Evidence map›Paper›PMID 23204462›Full record

ArticleJournal of bacteriology2013

Isolation of highly persistent mutants of Salmonella enterica serovar typhimurium reveals a new toxin-antitoxin module.

Andrew Slattery, Alec H Victorsen, April Brown, Kai Hillman, Gregory J Phillips

Abstract read
In one paragraph

Article in Journal of bacteriology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
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  7. Article
  8. Immune response modulation bybioRxiv : the preprint server for biology · 2023
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Microbiology and molecular biology reviews : MMBR · 2020
    Review
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  18. Article
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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

5 authors.

Andrew SlatteryDepartment of Veterinary Microbiology, Iowa State University, Ames, IA, USA.
Alec H Victorsen
April Brown
Kai Hillman
Gregory J Phillips

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial persistence is characterized by the ability of a subpopulation within bacterial cultures to survive exposure to antibiotics and other lethal treatments. The surviving persisters are not the result of genetic changes but represent epigenetic variants that are in a physiological state where growth is inhibited. Since characterization of persisters has been performed mainly in Escherichia coli K-12, we sought to identify mechanisms of persistence in the pathogen Salmonella enterica serovar Typhimurium. Isolation of new highly persistent mutants revealed that the shpAB locus (Salmonella high persistence) imparted a 3- to 4-order-of-magnitude increase in survival after ampicillin exposure throughout its growth phase and protected the population against exposure to multiple antibiotics. Genetic characterization revealed that shpAB is a newly discovered toxin-antitoxin (TA) module. The high-persistence phenotype was attributed to a nonsense mutation in the 3' end of the shpB gene encoding an antitoxin protein. Characteristic of other TA modules, shpAB is autoregulated, and high persistence depends on the Lon protease.

Indexed as

Amino Acid SequenceAmpicillinAnti-Bacterial AgentsAntitoxinsBacterial ProteinsBacterial ToxinsChromosome MappingDrug Resistance, BacterialGene Expression Regulation, BacterialGenetic EngineeringGenome, BacterialMicrobial Sensitivity TestsMolecular Sequence DataMutationPlasmidsSalmonella typhimuriumAmpicillinAnti-Bacterial AgentsAntitoxinsBacterial ProteinsBacterial Toxins

Identifiers

PMID23204462
PMCPMC3562109

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.