Evidence map›Paper›PMID 32591382›Full record

ArticleApplied and environmental microbiology2020

Validating the Use of Bovine Buccal Sampling as a Proxy for the Rumen Microbiota by Using a Time Course and Random Forest Classification Approach.

Juliana Young, Joseph H Skarlupka, Madison S Cox, Rafael Tassinari Resende, Amelie Fischer, Kenneth F Kalscheur, Jennifer C McClure, John B Cole, Garret Suen, Derek M Bickhart

Open access · greenAbstract readValidation Study
In one paragraph

Article in Applied and environmental microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 37 citations in OpenAlex.

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  9. Gut Microbiota of Ruminants and Monogastric Livestock: An Overview.Animals : an open access journal from MDPI · 2025
    Review
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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 at 4 institutions in 3 countries.

Juliana YoungUS Dairy Forage Research Center, USDA-Agricultural Research Service, Madison, Wisconsin, USA.
Joseph H SkarlupkaDepartment of Bacteriology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0002-0946-5061
Madison S CoxDepartment of Bacteriology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0001-7092-2754
Rafael Tassinari ResendeSchool of Agronomy, Universidade Federal de Goiás (UFG), Goiânia, Goiás, Brazil.
Amelie FischerInstitut de l'élevage, Beaucouse, France.
Kenneth F KalscheurUS Dairy Forage Research Center, USDA-Agricultural Research Service, Madison, Wisconsin, USA.ORCID 0000-0002-5290-3602
Jennifer C McClureUS Dairy Forage Research Center, USDA-Agricultural Research Service, Madison, Wisconsin, USA.
John B ColeAnimal Genomics and Improvement Laboratory, USDA-Agricultural Research Service, Beltsville, Maryland, USA.ORCID 0000-0003-1242-4401
Garret SuenDepartment of Bacteriology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0002-6170-711X
Derek M BickhartUS Dairy Forage Research Center, USDA-Agricultural Research Service, Madison, Wisconsin, USA derek.bickhart@usda.gov.ORCID 0000-0003-2223-9285
Agricultural Research Service · USUniversity of Wisconsin–Madison · USInstitut de l’Elevage · FRUniversidade Federal de Goiás · BR

Funding

GRADUATE TRAINING IN MOLECULAR BIOSCIENCEST32GM007215 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI HULL, CHRISTINA M · 1985 to 2018
$22.5M
NIGMS NIH HHS T32 GM007215
6 · The paper itself

Abstract

Analysis of the cow microbiome, as well as host genetic influences on the establishment and colonization of the rumen microbiota, is critical for development of strategies to manipulate ruminal function toward more efficient and environmentally friendly milk production. To this end, the development and validation of noninvasive methods to sample the rumen microbiota at a large scale are required. In this study, we further optimized the analysis of buccal swab samples as a proxy for direct bacterial samples of the rumen of dairy cows. To identify an optimal time for sampling, we collected buccal swab and rumen samples at six different time points relative to animal feeding. We then evaluated several biases in these samples using a machine learning classifier (random forest) to select taxa that discriminate between buccal swab and rumen samples. Differences in the inverse Simpson's diversity, Shannon's evenness, and Bray-Curtis dissimilarities between methods were significantly less apparent when sampling was performed prior to morning feeding (

Indexed as

Gastrointestinal MicrobiomeAnimalsCattleCheekMicrobiological TechniquesRumenSampling Studiesbacteriabuccal swabmachine learningoral communityrandom forestrumen microbiota

Identifiers

PMID32591382
PMCPMC7440797
OpenAlexW3037088128

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.