Evidence map›Paper›PMID 26747663›Full record

ReviewCold Spring Harbor perspectives in biology2016

Thoughts Toward a Theory of Natural Selection: The Importance of Microbial Experimental Evolution.

Daniel Dykhuizen

Abstract readReview
In one paragraph

Review in Cold Spring Harbor perspectives in biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Development of heat-shock resistance inApplied and environmental microbiology · 2023
    Article
  3. Article
  4. Experimental evolution and proximate mechanisms in biology.Synthetic and systems biotechnology · 2017
    Review
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.

Daniel DykhuizenDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural selection should no longer be thought of simply as a primitive (magical) concept that can be used to support all kinds of evolutionary theorizing. We need to develop causal theories of natural selection; how it arises. Because the factors contributing to the creation of natural selection are expected to be complex and intertwined, theories explaining the causes of natural selection can only be developed through the experimental method. Microbial experimental evolution provides many benefits that using other organisms does not. Microorganisms are small, so millions can be housed in a test tube; they have short generation times, so evolution over hundreds of generations can be easily studied; they can grow in chemically defined media, so the environment can be precisely defined; and they can be frozen, so the fitness of strains or populations can be directly compared across time. Microbial evolution experiments can be divided into two types. The first is to measure the selection coefficient of two known strains over the first 50 or so generations, before advantageous mutations rise to high frequency. This type of experiment can be used to directly test hypotheses. The second is to allow microbial cultures to evolve over many hundreds or thousands of generations and follow the genetic changes, to infer what phenotypes are selected. In the last section of this article, I propose that selection coefficients are not constant, but change as the population becomes fitter, introducing the idea of the selection space.

Indexed as

Directed Molecular EvolutionSelection, GeneticBacteriaLac OperonMetabolic Networks and PathwaysModels, Genetic

Identifiers

PMID26747663
PMCPMC4772105

What OpenQuestion holds

Textmetadata
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.