Evidence map›Paper›PMID 28928474›Full record

ArticleThe Journal of antibiotics2018

Using experimental evolution to identify druggable targets that could inhibit the evolution of antimicrobial resistance.

Heer H Mehta, Amy G Prater, Yousif Shamoo

Abstract read
In one paragraph

Article in The Journal of antibiotics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Intracellular Experimental Evolution ofACS infectious diseases · 2023
    Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Crossroads of Antibiotic Resistance and Biosynthesis.Journal of molecular biology · 2019
    Review
  17. Article
  18. 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.

Heer H MehtaDepartment of BioSciences at Rice, Rice University, Houston, TX, USA.
Amy G PraterDepartment of BioSciences at Rice, Rice University, Houston, TX, USA.
Yousif ShamooDepartment of BioSciences at Rice, Rice University, Houston, TX, USA.

Funding

Defining Evolutionary Trajectories: Molecular adaptation to antibiotic resistanceR01AI080714 · NIAID · RICE UNIVERSITY · PI SHAMOO, YOUSIF · 2009 to 2023
$4.3M
NIAID NIH HHS R01 AI080714
6 · The paper itself

Abstract

With multi-drug and pan-drug-resistant bacteria becoming increasingly common in hospitals, antibiotic resistance has threatened to return us to a pre-antibiotic era that would completely undermine modern medicine. There is an urgent need to develop new antibiotics and strategies to combat resistance that are substantially different from earlier drug discovery efforts. One such strategy that would complement current and future antibiotics would be a class of co-drugs that target the evolution of resistance and thereby extend the efficacy of specific classes of antibiotics. A critical step in the development of such strategies lies in understanding the critical evolutionary trajectories responsible for resistance and which proteins or biochemical pathways within those trajectories would be good candidates for co-drug discovery. We identify the most important steps in the evolution of resistance for a specific pathogen and antibiotic combination by evolving highly polymorphic populations of pathogens to resistance in a novel bioreactor that favors biofilm development. As the populations evolve to increasing drug concentrations, we use deep sequencing to elucidate the network of genetic changes responsible for resistance and subsequent in vitro biochemistry and often structure determination to determine how the adaptive mutations produce resistance. Importantly, the identification of the molecular steps, their frequency within the populations and their chronology within the evolutionary trajectory toward resistance is critical to assessing their relative importance. In this work, we discuss findings from the evolution of the ESKAPE pathogen, Pseudomonas aeruginosa to the drug of last resort, colistin to illustrate the power of this approach.

Indexed as

Evolution, MolecularAllelesAnti-Bacterial AgentsBacteriaBiofilmsBioreactorsColistinDNA, BacterialDrug DiscoveryDrug Resistance, BacterialDrug Resistance, Multiple, BacterialGenome, BacterialMetagenomicsMicrobial Sensitivity TestsMutationPseudomonas aeruginosaAnti-Bacterial AgentsColistinDNA, Bacterial

Identifiers

PMID28928474
PMCPMC5788704

What OpenQuestion holds

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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.