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.