Modeling the effect of copper availability on bacterial denitrification

Abstract

When denitrifying bacteria such as Paracoccus denitrificans respire anaerobically they convert nitrate to dinitrogen gas via a pathway which includes the potent greenhouse gas, nitrous oxide (NO). The copper-dependent enzyme Nitrous Oxide reductase (Nos) catalyzes the reduction of NO to dinitrogen. In low-copper conditions, recent experiments in chemostats have demonstrated that Nos efficiency decreases resulting in significant NO emissions. For the first time, a chemostat-based mathematical model is developed that describes the anaerobic denitrification pathway based on Michaelis-Menten kinetics and published kinetic parameters. The model predicts steady-state enzyme levels from experimental data. For low copper concentrations, the predicted Nos level is significantly reduced, whereas the levels for the non copper-dependent reductases in the pathway remain relatively unaffected. The model provides time courses for the pathway metabolites that accurately reflect previously published experimental data. In the absence of experimental data purely predictive analyses can also be readily performed by calculating the relative Nos level directly from the copper concentration. Here, the model quantitatively estimates the increasing level of emitted NO as the copper level decreases. We have developed a mathematical model for the denitrification pathway based on existing experimental results, Michaelis-Menten kinetics and experimentally obtained kinetic constants. This is the first such model to incorporate the copper concentration in order to predict emissions of the potent greenhouse gas, nitrous oxide (NO), as well as the other nitrogenous compounds in the pathway. The model predicts increasing NO emissions as the copper level is lowered, in agreement with experimental observations in chemostats. © 2013 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.