Huang-Lian-Jie-Du-Decoction alleviates atherosclerotic plaque and lipid profile in HFD-induced ApoE-/- mice involve the gut microbiota-mediated TMA/FMO3/TMAO axis

Huang-Lian-Jie-Du-Decoction alleviates atherosclerotic plaque and lipid profile in HFD-induced ApoE-/- mice involve the gut microbiota-mediated TMA/FMO3/TMAO axis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Huang-Lian-Jie-Du-Decoction alleviates atherosclerotic plaque and lipid profile in HFD-induced ApoE -/- mice involve the gut microbiota-mediated TMA/FMO3/TMAO axis Chaowen Fan, Jintao He, Shuwen Luo, Zunli Ke, Wenjia Wang, Weiyi Tian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6997421/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Huang-Lian-Jie-Du-Decoction (HLJDD), a classic traditional Chinese medicine formula, is commonly used clinically to improve atherosclerosis (AS). Previous studies have primarily focused on the mechanisms of action of its blood-absorbed compounds, while less attention has been paid to its effects on gut microbiota. The trimethylamine (TMA)/flavin-containing monooxygenase 3 (FMO3)/trimethylamine N-oxide (TMAO) pathway, co-mediated by gut bacteria and the liver, plays a critical role in AS-related dyslipidemia. Using ApoE −/− mice fed a high-fat diet, this study evaluated HLJDD's effects on AS and gut microbiota. Results showed HLJDD reduced atherosclerotic plaques, macrophage infiltration, hepatic lipid accumulation, and serum lipids. It also altered gut microbiota diversity, increasing Verrucomicrobia and Akkermansia while decreasing Dubosiella and Clostridium , a key TMA-producing genus. Furthermore, HLJDD significantly lowered serum TMA and TMAO levels and downregulated hepatic FMO3 protein expression in AS mice. Our results indicate that HLJDD ameliorates atherosclerotic lesions and improves lipid dysregulation in HFD-induced ApoE −/− mice. The underlying mechanism may involve regulation of the TMA/FMO3/TMAO axis, which is associated with alterations in gut microbial communities, especially reduced abundance of Clostridium , as well as suppressed hepatic FMO3. Health sciences/Diseases Biological sciences/Microbiology Atherosclerosis Huang-Lian-Jie-Du-Decoction Gut microbiota 16S rRNA gene sequencing FMO3 TMAO Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Atherosclerosis (AS) is a chronic vascular disease and the primary cause of cardiovascular diseases, posing a significant threat to human health [ 1 ] . Risk factors for AS are not limited to obesity, hypertension, diabetes, and metabolic syndrome. According to data from 2022, the prevalence of dyslipidemia and metabolic syndrome among adults in China was approximately 58.4% and 42.5%, respectively [ 2 ] . These high prevalence rates provide a significant pathological foundation for the elevated incidence of atherosclerotic cardiovascular diseases in the population. Although some conventional pharmaceuticals, such as statins (e.g., simvastatin, rosuvastatin, and atorvastatin), have been used clinically to treat AS, they still have many limitations [ 3 ] . Disturbance of lipid metabolism is one of the key drivers of atherosclerotic plaque formation, which is why a high-fat diet (HFD) is more likely to induce atherosclerosis [ 4 ] . In lipoprotein metabolism, high-density lipoprotein (HDL) levels are negatively associated with AS, and HDL2 has a greater role in protecting against AS compared to HDL3. low-density lipoprotein (LDL) levels are positively associated with AS, but small dense LDL (sdLDL) has a higher predictive value than regular LDL [ 5 ] . Additionally, oxidized low-density lipoprotein (oxLDL) phagocytosed by macrophages forms foam cells, which promotes the formation of atherosclerotic plaques [ 6 ] . Therefore, restoring lipid homeostasis is crucial for reducing the formation of atherosclerotic plaques. The intestine, as the body's largest immune organ, hosts a rich population of microorganisms that participate in the metabolism of dietary fiber to produce trimethylamine (TMA). Once TMA enters the bloodstream, it can be oxidized by flavin monooxygenase 3 (FMO3) in the liver to form trimethylamine N-oxide (TMAO) [ 7 ] . The research by Restini et al. [ 8 ] shows that endogenous TMAO and TMA can affect vascular smooth muscle directly and indirectly, thereby exacerbating the typical symptoms of atherosclerosis. Multiple studies have also reported that the TMA/FMO3/TMAO pathway, driven by gut microbiota, plays a critical regulatory role in lipid metabolic disorders associated with AS [ 9 – 11 ] . Huang-Lian-Jie-Du-Decoction (HLJDD) is a classic formula in traditional Chinese medicine (TCM) recorded in the book Wai-Tai-Mi-Yao . Generally, HLJDD plays a role in clearing heat and detoxifying in various diseases. Today, HLJDD is widely used clinically to treat inflammation and cardiovascular diseases without showing obvious side effects [ 12 ] . Recent studies have found that HLJDD can inhibit inflammation [ 13 ] , reduce blood lipids [ 14 ] , and remodel gut microbiota [ 15 ] . However, the specific mechanisms by which HLJDD treats AS are not yet fully elucidated, and its effects on AS-related microbiota have been rarely reported. In this study, we administered HLJDD to a HFD-induced AS mouse model to evaluate its effects on lipid profiles, atherosclerotic plaques in the carotid and aortic regions, macrophage infiltration in the aorta, and hepatic lipid deposition. To assess changes in gut microbiota composition, we utilized 16S rRNA gene sequencing and conducted correlation analysis of specific microbial taxa. Serum TMA and TMAO concentrations, as well as hepatic FMO3 protein expression levels, were measured to investigate whether HLJDD's modulation of gut microbiota impacts atherosclerosis through the TMA/FMO3/TMAO pathway. Finally, molecular docking analysis was conducted to predict key compounds involved in regulating hepatic FMO3 protein. Materials and methods Preparation and chemical profile of HLJDD HLJDD includes Coptis chinensis Franch. (CC), Scutellaria baicalensis Georgi (SB), Phellodendron chinense C.K.Schneid. (PC), and Gardenia jasminoides J.Ellis (GJ). These four herbs were obtained from Beijing Tongrentang (Guiyang Store, production license number: Wan 20160125, lot number: 200801, execution standard: the 2015 edition of the Pharmacopoeia of The People's Republic of China ) and identified by professor Shenghua Wei from the Guizhou University of TCM Chinese Herb Medicine Research Laboratory. Simvastatin Dispersible Tablets (Xinke, 10 mg, 14 tablets per box, product number: 3140884) were supplied by Guangzhou Nanxin Pharmaceutical Co., Ltd. Briefly, HLJDD was prepared according to the original formula with a compatibility ratio of 3:2:2:3 (CC 9 g, SB 6 g, PC 6 g, and GJ 9 g). Following conventional methods, the four herbs were grated, mixed, and soaked for 40 min. They were then boiled over high heat and simmered for an additional 40 minutes before filtration (herb-to-water ratio of 1:10, w/v). A second boiling was performed with a herb-to-water ratio of 1:8 (w/v). Subsequently, the two extracts were combined and concentrated to 2 g raw drug/mL. The final mixture was stored at 4 ℃ and freshly prepared once per week. The chemical profile of HLJDD aqueous decoction was analyzed using high-performance liquid chromatography (UltiMate 3000 RS, Thermo Fisher Scientific, USA) coupled with mass spectrometry (Q Exactive high-resolution mass spectrometer, Thermo Fisher Scientific, USA) (HPLC-MS/MS). Chromatographic separation was performed on an Ultimate AQ-C18 column (150 × 2.1 mm, 1.8 µ m, Welch, Shanghai, China). To prepare the sample, 200 µ L of the HLJDD aqueous decoction was mixed with 800 µ L of methanol, vortexed for 10 min, and then centrifuged at 13,000 rpm for 10 min. The supernatant was collected as the test sample. The mobile phase consisted of 0.1% formic acid in water (A) and methanol (B). The injection volume was 5 µ L, and the flow rate was set at 0.3 mL/min. The gradient elution conditions were as follows: 0–1 min, 2% B; 1–5 min, 2–20% B; 5–10 min, 20–50% B; 10–15 min, 50–80% B; 15–20 min, 80–95% B; 20–27 min, 95% B; 27–28 min, 95–2% B; 28–30 min, 2% B. The mass spectrometer was equipped with an electrospray ionization source and operated in both positive and negative ion switching modes. The detection mode was set to Full mass/dd-MS2, with resolutions of 70,000 and 17,500, respectively, and a scan range of m/z 100–1500. The electrospray voltage was set at 3.2 kV, and the capillary temperature was maintained at 300°C. High-purity argon was used as the collision gas, while nitrogen served as the sheath gas and auxiliary gas. The data were initially processed using Compound Discoverer software (v3.3) and subsequently searched and identified against the mzCloud database ( https://www.mzcloud.org/ ). Mice grouping and treatment All animal experiments in this study were conducted in strict accordance with the institutional guidelines for the care and use of laboratory animals and were approved by the Animal Care and Welfare Committee of Guizhou University of Traditional Chinese Medicine (Approval no: 20240033). Specific-pathogen-free male ApoE −/− mice, six-week-old and weighing 18 − 22 g, were obtained from Beijing Weitong Lihua Laboratory Animal Technology Co., Ltd. (Beijing, China, license number: SCXK (Beijing) 2021-0006). Male C57BL/6J mice under equal conditions were obtained from Sibeifu Biotechnology Co., Ltd. (Beijing, China, license number: SCXK (Beijing) 2024-0010). The ApoE −/− mice and C57BL/6J mice were housed at the Experimental Animal Center affiliated with Guizhou University of TCM. After one week of adaptive feeding, ApoE −/− mice were fed a HFD containing 21% fat and 0.15% cholesterol, while C57BL/6J mice were fed a regular diet. The mice were then randomly divided into the following groups ( n = 8): the HFD model (HFDM) group, the HLJDD low-dose (HLJDD_L) group, the HLJDD medium-dose (HLJDD_M) group, the HLJDD high-dose (HLJDD_H) group, the Simvastatin (ST) group, and the normal control (NC) group. Ten weeks later, ApoE −/− mice continued to receive the HFD and were intragastrically administered HLJDD at doses of 2.5 g/kg/day (HLJDD_L group), 5 g/kg/day (HLJDD_M group), and 10 g/kg/day (HLJDD_H group). The ST group received an aqueous solution of Simvastatin at 3.33 mg/kg/day. The HFDM group and the NC group were gavaged with normal saline. The volume of gavage for all mice was 0.1 mL/10 g, and treatments were administered once daily for six weeks. Samples collection After 16 weeks of treatment, the mice were fasted overnight with unrestricted access to water. Anesthesia was induced via intraperitoneal injection of 1.25% tribromoethanol at 0.2 mL/10 g. The depth of anesthesia was confirmed by the absence of toe-pinch and corneal reflexes. Following ocular protrusion via gentle traction on the neck skin, blood was collected from the retrobulbar venous plexus using a capillary glass tube. Subsequently, the mice were euthanized by cervical dislocation. Under aseptic conditions, the aorta, liver, and colon feces were harvested. One part was fixed in 4% neutral formaldehyde solution, while the other part was quickly frozen in liquid nitrogen and stored at − 80 ℃ for subsequent histopathological analysis, Western blotting, and intestinal flora sequencing. The blood was kept at room temperature for 2 h, then centrifuged at 3000 rpm for 10 min, and the serum was separated and stored at − 80 ℃ for biochemical index detection. Oil red O (ORO) and hematoxylin and eosin (H&E) ORO and H&E staining solutions were purchased from Servicebio (Wuhan, China). The specific staining steps were as follows: For ORO staining of the aorta, the entire aorta was placed in a fixative solution for more than 24 h, then removed and rinsed twice with PBS. The blood vessel was carefully cut open longitudinally and stained until the plaque on the inner wall turned orange or bright red. Staining was terminated, and images were taken and saved; For ORO staining of the liver and carotid artery, frozen sections of the liver lobe and right carotid artery were rewarmed and dried. These sections were fixed in a fixative solution for 15 min, washed with tap water, and dried. The sections were then immersed in an ORO dye solution for 8 − 10 min (covered to avoid light), counterstained with hematoxylin for 3 − 5 min, and mounted using glycerin gelatin mounting tablets. Under the microscope, the nuclei appeared blue, while lipid droplets appeared orange-red to bright red. For H&E staining of the aortic roots and liver lobe, sections were stained with hematoxylin for 3 − 5 min and eosin for 5 min, dehydrated, and mounted with neutral gum. Under the microscope, the cell nuclei appeared blue, and liver lipid degeneration was shown as hollow areas. Images were captured, saved, and analyzed using Image Pro Plus software (v6.0). Immunohistochemical (IH) staining To dewax the aorta sections, Xylene I and II were applied for 10 min each. Rehydration was performed using anhydrous ethanol I, anhydrous ethanol II, and gradient alcohol for 5 min each, followed by a 2-minute immersion in distilled water. The sections were then rinsed with PBS solution to repair the antigen. A 3% hydrogen peroxide solution incubated the sections for 20 min in the dark. The anti-CD68 antibody was subsequently added and incubated for 15 h. Next, the secondary antibody was applied and incubated for 50 min. DAB chromogenic solution was used to produce a brown positive signal. Hematoxylin was used for counterstaining for 3 min, after which ammonia was applied to turn the sections blue. After dehydrated, sections were observed and photographed under an optical microscope, and then analyzed using Image Pro Plus software (v6.0). Biochemical assessments Biochemical assay kits for high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TG) were obtained from the Jiancheng Institute of Biotechnology (Nanjing, China). ELISA kits for mouse HDL2, HDL3, sdLDL, TMA, and TMAO were obtained from MLBIO (Shanghai, China). The procedures were strictly followed according to the instructions provided with the kits. A Thermo Fisher Multiskan FC type multifunctional microplate reader (Thermo, USA) was used to test the results. Western blotting 50 mg of liver tissue was added to a centrifuge tube along with 500 µ L of RIPA lysate (Ya Enzyme, Shanghai, China) and 5 µ L of protease inhibitor. Each sample was homogenized and lysed, then centrifuged at 12,000 rpm for 10 min, and the supernatant was collected. A BCA protein level determination kit and the PAGE gel preparation kit were purchased from Solarbio (Beijing, China), and the procedures were carried out according to the instructions. Subsequently, 50 µ g of protein sample was loaded onto the gel, and electrophoresis was performed at 110 V. Wet transfer was conducted at a constant current of 300 mA for 1 h, transferring the protein to a poly(vinylidene fluoride) (0.45 µ m) membrane. The membranes were blocked with 5% skimmed milk powder for 1 h on a shaker at room temperature (RT). After being cut into small strips, the membranes were incubated with primary antibodies against Rabbit anti-FMO3 monoclonal antibody (1:5000, ab126711, Abcam, MA, USA) and anti-GAPDH antibody (1:10,000, abs173393, Absin, Shanghai, China) overnight at 4 ℃. The next day, the membranes were incubated with a secondary antibody, HRP-conjugated goat anti-rabbit antibody (1:20,000, abs20002, Absin, Shanghai, China), for 1 h at RT. Then, the ECL developer solution was applied to the membranes, which were exposed and imaged. ImageJ software was used to analyze the gray values of each set of images. 