Evidence map›Paper›PMID 22719037›Full record

ArticleProceedings. Biological sciences2012

Rapid antagonistic coevolution between strains of the social amoeba Dictyostelium discoideum.

Brian Hollis

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. WildEcology and evolution · 2020
    Article
  4. Genetic signatures of microbial altruism and cheating in social amoebas in the wild.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  5. Adaptation to public goods cheats inProceedings. Biological sciences · 2017
    Article
  6. 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

1 author.

Brian HollisDepartment of Ecology and Evolution, University of Lausanne, Biophore, 1015 Lausanne, Switzerland. brian.hollis@unil.ch

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social groups face a fundamental problem of overcoming selfish individuals capable of destroying cooperation. In the social amoeba Dictyostelium discoideum, there is evidence that some clones ('cheaters') contribute disproportionately to the viable spores in a fruiting body while avoiding the dead stalk cell fate. It remains unclear, however, whether this cheating is actually the product of selection. Here, I report the results of an experimental evolution study designed to test whether clones of D. discoideum will evolve resistance to cheating in the laboratory with genetic variation created only through spontaneous mutation. Two strains, one green fluorescent protein (GFP)-labelled and one wild-type, were allowed to grow and develop together before the wild-type strain was removed and replaced with a naïve strain evolving in parallel. Over the course of 10 social generations, the GFP-labelled strain reliably increased its representation in the spores relative to control populations that had never experienced the competitor. This competitive advantage extended to the non-social, vegetative growth portion of the life cycle, but not to pairwise competition with two other strains. These results indicate strong antagonism between strains, mediated by ample mutational variation for cheating and also suggest that arms races between strains in the wild may be common.

Indexed as

Biological EvolutionGenetic FitnessGenetic VariationDictyosteliumGreen Fluorescent ProteinsLinear ModelsMutationSpores, ProtozoanGreen Fluorescent Proteins

Identifiers

PMID22719037
PMCPMC3396919

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.