A systems biology analysis connects insulin receptor signaling with glucose transporter translocation in rat adipocytes

Insulin Signaling Pathway Model in Adipocyte Cells

BACKGROUND

Worldwide, type 2 diabetes mellitus (T2DM) is one of the most pervasive and fastgrowing disorders, bringing long-term adverse effects. T2DM arises from pancreatic β-cells deficiency to produce enough insulin or when the body cannot effectively use the insulin produced by such cells. Accordingly, early diagnosis will decrease the long-term effects and high-healthcare costs of diabetes.

OBJECTIVE

The objective is developing an integrated mathematical model of the insulin signaling network based on Brännmark's model, which can simulate the signaling events more comprehensively with the added key components.

METHODS

In this study, a thorough mathematical model of the insulin signaling network was developed by expanding the previously validated model and incorporating the glycogen synthesis module. Parameters (69 parameters) of the integrated model were evaluated by a genetic algorithm by fitting the model predictions to eighty percent of experimental data from the literature. Twenty percent of the experimental data were used to evaluate the final optimized model.

RESULTS

The time-response curves indicate that the GS phosphorylation reaches its maximum in response to 10^-7 M insulin after 4 min, while the maximum phosphorylated GSK3 is attained within ~50 min. The doseresponse curves for the GSP and GSK3 of the insulin signaling intermediaries in response to the increased concentration of insulin, after 10 min, in the input from 0-100 nM exhibits a decreasing trend, whereas an increasing trend was observed for the GS and GSK3P. The GSK and GS phosphorylation sensitivity was enhanced by increasing the initial insulin concentration level from 0.001 to 100 nM. However, the sensitivity of GSK3 to insulin concentration changes (from 0.001 to 100 nM) was 3-fold higher than GS sensitivity.

CONCLUSION

Considerably, the trends of all signaling components simulated by the expanded model shows high compatibility with experimental data (R2 ≥ 0.9), which approves the accuracy of the proposed model. The proposed mathematical model can be used in many biological systems and combined with the whole-body model of the blood glucose regulation system for a better understanding of the causes and potential treatment of type 2 diabetes. Although, this model is not a complete description of insulin signaling, yet it can make profound contributions to improvements regarding other important components and signaling branches such as epidermal growth factor (EGF) signaling, as well as signaling in other cell types in the model structure of future works.

Robust adaptation of PKCζ-IRS1 insulin signaling pathways through integral feedback control

Insulin signaling pathways in muscle tissue play a major role in maintaining glucose homeostasis. Dysregulation in these pathways results in the onset of serious metabolic disorders like type 2 diabetes. Robustness is an essential characteristic of insulin signaling pathways that ensures reliable signal transduction in the presence of perturbations as a result of several feedback mechanisms. Integral control, according to control engineering, provides reliable setpoint tracking and disturbance rejection. The presence of negative feedback and integrating process is crucial for biological processes to achieve integral control. The existence of an integral controller leads to the rejection of perturbations which resulted in the robust regulation of biochemical entities within acceptable levels. In the presentin silicoresearch work, the presence of integral control in the protein kinase Cζ- insulin receptor substrate-1 (PKCζ-IRS1) pathway is identified, verified mathematically and model is simulated in Cell Designer. The data is exported to Minitab software and robustness analysis is carried out statistically using the Mann-Whitney test. The p-value of the results obtained with given parameters perturbed by ±1% is greater than the significance level of 0.05 (0.2132 for 1% error in k7(rate constant of IRS1 phosphorylation), 0.2096 for -1% error in k7, 0.9037 for both ±1% error in insulin and 0.9037 for ±1% error in k1(association rate constant of the first molecule of insulin to bind the insulin receptor), indicated that our hypothesis is proved The results satisfactorily indicate that even when perturbations are present, glucose homeostasis in muscle tissue is robust due to the presence of integral regulation in the PKCζ-IRS1 insulin signaling pathways. In this paper, we have analysed the findings from the framework of robust control theory, which has allowed us to examine that how PKCζ-IRS1 insulin signaling pathways produces desired output in presence of perturbations.

Computational Analysis of Insulin-Glucagon Signalling Network: Implications of Bistability to Metabolic Homeostasis and Disease states

Insulin and glucagon control plasma macronutrient homeostasis through their signalling network composed of multiple feedback and crosstalk interactions. To understand how these interactions contribute to metabolic homeostasis and disease states, we analysed the steady state response of metabolic regulation (catabolic or anabolic) with respect to structural and input perturbations in the integrated signalling network, for varying levels of plasma glucose. Structural perturbations revealed: the positive feedback of AKT on IRS is responsible for the bistability in anabolic zone (glucose >5.5 mmol); the positive feedback of calcium on cAMP is responsible for ensuring ultrasensitive response in catabolic zone (glucose <4.5 mmol); the crosstalk between AKT and PDE3 is responsible for efficient catabolic response under low glucose condition; the crosstalk between DAG and PKC regulates the span of anabolic bistable region with respect to plasma glucose levels. The macronutrient perturbations revealed: varying plasma amino acids and fatty acids from normal to high levels gradually shifted the bistable response towards higher glucose range, eventually making the response catabolic or unresponsive to increasing glucose levels. The analysis reveals that certain macronutrient composition may be more conducive to homeostasis than others. The network perturbations that may contribute to disease states such as diabetes, obesity and cancer are discussed.

Insulin Receptor Trafficking: Consequences for Insulin Sensitivity and Diabetes

Insulin receptor (INSR) has been extensively studied in the area of cell proliferation and energy metabolism. Impaired INSR activities lead to insulin resistance, the key factor in the pathology of metabolic disorders including type 2 diabetes mellitus (T2DM). The mainstream opinion is that insulin resistance begins at a post-receptor level. The role of INSR activities and trafficking in insulin resistance pathogenesis has been largely ignored. Ligand-activated INSR is internalized and trafficked to early endosome (EE), where INSR is dephosphorylated and sorted. INSR can be subsequently conducted to lysosome for degradation or recycled back to the plasma membrane. The metabolic fate of INSR in cellular events implies the profound influence of INSR on insulin signaling pathways. Disruption of INSR-coupled activities has been identified in a wide range of insulin resistance-related diseases such as T2DM. Accumulating evidence suggests that alterations in INSR trafficking may lead to severe insulin resistance. However, there is very little understanding of how altered INSR activities undermine complex signaling pathways to the development of insulin resistance and T2DM. Here, we focus this review on summarizing previous findings on the molecular pathways of INSR trafficking in normal and diseased states. Through this review, we provide insights into the mechanistic role of INSR intracellular processes and activities in the development of insulin resistance and diabetes.