Modeling microbial communities from atrazine contaminated soils promotes the development of biostimulation solutions

Abstract

Microbial communities play a vital role in biogeochemical cycles, allowing the biodegradation of a wide range of pollutants. The composition of the community and the interactions between its members affect degradation rate and determine the identity of the final products. Here, we demonstrate the application of sequencing technologies and metabolic modeling approaches towards enhancing biodegradation of atrazine-a herbicide causing environmental pollution. Treatment of agriculture soil with atrazine is shown to induce significant changes in community structure and functional performances. Genome-scale metabolic models were constructed for Arthrobacter, the atrazine degrader, and four other non-atrazine degrading species whose relative abundance in soil was changed following exposure to the herbicide. By modeling community function we show that consortia including the direct degrader and non-degrader differentially abundant species perform better than Arthrobacter alone. Simulations predict that growth/degradation enhancement is derived by metabolic exchanges between community members. Based on simulations we designed endogenous consortia optimized for enhanced degradation whose performances were validated in vitro and biostimulation strategies that were tested in pot experiments. Overall, our analysis demonstrates that understanding community function in its wider context, beyond the single direct degrader perspective, promotes the design of biostimulation strategies.These authors contributed equally:

Labour sharing promotes coexistence in atrazine degrading bacterial communities

“…When evaluating the mineralization potential of the s -triazinic cycle, results are quite contrasted with a significant increase of the mineralization potential in the atrazine only supplemented medium (from 48.3 %; CI 95% =[36.5 – 60] to 86.9 %; CI 95% =[81.6 – 92.2]), and significant decreases or no change in the two and three nitrogen sources supplemented media. Altogether, these results indicate that the upper part of the atrazine degradation pathway ( atzA , trzN , atzB and atzC ) has been improved in the evolved consortia, presumably leading to increased intermediary metabolite production, such as aminoethanol, ethylamine or hypoxanthine 18 . While the upper pathway is constitutively expressed, studies have shown that the lower pathway was repressed by the presence of ammonium in the environment 23 .…”

“…However, in nitrogen limited environments, atrazine degrading capacities must be conserved because mineralization of atrazine leads to the essential delivery of nitrogen 17 . Also, exchange of metabolites, such as desisopropylamine, aminoethanol and desethylamine, are produced and released in the environment during atrazine degradation 18 . Therefore, atrazine biodegradation is a good candidate function to test the BQH predictions, and in particular the emergence of dependency between species in a spatially unstructured environment.…”

Genome-Scale reconstruction ofPaenarthrobacter aurescensTC1 metabolic model towards the study of atrazine bioremediation

“…Additionally, we demonstrate that through using metabolic time dependent simulations, an optimal range of nutrient augmentation may also be planned. Though soil communities are complex in terms of their composition and microbial consortia dynamics, in a recent study we demonstrated the usefulness of modeling approaches for deciphering metabolic complexities 44 , pointing at the future potential of modeling approaches. Despite the complexity of soil communities, supplementing soil with carbon sources is long known to induce a change in microbial structure and function.…”

“…To this end, we simulated the behavior of our metabolic model across time. This was done as described in 44 and illustrated in Supplemental data 5, based on concepts defined in 63 . Briefly, the model works under the following assumptions: (1) A finite start amount of media components is available; (2) A maximal amount of uptake a single cell can acquire from the media in a given time point is defined (the lower bound of the exchange reaction value); (3) New substrate concentrations in time t, are determined by the predicted substrate concentration for the previous step augmented with any additional substrates provided or consumed in the current iteration.…”

“…Xu et al have demonstrate the use of metabolic models for predicting interactions between P.aurescens TC1 and endogenous soil species. Exchange metabolites secreted by non-degraders species contribute for enhancing P.aurescens TC1 growth and expediting degradation efficiency 44,45 . Here, we directly focused on modeling-based identification of media supplements that can enhance degradation.…”