Evidence map›Paper›PMID 34001313›Full record

ArticleeLife2021

Multi-step vs. single-step resistance evolution under different drugs, pharmacokinetics, and treatment regimens.

Claudia Igler, Jens Rolff, Roland Regoes

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing 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

39 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Dual Mutations inInternational journal of molecular sciences · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Resistance profiles ofIranian journal of microbiology · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Multiplicity of type 6 secretion system toxins limits the evolution of resistance.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Unveiling the Multifaceted Capabilities of EndophyticPharmaceuticals (Basel, Switzerland) · 2024
    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.

Claudia IglerInstitute of Integrative Biology, ETH Zurich, Zurich, Switzerland.ORCID 0000-0001-7777-546X
Jens RolffEvolutionary Biology, Institute for Biology, Freie Universität Berlin, Berlin, Germany.ORCID 0000-0002-1529-5409
Roland RegoesInstitute of Integrative Biology, ETH Zurich, Zurich, Switzerland.ORCID 0000-0001-8319-5293

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The success of antimicrobial treatment is threatened by the evolution of drug resistance. Population genetic models are an important tool in mitigating that threat. However, most such models consider resistance emergence via a single mutational step. Here, we assembled experimental evidence that drug resistance evolution follows two patterns: (i) a single mutation, which provides a large resistance benefit, or (ii) multiple mutations, each conferring a small benefit, which combine to yield high-level resistance. Using stochastic modeling, we then investigated the consequences of these two patterns for treatment failure and population diversity under various treatments. We find that resistance evolution is substantially limited if more than two mutations are required and that the extent of this limitation depends on the combination of drug type and pharmacokinetic profile. Further, if multiple mutations are necessary, adaptive treatment, which only suppresses the bacterial population, delays treatment failure due to resistance for a longer time than aggressive treatment, which aims at eradication.

Indexed as

MutationAnti-Bacterial AgentsBacteriaBacterial InfectionsBiological EvolutionDrug Resistance, BacterialModels, TheoreticalAnti-Bacterial Agentsantibiotic resistance evolutionevolutionary biologymultiple mutationsnonepharmacodynamic model

Identifiers

PMID34001313
PMCPMC8184216

What OpenQuestion holds

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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.