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Advancing microbial sciences by individual-based modelling

Nature Reviews Microbiology volume 14, pages 461–471 (2016)Cite this article

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Abstract

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage–CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE).

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Figure 1: Simplified overview of approaches that are useful for modelling communities and single cells.
Figure 2: Using individual-based models to predict complex systems.
Figure 3: Using individual-based models to predict evolution.

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Acknowledgements

The authors thank their colleagues C. Picioreanu, J. Xavier, B. Smets, V. Grimm, T. Banitz, I. Klapper, T. Curtis, H. Kettle, R. Allen, O. Soyer, T. Grosskopf and many other fellow participants of two workshops for many stimulating discussions: a US National Institute for Mathematical and Biological Synthesis (NIMBioS) workshop in June 2011 in the USA (US National Science Foundation Award #EF-0832858) and the 'Understanding Microbial Communities' workshop that was funded by the Isaac Newton Institute (INI) in Cambridge, UK, held in December 2014. The authors also thank B. Momeni for unpublished images, and S. Matsumoto and C. Picioreanu for sharing data. The authors are grateful to the UK National Centre for the Replacement, Refinement & Reduction of Animals in Research (NC3Rs) for funding their development of individual-based models (IBMs) for the gut environment (eGUT grant NC/K000683/1), to the US National Science Foundation for funding the development and application of IBMs for phytoplankton, and to the Natural Environment Research Council (NERC), UK, for National Capability funding for marine ecosystem modelling.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Northeastern University, 360 Huntington Avenue, Boston, 02115, Massachusetts, USA

    Ferdi L. Hellweger

  2. Centre for Computational Biology & Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK

    Robert J. Clegg & Jan-Ulrich Kreft

  3. Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3DH, UK

    James R. Clark

  4. Laboratory of Microbiology, Wageningen University, 6708 WE Wageningen, The Netherlands

    Caroline M. Plugge

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Correspondence to Jan-Ulrich Kreft.

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Supplementary information 1 (box)

Primer of some modelling approaches used in microbial ecology (PDF 419 kb)

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Software for individual-based modelling in microbial ecology (PDF 212 kb)

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Generic open source platforms for individual-based modelling in microbial ecology (PDF 287 kb)

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Hellweger, F., Clegg, R., Clark, J. et al. Advancing microbial sciences by individual-based modelling. Nat Rev Microbiol 14, 461–471 (2016). https://doi.org/10.1038/nrmicro.2016.62

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