Handling the microbial complexity associated to ticks
2018
Cabezas-Cruz, Alejandro | Pollet, Thomas | Estrada-Peña, Agustín | Allain, Eleonore | Bonnet, Sarah I. | Moutailler, Sara | Biologie moléculaire et immunologie parasitaires et fongiques (BIPAR) ; École nationale vétérinaire d'Alfort (ENVA)-Laboratoire de santé animale, sites de Maisons-Alfort et de Normandie ; Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Universidad de Zaragoza = University of Zaragoza [Saragossa University] = Université de Saragosse
International audience
Mostrar más [+] Menos [-]Inglés. Ticks and the pathogens they transmit constitute a growing burden for human and animal health worldwide. In the last years, high-throughput detection and sequencing technologies (HTT) have revealed that individual ticks carry a high diversity of microorganisms, including pathogenic and non-pathogenic bacteria. Despite several studies have contributed to the availability of a catalog of microorganisms associated to different tick species, major limitations and challenges remain ahead HTT studies to acquire further insights on the microbial complexity associated to ticks. Currently, using next generation sequencing (NGS), bacteria genera (or higher taxonomic levels) can be recorded; however, species identification remains problematic which in turn affects pathogen detection using NGS. Microfluidic PCR, a high-throughput detection technology, can detect up to 96 different pathogen species, and its combination with NGS might render interesting insights into pathogen-microbiota co-occurrence patterns. Microfluidic PCR, however, is also limited because detection of pathogen strains has not been implemented, and therefore, putative associations among bacterial genotypes are currently unknown. Combining NGS and microfluidic PCR data may prove challenging. Here, we review the impact of some HTT applied to tick microbiology research and propose network analysis as an integrative data analysis benchmark to unravel the structure and significance of microbial communities associated to ticks in different ecosystems.
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