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

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 (Fe 3+ )-reducing bacteria Shewanella spp. and the microaerophilic ferrous iron (Fe 2+ )-oxidizing bacteria Sideroxydans spp. By including the key processes of reduction/oxidation, movement, adhesion, Fe 2+ -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 Fe 3+ -reducing/Fe 2+ -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 Fe 3+ 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 Fe 2+ 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 Fe 3+ reduction rate than longer periods.

Studying mixed-species biofilms of Candida albicans and Staphylococcus aureus using evolutionary game theory

“…In this way, mathematical modelling can support experimental studies. Ideally, the interplay between computational biology studies and wet lab experiments fosters an improved understanding of these complex systems [ 63 , 64 ]. For the system under study, quantitative experimental data are scarce so far.…”