ArticleBiophysical journal2008
Collective decision making in bacterial viruses.
Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed, 84 citations in OpenAlex.
- Counting to two: how phages decide between lysis and lysogeny.bioRxiv : the preprint server for biology · 2026Article
- Single-phage profiling illuminates viral individuality during bacterial cell fate determination.Nature communications · 2026Article
- Single-phage profiling illuminates viral individuality during cell fate determination.bioRxiv : the preprint server for biology · 2026Article
- The adaptive plasticity of temperate phageVirus evolution · 2026Article
- Temperate phage evolve to integrate host stress and quorum signals in lysis-lysogeny decisions.PLoS biology · 2026Article
- Coinfecting phages impede each other's entry into the cell.Current biology : CB · 2024Article
- Article
- Superinfection exclusion: A viral strategy with short-term benefits and long-term drawbacks.PLoS computational biology · 2022Article
- Interactions between bacterial and phage communities in natural environments.Nature reviews. Microbiology · 2022Review
- Timescales modulate optimal lysis-lysogeny decision switches and near-term phage reproduction.Virus evolution · 2022Article
- Bacteriophage self-counting in the presence of viral replication.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling.Annual review of biophysics · 2021Review
- When to be temperate: on the fitness benefits of lysis vs. lysogeny.Virus evolution · 2020Article
- High-resolution studies of lysis-lysogeny decision-making in bacteriophage lambda.The Journal of biological chemistry · 2019Review
- Viral invasion fitness across a continuum from lysis to latency.Virus evolution · 2019Article
- Coupling of DNA Replication and Negative Feedback Controls Gene Expression for Cell-Fate Decisions.iScience · 2018Article
- Infection by bacteriophage lambda: an evolving paradigm for cellular individuality.Current opinion in microbiology · 2018Review
- Late-Arriving Signals Contribute Less to Cell-Fate Decisions.Biophysical journal · 2017Article
- Stochastic Cell Fate and Longevity of Offspring.Cell journal · 2017Article
- Cell fate decisions emerge as phages cooperate or compete inside their host.Nature communications · 2017Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For many bacterial viruses, the choice of whether to kill host cells or enter a latent state depends on the multiplicity of coinfection. Here, we present a mathematical theory of how bacterial viruses can make collective decisions concerning the fate of infected cells. We base our theory on mechanistic models of gene regulatory dynamics. Unlike most previous work, we treat the copy number of viral genes as variable. Increasing the viral copy number increases the rate of transcription of viral mRNAs. When viral regulation of cell fate includes nonlinear feedback loops, very small changes in transcriptional rates can lead to dramatic changes in steady-state gene expression. Hence, we prove that deterministic decisions can be reached, e.g., lysis or latency, depending on the cellular multiplicity of infection within a broad class of gene regulatory models of viral decision-making. Comparisons of a parameterized version of the model with molecular studies of the decision structure in the temperate bacteriophage lambda are consistent with our conclusions. Because the model is general, it suggests that bacterial viruses can respond adaptively to changes in population dynamics, and that features of collective decision-making in viruses are evolvable life history traits.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.