Evidence map›Paper›PMID 33541358›Full record

ArticleBMC biology2021

Evolutionary dynamics and structural consequences of de novo beneficial mutations and mutant lineages arising in a constant environment.

Margie Kinnersley, Katja Schwartz, Dong-Dong Yang, Gavin Sherlock, Frank Rosenzweig

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Margie Kinnersley *Division of Biological Sciences, The University of Montana, Missoula, MT, 59812, USA.
Katja Schwartz *Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305-5120, USA.
Dong-Dong YangSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Gavin SherlockDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, 94305-5120, USA. gsherloc@stanford.edu.
Frank RosenzweigDivision of Biological Sciences, The University of Montana, Missoula, MT, 59812, USA. frank.rosenzweig@biology.gatech.edu.ORCID 0000-0003-0448-3188
Georgia Institute of Technology · USStanford University · USUniversity of Montana · US

Funding

Multisizer 4e - equipment for "Fitness Effects of Beneficial Mutations"R35GM131824 · NIGMS · STANFORD UNIVERSITY · PI Gavin J Sherlock · 2019 to 2026
$3.6M
NASA 80NSSC20K0621NASA NNA17BB05ANASA NNX12AD87GNIGMS NIH HHS R35 GM131824
6 · The paper itself

Abstract

backgroundMicrobial evolution experiments can be used to study the tempo and dynamics of evolutionary change in asexual populations, founded from single clones and growing into large populations with multiple clonal lineages. High-throughput sequencing can be used to catalog de novo mutations as potential targets of selection, determine in which lineages they arise, and track the fates of those lineages. Here, we describe a long-term experimental evolution study to identify targets of selection and to determine when, where, and how often those targets are hit.

resultsWe experimentally evolved replicate Escherichia coli populations that originated from a mutator/nonsense suppressor ancestor under glucose limitation for between 300 and 500 generations. Whole-genome, whole-population sequencing enabled us to catalog 3346 de novo mutations that reached > 1% frequency. We sequenced the genomes of 96 clones from each population when allelic diversity was greatest in order to establish whether mutations were in the same or different lineages and to depict lineage dynamics. Operon-specific mutations that enhance glucose uptake were the first to rise to high frequency, followed by global regulatory mutations. Mutations related to energy conservation, membrane biogenesis, and mitigating the impact of nonsense mutations, both ancestral and derived, arose later. New alleles were confined to relatively few loci, with many instances of identical mutations arising independently in multiple lineages, among and within replicate populations. However, most never exceeded 10% in frequency and were at a lower frequency at the end of the experiment than at their maxima, indicating clonal interference. Many alleles mapped to key structures within the proteins that they mutated, providing insight into their functional consequences.

conclusionsOverall, we find that when mutational input is increased by an ancestral defect in DNA repair, the spectrum of high-frequency beneficial mutations in a simple, constant resource-limited environment is narrow, resulting in extreme parallelism where many adaptive mutations arise but few ever go to fixation.

Indexed as

Evolution, MolecularMutationSelection, GeneticEscherichia coliEscherichia coli ProteinsGlucoseHigh-Throughput Nucleotide SequencingEscherichia coli ProteinsGlucoseAdaptationClonal interferenceE. coliExperimental evolutionParallelismResource limitation

Identifiers

PMID33541358
PMCPMC7863352
OpenAlexW3128982038

What OpenQuestion holds

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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.