Evidence map›Paper›PMID 21876679›Full record

ArticlePLoS genetics2011

Frequent beneficial mutations during single-colony serial transfer of Streptococcus pneumoniae.

Kathleen E Stevens, Michael E Sebert

Abstract read
In one paragraph

Article in PLoS genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Estimating geographical spread ofMicrobial genomics · 2024
    Article
  2. Horizontal Gene Transfer and Drug Resistance InvolvingAntibiotics (Basel, Switzerland) · 2023
    Article
  3. Experimental EvolutionmSystems · 2020
    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

2 authors.

Kathleen E StevensChildren's Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania, USA.
Michael E Sebert

Funding

Streptococcus pneumoniae genetic competence and pathogenesisR01AI075194 · NIAID · CHILDREN'S HOSP OF PHILADELPHIA · PI SEBERT, MICHAEL E · 2008 to 2011
$1.6M
NIAID NIH HHS AI075194NIAID NIH HHS R01 AI075194
6 · The paper itself

Abstract

The appearance of new mutations within a population provides the raw material for evolution. The consistent decline in fitness observed in classical mutation accumulation studies has provided support for the long-held view that deleterious mutations are more common than beneficial mutations. Here we present results of a study using a mutation accumulation design with the bacterium Streptococcus pneumoniae in which the fitness of the derived populations increased. This rise in fitness was associated specifically with adaptation to survival during brief stationary phase periods between single-colony population bottlenecks. To understand better the population dynamics behind this unanticipated adaptation, we developed a maximum likelihood model describing the processes of mutation and stationary-phase selection in the context of frequent population bottlenecks. Using this model, we estimate that the rate of beneficial mutations may be as high as 4.8×10(-4) events per genome for each time interval corresponding to the pneumococcal generation time. This rate is several orders of magnitude higher than earlier estimates of beneficial mutation rates in bacteria but supports recent results obtained through the propagation of small populations of Escherichia coli. Our findings indicate that beneficial mutations may be relatively frequent in bacteria and suggest that in S. pneumoniae, which develops natural competence for transformation, a steady supply of such mutations may be available for sampling by recombination.

Indexed as

MutationAdaptation, PhysiologicalEscherichia coliGene FrequencyLikelihood FunctionsSelection, GeneticStreptococcus pneumoniae

Identifiers

PMID21876679
PMCPMC3158050

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.