Computational Modeling of Glucose Uptake in the Enterocyte

Experimental and computational investigation of the kinetic evolution of the glutaminolysis pathway and its interplay with the glycolysis pathway

Exploring cellular responses necessitates studying real-time metabolic pathway kinetics, considering the adaptable nature of cells. Glycolysis and glutaminolysis are interconnected pathways fundamental to driving cellular metabolism, generating both energy and essential biosynthetic molecules. While prior studies explored glycolysis tracking, this research focuses on monitoring the kinetics of the glutaminolysis pathway by evaluating the effect of glutamine availability on glycolytic kinetics and by investigating the impact of a stimulator (oligomycin) and inhibitor (2DG) on the glycolytic flux in the presence of glutamine. Additionally, we adapted a rate equation model to provide improved understanding of the pathway kinetics. The experimental and simulated results indicate a significant reduction in extracellular lactate production in the presence of glutamine, reflecting a shift from glycolysis towards oxidative phosphorylation, due to the additional contribution of glutamine to energy production through the ETC (electron transport chain), reducing the glycolytic load. Oligomycin, an ETC inhibitor, increases lactate production to the original glycolytic level, despite the presence of glutamine. Nevertheless, its mechanism is influenced by the presence of glutamine, as predicted by the model. Conversely, 2DG notably reduces lactate production, affirming its glycolytic origin. The gradual increase in lactate production under the influence of 2DG implies increased activation of glutaminolysis as an alternative energy source. The model also simulates the varying metabolic responses under varying carbon/modulator concentrations. In conclusion, the kinetic model described here contributes to the understanding of changes in intracellular metabolites and their interrelationships in a way which would be challenging to obtain solely through kinetic assays.

Brain microvascular endothelial cell metabolism and its ties to barrier function

Brain microvascular endothelial cells, which lie at the interface between blood and brain, are critical to brain energetics. These cells must precisely balance metabolizing nutrients for their own demands with transporting nutrients into the brain to sustain parenchymal cells. It is essential to understand this integrated metabolism and transport so that we can develop better diagnostics and therapeutics for neurodegenerative diseases such as Alzheimer's disease, multiple sclerosis, and traumatic brain injury. In this chapter, we first describe brain microvascular endothelial cell metabolism and how these cells regulate both blood flow and nutrient transport. We then explain the impact of brain microvascular endothelial cell metabolism on the integrity of the blood-brain barrier, as well as how metabolites produced by the endothelial cells impact other brain cells. We detail some ways that cell metabolism is typically measured experimentally and modeled computationally. Finally, we describe changes in brain microvascular endothelial cell metabolism in aging and neurodegenerative diseases. At the end of the chapter, we highlight areas for future research in brain microvascular endothelial cell metabolism. The goal of this chapter is to underscore the importance of nutrient metabolism and transport at the brain endothelium for cerebral health and neurovascular disease treatment.

Computational Modelling of Glucose Uptake by SGLT1 and Apical GLUT2 in the Enterocyte

It has been suggested that glucose absorption in the small intestine depends on both constitutively expressed SGLT1 and translocated GLUT2 in the brush border membrane, especially in the presence of high levels of luminal glucose. Here, we present a computational model of non-isotonic glucose uptake by small intestinal epithelial cells. The model incorporates apical uptake via SGLT1 and GLUT2, basolateral efflux into the blood via GLUT2, and cellular volume changes in response to non-isotonic conditions. The dependence of glucose absorption on luminal glucose, blood flow rate, and inlet blood glucose concentration is studied. Uptake via apical GLUT2 is found to be sensitive to all these factors. Under a range of conditions, the maximum apical GLUT2 flux is about half of the SGLT1 flux and is achieved at high luminal glucose (> 50 mM), high blood flow rates, and low inlet blood concentrations. In contrast, SGLT1 flux is less sensitive to these factors. When luminal glucose concentration is less than 10 mM, apical GLUT2 serves as an efflux pathway for glucose to move from the blood to the lumen. The model results indicate that translocation of GLUT2 from the basolateral to the apical membrane increases glucose uptake into the cell; however, the reduction of efflux capacity results in a decrease in net absorption. Recruitment of GLUT2 from a cytosolic pool elicits a 10–20% increase in absorption for luminal glucose levels in the a 20–100 mM range. Increased SGLT1 activity also leads to a roughly 20% increase in absorption. A concomitant increase in blood supply results in a larger increase in absorption. Increases in apical glucose transporter activity help to minimise cell volume changes by reducing the osmotic gradient between the cell and the lumen.

