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Araujo-Granda, Pablo, Gras, Anna, Ginovart, Marta and Moulton, Vincent 
ORCID: https://orcid.org/0000-0001-9371-6435
(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 |
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| Additional Information: | Funding Information: The financial support of the Ecuador National Secretary of Higher Education, Science, Technology and Innovation (SENESCYT) (Grant Convocatoria Abierta 2011—no. 94-2012), to the Universidad Central del Ecuador (Research Project no. 26 according to RHCU.SO.08 No. 0082-2017 in official resolution with date March 21th, 2017) and the Plan Nacional I + D+i from the Spanish Ministerio de Educación y Ciencia (MICINN, CGL2010-20160). We would also like to thank Dr. David Richardson and Dr. Andrew Gates for helpful discussions at early stages in this project and for providing us with the full dataset presented in Felgate et al. []. Funding Information: The financial support of the Ecuador National Secretary of Higher Education, Science, Technology and Innovation (SENESCYT) (Grant Convocatoria Abierta 2011?no. 94-2012), to the Universidad Central del Ecuador (Research Project no. 26 according to RHCU.SO.08 No. 0082-2017 in official resolution with date March 21th, 2017) and the Plan Nacional I?+?D+i from the Spanish Ministerio de Educaci?n y Ciencia (MICINN, CGL2010-20160). We would also like to thank Dr. David Richardson and Dr. Andrew Gates for helpful discussions at early stages in this project and for providing us with the full dataset presented in Felgate et al. [18]. Publisher Copyright: © 2019, Society for Industrial Microbiology and Biotechnology. |
| 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 |
| UEA Research Groups: | Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 27 Nov 2019 02:02 |
| Last Modified: | 21 Apr 2023 00:15 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/73133 |
| DOI: | 10.1007/s10295-019-02245-8 |
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