16S rRNA sequencing Fecal DNA was extracted using the E.Z.N.A.® Stool DNA Kit (Omega, USA) according to the manufacturer’s instructions. The total DNA was measured by LC-Bio (Hangzhou, China). Specific primers (341F: 5'-CCTACGGGNGGCWGCAG-3' and 805R: 5'-GACTACHVGGGTATCTAATCC-3') were used to amplify the V3-V4 region of the 16S rRNA gene in mouse colon contents (feces). The amplicon libraries were prepared for sequencing, and their size and quantity were evaluated using an Agilent 2100 bioanalyzer (Agilen, USA) and the Kapa library quantification kit for Illumina (Kapa Biosystems, MA, USA). Sequencing was performed on an Illumina NovaSeq PE250 platform (Biotree, Shanghai, China) according to the manufacturer's recommendations, provided by LC-Bio. DADA2 (v2019.7) was used to obtain the feature table and feature sequences. The plots were drawn with R version 4.1.3 on the OmicStudio platform ( https://www.omicstudio.cn ). Among them, the heatmap was generated on an online platform for data analysis and visualization ( https://www.bioinformatics.com.cn ). Molecular docking The entire molecular docking process was carried out in a Python (v3.10.6) virtual environment within Anaconda (v25.3.1). First, the small molecule compounds identified by HPLC-MS/MS were input into the PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ) to retrieve their SMILES. The SMILES were subsequently imported into SwissADME ( http://www.swissadme.ch/ ) to predict their pharmacokinetic properties and druglikeness. Based on the SMILES, molscrub (v0.1.1) was used to batch-generate 3D models of the compounds while performing optimization operations such as energy minimization, pH adjustment to 7.0, and conversion of boat conformations to chair conformations. The 3D models of the compounds were further processed using Meeko (v0.6.1), which included adding hydrogen atoms, calculating Gasteiger charges, identifying rotatable bonds, and constructing torsion trees. Since no suitable model for the human FMO3 protein was available in the PDB database, the protein sequence was retrieved from the UniProt database ( https://www.uniprot.org/ ). The AlphaFold3 online server ( https://alphafoldserver.com/ ) was then used to predict the 3D structure of FMO3. The FMO3 model was repaired and optimized using pdbfixer (v1.11), including standardizing amino acid residues, adding all missing heavy atoms and hydrogen atoms, as well as adjusting the pH to 7.0. Energy minimization was performed using OpenMM (v8.2.0) with the AMBER99SB force field. P2Rank (v2.5) [ 16 ] was employed to predict the active pockets of the processed FMO3 protein, and the pocket with the highest score and probability was selected as the docking pocket. Based on the P2Rank prediction results, the PyMOL plugin GetBox was used in open-source PyMOL (v2.5.0) to obtain the center coordinates and dimension parameters of the grid box based on the protein docking pocket. The FMO3 protein model was preprocessed for docking using Meeko. Batch molecular docking analysis was performed using QVina (v2.1) [ 17 ] with the Exhaustiveness parameter set to 32 to obtain the optimal binding conformations and affinity scores of all compounds with FMO3. The results were uploaded to the Protein-Ligand Interaction Profiler online platform ( https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index ) to analyze the interaction patterns of the small molecule-FMO3 complexes. 3D interaction diagrams were generated using open-source PyMOL. Statistical analysis Data are presented as mean ± standard deviation (SD). Significant differences among groups were assessed by one-way ANOVA followed by Tukey’s test for multiple comparisons. Statistical significance was set at p < 0.05 using GraphPad Prism (v9.0). Gut microbiome α diversity and β diversity were calculated by QIIME2, and the graphs were generated using the R package (v3.5.2). The Kruskal-Wallis test was used to analyze differences in flora among groups, with p < 0.05 considered statistically significant. The Spearman correlation analysis method was used to assess the correlation between the levels of gut flora and the indicators of TMA, FMO3, TMAO, TC, TG, HDL-C, LDL-C, sdLDL, and HDL2, with p < 0.05 indicating statistical significance. Results Effect of HLJDD on body weight, liver weight, and hepatic lipid accumulation in AS mice During the administration period, there was no notable variation in the body weight of the mice across the groups ( p > 0.05). However, there were notable changes in the liver index. Compared to the NC group, the liver index in the HFDM group increased significantly. After treatment with HLJDD, the liver index was significantly reduced ( p < 0.01) (Fig. 1 A, B). ORO and H&E staining were used to observe the accumulation of lipids in the liver tissue. The results showed that, compared to the NC group, the area of lipid droplets in the HFDM group increased significantly, with a marked increase in fatty degeneration and abnormal morphology and arrangement of hepatocytes. Compared to the HFDM group, the areas of lipid droplets and the degree of fatty degeneration were notably reduced in both the HLJDD and ST treatment groups, showing a dose-dependent relationship (Fig. 1 C, D). This indicates that intervention with HLJJD can improve hepatic lipid metabolism and reduce hepatocyte damage. HLJDD improves atherosclerotic plaque and macrophage infiltration in AS mice Images of ORO, H&E, and IH staining revealed that, compared to the NC group, the HFDM group had a significantly increased plaque area throughout the entire aorta, the right carotid artery, and at the aortic root, accompanied by evident macrophage infiltration in the aortic root. However, after treatment with HLJDD or ST, both the plaque area and macrophage infiltration in the mice were significantly reduced (Fig. 2 A − D). These results suggest that HLJDD intervention can reduce the severity of AS induced by a HFD in ApoE −/− mice, with effects similar to those of ST treatment. HLJDD reduces serum lipid levels in AS mice Compared to the NC group, the HFDM group showed a significant increase in TC, TG, LDL-C, and sdLDL levels ( p < 0.01), while HDL-C and HDL2 levels were significantly decreased ( p < 0.01). After treatment with HLJDD or ST, the trends in the aforementioned indicators were reversed. Furthermore, the high dose of HLJDD was more effective in lowering TC levels compared to simvastatin ( p 0.05). There were no significant differences in serum HDL3 levels among the groups ( p > 0.05) (Fig. 3 A − G). These data indicate that HLJDD can reduce the blood lipid abnormalities in AS mice induced by HFD. HLJDD changes the composition of gut microbiota in HFD-induced AS mice In the 16S rRNA sequencing analysis, indices such as chao1, shannon, and goods coverage, along with their respective rarefaction curves, were used to evaluate the α -diversity of the gut microbiota and the current sequencing depth. The data showed no significant difference in α -diversity indices among the NC group, HFDM group, HLJDD treatment groups, and ST group ( p > 0.05), and all groups had reached the maximum sequencing depth (Fig. 4 A − F). Principal component analysis (PCA), principal coordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS) analysis revealed significant separation of microbial community structures between groups ( p = 0.001, Stess = 0.19) (Fig. 4 G − I). The Venn diagram showed that the number of features in the HLJDD treatment groups increased with the concentration gradient compared to the HFD model group (Fig. 5 A), indicating that HLJDD affects the abundance of gut microbiota in HFD-induced ApoE −/− mice. Bacteroidetes, Firmicutes, Verrucomicrobia, and Proteobacteria are the predominant phyla in the gut microbiota. In comparison with the mice of NC group, AS mice exhibited a decreased proportion of Bacteroidetes and an elevated proportion of Firmicutes. Following treatment with HLJDD, the proportions of Bacteroidetes (with the exception of the high-dose group) and Verrucomicrobia were observed to increase, whereas the proportion of Firmicutes was reduced (Fig. 5 B). At the genus level, we also analyzed the abundance changes of major gut microbiota across the groups (Fig. 5 C). Furthermore, the Circos plots depict the compositional proportions of dominant species in each group and simultaneously showcases the distribution of these dominant species across the various groups (Fig. 5 D, E). To further identify specific microbial differences, we used linear discriminant analysis effect size (LEfSe) analysis (LDA > 3) to identify taxonomic associations among the gut microbiota and and to highlight taxa that significantly differed among the groups (Fig. 6 A, B; Supplementary Fig. 1). Additionally, we employed random forest (RF) analysis to evaluate the importance of differentially abundant bacteria at the phylum and genus levels. At the phylum level, the abundance of Verrucomicrobia significantly increased in the HLJDD treatment groups ( p < 0.05) (Fig. 7 A). At the genus level, HLJDD treatment significantly increased the abundances of Akkermansia , Odoribacter , Ruminococcus_1 , Desulfovibrio , and Alistipes ( p < 0.05), while significantly decreasing the abundances of Dubosiella , Clostridium , and Lachnospira ( p < 0.05) (Fig. 7 B). Among these, Verrucomicrobia, Akkermansia , Dubosiella , and Clostridium ranked at the forefront in terms of importance (Fig. 7 C, D), suggesting that these core microbial taxa are responsible for the changes in gut microbiota abundance caused by HLJDD. Given this observation, we performed Spearman correlation analyses to investigate the relationships among key bacterial genera and their associations with serum lipid and lipoprotein levels, as well as the levels of TMA and TMAO. The results showed that Akkermansia exhibited a positive correlation with Dubosiella and a negative correlation with Clostridium (Fig. 7 E). Moreover, Akkermansia was negatively associated with TC and HDL-C ( p < 0.05). Dubosiella was negatively associated with LDL-C ( p < 0.01) and positively associated with sdLDL ( p < 0.05). Clostridium was positively correlated with TMA ( p < 0.01) (Fig. 7 F). Briefly, the effects of HLJDD on the blood lipids of AS mice are primarily associated with these bacterial genera. HLJDD reduces FMO3 protein expression in the liver and serum levels of TMA and TMAO in AS mice To investigate whether the effect of HLJDD in improving AS is related to the TMA/FMO3/TMAO pathway, we separately measured the serum levels of TMA and TMAO, as well as the protein level of FMO3 in the liver. The data showed that compared to the NC group, the serum TMA and TMAO levels in the HFDM group significantly increased ( p < 0.01). The levels of TMA and TMAO in the HLJDD groups and the ST group were significantly lower than those in the HFDM group ( p < 0.01) (Fig. 8 A, B). Compared to the NC group, the expression of FMO3 in the liver of the HFDM group markedly increased ( p < 0.01), whereas it was significantly downregulated in the HLJDD groups ( p < 0.01) and the ST group ( p < 0.05) (Fig. 8 C). These findings imply that the gut microbiota and liver-mediated TMA/FMO3/TMAO pathway may be a key pathways through which HLJDD exerts its beneficial effects on AS in ApoE −/− mice induced by HFD. Molecular docking predicts potential compounds in HLJDD aqueous decoction targeting FMO3 protein Base peak chromatograms of the HLJDD aqueous decoction under positive and negative ionization modes in HPLC-MS/MS are presented in Fig. 9 A and 9 B. A total of 54 compounds were identified based on retention time (RT), molecular weight, m/z values, and matching scores from the mzCloud database, using a match score ≥ 90 and a mass deviation (Δm/z) within ± 5 ppm (Supplementary Table S1 ). To perform molecular docking between these 54 compounds and the FMO3 protein, we employed AlphaFold3 to predict the 3D structure of FMO3. A high-quality 3D model was successfully generated, with a global predicted local distance difference test (pLDDT) score of 91.68 and a predicted template modeling (pTM) score of 0.93 (Fig. 9 C). This model was subsequently submitted to P2Rank for prediction of the active site, resulting in a highly confident binding pocket with a confidence score of 98.63 and a probability of 0.996 (Fig. 9 D).Ultimately, 54 ligand–receptor complexes were generated, among which 27 exhibited a minimum binding energy ≤ − 7 kcal/mol, suggesting