Agent-based modelling of iron cycling bacteria provides a framework for testing alternative environmental conditions and modes of action

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Iron-reducing and iron-oxidizing bacteria are of interest in a variety of environmental and industrial applications. Such bacteria often co-occur at oxic-Anoxic gradients in aquatic and terrestrial habitats. In this paper, we present the first computational agent-based model of microbial iron cycling, between the anaerobic ferric iron (Fe3+)-reducing bacteria Shewanella spp. and the microaerophilic ferrous iron (Fe2+)-oxidizing bacteria Sideroxydans spp. By including the key processes of reduction/oxidation, movement, adhesion, Fe2+-equilibration and nanoparticle formation, we derive a core model which enables hypothesis testing and prediction for different environmental conditions including temporal cycles of oxic and anoxic conditions. We compared (i) combinations of different Fe3+-reducing/Fe2+-oxidizing modes of action of the bacteria and (ii) system behaviour for different pH values. We predicted that the beneficial effect of a high number of iron-nanoparticles on the total Fe3+ reduction rate of the system is not only due to the faster reduction of these iron-nanoparticles, but also to the nanoparticles additional capacity to bind Fe2+ on their surfaces. Efficient iron-nanoparticle reduction is confined to pH around 6, being twice as high than at pH 7, whereas at pH 5 negligible reduction takes place. Furthermore, in accordance with experimental evidence our model showed that shorter oxic/anoxic periods exhibit a faster increase of total Fe3+ reduction rate than longer periods.

Cite

CITATION STYLE

APA

Then, A., Ewald, J., Söllner, N., Cooper, R. E., Kösel, K., Ibrahim, B., & Schuster, S. (2022). Agent-based modelling of iron cycling bacteria provides a framework for testing alternative environmental conditions and modes of action. Royal Society Open Science, 9(5). https://doi.org/10.1098/rsos.211553

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free