Abstract
Ticks transmit a variety of viral, bacterial and protozoal pathogens, which are often zoonotic. The aim of this study was to identify diverse tick microbiomes, which may contain as-yet unidentified pathogens, using a metagenomic approach. DNA prepared from bacteria/archaea-enriched fractions obtained from seven tick species, namely Amblyomma testudinarium, Amblyomma variegatum, Haemaphysalis formosensis, Haemaphysalis longicornis, Ixodes ovatus, Ixodes persulcatus and Ixodes ricinus, was subjected to pyrosequencing after whole-genome amplification. The resulting sequence reads were phylotyped using a Batch Learning Self-Organizing Map (BLSOM) program, which allowed phylogenetic estimation based on similarity of oligonucleotide frequencies, and functional annotation by BLASTX similarity searches. In addition to bacteria previously associated with human/animal diseases, such as Anaplasma, Bartonella, Borrelia, Ehrlichia, Francisella and Rickettsia, BLSOM analysis detected microorganisms belonging to the phylum Chlamydiae in some tick species. This was confirmed by pan-Chlamydia PCR and sequencing analysis. Gene sequences associated with bacterial pathogenesis were also identified, some of which were suspected to originate from horizontal gene transfer. These efforts to construct a database of tick microbes may lead to the ability to predict emerging tick-borne diseases. Furthermore, a comprehensive understanding of tick microbiomes will be useful for understanding tick biology, including vector competency and interactions with pathogens and symbionts.
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Acknowledgements
We thank everyone who helped with tick collection, especially Nariaki Nonaka, Jacqueline Schipper, Joseph W. Magona, Joseph M. Kamau, Noboru Sasaki and Noriko Nakao. The first author was supported by a research grant fellowship from the Japanese Society for the Promotion of Science (JSPS) for young scientists. This work was supported by a Grant-in-Aid for JSPS fellows and for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT), the program of Funding Research Center for Emerging and Re-emerging Infectious Disease, MEXT. The BLSOM calculation was done, in part, by the Earth Simulator of the Japan Agency for Marine-Earth Science and Technology.
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Nakao, R., Abe, T., Nijhof, A. et al. A novel approach, based on BLSOMs (Batch Learning Self-Organizing Maps), to the microbiome analysis of ticks. ISME J 7, 1003–1015 (2013). https://doi.org/10.1038/ismej.2012.171
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DOI: https://doi.org/10.1038/ismej.2012.171
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