4.6 Article

Probabilistic Models to Describe the Dynamics of Migrating Microbial Communities

Journal

PLOS ONE
Volume 10, Issue 3, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0117221

Keywords

-

Funding

  1. Engineering and Physical Sciences Research Council, UK [EP/F007868, EP/H019480/1, EP/K035886/1]
  2. National Science Foundation Award [0613193]
  3. University of Michigan
  4. Engineering and Physical Sciences Research Council [EP/F007868/1, EP/K038885/1, EP/D073693/1, EP/H009604/1, EP/K035886/1] Funding Source: researchfish
  5. EPSRC [EP/K038885/1, EP/D073693/1, EP/H009604/1, EP/K035886/1, EP/F007868/1] Funding Source: UKRI
  6. Directorate For Engineering [0613193] Funding Source: National Science Foundation
  7. Div Of Chem, Bioeng, Env, & Transp Sys [0613193] Funding Source: National Science Foundation

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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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