BMC Veterinary Research | 2021

Subgingival microbiota of dogs with healthy gingiva or early periodontal disease from different geographical locations

 
 
 
 
 
 

Abstract


Background Periodontal disease is the most common oral disease of dogs worldwide and results from a complex interplay between plaque bacteria, the host and environmental factors. Recent studies have enhanced our understanding of the associations between the plaque microbiota and canine periodontal disease. These studies, however, were limited in their geographical reach. Thus associations between the canine oral microbiota and geographical location were investigated by determining the composition of subgingival plaque samples from 587 dogs residing in the United Kingdom (UK), United States of America (USA), China and Thailand using 454-pyrosequencing. Results After quality filtering 6,944,757 sequence reads were obtained and clustering of these at ≥98% sequence resulted in 280 operational taxonomic units (OTUs) following exclusion of rare OTUs (present at <\u20090.05% in all four countries). The subgingival plaque from dog populations located in the UK, USA, China and Thailand had a similar composition although the abundance of certain taxa varied significantly among geographical locations. Exploration of the effect of clinical status and age revealed a marked similarity among the bacteria associated with increased age and those associated with gingivitis: Young dogs and those with no gingivitis were dominated by taxa from the phyla Bacteroidetes and Proteobacteria whereas older dogs and those with moderate gingivitis were dominated by members of the Firmicutes. The plaque microbiota of small breed dogs was found to significantly differ to medium and large breeds and was dominated by species belonging to the Firmicutes. Conclusions The bacterial associations with health, gingivitis and periodontitis were conserved across dogs from the UK, USA, China and Thailand. These bacterial signatures of periodontal health and disease have potential as biomarkers for disease detection.

Volume 17
Pages None
DOI 10.1186/s12917-020-02660-5
Language English
Journal BMC Veterinary Research

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