Modeling the effect of copper availability on bacterial denitrification
Article first published online: 30 JUL 2013
© 2013 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Volume 2, Issue 5, pages 756–765, October 2013
How to Cite
MicrobiologyOpen 2013; 2(5): 756–765
- Issue published online: 8 OCT 2013
- Article first published online: 30 JUL 2013
- Manuscript Accepted: 10 JUN 2013
- Manuscript Revised: 7 JUN 2013
- Manuscript Received: 22 JAN 2013
- Biotechnology and Biological Sciences Research Council. Grant Number: BB/H012796/1
- Michaelis–Menten kinetics;
- nitrous oxide;
- Paracoccus denitrificans ;
- respiratory model
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.