Evidence map›Paper›PMID 32276591›Full record

ArticleBMC microbiology2020

Assessment of the lung microbiota in dogs: influence of the type of breed, living conditions and canine idiopathic pulmonary fibrosis.

Aline Fastrès, Elodie Roels, Emilie Vangrinsven, Bernard Taminiau, Hiba Jabri, Géraldine Bolen, Anne-Christine Merveille, Alexandru-Cosmin Tutunaru, Evelyne Moyse, Georges Daube and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 18 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

11 authors at 1 institution in 1 country.

Aline FastrèsDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium. afastres@uliege.be.
Elodie RoelsDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Emilie VangrinsvenDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Bernard TaminiauDepartment of Food Sciences - Microbiology, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Hiba JabriDepartment of Food Sciences - Microbiology, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Géraldine BolenDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Anne-Christine MerveilleDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Alexandru-Cosmin TutunaruDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Evelyne MoyseDepartment of Veterinary Management of Animal Resources/Biostatistics and Bioinformatics Applied to Veterinary Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Georges DaubeDepartment of Food Sciences - Microbiology, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
Cécile ClercxDepartment of Clinical Sciences, FARAH, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
University of Liège · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLiterature about the lung microbiota (LM) in dogs is sparse. Influence of breed and living conditions on the LM in healthy dogs is currently unknown, as well as the influence of chronic respiratory diseases such as canine idiopathic pulmonary fibrosis (CIPF) in West highland white terriers (WHWTs). Aims of this study were (1) to assess the characteristics of the healthy LM according to breed and living conditions, and (2) to study LM changes associated with CIPF in WHWTs. Forty-five healthy dogs divided into 5 groups: domestic terriers (n = 10), domestic shepherds (n = 11), domestic brachycephalic dogs (n = 9), domestic WHWTs (n = 6) (H-WHWTs) and experimental beagles (n = 9) and 11 diseased WHWTs affected with CIPF (D-WHWTs) were included in the study to achieve those objectives.

resultsIn healthy domestic dogs, except in H-WHWTs, the presence of few discriminant genera in each type of breed was the only LM modification. LM of experimental dogs displayed a change in b-diversity and an increased richness compared with domestic dogs. Moreover, Prevotella_7 and Dubosiella genera were more abundant and 19 genera were discriminant in experimental dogs. LM of both H-WHWTs and D-WHWTs revealed increased abundance of 6 genera (Brochothrix, Curvibacter, Pseudarcicella, Flavobacteriaceae genus, Rhodoluna and Limnohabitans) compared with other healthy domestic dogs. Brochothrix and Pseudarcicella were also discriminant in D-WHWTs compared with H-WHWTs and other healthy domestic dogs.

conclusionsIn domestic conditions, except for H-WHWT, the breed appears to have minor influence on the LM. LM modifications were found in experimental compared with domestic living conditions. LM modifications in H-WHWTs and D-WHWTs compared with other healthy domestic dogs were similar and seemed to be linked to the breed. Whether this breed difference might be related with the high susceptibility of WHWTs for CIPF requires further studies.

Indexed as

AnimalsBacteriaBreedingDNA, BacterialDNA, RibosomalDog DiseasesDogsFemaleIdiopathic Pulmonary FibrosisLungMalePhylogenyReal-Time Polymerase Chain ReactionRNA, Ribosomal, 16SDNA, BacterialDNA, RibosomalRNA, Ribosomal, 16SBreedCIPFDogsEnvironmentLungMicrobiota

Identifiers

PMID32276591
PMCPMC7147050
OpenAlexW3015432644

What OpenQuestion holds

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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.