Multi-omics analysis identifies symbionts and pathogens of blacklegged ticks ( <i>Ixodes scapularis</i> ) from a Lyme disease hotspot in southeastern Ontario, Canada
Bibliographic record
Abstract
Abstract Ticks in the family Ixodidae are 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 scapularis ) 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 a LD hotspot near Kingston, Ontario, Canada. 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 also differed among 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). IMPORTANCE A vector of human health concern, blacklegged ticks, Ixodes scapularis , transmit pathogens that cause tick-borne diseases (TBDs), including Lyme disease (LD). Several hotspots of elevated LD risk have emerged across Canada as I. scapularis expands its range. Focusing on a hotspot in southeastern Ontario, we used high-throughput sequencing on whole ticks and dissected salivary glands and midguts. Compared to whole ticks, analysis of salivary glands and midguts revealed greater β-diversity among microbiomes that are less dominated by Rickettsia endosymbiont bacteria and enriched for pathogenic bacteria including a Bbsl- associated Borrelia , Borrelia miyamotoi , and Anaplasma phagocytophilum . We also find evidence of co-infection of I. scapularis in this region by multiple microbes. Overall, our study highlights the challenges and opportunities associated with the surveillance of the microbiome of I. scapularis for pathogen detection using metabarcoding and metatranscriptome approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".