ArticlePloS one2011
The phenotype-fitness map in experimental evolution of phages.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Inferring single-cell heterogeneity of bacteriophage lysis-associated life-history traits from population-scale dynamics.Science advances · 2026Article
- Live and let die: Lysis time variability and resource limitation shape lytic bacteriophage fitness.PLoS computational biology · 2026Article
- Modeling the Phage Properties Best for Therapy.Viruses · 2026Article
- Availability of Charged tRNAs Drives Maximal Protein Synthesis at Intermediate Levels of Codon Usage Bias.Bulletin of mathematical biology · 2026Article
- Single capsid mutations modulating phage adsorption, persistence, and plaque morphology shape evolutionary trajectories in ΦX174.Virus evolution · 2026Article
- Modeling the phage properties best for therapy.bioRxiv : the preprint server for biology · 2025Article
- ΦX174 bacteriophage viability predicted by protein biophysical modeling.bioRxiv : the preprint server for biology · 2025Article
- Article
- Mathematical comparison of protocols for adapting a bacteriophage to a new host.Virus evolution · 2024Article
- Genome-scale top-down strategy to generate viable genome-reduced phages.Nucleic acids research · 2022Article
- Modeling the Directed Evolution of Broad Host Range Phages.Antibiotics (Basel, Switzerland) · 2022Article
- Article
- Superinfection exclusion: A viral strategy with short-term benefits and long-term drawbacks.PLoS computational biology · 2022Article
- Intra-Population Competition during Adaptation to Increased Temperature in an RNA Bacteriophage.International journal of molecular sciences · 2021Article
- Methods for measuring the evolutionary stability of engineered genomes to improve their longevity.Synthetic biology (Oxford, England) · 2021Article
- Article
- Article
- Transcript degradation and codon usage regulate gene expression in a lytic phage.Virus evolution · 2019Article
- Predicting Evolution of the Transcription Regulatory Network in a Bacteriophage.Genome biology and evolution · 2018Article
- Viral attenuation by engineered protein fragmentation.Virus evolution · 2018Article
Corrections and comments
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Authors and funding
3 authors.
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Abstract
Evolutionary biologists commonly interpret adaptations of organisms by reference to a phenotype-fitness map, a model of how different states of a phenotype affect fitness. Notwithstanding the popularity of this approach, it remains difficult to directly test these mappings, both because the map often describes only a small subset of phenotypes contributing to total fitness and because direct measures of fitness are difficult to obtain and compare to the map. Both limitations can be overcome for bacterial viruses (phages) grown in the experimental condition of unlimited hosts. A complete accounting of fitness requires 3 easily measured phenotypes, and total fitness is also directly measurable for arbitrary genotypes. Yet despite the presumed transparency of this system, directly estimated fitnesses often differ from fitnesses calculated from the phenotype-fitness map. This study attempts to resolve these discrepancies, both by developing a more exact analytical phenotype-fitness map and by exploring the empirical foundations of direct fitness estimates. We derive an equation (the phenotype-fitness map) for exponential phage growth that allows an arbitrary distribution of lysis times and burst sizes. We also show that direct estimates of fitness are, in many cases, plausibly in error because the population has not attained stable age distribution and thus violates the model underlying the phenotype-fitness map. In conjunction with data provided here, the new understanding appears to resolve a discrepancy between the reported fitness of phage T7 and the substantially lower value calculated from its phenotype-fitness map.
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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.