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Bacteriophage Evolution and Host Range
Research Guide

What is Bacteriophage Evolution and Host Range?

Bacteriophage evolution and host range examines how phages adapt through mutation, coevolution, and receptor-binding diversification to expand or shift infection specificity across bacterial hosts.

Experimental evolution tracks arms-race dynamics between phages and bacteria, revealing rapid host range shifts (Koskella and Brockhurst, 2014, 872 citations). Comparative genomics identifies specificity determinants in tail fiber proteins across phage families. Over 1700 papers explore these processes since Weinbauer (2003, 1735 citations) highlighted viral abundance exceeding prokaryotes.

Curated Papers

Key Challenges

Why It Matters

Phage host range evolution determines therapy success against MDR pathogens, as evolved resistance reduces efficacy (Chan et al., 2016, 691 citations). Coevolutionary insights predict community dynamics in microbiomes, informing phage cocktails for Pseudomonas infections. Koskella and Brockhurst (2014) show bacteria-phage arms races drive diversity, impacting antibiotic alternatives amid resistance spread (Peterson and Kaur, 2018, 957 citations).

Key Research Challenges

Quantifying Coevolutionary Dynamics

Tracking reciprocal adaptations requires long-term experiments distinguishing arms-race from Red Queen dynamics (Koskella and Brockhurst, 2014). High mutation rates complicate fitness trade-offs across host ranges. Statistical models struggle with metagenomic noise in natural populations (Weinbauer, 2003).

Determining Host Range Mechanisms

Receptor-binding protein mutations drive specificity shifts, but genomics alone misses functional validation (Yooseph et al., 2007, 925 citations). Phage families vary in diversification strategies, hindering predictions. CRISPR defenses add complexity to infection outcomes (Sorek et al., 2013).

Predicting Therapy Escape Variants

Evolved phages regain sensitivity in MDR strains, but bacterial countermeasures emerge rapidly (Chan et al., 2016). Metagenomic surveys reveal uncultured diversity, underestimating risks (Roux et al., 2018, 727 citations). Models fail to integrate horizontal gene transfer effects.

Essential Papers

Ecology of prokaryotic viruses

Markus G. Weinbauer · 2003 · FEMS Microbiology Reviews · 1.7K citations

The finding that total viral abundance is higher than total prokaryotic abundance and that a significant fraction of the prokaryotic community is infected with phages in aquatic systems has stimula...

Antibiotic Resistance Mechanisms in Bacteria: Relationships Between Resistance Determinants of Antibiotic Producers, Environmental Bacteria, and Clinical Pathogens

Elizabeth Peterson, Parjit Kaur · 2018 · Frontiers in Microbiology · 957 citations

Emergence of antibiotic resistant pathogenic bacteria poses a serious public health challenge worldwide. However, antibiotic resistance genes are not confined to the clinic; instead they are widely...

The Sorcerer II Global Ocean Sampling Expedition: Expanding the Universe of Protein Families

Shibu Yooseph, Granger Sutton, Douglas B. Rusch et al. · 2007 · PLoS Biology · 925 citations

Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehens...

Bacteria–phage coevolution as a driver of ecological and evolutionary processes in microbial communities

Britt Koskella, Michael A. Brockhurst · 2014 · FEMS Microbiology Reviews · 872 citations

Bacteria-phage coevolution, the reciprocal evolution between bacterial hosts and the phages that infect them, is an important driver of ecological and evolutionary processes in microbial communitie...

Minimum Information about an Uncultivated Virus Genome (MIUViG)

Simon Roux, Evelien M. Adriaenssens, Bas E. Dutilh et al. · 2018 · Nature Biotechnology · 727 citations

Phage selection restores antibiotic sensitivity in MDR Pseudomonas aeruginosa

Benjamin K. Chan, Mark Sistrom, John E. Wertz et al. · 2016 · Scientific Reports · 691 citations

Abstract Increasing prevalence and severity of multi-drug-resistant (MDR) bacterial infections has necessitated novel antibacterial strategies. Ideally, new approaches would target bacterial pathog...

