{
  "abstract": "The rise of antibiotic-resistant bacterial infections has driven renewed interest in bacteriophage therapy, where viruses that specifically kill bacteria are used as targeted antimicrobials. Pseudomonas aeruginosa , a WHO critical-priority pathogen that causes severe infections in hospitalized and immunocompromised patients, presents a major challenge for phage therapy because of its extraordinary genetic diversity. Phages effective against one bacterial strain often fail against others, and existing cross-resistance-profiling approaches require iterative empirical testing of each new patient isolate. To establish a genome-based framework for rapid phage-isolate matching, we assembled a collection of 95 genomically diverse P. aeruginosa phages representing 20 genera and tested each against 99 genetically diverse clinical isolates, generating 9,405 infection outcome measurements. Bacterial O-antigen serotype emerged as the dominant determinant of strain susceptibility, while defense systems, anti-defense systems, and prophage burden contributed smaller strain-specific effects. The full curated multivariate model explained 47% of strain-susceptibility variance. Machine-learning models integrating these features and pangenome-derived gene clusters reached a per-strain AUROC of 0.86. In an in vivo proof-of-concept test against a single held-out strain, the ML-designed cocktail produced a ∼12-fold greater median CFU reduction than the expert-designed cocktail (q = 0.045), with both cocktails substantially reducing burden relative to the untreated control (∼113-fold for ML, ∼9-fold for CG; both q < 10□³). SHAP analysis of the model identified bacterial surface-architecture genes (LPS biosynthesis, outer membrane proteins, type IV pili) as the dominant predictors, with defense-system content modulating which specific phages succeed against a strain rather than uniformly damping susceptibility. Together, these results establish a genome-based framework for predicting phage susceptibility in genetically diverse clinical isolates.",
  "abstract_shown": true,
  "affiliations": [
    "Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA",
    "Molecular and Cell Biology Department, University of California Berkeley, Berkeley, CA, USA",
    "Plant and Microbial Biology Department, University of California Berkeley, Berkeley, CA, USA",
    "Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA",
    "Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA, USA",
    "DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 20,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Denish Piya",
      "orcid": "0000-0001-8495-4511"
    },
    {
      "affs": [
        0
      ],
      "name": "Avery J. C. Noonan",
      "orcid": "0000-0002-9039-8379"
    },
    {
      "affs": [
        0
      ],
      "name": "Hemaa Selvakumar",
      "orcid": "0009-0008-8329-3385"
    },
    {
      "affs": [
        0
      ],
      "name": "Mohamad Alayouni"
    },
    {
      "affs": [
        0
      ],
      "name": "Sarshad Koderi Valappil",
      "orcid": "0000-0002-1627-1572"
    },
    {
      "affs": [
        0
      ],
      "name": "Flavien Maucourt",
      "orcid": "0000-0002-8030-5394"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Isabella Murray",
      "orcid": "0000-0001-7478-247X"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Madeline Svab",
      "orcid": "0009-0008-7596-8346"
    },
    {
      "affs": [
        3,
        0
      ],
      "name": "Collis Bousliman",
      "orcid": "0009-0006-6334-9834"
    },
    {
      "affs": [
        0
      ],
      "name": "Matthew Heidenblut",
      "orcid": "0009-0003-8880-1282"
    },
    {
      "affs": [
        0
      ],
      "name": "Britney Orihuela"
    },
    {
      "affs": [
        0
      ],
      "name": "Alexey Kazakov"
    },
    {
      "affs": [
        0
      ],
      "name": "Hans K. Carlson",
      "orcid": "0000-0002-1583-5313"
    },
    {
      "affs": [
        4
      ],
      "name": "Yiyan Yao",
      "orcid": "0009-0000-4163-9079"
    },
    {
      "affs": [
        4
      ],
      "name": "Emerson Smith"
    },
    {
      "affs": [
        5
      ],
      "name": "Simon Roux",
      "orcid": "0000-0002-5831-5895"
    },
    {
      "affs": [
        0
      ],
      "name": "Adam M. Deutschbauer",
      "orcid": "0000-0003-2728-7622"
    },
    {
      "affs": [
        4
      ],
      "name": "Jamie L. Inman",
      "orcid": "0000-0002-6056-1219"
    },
    {
      "affs": [
        3,
        0
      ],
      "name": "Adam P. Arkin",
      "orcid": "0000-0002-4999-2931"
    },
    {
      "affs": [
        4,
        0
      ],
      "name": "Vivek K. Mutalik",
      "orcid": "0000-0001-7934-0400"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0e5m6qn3ar3nx.bib",
  "cited_by": 5,
  "doi": "10.64898/2026.05.19.726084",
  "fulltext_url": null,
  "id": "0e5m6qn3ar3nx",
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  "landing_url": "https://doi.org/10.64898/2026.05.19.726084",
  "language": "en",
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2406|Bacteriophages and microbial interactions"
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  "pdf_url": "https://www.biorxiv.org/content/biorxiv/early/2026/05/20/2026.05.19.726084.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-05-20",
  "publisher": "Cold Spring Harbor Laboratory",
  "ris": "https://research.draconitic.com/paper/0e5m6qn3ar3nx.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T13:20:53Z",
      "native_id": "W7161816662",
      "source": "openalex",
      "url": "https://doi.org/10.64898/2026.05.19.726084"
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  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2406|Bacteriophages and microbial interactions",
      "subfield": "microbiology"
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  ],
  "title": "Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa",
  "title_text": "Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa",
  "type": "preprint",
  "updated_at": "2026-11-09T13:21:11Z",
  "url": "https://research.draconitic.com/paper/0e5m6qn3ar3nx",
  "venue": "bioRxiv (Cold Spring Harbor Laboratory)",
  "versions": []
}