Evidence map›Paper›PMID 36910202›Full record

ReviewFrontiers in microbiology2023

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations.

Leigh Combrink, Ian R Humphreys, Quinn Washburn, Holly K Arnold, Keaton Stagaman, Kristin D Kasschau, Anna E Jolles, Brianna R Beechler, Thomas J Sharpton

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  16. Comparative assessment of Texas horned lizard (Frontiers in microbiomes · 2025
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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

9 authors.

Leigh CombrinkDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Ian R HumphreysDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Quinn WashburnDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Holly K ArnoldDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Keaton StagamanDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Kristin D KasschauDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.
Anna E JollesDepartment of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR, United States.
Brianna R BeechlerDepartment of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR, United States.
Thomas J SharptonDepartment of Microbiology, Oregon State University, Corvallis, OR, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.

Indexed as

16S rRNA geneecologymethodologymicrobiomereviewwildlife

Identifiers

PMID36910202
PMCPMC9992432

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.