Published November 17, 2022 | Version v1
Dataset Open

Data for: Multi-omics analysis identifies symbionts and pathogens of blacklegged ticks (Ixodes scapularis) from a Lyme disease hotspot in southeastern Ontario, Canada

  • 1. Queen's University

Description

Ticks in the family Ixodidae are recognized as important vectors of zoonoses including Lyme disease (LD), which is caused by spirochete bacteria from the Borreliella (Borrelia) burgdorferi sensu lato (Bbsl) complex. The blacklegged tick (Ixodes scapulars) continues to expand across Canada, creating hotspots of elevated LD risk at the leading edge of its expansion range. Current efforts to understand the risk of pathogen transmission associated with I. scapularis in Canada focus primarily on targeted screens, while variation in the tick microbiome remains poorly understood. Using multi-omics consisting of 16S metabarcoding and ribosome-depleted, whole-shotgun RNA transcriptome sequencing, we examined the microbial communities associated with adult I. scapularis (N = 32), sampled from four tissue types (whole tick, salivary glands, midgut, and viscera) and three geographical locations within an LD hotspot near Kingston, Ontario. The communities consisted of both endosymbiotic and known or potentially pathogenic microbes, including RNA viruses, bacteria, and a Babesia sp. intracellular parasite. We show that β-diversity is significantly higher between individual tick salivary gland and midgut bacterial communities, compared to whole ticks; while linear discriminant analysis (LDA) effect size (LEfSe) determined that the three potentially pathogenic bacteria detected by V4 16S rDNA sequencing were also discriminatory for dissected tissues only, including a Borrelia from the Bbsl complex, Borrelia miyamotoi, and Anaplasma phagocytophilum. Importantly, we find co-infection of I. scapularis by multiple microbes, in contrast to diagnostic protocols for LD, which typically focus on infection from a single pathogen of interest (B. burgdorferi sensu stricto).

Notes

All code is based on the dada2 pipeline in R, which uses text-based files. 

Funding provided by: Government of Canada
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000023
Award Number:

Funding provided by: Queen's University
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100003321
Award Number:

Funding provided by: Ontario Government
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100013873
Award Number:

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Additional details

Related works

Is derived from
10.5281/zenodo.7199733 (DOI)
Is source of
10.5281/zenodo.7199737 (DOI)