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Exploiting 16S rRNA-based metagenomics to reveal neglected microorganisms associated with infertility in breeding bulls in Spanish extensive herds

Research in Veterinary Science publica este artículo de investigación

1 de diciembre de 2022

Bovine infectious infertility represents a problem due to the high impact on animal production and, in many cases, in public health. A lack of information on the characteristics of the bacterial population of the bovine reproductive system can hamper a comprehensive understanding of reproductive pathologies and the role that the microbiome could play. A metagenomic study based on the V3-V4 hypervariable region of the bacterial 16S rRNA gene was performed in 1029 preputial samples from bulls raised in an extensive regimen in Spain (944 from herds with low fertility rates -case group-, and 85 samples from reproductively healthy herds -control group-). The most representative phyla as well as the most 10 abundant bacterial families and their abundance did not show significant differences in both case and control groups. Similarly, the (alpha and beta) diversity of the bacterial populations was similar in both type of herds: the Shannon and Simpson indices show a high diversity of species, while the Bray-Curtis dissimilarity index did not show relevant differences in the bacterial communities. A deeper analysis of the operational taxonomic units showed the presence of one genera, Mycoplasma spp. significantly associated with fertility problems. Our study highlights the promising potential that the application of sequencing techniques (e.g. 16S rRNA-based metagenomics) possesses in examining bovine infertility, as they are able to reveal different pathogens that could go unnoticed using diagnostic approaches for only the main known pathogens




Polo C., Hernandez M., Garcia-Seco T., Fernandez V., Briones V., Diez-Guerrier A., Abad D., Rodriguez-Lazaro D., Dominguez L. y Perez-Sancho M..




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Exploiting 16S rRNA-based metagenomics to reveal neglected microorganisms associated with infertility in breeding bulls in Spanish extensive herds

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Exploiting 16S rRNA-based metagenomics to reveal neglected microorganisms associated with infertility in breeding bulls in Spanish extensive herds



Participantes:

Universidad ComplutenseServicio de Identificación y Caracterización Microbiana (ICM). Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

MAEVA SERVET, S.L.MAEVA SERVET, S.L..

Instituto Tecnológico Agrario de Castilla y LeónLaboratorio de Biología Molecular y Microbiología. Instituto Tecnológico Agrario de Castilla y León (ITACyL).

Zootecnia Análisis Clínicos VeterinariosZootecnia Análisis Clínicos Veterinarios.

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

Universidad de BurgosUnidad de Microbiología. Departamento de Biotecnología y Ciencia de los Alimentos. Universidad de Burgos (UBU).







Research in Veterinary Science
FACTOR YEAR Q
2.400 2022

NLMID: 401300

PMID: 35803007

ISSN: 0034-5288



TÍTULO: Exploiting 16S rRNA-based metagenomics to reveal neglected microorganisms associated with infertility in breeding bulls in Spanish extensive herds


REVISTA: Res Vet Sci


NUMERACIÓN: 150:52-57


AÑO: 2022


EDITORIAL: Elsevier


AUTORES: Polo C., Hernandez M., Garcia-Seco T., Fernandez V., Briones V., Diez-Guerrier A., Abad D., Rodriguez-Lazaro D., Dominguez L. and Perez-Sancho M..


First
Coral Polo Vaquero
3rd
María Teresa García-Seco Romero
5th
Víctor Briones Dieste
6th
Alberto Antoine Díez Guerrier
8th
Alfonso David Rodríguez Lázaro
9th
Lucas Domínguez Rodríguez
Last
Marta Pérez Sancho

DOI: https://doi.org/10.1016/j.rvsc.2022.04.019


CITA ESTA PUBLICACIÓN:

Polo C., Hernandez M., Garcia-Seco T., Fernandez V., Briones V., Diez-Guerrier A., Abad D., Rodriguez-Lazaro D., Dominguez L. y Perez-Sancho M. Exploiting 16S rRNA-based metagenomics to reveal neglected microorganisms associated with infertility in breeding bulls in Spanish extensive herds. Research in Veterinary Science. 150:52-57. 2022. (A). ISSN: 0034-5288. DOI: 10.1016/j.rvsc.2022.04.019


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