INDISIM-Denitrification, an individual-based model for study the denitrification process

Araujo-Granda, Pablo, Gras, Anna, Ginovart, Marta and Moulton, Vincent (2020) INDISIM-Denitrification, an individual-based model for study the denitrification process. Journal of Industrial Microbiology and Biotechnology, 47. pp. 1-20. ISSN 1367-5435

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Abstract

Denitrification is one of the key processes of the global nitrogen (N) cycle driven by bacteria. It has been widely known for more than 100 years as a process by which the biogeochemical N-cycle is balanced. To study this process, we develop an individual-based model called INDISIM-Denitrification. The model embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM and is designed to simulate in aerobic and anaerobic conditions the cell growth kinetics of denitrifying bacteria. INDISIM-Denitrification simulates a bioreactor that contains a culture medium with succinate as a carbon source, ammonium as nitrogen source and various electron acceptors. To implement INDISIM-Denitrification, the individual-based model INDISIM was used to give sub-models for nutrient uptake, stirring and reproduction cycle. Using a thermodynamic approach, the denitrification pathway, cellular maintenance and individual mass degradation were modeled using microbial metabolic reactions. These equations are the basis of the sub-models for metabolic maintenance, individual mass synthesis and reducing internal cytotoxic products. The model was implemented in the open-access platform NetLogo. INDISIM-Denitrification is validated using a set of experimental data of two denitrifying bacteria in two different experimental conditions. This provides an interactive tool to study the denitrification process carried out by any denitrifying bacterium since INDISIM-Denitrification allows changes in the microbial empirical formula and in the energy-transfer-efficiency used to represent the metabolic pathways involved in the denitrification process. The simulator can be obtained from the authors on request.

Item Type: Article
Uncontrolled Keywords: biomass yields,bacterial yield prediction,dependent methionine synthase,denitrification,emissions,escherichia-coli,indisim,individual-based model,microbial-growth,nitric-oxide,nitrous-oxide reductase,netlogo,paracoccus-denitrificans,thermodynamic model,thermodynamic electron equivalent model,yield prediction,applied microbiology and biotechnology,bioengineering,biotechnology ,/dk/atira/pure/subjectarea/asjc/2400/2402
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 27 Nov 2019 02:02
Last Modified: 07 Apr 2020 00:41
URI: https://ueaeprints.uea.ac.uk/id/eprint/73133
DOI: 10.1007/s10295-019-02245-8

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