strong binding affinity [ 18 ] . Of these, 16 small-molecule ligands demonstrated favorable gastrointestinal (GI) absorption profiles and drug-likeness according to pharmacokinetic and drug-likeness predictions (Supplementary Table S2 ). Three ligand–receptor pairs with binding energies ≤ − 8 kcal/mol were selected for further analysis: limonin, berberine, and dihydrooroxylin A. These ligands complied with all Lipinski, Ghose, Veber, Egan, and Muegge rules and were confirmed as bioactive constituents present in the four component herbs based on data from the Traditional Chinese Medicine Systems Pharmacology database ( https://www.91tcmsp.com/#/home ). Potential interaction patterns were further analyzed, revealing hydrogen bonds, π–cation interactions, π–π stacking, hydrophobic contacts, and salt bridges (Fig. 9 E). Discussion In this study, we induced atherosclerotic typical pathological phenomena in ApoE −/− mice using a HFD, including the formation of atherosclerotic plaques, macrophage infiltration, and elevated blood lipids. Subsequently, we administered HLJDD and found that this intervention may mitigate atherosclerotic pathologies through the inhibition of the TMA/FMO3/TMAO pathway, which is co-mediated by the gut microbiota and the liver. The specific mechanism involves changes in the abundance of bacterial genera including Akkermansia , Dubosiella , and Clostridium , as well as the downregulation of FMO3 expression in the live. Our study is the first to link the improvement of AS by HLJDD with gut microbiota, and through HPLC-MS/MS and molecular docking analysis, we speculate that limonin, berberine, and dihydrooroxylin A in the HLJDD aqueous decoction play key roles in the anti-AS effects by targeting FMO3. HLJDD, known in English as “Huang-Lian-Jie-Du-Decoction (HLJDD)” or “Huang-Lain-Jie-Du-Tang (HLJDT)”, serves as representative TCM formula used for clearing heat and detoxifying. A PubMed search using the keywords “HLJDD” and “HLJDT” retrieved a total of 155 articles, with 100 of them related to diseases, involving 25 types of diseases (data retrieved until December 2024). The top five diseases include diabetes (16%), stroke (15%), Alzheimer's disease (13%), cancer (9%), and AS (7%). In AS-related research during the last five years, several studies have highlighted the anti-AS effects of HLJDD. Cai et al. [ 19 ] found that HLJDD could decrease M1 macrophage polarization and increase M2 macrophage polarization in both animal and cell-based AS models. Liang et al. [ 20 ] reported that HLJDD reduced lipid and inflammatory factor levels in HFD-induced AS rabbits. Yang et al. [ 21 ] demonstrated that HLJDD altered the serum lipid profile in HFD-fed ApoE −/− mice. Lin et al. [ 22 ] showed that HLJDD inhibited oxLDL-stimulated foam cell formation in vascular smooth muscle cells by enhancing autophagy. Zhou et al. [ 23 ] found that HLJDD enhanced the phagocytic efficiency of macrophages, accelerating the clearance of apoptotic vascular smooth muscle cells. These studies confirm that HLJDD has significant anti-AS effects, including reducing atherosclerotic plaque area, lipid deposition, and inflammation, which are consistent with our findings. Atherosclerotic plaques consist of extracellular lipid deposits, foam cells, and cellular remnants, and their formation and progression are closely associated with persistent dyslipidemia [ 24 ] . The liver is the central organ for lipid metabolism and the primary site for lipoprotein production. Excessive intake of lipids can lead to hepatic lipid deposition and metabolic dysfunction, causing a large amount of fat to remain in the blood, which in turn results in persistently elevated blood lipids, laying the foundation for AS plaque formation. Therefore, HFD-induced ApoE −/− mice often exhibit both fatty liver and atherosclerosis, as reflected in our results. After administering HLJDD, we observed significant improvements in serum total TC and TG levels, aortic lipid deposition, and plaques in the aortic root and carotid arteries. Additionally, the liver index and hepatic lipid deposition were markedly reduced. Furthermore, neither the HFD nor HLJDD intervention significantly affected the body weight of the mice. This suggests that AS is not directly related to body weight and also indicates that HLJDD has a certain level of safety within the experimental dose range. LDL-C tends to deposit on arterial walls, where it undergoes oxidation to form ox-LDL and simultaneously recruits macrophages. When macrophages engulf ox-LDL, they become foam cells, a critical event in the development of AS. In Addition, sdLDL is a particularly oxidizable subtype of LDL that is more capable of penetrating the arterial wall compared to regular LDL, thereby promoting the formation of foam cells by macrophages. Our data show that HLJDD intervention significantly reduced serum LDL-C and sdLDL in AS mice. IH detection of the macrophage marker CD68 revealed that HLJDD effectively decreased macrophage infiltration in the aortic walls, thereby inhibiting the further progression of AS. Moreover, HDL can reduce cholesterol accumulation in the arterial walls through reverse cholesterol transport. Among its subtypes, HDL2, which contains more apolipoproteins, is considered to have stronger anti-AS effects compared to HDL3. Our results indicate that HLJDD intervention increased serum HDL-C levels, specifically by increasing HDL2 rather than HDL3 in AS mice. The gut microbiota is known to indirectly regulate lipid metabolism and storage in the blood and tissues of mice and humans through dietary metabolites like short-chain fatty acids, secondary bile acids, and trimethylamine, as well as bacterial endotoxins like lipopolysaccharides. Therefore, changes in the gut microbiota profile are tightly associated with the onset and progression of AS. To observe the role of HLJDD on the gut microbiota, we used 16S rRNA sequencing technology to analyze the cecal contents of HFD-induced ApoE −/− mice. Our data indicate that there was no notable statistical difference in α -diversity under the condition that the rarefaction curve reaches the enough depth. However, the analysis of β -diversity (PCA and PCoA) showed that the intestinal flora was clearly clustered among the groups. The ratio of Firmicutes to Bacteroidetes (F/B ratio) is often used as one of the markers of gut microbiota dysbiosis. A Study [ 25 ] has shown that HFD can increase the F/B ratio, while Bacteroidetes contribute to the metabolism of bile acids and short-chain fatty acids [ 26 ] , which have positive effects in reducing the risk of AS. Therefore, an increase in the F/B ratio is correlated with a decrease in short-chain fatty acid synthesis, which can increase the risk of AS to some extent. Our study found that HLJDD can reduce the F/B ratio and also increase the abundance of Verrucomicrobia. At the genus level, combining RF analysis and Spearman correlation analysis results, we found that the increase in Akkermansia abundance and the decrease in Dubosiella and Clostridium abundances are key factors influencing the alterations in the gut microbiota profile of HFD-induced ApoE −/− mice, and are significantly correlated with the improvement of serum lipids and lipoprotein levels in AS. Akkermansia , a representative of Verrucomicrobia, is considered one of the most promising next-generation probiotics due to its potential to maintain intestinal barrier integrity, regulate host immune responses, and control glucose and energy metabolism [ 27 ] . The study by Khalili et al. [ 28 ] demonstrated that natural compounds from plants can improve AS in animal models by increasing the abundance of Akkermansia . Recent research has also found that Akkermansia improves fatty liver by producing acetate, which activates the 5-AMP activated protein kinase signaling pathway and inhibits fatty acid synthesis [ 29 ] . This mechanism may be linked to the increased abundance of Akkermansia and reduced hepatic lipid accumulation observed in AS mice after HLJDD intervention in our study. Notably, Clostridiales have been reported to contain the TMAO metabolic genes CutC/D [ 30 ] , and Wang et al. [ 31 ] found that when TMAO levels are reduced through dietary regulation, Clostridiales also significantly decrease. Additionally, our Spearman correlation analysis also showed a positive correlation between Clostridium and TMA. Therefore, we further speculate that the TMA/FMO3/TMAO pathway may contribute critically to the treatment of AS by HLJDD. Gut bacteria metabolize human-intaken choline, phosphatidylcholine, as well as L-carnitine to synthesize TMA, which is subsequently metabolized to TMAO in the liver. High concentrations of TMAO have been found to increase the risk of AS in both animal models and humans [ 32 ] . Current literature has extensively confirmed this. For instance, Bennett et al. [ 33 ] found that high blood TMAO levels activate cholesterol influx in macrophages, thus promoting foam cell formation. Zhu et al. [ 34 ] found that high blood TMAO levels increase platelet activity and the risk of thrombotic events, contributing to the development of AS. Seldin et al. [ 35 ] found that TMAO promotes the adhesion of endothelial cells to white blood cells and activates the nuclear factor κ B signaling pathway, upregulating the gene expression of inflammatory cytokines. Xiong et al. [ 36 ] also found a significant positive correlation between plasma TMAO and TG, and a significant negative correlation with HDL-C, revealing a potential link between TMAO and dyslipidemia in AS. To investigate whether HLJDD affects the TMA/FMO3/TMAO pathway, we measured the levels of TMA and TMAO in mouse serum as well as the expression of hepatic FMO3 protein. The results showed that HLJDD intervention significantly reduced serum TMA and TMAO levels. Combined with 16S rRNA sequencing data, this suggests that HLJDD alters the abundance of specific gut microbiota (e.g., Clostridiales ) during intestinal metabolism, thereby reducing TMA and TMAO concentrations and improving foam cell formation and lipid abnormalities in AS mice. In addition, we found that the expression of FMO3 protein in the livers of AS mice was significantly downregulated after HLJDD intervention, suggesting that the components of the HLJDD aqueous decoction that enter the liver may participate in the regulation of TMAO levels by targeting the FMO3 protein. Therefore, we performed molecular docking analysis to screen the compounds identified in the HLJDD aqueous decoction by HPLC-MS/MS, based on their docking affinity, intestinal absorption potential, and compliance with drug-likeness criteria. Our results suggest that limonin, berberine, and dihydrooroxylin A are likely key bioactive components of HLJDD that may interact with the hepatic FMO3 protein. Current research on HLJDD for the treatment of AS tends to focus on the effects of its blood-absorbed compounds, while neglecting the impact of compounds that are not easily absorbed and are subject to first-pass elimination in the gut and liver. For example, berberine, the main active component of Huanglian ( Coptis chinensis ) and Huangbo ( Phellodendron chinense ), is widely used in China for treating obesity, diabetes, AS, and metabolic diseases. However, Hua et al. [ 37 ] found that the plasma concentration of berberine in subjects is extremely low. Liu et al. [ 38 ] suggest that first-pass elimination in the gut and preferential accumulation in the liver may be one of the causes for the low plasma concentration. Furthermore, Ma et al. [ 39 ] found that feces is the primary excretion route for berberine. Since berberine cannot act on target cells via the bloodstream, its hypoglycemic effect must be closely related to the gut microbiota, as confirmed by a recent randomized controlled trial [ 40 ] . Interestingly, Jiang et al. [ 41 ] found that after oral administration of HLJDD to HFD-induced AS rats, the main active compounds such as baicalin, baicalein, wogonoside, and wogonin were detected at higher concentrations in the plasma and showed dose-dependent increases. In contrast, berberine, palmatine, and jatrorrhizine were present at very low concentrations and did not show dose-dependent increases. In addition, limonin, another active compound found in Huanglian and Huangbo, exhibits significant lipid-lowering and liver-protective effects. However, there are no reports on its application in the context of AS. Similar to berberine, limonin has poor bioavailability. After oral administration, the majority of limonin is metabolized and eliminated by the gut microbiota, with only a small fraction entering the liver, where it exerts complex effects on hepatic metabolic enzymes [ 42 ] . These studies indicate that the mechanism of action of HLJDD is not solely dependent on its blood-absorbed compounds, but should also take into account the effects of poorly absorbed compounds on the gut microbiota and liver. Conclusion This study demonstrated that HLJDD significantly ameliorates atherosclerotic plaque formation, dyslipidemia, and hepatic lipid abnormalities in HFD-induced ApoE −/− mice, with these effects being associated with modulation of the TMA/FMO3/TMAO pathway mediated by both the gut microbiota (such as Clostridium ) and liver. Furthermore, we hypothesize that poorly absorbed constituents in the HLJDD aqueous decoction, such as berberine and limonin, may play important roles in mediating these therapeutic effects. In recent years, research on TCM has predominantly focused on blood-absorbed compounds. Even network pharmacology studies often prioritize high oral bioavailability as a key criterion for identifying core active ingredients. However, this approach may underestimate the potential therapeutic value of compounds subjected to extensive first-pass metabolism in the gut and liver, thereby limiting their further exploration and development. The mechanisms of action of TCM are complex and typically involve synergistic interactions among multiple components. Compared with single compounds exerting specific functions, we propose that the combined effects of both systemically absorbed and poorly absorbed constituents likely represent the true therapeutic advantage of TCM formulas. Declarations Data availability The data presented in this study are available in the NCBI Sequence Read Archive repository (accession number: PRJNA1209248) and supplementary materials. Author contributions CF: Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. JH: Data curation, Formal analysis, Methodology, Resources, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. SL: Formal analysis, Methodology, Software, Validation, Writing - review & editing. ZK: Investigation, Methodology, Writing - review & editing. WW: Investigation, Methodology, Writing - review & editing. WT: Funding acquisition, Project administration, Supervision, Writing - review & editing. QY: Funding acquisition, Project administration, Supervision, Writing - review & editing. Funding This work was supported by Guiyang College of Traditional Chinese Medicine, 2018 Academic New Talent Cultivation and Innovation Exploration Project (Qiankehe platform talents-[2017] 5735-17), Traditional Chinese Medicine and Ethnic Medicine Guizhou Provincial Scientific Innovation Leading Talent Workstation, Guizhou Provincial Department of Science and Technology Plan Project (Qiankehe platform-KXJZ [2024] 034), Key Laboratory of Microbial and Infectious Disease Prevention & Control in Guizhou Province (Qiankehe platform talents-ZDSYS [2023] 004), Guizhou University of Traditional Chinese Medicine Talent Innovation Team (Gui Traditional Chinese Medicine TD He Zi [2023] 002). Competing interests The authors declare no competing interests. Ethics statement All animal experiments were performed in strict accordance with the ARRIVE guidelines and the institutional guidelines for the care and use of laboratory animals. