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Reptile-associated Borrelia species in the goanna tick (Bothriocroton undatum) from Sydney, Australia
JL. Panetta, R. Šíma, NED. Calvani, O. Hajdušek, S. Chandra, J. Panuccio, J. Šlapeta,
Language English Country England, Great Britain
Document type Evaluation Study, Journal Article
NLK
BioMedCentral
from 2008-12-01
BioMedCentral Open Access
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Directory of Open Access Journals
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Free Medical Journals
from 2008
PubMed Central
from 2008
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ProQuest Central
from 2009-01-01
Open Access Digital Library
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Open Access Digital Library
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Medline Complete (EBSCOhost)
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- MeSH
- Borrelia classification genetics isolation & purification MeSH
- DNA, Bacterial chemistry genetics isolation & purification MeSH
- Entomology methods MeSH
- Phylogeny MeSH
- Ixodidae microbiology MeSH
- Microbiological Techniques methods MeSH
- DNA, Ribosomal chemistry genetics MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Sequence Analysis, DNA MeSH
- Sensitivity and Specificity MeSH
- Cluster Analysis MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Evaluation Study MeSH
- Geographicals
- Australia MeSH
BACKGROUND: Knowledge on the capacity of Australian ticks to carry Borrelia species is currently limited or missing. To evaluate the potential of ticks to carry bacterial pathogens and their DNA, it is imperative to have a robust workflow that maximises recovery of bacterial DNA within ticks in order to enable accurate identification. By exploiting the bilateral anatomical symmetry of ticks, we were able to directly compare two DNA extraction methods for 16S rRNA gene diversity profiling and pathogen detection. We aimed to assess which combination of DNA extraction and 16S rRNA hypervariable region enables identification of the greatest bacterial diversity, whilst minimising bias, and providing the greatest capacity for the identification of Borrelia spp. RESULTS: We collected Australian endemic ticks (Bothriocroton undatum), isolated DNA from equal tick halves using two commercial DNA extraction methods and sequenced samples using V1-V3 and V3-V4 16S rRNA gene diversity profiling assays. Two distinct Borrelia spp. operational taxonomic units (OTUs) were detected using the V1-V3 16S rRNA hypervariable region and matching Borrelia spp. sequences were obtained using a conventional nested-PCR. The tick 16S rRNA gene diversity profile was dominated by Rickettsia spp. (98-99%), while the remaining OTUs belonged to Proteobacteria (51-81%), Actinobacteria (6-30%) and Firmicutes (2-7%). Multiple comparisons tests demonstrated biases in each of the DNA extraction kits towards different bacterial taxa. CONCLUSIONS: Two distinct Borrelia species belonging to the reptile-associated Borrelia group were identified. Our results show that the method of DNA extraction can promote bias in the final microbiota identified. We determined an optimal DNA extraction method and 16S rRNA gene diversity profile assay that maximises detection of Borrelia species.
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