Dataset Information

Trifolium pratense ethanolic extract alters the gut microbiota composition and regulates serum lipid profile in the ovariectomized rats.

ABSTRACT:

Background

Trifolium pratense (red clover) ethanolic extract (TPEE) has been used as a popular over-the-counter remedy for the management of menopausal symptoms. Prolonged consumption of herbal extract has been shown to regulate the composition of gut microbiota. This study was designed to elucidate the influence of TPEE on the gut microbiota composition in the ovariectomized (OVX) rats.

Methods

OVX rats were treated with TPEE at 125, 250, 500 mg/kg/day, or controls (pomegranate extract, 500 mg/kg/day; estradiol, 25 μg/kg/day) for 12 weeks. Gut microbiota analysis was conducted by extracting the microbial DNA from fecal samples and microbiome taxonomic profiling was carried out by using next-generation sequencing. The levels of serum biomarkers were analyzed using enzyme-linked immunosorbent assay (ELISA) kit. The prediction of functional biomarker of microbiota was performed using PICRUSt to investigate the potential pathways associated with gut health and serum lipid profile regulation. To study the correlation between gut microbiota composition and serum lipid levels, Spearman's correlation coefficients were defined and analyzed. Additionally, gas chromatography-mass spectrometry analysis was conducted to uncover additional physiologically active ingredients.

Results

TPEE-treated OVX rats showed significant reduction in serum triglycerides (TG), total cholesterols (TCHOL), and LDL/VLDL levels but increase in HDL level. The alteration in the pathways involve in metabolism was the most common among the other KEGG categories. Particularly, TPEE also significantly reduced the relative abundance of sequences read associated with inflammatory bowel disease (IBD) and the peroxisome proliferator-activated receptor (PPAR) signalling pathway. TPEE intervention was seen to reduce the Firmicutes to Bacteroidetes (F/B) ratio in the OVX rats, denoting a reduction in microbial dysbiosis in the OVX rats. Correlation analysis at the phylum level revealed that Bacteriodetes and Proteobacteria were strongly correlated with serum TG, TCHOL and HDL levels. At the species level, Bifidobacterium pseudolongum group was seen to positively correlate with serum HDL level and negatively correlated with serum AST, ALT, LDL/VLDL, TCHOL, and TG levels.

Conclusions

TPEE treatment showed therapeutic benefits by improving the intestinal microbiota composition which strongly correlated with the serum lipid and cholesterol levels in the OVX rats.

SUBMITTER: Quah Y

PROVIDER: S-EPMC8725312 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRecent years, a soaring number of marketed Trifolium pratense (red clover) extract products have denoted that a rising number of consumers are turning to natural alternatives to manage postmenopausal symptoms. T. pratense ethanolic extract (TPEE) showed immense potential for their uses in the treatment of menopause complications including osteoporosis and hormone dependent diseases. Early diagnosis of osteoporosis can increase the chance of efficient treatment and reduce fracture risks. Currently, the most common diagnosis of osteoporosis is performed by using dual-energy x-ray absorptiometry (DXA). However, the major limitation of DXA is that it is inaccessible and expensive in rural areas to be used for primary care inspection. Hence, serum biomarkers can serve as a meaningful and accessible data for osteoporosis diagnosis.MethodsThe present study systematically elucidated the anti-osteoporosis and estrogenic activities of TPEE in ovariectomized (OVX) rats by evaluating the bone microstructure, uterus index, serum and bone biomarkers, and osteoblastic and osteoclastic gene expression. Leverage on a pool of serum biomarkers obtained from this study, recursive feature elimination with a cross-validation method (RFECV) was used to select useful biomarkers for osteoporosis prediction. Then, using the key features extracted, we employed five classification algorithms: extreme gradient boosting (XGBoost), random forest, support vector machine, artificial neural network, and decision tree to predict the bone quality in terms of T-score.ResultsTPEE treatments down-regulated nuclear factor kappa-B ligand, alkaline phosphatase, and up-regulated estrogen receptor β gene expression. Additionally, reduced serum C-terminal telopeptides of type 1 collagen level and improvement in the estrogen dependent characteristics of the uterus on the lining of the lumen were observed in the TPEE intervention group. Among the tested classifiers, XGBoost stood out as the best performing classification model with the highest F1-score and lowest standard deviation.ConclusionsThe present study demonstrates that TPEE treatment showed therapeutic benefits in the prevention of osteoporosis at the transcriptional level and maintained the estrogen dependent characteristics of the uterus. Our study revealed that, in the case of limited number of features, RFECV paired with XGBoost model could serve as a powerful tool to readily evaluate and diagnose postmenopausal osteoporosis.