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6997421","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":488765755,"identity":"345e493a-9c65-4dc9-90a4-ce16b769a09c","order_by":0,"name":"Chaowen Fan","email":"","orcid":"","institution":"Guizhou University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chaowen","middleName":"","lastName":"Fan","suffix":""},{"id":488765756,"identity":"df243223-b0e8-4aba-82f4-51d1b955c99f","order_by":1,"name":"Jintao He","email":"","orcid":"","institution":"Jinsui Kexin Road Traditional Chinese Medicine Clinic of Henan Zhongjing Zhang Guoyi Pavilion Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Jintao","middleName":"","lastName":"He","suffix":""},{"id":488765757,"identity":"3786535e-01ff-42ef-9471-b8f9a4b9cee4","order_by":2,"name":"Shuwen Luo","email":"","orcid":"","institution":"Kunming Municipal Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shuwen","middleName":"","lastName":"Luo","suffix":""},{"id":488765758,"identity":"ea4d4bc6-6e1a-4ee2-b176-61faf3b7c6f3","order_by":3,"name":"Zunli Ke","email":"","orcid":"","institution":"Guizhou University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zunli","middleName":"","lastName":"Ke","suffix":""},{"id":488765759,"identity":"ae192627-e1d8-4d5d-9394-6c55ce3138cd","order_by":4,"name":"Wenjia Wang","email":"","orcid":"","institution":"Guizhou University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wenjia","middleName":"","lastName":"Wang","suffix":""},{"id":488765760,"identity":"c7d470a7-13cf-4379-96b4-71ce09af0283","order_by":5,"name":"Weiyi Tian","email":"","orcid":"","institution":"Guizhou University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Weiyi","middleName":"","lastName":"Tian","suffix":""},{"id":488765761,"identity":"d2b4f909-d2c2-4882-be0d-6539ca8ef2a6","order_by":6,"name":"Qi Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBAC+/uHDxz4UCEhx8/eQKyeG2yJB2ecsTGW7DlAtBYe5cO8bWmJG24kEKmDcXYPwwGeM4cTN9x8vPEGQ41NNEEtzDJnDxyQqDhsPPN2WrEFw7G03AZCWtgY8hIOGJw5LNt3O8dMgrHhMGEtPAw5BgcS2w4zNtw8Q6QWCQmgloNtaYoTbvAQqcWA51jCwQZwIAP9kkCMXwzYmw9//gOOysMbb3yosSGsBUW7RAIpyiFaSNUxCkbBKBgFIwMAAG5SSiwsE30/AAAAAElFTkSuQmCC","orcid":"","institution":"Guizhou University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Qi","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2025-06-28 11:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6997421/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6997421/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87423068,"identity":"7d9dfeb6-f066-444e-9a8c-0d0b7d28f3ab","added_by":"auto","created_at":"2025-07-23 15:53:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":12425410,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on body weight, liver index, hepatocyte morphology, and lipid content in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e) Line graph showing changes in body weight during the six-week treatment period. (\u003cstrong\u003eB\u003c/strong\u003e) Comparison of liver indices among the groups. (\u003cstrong\u003eC\u003c/strong\u003e) ORO staining and (\u003cstrong\u003eD\u003c/strong\u003e) H\u0026amp;E staining images of the mice's livers. Data are presented as mean ± SD. Bars labeled with different letters indicate significant differences between group means (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), where the letters also represent the ranking of the means such that earlier letters correspond to larger means. ORO, oil red O; H\u0026amp;E, hematoxylin and eosin; NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/444b9ef52c029dc1264d162a.png"},{"id":87423107,"identity":"a8ef777e-c39c-4b95-a979-2547fad0696e","added_by":"auto","created_at":"2025-07-23 15:53:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13581842,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on atherosclerotic plaque and macrophage infiltration in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e) ORO staining images of whole aorta. (\u003cstrong\u003eB\u003c/strong\u003e) H\u0026amp;E staining images of the aortic root. (\u003cstrong\u003eC\u003c/strong\u003e) ORO staining images of the carotid artery. (\u003cstrong\u003eD\u003c/strong\u003e) CD68 immunohistochemistry detection images of the aorta. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group; ORO, oil red O; H\u0026amp;E, hematoxylin and eosin; IH, immunohistochemical staining.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/4bd2cbc197462a7d2ad97299.png"},{"id":87423070,"identity":"b2a721d6-52e7-45f1-be3a-69dfef40a81c","added_by":"auto","created_at":"2025-07-23 15:53:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":668442,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on serum lipid and lipoprotein levels in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e) Serum TC levels. (\u003cstrong\u003eB\u003c/strong\u003e) Serum TG levels. (\u003cstrong\u003eC\u003c/strong\u003e) Serum LDL-C levels. (\u003cstrong\u003eD\u003c/strong\u003e) Serum sdLDL levels. (\u003cstrong\u003eE\u003c/strong\u003e) Serum HDL-C levels. (\u003cstrong\u003eF\u003c/strong\u003e) Serum HDL2 levels. (\u003cstrong\u003eG\u003c/strong\u003e) Serum HDL3 levels. Data are presented as mean ± SD. Bars labeled with different letters indicate significant differences between group means (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), where the letters also represent the ranking of the means such that earlier letters correspond to larger means. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; sdLDL, small dense low-density lipoprotein; HDL-C, high-density lipoprotein cholesterol.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/81f2cc53d75eac4a8bf13097.png"},{"id":87423112,"identity":"bd9bcb4e-fbf8-40fc-af2d-11a29a60e9d9","added_by":"auto","created_at":"2025-07-23 15:53:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2077735,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of HLJDD on \u003cem\u003eα\u003c/em\u003e-diversity and \u003cem\u003eβ\u003c/em\u003e-diversity of gut microbiota in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e−\u003cstrong\u003eC\u003c/strong\u003e) Rarefaction curves from 16S rRNA sequencing. (\u003cstrong\u003eD\u003c/strong\u003e−\u003cstrong\u003eF\u003c/strong\u003e) Box plot of \u003cem\u003eα\u003c/em\u003e-diversity indices of the gut microbiota among the groups (ns: no significance). (\u003cstrong\u003eG\u003c/strong\u003e−\u003cstrong\u003eI\u003c/strong\u003e) PCA, PCoA, and NMDS analysis show the \u003cem\u003eβ\u003c/em\u003e-diversity of the gut microbiota in each group. Data are presented as mean ± SD. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group; PCA, principal component analysis; PCoA, principal coordinates analysis; NMDS, non-metric multidimensional scaling.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/9d0d52eb476297f2ba17dfd1.png"},{"id":87423595,"identity":"f1298ae8-6e29-4a93-ae1f-940f815d3033","added_by":"auto","created_at":"2025-07-23 16:01:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4226562,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on the gut microbiota diversity and abundance in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e) A Venn diagram illustrates the number of shared and unique features in gut microbiota composition across different groups. (\u003cstrong\u003eB\u003c/strong\u003e, \u003cstrong\u003eC\u003c/strong\u003e) Relative abundance of the microbiota at the phylum and genus levels across different groups. (\u003cstrong\u003eD\u003c/strong\u003e, \u003cstrong\u003eE\u003c/strong\u003e) Circos plots show the compositional proportions of dominant species in each group. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/53479d3789a3353b6e42824b.png"},{"id":87423073,"identity":"a6612cda-fe5c-4996-af28-367be7c2e071","added_by":"auto","created_at":"2025-07-23 15:53:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2702975,"visible":true,"origin":"","legend":"\u003cp\u003eLEfSe analysis. (\u003cstrong\u003eA\u003c/strong\u003e) LEfSe cladogram. (\u003cstrong\u003eB\u003c/strong\u003e) Bar chart of LDA value for dominant bacteria in each group from LEfSe analysis (LDA value \u0026gt; 3). In the LEfSe cladogram, different colored dots represent different species, dot size indicates species abundance, and the order from center to outer layers represents the taxonomic hierarchy from phylum to genus. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/5fb884117ca9115dfc4d2ba2.png"},{"id":87423592,"identity":"bad67fdf-fe62-40ac-9f69-0e2903b56a14","added_by":"auto","created_at":"2025-07-23 16:01:46","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1817118,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on the relative abundance, significance, and correlations of key differential bacteria at phylum and genus levels in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e,\u003cstrong\u003e B\u003c/strong\u003e) Comparison of relative abundance of key differential bacteria at phylum and genus levels across groups. (\u003cstrong\u003eC\u003c/strong\u003e,\u003cstrong\u003e D\u003c/strong\u003e) RF analysis comparing the importance of key differential bacteria at phylum and genus levels. (\u003cstrong\u003eE\u003c/strong\u003e, \u003cstrong\u003eF\u003c/strong\u003e) Correlation analysis of key differential bacterial genera and their associations with AS-related lipids, lipoproteins, and gut microbiota metabolites. *: \u003cem\u003ep \u0026lt;\u003c/em\u003e 0.05, **: \u003cem\u003ep \u0026lt;\u003c/em\u003e 0.01. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; sdLDL, small dense low-density lipoprotein; HDL-C, high-density lipoprotein cholesterol. TMA, trimethylamine; TMAO, trimethylamine N-oxide.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/2231a3376ae9f4b673252726.png"},{"id":87423598,"identity":"cbb92c77-5db8-4d05-b205-b096f6bd7d6d","added_by":"auto","created_at":"2025-07-23 16:01:47","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":841234,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of HLJDD on the TMA/FMO3/TMAO pathway in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eA\u003c/strong\u003e) Serum TMA levels. (\u003cstrong\u003eB\u003c/strong\u003e) Serum TMAO levels. (\u003cstrong\u003eC\u003c/strong\u003e) Liver FMO3 protein expression. Data are presented as mean ± SD. Bars labeled with different letters indicate significant differences between group means (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), where the letters also represent the ranking of the means such that earlier letters correspond to larger means. NC, the normal control group; HFDM, high-fat diet model group; HLJDD_L, the Huang-Lian-Jie-Du-Decoction low-dose group; HLJDD_M, the Huang-Lian-Jie-Du-Decoction medium-dose group; HLJDD_H, the Huang-Lian-Jie-Du-Decoction high-dose group; ST, the simvastatin group; TMA, trimethylamine; TMAO, trimethylamine N-oxide; FMO3, flavin-containing monooxygenase 3.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/a2119a0056f15efc919bf684.png"},{"id":87423084,"identity":"8586a434-d571-47af-916e-852ba4b658ed","added_by":"auto","created_at":"2025-07-23 15:53:47","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":3359366,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Base peak chromatogram in positive ion mode. (\u003cstrong\u003eB\u003c/strong\u003e) Base peak chromatogram in negative ion mode. (\u003cstrong\u003eC\u003c/strong\u003e) The 3D model of the FMO3 protein predicted by AlphaFold 3. (\u003cstrong\u003eD\u003c/strong\u003e) The docking pocket location of the FMO3 protein 3D model predicted by P2Rank. (\u003cstrong\u003eE\u003c/strong\u003e) Interaction patterns of limonin, berberine, and dihydrooroxylin A with FMO3. pIDDT, global predicted local distance difference test; pTM, predicted template modeling score.\u003c/p\u003e","description":"","filename":"Fig.9.