Modeling the Interaction between ß-Amyloid Aggregates and Choline Acetyltransferase Activity and Its Relation with Cholinergic Dysfunction through Two-Enzyme/Two-Compartment Model.

The effect of ß-amyloid aggregates on activity of choline acetyltransferase (ChAT) which is responsible for synthesizing acetylcholine (ACh) in human brain is investigated through the two-enzyme/two-compartment (2E2C) model where the presynaptic neuron is considered as compartment 1 while both the synaptic cleft and the postsynaptic neuron are considered as compartment 2 through suggesting three different kinetic mechanisms for the inhibition effect. It is found that the incorporation of ChAT inhibition by ß-amyloid aggregates into the 2E2C model is able to yield dynamic solutions for concentrations of generated ß-amyloid, ACh, choline, acetate, and pH in addition to the rates of ACh synthesis and ACh hydrolysis in compartments 1 and 2. It is observed that ChAT activity needs a high concentration of ß-amyloid aggregates production rate. It is found that ChAT activity is reduced significantly when neurons are exposed to high levels of ß-amyloid aggregates leading to reduction in levels of ACh which is one of the most significant physiological symptoms of AD. Furthermore, the system of ACh neurocycle is dominated by the oscillatory behavior when ChAT enzyme is completely inhibited by ß-amyloid. It is observed that the direct inactivation of ChAT by ß-amyloid aggregates may be a probable mechanism contributing to the development of AD.

An allelopathy based model for the Listeria overgrowth phenomenon.

In a standard procedure of food safety testing, the presence of the pathogenic bacterium Listeria monocytogenes can be masked by non-pathogenic Listeria. This phenomenon of Listeria overgrowth is not well understood. We present a mathematical model for the growth of a mixed population of L. innocua and L. monocytogenes that includes competition for a common resource and allelopathic control of L. monocytogenes by L. innocua when this resource becomes limited, which has been suggested as one potential explanation for the overgrowth phenomenon. The model is tested quantitatively and qualitatively against experimental data in batch experiments. Our results indicate that the phenomenon of masked pathogens can depend on initial numbers of each population present, and on the intensity of the allelopathic effect. Prompted by the results for the batch setup, we also analyze the model in a hypothetical chemostat setup. Our results suggest that it might be possible to operate a continuous growth environment such that the pathogens outcompete the non-pathogenic species, even in cases where they would be overgrown in a batch environment.

Antagonistic control of microbial pathogens under iron limitations by siderophore producing bacteria in a chemostat setup.

Certain bacteria develop iron chelation mechanisms that allow them to scavenge dissolved iron from the environment and to make it unavailable to competitors. This is achieved by producing siderophores that bind the iron which is later liberated internally in the cell. Under conditions of iron limitation, siderophore producing bacteria have therefore an antagonistic growth advantage over other species. This has been observed in particular in agricultural and aquacultural systems, as well as in food microbiology. We investigate here the possibility of a probiotic biocontrol strategy to eradicate a well established, often pathogenic, non-chelating population by supplementing the system with generally regarded as safe siderophore producing bacteria. Set in a chemostat setup, our modeling and simulation studies suggest that this is indeed possible in a finite time treatment.

A competition model between Pseudomonas fluorescens and pathogens via iron chelation.

In this study we present a competition model between a non-chelator (e.g. pathogen) microorganism and an iron chelator microorganism (e.g. Pseudomonas fluorescens). This latter is a beneficial bacteria that can inhibit the growth of the non-chelator through its iron chelating capability. This phenomena of iron chelation is shown to prevent the pathogen from proliferating to numbers capable of causing disease. A mathematical model is formulated and used to study this competition. The model proposes a new and simple conceptual explanation of interactions. It is a nonlinear system of ordinary differential equations. A qualitative analysis of the model for the batch case (no inflow or outflow from the system) is carried out and the global behavior of the model variables is studied. For the chemostat case, the equilibrium points were derived and their stability was performed through extensive numerical simulations. It is found that iron chelation is able to control the non-chelator microorganism growth under a wide range of conditions.

Predictive modeling of siderphore production by Pseudomonas fluorescens under iron limitation.

Iron is required by many microorganisms for growth. Although it is the most abundant transition metal on earth, its solubility is very low and therefore its bioavailability is poor. To overcome this limitation, many microorganisms have developed iron chelating mechanisms that enable them to bind the metal to organic molecules from which they are later released. In particular, pseudomonads are prominent producers of the chelator pyoverdine that has a high iron binding capability. We present a mathematical model for pyoverdine production by Pseudomonas fluorescens. It is a nonlinear and non-autonomous system of four ordinary differential equations for the dependent variables size of bacterial population, pyoverdine, dissolved iron and chelated iron. The transient adaptation of the average physiological state of the population to the environmental condition is explicitly included in the model formulation. A complete qualitative description of the model solution is given, based on analytical techniques. The model is quantitatively validated against experimental data of pyoverdine and population size. To this end we conduct and discuss a parameter identification study. It is found that the model, if calibrated using pyoverdine data alone is able to predict the population size and vice versa, with some restrictions. Thus the model can be used as an indirect experimental tool.