A novel method for simulating insulin mediated GLUT4 translocation

Queueing theory model of mTOR complexes' impact on Akt-mediated adipocytes response to insulin

A queueing theory based model of mTOR complexes impact on Akt-mediated cell response to insulin is presented in this paper. The model includes several aspects including the effect of insulin on the transport of glucose from the blood into the adipocytes with the participation of GLUT4, and the role of the GAPDH enzyme as a regulator of mTORC1 activity. A genetic algorithm was used to optimize the model parameters. It can be observed that mTORC1 activity is related to the amount of GLUT4 involved in glucose transport. The results show the relationship between the amount of GAPDH in the cell and mTORC1 activity. Moreover, obtained results suggest that mTORC1 inhibitors may be an effective agent in the fight against type 2 diabetes. However, these results are based on theoretical knowledge and appropriate experimental tests should be performed before making firm conclusions.

Intravenous regular insulin is an efficient and safe procedure for obtaining high-quality cardiac 18F-FDG PET images: an open-label, single-center, randomized controlled prospective trial

BACKGROUND

An open-label, single-center, randomized controlled prospective trial was performed to assess the efficiency and safety of an insulin loading procedure to obtain high-quality cardiac 18F-FDG PET/CT images for patients with coronary artery disease (CAD).

METHODS

Between November 22, 2018 and August 15, 2019, 60 patients with CAD scheduled for cardiac 18F-FDG PET/CT imaging in our department were randomly allocated in a 1:1 ratio to receive an insulin or standardized glucose loading procedure for cardiac 18F-FDG imaging. The primary outcome was the ratio of interpretable images (high-quality images defined as myocardium-to-liver ratios ≥ 1). The secondary outcome was the patient preparation time (time interval between administration of insulin/glucose and 18F-FDG injection). Hypoglycemia events were recorded.

RESULTS

The ratio of interpretable cardiac PET images in the insulin loading group surpassed the glucose loading group (30/30 vs. 25/30, P = 0.026). Preparation time was 71±2 min shorter for the insulin loading group than for the glucose loading group (P < 0.01). Two and six hypoglycemia cases occurred in the insulin and glucose loading groups, respectively.

CONCLUSION

The insulin loading protocol was a quicker, more efficient, and safer preparation for gaining high-quality cardiac 18F-FDG images.

Rescue Protocol to Improve the Image Quality of 18F-FDG PET/CT Myocardial Metabolic Imaging

PURPOSE

18F-FDG PET myocardial metabolic imaging is used to estimate myocardial viability. However, poor image quality can affect the accurate quantification of viable myocardium. We assessed the feasibility of a rescue protocol that reinjected low-dose 18F-FDG with simultaneous 1 to 2 U of insulin injection and oral administration of 10 g of glucose to improve the image quality of 18F-FDG PET myocardial metabolic imaging.

PATIENTS AND METHODS

Fifty-one consecutive patients with poor quality to uninterpretable 18F-FDG PET/CT myocardial metabolic images received the rescue protocol immediately after the initial image acquisition. The postrescue image acquisition was performed 1 hour later. The rescue image quality was compared with the initial image. The qualitative visual estimation of the images was graded as follows: grade 0, homogeneous, minimal uptake; grade 1, predominantly minimal or mild uptake; grade 2, moderate uptake; and grade 3, good uptake. The myocardium-to-blood pool activity ratio (M/B) was measured to assess the image quality quantitatively.

RESULTS

The grades of 0 to 3 were observed in 24 (47%), 27 (53%), 0 (0%), and 0 (0%) patients, respectively, for the initial imaging, and in 0 (0%), 3 (5.9%), 4 (7.8%), and 44 (86.3%) patients for the rescue imaging (P < 0.001). The rescue M/B was significantly higher than the initial M/B (3.4 ± 1.4 vs 1.6 ± 0.6, respectively; P < 0.001).

CONCLUSIONS

The rescue protocol successfully and rapidly improved the quality of myocardial 18F-FDG metabolic imaging.

