Evidence map›Paper›PMID 38988700›Full record

ArticleISME communications2024

Evolutionary and co-evolutionary phage training approaches enhance bacterial suppression and delay the emergence of phage resistance.

Lyman Ngiam, Karen Weynberg, Jianhua Guo

Abstract read
In one paragraph

Article in ISME communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Phage and endolysin-based inhibition ofFrontiers in cellular and infection microbiology · 2026
    Review
  5. Whole-Genome Sequencing and Functional Characterization of a NovelInternational journal of molecular sciences · 2025
    Article
  6. Article
  7. [Regulation of phage therapy medicinal products: developments, challenges and opportunities].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025
    Review
  8. Article
  9. Review
  10. Phage therapy to treat cystic fibrosisFrontiers in microbiology · 2024
    Review
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.

Lyman NgiamAustralian Centre for Water and Environmental Biotechnology, The University of Queensland, 4 Gehrmann Laboratories Building, Research Road, St Lucia, Queensland 4072, Australia.
Karen WeynbergAustralian Centre for Ecogenomics, The University of Queensland, Chemistry Building 68, Cooper Road, St Lucia, Queensland 4072, Australia.
Jianhua GuoAustralian Centre for Water and Environmental Biotechnology, The University of Queensland, 4 Gehrmann Laboratories Building, Research Road, St Lucia, Queensland 4072, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of phage resistance by bacteria is a major barrier that impedes the therapeutic use of phages. Phage training has been proposed as a novel tool that harnesses the evolutionary potential of phages to improve phage infectivity. Both evolutionary and co-evolutionary phage training models have been previously reported to train phages. However, both of these phage training models have been reported able to effectively suppress the emergence of phage-resistant bacteria mutants, thus presenting a contradictory phenomenon. Therefore, in this study, we set out to systematically compare the effectiveness of both evolutionary and co-evolutionary phage training models with regard to phage physiology, infectivity, and genotype. To this end, a natural lytic phage capable of infecting a

Indexed as

bacteriophagebacteriophage-resistant bacteria mutantco-evolutionaryevolutionevolutionaryphage trainingvirus host interaction

Identifiers

PMID38988700
PMCPMC11234896

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.