Literature DB >> 24806936

Variable cell morphology approach for individual-based modeling of microbial communities.

Tomas Storck1, Cristian Picioreanu2, Bernardino Virdis3, Damien J Batstone4.   

Abstract

An individual-based, mass-spring modeling framework has been developed to investigate the effect of cell properties on the structure of biofilms and microbial aggregates through Lagrangian modeling. Key features that distinguish this model are variable cell morphology described by a collection of particles connected by springs and a mechanical representation of deformable intracellular, intercellular, and cell-substratum links. A first case study describes the colony formation of a rod-shaped species on a planar substratum. This case shows the importance of mechanical interactions in a community of growing and dividing rod-shaped cells (i.e., bacilli). Cell-substratum links promote formation of mounds as opposed to single-layer biofilms, whereas filial links affect the roundness of the biofilm. A second case study describes the formation of flocs and development of external filaments in a mixed-culture activated sludge community. It is shown by modeling that distinct cell-cell links, microbial morphology, and growth kinetics can lead to excessive filamentous proliferation and interfloc bridging, possible causes for detrimental sludge bulking. This methodology has been extended to more advanced microbial morphologies such as filament branching and proves to be a very powerful tool in determining how fundamental controlling mechanisms determine diverse microbial colony architectures.
Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 24806936      PMCID: PMC4017289          DOI: 10.1016/j.bpj.2014.03.015

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  45 in total

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8.  Individual-based modelling of biofilms.

Authors:  J U Kreft; C Picioreanu; J W Wimpenny; M C van Loosdrecht
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4.  Cell morphology drives spatial patterning in microbial communities.

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7.  Incorporating Cellular Stochasticity in Solid-Fluid Mixture Biofilm Models.

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8.  Mechanics of biofilms formed of bacteria with fimbriae appendages.

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