Evidence map›Paper›PMID 24968217›Full record

ArticlePLoS genetics2014

Ex uno plures: clonal reinforcement drives evolution of a simple microbial community.

Margie Kinnersley, Jared Wenger, Evgueny Kroll, Julian Adams, Gavin Sherlock, Frank Rosenzweig

Abstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Frequency-dependent fitness effects are ubiquitous.bioRxiv : the preprint server for biology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. Fitness and Productivity Increase with Ecotypic Diversity amongApplied and environmental microbiology · 2020
    Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  18. Article
  19. Article
  20. 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

6 authors.

Margie KinnersleyDivision of Biological Sciences, The University of Montana, Missoula, Montana, United States of America.
Jared WengerDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Evgueny KrollDivision of Biological Sciences, The University of Montana, Missoula, Montana, United States of America.
Julian AdamsDepartments of Molecular, Cellular and Developmental Biology and Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.
Gavin SherlockDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Frank RosenzweigDivision of Biological Sciences, The University of Montana, Missoula, Montana, United States of America.

Funding

GENETICS TRAINING PROGRAM FOR PHD CANDIDATEST32GM007790 · NIGMS · STANFORD UNIVERSITY · PI BRUNET, ANNE, KINGSLEY, DAVID M · 1985 to 2020
$12.8M
Molecular Characterization of Adaptive EvolutionR01HG003328 · NHGRI · STANFORD UNIVERSITY · PI SHERLOCK, GAVIN J · 2005 to 2015
$4.1M
NHGRI NIH HHS R01 HG003328NIGMS NIH HHS GM007790NIGMS NIH HHS T32 GM007790
6 · The paper itself

Abstract

A major goal of genetics is to define the relationship between phenotype and genotype, while a major goal of ecology is to identify the rules that govern community assembly. Achieving these goals by analyzing natural systems can be difficult, as selective pressures create dynamic fitness landscapes that vary in both space and time. Laboratory experimental evolution offers the benefit of controlling variables that shape fitness landscapes, helping to achieve both goals. We previously showed that a clonal population of E. coli experimentally evolved under continuous glucose limitation gives rise to a genetically diverse community consisting of one clone, CV103, that best scavenges but incompletely utilizes the limiting resource, and others, CV101 and CV116, that consume its overflow metabolites. Because this community can be disassembled and reassembled, and involves cooperative interactions that are stable over time, its genetic diversity is sustained by clonal reinforcement rather than by clonal interference. To understand the genetic factors that produce this outcome, and to illuminate the community's underlying physiology, we sequenced the genomes of ancestral and evolved clones. We identified ancestral mutations in intermediary metabolism that may have predisposed the evolution of metabolic interdependence. Phylogenetic reconstruction indicates that the lineages that gave rise to this community diverged early, as CV103 shares only one Single Nucleotide Polymorphism with the other evolved clones. Underlying CV103's phenotype we identified a set of mutations that likely enhance glucose scavenging and maintain redox balance, but may do so at the expense of carbon excreted in overflow metabolites. Because these overflow metabolites serve as growth substrates that are differentially accessible to the other community members, and because the scavenging lineage shares only one SNP with these other clones, we conclude that this lineage likely served as an "engine" generating diversity by creating new metabolic niches, but not the occupants themselves.

Indexed as

Directed Molecular EvolutionSelection, GeneticAmino Acid SubstitutionCodon, NonsenseEscherichia coliGenetic VariationGenome, BacterialGlucoseGlycerolPhylogenyPolymorphism, Single NucleotideCodon, NonsenseGlucoseGlycerol

Identifiers

PMID24968217
PMCPMC4072538

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LicenceCC BY
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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.