Evidence map›Paper›PMID 30214695›Full record

ArticleComputational and structural biotechnology journal2018

Intermediate Levels of Antibiotics May Increase Diversity of Colony Size Phenotype in Bacteria.

Lewis Lee, Van M Savage, Pamela J Yeh

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

3 authors.

Lewis LeeDepartment of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, USA.
Van M SavageDepartment of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, USA.
Pamela J YehDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, USA.

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
NCATS NIH HHS UL1 TR001881
6 · The paper itself

Abstract

Antibiotics select for resistant bacteria whose existence and emergence is more likely in populations with high phenotypic and genetic diversity. Identifying the mechanisms that generate this diversity can thus have clinical consequences for drug-resistant pathogens. We show here that intermediate levels of antibiotics are associated with higher levels of phenotypic diversity in size of colony forming units (cfus), within a single bacterial population. We examine experimentally thousands of populations of bacteria subjected to different disturbance levels that are created by varying antibiotic concentrations. Based on colony sizes, we find that intermediate levels of antibiotics always result in the highest phenotypic variation of this trait. This result is supported across bacterial densities and in the presence of three different antibiotics with two different mechanisms of action. Our results suggest intermediate levels of a stressor (as opposed to very low or very high levels) could affect the phenotypic diversity of a population, at least with regards to the single trait measured here. While this study is limited to a single phenotypic trait within a single species, the results suggest examining phenotypic and genetic variation created by disturbances and stressors could be a promising way to understand and limit variation in pathogens.

Indexed as

DisturbanceDrug concentrationGeneticPhenotypicSelectionSub-lethalVariation

Identifiers

PMID30214695
PMCPMC6134325

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.