ArticleNature microbiology2024
Prediction of strain level phage-host interactions across the Escherichia genus using only genomic information.
Article in Nature microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
105 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- From genomic signals to prediction tools: a critical feature analysis and rigorous benchmark for phage-host prediction.Briefings in bioinformatics · 2025Pooled it
- Article
- Potential Roles of Escherichia coli in IgA Nephropathy: Evidence, Mechanistic Hypotheses and Microbiota-Targeted Strategies.Microbial biotechnology · 2026Review
- Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes using machine learning.Nature microbiology · 2026Article
- Innovative Applications of Artificial Intelligence in Bacteriophage Research: A New Chapter in Future Medicine.Microorganisms · 2026Review
- AI-assisted phage formulation delivered via injectable hydrogels for localized control of implant-associated infections.Bioactive materials · 2026Article
- Phage bioinformatics tools: a review of computational approaches for bacteriophage research.Briefings in bioinformatics · 2026Review
- Phage therapy: from basic biology to clinical application.Nature reviews. Microbiology · 2026Review
- Strain-level molecular and infection traits are associated with differences in phage efficacy against Pseudomonas aeruginosa.Scientific reports · 2026Article
- Phage host range: determinants, dynamics and applications.Nature reviews. Microbiology · 2026Review
- Whole genome sequence-based comparative genomics reveals preliminary genomic features of Salmonella enterica subsp. enterica serovar Enteritidis phage type 1 and phage type 4 strains from EnteroBase.BMC microbiology · 2026Article
- From screening to treatment:Microbiology spectrum · 2026Article
- Genomic and phenotypic characterization of novel jumbo and small bacteriophages infectingMicrobiology spectrum · 2026Article
- Reliable evaluation and learning in multi-input biological association prediction.Briefings in bioinformatics · 2026Article
- PhageMind: generalized strain-level phage host range prediction via meta-learning.Bioinformatics (Oxford, England) · 2026Article
- Cross-family and phage-specific gene requirements for Klebsiella infection revealed by scalable RB-TnSeq genetic screens.PLoS genetics · 2026Article
- Modular plug-and-play engineering of Klebsiella phages with dual receptor-binding proteins for efficient host range design.Journal of biological engineering · 2026Article
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- Intracellular barriers and receptor masking limit success of abioRxiv : the preprint server for biology · 2026Article
45 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Predicting bacteriophage infection of specific bacterial strains promises advancements in phage therapy and microbial ecology. Whether the dynamics of well-established phage-host model systems generalize to the wide diversity of microbes is currently unknown. Here we show that we could accurately predict the outcomes of phage-bacteria interactions at the strain level in natural isolates from the genus Escherichia using only genomic data (area under the receiver operating characteristic curve (AUROC) of 86%). We experimentally established a dataset of interactions between 403 diverse Escherichia strains and 96 phages. Most interactions are explained by adsorption factors as opposed to antiphage systems which play a marginal role. We trained predictive algorithms and pinpoint poorly predicted interactions to direct future research efforts. Finally, we established a pipeline to recommend tailored phage cocktails, demonstrating efficiency on 100 pathogenic E. coli isolates. This work provides quantitative insights into phage-host specificity and supports the use of predictive algorithms in phage therapy.
Indexed as
Identifiers
39482383What 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.