Evidence map›Paper›PMID 31015333›Full record

ArticlemBio2019

Lighting Up Mutation: a New Unbiased System for the Measurement of Microbial Mutation Rates.

Kylie J Boyce, Alexander Idnurm

Open access · goldAbstract readComment
In one paragraph

Article in mBio, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 41% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Kylie J BoyceSchool of Science, RMIT University, Melbourne, Victoria, Australia kylie.boyce@rmit.edu.au alexander.idnurm@unimelb.edu.au.
Alexander IdnurmSchool of BioSciences, University of Melbourne, Parkville, Victoria, Australia kylie.boyce@rmit.edu.au alexander.idnurm@unimelb.edu.au.
RMIT University · AUUniversity of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although mutation drives evolution over long and short terms, measuring and comparing mutation rates accurately have been particularly difficult. This is especially true when mutations lead to an alteration in fitness. E. Shor, J. Schuyler, and D. S. Perlin (https://doi.org/10.1128/mBio.00120-19) present a new method to compare mutation rates across fungal strains and under different growth conditions: they employ the green fluorescent protein (GFP) as the reporter and count mutations using fluorescence-activated cell sorting (FACS). The estimates of mutation rates using the GFP-FACS approach are similar to those calculated with other reporters, and the method was used to assess if different alleles of the mismatch repair pathway gene

Indexed as

Candida glabrataMutation RateDrug Resistance, FungalFluorescenceHumansMutationantifungal drug resistanceCRISPR-Cas9FACSfluctuation testGFPmismatch repairMSH2

Identifiers

PMID31015333
PMCPMC6479009
OpenAlexW2941548760

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.