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 (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.

Nitrous Oxide Metabolism in Nitrate-Reducing Bacteria

“…This phenomenon has been explored in detail in Pa. denitrificans, where bacterial cultures lacking the trace element copper accumulate significant amounts of N 2 O . Furthermore, mathematical models have been developed that quantitatively predict the levels of N 2 O emitted by bacterial denitrification in response to copper availability (Woolfenden et al, 2013). A recent global transcriptomic study by Sullivan and coworkers has revealed that copper deficiency not only affects functional maturation of N 2 OR, but it has an important impact on gene expression in Pa. denitrificans, including expression of nosZ that is downregulated during copper-limited growth (Sullivan, Gates, Appia-Ayme, Rowley, & Richardson, 2013).…”

INDISIM-Paracoccus, an individual-based and thermodynamic model for a denitrifying bacterium

“…In general, fitting a single response variable is straight-forward, but a global fitting for the whole system is much more demanding and challenging to achieve, and even more so if there are different experimental medium conditions jointly with aerobic and anaerobic metabolisms (Woolfenden et al, 2013). We prioritized the diversity of the results because we are convinced that the use of multiple outputs (patterns) to test models is one of the main and most relevant features of the pattern-oriented modelling strategy used in the framework of IBMs (Grimm et al, 2005).…”

“…The global warming potential of N 2 O is 296 times greater than a unit of CO 2 (Richardson et al, 2009). In agricultural soils, N 2 O emissions are of great importance due to the large amount of Nfertilizer in crops and soil organic matter mineralization which depends on the conditions the microorganism encounters in its surrounding environment (Snyder et al, 2009;Woolfenden et al, 2013).…”

“…The simplest models are obtained by adjusting empirical functions to the experimental results used for their studies. More recently, Kampschreur et al (2012) and Woolfenden et al (2013) published specific denitrification models describing the process carried out by microbes in terms of a set of differential equations according to Monod and Michaelis-Menten kinetics. Therefore, the population-level models deal with population variables and fix a set of governing laws (equations) which are based on, or at least consistent with, an assemblage of assumptions about the individual behaviour of microbes.…”

MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process

“…Models such as individual-based models (IBMs) [24], [25], [26], [27], metabolic energy-based modelling (EBMs) [28], reaction-centric models (RCMs) [29], and even, deterministic-population models (DPMs) [30] can obtain useful information from a MMR. The reason is that these reactions, or the stoichiometry between chemical species described in the metabolic sub-model, can help in understanding how the microbial interactions happen and why microbial systems behave as they do.…”