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Infection with diverse immune-modulating poxviruses elicits different compositional shifts in the mouse gut microbiome

It is often not possible to demonstrate causality within the context of gut microbiota dysbiosis-linked diseases. Thus, we need a better understanding of the mechanisms whereby an altered host immunophysiology shapes its resident microbiota. In this regard, immune-modulating poxvirus strains and mut...

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Detalles Bibliográficos
Autores principales: Aguirre de Cárcer, Daniel, Hernáez, Bruno, Rastrojo, Alberto, Alcamí, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5345840/
https://www.ncbi.nlm.nih.gov/pubmed/28282449
http://dx.doi.org/10.1371/journal.pone.0173697
Descripción
Sumario:It is often not possible to demonstrate causality within the context of gut microbiota dysbiosis-linked diseases. Thus, we need a better understanding of the mechanisms whereby an altered host immunophysiology shapes its resident microbiota. In this regard, immune-modulating poxvirus strains and mutants could differentially alter gut mucosal immunity in the context of a natural immune response, providing a controlled natural in vivo setting to deepen our understanding of the immune determinants of microbiome composition. This study represents a proof-of-concept that the use of an existing collection of different immune-modulating poxviruses may represent an innovative tool in gut microbiome research. To this end, 16S rRNA amplicon sequencing and RNAseq transcriptome profiling were employed as proxies for microbiota composition and gut immunophysiological status in the analysis of caecal samples from control mice and mice infected with various poxvirus types. Our results show that different poxvirus species and mutants elicit different shifts in the mice mucosa-associated microbiota and, in some instances, significant concomitant shifts in gut transcriptome profiles, thus providing an initial validation to the proposed model.