Next Article in Journal
Evaluation of Nisin and Cultured Dextrose as Clean Label Preservatives in Braised Chicken Breast: Antibacterial Activity and Quality Preservation
Previous Article in Journal
Estimating Fibrosity Scores of Plant-Based Meat Products from Images: A Deep Neural Network Approach
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Foods
Volume 15
Issue 4
10.3390/foods15040666
foods-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Impact of Dietary Interventions with Schleiferilactobacillus harbinensis Z171, Its Exopolysaccharide, and Postbiotics on Hepatic Cholesterol Metabolism in High-Fat Diet-Fed Mouse Model

by
Mohamedelfatieh Ismael
†,
Jinsong Wu
†,
Huirong Yang
and
Qingping Zhong
*
Guangdong Provincial Key Laboratory of Food Quality and Safety, College of Food Science, South China Agricultural University, Guangzhou 510642, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Foods 2026, 15(4), 666; https://doi.org/10.3390/foods15040666
Submission received: 8 January 2026 / Revised: 29 January 2026 / Accepted: 9 February 2026 / Published: 12 February 2026
(This article belongs to the Section Food Microbiology)
Browse Figures
Versions Notes

Abstract

Lactic acid bacteria (LAB) and their metabolic derivatives, including exopolysaccharide (EPS), as well as postbiotics (POS), exhibit considerable potential for application as healthy foods and dietary supplements for the host. Evaluating the cholesterol-lowering activities of LAB, EPS and POS, with a focus on their impact on lipid metabolism, has become a hotspot in the development of cholesterol-lowering food products. This study was designed to assess the impacts of Schleiferilactobacillus harbinensis Z171 and its EPS and POS on hepatic cholesterol metabolism of C57BL/6 mice fed a high-fat diet (HFD). Key biomarkers related to cholesterol synthesis, bile acid production, cholesterol transport, and the role of AMPKα activation in inhibiting cholesterol synthesis were studied. The results indicated that Z171, POS, and a high dose of EPS (400 mg/kg) significantly reduced serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) by 39.73–41.74%, 34.72–37.43, and 31.74–40.76%, respectively, while simultaneously increasing high-density lipoprotein cholesterol (HDL-C) level by 26.57–31.00%. Furthermore, histopathological analysis revealed that these interventions led to reduced fat accumulation in the liver and an improved liver morphology. Additionally, metabolomic analysis demonstrated that these interventions promoted bile acid synthesis, as evidenced by increased CYP7A1 expression, leading to enhanced cholesterol catabolism. These findings suggested that Z171, POS, and high-dose EPS may be effective in managing hypercholesterolemia by regulating cholesterol synthesis, enhancing bile acid production, and improving lipid metabolism in HFD mice. This work contributes to the understanding of the potential of LAB, POS and EPS as functional ingredients for improving metabolic health.

1. Introduction

The global prevalence of lipid metabolism disorders (LMD) has reached alarming levels. This has notably elevated the incidence of cardiovascular disease (CVD), with high blood cholesterol levels and blood pressure being prominent risk factors endangering human health [1]. Globally, CVD affects the lives of 23.6 million individuals and remains the leading cause of mortality worldwide [2,3]. The American Heart Association has reported that CVD is the main cause of death in the United States. By 2030, it is estimated that 40.5% of the population may be afflicted with some form of CVD [4]. In this backdrop, there is growing interest in exploring intervention strategies for the management of LMD, particularly those related to probiotics and their bioactive components.
Lactic acid bacteria (LAB) are renowned for their diverse healthy benefits to the host and are generally recognized as safe (GRAS) [5]. Emerging evidence has indicated that LAB postbiotics and the secreted metabolites such as exopolysaccharides (EPSs) hold significant promise in modulating lipid profiles and improving cardiovascular health through various mechanisms [6]. In 2019, the International Scientific Association for Probiotics and Prebiotics (ISAPP) put forward the definition of postbiotics, describing them as preparations of inanimate microorganisms and/or their components that exert beneficial effects on host health [7,8]. This definition has established a standardized framework for the researcher to explore the health-benefit potential of these non-living microorganisms. EPSs, on the other hand, are defined as high-molecular-weight carbohydrates that are naturally secreted by microorganisms as extracellular microbial polymers [9]. LAB synthesize EPSs via the extracellular synthesis pathways [10]. Different genera of LAB can produce different polymers that possess excellent biological properties beneficial to the host. The hydrophobic domains, functional groups, and viscosity augmenting characteristics of EPS are responsible for the direct cholesterol-lowering efficacy of EPSs as dietary supplements. These structural features enable EPSs to interact with cholesterol molecules in the gastrointestinal tract, facilitating cholesterol sequestration and subsequent excretion [11]. In contrast, the production of short-chain fatty acids (SCFAs) derived from EPS fermentation exerts an indirect influence on cholesterol homeostasis by modulating hepatic lipid metabolism pathways [12]. The beneficial effects of LAB postbiotics and EPSs are mediated through multiple underlying mechanisms. These include the activity of bile salt hydrolase, interaction with hydroxymethylglutaryl-CoA reductase, the modulation of the gut microbiota, immuno-modulatory effects, cholesterol-lowering activities, and the modulation of gene expression associated with lipid metabolism [1,13].
Several studies indicated that LAB and their postbiotics and EPSs exhibited cholesterol-lowering and hypoglycemic activities through in vitro assays such as Lacticaseibacillus paracasei NWAFU334 and Limosilactobacillus fermentum NWAFU0035 [14]. The EPSs produced by Lactiplantibacillus paraplantarum NCCP 962, Levilactobacillus brevis MT950194 and L. brevis MW365351 showed reduction in cholesterol concentration up to 46.4%, 35%, and 54%, respectively [12,15]. Enterococcus faecium F12 achieved cholesterol reduction rates of 70% and 72% via assimilation and coupled assimilation, respectively [16]. Supplementation by Pediococcus parvulus 2.6 and Lactobacillus mucosae reduced the total cholesterol in serum (approximately 33∼50%) and liver (approximately 30%) and serum triglyceride concentrations (approximately 15∼25%) in mice [17]. However, there is limited in vivo research on the exact mechanisms of cholesterol-lowering activities [18], especially for the S. harbinensis probiotic and their post-probiotic and EPS. When evaluating the cholesterol-lowering activity, it is also essential to investigate the mechanism of cholesterol regulation in mice fed a high-fat diet (HFD). Some studies have indicated that cholesterol metabolism can be regulated via multiple pathways, with each pathway involving several biomarkers. The liver, serving as the chemical factory of the body and the largest metabolic organ, participates in the majority of metabolic processes and is considered a key organ in cholesterol metabolism [19]. The metabolic processes involving the liver include inhibiting cholesterol synthesis (biomarkers: HMG-CoAr, AMPKα, SREBP-1c), promoting bile acid synthesis (biomarkers: CYP7A1, FXR, CYP27A1), and preventing cholesterol accumulation in peripheral tissues (biomarkers: PPARα, ApoB, LDL-R) [20]. Therefore, by quantifying these biomarkers, we can investigate the cholesterol regulatory mechanisms.
In our previous study [21,22], the in vitro cholesterol-lowering effect of EPSs from S. harbinensis Z171 was investigated. The EPS prepared using fructose as a carbon source under 1.0 mM H2O2 exhibited the highest cholesterol-lowering effect. Therefore, it is imperative to conduct an in-depth exploration of in vivo cholesterol-lowering efficacy. In the present study, the postbiotics of S. harbinensis Z171 were also prepared through the fermentation of this specific strain in a modified MRS medium. Subsequently, a comprehensive and systematic study was conducted to explore the in vivo cholesterol-lowering efficacies of S. harbinensis Z171, its EPS and postbiotics. HFD-fed C57BL/6 mice were utilized as the animal model. The assessment of cholesterol-lowering effects involved multiple aspects. Four lipid parameters, namely, triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were determined. Additionally, several common indicators related to liver function, including alanine aminotransferase (ALT), and aspartate aminotransferase (AST), were analyzed. The organ index was also determined to evaluate the potential impact on major organs. The atherosclerosis index, an important parameter reflecting the risk of atherosclerotic plaque formation, was also calculated. Moreover, histopathological analysis of liver and epididymal adipose tissue was carried out to assess tissue-level morphological alterations, providing visual evidence of the effects of the interventions. To further elucidate the underlying mechanisms, liver tissue metabolomics analysis was carried out to comprehensively profile the metabolic changes, identifying key metabolites and metabolic pathways associated with cholesterol metabolism and liver function. Western blotting (protein molecular blotting) was applied for the quantitative analysis of biomarker expression levels involved in the above pathways. This study employed an integrated multi-level analytical approach, offering novel and comprehensive mechanistic insights into the regulatory effects of S. harbinensis Z171, its EPS and postbiotics on hepatic cholesterol and lipid metabolism in HFD-fed mice. Moreover, the findings suggest that S. harbinensis Z171, its EPS, and postbiotics may potentially serve as functional foods and dietary supplements with cholesterol-lowering and anti-atherosclerotic effects.