The ancient Virus World and evolution of cells.

Eugene V. Koonin, Tatiana G. Senkevich, Valerian V. Dolja · 2006 · Biology Direct · 687 citations

W. Ford Doolittle, J. Peter Gogarten, and Arcady Mushegian.

Reading Guide

Foundational Papers

Start with Weinbauer (2003, 1735 citations) for viral ecology baselines, then Koskella and Brockhurst (2014, 872 citations) for coevolution mechanisms, as they frame experimental and genomic approaches.

Recent Advances

Study Chan et al. (2016, 691 citations) on phage therapy restoration and Roux et al. (2018, 727 citations) for uncultured virus standards to grasp applied evolution.

Core Methods

Core techniques include experimental evolution via serial dilution, comparative genomics of receptor-binding proteins, and metagenomic clustering (Yooseph et al., 2007; Ren et al., 2017).

How PapersFlow Helps You Research Bacteriophage Evolution and Host Range

Discover & Search

Research Agent uses searchPapers('bacteriophage host range evolution coevolution') to retrieve Koskella and Brockhurst (2014), then citationGraph reveals 872 citing papers on arms-race dynamics, while findSimilarPapers expands to experimental evolution studies and exaSearch uncovers niche aquatic phage ecology from Weinbauer (2003).

Analyze & Verify

Analysis Agent applies readPaperContent on Chan et al. (2016) to extract phage selection data against MDR Pseudomonas, verifyResponse with CoVe cross-checks claims against Sorek et al. (2013) CRISPR mechanisms, and runPythonAnalysis simulates mutation rates with NumPy/pandas on host range datasets; GRADE scores evidence strength for therapy predictions.

Synthesize & Write

Synthesis Agent detects gaps in host range prediction models across phage families, flags contradictions between lab coevolution (Koskella and Brockhurst, 2014) and metagenomic data (Yooseph et al., 2007), while Writing Agent uses latexEditText, latexSyncCitations for evolved receptor protein figures, and latexCompile generates phage-bacteria interaction diagrams via exportMermaid.

Use Cases

"Analyze mutation rates in experimental phage evolution datasets from coevolution papers"

Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (NumPy/pandas plots burst sizes vs. host range) → matplotlib figures of arms-race trajectories.

"Draft LaTeX review on phage host range diversification with citations"

Synthesis Agent → gap detection → Writing Agent → latexEditText('receptor-binding evolution') → latexSyncCitations(Koskella 2014) → latexCompile → PDF with mermaid coevolution diagrams.

"Find code for phage host range genomic analysis"

Research Agent → paperExtractUrls(Ren et al. 2017 VirFinder) → paperFindGithubRepo → githubRepoInspect → runPythonAnalysis on k-mer viral detection scripts for metagenomic host prediction.

Automated Workflows

Deep Research workflow scans 50+ papers via searchPapers on 'phage host range coevolution', structures reports with GRADE-verified sections on therapy applications (Chan et al., 2016). DeepScan's 7-step chain analyzes Weinbauer (2003) ecology with CoVe checkpoints and Python stats on viral abundance. Theorizer generates hypotheses on CRISPR-phage arms races from Sorek et al. (2013) and Koskella and Brockhurst (2014).

Try Doxa for Bacteriophage Evolution and Host Range Research

Frequently Asked Questions

What defines bacteriophage host range evolution?

Host range evolution involves phages adapting via tail fiber mutations to infect new bacterial receptors, driven by coevolutionary arms races (Koskella and Brockhurst, 2014).

What experimental methods study phage evolution?

Serial passage experiments track host range expansion and resistance breakdown, often quantifying infection rates and sequencing receptor genes (Chan et al., 2016).

What are key papers on phage-bacteria coevolution?

Koskella and Brockhurst (2014, 872 citations) reviews ecological drivers; Weinbauer (2003, 1735 citations) establishes viral abundance foundations.

What open problems exist in phage host range research?

Predicting cross-family specificity shifts and integrating metagenomic uncultured viruses with lab evolution remain unsolved (Roux et al., 2018; Yooseph et al., 2007).