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MiR-125b-2 knockout increases high-fat diet-induced fat accumulation and insulin resistance

ABSTRACT: Obese individuals are more susceptible to comorbidities than individuals of healthy weight, including cardiovascular disease and metabolic disorders. MicroRNAs are a class of small and noncoding RNAs that are implicated in the regulation of chronic human diseases. We previously reported that miR-125b plays a critical role in adipogenesis in vitro. However, the involvement of miR-125b-2 in fat metabolism in vivo remains unknown. In the present study, miR-125b-2 knockout mice were generated using CRISPR/CAS9 technology, resulting in mice with a 7 bp deletion in the seed sequence of miR-125b-2. MiR-125b-2 knockout increased the weight of liver tissue, epididymal white fat and inguinal white fat. MiR-125b-2 knockout also increased adipocyte volume in HFD-induced obese mice, while there were no significant differences in body weight and feed intake versus mice fed a normal diet. Additionally, qRT-PCR and western blot analysis revealed that the expression of the miR-125b-2 target gene SCD-1 and fat synthesis-associated genes, such as PPAR? and C/EBP?, were significantly up-regulated in miR-125b-2KO mice (P?

SUBMITTER: Wei L

PROVIDER: S-EPMC7738482 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Recent discovery reveals HFD insult can cause insulin resistance very rapidly, but the underlying mechanism is still not well understood. We performed a short term experiment in a Diet Induced Insulin resistance mouse model. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between Î²-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the Î²-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation. Comparison of gene expression in muscle tissue during High Fat Diet (HFD) time course (day 5 and day 42). Chow diet will serve as control for HFD. 4 samples per group serve as experimental replicates.

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MiR-125b-2 knockout increases high-fat diet-induced fat accumulation and insulin resistance

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