2. Materials and Methods

2.1. Preparation of EPS and Postbiotics of S. harbinensis Z171

The purified EPS was employed for oral administration as previously reported [22]. The bacterial suspension for oral administration was prepared as follows: S. harbinensis Z171 was cultivated for 24 h in modified MRS medium and then centrifuged at 5000 rpm at 4 °C for 15 min. The bacterial precipitate was collected and mixed with skim milk powder in a ratio of 1:9. Then, the bacterial powder was obtained after freeze-drying for 48 h. The bacterial powder was dissolved in sterile saline to prepare a fresh bacterial suspension at a concentration of 109 CFU/mL [21]. In addition, the postbiotics were prepared by culturing S. harbinensis Z171 in modified MRS medium for 24 h, then inactivating it at 90 °C for 30 min. The fermented bacterial suspension was concentrated to half volume using a rotary evaporator, followed by freeze-drying for 72 h and storing for later use.

2.2. Animal Grouping and Experimentation

Sixty SPF-grade male C57BL/6J mice, aged 4 weeks and purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Production license number: SCXK (Beijing, China) 2019-0010), were kept in an environment with controlled temperature (23 ± 3 °C), relative humidity (50–60%), and a light/dark cycle of 12 h each. Throughout the experiment, they had free access to food and water. Before the intervention trial, the mice were adaptively fed for one week with 60Co-irradiated mouse maintenance feed. The main nutritional components of this feed are crude protein ≥ 180 g/kg, moisture ≤ 100 g/kg, crude ash ≤ 80 g/kg, crude fat 40 g/kg, calcium 10–18 g/kg, and total phosphorus 6–12 g/kg. The animal trial was approved by the Animal Ethics Committee of South China Agricultural University, with ethics review number 2023B164. After the mice had undergone a one-week acclimatization period, they were allocated randomly into six groups (n = 10). Different doses of polysaccharides, probiotic, and postbiotics have been proposed for oral gavage, as shown in Table 1. The groups were as follows: normal diet group (ND), high-fat diet group (HFD), low-dose EPS intervention group (HFD+LEPS), high-dose EPS intervention group (HFD+HEPS), lactic acid bacteria intervention group (HFD+LAB), and postbiotic intervention group (HFD+POS). The nutritional components of the HFD employed to induce hypercholesterolemia in mice consisted of 58.6% 60Co-irradiated mouse maintenance feed, 150 g/kg of lard, 200 g/kg of sucrose, 50 g/kg of casein, 12 g/kg of cholesterol, and 2 g/kg of sodium cholate [23,24,25,26].

2.3. Body Weight and Energy Intake Measurement and Euthanasia of Mice

The body weights of the mice were measured and recorded weekly. Energy intake per mouse was estimated for each cage based on the assumption of equivalent food intake per unit body weight [27]. After eight weeks of feeding, the mice were sacrificed. Chloral hydrate solution (300 mg/kg body weight) was administered intraperitoneally for anesthesia. The blood was drawn from retro-orbital capillaries, and the mice were euthanized. The liver, heart, kidneys, small intestine contents, cecum contents, and fecal samples were collected for H&E and SCFA analyses [28,29].

2.4. Organ Index and Biochemical Parameters Measurement in Serum

The liver, heart, and kidneys were weighed for the calculation of the organ index (OI). Subsequently, the samples were preserved frozen at −80 °C. The OI was measured by using Formula (1) [30].
O I = O r g a n   w e i g h t B o d y   w e i g h t × 100  
The serum was obtained through centrifuging blood at 3500 rpm, 4 °C, for 10 min for the measurement of blood biochemical parameters. The levels of total cholesterol (TC), triglycerides (TG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were determined using test kits produced by Nanjing Jiancheng Bioengineering Institute, Nanjing, China. The absorbance values were measured by a fully automatic biochemical analyzer (Chemray 420 of Rayto Life Science Co., Ltd., Shenzhen, China). The atherosclerosis index (AI) was calculated using Formula (2) [31].
A I = T C − H D L − C H D L − C  

2.5. Histopathological Analysis of Liver and Epididymal Fat Tissue

Small portions of liver and epididymal tissue were fixed in 10% formalin solution for 24 h. After fixing, the tissue samples were washed, dehydrated, embedded in paraffin, sectioned, stained with hematoxylin (Wuhan Servicebio Technology Co., Ltd., Wuhan, China) and eosin (H&E), and then covered with coverslips. A microscope from Leica Instruments, Wetzlar, Germany, was employed for microscopic examination. Imaging was carried out using a ScopeImage 9.0 system at a magnification of 200× [32,33].

2.6. Analysis of Relative Content of Bile Acids

Bile acids are synthesized from cholesterol in the liver [34]. In this study, the relative concentrations of four primary bile acids, namely, cholic acid (CA), 3α,7α-dihydroxycholestanoic acid (DHCA), taurocholic acid (TCA), and β-muricholic acid (β-MCA), were analyzed using commercial kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).

2.7. Measurement of Total Cholesterol in Liver Tissue

The frozen liver tissue stored at −80 °C was thawed, and approximately 20 mg sample was weighed. Subsequently, 180 µL of PBS was added, and the tissue was fully homogenized using a homogenizer. Following centrifugation of the homogenate at 2500 rpm, 4 °C, for 10 min, the supernatant was obtained. The total cholesterol concentration of the liver tissue was measured using a cholesterol assay kit (Nanjing Jiancheng Bioengineering Institute China), and the protein concentration of the supernatant was analyzed with a BCA protein concentration assay kit. The total cholesterol concentration of the liver tissue was normalized to the protein concentration, and the experimental results were presented as mmol/g protein.

2.8. Metabolomics Analysis of Liver Tissue

2.8.1. Extraction of Metabolites

Approximately 30 ± 5 mg of liver tissue was precisely weighed and placed in a 2.0 mL centrifuge tube. A grinding bead, roughly 6 mm in diameter, was added. A mixed extraction solvent with water and methanol at a volume ratio of 1:4 was prepared, and 200 µL of this solution was added to the tube along with four internal standards (for example, L-2-chlorophenylalanine at a concentration of 0.02 mg/mL). The mixture was ground at a frequency of 50 Hz under −10 °C for 6 min using a frozen tissue grinder (Shanghai Wanbo Biological Technology Co., Ltd., Shanghai, China). Then, it was subjected to low-temperature ultrasonic extraction under 5 °C at a frequency of 40 kHz for 30 min. After that, the samples were allowed to stand at −20 °C for 30 min and then centrifuged at 13,000 rpm, 4 °C, for 15 min. Then, the supernatant was obtained for analysis. Meanwhile, for quality control purposes, 20 µL of the supernatant from each sample was taken to prepare the quality control sample.

2.8.2. LC-MS Analysis

A UHPLC system of Thermo Fisher Scientific, Waltham, MA, USA, equipped with an ACQUITY UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 µm) was used. Mobile phase A was composed of 5% acetonitrile and 95% water (containing 0.1% formic acid), while mobile phase B consisted of 47.5% isopropanol, acetonitrile, and 5% water (containing 0.1% formic acid). A 3 µL injection volume was employed, with the column temperature maintained at 40 °C.
Mass spectrometry signals were collected by employing electrospray ionization (ESI) Q-Exactive HF-X from Thermo Fisher Scientific, USA, in both positive and negative ion scanning modes. The scan range was kept at 70–1050 m/z. The flow rate of sheath gas was 50 arb, while the flow rate of auxiliary gas was 13 arb; the heating and capillary temperatures were set at 425 °C and 325 °C, respectively. The spray voltage for positive and negative modes was 3500 V and −3500 V, respectively, and the collision energy was adjusted to 20, 40, and 60 eV.

2.8.3. Metabolite Analysis

The original raw data were uploaded into Progenesis QI v3.0 (Waters Corporation, Milford, MA, USA), a specialized metabolomics analysis software, for a series of preprocessing procedures, including baseline filtering, peak detection, peak integration, retention time calibration, and peak alignment. The resulting data matrix contained information on the mass-to-charge ratio (m/z), retention time, and peak intensity. The software was applied to match characteristic peaks with metabolite databases, comparing the MS/MS and MS data. A mass error below 10 ppm was set, and metabolite identification was confirmed based on the MS/MS match scores. The main databases used were https://www.hmdb.ca/ and https://metlin.scripps.edu (accessed on 20 December 2025), as well as the self-constructed database of Shanghai Majorbio Bio-pharm Technology Co., Ltd. Shanghai, China [35].

2.8.4. Pathway Analysis of Differential Metabolites

The metabolites in the liver tissue were mapped to KEGG pathways through the Majorbio cloud computing platform (https://www.majorbio.com/). Significant pathway enrichments were analyzed on the KEGG website.

