia-Shigella, and Alloprevotella (Fig. 5a, b) and positively correlated with Bacteroides (Fig. 5b). Additionally, we observed a reduced relative abundance of Clostridia_UCG-014 and Escherichia-Shigella in the diseased rats (Fig. 5c, d; *p < 0.05), a reduced relative abundance of Alloprevotella in the diseased rats (Fig. 5e; *p < 0.05), and an increased relative abundance of Bacteroides in the FMT-Diseased rats (Fig. 5f; **p < 0.01). Furthermore, LPS levels in the blood of the Diseased and FMT-Diseased rats were significantly higher than those in the blood of the control and FMT-Normal rats (Fig. 6a; **p < 0.01). The protein expression levels of TLR4, MYD88, NF-κBp65, IKKβ, and TNF-α in the heart and hippocampal tissues of the rats from the Disease and FMT-Diseased groups were elevated, whereas the IκB-α levels decreased (Fig. 6b, c, g, h, l–n; **p < 0.01). This finding suggests that LPSs mediate the inflammatory responses between cardiovascular disease and depression-like disorders.
Fig. 5.
Correlation analysis between lipopolysaccharide (LPS) levels and microbiota. a Redundancy analysis (RDA) results of LPS with the control and disease groups. b RDA results of LPS with the fecal microbiota transplantation (FMT)-Normal and FMT-Diseased groups. c Relative abundance of Clostridia_UCG-014 in the control and disease groups. d Relative abundance of Escherichia-Shigella in the control and disease groups. e Relative abundance of Alloprevotella in the FMT-Normal and FMT-Diseased groups. f Relative abundance of Bacteroides in the FMT-Normal and FMT-Diseased groups
Fig. 6.
Comparison of lipopolysaccharide (LPS) levels and inflammatory pathway indexes. a Comparative diagram of LPS content in the blood. b–e, l Comparison of the contents of inflammatory pathway indexes in hearts from each group. f, k Comparison of the results of forced swimming test in each group. g–j, n Comparative map depicting the inflammatory pathway indexes in the hippocampus of each group. Data are expressed as the means ± standard error of the mean. *p < 0.05, **p < 0.01
TAK-242 is an effective Toll-like receptor antagonist. To confirm whether LPSs mediate inflammatory responses through the TLR4/MYD88/NF-κB pathway, increasing CHDWD risk, TAK-242 (3 mg/kg, daily for 4 weeks) was administered to the Diseased and FMT-Diseased rats. Our results showed that LPS levels in the blood decreased after TAK-242 injection (Fig. 6a, **p < 0.01), along with reduced TLR4, MYD88, NF-κBp65, IKKβ, and TNF-α protein expression levels and elevated IκB-α levels in the heart and hippocampal tissues (Fig. 6d, e, i, j, l–n; **p < 0.01). Depression-like behaviors (as observed by the forced swim test) were suppressed (Fig. 6f, k; **p < 0.01), and myocardial damage was reduced (Fig. 7). These findings indicate that disease microbiota increase the susceptibility to CHDWD by elevating the systemic LPS levels, regulating the TLR4/MYD88/NF-κB inflammatory pathway.
Fig. 7.
Comparative chart depicting the heart condition in each group. a Comparative map of cardiac cells in each group. b Comparative electrocardiogram findings of each group
Long-term healthy microbiota transplantation reduced myocardial damage and depression-like behavior in CHDWD
Our previous findings (section "Microbial metabolite lipopolysaccharide promotes CHDWD development by sctivating the TLR4/MYD88/NF-κB inflammatory pathway") revealed that LPSs enhanced systemic inflammatory responses by binding to TLR4, leading to the accumulation of inflammatory markers in heart and hippocampal tissues. Therefore, we used healthy microbiota from diseased rats to evaluate the potential therapeutic effects of microbiota recolonization in rats with CHDWD.
