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Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
A microbiome analysis of equine peripheral dental caries using next generation sequencing
D Borkent1, R J M Reardon1, G McLACHLAN1
1Division of Veterinary Clinical Studies, Royal (Dick) School of Veterinary Studies and Roslin Institute, The University of Edinburgh, Midlothian, UK.
This study identified key bacteria in equine peripheral caries (PC), finding Streptococcus species linked to affected teeth. Molecular methods revealed distinct microbial communities in rostral versus caudal cheek teeth, offering insights into equine dental health.
Area of Science:
- Veterinary Microbiology
- Equine Dentistry
- Oral Microbiome Analysis
Background:
- Peripheral caries (PC) is prevalent in horses, yet its microbiology remains understudied.
- Conventional culturing methods fail to capture the full spectrum of oral bacteria.
- Next-Generation Sequencing (NGS) is crucial for understanding complex oral microbiomes.
Purpose of the Study:
- To identify the specific microbiota associated with equine peripheral caries (PC).
- To compare the microbial communities between affected caudal cheek teeth and less affected rostral cheek teeth.
- To establish a baseline for future research into equine oral health.
Main Methods:
- Collected equine dental plaque samples from 63 horses.
- Utilized Polymerase Chain Reaction (PCR) and 16S rRNA gene sequencing (V4 region).
- Analyzed sequencing data using Mothur and R for microbial identification.
Main Results:
- Streptococcus species were most frequently associated with equine PC.
- Gemella species were predominant in the control group.
- Veillonella species were linked to rostral PC, Streptococcus to caudal PC, and Corynebacterium to controls.
Conclusions:
- Acidogenic and acid-resistant bacteria, notably Streptococcus species, are implicated in equine PC.
- Microbial composition varies between rostral and caudal cheek teeth in horses with PC.
- Further research is needed to address potential biases in 16S rRNA gene copy number variations.
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