2.9. Western Blotting

Frozen liver tissue (approximately 30 mg) was homogenized in 1 mL of RIPA lysis buffer containing 10 µL of PMSF (100:1). Following centrifugation of the homogenate at 12,000 rpm, 4 °C, for 10 min, the supernatant was retained, and the protein concentration was determined with a BCA assay kit and adjusted accordingly. The samples were denatured at 95 °C for 5 min, separated by SDS-PAGE on a Western blotting electrophoresis power supply (Shanghai Tianneng Co., Ltd., Shanghai, China) and transferred to membranes. After blocking and antibody reactions, the specific proteins were detected using a Bio-Rad ChemiDoc XRS+ imaging system (Bio-rad, Hercules, CA, USA). The specific primary antibodies were CYP7A1, LDL-R, and HMG-CoA (Shanghai Biyuntian Biotechnology Co., Ltd., Shanghai, China). The loading control protein was β-actin. The blots were performed from pooled samples. The band intensities of the proteins were quantified using Image J 1.x software [36,37].

2.10. Statistical Analysis

All data are expressed as the mean ± standard error of the mean (SEM), with each value derived from three or more independent experimental replicates. One-way analysis of variance (ANOVA) was conducted using GraphPad Prism 8 software, and then Tukey’s test was utilized for multiple comparisons.

3. Results

3.1. Effects of Different Dietary Interventions on Body Weight and Energy Intake

The body weight and dietary intake in each group were determined weekly, and the weight gain and energy intake were calculated. As presented in Figure 1a,b, starting from the 6th week, the weight gains of the high-fat diet (HFD) group and low-dose EPS group (HFD+LEPS) were remarkably higher compared with those of the normal diet (ND) group, high-dose EPS group (HFD+HEPS), lactic acid bacteria group (HFD+LAB), and postbiotic group (HFD+POS). These findings indicated that high-fat diet components promoted weight gain. The high-dose EPS, LAB, and postbiotics may reduce intestinal fat absorption, increase satiety signals, enhance energy expenditure, and elevate insulin sensitivity, thereby leading to the reduction in body weight gain [38].

3.2. Levels of Plasma Lipids in Mouse Model

The levels of total cholesterol (TC), triglycerides (TG), LDL-C, and HDL-C in serum were determined after 8 weeks. Compared with the ND group, the levels of TG, TC, and LDL-C in the HFD group were significantly increased by 48.37%, 87.32%, and 73.77% respectively, while the HDL-C level was notably decreased by 22.64% (p < 0.05); see Figure 2.

3.3. Changes in Serum ALT and AST Levels of HFD-Fed Mouse Model

Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are metabolic enzymes found in liver cells. These enzymes are used as biological markers for detecting liver cell injury in prolonged medical condition or aggressive agents, which can cause a leak of these enzymes into the blood, increasing serum ALT and AST concentrations [39]. As presented in Figure 3, the high-dose EPS, LAB, and POS groups exhibited significantly lower levels of ALT by 44.79%, 41.54%, and 45.73%, respectively, in comparison with those in the HFD and low-dose EPS groups. Similar results were found for AST, with reductions of 25.85%, 45.61%, and 49.23%, respectively. Particularly, the serum AST levels in the LAB group and postbiotic group were notably lower than that of the high-dose EPS group, though they remained notably higher than that of the ND group (p < 0.05).

3.4. Impacts on the Organ Index and Atherosclerosis Index in HFD-Fed Mice

The organ indices of the heart, liver, and kidneys in the mice are shown in Table 2. The liver plays a vital role in regulating cholesterol synthesis, lipoprotein uptake, and cholesterol secretion [40]. The liver indices of the HFD group and low-dose EPS group were remarkably higher compared with those of the ND, high-dose EPS, LAB, and postbiotic groups (p < 0.05). In addition, no notable discrepancies were found in the heart and kidney organ indices among the groups.
The atherosclerosis index (AI) serves as an indicator reflecting the risk of atherosclerosis. Figure 4 shows that the AIs of the HFD group (2.7850 U/L) and low-dose EPS group (2.9478 U/L) were notably higher compared with those of the ND group (0.9245 U/L), high-dose EPS group (0.9916 U/L), LAB group (0.8234 U/L), and postbiotic group (0.9251 U/L) (p < 0.05). No significant differences were observed among the ND group, high-dose EPS group, LAB group, and postbiotic group (p > 0.05), indicating that a high-fat diet remarkably increased the AI. However, the low-dose EPS did not bring about significant improvement in these parameters.

3.5. Influence of Dietary Interventions on Liver and Epididymal Tissue Morphology in HFD-Fed Mice

3.5.1. Liver Tissue Morphology

Hematoxylin and eosin (H&E) staining is a widely applied method in histology and pathology for visualizing tissue structure. After staining liver tissue with H&E, the alterations in hepatocytes and fat droplets were observed [41].
Figure 5 shows that the hepatocytes in the ND group appeared to have normal characteristics, with complete cell morphology, clear cytoplasm, and well-defined nuclei. The boundaries between cells were distinct. In contrast, the hepatocytes in the HFD group displayed fat degeneration. There were many diffuse vacuoles present. The nuclei were pushed to the periphery, and the boundary between the cytoplasm and nuclei became blurred. Meanwhile, the low-dose EPS group showed a slight improvement in liver cell fat degeneration, with fewer diffuse vacuoles. However, there were no notable variations in the overall morphological characteristics compared with the HFD group.

3.5.2. Influences on Epididymal Tissue Morphology

The morphology of epididymal fat tissue was observed by means of H&E staining. The results are presented in Figure 6. When compared to the ND group, the fat cells in the HFD group were hypertrophied, and the number of cells within a fixed area was obviously decreased. Meanwhile, in the high-dose EPS, LAB, and POS groups, the number of cells within the same area was notably elevated, and the size of fat droplets was decreased. These results indicated that these interventions reduced the size of epididymal fat cells.

3.6. Contents of Bile Acids and Total Cholesterol

The relative concentrations of CA, DHCA, TCA, and β-MCA in the HFD and low-dose EPS groups were remarkably decreased (p < 0.05) in comparison with the high-dose EPS, LAB, POS, and ND groups (Table 3).
The liver plays a pivotal role in lipid metabolism, particularly cholesterol. The levels of cholesterol can be regulated by some key enzymes such as CYP7A1 [42]. The total cholesterol concentration in liver tissues was measured and adjusted using the protein concentration. As shown in Figure 7, in comparison with the HFD and low-dose EPS groups, the total cholesterol concentrations in the high-dose EPS, LAB, and POS groups were significantly decreased (p < 0.05).

3.7. Metabolomics Analysis

3.7.1. Comparative Analysis of Metabolites

Partial least squares discriminant analysis (PLS-DA) was employed to analyze the similarity within samples and the differences between groups based on the relative expression of metabolites [43]. As shown in Figure 8a, PLS-DA analysis revealed a clear separation among the ND, HFD, low-dose EPS, high-dose EPS, LAB, and POS groups. Hence, model validation through permutation tests demonstrated that the model was credible (Figure 8b,c).

3.7.2. Differential Metabolite Analysis and KEGG Pathway Enrichment

To visualize the overall differences in metabolites among the groups, volcano plots were adopted [44]. KEGG pathway enrichment analysis was conducted on the selected metabolite sets using a hypergeometric distribution algorithm to identify the enriched pathways [45]. A total of 1665 metabolites were detected in the liver tissue of the HFD and ND groups (Figure 9(A1,A2)). Compared to the ND group, 213 metabolites were upregulated, and 187 metabolites were downregulated in the HFD group. The differentially enriched pathways encompassed choline metabolism in cancer, nucleotide metabolism, tryptophan metabolism, glycerophospholipid metabolism, the cAMP signaling pathway, the PPAR signaling pathway, primary bile acid biosynthesis, the AMPK signaling pathway, and bile secretion.
Furthermore, 1752 metabolites were detected in the liver tissues of the HFD group and low-dose EPS group. Compared with the HFD group, 199 metabolites were upregulated and 114 were downregulated in the low-dose EPS group (Figure 9(B1,B2)). The differentially enriched pathways included purine metabolism, pyrimidine metabolism, FoxO signaling pathway, bile secretion, and glycine, serine, and threonine metabolism.
In contrast, 1567 metabolites were detected in both the high-dose EPS group and HFD group, and 334 were upregulated and 164 were downregulated in the high-dose EPS group (Figure 9(C1,C2)). Their differentially enriched pathways included nucleotide metabolism, pyrimidine metabolism, purine metabolism, the FoxO signaling pathway, primary bile acid biosynthesis, glycine, serine, and threonine metabolism, the PPAR signaling pathway, the AMPK signaling pathway, and bile secretion. In the high-dose EPS group, the metabolites directly involved in the classical bile acid synthesis pathway were notably upregulated, including 7α-hydroxycholesterol (a direct CYP7A1 product; FC = 2.1; p < 0.01) and chenodeoxycholic acid (FC = 1.8; p < 0.05). Concurrently, the intermediates of hepatic cholesterol synthesis, such as lanosterol, were downregulated (FC = 0.6; p < 0.05).
In the LAB group, 1595 metabolites were detected. Among them, 224 metabolites were upregulated and 226 were downregulated compared to the HFD group (Figure 9(D1,D2)). The involved pathways included tryptophan metabolism, pyrimidine metabolism, glycerophospholipid metabolism, choline metabolism in cancer, the AMPK signaling pathway, the PPAR signaling pathway, and bile secretion.
The postbiotic group contained 1767 metabolites. Compared to the HFD group, 188 metabolites were upregulated and 110 were downregulated (Figure 9(E1,E2)). Their differentially enriched pathways included purine metabolism, pyrimidine metabolism, glycerophospholipid metabolism, the AMPK signaling pathway, and primary bile acid biosynthesis.

