An Individual-based Model for Simulating Antibiotic Resistance Spread in Bacterial Flocs in Wastewater Treatment Plants


  • Svein H. Stokka
  • Roald Kommedal
  • Kristian Thorsen
  • Cansu Uluseker



antibiotic resistance, wastewater treatment, individual-based model, simulation


Wastewater treatment plants (WWTPs) receive wastewater that carries a variety of pollutants, including antibiotics and antibiotic-resistant bacteria. The potential for horizontal gene transfer of resistance through conjugation – direct cell-to-cell transfer of genes carried on a plasmid – is high in WWTPs because of high cell density and residence time in bacterial flocs. To better understand how resistance spreads by growth and conjugation in such flocs, we propose an individual-based model with a solver algorithm for dynamic simulation. Our model includes only the most relevant bacteria properties and functions such as movement, growth, division, gene transfer, and death. Simulation of our model suggests that resistance can increase by conjugation at the early growth stages of a floc and that the overall rate of gene transfer depends on floc size. Results indicate that our simple model can be a useful tool for examining how gene exchange and heterogeneity contribute to the spread of antibiotic resistance in bacterial flocs.


M. Amarasiri, D. Sano, and S. Suzuki. Understanding human health risks caused by antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG) in water environments: current knowledge and questions to be answered. Crit. Rev. Environ. Sci. Technol., 50(19), 2016–2059, 2020. doi:10.1080/10643389.2019.1692611

A. C. Birkegård, T. Halasa, N. Toft, A. Folkesson, and K. Græsbøll. Send more data: a systematic review of mathematical models of antimicrobial resistance. Antimicrobial Resistance and Infection Control, 7:117, 2018. doi:10.1186/s13756-018-0406-1

D. J. Duarte, R. Oldenkamp, and A. M. J. Ragas. Modelling environmental antibiotic-resistance gene abundance: A meta-analysis. Science of The Total Environment, 659, 335-341, 2019. doi:10.1016/j.scitotenv.2018.12.233

P. Gao, M. Munir, and I. Xagoraraki. Correlation of tetracycline and sulfonamide antibiotics with corresponding resistance genes and resistant bacteria in a conventional municipal wastewater treatment plant. Sci. Total Environ., 421–422,173–183, 2012. doi:10.1016/j.scitotenv.2012.01.061

R. Gregory, J. R. Saunders, and V. A. Saunders. Rule-based modelling of conjugative plasmid transfer and incompatibility. BioSystems, 91, 201–215, 2008. doi:10.1016/j.biosystems.2007.09.003

N. Hassoun-Kheir, Y. Stabholz, J. U. Kreft, R. de la Cruz, J. L. Romalde, J. Nesme, S. J. Sørensen, B. F. Smeths, D. Graham, and M. Paul. Comparison of antibiotic-resistant bacteria and antibiotic resistance genes abundance in hospital and community wastewater: A systematic review. Sci. Total Environ., 743, 140804, 2020. doi:10.1016/j.scitotenv.2020.140804

F. L. Hellweger, X. Ruan, and S. Sanchez. A Simple Model of Tetracycline antibiotic resistance in the aquatic environment (with application to the Poudre River). Int. J. Environ. Res. Public Health, 8, 480-497, 2011. doi:10.3390/ijerph8020480

F. L. Hellweger, R. J. Clegg, J. R. Clark, C. M. Plugge, and J. U. Kreft. Advancing microbial sciences by individual-based modelling. Nat. Rev. Microbiol., 14(7), 461–471, 2016. doi:10.1038/nrmicro.2016.62

D. Jenkins, and J. Wanner. Eds., Activated Sludge – 100 Years and Counting. London, UK: IWA Publishing, 2014. doi:10.2166/9781780404943

G. Koraimann, and M. Wagner. Social behaviour and decision making in bacterial conjugation. Front. Cell. and Infec. Microbiol. 4, 763–783, 2004. doi:10.3389/fcimb.2014.00054

J. U. Kreft, G. Booth, and J. W. T. Wimpenny. BacSim, a simulator for individual-based modelling of bacterial colony growth. Microbiology, 144, 3275–3287, 1998. doi:10.1099/00221287-144-12-3275

J. U. Kreft, C. Picioreanu, J. W. T. Wimpenny, and M. C. M. van Loosdrecht. Individual-based modelling of biofilms. Microbiology, 147(11), 2897–2912, 2001. doi:10.1099/00221287-147-11-2897 S. M. Krone, R. Lu, R. Fox, H. Suzuki, E. M. Top. Modelling the spatial dynamics of plasmid transfer and persistence. Microbiology, 153(8), 2007. doi:10.1099/mic.0.2006/004531-0

L. A. Lardon, B. V. Merkey, S. Martins, A. Dötsch, C. Picioreanu, J.-U. Kreft, and B. F. Smets. iDynoMiCS: next-generation individual-based modelling of biofilms. Environmental Microbiology, 13(9), 2416-2434, 2011. doi:10.1111/j.1462-2920.2011.02414.x

B. Li, D. Taniguchi, J. P. Gedara, V. Gogulancea, R. Gonzalez-Cabaleiro, J. Chen, A. S. McGough, I. D. Ofiteru, T. P. Curtis, and P. Zuliani. NUFEB: A massively parallel simulator for individual-based modelling of microbial communities. PLOS Computational Biology, 15(12), e1007125, 2019. doi:10.1371/journal.pcbi.1007125

J. O’Neil. Tackling drug-resistant infections globally - AMR Review. In: Ro A, ed. Resistance. London, United Kingdom, 1, 84, 2016.

J. Park, M. Cho, and H. S. Son. Simulation model of bacterial resistance to antibiotics using individual-based modeling. Journal of Computational Biology, 25, 1–12, 2018. doi:10.1089/cmb.2018.0064

N. A. Sabri, H. Schmitt, Van der Zaan, H. W. Gerritsen, T. Zuidema, H. H. M. Rijnaarts, and A. A. M. Langenhoff. Prevalence of antibiotics and antibiotic resistance genes in a wastewater effluent-receiving river in the Netherlands. Journal of Environmental Chemical Engineering, 8(1),102245, 2020. doi:10.1016/j.jece.2018.03.004

C. Uluseker, K. M. Kaster, K. Thorsen, D. Basiry, S. Shobana, M. Jain, G. Kumar, R. Kommedal, and I. Pala-Ozkok. A review on occurrence and spread of antibiotic resistance in wastewaters and in wastewater treatment plants: mechanisms and perspectives. Front. Microbiol. 2021. doi:10.3389/fmicb.2021.717809