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Candidiasis is reported to be the most common fungal infection in the critical care setting. The causative agent of this infection is a commensal pathogen belonging to the genus

Absolute concentration robustness (ACR) and concordance are novel concepts in the theory of robustness and stability within Chemical Reaction Network Theory. In this paper, we have extended Shinar and Feinberg's reaction network analysis approach to the insulin signaling system based on recent advances in decomposing reaction networks. We have shown that the network with 20 species, 35 complexes, and 35 reactions is concordant, implying at most one positive equilibrium in each of its stoichiometric compatibility class. We have obtained the system's finest independent decomposition consisting of 10 subnetworks, a coarsening of which reveals three subnetworks which are not only functionally but also structurally important. Utilizing the network's deficiency-oriented coarsening, we have developed a method to determine positive equilibria for the entire network. Our analysis has also shown that the system has ACR in 8 species all coming from a deficiency zero subnetwork. Interestingly, we have shown that, for a set of rate constants, the insulin-regulated glucose transporter GLUT4 (important in glucose energy metabolism), has stable ACR., 34 pages, 1 figure

Candidiasis is reported as the most common fungal infection in the critical care setting. The causative agent of this infection is a commensal pathogen belonging to the genus Candida, most common species of which is the Candida albicans. The ergosterol pathway in yeast is a common target by many antifungal agents since ergosterol is an essential component of the cell membrane. The current antifungal agent of choice for the treatment of Candidiasis is fluconazole, which is classified under the azole antifungals. In recent years, the significant increase of fluconazole-resistant C. albicans in clinical samples calls for a need to search for other possible drug targets. In this study, we constructed a mathematical model of the ergosterol pathway of C. albicans using ordinary differential equations with mass action kinetics. From the model simulations, we found the following results: (1) a partial inhibition of the sterol-methyltransferase enzyme yields a fair amount of fluconazole resistance, (2) an overexpression of the ERG6 gene, leading to increased sterol-methyltransferase enzyme, is a good target of antifungals as an adjunct to fluconazole, (3) a partial inhibition of lanosterol yields a fair amount of fluconazole resistance, (4) the C5-desaturase enzyme is not a good target of antifungals as an adjunct to fluconazole, (5) the C14α-demethylase enzyme is confirmed to be a good target of fluconazole, and (6) the dose-dependent effect of fluconazole is confirmed. This study hopes to aid experimenters narrow down the possible drug targets prior to doing costly and time-consuming experiments, and to serve as a cross-validation tool for experimental data.

Absolute concentration robustness (ACR) and concordance are novel concepts in the theory of robustness and stability within Chemical Reaction Network Theory. In this paper, we have extended Shinar and Feinberg's reaction network analysis approach to the insulin signaling system based on recent advances in decomposing reaction networks. We have shown that the network with 20 species, 35 complexes, and 35 reactions is concordant, implying at most one positive equilibrium in each of its stoichiometric compatibility class. We have obtained the system's finest independent decomposition consisting of 10 subnetworks, a coarsening of which reveals three subnetworks which are not only functionally but also structurally important. Utilizing the network's deficiency-oriented coarsening, we have developed a method to determine positive equilibria for the entire network. Our analysis has also shown that the system has ACR in 8 species all coming from a deficiency zero subnetwork. Interestingly, we have shown that, for a set of rate constants, the insulin-regulated glucose transporter GLUT4 (important in glucose energy metabolism), has stable ACR.

Mathematical models for the spread of diseases help us understand the mechanisms on how diseases spread, evaluate the possible effects of interventions, predict outcomes of epidemics, and forecast the course of outbreaks. Compartmental models are widely used in synthetic biology since they can represent a biological system as an assembly of various parts or compartments with different functions. Here we present a framework for the analysis of a compartmental model for the transmission of diseases using ordinary differential equations. We apply this method on a study about the spread of tuberculosis.

Mathematical models for the spread of diseases help us understand the mechanisms on how diseases spread, evaluate the possible effects of interventions, predict outcomes of epidemics, and forecast the course of outbreaks. Compartmental models are widely used in synthetic biology since they can represent a biological system as an assembly of various parts or compartments with different functions. Here we present a framework for the analysis of a compartmental model for the transmission of diseases using ordinary differential equations. We apply this method on a study about the spread of tuberculosis.