3.8. Effects on Cholesterol Synthesis-Related Proteins in Liver Tissue

The de novo synthesis of hepatic cholesterol involves multiple enzymes, among which HMG-CoA reductase (HMG-CoAr) is a key enzyme in this pathway [46]. The expression of HMG-CoAr is regulated by upstream genes such as SREBP-1c and AMPKα. These genes are capable of suppressing cholesterol synthesis through the induction of HMG-CoAr phosphorylation. Moreover, they can also hinder fatty acid synthesis by mediating the phosphorylation of SREBP-1c [47,48].
The results presented in Figure 10 indicate that the protein expression levels of SREBP-1c and HMG-CoAr in the HFD group were significantly elevated in comparison with the ND group. In contrast, there was no remarkable difference in the expressions of HMG-CoAr and SREBP-1c in the low-dose EPS group when compared with those in the HFD group. However, the expression of AMPKα was significantly upregulated. Moreover, in the high-dose EPS, LAB, and POS groups, the expression levels of HMG-CoAr and SREBP-1c were significantly downregulated compared to those of the HFD group (p < 0.05). On the other hand, the expression of AMPKα was markedly upregulated.

3.9. Effects on Bile Acid Synthesis-Related Proteins in Liver Tissue

To determine whether bile acid synthesis took place via the classical pathway or alternative pathways, we analyzed the expression of rate-limiting enzymes in both pathways. The CYP7A1 expressions in the high-dose EPS, LAB, and POS groups were notably enhanced (p < 0.05) This finding was further validated by the substantial accumulation of its catalytic product, 7α-hydroxycholesterol, in hepatic metabolomic analysis. In contrast, the expressions were decreased in the HFD and low-dose EPS groups compared to that of the ND group (Figure 11b). Conversely, the expressions of CYP27A1 in the high-dose EPS, LAB, and POS groups were obviously decreased, while they were increased in the HFD and low-dose EPS groups (Figure 11c). These results strongly suggested that bile acid synthesis mainly occurred through the classical pathway in these groups, while the HFD group and low-dose EPS group primarily utilized the alternative pathway.

3.10. Changes in Cholesterol Accumulation-Related Proteins in Liver Peripheral Tissues

Proteins implicated in the regulation of cholesterol transport in liver cells and peripheral tissues comprise LDL-R, PPARα, and ApoB [49]. To analyze the influences of different dietary interventions on cholesterol transport and accumulation in peripheral tissues, the expressions of these proteins were measured. The expressions of LDL-R and PPARα were notably upregulated in the ND group, while ApoB expression was significantly downregulated in comparison with that of the HFD group (p < 0.05). However, there was no notable upregulation of LDL-R in the low-dose EPS group, although PPARα expression was remarkably upregulated. On the other hand, the high-dose EPS, LAB, and POS groups exhibited significant upregulation of LDL-R and PPARα and downregulation of ApoB compared with the HFD group (p < 0.05), as indicated in Figure 12. Additionally, the metabolomics results of liver tissue showed enrichment in the PPAR signaling pathway.

4. Discussion

This study probed into the potential cholesterol-lowering efficacy and the alleviation of lipid metabolic disorder by the EPS, LAB, and POS of S. harbinensis Z171 in HFD-fed mice. The findings revealed that after 8 weeks of dietary interventions, compared with the HFD group, the low-dose EPS group did not exhibit marked improvement in lipid metabolism. However, the high-dose EPS, LAB, and POS alleviations significantly enhanced lipid metabolism in mice.
Nevertheless, in comparison with the ND group, there were no statistically significant disparities in food consumption quantity between the HFD group and the intervention groups. Conversely, the energy intakes of both the intervention groups and HFD group were found to be higher than that of the ND group. These values for the ND and intervention groups were 3.2 and 4.8 kcal/g, respectively. The HFD group consumed an average of 1.59 kcal/day, which was higher than that of ND group. No significant disparity in energy intake was observed between the HFD group and the intervention groups. These results suggested that the improvement in cholesterol metabolism in the intervention groups was not achieved through the pathway of reducing energy intake but perhaps through other mechanisms.
The measurement of lipid levels indicated that HFD showed a pronounced influence on lipid levels. The notable increase in TC, TG, and LDL-C and reduction in HDL-C in the HFD group compared to the ND group indicated that HFD led to dyslipidemia. However, the high-dose EPS, LAB, and POS groups showed significantly reduced levels of TG, TC, and LDL-C levels (p < 0.05), and a notably increase in HDL-C levels (p < 0.05). There were no remarkable disparities in the levels of TC, TG, HDL-C and LDL-C in the low-dose EPS group in comparison with those of the HFD group. These results demonstrated that these interventions significantly improved lipid metabolism, and EPS showed a dose-dependent effect (Figure 2). Generally, the raised levels of TG, TC and LDL-C and decreased HDL-C levels are often considered as indicators of hyperlipidemia, which is associated with an increased risk of cardiovascular disease [50]. Potentially, high levels of TC and TG can elevate blood viscosity and cause liver injury. Excess LDL-C can deposit on blood vessel walls, inducing atherosclerosis [51]. Reducing TC and LDL-C while increasing HDL-C is an effective measure for lowering cardiovascular disease risk [52]. Cao, Zou [23] also reported that both high and low doses of quinoa polysaccharides led to a significant reduction in LDL-C and TG levels when compared with the HFD group. Similarly, Yang, Huang [53] found that a high dose of ulvan polysaccharides significantly reduced TC and LDL-C levels. Additionally, several reports confirmed the cholesterol-lowering effects of lactic acid bacteria using the high-fat diet mouse model [54,55], while there is a lack of studies focused on postbiotics. Accordingly, these approaches play a pivotal role in improving cardiovascular health by promoting reverse cholesterol transport, mitigating systemic inflammation, and optimizing lipid homeostasis [56]. These interventions culminated in a notable increase in HDL-C levels. HDL-C is a key biomarker related to a decreased risk of atherosclerotic cardiovascular disease, making the increase in its level a significant indicator of improved cardiovascular protection.
The metabolic enzymes of ALT and AST showed that daily dietary supplementation with high doses of EPS, LAB, and postbiotics did not cause liver toxicity or damage in mice. To some extent, it mitigated liver injury induced by HFD. Furthermore, the liver and AI indices indicated that HFD significantly elevated these indices. Notably, the interventions of high-dose EPS, LAB, and POS significantly reduced the liver organ index and AI (p < 0.05) in mice, which could lower the risk of atherosclerosis [57].
In general, H&E staining exhibited that the high-dose EPS, LAB, and POS groups showed significant improvements in liver fat degeneration and a reduction in epididymal fat cell size in mice, along with a notable reduction in the number of vacuoles. However, the low-dose EPS group did not exhibit significant improvements in liver fat degeneration. Additionally, the boundaries between cells were distinct, and the tissue morphology resembled that of the ND group. This indicated that high-dose EPS, LAB, and POS significantly ameliorated the fat degeneration. Evidently, the histopathological results were consistent with the changes observed in serum total cholesterol and triglycerides, further confirming the cholesterol-lowering effects of these interventions. Consequently, it appeared that the alleviation of fat degeneration in the liver by EPS had a dose-dependent effect. Similar histopathological results were reported by Song, Liu [51] and Munir, Javed [15].
The PLS-DA analysis was reliable and clearly indicated a distinct separation between the intervention groups. The comparative analysis of metabolites demonstrated that the high-dose EPS, LAB, and POS groups were positioned between the ND, HFD, and low-dose EPS groups, suggesting that they had significantly mitigated hepatic metabolic alterations caused by HFD. The enrichment of primary bile acid metabolites (CA and TCA) was correlated with the increased fecal bile acid excretion, confirming the enhancement of cholesterol catabolism and clearance through the enterohepatic circulation. KEGG pathway enrichment analysis showed that the high-dose EPS, LAB, and POS groups had more than 15 differential metabolite-enriched pathways. Metabolomic profiling verified active flux through the classical bile acid pathway, as evidenced by the accumulation of early-stage intermediates (7α-hydroxycholesterol) and end-products (taurocholic acid). This finding provides a molecular explanation for the CYP7A1-mediated reduction in hepatic cholesterol content and is consistent with the increased bile acid pool size. Such an elevation provides direct biochemical evidence for the upregulated CYP7A1 protein expression detected by Western blotting analysis. These pathways may contribute to the regulation of liver metabolism in mice fed a high-fat diet. Therefore, these interventions could be strongly proposed for regulating the metabolism of liver tissue in HFD-fed mice through these pathways. Additionally, the relative concentrations of four primary bile acids (CA, DHCA, TCA, and β-MCA) were significantly increased in the high-dose EPS, LAB, and POS groups, while the total cholesterol concentration in the liver was notably reduced in the same groups. This reduction could be attributed to the regulation of the expression of key enzymes that catalyze the conversion of cholesterol into bile acids [42]. A previous study implied that polysaccharides extracted from Pleurotus eryngii SI-04 significantly mitigated lipid levels, effected lipid metabolic disturbance, lowered the levels of TG, TC, LDL-C, CYP2E1 and VLDL-C, and elevated the HDL-C level [51]. Evidently, these interventions remarkably upregulated the expression of CYP7A1 enzyme in the classical bile acid synthesis pathway and the expression of CYP27A1 in the alternative bile acid synthesis pathway.
The gene expression of cholesterol synthesis-related proteins of HMG-CoAr and SREBP-1c confirmed that the interventions of high-dose EPS, LAB, and POS could improve lipid metabolism and reduce cholesterol synthesis in the liver by downregulating their expression levels. The upregulation of AMPKα in these groups supported the findings. Apparently, the effect of EPS on the inhibition of lipid metabolism and cholesterol synthesis demonstrated a dose-dependent nature. The reduction in HMG-CoAr levels may be attributed to the upregulation of AMPKα and the downregulation of SREBP-1c. Subsequently, the expression of bile acid synthesis-related protein CYP7A1 was significantly elevated (p < 0.05) in the high-dose EPS, LAB, and POS groups, while that of CYP27A1 was decreased. The recombinant Lactobacillus paracasei produced β-glucan by expressing the glycosyltransferase gene from Pediococcus parvulus 2.6. The bacterium showed the same effects in inducing the mRNA expression of hepatic Cyp7a1 [17]. These results indicated that a substantial amount of cholesterol was converted into bile acids through the classical pathway, thereby reducing serum cholesterol levels. Evidently, EPS showed a dose-dependent effect on bile acid synthesis in HFD-fed mice.
Cholesterol transport in liver peripheral tissues was investigated by measuring the expression of proteins (LDL-R, PPARα, and ApoB) involved in cholesterol transport and accumulation. The interventions of high-dose EPS, LAB, and POS significantly improved their expressions. The reduction in LDL-C levels in these groups could be attributed to the upregulation of LDL-R expression and downregulation of ApoB expression. Meanwhile, the elevated HDL-C contents could be attributed to the upregulation of PPARα expression. These findings were consistent with the observations documented by Zhang, Zhou [58], who demonstrated that fat pads and triacylglycerol accumulation in mice were significantly decreased by injection of EPS (50 mg/kg) from Lactobacillus rhamnosus GG. Li, Han [59] reveled that the intervention by co-fermented Moringa oleifera Lam. leaf and Fuzhuan brick tea partially ameliorated obesity through regulating the expression of PPARγ, CEBPα, and CD36. Moreover, treatment with Levilactobacillus brevis MT950194 and L. brevis MW365351 resulted in marked decreases in serum and hepatic cholesterol levels, alleviated liver steatosis and reduced adipocyte size, while also ameliorating the diet-induced alterations in hepatic enzyme activities [15].
Therefore, this study indicated that S. harbinensis Z171, its EPS and postbiotics could be considered as potential functional food supplements for regulating cholesterol metabolisms and preventing liver injury in mice fed high-fat diets. The molecular mechanisms through which they impact cholesterol metabolism are multifaceted. These regulatory mechanisms include the direct binding of cholesterol, the modulation of SCFA-mediated pathways, the regulation of bile acid metabolism, alterations in gene transcriptional activity, the modulation of the microbiota, and the regulation of anti-inflammatory signaling pathways. Acting in concert, these processes lead to a notable reduction in serum cholesterol levels, thereby highlighting the potential of these components in cholesterol management and liver protection. Therefore, S. harbinensis Z171, its EPS and postbiotics hold significant potential as valuable food functional ingredients for enhancing lipid metabolic health. The present study advances the field of probiotic-mediated cholesterol-lowering research by conducting a novel, comprehensive and comparative evaluation of the in vivo cholesterol-lowering efficacies of a previously unexplored probiotic strain, S. harbinensis Z171, and its derivatives. Furthermore, the integrated application of metabolomics and protein expression analysis enabled us to move beyond merely descriptive lipid analysis. The relevant metabolic pathways were verified to undergo changes, such as the significant enrichment of primary bile acid biosynthesis. This multi-omics analysis provides a more robust and detailed mechanistic framework for elucidating the underlying mechanisms. Future studies should take into account the adoption of complementary experimental models, such as humanized microbiota mouse models or non-human primate models. Ultimately, efforts should progress toward human clinical trials to verify the efficacy and safety of these interventions.

