A network biology approach to denitrification in Pseudomonas aeruginosa

Abstract

Pseudomonas aeruginosa is a metabolically flexible member of the Gammaproteobacteria. Under anaerobic conditions and the presence of nitrate, P. aeruginosa can perform (complete) denitrification, a respiratory process of dissimilatory nitrate reduction to nitrogen gas via nitrite (NO2), nitric oxide (NO) and nitrous oxide (N2O). This study focuses on understanding the influence of environmental conditions on bacterial denitrification performance, using a mathematical model of a metabolic network in P. aeruginosa. To our knowledge, this is the first mathematical model of denitrification for this bacterium. Analysis of the long-term behavior of the network under changing concentration levels of oxygen (O2), nitrate (NO3), and phosphate (PO4) suggests that PO4 concentration strongly affects denitrification performance. The model provides three predictions on denitrification activity of P. aeruginosa under various environmental conditions, and these predictions are either experimentally validated or supported by pertinent biological literature. One motivation for this study is to capture the effect of PO4 on a denitrification metabolic network of P. aeruginosa in order to shed light on mechanisms for greenhouse gas N2O accumulation during seasonal oxygen depletion in aquatic environments such as Lake Erie (Laurentian Great Lakes, USA). Simulating the microbial production of greenhouse gases in anaerobic aquatic systems such as Lake Erie allows a deeper understanding of the contributing environmental effects that will inform studies on, and remediation strategies for, other hypoxic sites worldwide.

Fig 1. Denitrification regulatory network of P. aeruginosa.

Green solid arrows indicate upregulation and red dashed arrows indicate downregulation. Model components are PhoPQ, PmrA, Anr, NarXL, Dnr, NirQ, nar, nir, nor, nos, NO ₂, NO, N ₂ O, and N ₂. Our interest lies in perturbation of the external parameters (O ₂, PO ₄, NO ₃) and their effect on the long-term behavior of the network.

Fig 2. Steady states of the denitrification network under different environmental conditions.

The first condition (low O ₂, low PO ₄ and high NO ₃) corresponds to the perfect condition for denitrification and the second condition (low O ₂, high PO ₄ and high NO ₃) corresponds to the denitrification condition disrupted by PO ₄ availability. The remaining conditions can be labeled as aerobic conditions.