Masson staining showed that the rats in the Disease + Normal FMT group had lower numbers of myocardial cell gaps and lesser degrees of edema, necrosis, and nuclear shrinkage than those in the Disease + Disease FMT group (Fig. 7a). The ECG signals also returned to near-normal levels (Fig. 7b). Moreover, the serum LPS levels in the Disease + Normal FMT group decreased significantly (Fig. 8a; **p < 0.01). Notably, the levels of inflammatory markers (TLR4, MYD88, NF-κBp65, IKKβ, and TNF-α) in the heart and hippocampal tissues were significantly reduced (Fig. 8b, c, e, f; **p < 0.01), whereas the levels of the anti-inflammatory factor IκB-α increased significantly. Finally, the occurrence of depression-like behaviors was suppressed in the rats from the Disease + Normal FMT group, as evidenced by the increased dive and struggle times in the forced swim test (Fig. 8d; **p < 0.01), indicating that these rats demonstrated stronger survival instincts than those in the Disease + Disease FMT group. Overall, our findings suggest that long-term healthy microbiota intervention can alleviate the clinical symptoms of CHDWD by inhibiting the signaling associated with the TLR4/MYD88/NF-κB inflammatory pathway.
Fig. 8.
Status of rats after treatment with healthy microflora. a Comparative diagram of blood lipopolysaccharide (LPS) levels. b, c Comparative map of inflammatory pathway indexes in the heart and hippocampus (PCR results). d Comparison of the results of forced swimming test in each group. e, f Comparative map of inflammatory pathway indexes in the heart and hippocampus (western blotting results). Data are expressed as the mean ± standard error of the mean. *p < 0.05, **p < 0.01
Discussion
In the present study, we developed a rat model of CHDWD and investigated the role of gut microbiota dysbiosis, systemic LPSs, and the TLR4/MYD88/NF-κB inflammatory pathway in CHDWD. Our study shifted the focus from the consequences of post-disease gut microbial imbalance to the potential of these imbalances to initiate disease, presenting new avenues for CHDWD management. Our findings revealed that gut dysbiosis was associated with increased levels of systemic LPSs, which activate the TLR4/MYD88/NF-κB pathway, enhancing CHDWD risk. Notably, depressive symptoms and myocardial damage were mitigated after the transplantation of microbiota from the healthy mice, indicating that the impact of CHDWD may be reversible. This highlights the potential of microbiota modulation as a therapeutic strategy for treating CHDWD.
Research has demonstrated differences in the gut microbiota composition between CHDWD patients and healthy individuals, indicating an imbalance of gut microbiota in the former [3]. Although the exact mechanisms underlying this imbalance remain unclear, factors such as the environment, diet, lifestyle, and medications can alter the gut microbiota and influence CHDWD development. Dysbiosis may lead to depressive symptoms and heart damage, further disrupting the gut environment and potentially exacerbating the disease. For example, an increase in the abundance of Desulfobacterota can lead to cognitive dysfunction and inflammatory cell infiltration in mice [19, 20], whereas an increase in the abundance of Campylobacterota is associated with inflammation and neurobehavioral deficits [21–23]. Moreover, an increased F/B ratio is associated with reduced short-chain fatty acid production, which, in turn, increases the risk of developing cardiovascular disease [24]. These findings support the close association between CHDWD progression and gut microbiota dysbiosis.