Modeling of an immune response: Queuing network analysis of the impact of zinc and cadmium on macrophage activation

Chronic obstructive pulmonary disease is characterized by progressive, irreversible airflow obstruction resulting from an abnormal inflammatory response to noxious gases and particles. Alveolar macrophages rely on the transcription factors, nuclear factor κB and mitogen-activated protein kinase, among others, to facilitate the production of inflammatory mediators designed to help rid the lung of foreign pathogens and noxious stimuli. Building a kinetic model using queuing networks, provides a quantitative approach incorporating an initial number of individual molecules along with rates of the reactions in any given pathway. Accordingly, this model has been shown useful to model cell behavior including signal transduction, transcription, and metabolic pathways. The aim of this study was to determine whether a queuing theory model that involves lipopolysaccharide-mediated macrophage activation in tandem with changes in intracellular Cd and zinc (Zn) content or a lack thereof, would be useful to predict their impact on immune activation. We then validate our model with biologic cytokine output from human macrophages relative to the timing of innate immune activation. We believe that our results further prove the validity of the queuing theory approach to model intracellular molecular signaling and postulate that it can be useful to predict additional cell signaling pathways and the corresponding biological outcomes.

From insulin to Akt: Time delays and dominant processes

Akt/PKB regulates numerous processes in the mammalian cell, including cell survival and proliferation, and glucose uptake in response to insulin. Abnormalities in Akt signalling are linked to the development of Type 2 diabetes, cardio-vascular disease, and cancer. In the absence of insulin, Akt is predominantly found in the inactive state in the cytosol. Following insulin stimulation, Akt translocates to the plasma membrane, docks, and is phosphorylated to take on the active conformation. In turn, the activated Akt travels to and phosphorylates its many downstream substrates. Although crucial to the activation process, the translocation of Akt from the cytosol to the plasma membrane is currently not well understood. Here we detail the parameter optimisation of a mathematical model of Akt translocation to experimental data. We have quantified the time delay between the application of insulin and the downstream Akt translocation response, indicating the constraints on the timing of the intermediate processes. A delay of approximately 0.4 min prior to the Akt response was determined for the application of 1 nM insulin to cells in the basal state, whereas it was found that a further transition from physiological insulin to higher stimuli did not incur a delay. Furthermore, our investigation indicates that the dominant processes regulating the appearance of Akt at the plasma membrane differ with the insulin level. For physiological insulin, the rate limiting step was the release of Akt to the plasma membrane in response to the insulin signal. In contrast, at high insulin levels, regulation of the recycling of Akt from the plasma membrane to the cytosol was also required.

Stochastic Simulation of Cellular Metabolism

Increased technological methods have enabled the investigation of biology at nanoscale levels. Such systems require the use of computational methods to comprehend the complex interactions that occur. The dynamics of metabolic systems have been traditionally described utilizing differential equations without fully capturing the heterogeneity of biological systems. Stochastic modeling approaches have recently emerged with the capacity to incorporate the statistical properties of such systems. However, the processing of stochastic algorithms is a computationally intensive task with intrinsic limitations. Alternatively, the queueing theory approach, historically used in the evaluation of telecommunication networks, can significantly reduce the computational power required to generate simulated results while simultaneously reducing the expansion of errors. We present here the application of queueing theory to simulate stochastic metabolic networks with high efficiency. With the use of glycolysis as a well understood biological model, we demonstrate the power of the proposed modeling methods discussed herein. Furthermore, we describe the simulation and pharmacological inhibition of glycolysis to provide an example of modeling capabilities.

Autophagy and GLUT4: The missing pieces

BACKGROUND

Autophagy is a process devoted to degrade and recycle cellular components inside mammalian cells through lysosomal system. It plays a main function in the pathophysiology of several diseases. In type 2 diabetes, works demonstrated the dual functions of autophagy in diabetes biology. Studies had approved the role of autophagy in promoting different routes for movement of integral membrane proteins to the plasma membrane. But its role in regulation of GLUT4 trafficking has not been widely observed. In normal conditions, insulin promotes GLUT4 translocation from intracellular membrane compartments to the plasma membrane, while in type 2 diabetes defects occur in this translocation.

METHOD

Intriguing evidences discussed the contribution of different intracellular compartments in autophagy membrane formation. Furthermore, autophagy serves to mobilise membranes within cells, thereby promoting cytoplasmic components reorganisation. The intent of this review is to focus on the possibility of autophagy to act as a carrier for GLUT4 through regulating GLUT4 endocytosis, intracellular trafficking in different compartments, and translocation to cell membrane.

