Evidence map›Paper›PMID 25701634›Full record

ArticleJournal of theoretical biology2015

Bacterial fitness shapes the population dynamics of antibiotic-resistant and -susceptible bacteria in a model of combined antibiotic and anti-virulence treatment.

Lucy Ternent, Rosemary J Dyson, Anne-Marie Krachler, Sara Jabbari

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. AACS synthetic biology · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. An ecosystem framework for understanding and treating disease.Evolution, medicine, and public health · 2018
    Review
  13. Small Molecules That Sabotage Bacterial Virulence.Trends in pharmacological sciences · 2017
    Review
  14. Review
  15. Review
  16. Article
  17. 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

4 authors.

Lucy TernentSchool of Mathematics, University of Birmingham, United Kingdom.
Rosemary J DysonSchool of Mathematics, University of Birmingham, United Kingdom.
Anne-Marie KrachlerInstitute of Microbiology and Infection, University of Birmingham, United Kingdom.
Sara JabbariSchool of Mathematics, University of Birmingham, United Kingdom; Institute of Microbiology and Infection, University of Birmingham, United Kingdom. Electronic address: s.jabbari@bham.ac.uk.

Funding

Biotechnology and Biological Sciences Research CouncilMedical Research Council G1002093
6 · The paper itself

Abstract

Bacterial resistance to antibiotic treatment is a huge concern: introduction of any new antibiotic is shortly followed by the emergence of resistant bacterial isolates in the clinic. This issue is compounded by a severe lack of new antibiotics reaching the market. The significant rise in clinical resistance to antibiotics is especially problematic in nosocomial infections, where already vulnerable patients may fail to respond to treatment, causing even greater health concern. A recent focus has been on the development of anti-virulence drugs as a second line of defence in the treatment of antibiotic-resistant infections. This treatment, which weakens bacteria by reducing their virulence rather than killing them, should allow infections to be cleared through the body׳s natural defence mechanisms. In this way there should be little to no selective pressure exerted on the organism and, as such, a predominantly resistant population should be less likely to emerge. However, before the likelihood of resistance to these novel drugs emerging can be predicted, we must first establish whether such drugs can actually be effective. Many believe that anti-virulence drugs would not be powerful enough to clear existing infections, restricting their potential application to prophylaxis. We have developed a mathematical model that provides a theoretical framework to reveal the circumstances under which anti-virulence drugs may or may not be successful. We demonstrate that by harnessing and combining the advantages of antibiotics with those provided by anti-virulence drugs, given infection-specific parameters, it is possible to identify treatment strategies that would efficiently clear bacterial infections, while preventing the emergence of antibiotic-resistant subpopulations. Our findings strongly support the continuation of research into anti-virulence drugs and demonstrate that their applicability may reach beyond infection prevention.

Indexed as

Drug Resistance, BacterialAnti-Bacterial AgentsBacteriaBacterial InfectionsCross InfectionHumansModels, BiologicalPopulation DynamicsVirulenceAnti-Bacterial AgentsAntibiotic resistanceAnti-virulence drugsMathematical Modelling

Identifiers

PMID25701634
PMCPMC4396697

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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 OpenQuestion graph.