ArticlePloS one2014
Stochastic cellular fate decision making by multiple infecting lambda phage.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Counting to two: how phages decide between lysis and lysogeny.bioRxiv : the preprint server for biology · 2026Article
- Characterizing behavioural differentiation in gene regulatory networks with representation graphs.NAR genomics and bioinformatics · 2024Article
- Competitive advantages of T-even phage lysis inhibition in response to secondary infection.PLoS computational biology · 2024Article
- Phage-Inducible Chromosomal Islands as a Diagnostic Platform to Capture and Detect Bacterial Pathogens.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Phage-inducible chromosomal islands promote genetic variability by blocking phage reproduction and protecting transductants from phage lysis.PLoS genetics · 2022Article
- Coupling of DNA Replication and Negative Feedback Controls Gene Expression for Cell-Fate Decisions.iScience · 2018Article
- Late-Arriving Signals Contribute Less to Cell-Fate Decisions.Biophysical journal · 2017Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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