The gut microbiota can influence host metabolism through active metabolites, such as LPSs, which participate in the immune, endocrine, and microbiota–gut–brain axis pathways to regulate energy absorption, lipid metabolism, and inflammatory responses [25–28]. LPS is a notable pathogen-associated molecular pattern that is associated with the development of cardiovascular and neurological diseases. Elevated LPS levels in systemic circulation play a crucial role in the development of inflammation-related diseases, with inflammatory markers serving as key factors in the onset of cardiovascular diseases and depression-like behaviors. Upon entering the bloodstream through the intestinal mucosa, LPSs primarily act on TLR4 on cell membranes to regulate pro-inflammatory cytokine secretion, triggering complex immune-inflammatory and microbiota–gut–brain axis responses [17, 29, 30]. Therefore, we hypothesized that LPSs promote CHDWD progression by mediating systemic inflammatory responses. Our findings showed that in rats from the FMT-Disease group, the composition of intestinal microorganisms was disturbed, serum LPS levels were elevated, and the TLR4, MYD88, and NF-κB levels were increased in heart and hippocampal tissues. These changes were accompanied by depression-like behaviors and myocardial damage, confirming that LPSs mediate inflammatory responses and increase the susceptibility to cardiovascular and depression-like diseases. Additionally, our results revealed that both rats with CHDWD and rats transplanted with feces from rats with CHDWD exhibited gut microbiota dysbiosis. This dysbiosis was characterized by abnormally reduced relative abundances of Clostridia_UCG-014, Escherichia-Shigella, and Alloprevotella and an abnormally increased relative abundance of Bacteroides. These changes led to the elevation of the serum LPS levels, which was reversed by the transplantation of healthy microbiota. These findings indicate that LPS is a specific inducer of gut microbiota dysbiosis, leading to CHDWD manifestations and progressive accumulation in the host bloodstream, which activates inflammatory pathways in the heart and hippocampus and exacerbates the progression of the disease.
Recent scholarly work has illuminated the activation of inflammatory markers, including TLR4, MYD88, and NF-κB, within the cardiac and hippocampal tissues of individuals with cardiovascular and depressive conditions [31, 32]. TLR4, a pivotal innate immune recognition protein, has been well-studied and detected in various organs, such as the heart, brain ventricles, and choroid plexus. TLR4 initiates inflammatory responses by triggering downstream signaling molecules, such as MYD88 and NF-κB. These pathways are instrumental in modulating the expression of inflammatory genes and proteins, including IKK-β, TNF-α, and IκB-α, which are implicated in the pathogenesis of atherosclerosis and depression. This study highlights the significance of TLR4 and its associated pathways in the complex interplay between inflammation and the development of cardiovascular and mood disorders.
In the present study, we found that the TLR4/MYD88/NF-κB inflammatory pathway was activated in the heart and hippocampal tissues of rats with CHDWD and in rats transplanted with the fecal microbiota of rats with CHDWD, indicating that TLR4 was activated by LPSs produced by the transplantation of fecal microbiota from rats with CHDWD. Moreover, the expression of inflammatory markers, such as TLR4, was higher in the heart and hippocampal tissues of rats with CHDWD than in healthy rats, suggesting that LPS-induced CHDWD development depends on the host’s TLR4 specificity. Serum LPS levels can predict adverse prognoses in patients with CHDWD. Notably, the inhibition of the activity of TLR4-associated inflammatory factors can modulate inflammation and the levels of microbial metabolites, potentially intervening with in cardiac damage and depressive behavior; this indirectly proves the involvement of TLR4-associated inflammatory factors in the development of CHDWD caused by microbial dysbiosis. Our study also found that the TLR4 inhibitor TAK-242 effectively reversed myocardial damage and depressive behavior in rats receiving the fecal microbiota from the rats with CHDWD. Additionally, healthy microbiota transplantation significantly reduced the LPS levels, inhibited the activity of inflammatory markers (TLR4, MYD88, NF-κBp65, IKK-β, and TNF-α), activated anti-inflammatory factors (IκB-α), ameliorated myocardial cell damage, and suppressed the occurrence of depressive behaviors.