Mechanistic Computational Models of Epithelial Cell Transporters-the Adorned Heroes of Pharmacokinetics

Epithelial membrane transporter kinetics portray an irrefutable role in solute transport in and out of cells. Mechanistic models are used to investigate the transport of solutes at the organ, tissue, cell or membrane scale. Here, we review the recent advancements in using computational models to investigate epithelial transport kinetics on the cell membrane. Various methods have been employed to develop transport phenomena models of solute flux across the epithelial cell membrane. Interestingly, we noted that many models used lumped parameters, such as the Michaelis-Menten kinetics, to simplify the transporter-mediated reaction term. Unfortunately, this assumption neglects transporter numbers or the fact that transport across the membrane may be affected by external cues. In contrast, more recent mechanistic transporter kinetics models account for the transporter number. By creating models closer to reality researchers can investigate the downstream effects of physical or chemical disturbances on the system. Evidently, there is a need to increase the complexity of mechanistic models investigating the solute flux across a membrane to gain more knowledge of transporter-solute interactions by assigning individual parameter values to the transporter kinetics and capturing their dependence on each other. This change results in better pharmacokinetic predictions in larger scale platforms. More reliable and efficient model predictions can be made by creating mechanistic computational models coupled with dedicated in vitro experiments. It is also vital to foster collaborative efforts among transporter kinetics researchers in the modeling, material science and biological fields.

Glucose transporters in the small intestine in health and disease

Absorption of monosaccharides is mainly mediated by Na+-D-glucose cotransporter SGLT1 and the facititative transporters GLUT2 and GLUT5. SGLT1 and GLUT2 are relevant for absorption of D-glucose and D-galactose while GLUT5 is relevant for D-fructose absorption. SGLT1 and GLUT5 are constantly localized in the brush border membrane (BBM) of enterocytes, whereas GLUT2 is localized in the basolateral membrane (BLM) or the BBM plus BLM at low and high luminal D-glucose concentrations, respectively. At high luminal D-glucose, the abundance SGLT1 in the BBM is increased. Hence, D-glucose absorption at low luminal glucose is mediated via SGLT1 in the BBM and GLUT2 in the BLM whereas high-capacity D-glucose absorption at high luminal glucose is mediated by SGLT1 plus GLUT2 in the BBM and GLUT2 in the BLM. The review describes functions and regulations of SGLT1, GLUT2, and GLUT5 in the small intestine including diurnal variations and carbohydrate-dependent regulations. Also, the roles of SGLT1 and GLUT2 for secretion of enterohormones are discussed. Furthermore, diseases are described that are caused by malfunctions of small intestinal monosaccharide transporters, such as glucose-galactose malabsorption, Fanconi syndrome, and fructose intolerance. Moreover, it is reported how diabetes, small intestinal inflammation, parental nutrition, bariatric surgery, and metformin treatment affect expression of monosaccharide transporters in the small intestine. Finally, food components that decrease D-glucose absorption and drugs in development that inhibit or downregulate SGLT1 in the small intestine are compiled. Models for regulations and combined functions of glucose transporters, and for interplay between D-fructose transport and metabolism, are discussed.

Effects of 120 g/h of Carbohydrates Intake during a Mountain Marathon on Exercise-Induced Muscle Damage in Elite Runners

Background-exercise-induced muscle damage (EIMD) and internal exercise load are increased after competing in ultraendurance events such as mountain marathons. Adequate carbohydrate (CHO) intake during exercise optimizes athletic performance and could limit EIMD, reduce internal exercise load and, thus, improve recovery. Therefore, the aim of this study was to research into and compare the effects of high CHO intake (120 g/h) in terms of CHO intake recommendation (90 g/h) and regular CHO intake performed by ultraendurance athletes (60 g/h) during a mountain marathon, on exercise load and EIMD markers (creatine kinase (CK), lactate dehydrogenase (LDH), glutamic oxaloacetic transaminase (GOT), urea and creatinine). Materials and Methods-a randomized trial was carried out on 20 male elite runners who had previously undertaken nutritional and gut training, and who consumed different CHO dosages according to experimental (EXP-120 g/h), control (CON-90 g/h) and low CHO intake (LOW-60 g/h) groups during a ~4000 m cumulative slope mountain marathon. EIMD markers were analyzed before the race and 24 h afterwards. Internal exercise load was calculated based on rate of perceived exertion (RPE) during and after the marathon event. Results-internal exercise load during the mountain marathon was significantly lower (p = 0.019; η2p = 0.471) in EXP (3805 ± 281 AU) compared to LOW (4688 ± 705 AU) and CON (4692 ± 716 AU). Moreover, results revealed that the EXP group evidenced significantly lower CK (p = 0.019; η2p = 0.373), LDH (p < 0.001; η2p = 0.615) and GOT (p = 0.003; η2p = 0.500) values 24 h after the mountain marathon race compared to LOW and CON. Along these lines, EIMD and exercise load evidenced a close correlation (R = 0.742; p < 0.001). Conclusion: High CHO intake (120 g/h) during a mountain marathon could limit the EIMD observed by CK, LDH and GOT and internal exercise load compared to CHO ingestion of 60 and 90 g/h.