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/689f14c4b6995591d65c8f8a.png"},{"id":87423113,"identity":"87a35c48-7926-47a3-a83b-02e2494e3e7b","added_by":"auto","created_at":"2025-07-23 15:53:50","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":3291345,"visible":true,"origin":"","legend":"\u003cp\u003eWorking model of HLJDD-mediated AS treatment. HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice exhibit typical atherosclerotic pathologies, including the formation of atherosclerotic plaques, macrophage infiltration, and elevated blood lipids. Oral administration of HLJDD improves the atherosclerotic condition by modulating the diversity and abundance of gut microbiota, such as \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eDubosiella\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e, and regulating the TMA/FMO3/TMAO pathway.\u003c/p\u003e","description":"","filename":"Fig.10.png","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/9afad38feaba11b96477fd19.png"},{"id":109800051,"identity":"53bc0902-6240-4f44-b433-580a88e72a37","added_by":"auto","created_at":"2026-05-22 15:35:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":41542079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/06325500-84cd-41b3-993a-b292f5606d1f.pdf"},{"id":87423115,"identity":"fe4d0a06-3506-4e7e-ba6f-ceb4062390de","added_by":"auto","created_at":"2025-07-23 15:53:50","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":487331,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial1.zip","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/e21a37be06a9a9e2e1e7e6c6.zip"},{"id":87423119,"identity":"38aa7dc1-8f6b-4340-9854-635a5c6dd741","added_by":"auto","created_at":"2025-07-23 15:53:51","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":127106150,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial2.zip","url":"https://assets-eu.researchsquare.com/files/rs-6997421/v1/2be1dcb78ae3c0c363b609dc.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eHuang-Lian-Jie-Du-Decoction alleviates atherosclerotic plaque and lipid profile in HFD-induced ApoE\u003csup\u003e-/-\u003c/sup\u003e mice involve the gut microbiota-mediated TMA/FMO3/TMAO axis\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAtherosclerosis (AS) is a chronic vascular disease and the primary cause of cardiovascular diseases, posing a significant threat to human health\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Risk factors for AS are not limited to obesity, hypertension, diabetes, and metabolic syndrome. According to data from 2022, the prevalence of dyslipidemia and metabolic syndrome among adults in China was approximately 58.4% and 42.5%, respectively\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. These high prevalence rates provide a significant pathological foundation for the elevated incidence of atherosclerotic cardiovascular diseases in the population. Although some conventional pharmaceuticals, such as statins (e.g., simvastatin, rosuvastatin, and atorvastatin), have been used clinically to treat AS, they still have many limitations\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDisturbance of lipid metabolism is one of the key drivers of atherosclerotic plaque formation, which is why a high-fat diet (HFD) is more likely to induce atherosclerosis\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In lipoprotein metabolism, high-density lipoprotein (HDL) levels are negatively associated with AS, and HDL2 has a greater role in protecting against AS compared to HDL3. low-density lipoprotein (LDL) levels are positively associated with AS, but small dense LDL (sdLDL) has a higher predictive value than regular LDL\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Additionally, oxidized low-density lipoprotein (oxLDL) phagocytosed by macrophages forms foam cells, which promotes the formation of atherosclerotic plaques\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Therefore, restoring lipid homeostasis is crucial for reducing the formation of atherosclerotic plaques.\u003c/p\u003e\u003cp\u003eThe intestine, as the body's largest immune organ, hosts a rich population of microorganisms that participate in the metabolism of dietary fiber to produce trimethylamine (TMA). Once TMA enters the bloodstream, it can be oxidized by flavin monooxygenase 3 (FMO3) in the liver to form trimethylamine N-oxide (TMAO)\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The research by Restini et al.\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e shows that endogenous TMAO and TMA can affect vascular smooth muscle directly and indirectly, thereby exacerbating the typical symptoms of atherosclerosis. Multiple studies have also reported that the TMA/FMO3/TMAO pathway, driven by gut microbiota, plays a critical regulatory role in lipid metabolic disorders associated with AS\u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHuang-Lian-Jie-Du-Decoction (HLJDD) is a classic formula in traditional Chinese medicine (TCM) recorded in the book \u003cem\u003eWai-Tai-Mi-Yao\u003c/em\u003e. Generally, HLJDD plays a role in clearing heat and detoxifying in various diseases. Today, HLJDD is widely used clinically to treat inflammation and cardiovascular diseases without showing obvious side effects\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Recent studies have found that HLJDD can inhibit inflammation\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, reduce blood lipids\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, and remodel gut microbiota\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. However, the specific mechanisms by which HLJDD treats AS are not yet fully elucidated, and its effects on AS-related microbiota have been rarely reported.\u003c/p\u003e\u003cp\u003eIn this study, we administered HLJDD to a HFD-induced AS mouse model to evaluate its effects on lipid profiles, atherosclerotic plaques in the carotid and aortic regions, macrophage infiltration in the aorta, and hepatic lipid deposition. To assess changes in gut microbiota composition, we utilized 16S rRNA gene sequencing and conducted correlation analysis of specific microbial taxa. Serum TMA and TMAO concentrations, as well as hepatic FMO3 protein expression levels, were measured to investigate whether HLJDD's modulation of gut microbiota impacts atherosclerosis through the TMA/FMO3/TMAO pathway. Finally, molecular docking analysis was conducted to predict key compounds involved in regulating hepatic FMO3 protein.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003ePreparation and chemical profile of HLJDD\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHLJDD includes \u003cem\u003eCoptis chinensis\u003c/em\u003e Franch. (CC), \u003cem\u003eScutellaria baicalensis\u003c/em\u003e Georgi (SB), \u003cem\u003ePhellodendron chinense\u003c/em\u003e C.K.Schneid. (PC), and \u003cem\u003eGardenia jasminoides\u003c/em\u003e J.Ellis (GJ). These four herbs were obtained from Beijing Tongrentang (Guiyang Store, production license number: Wan 20160125, lot number: 200801, execution standard: the 2015 edition of the \u003cem\u003ePharmacopoeia of The People's Republic of China\u003c/em\u003e) and identified by professor Shenghua Wei from the Guizhou University of TCM Chinese Herb Medicine Research Laboratory. Simvastatin Dispersible Tablets (Xinke, 10 mg, 14 tablets per box, product number: 3140884) were supplied by Guangzhou Nanxin Pharmaceutical Co., Ltd.\u003c/p\u003e\u003cp\u003eBriefly, HLJDD was prepared according to the original formula with a compatibility ratio of 3:2:2:3 (CC 9 g, SB 6 g, PC 6 g, and GJ 9 g). Following conventional methods, the four herbs were grated, mixed, and soaked for 40 min. They were then boiled over high heat and simmered for an additional 40 minutes before filtration (herb-to-water ratio of 1:10, w/v). A second boiling was performed with a herb-to-water ratio of 1:8 (w/v). Subsequently, the two extracts were combined and concentrated to 2 g raw drug/mL. The final mixture was stored at 4 ℃ and freshly prepared once per week.\u003c/p\u003e\u003cp\u003eThe chemical profile of HLJDD aqueous decoction was analyzed using high-performance liquid chromatography (UltiMate 3000 RS, Thermo Fisher Scientific, USA) coupled with mass spectrometry (Q Exactive high-resolution mass spectrometer, Thermo Fisher Scientific, USA) (HPLC-MS/MS). Chromatographic separation was performed on an Ultimate AQ-C18 column (150 \u0026times; 2.1 mm, 1.8 \u003cem\u003e\u0026micro;\u003c/em\u003em, Welch, Shanghai, China). To prepare the sample, 200 \u003cem\u003e\u0026micro;\u003c/em\u003eL of the HLJDD aqueous decoction was mixed with 800 \u003cem\u003e\u0026micro;\u003c/em\u003eL of methanol, vortexed for 10 min, and then centrifuged at 13,000 rpm for 10 min. The supernatant was collected as the test sample. The mobile phase consisted of 0.1% formic acid in water (A) and methanol (B). The injection volume was 5 \u003cem\u003e\u0026micro;\u003c/em\u003eL, and the flow rate was set at 0.3 mL/min. The gradient elution conditions were as follows: 0\u0026ndash;1 min, 2% B; 1\u0026ndash;5 min, 2\u0026ndash;20% B; 5\u0026ndash;10 min, 20\u0026ndash;50% B; 10\u0026ndash;15 min, 50\u0026ndash;80% B; 15\u0026ndash;20 min, 80\u0026ndash;95% B; 20\u0026ndash;27 min, 95% B; 27\u0026ndash;28 min, 95\u0026ndash;2% B; 28\u0026ndash;30 min, 2% B. The mass spectrometer was equipped with an electrospray ionization source and operated in both positive and negative ion switching modes. The detection mode was set to Full mass/dd-MS2, with resolutions of 70,000 and 17,500, respectively, and a scan range of m/z 100\u0026ndash;1500. The electrospray voltage was set at 3.2 kV, and the capillary temperature was maintained at 300\u0026deg;C. High-purity argon was used as the collision gas, while nitrogen served as the sheath gas and auxiliary gas. The data were initially processed using Compound Discoverer software (v3.3) and subsequently searched and identified against the mzCloud database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mzcloud.org/\u003c/span\u003e\u003cspan address=\"https://www.mzcloud.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMice grouping and treatment\u003c/b\u003e\u003c/p\u003e\u003cp\u003e All animal experiments in this study were conducted in strict accordance with the institutional guidelines for the care and use of laboratory animals and were approved by the Animal Care and Welfare Committee of Guizhou University of Traditional Chinese Medicine (Approval no: 20240033).\u003c/p\u003e\u003cp\u003eSpecific-pathogen-free male ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, six-week-old and weighing 18\u0026thinsp;\u0026minus;\u0026thinsp;22 g, were obtained from Beijing Weitong Lihua Laboratory Animal Technology Co., Ltd. (Beijing, China, license number: SCXK (Beijing) 2021-0006). Male C57BL/6J mice under equal conditions were obtained from Sibeifu Biotechnology Co., Ltd. (Beijing, China, license number: SCXK (Beijing) 2024-0010). The ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice and C57BL/6J mice were housed at the Experimental Animal Center affiliated with Guizhou University of TCM. After one week of adaptive feeding, ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice were fed a HFD containing 21% fat and 0.15% cholesterol, while C57BL/6J mice were fed a regular diet. The mice were then randomly divided into the following groups (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8): the HFD model (HFDM) group, the HLJDD low-dose (HLJDD_L) group, the HLJDD medium-dose (HLJDD_M) group, the HLJDD high-dose (HLJDD_H) group, the Simvastatin (ST) group, and the normal control (NC) group. Ten weeks later, ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice continued to receive the HFD and were intragastrically administered HLJDD at doses of 2.5 g/kg/day (HLJDD_L group), 5 g/kg/day (HLJDD_M group), and 10 g/kg/day (HLJDD_H group). The ST group received an aqueous solution of Simvastatin at 3.33 mg/kg/day. The HFDM group and the NC group were gavaged with normal saline. The volume of gavage for all mice was 0.1 mL/10 g, and treatments were administered once daily for six weeks.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSamples collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter 16 weeks of treatment, the mice were fasted overnight with unrestricted access to water. Anesthesia was induced via intraperitoneal injection of 1.25% tribromoethanol at 0.2 mL/10 g. The depth of anesthesia was confirmed by the absence of toe-pinch and corneal reflexes. Following ocular protrusion via gentle traction on the neck skin, blood was collected from the retrobulbar venous plexus using a capillary glass tube. Subsequently, the mice were euthanized by cervical dislocation. Under aseptic conditions, the aorta, liver, and colon feces were harvested. One part was fixed in 4% neutral formaldehyde solution, while the other part was quickly frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;80 ℃ for subsequent histopathological analysis, Western blotting, and intestinal flora sequencing. The blood was kept at room temperature for 2 h, then centrifuged at 3000 rpm for 10 min, and the serum was separated and stored at \u0026minus;\u0026thinsp;80 ℃ for biochemical index detection.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOil red O (ORO) and hematoxylin and eosin (H\u0026amp;E)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eORO and H\u0026amp;E staining solutions were purchased from Servicebio (Wuhan, China). The specific staining steps were as follows: For ORO staining of the aorta, the entire aorta was placed in a fixative solution for more than 24 h, then removed and rinsed twice with PBS. The blood vessel was carefully cut open longitudinally and stained until the plaque on the inner wall turned orange or bright red. Staining was terminated, and images were taken and saved; For ORO staining of the liver and carotid artery, frozen sections of the liver lobe and right carotid artery were rewarmed and dried. These sections were fixed in a fixative solution for 15 min, washed with tap water, and dried. The sections were then immersed in an ORO dye solution for 8\u0026thinsp;\u0026minus;\u0026thinsp;10 min (covered to avoid light), counterstained with hematoxylin for 3\u0026thinsp;\u0026minus;\u0026thinsp;5 min, and mounted using glycerin gelatin mounting tablets. Under the microscope, the nuclei appeared blue, while lipid droplets appeared orange-red to bright red. For H\u0026amp;E staining of the aortic roots and liver lobe, sections were stained with hematoxylin for 3\u0026thinsp;\u0026minus;\u0026thinsp;5 min and eosin for 5 min, dehydrated, and mounted with neutral gum. Under the microscope, the cell nuclei appeared blue, and liver lipid degeneration was shown as hollow areas. Images were captured, saved, and analyzed using Image Pro Plus software (v6.0).