5. Conclusions

This study highlighted the novel potential of S. harbinensis Z171 as a source of functional ingredients. Dietary interventions with S. harbinensis Z171, its EPS and postbiotics exhibited considerable regulatory effects on lipid metabolism and hepatic functions in obesity-induced murine models. These interventions could be conducive to mitigating HFD-induced hepatic fat synthesis and promoting hepatic fat catabolism. The integrated metabolomic and proteomic analysis clarified the underlying regulatory mechanisms of the aforementioned interventions. Collectively, S. harbinensis Z171, its EPS and postbiotics may act as promising and potent food supplements for mitigating obesity-related metabolic dysfunctions. These findings lay a solid foundation for the development of targeted strategies for hypercholesterolemia management. Although the research results are relatively abundant, the structural complexities of EPS and POS are still factors that influence their application. Future research endeavors should focus on the elucidation of structure–function relationships, the optimization of their physicochemical properties, and the enhancement of production efficiency. Additionally, their safety and efficacy as food functional ingredients should be further validated. These efforts are essential for enhancing the full commercial potential of Z171, POS, and EPS.

Author Contributions

M.I. was responsible for data curation, formal analysis, investigation, methodology, and writing—original draft. J.W. was responsible for investigation, methodology, software, formal analysis, and writing—review and editing. H.Y. was responsible for software, formal analysis, data curation, and validation. Q.Z. was responsible for funding acquisition, project administration, resources, supervision, review and revision. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2024A1515012695), the National Natural Science Foundation of China (Grant No. 31972046), and the Science and Technology Projects of Guangdong Province (Grant No. 2020B1212060059).

