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Insulin action and binding in isolated hepatocytes from fasted, streptozotocin-diabetic, and older, spontaneously obese rats.

ABSTRACT: Insulin binding and basal and insulin-stimulated uptake of alpha-aminoisobutyric acid were measured in isolated hepatocytes from young control rats as well as from older spontaneously obese, 72h-starved, and nonketotic streptozotocin-diabetic rats. Isolated hepatocytes from older spontaneously obese rats are similar to those from younger smaller rats in size, maximal insulin responsiveness, the dose-response relationship for insulin-stimulated aminoisobutyrate uptake, and the number and affinity of insulin receptors. Hepatocytes from 72h-fasted rats have similar numbers of insulin receptors per cell as cells from young control animals, but are significantly smaller, have an enhanced basal rate of aminoisobutyrate uptake, and are insulin resistant with regard to maximal insulin-stimulated uptake of aminoisobutyrate at 0.1mm-aminoisobutyrate. Because of the decreased maximal response to insulin, the concentration of insulin that elicits a half-maximal response of aminoisobutyrate uptake is decreased. Hepatocytes from diabetic animals, like those from starved rats, have significantly greater basal rates of aminoisobutyrate uptake; whereas the maximal absolute insulin response is the same as control cells, the percentage response is smaller. These cells bind significantly more insulin than do control cells. The increase in insulin binding is reflected in a shift to the left of the dose-response curve for insulin-stimulated uptake of aminoisobutyrate. These studies indicate that there is no insulin resistance with regard to uptake of aminoisobutyrate in hepatocytes from older obese rats. Furthermore, the insulin resistance observed in hepatocytes from starved rats occurs despite an increase in the number of receptors per unit surface area and cannot be explained by alterations in the interaction between insulin and its receptor. The enhanced insulin binding per unit surface area, however, is reflected in the shift to the left of the dose-response curve for insulin. This is also true for hepatocytes from diabetic animals, in which insulin binding per cell is increased.

SUBMITTER: Cech JM

PROVIDER: S-EPMC1161968 | biostudies-other | 1980 Jun

REPOSITORIES: biostudies-other

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Project description:BackgroundAdipose-derived mesenchymal stem cells (ASCs) therapy is emerging as a novel therapeutic option for the treatment of a variety of diseases including diabetes and diabetic wound healing. Multiple studies indicate that ASCs could promote wound healing and reverse diabetes. However, whether ASCs from diabetic donors retain their therapeutic functions and the mechanisms of how ASCs contribute to wound healing remain largely unknown. In this study, we explored the cutaneous wound healing ability of ASCs collected from C57BL/6 mice that had been rendered diabetic with streptozotocin (STZ).MethodsASCs were harvested from adipose tissues of type 1 diabetic (T1D) or normal C57BL/6 mice. Cell phenotypes were evaluated by flow cytometry analysis, and cell differentiation into adipocytes, chondrocytes, and osteocytes was compared. Secretions of transforming growth factor β (TGF-β1), basic fibroblast growth factor (bFGF), and vascular endothelial growth factor (VEGF) by ASCs were assessed by ELISA. Migration and proliferation of fibroblasts co-cultured with T1D ASCs or control ASCs were also compared. The therapeutic effects of T1D and control ASCs in promoting wound closure were measured in vivo in a T1D wound mouse model. Granulation tissues were collected and stained with H&E at 14th day. CD34 and collagen I were detected by immunohistochemistry. Expressions of IL-6, α-SMA, CD31, collagen I, and collagen III were quantified by real-time PCR. GFP-expressing ASCs were used to trace in vivo cell differentiation.ResultsT1D ASCs and control ASCs showed similar expression of cell surface markers (CD29, CD34, CD105) and proliferation pattern. They can both differentiate into different cell types. T1D ASCs secreted similar amounts of VEGF and bFGF, but less TGF-β compared with control ASCs. Like control ASCs, T1D ASCs promoted the proliferation and migration of skin fibroblast cells. When injected in cutaneous wound of T1D mice, T1D ASCs increased wound closure and hair follicle regeneration at a comparable extent as ASCs. Mice receiving T1D ASCs or ASCs exhibited significantly higher expressions of collagen I, collagen III, and CD31 and reduced expression of IL-6 in wound tissues. Immunohistochemistry staining showed increased angiogenesis in mice receiving ASCs as was evident by increased CD34+ cells and collagen I staining. GFP+ ASCs injection showed that ASCs differentiated into fibroblasts and endothelial cells in vivo.ConclusionsOur results suggest that T1D ASCs could accelerate cutaneous wound healing. Mechanisms may include increasing fibroblast growth and migration, skin angiogenesis, and differentiation into fibroblasts and endothelial cells. This study provides evidence that diabetic ASCs may be used as a therapeutic option in cutaneous wound healing in diabetic recipients.

Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. 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. Gene expression from muscle biopsies of Lean, Obese insulin sensitive (OIS), Obese insulin resistant (OIR) and obese T2D patients (T2D) were compared for differential expression between the groups (n=7 in each group)

Project description:The obese people with abnormal BMI are predisposed to insulin resistance and diabetes. At the same time, human subjects with obesity and high BMI that are otherwise insulin sensitive are an interesting group to study the underlying gene expression patterns which provide them with such protective phenotype. 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 β-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 β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation.

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Insulin action and binding in isolated hepatocytes from fasted, streptozotocin-diabetic, and older, spontaneously obese rats.

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