Evidence map›Paper›PMID 39963611›Full record

ArticleEntropy (Basel, Switzerland)2011

Towards an Evolutionary Model of Animal-Associated Microbiomes.

Carl J Yeoman, Nicholas Chia, Suleyman Yildirim, Margret E Berg Miller, Angela Kent, Rebecca Stumpf, Steven R Leigh, Karen E Nelson, Bryan A White, Brenda A Wilson

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 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. Article
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  10. The Gut Microbiota of the Egyptian Mongoose as an Early Warning Indicator of Ecosystem Health in Portugal.International journal of environmental research and public health · 2020
    Article
  11. Article
  12. 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

10 authors.

Carl J YeomanInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Nicholas ChiaInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Suleyman YildirimInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Margret E Berg MillerInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Angela KentDepartment of Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL 61801, USA.
Rebecca StumpfInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Steven R LeighInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Karen E NelsonJ. Craig Venter Institute, Rockville, MD 20850, USA.
Bryan A WhiteInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Brenda A WilsonInstitute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.

Funding

The Human Vaginal Microbiome and Bacterial VaginosisR56AI085096 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI WHITE, BRYAN · 2010 to 2010
$660k
NIAID NIH HHS R56 AI085096
6 · The paper itself

Abstract

Second-generation sequencing technologies have granted us greater access to the diversity and genetics of microbial communities that naturally reside endo- and ecto-symbiotically with animal hosts. Substantial research has emerged describing the diversity and broader trends that exist within and between host species and their associated microbial ecosystems, yet the application of these data to our evolutionary understanding of microbiomes appears fragmented. For the most part biological perspectives are based on limited observations of oversimplified communities, while mathematical and/or computational modeling of these concepts often lack biological precedence. In recognition of this disconnect, both fields have attempted to incorporate ecological theories, although their applicability is currently a subject of debate because most ecological theories were developed based on observations of macro-organisms and their ecosystems. For the purposes of this review, we attempt to transcend the biological, ecological and computational realms, drawing on extensive literature, to forge a useful framework that can, at a minimum be built upon, but ideally will shape the hypotheses of each field as they move forward. In evaluating the top-down selection pressures that are exerted on a microbiome we find cause to warrant reconsideration of the much-maligned theory of multi-level selection and reason that complexity must be underscored by modularity.

Indexed as

animalcomplexityecologyevolutioninterdependencymicrobiomemodularitymulti-level selection

Identifiers

PMID39963611
PMCPMC11831856

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.