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The impact of Rhodiola Rosea on biomarkers of diabetes, inflammation, and microbiota in a leptin receptor-knockout mouse model

Cite this dataset

Courville, Robert et al. (2022). The impact of Rhodiola Rosea on biomarkers of diabetes, inflammation, and microbiota in a leptin receptor-knockout mouse model [Dataset]. Dryad. https://doi.org/10.7280/D1FX2D

Abstract

Type 2 diabetes is the most prevalent endocrine disease in the world, and recently the gut microbiota have become a potential target for its management. Recent studies have illustrated that this disease may predispose individuals to certain microbiome compositions, and treatments like metformin have been shown to change gut microbiota and their associated metabolic pathways. However, given the limitations and side effects associated with pharmaceuticals currently being used for therapy of diabetes, there is a significant need for alternative treatments. In this study, we investigated the effects of a root extract from Rhodiola rosea in a Leptin receptor knockout (db/db) mouse model of type 2 diabetes. Our previous work showed that Rhodiola rosea had anti-inflammatory and gut microbiome-modulating properties, while extending lifespan in several animal models.In this study, treatment with Rhodiola rosea improved fasting blood glucose levels, altered the response to exogenous insulin, and decreased circulating lipopolysaccharide and hepatic C-reactive protein transcript levels. We hypothesize that these changes may in part reflect the modulation of the microbiota, resulting in improved gut barrier integrity and decreasing the translocation of inflammatory biomolecules into the bloodstream. These findings indicate that Rhodiola rosea is an attractive candidate for further research in the management of type 2 diabetes.

Methods

Mice were sacrificed at week 14 (Fig. 1 of manuscript) and RNA extracted from liver tissue using Trizol. A total of 5 samples were collected from R. rosea-treated mice and 6 samples from control water-treated mice. Samples were blinded and the RNA extract was treated with DNA-free™ DNA Removal Kit from Invitrogen to remove any contaminating DNA. A cDNA library was generated with the iScript™ cDNA Synthesis Kit from Bio-Rad. qPCR was performed on a BioRadMJ Mini Personal Thermal Cycler with iQ SYBR Green Supermix. The PCR amplification program consisted of an initial denaturation set at 94 °C for 3 min, followed by 40 three-step cycles at 94 °C for 10 s, 60 °C at 30 s and at 72 °C for 45 s. The ΔΔCt Method was used to quantify the relative expression of genes of interest. The CRP (gene of interest) and GAPDH (reference gene) primers were derived from PrimerBank (Supplementary Table 1 of manuscript). Data were plotted and analyzed using GraphPad Prism v8.

Funding

University of California, Irvine