title: Stochastic cellular fate decision making by multiple infecting lambda phage.
abstract: Bacteriophage lambda is a classic system for the study of cellular decision making. Both experiments and mathematical models have demonstrated the importance of viral concentration in the lysis-lysogeny decision outcome in lambda phage. However, a recent experimental study using single cell and single phage resolution reported that cells with the same viral concentrations but different numbers of infecting phage (multiplicity of infection) can have markedly different rates of lysogeny. Thus the decision depends on not only viral concentration, but also directly on the number of infecting phage. Here, we attempt to provide a mechanistic explanation of these results using a simple stochastic model of the lambda phage genetic network. Several potential factors including intrinsic gene expression noise, spatial dynamics and cell-cycle effects are investigated. We find that interplay between the level of intrinsic noise and viral protein decision threshold is a major factor that produces dependence on multiplicity of infection. However, simulations suggest spatial segregation of phage particles does not play a significant role. Cellular image processing is used to re-analyse the original time-lapse movies from the recent study and it is found that higher numbers of infecting phage reduce the cell elongation rate. This could also contribute to the observed phenomena as cellular growth rate can affect transcription rates. Our model further predicts that rate of lysogeny is dependent on bacterial growth rate, which can be experimentally tested. Our study provides new insight on the mechanisms of individual phage decision making. More generally, our results are relevant for the understanding of gene-dosage compensation in cellular systems.
authors.affiliation: Department of Mathematics, Imperial College, London, United Kingdom.
authors.forename: Matthew L
authors.initials: ML
authors.lastname: Robb
authors.affiliation: Department of Mathematics, Imperial College, London, United Kingdom.
authors.forename: Vahid
authors.initials: V
authors.lastname: Shahrezaei
mesh_terms: D010582:Bacteriophage lambda / Q000235:genetics* / Q000502:physiology; D015967:Gene Expression Regulation, Viral / Q000502:physiology*; D053263:Gene Regulatory Networks / Q000235:genetics; D007091:Image Processing, Computer-Assisted; D008242:Lysogeny / Q000235:genetics* / Q000502:physiology; D008954:Models, Biological; D013269:Stochastic Processes; D059008:Time-Lapse Imaging
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