Mathematical Modelling of Bacteria and Phage: Coevolution, Ecology and Stochastic Decision Making
File(s)
Author(s)
Robb, Matthew
Type
Thesis
Abstract
The aim of this thesis is to use mathematical models to develop understanding of bacteria and phage interactions. The work focused on both population scale interactions and analysis at the cellular level. Models developed in this thesis reveal the importance of connecting work at the single cell level and population scale level and also the significance of of global cell effects of noise in cellular systems.
At the population level, the effects of gene flow on diversity in coevolving bacteria and phage were analysed. It was found experimentally that the effects of gene flow on diversity depend on the direction of gene flow. Through a deterministic model it was found that this conclusion is dependent on both the rate of gene flow and the genetic interaction. Recent experimental work giving additional information on the factors affecting the rate of choosing lysogeny in lambda phage enabled us to revisit an ecological model to understand the reasons for being temperate. This was carried out using bifurcation analysis and
numerically solving differential equations. At the single cell level, stochastic modelling of genetic networks was used to develop a mechanistic understanding of decision making in lambda phage. It was found using a simple representation of the genetic switch that the effects of intrinsic noise can largely explain experimental observations on the dependence of rate of lysogeny on the number of infecting phage. Further analysis revealed that there are also possible contributions from spatial and cell cycle effects. Stochastic models were also used to investigate the effects of random partitioning at cell partitioning, generation time and cell size on protein noise. Finally, the effects of growth rate on global cell parameters was investigated for simple genetic circuits including the phage genetic switch.
At the population level, the effects of gene flow on diversity in coevolving bacteria and phage were analysed. It was found experimentally that the effects of gene flow on diversity depend on the direction of gene flow. Through a deterministic model it was found that this conclusion is dependent on both the rate of gene flow and the genetic interaction. Recent experimental work giving additional information on the factors affecting the rate of choosing lysogeny in lambda phage enabled us to revisit an ecological model to understand the reasons for being temperate. This was carried out using bifurcation analysis and
numerically solving differential equations. At the single cell level, stochastic modelling of genetic networks was used to develop a mechanistic understanding of decision making in lambda phage. It was found using a simple representation of the genetic switch that the effects of intrinsic noise can largely explain experimental observations on the dependence of rate of lysogeny on the number of infecting phage. Further analysis revealed that there are also possible contributions from spatial and cell cycle effects. Stochastic models were also used to investigate the effects of random partitioning at cell partitioning, generation time and cell size on protein noise. Finally, the effects of growth rate on global cell parameters was investigated for simple genetic circuits including the phage genetic switch.
Version
Open Access
Date Issued
2013-11
Date Awarded
2014-03
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Shahrezaei, Vahid
Gudelj, Ivana
Sponsor
Natural Environment Research Council (Great Britain)
Grant Number
NE/H524730/1
Publisher Department
Mathematics
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)