Reaction-centric modeling of microbial ecosystems

Stilianos Louca and Michael Doebeli

Ecological Modelling, 2016, vol. 335, issue C, 74-86

Abstract: The growth of microbial populations catalyzing biochemical reactions leads to positive feedback loops and self-amplifying process dynamics at ecosystem scales. Hence, the state of a biocatalyzed process is not completely determined by its physicochemical state, but also depends on current cell or enzyme concentrations that are often unknown. Here we propose a generic approach to modeling reaction networks of natural and engineered microbial ecosystems, that is able to capture the self-amplifying nature of biochemical reactions without explicit reference to the underlying microbial populations. This is achieved by keeping track of a system's “capacity” to perform particular reactions, rather than the cell populations actually catalyzing them. Our reaction-centric approach minimizes the need for cell-physiological parameters such as yield factors and provides a suitable framework for describing a system's dynamics purely in terms of chemical concentrations and fluxes. We demonstrate our approach using data from an incubation experiment involving urea hydrolysis and nitrification, as well as time series from a long-term nitrifying bioreactor experiment. We show that reaction-centric models can capture the dynamical character of microbially catalyzed reaction kinetics and enable the reconstruction of bioprocess states using solely chemical data, hence reducing the need for laborious biotic measurements in environmental and industrial process monitoring.

Keywords: Biochemical reaction network; Bioprocess monitoring; Bioreactor; Pathway-centric; Microbial ecology (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380016301910
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:335:y:2016:i:c:p:74-86

DOI: 10.1016/j.ecolmodel.2016.05.011

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().