\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunohistochemical (IH) staining\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo dewax the aorta sections, Xylene I and II were applied for 10 min each. Rehydration was performed using anhydrous ethanol I, anhydrous ethanol II, and gradient alcohol for 5 min each, followed by a 2-minute immersion in distilled water. The sections were then rinsed with PBS solution to repair the antigen. A 3% hydrogen peroxide solution incubated the sections for 20 min in the dark. The anti-CD68 antibody was subsequently added and incubated for 15 h. Next, the secondary antibody was applied and incubated for 50 min. DAB chromogenic solution was used to produce a brown positive signal. Hematoxylin was used for counterstaining for 3 min, after which ammonia was applied to turn the sections blue. After dehydrated, sections were observed and photographed under an optical microscope, and then analyzed using Image Pro Plus software (v6.0).\u003c/p\u003e\u003cp\u003e\u003cb\u003eBiochemical assessments\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBiochemical assay kits for high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TG) were obtained from the Jiancheng Institute of Biotechnology (Nanjing, China). ELISA kits for mouse HDL2, HDL3, sdLDL, TMA, and TMAO were obtained from MLBIO (Shanghai, China). The procedures were strictly followed according to the instructions provided with the kits. A Thermo Fisher Multiskan FC type multifunctional microplate reader (Thermo, USA) was used to test the results.\u003c/p\u003e\u003cp\u003e\u003cb\u003eWestern blotting\u003c/b\u003e\u003c/p\u003e\u003cp\u003e50 mg of liver tissue was added to a centrifuge tube along with 500 \u003cem\u003e\u0026micro;\u003c/em\u003eL of RIPA lysate (Ya Enzyme, Shanghai, China) and 5 \u003cem\u003e\u0026micro;\u003c/em\u003eL of protease inhibitor. Each sample was homogenized and lysed, then centrifuged at 12,000 rpm for 10 min, and the supernatant was collected. A BCA protein level determination kit and the PAGE gel preparation kit were purchased from Solarbio (Beijing, China), and the procedures were carried out according to the instructions. Subsequently, 50 \u003cem\u003e\u0026micro;\u003c/em\u003eg of protein sample was loaded onto the gel, and electrophoresis was performed at 110 V. Wet transfer was conducted at a constant current of 300 mA for 1 h, transferring the protein to a poly(vinylidene fluoride) (0.45 \u003cem\u003e\u0026micro;\u003c/em\u003em) membrane. The membranes were blocked with 5% skimmed milk powder for 1 h on a shaker at room temperature (RT). After being cut into small strips, the membranes were incubated with primary antibodies against Rabbit anti-FMO3 monoclonal antibody (1:5000, ab126711, Abcam, MA, USA) and anti-GAPDH antibody (1:10,000, abs173393, Absin, Shanghai, China) overnight at 4 ℃. The next day, the membranes were incubated with a secondary antibody, HRP-conjugated goat anti-rabbit antibody (1:20,000, abs20002, Absin, Shanghai, China), for 1 h at RT. Then, the ECL developer solution was applied to the membranes, which were exposed and imaged. ImageJ software was used to analyze the gray values of each set of images.\u003c/p\u003e\u003cp\u003e\u003cb\u003e16S rRNA sequencing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFecal DNA was extracted using the E.Z.N.A.\u0026reg; Stool DNA Kit (Omega, USA) according to the manufacturer\u0026rsquo;s instructions. The total DNA was measured by LC-Bio (Hangzhou, China). Specific primers (341F: 5'-CCTACGGGNGGCWGCAG-3' and 805R: 5'-GACTACHVGGGTATCTAATCC-3') were used to amplify the V3-V4 region of the 16S rRNA gene in mouse colon contents (feces). The amplicon libraries were prepared for sequencing, and their size and quantity were evaluated using an Agilent 2100 bioanalyzer (Agilen, USA) and the Kapa library quantification kit for Illumina (Kapa Biosystems, MA, USA). Sequencing was performed on an Illumina NovaSeq PE250 platform (Biotree, Shanghai, China) according to the manufacturer's recommendations, provided by LC-Bio. DADA2 (v2019.7) was used to obtain the feature table and feature sequences. The plots were drawn with R version 4.1.3 on the OmicStudio platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicstudio.cn\u003c/span\u003e\u003cspan address=\"https://www.omicstudio.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Among them, the heatmap was generated on an online platform for data analysis and visualization (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.com.cn\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.com.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMolecular docking\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe entire molecular docking process was carried out in a Python (v3.10.6) virtual environment within Anaconda (v25.3.1). First, the small molecule compounds identified by HPLC-MS/MS were input into the PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to retrieve their SMILES. The SMILES were subsequently imported into SwissADME (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to predict their pharmacokinetic properties and druglikeness. Based on the SMILES, molscrub (v0.1.1) was used to batch-generate 3D models of the compounds while performing optimization operations such as energy minimization, pH adjustment to 7.0, and conversion of boat conformations to chair conformations. The 3D models of the compounds were further processed using Meeko (v0.6.1), which included adding hydrogen atoms, calculating Gasteiger charges, identifying rotatable bonds, and constructing torsion trees. Since no suitable model for the human FMO3 protein was available in the PDB database, the protein sequence was retrieved from the UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The AlphaFold3 online server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://alphafoldserver.com/\u003c/span\u003e\u003cspan address=\"https://alphafoldserver.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was then used to predict the 3D structure of FMO3. The FMO3 model was repaired and optimized using pdbfixer (v1.11), including standardizing amino acid residues, adding all missing heavy atoms and hydrogen atoms, as well as adjusting the pH to 7.0. Energy minimization was performed using OpenMM (v8.2.0) with the AMBER99SB force field. P2Rank (v2.5)\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e was employed to predict the active pockets of the processed FMO3 protein, and the pocket with the highest score and probability was selected as the docking pocket. Based on the P2Rank prediction results, the PyMOL plugin GetBox was used in open-source PyMOL (v2.5.0) to obtain the center coordinates and dimension parameters of the grid box based on the protein docking pocket. The FMO3 protein model was preprocessed for docking using Meeko. Batch molecular docking analysis was performed using QVina (v2.1)\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e with the Exhaustiveness parameter set to 32 to obtain the optimal binding conformations and affinity scores of all compounds with FMO3. The results were uploaded to the Protein-Ligand Interaction Profiler online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plip-tool.biotec.tu-dresden.de/plip-web/plip/index\u003c/span\u003e\u003cspan address=\"https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to analyze the interaction patterns of the small molecule-FMO3 complexes. 3D interaction diagrams were generated using open-source PyMOL.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Significant differences among groups were assessed by one-way ANOVA followed by Tukey\u0026rsquo;s test for multiple comparisons. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 using GraphPad Prism (v9.0). Gut microbiome \u003cem\u003eα\u003c/em\u003e diversity and \u003cem\u003eβ\u003c/em\u003e diversity were calculated by QIIME2, and the graphs were generated using the R package (v3.5.2). The Kruskal-Wallis test was used to analyze differences in flora among groups, with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant. The Spearman correlation analysis method was used to assess the correlation between the levels of gut flora and the indicators of TMA, FMO3, TMAO, TC, TG, HDL-C, LDL-C, sdLDL, and HDL2, with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistical significance.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eEffect of HLJDD on body weight, liver weight, and hepatic lipid accumulation in AS mice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDuring the administration period, there was no notable variation in the body weight of the mice across the groups (\u003cem\u003ep\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). However, there were notable changes in the liver index. Compared to the NC group, the liver index in the HFDM group increased significantly. After treatment with HLJDD, the liver index was significantly reduced (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). ORO and H\u0026amp;E staining were used to observe the accumulation of lipids in the liver tissue. The results showed that, compared to the NC group, the area of lipid droplets in the HFDM group increased significantly, with a marked increase in fatty degeneration and abnormal morphology and arrangement of hepatocytes. Compared to the HFDM group, the areas of lipid droplets and the degree of fatty degeneration were notably reduced in both the HLJDD and ST treatment groups, showing a dose-dependent relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D). This indicates that intervention with HLJJD can improve hepatic lipid metabolism and reduce hepatocyte damage.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHLJDD improves atherosclerotic plaque and macrophage infiltration in AS mice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eImages of ORO, H\u0026amp;E, and IH staining revealed that, compared to the NC group, the HFDM group had a significantly increased plaque area throughout the entire aorta, the right carotid artery, and at the aortic root, accompanied by evident macrophage infiltration in the aortic root. However, after treatment with HLJDD or ST, both the plaque area and macrophage infiltration in the mice were significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026thinsp;\u0026minus;\u0026thinsp;D). These results suggest that HLJDD intervention can reduce the severity of AS induced by a HFD in ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, with effects similar to those of ST treatment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHLJDD reduces serum lipid levels in AS mice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCompared to the NC group, the HFDM group showed a significant increase in TC, TG, LDL-C, and sdLDL levels (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01), while HDL-C and HDL2 levels were significantly decreased (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01). After treatment with HLJDD or ST, the trends in the aforementioned indicators were reversed. Furthermore, the high dose of HLJDD was more effective in lowering TC levels compared to simvastatin (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01), and its effect on reducing the levels of LDL-C and sdLDL was comparable to that of simvastatin (\u003cem\u003ep\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). There were no significant differences in serum HDL3 levels among the groups (\u003cem\u003ep\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026thinsp;\u0026minus;\u0026thinsp;G). These data indicate that HLJDD can reduce the blood lipid abnormalities in AS mice induced by HFD.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHLJDD changes the composition of gut microbiota in HFD-induced AS mice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the 16S rRNA sequencing analysis, indices such as chao1, shannon, and goods coverage, along with their respective rarefaction curves, were used to evaluate the \u003cem\u003eα\u003c/em\u003e-diversity of the gut microbiota and the current sequencing depth. The data showed no significant difference in \u003cem\u003eα\u003c/em\u003e-diversity indices among the NC group, HFDM group, HLJDD treatment groups, and ST group (\u003cem\u003ep\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05), and all groups had reached the maximum sequencing depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026thinsp;\u0026minus;\u0026thinsp;F). Principal component analysis (PCA), principal coordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS) analysis revealed significant separation of microbial community structures between groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, Stess\u0026thinsp;=\u0026thinsp;0.19) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u0026thinsp;\u0026minus;\u0026thinsp;I). The Venn diagram showed that the number of features in the HLJDD treatment groups increased with the concentration gradient compared to the HFD model group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), indicating that HLJDD affects the abundance of gut microbiota in HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. Bacteroidetes, Firmicutes, Verrucomicrobia, and Proteobacteria are the predominant phyla in the gut microbiota. In comparison with the mice of NC group, AS mice exhibited a decreased proportion of Bacteroidetes and an elevated proportion of Firmicutes. Following treatment with HLJDD, the proportions of Bacteroidetes (with the exception of the high-dose group) and Verrucomicrobia were observed to increase, whereas the proportion of Firmicutes was reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). At the genus level, we also analyzed the abundance changes of major gut microbiota across the groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Furthermore, the Circos plots depict the compositional proportions of dominant species in each group and simultaneously showcases the distribution of these dominant species across the various groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, E).