Data analysis workflow for the detection of canine vector-borne pathogens using 16 S rRNA Next-Generation Sequencing

Background: Vector-borne diseases (VBDs) impact both human and veterinary medicine and pose special public health challenges. The main bacterial vector-borne pathogens (VBPs) of importance in veterinary medicine include Anaplasma spp., Bartonella spp., Ehrlichia spp., and Spotted Fever Group Rickettsia. Taxon-targeted PCR assays are the current gold standard for VBP diagnostics but limitations on the detection of genetically diverse organisms support a novel approach for broader detection of VBPs. We present a methodology for genetic characterization of VBPs using Next-Generation Sequencing (NGS) and computational approaches. A major advantage of NGS is the ability to detect multiple organisms present in the same clinical sample in an unsupervised (i.e. non-targeted) and semi-quantitative way. The Standard Operating Procedure (SOP) presented here combines industry-standard microbiome analysis tools with our ad-hoc bioinformatic scripts to form a complete analysis pipeline accessible to veterinary scientists and freely available for download and use at https://github.com/eltonjrv/microbiome.westernu/ tree/SOP. Results: We tested and validated our SOP by mimicking single, double, and triple infections in genomic canine DNA using serial dilutions of plasmids containing the entire 16 S rRNA gene sequence of (A) phagocytophilum, (B) v. berkhoffii, and E. canis. NGS with broad-range 16 S rRNA primers followed by our bioinformatics SOP was capable of detecting these pathogens in biological replicates of different dilutions. These results illustrate the ability of NGS to detect and genetically characterize multi-infections with different amounts of pathogens in a single sample. Conclusions: Bloodborne microbiomics & metagenomics approaches may help expand the molecular diagnostic toolbox in veterinary and human medicine. In this paper, we present both in vitro and in silico detailed protocols that can be combined into a single workflow that may provide a significant improvement in VBP diagnostics and also facilitate future applications of microbiome research in veterinary medicine.

Automated summary

The study introduces a method for genetic characterization of VBPs using NGS and computational approaches, showing its effectiveness in detecting multiple pathogens in a single sample. This approach has the potential to expand the molecular diagnostic toolbox in veterinary and human medicine and provide significant improvements in VBP diagnostics.