Probabilistic models to describe the dynamics of migrating microbial communities.
Probabilistic models to describe the dynamics of migrating microbial communities.
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DOI：
10.1371/journal.pone.0117221
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Sloan WT
中科院分区：
文献类型：
--
作者：
Schroeder JL;Lunn M;Pinto AJ;Raskin L;Sloan WT
在除最无菌环境之外的所有环境中，细菌将驻留在通过导管输送的流体中，并且其中一些细菌将作为生物膜附着并生长在导管壁上。在输送点处流体中的细菌的浓度和多样性将是当其进入导管时的那些细菌和由于从生物膜接种而被夹带到流中的那些细菌的混合。实例包括通过导管的流体，例如饮用水管网、气管内导管、导管和通气系统。在这里，我们提出了两个概率模型来描述散装流体微生物群落的组成的变化，因为它们是通过管道运输，同时暴露于生物膜社区。第一个（离散）模型模拟单个细胞的绝对数量，而另一个（连续）模型模拟的相对丰度的分类群在散装流体。离散模型建立在出生-死亡过程的基础上，其中社区每次改变一个个体，系统中的细胞数量可以变化。连续模型是从离散模型导出的随机微分方程，并且还可以适应本体流体的承载能力的变化。这些模型提供了一个新的拉格朗日框架，调查和预测迁移微生物群落的动态。在本文中，我们比较了这两种模型，讨论了它们的优点，可能的应用和饮用水分配系统的背景下，目前的模拟结果。我们的研究结果提供了新的见解随机动力学的非静态微生物群落的组成，暴露于生物膜的影响，并提供了一个新的途径，模拟微生物动力学的系统中，流体被运输。
In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete) model simulates absolute numbers of individual cells, whereas the other (continuous) model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.
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DOI：
10.1098/rspb.2013.1760
发表时间：
2013-11-22
期刊：
Proceedings. Biological sciences
影响因子：
--
作者：
Besemer K;Singer G;Quince C;Bertuzzo E;Sloan W;Battin TJ
通讯作者：
Battin TJ
影响因子：
3.7
作者：
Halliday E;McLellan SL;Amaral-Zettler LA;Sogin ML;Gast RJ
通讯作者：
Gast RJ
DOI：
10.1073/pnas.1000604107
发表时间：
2010-08-31
影响因子：
11.1
作者：
Ofiteru, Irina Dana;Lunn, Mary;Sloan, William T.
通讯作者：
Sloan, William T.
影响因子：
2.4
作者：
Warren, Patrick B.
通讯作者：
Warren, Patrick B.
影响因子：
4.2
作者：
Woodcock, Stephen;van der Gast, Christopher J.;Sloan, William T.
通讯作者：
Sloan, William T.