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further identify specific microbial differences, we used linear discriminant analysis effect size (LEfSe) analysis (LDA\u0026thinsp;\u0026gt;\u0026thinsp;3) to identify taxonomic associations among the gut microbiota and and to highlight taxa that significantly differed among the groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B; Supplementary Fig.\u0026nbsp;1). Additionally, we employed random forest (RF) analysis to evaluate the importance of differentially abundant bacteria at the phylum and genus levels. At the phylum level, the abundance of Verrucomicrobia significantly increased in the HLJDD treatment groups (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). At the genus level, HLJDD treatment significantly increased the abundances of \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eOdoribacter\u003c/em\u003e, \u003cem\u003eRuminococcus_1\u003c/em\u003e, \u003cem\u003eDesulfovibrio\u003c/em\u003e, and \u003cem\u003eAlistipes\u003c/em\u003e (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while significantly decreasing the abundances of \u003cem\u003eDubosiella\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e, and \u003cem\u003eLachnospira\u003c/em\u003e (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Among these, Verrucomicrobia, \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eDubosiella\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e ranked at the forefront in terms of importance (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, D), suggesting that these core microbial taxa are responsible for the changes in gut microbiota abundance caused by HLJDD. Given this observation, we performed Spearman correlation analyses to investigate the relationships among key bacterial genera and their associations with serum lipid and lipoprotein levels, as well as the levels of TMA and TMAO. The results showed that \u003cem\u003eAkkermansia\u003c/em\u003e exhibited a positive correlation with \u003cem\u003eDubosiella\u003c/em\u003e and a negative correlation with \u003cem\u003eClostridium\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). Moreover, \u003cem\u003eAkkermansia\u003c/em\u003e was negatively associated with TC and HDL-C (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). \u003cem\u003eDubosiella\u003c/em\u003e was negatively associated with LDL-C (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) and positively associated with sdLDL (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). \u003cem\u003eClostridium\u003c/em\u003e was positively correlated with TMA (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). Briefly, the effects of HLJDD on the blood lipids of AS mice are primarily associated with these bacterial genera.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHLJDD reduces FMO3 protein expression in the liver and serum levels of TMA and TMAO in AS mice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate whether the effect of HLJDD in improving AS is related to the TMA/FMO3/TMAO pathway, we separately measured the serum levels of TMA and TMAO, as well as the protein level of FMO3 in the liver. The data showed that compared to the NC group, the serum TMA and TMAO levels in the HFDM group significantly increased (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01). The levels of TMA and TMAO in the HLJDD groups and the ST group were significantly lower than those in the HFDM group (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA, B). Compared to the NC group, the expression of FMO3 in the liver of the HFDM group markedly increased (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01), whereas it was significantly downregulated in the HLJDD groups (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) and the ST group (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). These findings imply that the gut microbiota and liver-mediated TMA/FMO3/TMAO pathway may be a key pathways through which HLJDD exerts its beneficial effects on AS in ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice induced by HFD.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMolecular docking predicts potential compounds in HLJDD aqueous decoction targeting FMO3 protein\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBase peak chromatograms of the HLJDD aqueous decoction under positive and negative ionization modes in HPLC-MS/MS are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB. A total of 54 compounds were identified based on retention time (RT), molecular weight, m/z values, and matching scores from the mzCloud database, using a match score\u0026thinsp;\u0026ge;\u0026thinsp;90 and a mass deviation (Δm/z) within \u0026plusmn;\u0026thinsp;5 ppm (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). To perform molecular docking between these 54 compounds and the FMO3 protein, we employed AlphaFold3 to predict the 3D structure of FMO3. A high-quality 3D model was successfully generated, with a global predicted local distance difference test (pLDDT) score of 91.68 and a predicted template modeling (pTM) score of 0.93 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). This model was subsequently submitted to P2Rank for prediction of the active site, resulting in a highly confident binding pocket with a confidence score of 98.63 and a probability of 0.996 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eD).Ultimately, 54 ligand\u0026ndash;receptor complexes were generated, among which 27 exhibited a minimum binding energy\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;7 kcal/mol, suggesting strong binding affinity\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Of these, 16 small-molecule ligands demonstrated favorable gastrointestinal (GI) absorption profiles and drug-likeness according to pharmacokinetic and drug-likeness predictions (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Three ligand\u0026ndash;receptor pairs with binding energies\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;8 kcal/mol were selected for further analysis: limonin, berberine, and dihydrooroxylin A. These ligands complied with all Lipinski, Ghose, Veber, Egan, and Muegge rules and were confirmed as bioactive constituents present in the four component herbs based on data from the Traditional Chinese Medicine Systems Pharmacology database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.91tcmsp.com/#/home\u003c/span\u003e\u003cspan address=\"https://www.91tcmsp.com/#/home\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Potential interaction patterns were further analyzed, revealing hydrogen bonds, π\u0026ndash;cation interactions, π\u0026ndash;π stacking, hydrophobic contacts, and salt bridges (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we induced atherosclerotic typical pathological phenomena in ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice using a HFD, including the formation of atherosclerotic plaques, macrophage infiltration, and elevated blood lipids. Subsequently, we administered HLJDD and found that this intervention may mitigate atherosclerotic pathologies through the inhibition of the TMA/FMO3/TMAO pathway, which is co-mediated by the gut microbiota and the liver. The specific mechanism involves changes in the abundance of bacterial genera including \u003cem\u003eAkkermansia\u003c/em\u003e, \u003cem\u003eDubosiella\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e, as well as the downregulation of FMO3 expression in the live. Our study is the first to link the improvement of AS by HLJDD with gut microbiota, and through HPLC-MS/MS and molecular docking analysis, we speculate that limonin, berberine, and dihydrooroxylin A in the HLJDD aqueous decoction play key roles in the anti-AS effects by targeting FMO3.\u003c/p\u003e\u003cp\u003eHLJDD, known in English as \u0026ldquo;Huang-Lian-Jie-Du-Decoction (HLJDD)\u0026rdquo; or \u0026ldquo;Huang-Lain-Jie-Du-Tang (HLJDT)\u0026rdquo;, serves as representative TCM formula used for clearing heat and detoxifying. A PubMed search using the keywords \u0026ldquo;HLJDD\u0026rdquo; and \u0026ldquo;HLJDT\u0026rdquo; retrieved a total of 155 articles, with 100 of them related to diseases, involving 25 types of diseases (data retrieved until December 2024). The top five diseases include diabetes (16%), stroke (15%), Alzheimer's disease (13%), cancer (9%), and AS (7%). In AS-related research during the last five years, several studies have highlighted the anti-AS effects of HLJDD. Cai et al.\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e found that HLJDD could decrease M1 macrophage polarization and increase M2 macrophage polarization in both animal and cell-based AS models. Liang et al.\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e reported that HLJDD reduced lipid and inflammatory factor levels in HFD-induced AS rabbits. Yang et al.\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e demonstrated that HLJDD altered the serum lipid profile in HFD-fed ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. Lin et al.\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e showed that HLJDD inhibited oxLDL-stimulated foam cell formation in vascular smooth muscle cells by enhancing autophagy. Zhou et al.\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e found that HLJDD enhanced the phagocytic efficiency of macrophages, accelerating the clearance of apoptotic vascular smooth muscle cells. These studies confirm that HLJDD has significant anti-AS effects, including reducing atherosclerotic plaque area, lipid deposition, and inflammation, which are consistent with our findings.\u003c/p\u003e\u003cp\u003eAtherosclerotic plaques consist of extracellular lipid deposits, foam cells, and cellular remnants, and their formation and progression are closely associated with persistent dyslipidemia\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. The liver is the central organ for lipid metabolism and the primary site for lipoprotein production. Excessive intake of lipids can lead to hepatic lipid deposition and metabolic dysfunction, causing a large amount of fat to remain in the blood, which in turn results in persistently elevated blood lipids, laying the foundation for AS plaque formation. Therefore, HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice often exhibit both fatty liver and atherosclerosis, as reflected in our results. After administering HLJDD, we observed significant improvements in serum total TC and TG levels, aortic lipid deposition, and plaques in the aortic root and carotid arteries. Additionally, the liver index and hepatic lipid deposition were markedly reduced. Furthermore, neither the HFD nor HLJDD intervention significantly affected the body weight of the mice. This suggests that AS is not directly related to body weight and also indicates that HLJDD has a certain level of safety within the experimental dose range. LDL-C tends to deposit on arterial walls, where it undergoes oxidation to form ox-LDL and simultaneously recruits macrophages. When macrophages engulf ox-LDL, they become foam cells, a critical event in the development of AS. In Addition, sdLDL is a particularly oxidizable subtype of LDL that is more capable of penetrating the arterial wall compared to regular LDL, thereby promoting the formation of foam cells by macrophages. Our data show that HLJDD intervention significantly reduced serum LDL-C and sdLDL in AS mice. IH detection of the macrophage marker CD68 revealed that HLJDD effectively decreased macrophage infiltration in the aortic walls, thereby inhibiting the further progression of AS. Moreover, HDL can reduce cholesterol accumulation in the arterial walls through reverse cholesterol transport. Among its subtypes, HDL2, which contains more apolipoproteins, is considered to have stronger anti-AS effects compared to HDL3. Our results indicate that HLJDD intervention increased serum HDL-C levels, specifically by increasing HDL2 rather than HDL3 in AS mice.\u003c/p\u003e\u003cp\u003eThe gut microbiota is known to indirectly regulate lipid metabolism and storage in the blood and tissues of mice and humans through dietary metabolites like short-chain fatty acids, secondary bile acids, and trimethylamine, as well as bacterial endotoxins like lipopolysaccharides. Therefore, changes in the gut microbiota profile are tightly associated with the onset and progression of AS. To observe the role of HLJDD on the gut microbiota, we used 16S rRNA sequencing technology to analyze the cecal contents of HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. Our data indicate that there was no notable statistical difference in \u003cem\u003eα\u003c/em\u003e-diversity under the condition that the rarefaction curve reaches the enough depth. However, the analysis of \u003cem\u003eβ\u003c/em\u003e-diversity (PCA and PCoA) showed that the intestinal flora was clearly clustered among the groups. The ratio of Firmicutes to Bacteroidetes (F/B ratio) is often used as one of the markers of gut microbiota dysbiosis. A Study\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e has shown that HFD can increase the F/B ratio, while Bacteroidetes contribute to the metabolism of bile acids and short-chain fatty acids\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, which have positive effects in reducing the risk of AS. Therefore, an increase in the F/B ratio is correlated with a decrease in short-chain fatty acid synthesis, which can increase the risk of AS to some extent. Our study found that HLJDD can reduce the F/B ratio and also increase the abundance of Verrucomicrobia. At the genus level, combining RF analysis and Spearman correlation analysis results, we found that the increase in \u003cem\u003eAkkermansia\u003c/em\u003e abundance and the decrease in \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eClostridium\u003c/em\u003e abundances are key factors influencing the alterations in the gut microbiota profile of HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, and are significantly correlated with the improvement of serum lipids and lipoprotein levels in AS. \u003cem\u003eAkkermansia\u003c/em\u003e, a representative of Verrucomicrobia, is considered one of the most promising next-generation probiotics due to its potential to maintain intestinal barrier integrity, regulate host immune responses, and control glucose and energy metabolism\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. The study by Khalili et al.