RESULTS

The common themes of autophagy and GLUT4 have been highlighted. The review discussed the overlapping of endocytosis mechanism and intracellular compartments, and has shown that autophagy and GLUT4 utilise similar proteins (SNAREs) which are used for exocytosis. On top of that, PI3K and AMPK also control both autophagy and GLUT4.

CONCLUSION

The control of GLUT4 trafficking through autophagy could be a promising field for treating type 2 diabetes.

Crosstalk in transition: the translocation of Akt

Akt/PKB is an important crosstalk node at the junction between a number of major signalling pathways in the mammalian cell. As a significant nutrient sensor, Akt plays a central role in many cellular processes, including cell growth, cell survival and glucose metabolism. The dysregulation of Akt signalling is implicated in the development of many diseases, from diabetes to cancer. The translocation of Akt from cytosol to plasma membrane is a crucial step in Akt activation. Akt is initially synthesized on the endoplasmic reticulum, but translocates to the plasma membrane (PM) in response to insulin stimulation, where it may be activated. The Akt is then recycled to the cytoplasm. The activated Akt may propagate signals to downstream substrates both at the PM and in the cytosol, hence understanding the translocation dynamics is an important step in dissecting the signalling system. At the present time, however, knowledge concerning the translocation of either activated and unactivated Akt is scant. Here we present a simple, deterministic, three-compartment ordinary differential equation model of Akt translocation in vitro. This model can reproduce the salient features of Akt translocation in a manner consistent with the experimental data. Furthermore, we demonstrate that this system is equivalent to a damped harmonic oscillator, and analyse the steady state and transient behaviour of the model over the entire parameter space.

The Akt switch model: Is location sufficient?

Akt/PKB is a biochemical regulator that functions as an important cross-talk node between several signalling pathways in the mammalian cell. In particular, Akt is a key mediator of glucose transport in response to insulin. The phosphorylation (activation) of only a small percentage of the Akt pool of insulin-sensitive cells results in maximal translocation of glucose transporter 4 (GLUT4) to the plasma membrane (PM). This enables the diffusion of glucose into the cell. The dysregulation of Akt signalling is associated with the development of diabetes, cancer and cardiovascular disease. Akt is synthesised in the cytoplasm in the inactive state. Under the influence of insulin, it moves to the PM, where it is phosphorylated to form pAkt. Although phosphorylation occurs only at the PM, pAkt is found in many cellular locations, including the PM, the cytoplasm, and the nucleus. Indeed, the spatial distribution of pAkt within the cell appears to be an important determinant of downstream regulation. Here we present a simple, linear, four-compartment ordinary differential equation (ODE) model of Akt activation that tracks both the biochemical state and the physical location of Akt. This model embodies the main features of the activation of this important cross-talk node and is consistent with the experimental data. In particular, it allows different downstream signalling motifs without invoking separate feedback pathways. Moreover, the model is computationally tractable, readily analysed, and elucidates some of the apparent anomalies in insulin signalling via Akt.

Lack of association between the insulin receptor substrates-1 Gly972Arg polymorphism and type-2 diabetes mellitus among Saudis from Eastern Saudi Arabia

Objectives:

To investigate the association between the insulin receptor substrate-1 (IRS1) Gly972Arg polymorphism and type-2 diabetes mellitus (T2DM) among Saudis from Eastern Saudi Arabia.

Methods:

This study was conducted between May and December 2014 at King Fahad Hospital of the University, Al-Khobar, Kingdom of Saudi Arabia. In a case-control study design, a total of 143 subjects (age range: 35-73 years) comprising 74 healthy controls and 69 patients with T2DM were examined. Blood samples were collected from subjects and subjected to genomic DNA extraction and chemical analysis. The IRS1 Gly972Arg polymorphism was then genotyped using the standard polymerase chain reaction-restriction fragment length polymorphism technique.

Results:

Eight out of 74 (10.8%) of the control group carried at least one copy of the mutated allele. The frequency (8.7%) of the IRS1 variant was also found in the diabetic group. Logistic regression analysis showed an adjusted odds ratio of 1.04, 95% confidence interval 0.28 - 3.95, and a p-value of 0.94.

Conclusion:

We failed to find any association between the IRS1 Gly972Arg polymorphism and T2DM.