Evidence map›Paper›PMID 40839215›Full record

ArticleBioinformatics (Oxford, England)2025

PDP-Miner: an AI/ML tool to detect prophage tail proteins with depolymerase domains across thousands of bacterial genomes.

Jeff Gauthier, Irena Kukavica-Ibrulj, Roger C Levesque

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jeff GauthierInstitut de Biologie Intégrative et des Systèmes, Université Laval, Québec, QC, G1V 0A6, Canada.ORCID 0000-0002-2523-2698
Irena Kukavica-IbruljInstitut de Biologie Intégrative et des Systèmes, Université Laval, Québec, QC, G1V 0A6, Canada.
Roger C LevesqueInstitut de Biologie Intégrative et des Systèmes, Université Laval, Québec, QC, G1V 0A6, Canada.

Funding

Canadian Institutes of Health Research, Genome Canada, Genome Québec, and Ontario Genomics
6 · The paper itself

Abstract

motivationAntibiotic resistance is predicted to become the leading cause of human mortality by 2050. Despite this, no other major antibiotic class has been approved for medical use since 1987. Nevertheless, phage tail proteins offer a promising alternative, given their depolymerase activity toward outer membrane polysaccharides. Several pathogenic bacteria harbor prophages, thus making these prophages' molecular target already known.

resultsWe therefore developed a wrapper for an existing machine learning-based phage depolymerase prediction tool (Depolymerase-Predictor), called PDP-Miner, which annotates phage tail proteins ab initio, detects depolymerase activity within this candidate protein subset, and then performs post-hoc validation by annotating protein domains thereby allowing the user to investigate for protein domains indicative of depolymerase activity. This tool allowed identification of 10 high confidence phage depolymerase gene candidates across all 1294 Pseudomonas genomes available on the International Pseudomonas Consortium Database while also accurately reporting depolymerases in known phage genomes, similarly to other software like PhageDPO or DepoScope. AVAILABILITY AND IMPLEMENTATION: Source code, test datasets and documentation are freely available for download at http:///www.github.com/jeffgauthier/pdpminer. This software is free and open source under the GNU General Public License v3.0.

Indexed as

Genome, BacterialProphagesSoftwareViral Tail ProteinsMachine LearningProtein DomainsPseudomonasViral Tail Proteins

Identifiers

PMID40839215
PMCPMC12579547

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.