Evidence map›Paper›PMID 41325432›Full record

ArticlePLoS pathogens2025

Quantifying plasmid movement in drug-resistant Shigella species using phylodynamic inference.

Nicola F Müller, Ryan R Wick, Louise M Judd, Deborah A Williamson, Trevor Bedford, Benjamin P Howden, Sebastián Duchêne, Danielle J Ingle

Abstract read
In one paragraph

Article in PLoS pathogens, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Nicola F MüllerDivision of HIV, ID and Global Medicine, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-2927-1002
Ryan R WickDepartment of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Louise M JuddCenter for Pathogen Genomics, The University of Melbourne, Melbourne, Victoria, Australia.
Deborah A WilliamsonDepartment of Infectious Diseases at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Trevor BedfordVaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington State, United States of America.
Benjamin P HowdenDepartment of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Sebastián DuchêneDepartment of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.
Danielle J IngleDepartment of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia.

Funding

Real-time tracking of virus evolution for vaccine strain selection and epidemiological investigationR35GM119774 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BEDFORD, TREVOR BC · 2016 to 2025
$4.1M
NIGMS NIH HHS R35 GM119774
6 · The paper itself

Abstract

The 'silent pandemic' of antimicrobial resistance (AMR) represents a significant global public health threat. AMR genes in bacteria are often carried on mobile elements, such as plasmids. The horizontal movement of plasmids allows AMR genes and resistance to key therapeutics to disseminate in a population. However, the quantification of the movement of plasmids remains challenging with existing computational approaches. Here, we introduce a novel method that allows us to reconstruct and quantify the movement of plasmids in bacterial populations over time. To do so, we model chromosomal and plasmid DNA co-evolution using a joint coalescent and plasmid transfer process in a Bayesian phylogenetic network approach. This approach reconstructs differences in the evolutionary history of plasmids and chromosomes to reconstruct instances where plasmids likely move between bacterial lineages while accounting for parameter uncertainty. We apply this new approach to a five-year dataset of Shigella, exploring the plasmid transfer rates of five different plasmids with different AMR and virulence profiles. In doing so, we reconstruct the co-evolution of the large Shigella virulence plasmid with the chromosome DNA. We quantify higher plasmid transfer rates of three small plasmids that move between lineages of Shigella sonnei. Finally, we determine the recent dissemination of a multidrug-resistant plasmid between S. sonnei and S. flexneri lineages in multiple independent events and through steady growth in prevalence since 2010. This approach has a strong potential to improve our understanding of the evolutionary dynamics of AMR-carrying plasmids as they are introduced, circulate, and are maintained in bacterial populations.

Indexed as

Drug Resistance, BacterialPlasmidsShigellaAnti-Bacterial AgentsBayes TheoremDysentery, BacillaryEvolution, MolecularGene Transfer, HorizontalHumansPhylogenyAnti-Bacterial Agents

Identifiers

PMID41325432
PMCPMC12677775

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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.