Institutional Review Board Statement

The animal study protocol was approved by the Animal Ethics Committee of South China Agricultural University (approval number 2023B164, approval date: 23 November 2023).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors are very grateful to the funders for their financial support.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Werning, M.L.; Hernández-Alcántara, A.M.; Ruiz, M.J.; Soto, L.P.; Dueñas, M.T.; López, P.; Frizzo, L.S. Biological Functions of Exopolysaccharides from Lactic Acid Bacteria and Their Potential Benefits for Humans and Farmed Animals. Foods 2022, 11, 1284. [Google Scholar] [CrossRef]
  2. Di Cesare, M.; Perel, P.; Taylor, S.; Kabudula, C.; Bixby, H.; Gaziano, T.A.; McGhie, D.V.; Mwangi, J.; Pervan, B.; Narula, J.; et al. The Heart of the World. Glob. Heart 2024, 19, 11. [Google Scholar] [CrossRef]
  3. Ruban, A.; Stoenchev, K.; Ashrafian, H.; Teare, J. Current treatments for obesity. Clin. Med. 2019, 19, 205–212. [Google Scholar] [CrossRef]
  4. Korcz, E.; Kerényi, Z.; Varga, L. Dietary fibers, prebiotics, and exopolysaccharides produced by lactic acid bacteria: Potential health benefits with special regard to cholesterol-lowering effects. Food Funct. 2018, 9, 3057–3068. [Google Scholar] [CrossRef] [PubMed]
  5. Ismael, M.; Gu, Y.; Cui, Y.; Wang, T.; Yue, F.; Yantin, Q.; Lü, X. Lactic acid bacteria isolated from Chinese traditional fermented milk as novel probiotic strains and their potential therapeutic applications. 3 Biotech 2022, 12, 337. [Google Scholar] [CrossRef] [PubMed]
  6. Ma, C.; Xu, C.; Zheng, M.; Zhang, S.; Liu, Q.; Lyu, J.; Pang, X.; Wang, Y. Utilizing Lactic Acid Bacteria to Improve Hyperlipidemia: A Comprehensive Analysis from Gut Microbiota to Metabolic Pathways. Foods 2024, 13, 4058. [Google Scholar] [CrossRef] [PubMed]
  7. Aguilar-Toalá, J.E.; Arioli, S.; Behare, P.; Belzer, C.; Berni Canani, R.; Chatel, J.-M.; D’Auria, E.; de Freitas, M.Q.; Elinav, E.; Esmerino, E.A.; et al. Postbiotics—When simplification fails to clarify. Nat. Rev. Gastroenterol. Hepatol. 2021, 18, 825–826. [Google Scholar] [CrossRef]
  8. Salminen, S.; Collado, M.C.; Endo, A.; Hill, C.; Lebeer, S.; Quigley, E.M.M.; Sanders, M.E.; Shamir, R.; Swann, J.R.; Szajewska, H.; et al. The International Scientific Association of Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of postbiotics. Nat. Rev. Gastroenterol. Hepatol. 2021, 18, 649–667. [Google Scholar] [CrossRef]
  9. Sutherland, I.W. Phage-induced fucosidases hydrolysing the exopolysaccharide of Klebsiella arogenes type 54 [A3(S1)]. Biochem. J. 1967, 104, 278–285. [Google Scholar] [CrossRef]
  10. Wu, J.; Han, X.; Ye, M.; Li, Y.; Wang, X.; Zhong, Q. Exopolysaccharides synthesized by lactic acid bacteria: Biosynthesis pathway, structure-function relationship, structural modification and applicability. Crit. Rev. Food Sci. Nutr. 2023, 63, 7043–7064. [Google Scholar] [CrossRef]
  11. Zhang, H.; Li, Y.; Fu, Y.; Jiao, H.; Wang, X.; Wang, Q.; Zhou, M.; Yong, Y.-c.; Liu, J. A structure-functionality insight into the bioactivity of microbial polysaccharides toward biomedical applications: A review. Carbohydr. Polym. 2024, 335, 122078. [Google Scholar] [CrossRef]
  12. Afreen, A.; Ahmed, Z.; Khalid, N.; Ferheen, I.; Ahmed, I. Optimization and cholesterol-lowering activity of exopolysaccharide from Lactiplantibacillus paraplantarum NCCP 962. Appl. Microbiol. Biotechnol. 2023, 107, 1189–1204. [Google Scholar] [CrossRef]
  13. Yilmaz, B.; Arslan, N.; Şahin, T.Ö.; Ağadündüz, D.; Ozogul, F.; Rocha, J.M.F. Unveiling the Impact of Lactic Acid Bacteria on Blood Lipid Regulation for Cardiovascular Health. Fermentation 2024, 10, 350. [Google Scholar] [CrossRef]
  14. Qayyum, N.; Haoyue, H.; Ismael, M.; Yantin, Q.; Lü, X. In vitro assessment of antioxidant, antidiabetic, and cholesterol-modulating abilities of lactic acid bacteria: Implications for metabolic health and functional foods. Food Biosci. 2024, 59, 103952. [Google Scholar] [CrossRef]
  15. Munir, A.; Javed, G.A.; Javed, S.; Arshad, N. Levilactobacillus brevis from carnivores can ameliorate hypercholesterolemia: In vitro and in vivo mechanistic evidence. J. Appl. Microbiol. 2022, 133, 1725–1742. [Google Scholar] [CrossRef] [PubMed]
  16. Habib, B.; Vaid, S.; Bangotra, R.; Sharma, S.; Bajaj, B.K. Bioprospecting of probiotic lactic acid bacteria for cholesterol lowering and exopolysaccharide producing potential. Biologia 2022, 77, 1931–1951. [Google Scholar] [CrossRef]
  17. London, L.E.E.; Kumar, A.H.S.; Wall, R.; Casey, P.G.; O’Sullivan, O.; Shanahan, F.; Hill, C.; Cotter, P.D.; Fitzgerald, G.F.; Ross, R.P.; et al. Exopolysaccharide-Producing Probiotic Lactobacilli Reduce Serum Cholesterol and Modify Enteric Microbiota in ApoE-Deficient Mice. J. Nutr. 2014, 144, 1956–1962. [Google Scholar] [CrossRef]
  18. Zhang, K.; Liu, S.; Liang, S.; Xiang, F.; Wang, X.; Lian, H.; Li, B.; Liu, F. Exopolysaccharides of lactic acid bacteria: Structure, biological activity, structure-activity relationship, and application in the food industry: A review. Int. J. Biol. Macromol. 2024, 257, 128733. [Google Scholar] [CrossRef]
  19. Zhai, X.; Lin, D.; Zhao, Y.; Li, W.; Yang, X. Effects of Dietary Fiber Supplementation on Fatty Acid Metabolism and Intestinal Microbiota Diversity in C57BL/6J Mice Fed with a High-Fat Diet. J. Agric. Food Chem. 2018, 66, 12706–12718. [Google Scholar] [CrossRef] [PubMed]
  20. Li, X.; Du, Y.; Tu, Z.; Zhang, C.; Wang, L. Highland barley improves lipid metabolism, liver injury, antioxidant capacities and liver functions in high-fat/cholesterol diet mice based on gut microbiota and LC-MS metabonomics. Food Biosci. 2022, 50, 102094. [Google Scholar] [CrossRef]
  21. Wu, J.; Wu, Z.; Pan, Y.; Luo, D.; Zhong, Q. Effects of different stress conditions on the production, bioactivities, physicochemical and structural characteristics of exopolysaccharides synthetized by Schleiferilactobacillus harbinensis Z171. Int. J. Biol. Macromol. 2024, 257, 128675. [Google Scholar] [CrossRef] [PubMed]
  22. Wu, J.; Wu, Z.; Dong, S.; Wang, Q.; Zhong, Q. Simulated Gastrointestinal Digestion and Fecal Fermentation Characteristics of Exopolysaccharides Synthesized by Schleiferilactobacillus harbinensis Z171. J. Agric. Food Chem. 2024, 72, 19748–19765. [Google Scholar] [CrossRef]
  23. Cao, Y.; Zou, L.; Li, W.; Song, Y.; Zhao, G.; Hu, Y. Dietary quinoa (Chenopodium quinoa Willd.) polysaccharides ameliorate high-fat diet-induced hyperlipidemia and modulate gut microbiota. Int. J. Biol. Macromol. 2020, 163, 55–65. [Google Scholar] [CrossRef]
  24. Yang, X.; Ren, Y.; Zhang, L.; Wang, Z.; Li, L. Structural characteristics and antioxidant properties of exopolysaccharides isolated from soybean protein gel induced by lactic acid bacteria. LWT 2021, 150, 111811. [Google Scholar] [CrossRef]
  25. Chen, G.; Fang, C.; Chen, X.; Wang, Z.; Liu, M.; Kan, J. High-pressure ultrasonic-assisted extraction of polysaccharides from Mentha haplocalyx: Structure, functional and biological activities. Ind. Crops Prod. 2019, 130, 273–284. [Google Scholar] [CrossRef]
  26. Lim, J.; Kale, M.; Kim, D.-H.; Kim, H.-S.; Chon, J.-W.; Seo, K.-H.; Lee, H.G.; Yokoyama, W.; Kim, H. Antiobesity Effect of Exopolysaccharides Isolated from Kefir Grains. J. Agric. Food Chem. 2017, 65, 10011–10019. [Google Scholar] [CrossRef]
  27. Zaman, K.; Mun, H.-c.; Solon-Biet, S.M.; Senior, A.M.; Raubenheimer, D.; Simpson, S.J.; Conigrave, A.D. Mice Regulate Dietary Amino Acid Balance and Energy Intake by Selecting between Complementary Protein Sources. J. Nutr. 2024, 154, 1766–1780. [Google Scholar] [CrossRef]
  28. Ismael, M.; Qayyum, N.; Gu, Y.; Na, L.; Haoyue, H.; Farooq, M.; Wang, P.; Zhong, Q.; Lü, X. Functional Effects of Probiotic Lactiplantibacillus plantarum in Alleviation Multidrug-Resistant Escherichia coli–Associated Colitis in BALB/c Mice Model. Probiotics Antimicrob. Proteins 2024, 17, 4138–4155. [Google Scholar] [CrossRef]
  29. Jawad, I.; Bin Tawseen, H.; Irfan, M.; Ahmad, W.; Hassan, M.; Sattar, F.; Awan, F.R.; Khaliq, S.; Akhtar, N.; Akhtar, K.; et al. Dietary Supplementation of Microbial Dextran and Inulin Exerts Hypocholesterolemic Effects and Modulates Gut Microbiota in BALB/c Mice Models. Int. J. Mol. Sci. 2023, 24, 5314. [Google Scholar] [CrossRef]
