2018
DOI: 10.1101/441311
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Flux-Balance Based Modeling of Biofilm Communities

Abstract: Models of microbial community dynamics generally rely on a sub-scale model for microbial metabolisms. In systems such as distributed multispecies communities like biofilms, where it is not reasonable to simplify to a small number of limiting substrates, tracking the large number of active metabolites likely requires measurement or estimation of large numbers of kinetic and regulatory parameters. Alternatively, a largely kinetics-free methodology is proposed combining cellular level constrained, steady state me… Show more

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Cited by 2 publications
(3 citation statements)
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“…These systems often come with a certain degree of spatial organisation because access to nutrients can be limited to particular locations within the total population (e.g., at the extremities of a biofilm or base of a colony) and, consequently, heterogenous phenotypic traits may be adopted by cells or sub-populations occupying different spatial domains. Some of the best-characterised experimental systems are biofilms formed by the pathogenic bacteria P. aeruginosa [63,64], which have motivated several spatiotemporal modelling frameworks that can be used to understand metabolic cross-feeding (e.g., [65,66,67]). P. aeruginosa is of even greater relevance here, because as a species they are one of the prime examples for which a clear role has been established for quorum sensing in the regulation of cooperative metabolic behaviour [54,55,56], possibly including lactate-based metabolic cross-feeding [22].…”
Section: Application To Microbial Biofilms and Coloniesmentioning
confidence: 99%
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“…These systems often come with a certain degree of spatial organisation because access to nutrients can be limited to particular locations within the total population (e.g., at the extremities of a biofilm or base of a colony) and, consequently, heterogenous phenotypic traits may be adopted by cells or sub-populations occupying different spatial domains. Some of the best-characterised experimental systems are biofilms formed by the pathogenic bacteria P. aeruginosa [63,64], which have motivated several spatiotemporal modelling frameworks that can be used to understand metabolic cross-feeding (e.g., [65,66,67]). P. aeruginosa is of even greater relevance here, because as a species they are one of the prime examples for which a clear role has been established for quorum sensing in the regulation of cooperative metabolic behaviour [54,55,56], possibly including lactate-based metabolic cross-feeding [22].…”
Section: Application To Microbial Biofilms and Coloniesmentioning
confidence: 99%
“…Extensions to accommodate metabolic models with more detailed sets of pathways can be guided using the unique recursive nature of the maximum entropy control law in combination with EFM families as described in [32]. Moreover, increased spatial complexity is also readily introduced following the procedures outlined in [19,65,66,67]. In fact, in [67] a very similar dynamic model to that presented here was considered along with a rather different community-wide objective based on minimising the enthalpy of combustion in the environment.…”
Section: Application To Microbial Biofilms and Coloniesmentioning
confidence: 99%
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