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Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions

Bovine digital dermatitis (DD) is a significant cause of infectious lameness and economic losses in cattle production across the world. There is a lack of a consensus across different 16S metagenomic studies on DD-associated bacteria that may be potential pathogens of the disease. The goal of this m...

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Autores principales: Caddey, Ben, De Buck, Jeroen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322762/
https://www.ncbi.nlm.nih.gov/pubmed/34336713
http://dx.doi.org/10.3389/fcimb.2021.685861
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author Caddey, Ben
De Buck, Jeroen
author_facet Caddey, Ben
De Buck, Jeroen
author_sort Caddey, Ben
collection PubMed
description Bovine digital dermatitis (DD) is a significant cause of infectious lameness and economic losses in cattle production across the world. There is a lack of a consensus across different 16S metagenomic studies on DD-associated bacteria that may be potential pathogens of the disease. The goal of this meta-analysis was to identify a consistent group of DD-associated bacteria in individual DD lesions across studies, regardless of experimental design choices including sample collection and preparation, hypervariable region sequenced, and sequencing platform. A total of 6 studies were included in this meta-analysis. Raw sequences and metadata were identified on the NCBI sequence read archive and European nucleotide archive. Bacterial community structures were investigated between normal skin and DD skin samples. Random forest models were generated to classify DD status based on microbial composition, and to identify taxa that best differentiate DD status. Among all samples, members of Treponema, Mycoplasma, Porphyromonas, and Fusobacterium were consistently identified in the majority of DD lesions, and were the best genera at differentiating DD lesions from normal skin. Individual study and 16S hypervariable region sequenced had significant influence on final DD lesion microbial composition (P < 0.05). These findings indicate that members of Treponema, Mycoplasma, Porphyromonas, and/or Fusobacterium may have significant roles in DD pathogenesis, and should be studied further in respect to elucidating DD etiopathogenic mechanisms and developing more effective treatment and mitigation strategies.
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spelling pubmed-83227622021-07-31 Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions Caddey, Ben De Buck, Jeroen Front Cell Infect Microbiol Cellular and Infection Microbiology Bovine digital dermatitis (DD) is a significant cause of infectious lameness and economic losses in cattle production across the world. There is a lack of a consensus across different 16S metagenomic studies on DD-associated bacteria that may be potential pathogens of the disease. The goal of this meta-analysis was to identify a consistent group of DD-associated bacteria in individual DD lesions across studies, regardless of experimental design choices including sample collection and preparation, hypervariable region sequenced, and sequencing platform. A total of 6 studies were included in this meta-analysis. Raw sequences and metadata were identified on the NCBI sequence read archive and European nucleotide archive. Bacterial community structures were investigated between normal skin and DD skin samples. Random forest models were generated to classify DD status based on microbial composition, and to identify taxa that best differentiate DD status. Among all samples, members of Treponema, Mycoplasma, Porphyromonas, and Fusobacterium were consistently identified in the majority of DD lesions, and were the best genera at differentiating DD lesions from normal skin. Individual study and 16S hypervariable region sequenced had significant influence on final DD lesion microbial composition (P < 0.05). These findings indicate that members of Treponema, Mycoplasma, Porphyromonas, and/or Fusobacterium may have significant roles in DD pathogenesis, and should be studied further in respect to elucidating DD etiopathogenic mechanisms and developing more effective treatment and mitigation strategies. Frontiers Media S.A. 2021-07-16 /pmc/articles/PMC8322762/ /pubmed/34336713 http://dx.doi.org/10.3389/fcimb.2021.685861 Text en Copyright © 2021 Caddey and De Buck https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cellular and Infection Microbiology
Caddey, Ben
De Buck, Jeroen
Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title_full Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title_fullStr Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title_full_unstemmed Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title_short Meta-Analysis of Bovine Digital Dermatitis Microbiota Reveals Distinct Microbial Community Structures Associated With Lesions
title_sort meta-analysis of bovine digital dermatitis microbiota reveals distinct microbial community structures associated with lesions
topic Cellular and Infection Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322762/
https://www.ncbi.nlm.nih.gov/pubmed/34336713
http://dx.doi.org/10.3389/fcimb.2021.685861
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