  30. Ismael, M.; Gu, Y.; Cui, Y.; Wang, T.; Yue, F.; Qin, Y.; Lü, X. Probiotic of Lactiplantibacillus plantarum NWAFU-BIO-BS29 Isolated from Chinese Traditional Fermented Milk and Its Potential Therapeutic Applications Based on Gut Microbiota Regulation. Foods 2022, 11, 3766. [Google Scholar] [CrossRef] [PubMed]
  31. Wu, X.; Gao, Y.; Wang, M.; Peng, H.; Zhang, D.; Qin, B.; Pan, L.; Zhu, G. Atherosclerosis indexes and incident T2DM in middle-aged and older adults: Evidence from a cohort study. Diabetol. Metab. Syndr. 2023, 15, 23. [Google Scholar] [CrossRef]
  32. Wang, T.; Wang, S.; Dong, S.; Zhang, Y.; Ismael, M.; Wang, S.; Shi, C.; Yang, J.; Wang, X.; Lü, X. Interaction of Companilactobacillus crustorum MN047-derived bacteriocins with gut microbiota. Food Chem. 2022, 396, 133730. [Google Scholar] [CrossRef]
  33. Wang, T.; Yan, H.; Lu, Y.; Li, X.; Wang, X.; Shan, Y.; Yi, Y.; Liu, B.; Zhou, Y.; Lü, X. Anti-obesity effect of Lactobacillus rhamnosus LS-8 and Lactobacillus crustorum MN047 on high-fat and high-fructose diet mice base on inflammatory response alleviation and gut microbiota regulation. Eur. J. Nutr. 2020, 59, 2709–2728. [Google Scholar] [CrossRef]
  34. Chiang, J.Y.L. Bile acid metabolism and signaling in liver disease and therapy. Liver Res. 2017, 1, 3–9. [Google Scholar] [CrossRef]
  35. Ferrarini, A.; Di Poto, C.; He, S.; Tu, C.; Varghese, R.S.; Kara Balla, A.; Jayatilake, M.; Li, Z.; Ghaffari, K.; Fan, Z.; et al. Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma. J. Proteome Res. 2019, 18, 3067–3076. [Google Scholar] [CrossRef]
  36. Wang, T.; Sun, H.; Chen, J.; Luo, L.; Gu, Y.; Wang, X.; Shan, Y.; Yi, Y.; Liu, B.; Zhou, Y.; et al. Anti-Adhesion Effects of Lactobacillus Strains on Caco-2 Cells Against Escherichia coli and Their Application in Ameliorating the Symptoms of Dextran Sulfate Sodium-Induced Colitis in Mice. Probiotics Antimicrob. Proteins 2021, 13, 1632–1643. [Google Scholar] [CrossRef]
  37. Gesto, D.S.; Pereira, C.M.S.; Cerqueira, N.M.F.S.; Sousa, S.F. An Atomic-Level Perspective of HMG-CoA-Reductase: The Target Enzyme to Treat Hypercholesterolemia. Molecules 2020, 25, 3891. [Google Scholar] [CrossRef] [PubMed]
  38. Oudat, Q.; Okour, A. The Role of Probiotics in Modulating Gut Microbiota and Metabolic Health for Weight Management: A Mini Review. Acta Microbiol. Hell. 2025, 70, 5. [Google Scholar] [CrossRef]
  39. Choi, K.M.; Han, K.; Park, S.; Chung, H.S.; Kim, N.H.; Yoo, H.J.; Seo, J.-A.; Kim, S.G.; Kim, N.H.; Baik, S.H.; et al. Implication of liver enzymes on incident cardiovascular diseases and mortality: A nationwide population-based cohort study. Sci. Rep. 2018, 8, 3764. [Google Scholar] [CrossRef] [PubMed]
  40. Chiang, J.Y.L.; Ferrell, J.M.; Wu, Y.; Boehme, S. Bile Acid and Cholesterol Metabolism in Atherosclerotic Cardiovascular Disease and Therapy. Cardiol. Plus 2020, 5, 159–170. [Google Scholar] [CrossRef]
  41. Ruz-Maldonado, I.; Gonzalez, J.T.; Zhang, H.; Sun, J.; Bort, A.; Kabir, I.; Kibbey, R.G.; Suárez, Y.; Greif, D.M.; Fernández-Hernando, C. Heterogeneity of hepatocyte dynamics restores liver architecture after chemical, physical or viral damage. Nat. Commun. 2024, 15, 1247. [Google Scholar] [CrossRef] [PubMed]
  42. Chiang, J.Y.L.; Ferrell, J.M. Up to date on cholesterol 7 alpha-hydroxylase (CYP7A1) in bile acid synthesis. Liver Res. 2020, 4, 47–63. [Google Scholar] [CrossRef]
  43. Zontov, Y.V.; Rodionova, O.Y.; Kucheryavskiy, S.V.; Pomerantsev, A.L. PLS-DA—A MATLAB GUI tool for hard and soft approaches to partial least squares discriminant analysis. Chemom. Intell. Lab. Syst. 2020, 203, 104064. [Google Scholar] [CrossRef]
  44. Kumar, N.; Hoque, M.A.; Sugimoto, M. Robust volcano plot: Identification of differential metabolites in the presence of outliers. BMC Bioinform. 2018, 19, 128. [Google Scholar] [CrossRef] [PubMed]
  45. Du, J.; Li, M.; Yuan, Z.; Guo, M.; Song, J.; Xie, X.; Chen, Y. A decision analysis model for KEGG pathway analysis. BMC Bioinform. 2016, 17, 407. [Google Scholar] [CrossRef]
  46. Friesen, J.A.; Rodwell, V.W. The 3-hydroxy-3-methylglutaryl coenzyme-A (HMG-CoA) reductases. Genome Biol. 2004, 5, 248. [Google Scholar] [CrossRef]
  47. Alphonse, P.A.; Jones, P.J. Revisiting Human Cholesterol Synthesis and Absorption: The Reciprocity Paradigm and its Key Regulators. Lipids 2016, 51, 519–536. [Google Scholar] [CrossRef]
  48. Jeon, S.M. Regulation and function of AMPK in physiology and diseases. Exp. Mol. Med. 2016, 48, e245. [Google Scholar] [CrossRef] [PubMed]
  49. Luo, J.; Yang, H.; Song, B.-L. Mechanisms and regulation of cholesterol homeostasis. Nat. Rev. Mol. Cell Biol. 2020, 21, 225–245. [Google Scholar] [CrossRef]
  50. Shao, D.; Bartley, G.E.; Yokoyama, W.; Pan, Z.; Zhang, H.; Zhang, A. Plasma and hepatic cholesterol-lowering effects of tomato pomace, tomato seed oil and defatted tomato seed in hamsters fed with high-fat diets. Food Chem. 2013, 139, 589–596. [Google Scholar] [CrossRef]
  51. Song, X.; Liu, Z.; Zhang, J.; Yang, Q.; Ren, Z.; Zhang, C.; Liu, M.; Gao, Z.; Zhao, H.; Jia, L. Anti-inflammatory and hepatoprotective effects of exopolysaccharides isolated from Pleurotus geesteranus on alcohol-induced liver injury. Sci. Rep. 2018, 8, 10493. [Google Scholar] [CrossRef]
  52. Hao, W.; Kwek, E.; He, Z.; Zhu, H.; Liu, J.; Zhao, Y.; Ma, K.Y.; He, W.S.; Chen, Z.Y. Ursolic acid alleviates hypercholesterolemia and modulates the gut microbiota in hamsters. Food Funct. 2020, 11, 6091–6103. [Google Scholar] [CrossRef]
  53. Yang, C.; Huang, S.; Lin, Z.; Chen, H.; Xu, C.; Lin, Y.; Sun, H.; Huang, F.; Lin, D.; Guo, F. Polysaccharides from Enteromorpha prolifera alleviate hypercholesterolemia via modulating the gut microbiota and bile acid metabolism. Food Funct. 2022, 13, 12194–12207. [Google Scholar] [CrossRef]
  54. Liu, Y.; Zhao, F.; Liu, J.; Wang, H.; Han, X.; Zhang, Y.; Yang, Z. Selection of Cholesterol-Lowering Lactic Acid Bacteria and its Effects on Rats Fed with High-Cholesterol Diet. Curr. Microbiol. 2017, 74, 623–631. [Google Scholar] [CrossRef]
  55. Lu, M.; Sun, J.; Zhao, Y.; Zhang, H.; Li, X.; Zhou, J.; Dang, H.; Zhang, J.; Huang, W.; Qi, C.; et al. Prevention of High-Fat Diet-Induced Hypercholesterolemia by Lactobacillus reuteri Fn041 Through Promoting Cholesterol and Bile Salt Excretion and Intestinal Mucosal Barrier Functions. Front. Nutr. 2022, 9, 851541. [Google Scholar] [CrossRef] [PubMed]
  56. Wu, R.M.; Wang, C.Y.; Wang, J.; Xu, X.L. Promoting reverse cholesterol transport contributes to the amelioration of atherosclerosis by paeoniflorin. Eur. J. Pharmacol. 2023, 961, 176137. [Google Scholar] [CrossRef] [PubMed]
  57. Deng, J.; Tang, X.; Tang, R.; Chen, J.; Guo, H.; Zhou, Q.; Zhan, X.; Long, H.; Peng, F.; Wang, X.; et al. Atherogenic index predicts all-cause and cardiovascular mortality in incident peritoneal dialysis patients. Atherosclerosis 2023, 387, 117389. [Google Scholar] [CrossRef]
  58. Zhang, Z.; Zhou, Z.; Li, Y.; Zhou, L.; Ding, Q.; Xu, L. Isolated exopolysaccharides from Lactobacillus rhamnosus GG alleviated adipogenesis mediated by TLR2 in mice. Sci. Rep. 2016, 6, 36083. [Google Scholar] [CrossRef] [PubMed]
  59. Li, X.; Han, H.; Ma, Y.; Wang, X.; Lü, X. Identification of phenolic compounds from fermented Moringa oleifera Lam. leaf supplemented with Fuzhuan brick tea and their volatile composition and anti-obesity activity. J. Food Sci. 2024, 89, 3094–3109. [Google Scholar] [CrossRef]
Foods 15 00666 g001
Figure 1. Effects of different dietary interventions on body weight gain (a) and energy intake (b) of high-fat diet-fed mice. Note: Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Figure 1. Effects of different dietary interventions on body weight gain (a) and energy intake (b) of high-fat diet-fed mice. Note: Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Foods 15 00666 g001
Foods 15 00666 g002