However, this study has a few limitations. Although we provided novel evidence for the associations among CHDWD development, the gut microbiota, and the heart–hippocampus–gut axis and the involvement of LPS and the TLR4/MYD88/NF-κB inflammatory pathway in these associations, several issues are yet to be clarified. Currently, no clear or universally accepted definition exists for gut microbiota dysbiosis. Moreover, although the therapeutic effects of FMT observed in animal models are promising, long-term clinical safety data supporting its application are lacking. As reported in previous studies, FMT can rapidly spread fatal infectious diseases [17, 33], whereas prebiotics or probiotics (e.g., Bifidobacterium breve, Lactobacillus casei, Lactobacillus bulgaricus, Lactobacillus acidophilus), vitamin D, and selenium can improve mental health, ameliorate inflammation, and normalize the levels of cholesterol metabolism markers in patients with double-heart disease [34]. In summary, the safety of long-term FMT or specific probiotics in patients with double-heart disease should be tested in actual clinical settings. Moreover, although the diet and housing environment of the experimental rats were carefully controlled, unknown factors may have influenced the gut microbiota. Therefore, further studies addressing these drawbacks are urgently required to elucidate the abnormal changes in the gut microbiota during CHDWD development.
Conclusion
Our study represents an experimental investigation of the mechanistic association between the gut microbiota and the pathology of double-heart disease. Our findings confirmed that gut microbiota dysbiosis is closely associated with the pathogenesis of CHDWD. Healthy microbiota can alleviate myocardial damage and depression-like behaviors in rats with CHDWD by inhibiting the signaling associated with the TLR4/MYD88/NF-κB inflammatory pathway and activating the anti-inflammatory factor IκB-α. Based on these results, we believe that regulating gut microbiota composition to block the TLR4/MYD88/NF-κB inflammatory pathway is a potential novel therapeutic strategy for treating CHDWD.
Supplementary Information
Acknowledgements
Not applicable.
Abbreviations
- CHD
Coronary heart disease
- LPS
Lipopolysaccharide
- TLR4
Toll-like receptor 4
- FMT
Fecal microbiota transplantation
- MYD88
Myeloid differentiation primary response protein 88
- NF-κB
Nuclear factor-kappa B
- rRNA
Ribosomal ribonucleic acid
- CUMS
Chronic unpredictable mild stress
- ECG
Electrocardiogram
- LDH
Lactate dehydrogenase
- CK
Creatine kinase
- TC
Total cholesterol
- TGs
Triglycerides
- HDL
High-density lipoprotein
- LDL
Low-density lipoprotein
- H&E
Hematoxylin and eosin
- IKK
Inhibitory kappa B kinase
- TNF
Tumor necrosis factor
- IκB-α
Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha
- PCR
Polymerase chain reaction
- PCoA
Principal coordinate analysis
- F/B
Firmicutes/Bacteroidetes
Authors’ contributions
YP: Writing – original draft, Data curation, Formal analysis, Investigation, and Methodology. YL: Investigation. GW: Investigation. YL: Investigation. PY: Investigation. PK: Investigation and Formal analysis. CZ: Investigation and Formal analysis CW: Investigation and Formal analysis, Funding acquisition. LY: Review and editing, Conceptualization, Funding acquisition, Project administration, and Resources. XL: Review & editing, Funding acquisition, Project administration, and Supervision. AND All authors reviewed the manuscript.
Funding
The authors (s) declare that they received financial support for the research, authorship, and publication of this article. This research was supported by the Key Project of the Guangxi Natural Science Foundation (2022GXNSFDA035086), Guangxi Young Scientists Fund (2021GXNSFBA196059), National Natural Science Foundation of China (82060835), and National Natural Science Foundation of China (82360900).
Data availability
The datasets generated and analysed during the current study are available in the NCBI’s SRA database repository, BioProject ID: PRJNA1207804, link: https://www.ncbi.nlm.nih.gov/sra/PRINA1207804.
Declarations
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Liqiang Yang, Email: ylq6606@163.com.
Xiaohong Li, Email: lsyuan2008@126.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated and analysed during the current study are available in the NCBI’s SRA database repository, BioProject ID: PRJNA1207804, link: https://www.ncbi.nlm.nih.gov/sra/PRINA1207804.