Abstract

Metagenomic sequencing of clinical diagnostic specimens has a potential for unbiased detection of infectious agents, diagnosis of polymicrobial infections and discovery of emerging pathogens. Herein, next generation sequencing (NGS)-based metagenomic approach was used to investigate the cause of illness in a subset of horses recruited for a tick-borne disease surveillance study during 2017–2019. Blood samples collected from 10 horses with suspected tick-borne infection and five apparently healthy horses were subjected to metagenomic analysis. Total genomic DNA extracted from the blood samples were enriched for microbial DNA and subjected to shotgun next generation sequencing using Nextera DNA Flex library preparation kit and V2 chemistry sequencing kit on the Illumina MiSeq sequencing platform. Overall, 0.4–0.6 million reads per sample were analyzed using Kraken metagenomic sequence classification program. The taxonomic classification of the reads indicated that bacterial genomes were overrepresented (0.5 to 1%) among the total microbial reads. Most of the bacterial reads (~91%) belonged to phyla Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Cyanobacteria and Tenericutes in both groups. Importantly, 10–42.5% of Alphaproteobacterial reads in 5 of 10 animals with suspected tick-borne infection were identified as Anaplasma phagocytophilum. Of the 5 animals positive for A. phagocytophilum sequence reads, four animals tested A. phagocytophilum positive by PCR. Two animals with suspected tick-borne infection and A. phagocytophilum positive by PCR were found negative for any tick-borne microbial reads by metagenomic analysis. The present study demonstrates the usefulness of the NGS-based metagenomic analysis approach for the detection of blood-borne microbes.

Highlights

  • Tick-borne pathogens pose a growing threat to both animals and public health because ticks often harbor multiple known and unknown pathogens and geographic range of ticks is expanding in recent decades [1]

  • A subset of blood samples (n = 10) were randomly selected for metagenomic analysis from a larger cohort of horses suspected of having tick-borne diseases (TBD) recruited for studying prevalence of Anaplasma phagocytophilum and Borrelia burgdorferi infections during 2017–2019

  • 97 to 98% of the microbial reads were assigned to bacteria, virus, fungi and apicomplexan groups

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Summary

Introduction

Tick-borne pathogens pose a growing threat to both animals and public health because ticks often harbor multiple known and unknown pathogens and geographic range of ticks is expanding in recent decades [1]. Diagnosis of tick-borne diseases can be challenging due to non-specific clinical signs and transmission of multiple pathogens by ticks [7]. Use of single or multiplex PCR assays may result in missed detection of non-targeted or unknown etiologies and strategies targeting multiple pathogens have been attempted with limited success [9]. In this context, Generation Sequencing (NGS)-based metagenomic approach has a potential for the detection of diverse microbial pathogens and discovery of novel/unknown etiologies of infectious diseases [10,11,12]. Limited studies have examined the feasibility of using NGS-based metagenomic analysis for the diagnosis of tick-borne diseases in either humans or animals [13, 14]

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