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e demonstrated that natural compounds from plants can improve AS in animal models by increasing the abundance of \u003cem\u003eAkkermansia\u003c/em\u003e. Recent research has also found that \u003cem\u003eAkkermansia\u003c/em\u003e improves fatty liver by producing acetate, which activates the 5-AMP activated protein kinase signaling pathway and inhibits fatty acid synthesis\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. This mechanism may be linked to the increased abundance of \u003cem\u003eAkkermansia\u003c/em\u003e and reduced hepatic lipid accumulation observed in AS mice after HLJDD intervention in our study. Notably, \u003cem\u003eClostridiales\u003c/em\u003e have been reported to contain the TMAO metabolic genes \u003cem\u003eCutC/D\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, and Wang et al.\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e found that when TMAO levels are reduced through dietary regulation, \u003cem\u003eClostridiales\u003c/em\u003e also significantly decrease. Additionally, our Spearman correlation analysis also showed a positive correlation between \u003cem\u003eClostridium\u003c/em\u003e and TMA. Therefore, we further speculate that the TMA/FMO3/TMAO pathway may contribute critically to the treatment of AS by HLJDD.\u003c/p\u003e\u003cp\u003eGut bacteria metabolize human-intaken choline, phosphatidylcholine, as well as L-carnitine to synthesize TMA, which is subsequently metabolized to TMAO in the liver. High concentrations of TMAO have been found to increase the risk of AS in both animal models and humans\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Current literature has extensively confirmed this. For instance, Bennett et al.\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e found that high blood TMAO levels activate cholesterol influx in macrophages, thus promoting foam cell formation. Zhu et al.\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e found that high blood TMAO levels increase platelet activity and the risk of thrombotic events, contributing to the development of AS. Seldin et al.\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e found that TMAO promotes the adhesion of endothelial cells to white blood cells and activates the nuclear factor \u003cem\u003eκ\u003c/em\u003eB signaling pathway, upregulating the gene expression of inflammatory cytokines. Xiong et al.\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e also found a significant positive correlation between plasma TMAO and TG, and a significant negative correlation with HDL-C, revealing a potential link between TMAO and dyslipidemia in AS. To investigate whether HLJDD affects the TMA/FMO3/TMAO pathway, we measured the levels of TMA and TMAO in mouse serum as well as the expression of hepatic FMO3 protein. The results showed that HLJDD intervention significantly reduced serum TMA and TMAO levels. Combined with 16S rRNA sequencing data, this suggests that HLJDD alters the abundance of specific gut microbiota (e.g., \u003cem\u003eClostridiales\u003c/em\u003e) during intestinal metabolism, thereby reducing TMA and TMAO concentrations and improving foam cell formation and lipid abnormalities in AS mice. In addition, we found that the expression of FMO3 protein in the livers of AS mice was significantly downregulated after HLJDD intervention, suggesting that the components of the HLJDD aqueous decoction that enter the liver may participate in the regulation of TMAO levels by targeting the FMO3 protein.\u003c/p\u003e\u003cp\u003e Therefore, we performed molecular docking analysis to screen the compounds identified in the HLJDD aqueous decoction by HPLC-MS/MS, based on their docking affinity, intestinal absorption potential, and compliance with drug-likeness criteria. Our results suggest that limonin, berberine, and dihydrooroxylin A are likely key bioactive components of HLJDD that may interact with the hepatic FMO3 protein. Current research on HLJDD for the treatment of AS tends to focus on the effects of its blood-absorbed compounds, while neglecting the impact of compounds that are not easily absorbed and are subject to first-pass elimination in the gut and liver. For example, berberine, the main active component of Huanglian (\u003cem\u003eCoptis chinensis\u003c/em\u003e) and Huangbo (\u003cem\u003ePhellodendron chinense\u003c/em\u003e), is widely used in China for treating obesity, diabetes, AS, and metabolic diseases. However, Hua et al.\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e found that the plasma concentration of berberine in subjects is extremely low. Liu et al.\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e suggest that first-pass elimination in the gut and preferential accumulation in the liver may be one of the causes for the low plasma concentration. Furthermore, Ma et al.\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e found that feces is the primary excretion route for berberine. Since berberine cannot act on target cells via the bloodstream, its hypoglycemic effect must be closely related to the gut microbiota, as confirmed by a recent randomized controlled trial\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. Interestingly, Jiang et al.\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e found that after oral administration of HLJDD to HFD-induced AS rats, the main active compounds such as baicalin, baicalein, wogonoside, and wogonin were detected at higher concentrations in the plasma and showed dose-dependent increases. In contrast, berberine, palmatine, and jatrorrhizine were present at very low concentrations and did not show dose-dependent increases. In addition, limonin, another active compound found in Huanglian and Huangbo, exhibits significant lipid-lowering and liver-protective effects. However, there are no reports on its application in the context of AS. Similar to berberine, limonin has poor bioavailability. After oral administration, the majority of limonin is metabolized and eliminated by the gut microbiota, with only a small fraction entering the liver, where it exerts complex effects on hepatic metabolic enzymes\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. These studies indicate that the mechanism of action of HLJDD is not solely dependent on its blood-absorbed compounds, but should also take into account the effects of poorly absorbed compounds on the gut microbiota and liver.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrated that HLJDD significantly ameliorates atherosclerotic plaque formation, dyslipidemia, and hepatic lipid abnormalities in HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, with these effects being associated with modulation of the TMA/FMO3/TMAO pathway mediated by both the gut microbiota (such as \u003cem\u003eClostridium\u003c/em\u003e) and liver. Furthermore, we hypothesize that poorly absorbed constituents in the HLJDD aqueous decoction, such as berberine and limonin, may play important roles in mediating these therapeutic effects.\u003c/p\u003e\u003cp\u003eIn recent years, research on TCM has predominantly focused on blood-absorbed compounds. Even network pharmacology studies often prioritize high oral bioavailability as a key criterion for identifying core active ingredients. However, this approach may underestimate the potential therapeutic value of compounds subjected to extensive first-pass metabolism in the gut and liver, thereby limiting their further exploration and development. The mechanisms of action of TCM are complex and typically involve synergistic interactions among multiple components. Compared with single compounds exerting specific functions, we propose that the combined effects of both systemically absorbed and poorly absorbed constituents likely represent the true therapeutic advantage of TCM formulas.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are available in the NCBI Sequence Read Archive repository (accession number: PRJNA1209248) and supplementary materials.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eCF: Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review \u0026amp; editing. JH: Data curation, Formal analysis, Methodology, Resources, Software, Validation, Visualization, Writing - original draft, Writing - review \u0026amp; editing. SL: Formal analysis, Methodology, Software, Validation, Writing - review \u0026amp; editing. ZK: Investigation, Methodology, Writing - review \u0026amp; editing. WW: Investigation, Methodology, Writing - review \u0026amp; editing. WT: Funding acquisition, Project administration, Supervision, Writing - review \u0026amp; editing. QY: Funding acquisition, Project administration, Supervision, Writing - review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by Guiyang College of Traditional Chinese Medicine, 2018 Academic New Talent Cultivation and Innovation Exploration Project (Qiankehe platform talents-[2017] 5735-17), Traditional Chinese Medicine and Ethnic Medicine Guizhou Provincial Scientific Innovation Leading Talent Workstation, Guizhou Provincial Department of Science and Technology Plan Project (Qiankehe platform-KXJZ [2024] 034), Key Laboratory of Microbial and Infectious Disease Prevention \u0026amp; Control in Guizhou Province (Qiankehe platform talents-ZDSYS [2023] 004), Guizhou University of Traditional Chinese Medicine Talent Innovation Team (Gui Traditional Chinese Medicine TD He Zi [2023] 002).\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eEthics statement\u003c/p\u003e\n\u003cp\u003eAll animal experiments were performed in strict accordance with the ARRIVE guidelines and the institutional guidelines for the care and use of laboratory animals. The study was approved by the Animal Care and Welfare Committee of Guizhou University of Traditional Chinese Medicine (Approval No. 20240033).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLibby, P. The changing landscape of atherosclerosis. \u003cem\u003eNat\u003c/em\u003e\u003cstrong\u003e592\u003c/strong\u003e, 524\u0026ndash;533 (2021).\u003c/li\u003e\n\u003cli\u003eFu, J. \u003cem\u003eet al.\u003c/em\u003e National and provincial-level prevalence and risk factors of carotid atherosclerosis in Chinese adults. \u003cem\u003eJAMA Netw. Open\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, e2351225 (2024).\u003c/li\u003e\n\u003cli\u003eKadoglou, N. P. E. \u0026amp; Stasinopoulou, M. How to use statins in secondary prevention of atherosclerotic diseases: From the beneficial early initiation to the potentially unfavorable discontinuation. \u003cem\u003eCardiovasc. 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Previous studies have primarily focused on the mechanisms of action of its blood-absorbed compounds, while less attention has been paid to its effects on gut microbiota. The trimethylamine (TMA)/flavin-containing monooxygenase 3 (FMO3)/trimethylamine N-oxide (TMAO) pathway, co-mediated by gut bacteria and the liver, plays a critical role in AS-related dyslipidemia. Using ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice fed a high-fat diet, this study evaluated HLJDD's effects on AS and gut microbiota. Results showed HLJDD reduced atherosclerotic plaques, macrophage infiltration, hepatic lipid accumulation, and serum lipids. It also altered gut microbiota diversity, increasing Verrucomicrobia and Akkermansia while decreasing \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eClostridium\u003c/em\u003e, a key TMA-producing genus. Furthermore, HLJDD significantly lowered serum TMA and TMAO levels and downregulated hepatic FMO3 protein expression in AS mice. Our results indicate that HLJDD ameliorates atherosclerotic lesions and improves lipid dysregulation in HFD-induced ApoE\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. The underlying mechanism may involve regulation of the TMA/FMO3/TMAO axis, which is associated with alterations in gut microbial communities, especially reduced abundance of \u003cem\u003eClostridium\u003c/em\u003e, as well as suppressed hepatic FMO3.\u003c/p\u003e","manuscriptTitle":"Huang-Lian-Jie-Du-Decoction alleviates atherosclerotic plaque and lipid profile in HFD-induced ApoE-/- mice involve the gut microbiota-mediated TMA/FMO3/TMAO axis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 15:53:40","doi":"10.21203/rs.3.rs-6997421/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"abb8815d-e23b-45a8-8203-3ff78d5dcc68","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-19T17:20:20+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52004971,"name":"Health sciences/Diseases"},{"id":52004972,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-05-19T17:24:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 15:53:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6997421","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6997421","identity":"rs-6997421","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}