Obese rats intervened with Rhizoma coptidis revealed differential gene expression and microbiota by serum metabolomics.

BMC Complement Med Ther

Jiangxi Province Key Laboratory of TCM Etiopathogenisis, Research Center for Differention and Development of TCM Basic Theory, University of Jiangxi TCM, Nanchang, Jiangxi, 330006, P. R. China.

Published: August 2021

Background: Integrating systems biology is an approach for investigating metabolic diseases in humans. However, few studies use this approach to investigate the mechanism by which Rhizoma coptidis (RC) reduces the effect of lipids and glucose on high-fat induced obesity in rats.

Methods: Twenty-four specific pathogen-free (SPF) male Sprague-Dawley rats (80 ± 10 g) were used in this study. Serum metabolomics were detected by ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry. Liver tissue and cecum feces were used for RNA-Seq technology and 16S rRNA gene sequencing, respectively.

Results: We identified nine potential biomarkers, which are differential metabolites in the Control, Model and RC groups, including linoleic acid, eicosapentaenoic acid, arachidonic acid, stearic acid, and L-Alloisoleucine (p < 0.01). The liver tissue gene expression profile indicated the circadian rhythm pathway was significantly affected by RC (Q ≤ 0.05). A total of 149 and 39 operational taxonomic units (OTUs), which were highly associated with biochemical indicators and potential biomarkers in the cecum samples (FDR ≤ 0.05), respectively, were identified.

Conclusion: This work provides information to better understand the mechanism of the effect of RC intervention on hyperlipidemia and hypoglycemic effects in obese rats. The present study demonstrates that integrating systems biology may be a powerful tool to reveal the complexity of metabolic diseases in rats intervened by traditional Chinese medicine.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359625PMC
http://dx.doi.org/10.1186/s12906-021-03382-3DOI Listing

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