Assessment of a metabarcoding approach for the characterisation of vector-borne bacteria in canines from Bangkok, Thailand
Details
Publication Year 2019-08-08,Volume 12,Issue #1,Page 394
Journal Title
Parasites & Vectors
Publication Type
Journal Article
Abstract
BACKGROUND: Globally, bacterial vector-borne disease (VBD) exerts a large toll on dogs in terms of morbidity and mortality but nowhere is this more pronounced than in the tropics. Tropical environments permit a burgeoning diversity and abundance of ectoparasites some of which can transmit an extensive range of infectious agents, including bacteria, amongst others. Although some of these vector-borne bacteria are responsible for both animal and human diseases in the tropics, there is a scarcity of epidemiological investigation into these pathogens' prevalence. The situation is further exacerbated by frequent canine co-infection, complicating symptomatology that regular diagnostic techniques may miss or be unable to fully characterise. Such limitations draw attention to the need to develop screening tools capable of detecting a wide range of pathogens from a host simultaneously. RESULTS: Here, we detail the employment of a next-generation sequencing (NGS) metabarcoding methodology to screen for the spectrum of bacterial VBD that are infecting semi-domesticated dogs across temple communities in Bangkok, Thailand. Our NGS detection protocol was able to find high levels of Ehrlichia canis, Mycoplasma haemocanis and Anaplasma platys infection rates as well as less common pathogens, such as "Candidatus Mycoplasma haematoparvum", Mycoplasma turicensis and Bartonella spp. We also compared our high-throughput approach to conventional endpoint PCR methods, demonstrating an improved detection ability for some bacterial infections, such as A. platys but a reduced ability to detect Rickettsia. CONCLUSIONS: Our methodology demonstrated great strength at detecting coinfections of vector-borne bacteria and rare pathogens that are seldom screened for in canines in the tropics, highlighting its advantages over traditional diagnostics to better characterise bacterial pathogens in environments where there is a dearth of research.
Publisher
BMC
Research Division(s)
Advanced Technology And Biology
PubMed ID
31395073
Open Access at Publisher's Site
https://doi.org/10.1186/s13071-019-3651-0
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2019-08-13 12:35:12
Last Modified: 2019-08-13 01:08:58
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