ArticleViruses2019
Promises and Pitfalls of In Vivo Evolution to Improve Phage Therapy.
Article in Viruses, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 32 citations in OpenAlex.
- Modeling the Phage Properties Best for Therapy.Viruses · 2026Article
- Modeling the phage properties best for therapy.bioRxiv : the preprint server for biology · 2025Article
- Bacteriophage-Based Approach Against Biofilm Infections Associated with Medical Devices: A Narrative Review of ESKAPE Pathogens.International journal of molecular sciences · 2025Review
- Phage-induced protection against lethal bacterial reinfection.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- More evolvable bacteriophages better suppress their host.Evolutionary applications · 2024Article
- Thinking Phage Innovations Through Evolution and Ecology.PHAGE (New Rochelle, N.Y.) · 2024Review
- The untapped potential of phage model systems as therapeutic agents.Virus evolution · 2024Article
- NovelPHAGE (New Rochelle, N.Y.) · 2023Article
- Stepwise Evolution of E. coli C and ΦX174 Reveals Unexpected Lipopolysaccharide (LPS) Diversity.Molecular biology and evolution · 2023Article
- Experimental Evolution of the TolC-Receptor Phage U136B Functionally Identifies a Tail Fiber Protein Involved in Adsorption through Strong Parallel Adaptation.Applied and environmental microbiology · 2023Article
- Single-Cell Approach Reveals Intercellular Heterogeneity in Phage-Producing Capacities.Microbiology spectrum · 2023Article
- Comparison of bacterial suppression by phage cocktails, dual-receptor generalists, and coevolutionarily trained phages.Evolutionary applications · 2023Article
- Resistance-resistant antibacterial treatment strategies.Frontiers in antibiotics · 2023Article
- Article
- A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens.iScience · 2022Review
- Treatment of Wound Infections in a Mouse Model Using ZnACS nano · 2022Article
- Review
- Atomistic basis of force generation, translocation, and coordination in a viral genome packaging motor.Nucleic acids research · 2021Article
- Evaluating the potential efficacy and limitations of a phage for joint antibiotic and phage therapy ofProceedings of the National Academy of Sciences of the United States of America · 2021Article
- Fighting microbial pathogens by integrating host ecosystem interactions and evolution.BioEssays : news and reviews in molecular, cellular and developmental biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Phage therapy is the use of bacterial viruses (phages) to treat bacterial infections, a medical intervention long abandoned in the West but now experiencing a revival. Currently, therapeutic phages are often chosen based on limited criteria, sometimes merely an ability to plate on the pathogenic bacterium. Better treatment might result from an informed choice of phages. Here we consider whether phages used to treat the bacterial infection in a patient may specifically evolve to improve treatment on that patient or benefit subsequent patients. With mathematical and computational models, we explore in vivo evolution for four phage properties expected to influence therapeutic success: generalized phage growth, phage decay rate, excreted enzymes to degrade protective bacterial layers, and growth on resistant bacteria. Within-host phage evolution is strongly aligned with treatment success for phage decay rate but only partially aligned for phage growth rate and growth on resistant bacteria. Excreted enzymes are mostly not selected for treatment success. Even when evolution and treatment success are aligned, evolution may not be rapid enough to keep pace with bacterial evolution for maximum benefit. An informed use of phages is invariably superior to naive reliance on within-host evolution.
Indexed as
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What OpenQuestion holds
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.