Figure 2. Effects of different dietary interventions on serum cholesterol levels of high-fat diet-fed mice. Note: (a) TG; (b) TC; (c) HDL-C; (d) LDL-C. Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Figure 2. Effects of different dietary interventions on serum cholesterol levels of high-fat diet-fed mice. Note: (a) TG; (b) TC; (c) HDL-C; (d) LDL-C. Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Foods 15 00666 g002
Foods 15 00666 g003
Figure 3. Effects of different dietary interventions on serum ALT and AST levels of high-fat diet-fed mice. Note: (a) ALT; (b) AST. Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Figure 3. Effects of different dietary interventions on serum ALT and AST levels of high-fat diet-fed mice. Note: (a) ALT; (b) AST. Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Foods 15 00666 g003
Foods 15 00666 g004
Figure 4. Effects of different dietary interventions on the atherosclerosis index of high-fat diet-fed mice. Note: Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Figure 4. Effects of different dietary interventions on the atherosclerosis index of high-fat diet-fed mice. Note: Data are presented as mean ± SEM (n = 10). The shapes represent the data points belonging to each group. Different lowercase letters indicate significant differences between different groups (p < 0.05).
Foods 15 00666 g004
Foods 15 00666 g005
Figure 5. Effects of different dietary interventions on liver morphology of high-fat diet-fed mice (200×).
Figure 5. Effects of different dietary interventions on liver morphology of high-fat diet-fed mice (200×).
Foods 15 00666 g005
Foods 15 00666 g006
Figure 6. Effects of different dietary interventions on epididymis morphology of high-fat diet-fed mice.
Figure 6. Effects of different dietary interventions on epididymis morphology of high-fat diet-fed mice.
Foods 15 00666 g006
Foods 15 00666 g007
Figure 7. Effects of different interventions on total cholesterol concentration in liver of mice. Note: Data are presented as mean ± SEM (n = 10). Different letters indicate significant differences (p < 0.05).
Figure 7. Effects of different interventions on total cholesterol concentration in liver of mice. Note: Data are presented as mean ± SEM (n = 10). Different letters indicate significant differences (p < 0.05).
Foods 15 00666 g007
Foods 15 00666 g008
Figure 8. Group partial least squares discriminant analysis (PLS-DA) and model validation of different groups. Note: (a) PLS-DA, (b) model validation, and (c) permutation test. The dashed lines present the regression line of the permutation test model.
Figure 8. Group partial least squares discriminant analysis (PLS-DA) and model validation of different groups. Note: (a) PLS-DA, (b) model validation, and (c) permutation test. The dashed lines present the regression line of the permutation test model.
Foods 15 00666 g008
Foods 15 00666 g009
Figure 9. Metabolite difference volcano maps (A1,B1,C1,D1,E1) and KEGG pathway enrichment analyses (A2,B2,C2,D2,E2) of different intervention groups. Note: (A) ND vs. HFD; (B) HFD+LEPS vs. HFD; (C) HFD+HEPS vs. HFD; (D) HFD+LAB vs. HFD; (E) HFD+POS vs. HFD. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 9. Metabolite difference volcano maps (A1,B1,C1,D1,E1) and KEGG pathway enrichment analyses (A2,B2,C2,D2,E2) of different intervention groups. Note: (A) ND vs. HFD; (B) HFD+LEPS vs. HFD; (C) HFD+HEPS vs. HFD; (D) HFD+LAB vs. HFD; (E) HFD+POS vs. HFD. * p < 0.05, ** p < 0.01, *** p < 0.001.
Foods 15 00666 g009
Foods 15 00666 g010
Figure 10. Western blotting bands of proteins related to cholesterol synthesis and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b–d) Quantitative analysis of HMG-CoAr, AMPKα, and SREBP-1c. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Figure 10. Western blotting bands of proteins related to cholesterol synthesis and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b–d) Quantitative analysis of HMG-CoAr, AMPKα, and SREBP-1c. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Foods 15 00666 g010
Foods 15 00666 g011
Figure 11. Western blotting bands of proteins related to bile acid synthesis and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b,c) Quantitative analysis of CYP7A1 and CYP27A1. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Figure 11. Western blotting bands of proteins related to bile acid synthesis and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b,c) Quantitative analysis of CYP7A1 and CYP27A1. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Foods 15 00666 g011
Foods 15 00666 g012
Figure 12. Western blotting bands of proteins related to cholesterol accumulation and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b–d) Quantitative analysis of LDL-R, ApoB, and PPARα. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Figure 12. Western blotting bands of proteins related to cholesterol accumulation and quantitative analysis of protein expression. Note: (a) Western blotting bands. (b–d) Quantitative analysis of LDL-R, ApoB, and PPARα. Data are presented as mean ± SEM (n = 10); different letters indicate significant differences (p < 0.05).
Foods 15 00666 g012
Table 1. Intervention groups and administration.
Table 1. Intervention groups and administration.
Group NameFeed and Oral Dosage
ND60Co-irradiated maintenance feed + 0.90% saline
HFDHigh-fat feed + 0.90% saline
HFD+LEPSHigh-fat feed + 100 mg EPS/BW/1000 g
HFD+EPSHigh-fat feed + 400 mg EPS/BW/1000 g
HFD+LABHigh-fat feed + 109 CFU/mL lactic acid bacteria/BW/100 g
HFD+POSHigh-fat feed + 400 mg POS/BW/1000 g postbiotics
Note: BW refers to body weight; the dosage for each mouse is calculated based on its body weight: 1.0 mL/100 g; oral administration was given once daily at the same time.
Table 2. Organ indices.
Table 2. Organ indices.
OrganNDHFDHFD+LEPSHFD+HEPSHFD+LABHFD+POS
Heart0.57 ± 0.04 a0.56 ± 0.03 a0.55 ± 0.03 a0.53 ± 0.04 a0.56 ± 0.04 a0.52 ± 0.02 a
Liver4.65 ± 0.13 a5.68 ± 0.25 b5.36 ± 0.22 b4.76 ± 0.19 a4.56 ± 0.33 a4.49 ± 0.28 a
Kidney0.57 ± 0.06 a0.60 ± 0.07 a0.59 ± 0.09 a0.56 ± 0.03 a0.55 ± 0.05 a0.58 ± 0.06 a
Note: Data are presented as mean ± SEM (n = 10); different lowercase letters indicate significant differences between different intervention groups (p < 0.05).
Table 3. Concentrations of different bile acids (×106).
Table 3. Concentrations of different bile acids (×106).
GroupDHCACATCAβ-MCA
ND13.76 ± 0.56 b53.77 ± 3.75 b3.68 ± 0.23 b1.79 ± 0.15 b
HFD1.88 ± 0.12 a11.62 ± 1.03 a1.13 ± 0.15 a0.39 ± 0.05 a
HFD+LEPS1.95 ± 0.16 a13.23 ± 1.78 a1.28 ± 0.21 a0.49 ± 0.05 a
HFD+HEPS13.57 ± 0.38 b56.59 ± 4.11 b3.57 ± 0.27 b1.67 ± 0.13 b
HFD+LAB16.58 ± 0.43 b78.33 ± 5.23 b3.61 ± 0.31 b1.73 ± 0.15 b
HFD+POS13.31 ± 0.53 b57.39 ± 4.23 b3.52 ± 0.33 b1.16 ± 0.11 b
Note: Data are presented as mean ± SEM (n = 10); different lowercase letters indicate significant differences between different intervention groups (p < 0.05).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ismael, M.; Wu, J.; Yang, H.; Zhong, Q. Impact of Dietary Interventions with Schleiferilactobacillus harbinensis Z171, Its Exopolysaccharide, and Postbiotics on Hepatic Cholesterol Metabolism in High-Fat Diet-Fed Mouse Model. Foods 2026, 15, 666. https://doi.org/10.3390/foods15040666

AMA Style

Ismael M, Wu J, Yang H, Zhong Q. Impact of Dietary Interventions with Schleiferilactobacillus harbinensis Z171, Its Exopolysaccharide, and Postbiotics on Hepatic Cholesterol Metabolism in High-Fat Diet-Fed Mouse Model. Foods. 2026; 15(4):666. https://doi.org/10.3390/foods15040666

Chicago/Turabian Style

Ismael, Mohamedelfatieh, Jinsong Wu, Huirong Yang, and Qingping Zhong. 2026. "Impact of Dietary Interventions with Schleiferilactobacillus harbinensis Z171, Its Exopolysaccharide, and Postbiotics on Hepatic Cholesterol Metabolism in High-Fat Diet-Fed Mouse Model" Foods 15, no. 4: 666. https://doi.org/10.3390/foods15040666

APA Style

Ismael, M., Wu, J., Yang, H., & Zhong, Q. (2026). Impact of Dietary Interventions with Schleiferilactobacillus harbinensis Z171, Its Exopolysaccharide, and Postbiotics on Hepatic Cholesterol Metabolism in High-Fat Diet-Fed Mouse Model. Foods, 15(4), 666. https://doi.org/10.3390/foods15040666

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop