Modeling the effect of copper availability on bacterial denitrification



Vincent Moulton, School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, U.K. Tel: +44 (0) 1603 592607; Fax +44 (0) 1603 593345; E-mail


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 (N2O). The copper-dependent enzyme Nitrous Oxide reductase (Nos) catalyzes the reduction of N2O to dinitrogen. In low-copper conditions, recent experiments in chemostats have demonstrated that Nos efficiency decreases resulting in significant N2O 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 N2O as the copper level decreases.