Probabilistic models to describe the dynamics of migrating microbial communities

Schroeder, J. L., Lunn, M., Pinto, A. J., Raskin, L. and Sloan, W. T. (2015) Probabilistic models to describe the dynamics of migrating microbial communities. PLoS ONE, 10(3), e0117221. (doi: 10.1371/journal.pone.0117221) (PMID:25803866) (PMCID:PMC4372544)

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Abstract

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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Pinto, Dr Ameet and Schroeder, Dr Joanna and Sloan, Professor William
Authors: Schroeder, J. L., Lunn, M., Pinto, A. J., Raskin, L., and Sloan, W. T.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN:1932-6203
ISSN (Online):1932-6203
Copyright Holders:Copyright © 2015 The Authors
First Published:First published in PLoS ONE 10(3):e0117221
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
456331General and unifying concepts for wastewater treatment plant designWilliam SloanEngineering & Physical Sciences Research Council (EPSRC)EP/F007868/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR
402264The Supergen Biological Fuel Cells ConsortiumWilliam SloanEngineering & Physical Sciences Research Council (EPSRC)EP/H019480/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR
621651Developing an Event Prediction and Correction Framework for Microbial Management in Drinking Water Systems.Ameet PintoEngineering & Physical Sciences Research Council (EPSRC)EP/K035886/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR